The West Bank and Gaza has the highest population growth in the world.1 Years of high fertility rates have created a very young population structure, with roughly half of the population below the age of 15. Over the medium term, the demographics are projected to change in a way that will have profound economic implications. The fertility rate is projected to decline, causing a deceleration in the population growth rate and a rise in the average age of the population so that by 2025, the share of the population older than 15 will have increased to 64 percent from about 53 percent today. As a consequence, the labor force is projected to expand by 4–4 percent a year over the next ten years and at a modestly lower rate thereafter. The numbers would obviously be higher if the West Bank and Gaza were to experience immigration, a possibility after a final peace agreement with Israel.
The relationship between growth in the population and in the labor force on the one hand and per capita economic growth on the other is complex, and arguments have been made in favor of pessimistic, optimistic, and neutralist views.2 Empirical studies have typically found population growth to be negatively associated with long-term growth in per capita income once the age structure of the population is controlled for, and that an expansion in the population at working age relative to the population at large can bolster per capita income growth, albeit temporarily.3 This is also what the empirical part of this chapter finds. A good example is East Asia, which in 1965–90 experienced a rise in the share of the working-age population similar to the one the West Bank and Gaza is expected to go through over the coming 25 years, and the demographic (or age) transition in Asia is estimated to have contributed between 1.5 to 1.9 percentage points to annual per capita income growth over the 1965–90 period, explaining roughly half of the “miracle” in that region (Bloom and Williamson, 1998).
An increase in the share of working-age segment of the population can raise per capita income growth through several channels.4 It can contribute to higher private savings as predicted by the life-cycle model of savings, which in turn can allow an increase in investment to the extent that the private sector lacks access to foreign capital. Investment can be expected to surge in order to equip the new workers with capital, while housing investment could be expected to increase. The infusion of young and newly trained workers (an update of the human capital stock) can also help increase productivity and technological change. Finally, an increase in the labor force relative to the population can have important effects on public finances (additional taxpayers) and the composition of public expenditure.
There is nothing automatic about the demographic transition having a positive impact on growth, however, and it is not too difficult to envision a scenario under which the rapid expansion of the Palestinian labor force would lead to higher unemployment or a severe compression in real wages, or both. Standard economic theory would predict that an expansion in the labor supply due to population growth would negatively affect real wages or employment opportunities, or both, unless there are technological improvements that increase productivity.5 This has also been the general experience in the industrial countries that experienced a baby boom after World War II. When the baby boom cohort reached working age in these countries, it was generally absorbed into the workforce in the United States, but its relative wages declined, whereas in Europe, this group generally experienced higher unemployment than other age groups (Bloom, Freeman, Korenman, 1987). The experience in developing countries has been different, however, and expansions of labor supply have typically been accompanied by a structural shift away from low productivity agriculture to higher productivity industry and services, at the same time as the productivity within these sectors has increased. Thus, according to Bloom, Freeman, and Korenman (1987) developing countries have in general been able to absorb swelling labor supplies into higher productivity employment, at higher wages, fueling an increase in income per capita. The policy challenge for the Palestinian Authority (PA) is to create conditions to help ensure that the demographic transition will provide a boost rather than a drag on the Palestinian economy. This point is the focus of this chapter.
The purpose of this chapter is to analyze the challenge that confronts the Palestinian labor market and the economy more generally stemming from the projected changes in age composition and labor force participation, and the need to reduce unemployment; to compute the growth rates in real GDP, investment, and productivity required in order to reduce unemployment, while at the same time allowing real wages to rise; and to identify the key factors that can help the Palestinian economy achieve these growth rates. Figure 2.1 shows a stylized schema over the growth process in which the proximate factors for economic growth—changes in labor and capital inputs and productivity—are determined by what can be called the ultimate factors. This chapter follows (loosely) this schema.
A Stylized Schema Over the Long-Term Growth Process
A final word of caution. Although a considerable effort has been made to put together a solid database on the Palestinian economy, data weaknesses are a problem, especially the national income accounts where data are derived from the Israeli Central Bureau of Statistics (ICBS) for the period 1970–92 and for 1993 onward from IMF staff estimates based on data from the Palestinian Central Bureau of Statistics (PCBS). The PCBS is in the process of establishing a consistent time series of national accounts data for the period 1994–99, including, for the first time, data in real terms which were not available at the time this chapter was written.
Accounting for Growth, 1970–99
In order to gain insights to the sources of growth in the Palestinian economy, this section analyzes the Palestinian record of growth in four economic-indicators—output, investment, employment, and total factor productivity (TFP)—over the past 30 years using a growth accounting framework. Growth accounting, a simple analytical exercise that has been used for almost 40 years, abstracts from factors that influence annual changes in growth and focuses instead on medium- to long-run growth.6 (Appendix I explains the methodology and data sources for this exercise.) Output can grow either by increasing inputs, increasing productivity of each input, or both. The growth accounting exercise decomposes output growth into contributions from changes in the factors of production (capital and labor) and a residual component, known as TFP growth. The central message of the growth accounting framework is that a substantial and lasting increase in living standards requires a sustained growth in TFP.7
The Growth Record
Over the last thirty years, Palestinian real GDP growth averaged 6 percent per year but with considerable variability.8 In the 1970s, real output grew at an annual rate of 8 percent. The growth rate declined to 3.1 percent in the 1980s and then accelerated again to 6.8 percent in the 1990s (Table 2.1 and Figure 2.2). Growth was particularly high in 1970–73, a period of almost complete openness between the Palestinian economy and its integration into the richer and more developed Israeli economy.9 This integration included removal of trade barriers, employment of Palestinian workers in Israel, and the transfer of technology and expertise to the Palestinian agricultural sector, a dominant sector in the 1970s.10 The decline in output growth in the 1980s has been attributed in part to the lagged impact of the oil price shock of 1979, which adversely affected both Israel and the West Bank and Gaza, the negative effects from the hyperinflation that lasted into the mid-1980s, a slowdown in the process of technological transfer, and tailing prices of agricultural products.11 In 1990–93, output growth was high, spurred by taster employment growth, particularly in the construction sector, but output fell in 1995–96 because of the disruptions in economic activity caused by a deterioration in the security situation and the extensive closures imposed by Israel. The Palestinian economy experienced a strong recovery in 1998–99 and was expected to record positive per capita income growth also in 2000 before the turmoil that began in September (see Chapter 1).
Sources of Output Growth: 1970–99 and Subperiods
(Annual percent)
The assumptions are: depreciation rate of 4 percent and initial capital-output ratio of 2.5.
The intifada period is 1988–93.
Sources of Output Growth: 1970–99 and Subperiods
(Annual percent)
Contribution of: 1 | ||||
---|---|---|---|---|
Period | Growth of Output |
Capital Stock | Employment | Total Factor Productivity |
Capital share of income = 0.35 | ||||
1970–99 | 6.0 | 2.5 | 2.1 | 1.4 |
1973–94 | 5.8 | 2.7 | 1.5 | 1.6 |
Growth before, during, and after intifada2 | ||||
1970–87 | 6.1 | 2.8 | 0.6 | 2.8 |
1988–93 | 8.1 | 1.8 | 3.4 | 2.9 |
1994–99 | 3.3 | 2.5 | 5.2 | -4.4 |
Growth by decade | ||||
1970–79 | 8.0 | 3.0 | -0.2 | 5.2 |
1980–89 | 3.1 | 2.3 | 1.5 | -0.7 |
1990–99 | 6.8 | 2.3 | 5.0 | 0.4 |
Post–1973 growth slow down | ||||
1970–73 | 8.8 | 2.0 | -1.2 | 8.0 |
1973–99 | 5.2 | 2.6 | 2.4 | 0.1 |
Capital share of income = 0.58 | ||||
1970–99 | 6.0 | 4.2 | 1.3 | 0.4 |
1973–94 | 5.8 | 4.5 | 1.0 | 0.3 |
Growth before, during, and after intifada2 | ||||
1970–87 | 6.1 | 4.6 | 0.4 | 1.2 |
1988–93 | 8.1 | 3.0 | 2.2 | 2.9 |
1994–99 | 3.3 | 4.1 | 3.4 | -4.2 |
Growth by decade | ||||
1970–79 | 8.0 | 4.9 | -0.1 | 3.2 |
1980–89 | 3.1 | 3.9 | 1.0 | -1.7 |
1990–99 | 6.8 | 3.8 | 3.2 | -0.2 |
Post-1973 growth slowdown | ||||
1970–73 | 8.8 | 3.3 | -0.7 | 6.3 |
1973–99 | 5.2 | 4.3 | 1.6 | -0.7 |
The assumptions are: depreciation rate of 4 percent and initial capital-output ratio of 2.5.
The intifada period is 1988–93.
Sources of Output Growth: 1970–99 and Subperiods
(Annual percent)
Contribution of: 1 | ||||
---|---|---|---|---|
Period | Growth of Output |
Capital Stock | Employment | Total Factor Productivity |
Capital share of income = 0.35 | ||||
1970–99 | 6.0 | 2.5 | 2.1 | 1.4 |
1973–94 | 5.8 | 2.7 | 1.5 | 1.6 |
Growth before, during, and after intifada2 | ||||
1970–87 | 6.1 | 2.8 | 0.6 | 2.8 |
1988–93 | 8.1 | 1.8 | 3.4 | 2.9 |
1994–99 | 3.3 | 2.5 | 5.2 | -4.4 |
Growth by decade | ||||
1970–79 | 8.0 | 3.0 | -0.2 | 5.2 |
1980–89 | 3.1 | 2.3 | 1.5 | -0.7 |
1990–99 | 6.8 | 2.3 | 5.0 | 0.4 |
Post–1973 growth slow down | ||||
1970–73 | 8.8 | 2.0 | -1.2 | 8.0 |
1973–99 | 5.2 | 2.6 | 2.4 | 0.1 |
Capital share of income = 0.58 | ||||
1970–99 | 6.0 | 4.2 | 1.3 | 0.4 |
1973–94 | 5.8 | 4.5 | 1.0 | 0.3 |
Growth before, during, and after intifada2 | ||||
1970–87 | 6.1 | 4.6 | 0.4 | 1.2 |
1988–93 | 8.1 | 3.0 | 2.2 | 2.9 |
1994–99 | 3.3 | 4.1 | 3.4 | -4.2 |
Growth by decade | ||||
1970–79 | 8.0 | 4.9 | -0.1 | 3.2 |
1980–89 | 3.1 | 3.9 | 1.0 | -1.7 |
1990–99 | 6.8 | 3.8 | 3.2 | -0.2 |
Post-1973 growth slowdown | ||||
1970–73 | 8.8 | 3.3 | -0.7 | 6.3 |
1973–99 | 5.2 | 4.3 | 1.6 | -0.7 |
The assumptions are: depreciation rate of 4 percent and initial capital-output ratio of 2.5.
The intifada period is 1988–93.
Growth and the Composition of Growth, 1970–99
Source: ICBS (1996), World Bank (1993), and IMF staff estimates.1TFP=Total Factor Productivity.The growth pattern over the last thirty years reflects a complex set of factors, including the presence of external shocks, changes in the degree of economic integration of the Palestinian economy with that of Israel, and the presence of closures and political turmoil.
As indicated, political instability has contributed to the uneven growth performance. Rather surprisingly, however, real GDP growth accelerated during the intifada (1988–93) and decelerated afterwards. The higher output growth during the intifada was driven by rapid growth in domestic employment as the rising level of political tensions forced Palestinians working in Israel to seek employment in the West Bank and Gaza instead (see below). While GDP growth accelerated, growth in gross national income (GNI) decelerated on account of the loss of labor income from Israel.12 The acceleration in GDP growth during the intifada stands in sharp contrast to the experience in 1995–96 and in late 2000 when GDP and domestic employment fell. One reason for this difference is that during the intifada, although Palestinian workers lost their employment in Israel, the Palestinian economy was not subject to border closures and disruptions to exports and imports as in 1995–96 and in late 2000.
The Investment Record
Capital accumulation has been a key factor in the Palestinian economic growth process. The capital stock expanded at an annual average rate of 7.2 percent over the last 30 years, contributing roughly 2.5 percentage points to the 6 percent real GDP growth rate (see Table 2.1).13 Growth in the capital stock has been uneven, similar to output growth. Capital accumulation decelerated during the intifada but accelerated thereafter following the signing of the Oslo accords and the subsequent surge in donor-financed investment. Investment rose from 27 percent of GDP during the intifada to about 33 percent of GDP (in real terms) in 1994–99. Growth in aggregate investment, however, masks changes in its composition. Investment prior to 1994 was predominantly in the construction sector, a reflection of housing demand stemming from the high population growth. Construction activity has continued to dominate investment activity also after 1994 (including with large-scale hotel construction), but in addition, donor-financed investment has included investment in infrastructure and large rehabilitation projects—investments that should help raise the long-run productive capacity of the Palestinian economy. There is no evidence, however, of significant growth in private investment outside of construction after 1994, and despite the surge in investment, output growth slowed (because of the closures in 1995–96) resulting in a decline in the productivity of capital.
The Employment Record
In 1970–99, employment expanded at the same rate as the population—about 3 percent a year—but slightly below the growth in the labor force.14 Employment growth reflected primarily growth in the working-age population and, to a lesser extent, an increase in the labor force participation rate and a reduction in unemployment.15 Political events probably influenced short-term fluctuations in employment more than output and investment, and employment was more volatile than investment in 1970–99 and its subperiods and also more volatile than real output after 1994. During the period of integration (1970–73), Palestinian employment in Israel increased sharply, while domestic employment contracted at a rate of 1.8 percent per year. During the intifada, employment of Palestinians in Israel contracted at a rate of 4.4 percent per year but recovered after that.16 In contrast to earlier periods, changes in domestic employment since 1994 have mirrored changes in Palestinian employment in Israel and the settlements. Moreover, labor productivity has fallen since 1994 by almost 4.8 percent a year, as employment growth outpaced growth in output.17
Total Factor Productivity
Growth in TFP reflects technical progress, changes in the efficiency with which factors of production are used, and other factors, and TFP is derived as the residual from a decomposition of output growth into contributions from changes in the factors of production capital and labor. Using a Cobb-Douglas production function
where real output (Yt) is a function of the physical capital stock (Kt), labor (Lt), and technology (At), and α is the elasticity of output with respect to the capital stock. The following expression can be derived for TFP:
where yt, at, kt, and lt represent growth in output, TFP, capital stock, and labor, respectively.
In growth accounting, the estimate of α is crucial, and it is usually obtained from national income accounts, other growth studies, or regression analysis. We compute TFP for the West Bank and Gaza using two estimates of α. One estimate (0.35) is obtained by simply relying on other studies of growth accounting.18 The second estimate (0.58) is constructed using national income accounts data from the PCBS. Table 2.1 reports TFP growth rates based on both estimates of the capital share of national income. The analysis in the text focuses on the estimates based on the low (0.35) value for α because it seems more reliable (see Appendix I) than the high value and because it facilitates comparison of the West Bank and Gaza with other economies.19 The results show that TFP growth was 1.4 percent per year on average in 1970–99, so not all growth in real GDP over the last thirty years can be attributed to increases in employment and the capital stock. At 1.4 percent, however, TFP growth accounts for less than a quarter of the 6 percent annual growth in output. The main source of output growth over the last thirty years has been factor accumulation, in particular capital accumulation (see Table 2.1).20
The pattern of TFP growth has been uneven, reflecting the uneven growth patterns of factor inputs and output described earlier, and the averages are therefore quite sensitive to the time period chosen, as is clear from Table 2.1. TFP grew slightly less than 3 percent a year before and during the intifada but has fallen by 4.4 percent per annum since 1994. The fact that growth in TFP was sustained for 24 of the last 30 years is, however, an indication of the rather remarkable resiliency of the Palestinian economy, and it translated into a sustained increase in the standard of living as real per capita GDP grew at an annual average of 3 percent.
The importance of TFP in output growth has also varied over the years. It accounted for 46 percent of output growth during 1970–87, but its share fell to 36 percent in 1988–93 (the intifada) when factor accumulation (especially employment) became a more important source of growth. The importance of TFP in 1970–87 was also primarily due to the high TFP growth in 1970–73, a period marked by the integration of the Palestinian economy into that of Israel, the transfer of technology, and high labor mobility. During this period, TFP grew at an annual rate of 8 percent—the highest TFP growth registered over the last thirty years, accounting for almost 91 percent of output growth in that period. TFP growth slowed sharply after 1973 much like the recorded productivity slowdown in the OECD countries and Israel, and it was negative in the 1980s in the West Bank and Gaza. Furthermore, in contrast to the earlier periods, the negative TFP growth since 1994 has been accompanied by faster accumulation of capital and labor and lower output growth.21 This was due to a combination of factors, including the infusion of donor-financed investment (which may help raise TFP growth in the future), heavy focus on residential construction in private investment, the return of some Palestinians to the labor market following the Oslo accords, and the adverse impact of closures on output in 1995 and 1996. The decline in TFP might also reflect an underestimation of output growth.
How Does This Performance Compare with the Rest of the World?
To answer this question, a growth accounting exercise is undertaken for 88 countries and the West Bank and Gaza, using an identical set of assumptions and a common time period. The international data are taken from Collins and Bosworth (2000).22 The 88-country sample provides reasonably good and representative coverage of various geographic regions and income groups. It includes, for example, eight countries in the Middle East and North Africa region (MENA), 12 countries in the East Asia and Pacific region (EAP), 61 developing countries, and 22 OECD countries.23 The common time period 1973–94, chosen because the start year has been used frequently in other studies of growth accounting (for example, Bosworth and Collins, 1999), facilitates comparison with these studies. It also excludes the West Bank and Gaza’s unusually high TFP growth of 1970–73 and the unusually large negative TFP growth associated with the closures in 1995–96. Table 2.2 compares West Bank and Gaza’s TFP growth with the MENA region and eight countries in that region in 1973–94, and Table 2.3 compares the West Bank and Gaza with other regions in the world.
Sources of Output Growth: West Bank and Gaza and Selected Countries in the Middle East and North Africa, 1973–94
(Annual percent)
The assumptions are: capital share of income 0.35; depreciation rate of 4 percent; and initial capital-output ratio of 2.5.
Unweighted average of countries excluding West Bank and Gaza. Numbers may not add up to total due to rounding.
Sources of Output Growth: West Bank and Gaza and Selected Countries in the Middle East and North Africa, 1973–94
(Annual percent)
Contribution of:1 | ||||
---|---|---|---|---|
Countries | Growth of Output |
Capital Stock | Employment | Total Factor Productivity |
West Bank and Gaza | 5.8 | 2.7 | 1.5 | 1.6 |
MENA2 | 4.8 | 2.2 | 2.0 | 0.7 |
Algeria | 3.2 | 2.0 | 2.7 | -1.6 |
Egypt | 6.2 | 3.0 | 2.1 | 1.1 |
Iran | 1.7 | 2.1 | 2.1 | -2.5 |
Israel | 4.2 | 1.6 | 1.8 | 0.8 |
Jordan | 5.6 | 3.0 | 2.8 | -0.2 |
Malta | 6.7 | 1.8 | 0.5 | 4.5 |
Morocco | 4.4 | 2.1 | 2.3 | -0.1 |
Tunisia | 4.4 | 1.9 | 2.3 | 0.2 |
The assumptions are: capital share of income 0.35; depreciation rate of 4 percent; and initial capital-output ratio of 2.5.
Unweighted average of countries excluding West Bank and Gaza. Numbers may not add up to total due to rounding.
Sources of Output Growth: West Bank and Gaza and Selected Countries in the Middle East and North Africa, 1973–94
(Annual percent)
Contribution of:1 | ||||
---|---|---|---|---|
Countries | Growth of Output |
Capital Stock | Employment | Total Factor Productivity |
West Bank and Gaza | 5.8 | 2.7 | 1.5 | 1.6 |
MENA2 | 4.8 | 2.2 | 2.0 | 0.7 |
Algeria | 3.2 | 2.0 | 2.7 | -1.6 |
Egypt | 6.2 | 3.0 | 2.1 | 1.1 |
Iran | 1.7 | 2.1 | 2.1 | -2.5 |
Israel | 4.2 | 1.6 | 1.8 | 0.8 |
Jordan | 5.6 | 3.0 | 2.8 | -0.2 |
Malta | 6.7 | 1.8 | 0.5 | 4.5 |
Morocco | 4.4 | 2.1 | 2.3 | -0.1 |
Tunisia | 4.4 | 1.9 | 2.3 | 0.2 |
The assumptions are: capital share of income 0.35; depreciation rate of 4 percent; and initial capital-output ratio of 2.5.
Unweighted average of countries excluding West Bank and Gaza. Numbers may not add up to total due to rounding.
Sources of Output Growth: West Bank and Gaza and by Major Regional and Income Groups, 1973–94
(Annual percent)
The assumptions are: capital share of income 0.35: depreciation rate of 4 percent: and initial capital-output ratio of 2.5.
Unweighted average. The West Bank and Gaza would be in the lower middle-income group.
Consists of Indonesia, Korea, Singapore, Thailand, Philippines, Taiwan, Malaysia, and China.
Consists of 88 countries.
Sources of Output Growth: West Bank and Gaza and by Major Regional and Income Groups, 1973–94
(Annual percent)
Contribution of:1 | ||||
---|---|---|---|---|
Region and Income Group2 | Growth of Output |
Capital Stock | Employment | Total Factor Productivity |
West Bank and Gaza | 5.8 | 2.7 | 1.5 | 1.6 |
East Asia and Pacific3 | 7.0 | 3.3 | 1.8 | 2.0 |
Middle East and North Africa | 4.8 | 2.2 | 2.0 | 0.7 |
South Asia | 4.8 | 1.7 | 2.0 | 1.1 |
Sub-Saharan Africa | 1.9 | 1.2 | 1.6 | -0.9 |
Latin America and the Caribbean | 2.6 | 1.4 | 1.8 | -0.6 |
Low-income countries | 2.5 | 1.4 | 1.8 | -0.7 |
Lower middle-income countries | 3.5 | 1.8 | 2.0 | -0.3 |
Upper middle-income countries | 3.8 | 1.7 | 1.6 | 0.5 |
High-income OECD countries | 2.5 | 1.2 | 0.4 | 0.9 |
High-income countries | 3.2 | 1.4 | 0.6 | 1.1 |
Developing countries | 3.1 | 1.6 | 1.8 | -0.3 |
World 4 | 3.1 | 1.6 | 1.4 | 0.1 |
The assumptions are: capital share of income 0.35: depreciation rate of 4 percent: and initial capital-output ratio of 2.5.
Unweighted average. The West Bank and Gaza would be in the lower middle-income group.
Consists of Indonesia, Korea, Singapore, Thailand, Philippines, Taiwan, Malaysia, and China.
Consists of 88 countries.
Sources of Output Growth: West Bank and Gaza and by Major Regional and Income Groups, 1973–94
(Annual percent)
Contribution of:1 | ||||
---|---|---|---|---|
Region and Income Group2 | Growth of Output |
Capital Stock | Employment | Total Factor Productivity |
West Bank and Gaza | 5.8 | 2.7 | 1.5 | 1.6 |
East Asia and Pacific3 | 7.0 | 3.3 | 1.8 | 2.0 |
Middle East and North Africa | 4.8 | 2.2 | 2.0 | 0.7 |
South Asia | 4.8 | 1.7 | 2.0 | 1.1 |
Sub-Saharan Africa | 1.9 | 1.2 | 1.6 | -0.9 |
Latin America and the Caribbean | 2.6 | 1.4 | 1.8 | -0.6 |
Low-income countries | 2.5 | 1.4 | 1.8 | -0.7 |
Lower middle-income countries | 3.5 | 1.8 | 2.0 | -0.3 |
Upper middle-income countries | 3.8 | 1.7 | 1.6 | 0.5 |
High-income OECD countries | 2.5 | 1.2 | 0.4 | 0.9 |
High-income countries | 3.2 | 1.4 | 0.6 | 1.1 |
Developing countries | 3.1 | 1.6 | 1.8 | -0.3 |
World 4 | 3.1 | 1.6 | 1.4 | 0.1 |
The assumptions are: capital share of income 0.35: depreciation rate of 4 percent: and initial capital-output ratio of 2.5.
Unweighted average. The West Bank and Gaza would be in the lower middle-income group.
Consists of Indonesia, Korea, Singapore, Thailand, Philippines, Taiwan, Malaysia, and China.
Consists of 88 countries.
In 1973–94, TFP growth in the West Bank and Gaza averaged 1.6 percent a year; more than twice as high as the MENA average and also twice that of Israel and higher than that of Jordan by 1.8 percentage points per year. Historically, the MENA region has not been among the world’s better performers with respect to TFP or output growth, but the TFP performance of the Palestinian economy compares well with the rest of the world. In fact, its TFP growth exceeds the averages for all the income and regional groupings in Table 2.3 as well as the world sample of 88 countries, except for the high performing EAP region. Given the circumstances, TFP growth in the West Bank and Gaza during 1973–94 was quite good.
At the same time, it should be recalled that the above discussion focused on real GDP growth, ignoring differences in population growth developments. Taking into account the high population growth, the growth performance of the Palestinian economy is less impressive. This will be examined later.
The Palestinian economy has, moreover, exhibited substantial output volatility. In the period 1973–94 (the period for which cross-country data are available) the coefficient of variation of real GDP growth was 1.6 for the West Bank and Gaza compared with a median of 0.8 for the eight MENA countries, 1.4 in the 61 developing countries, and 0.5 in the EAP region (Figure 2.3). Among the various country groupings, it was only Latin America (1.7) that scored higher on volatility. The coefficient of variation for per capita real GDP growth in the West Bank and Gaza was even higher at 3.1 in 1973–94 and 3.9 in 1994–99. The issue of output volatility will be exploited further later in this chapter.
Comparison of Output Volatility, 1973–94
Sources: Collins and Bosworth (2000). PCBS. ICBS. and IMF staff calculations. Output volatility is defined as the coefficient of variation, which 15 the standard deviation of annual GDP growth divided by the mean of real GDP growth, for the period 1973–94. For country groupings it is the sample median of the country specific coefficients of variations. The number of countries included for each region is shown in parentheses. Table A1.1 shows a list of all countries.Projected Changes in Demographics, the Labor Force, and Employment
Changing Palestinian Demographics
Population growth in the West Bank and Gaza averaged about 3.7 percent in 1990–97, compared with 1.5 percent for the world as a whole, 2.3 percent in the MENA region, and 2.7 percent in generally fast-growing sub-Saharan Africa (Figure 2.4 and Table 2.4).24 The actual population growth, which includes migration, was even higher, at around 5.1 percent, as the West Bank and Gaza experienced strong immigration in the aftermath of the Gulf Crisis and in 1994–95, following the signing of the peace accords with Israel. Immigration has since declined to a point where it has been insignificant in the past few years, thereby eliminating the difference between actual and natural population growth rates. One consequence of the high fertility rates is that the population is now very young: almost 20 percent of the population is less than five years old, over a third is less than 10, and almost half of the population is younger than 15 (Figure 2.4). The median age is approximately 16 years.
Population Growth in the West Bank and Gaza Relative to the Rest of the World
Difference between crude birth and death rates.
Total births per woman.
Population Growth in the West Bank and Gaza Relative to the Rest of the World
Actual Population Growth Rate | Crude Birth Rate | Crude Death Rate | Natural Population Growth Rate1 | Fertility Rate2 | |
---|---|---|---|---|---|
West Bank and Gaza | 5.1 | 4.3 | 0.5 | 3.7 | 6.2 |
East Asia and Pacific | 1.4 | 2.1 | 0.7 | 1.3 | 2.3 |
Europe and Central Asia | 0.3 | 1.5 | 1.1 | 0.4 | 2.0 |
Latin America and Caribbean | 1.7 | 2.5 | 0.7 | 1.8 | 2.9 |
Middle East and North Africa | 2.4 | 3.0 | 0.7 | 2.3 | 4.2 |
South Asia | 1.9 | 3.0 | 1.0 | 2.0 | 3.8 |
Sub-Saharan Africa | 2.7 | 4.2 | 1.5 | 2.7 | 5.8 |
Low-income countries | 2.1 | 3.4 | 1.1 | 2.2 | 4.3 |
Low- and middle-income countries | 1.6 | 2.6 | 0.9 | 1.7 | 3.2 |
Middle-income countries | 1.3 | 2.1 | 0.8 | 1.3 | 14 |
Upper middle-income countries | 1.6 | 2.3 | 0.7 | 1.6 | 2.8 |
High-income countries | 0.7 | 1.3 | 0.9 | 0.4 | 1.7 |
Least developed countries (UN classification) | 2.4 | 4.0 | 1.5 | 2.5 | 5.4 |
World | 1.5 | 2.4 | 0.9 | 1.5 | 2.9 |
Difference between crude birth and death rates.
Total births per woman.
Population Growth in the West Bank and Gaza Relative to the Rest of the World
Actual Population Growth Rate | Crude Birth Rate | Crude Death Rate | Natural Population Growth Rate1 | Fertility Rate2 | |
---|---|---|---|---|---|
West Bank and Gaza | 5.1 | 4.3 | 0.5 | 3.7 | 6.2 |
East Asia and Pacific | 1.4 | 2.1 | 0.7 | 1.3 | 2.3 |
Europe and Central Asia | 0.3 | 1.5 | 1.1 | 0.4 | 2.0 |
Latin America and Caribbean | 1.7 | 2.5 | 0.7 | 1.8 | 2.9 |
Middle East and North Africa | 2.4 | 3.0 | 0.7 | 2.3 | 4.2 |
South Asia | 1.9 | 3.0 | 1.0 | 2.0 | 3.8 |
Sub-Saharan Africa | 2.7 | 4.2 | 1.5 | 2.7 | 5.8 |
Low-income countries | 2.1 | 3.4 | 1.1 | 2.2 | 4.3 |
Low- and middle-income countries | 1.6 | 2.6 | 0.9 | 1.7 | 3.2 |
Middle-income countries | 1.3 | 2.1 | 0.8 | 1.3 | 14 |
Upper middle-income countries | 1.6 | 2.3 | 0.7 | 1.6 | 2.8 |
High-income countries | 0.7 | 1.3 | 0.9 | 0.4 | 1.7 |
Least developed countries (UN classification) | 2.4 | 4.0 | 1.5 | 2.5 | 5.4 |
World | 1.5 | 2.4 | 0.9 | 1.5 | 2.9 |
Difference between crude birth and death rates.
Total births per woman.
Palestinian Population Dynamics
Sources: PCBS, World Bank Development Indicators, and IMF staff calculations and estimates.A stylized fact of economic development and demographics is that, as countries develop, they typically undergo a demographic transition during which both birth and death rates fall to much lower levels, and population growth accelerates temporarily because the fall in mortality tends to lead that in fertility (Figure 2.5). The West Bank and Gaza appears to be in the middle of such a demographic transition, with population growth now at or close to its peak.25 Indeed, its crude birth rate (4.3) is higher and, quite surprisingly, its crude death rate (0.5) is lower than the averages of all the various country groupings presented in Table 2.4. Over the medium term, and in line with the stylized demographic transition just described, the decline in the fertility rate is projected to become sharper, the population growth rate slower, and the population older. PCBS (1999) projects the median age to increase by 30 percent over the next 25 years to 21.4 years.
The baseline population projections presented here are based on PCBS (1999) but modified by IMF staff, as explained in Box 2.1. Population growth is projected to decline gradually to around 2.4 percent by 2025 under the assumptions that the fertility and infant mortality rates will both decline by 50 percent between 1997 and 2025 (as projected in the medium scenario in PCBS, 1999), and that there is no net migration during this period. The assumption of zero net migration in the baseline scenario is made in order to isolate the dynamics stemming from the existing population. On the basis of these three assumptions, the West Bank and Gaza would move further to the right on the stylized demographic transition curve in Figure 2.5, the natural population growth rate would fall, and the working-age population would increase from 53 percent of the population in 1999 to 64 percent in 2025 (Table 2.5).26 The lower left panel of Figure 2.4 shows how the age structure would change over time, compared with the population structure in 1997—while population will grow across all ages, the sharpened hump shows the faster growth in working-age population. Other countries in the Middle East region are expected to go through a similar demographic transition but nowhere will the changes be as dramatic as in the West Bank and Gaza.27
Population Projections in the West Bank and Gaza by Age Group, 1999–2025
Growth rates shown for 2010, 2015, 2020, and 2025 are the average annual growth rate in the five-year period ending that year.
Population of 15 years of age and older, in thousands.
Population Projections in the West Bank and Gaza by Age Group, 1999–2025
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | 2015 | 2020 | 2025 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|
(In thousands) | ||||||||||||
Population | 2,759 | 2.861 | 2,966 | 3.072 | 3.181 | 3,291 | 3,403 | 3,990 | 4,618 | 5,276 | 5,946 | |
0–4 | 515 | 531 | 547 | 561 | 572 | 583 | 593 | 643 | 690 | 728 | 750 | |
5–14 | 780 | 812 | 844 | 876 | 910 | 943 | 975 | 1,120 | 1,232 | 1,329 | 1,415 | |
15–24 | 529 | 547 | 566 | 587 | 610 | 634 | 660 | 808 | 971 | 1,116 | 1,228 | |
25–34 | 377 | 390 | 403 | 417 | 431 | 445 | 460 | 542 | 655 | 802 | 965 | |
35–44 | 243 | 258 | 271 | 285 | 298 | 310 | 322 | 385 | 455 | 536 | 649 | |
45–54 | 132 | 138 | 145 | 154 | 163 | 173 | 185 | 250 | 314 | 375 | 444 | |
55+ | 182 | 186 | 189 | 193 | 198 | 203 | 208 | 243 | 302 | 389 | 495 | |
(Annual percentage change)1 | ||||||||||||
Population | 3.8 | 3.7 | 3.7 | 3.6 | 3.5 | 3.5 | 3.4 | 3.2 | 3.0 | 2.7 | 2.4 | |
0–4 | 3.5 | 3.2 | 2.9 | 2.6 | 2.0 | 1.9 | 1.8 | 0.6 | 1.4 | 1.1 | 0.6 | |
5–14 | 4.1 | 4.1 | 3.9 | 3.8 | 3.9 | 3.6 | 3.4 | 2.8 | 1.9 | 1.5 | 1.3 | |
15–24 | 3.3 | 3.4 | 3.5 | 3.7 | 3.9 | 4.0 | 4.1 | 4.1 | 3.7 | 2.8 | 1.9 | |
25–34 | 3.5 | 3.5 | 3.4 | 3.4 | 3.4 | 3.3 | 3.3 | 3.3 | 3.8 | 4.1 | 3.8 | |
35–44 | 6.1 | 5.8 | 5.4 | 5.0 | 4.5 | 4.2 | 3.9 | 3.6 | 3.4 | 3.4 | 3.9 | |
45–54 | 4.3 | 4.6 | 5.1 | 5.6 | 6.1 | 6.4 | 6.5 | 6.2 | 4.6 | 3.7 | 3.4 | |
55+ | 1.7 | 1.9 | 2.0 | 2.2 | 2.3 | 2.5 | 2.7 | 3.1 | 4.5 | 5.2 | 5.0 | |
Memorandum items: | ||||||||||||
Working-age population2 | 1,463.6 | 1,518.1 | 1,575.4 | 1,635.6 | 1,699.0 | 1,765.6 | 1,835.2 | 2,227.1 | 2.695.8 | 3.218.4 | 3.780.7 | |
Growth in percent | 3.7 | 3.7 | 3.8 | 3.8 | 3.9 | 3.9 | 3.9 | 3.9 | 3.9 | 3.6 | 3.3 | |
In percent of total population | 53.1 | 53.1 | 53.1 | 53.2 | 53.4 | 53.6 | 53.9 | 55.8 | 58.4 | 61.0 | 63.6 |
Growth rates shown for 2010, 2015, 2020, and 2025 are the average annual growth rate in the five-year period ending that year.
Population of 15 years of age and older, in thousands.
Population Projections in the West Bank and Gaza by Age Group, 1999–2025
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | 2015 | 2020 | 2025 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|
(In thousands) | ||||||||||||
Population | 2,759 | 2.861 | 2,966 | 3.072 | 3.181 | 3,291 | 3,403 | 3,990 | 4,618 | 5,276 | 5,946 | |
0–4 | 515 | 531 | 547 | 561 | 572 | 583 | 593 | 643 | 690 | 728 | 750 | |
5–14 | 780 | 812 | 844 | 876 | 910 | 943 | 975 | 1,120 | 1,232 | 1,329 | 1,415 | |
15–24 | 529 | 547 | 566 | 587 | 610 | 634 | 660 | 808 | 971 | 1,116 | 1,228 | |
25–34 | 377 | 390 | 403 | 417 | 431 | 445 | 460 | 542 | 655 | 802 | 965 | |
35–44 | 243 | 258 | 271 | 285 | 298 | 310 | 322 | 385 | 455 | 536 | 649 | |
45–54 | 132 | 138 | 145 | 154 | 163 | 173 | 185 | 250 | 314 | 375 | 444 | |
55+ | 182 | 186 | 189 | 193 | 198 | 203 | 208 | 243 | 302 | 389 | 495 | |
(Annual percentage change)1 | ||||||||||||
Population | 3.8 | 3.7 | 3.7 | 3.6 | 3.5 | 3.5 | 3.4 | 3.2 | 3.0 | 2.7 | 2.4 | |
0–4 | 3.5 | 3.2 | 2.9 | 2.6 | 2.0 | 1.9 | 1.8 | 0.6 | 1.4 | 1.1 | 0.6 | |
5–14 | 4.1 | 4.1 | 3.9 | 3.8 | 3.9 | 3.6 | 3.4 | 2.8 | 1.9 | 1.5 | 1.3 | |
15–24 | 3.3 | 3.4 | 3.5 | 3.7 | 3.9 | 4.0 | 4.1 | 4.1 | 3.7 | 2.8 | 1.9 | |
25–34 | 3.5 | 3.5 | 3.4 | 3.4 | 3.4 | 3.3 | 3.3 | 3.3 | 3.8 | 4.1 | 3.8 | |
35–44 | 6.1 | 5.8 | 5.4 | 5.0 | 4.5 | 4.2 | 3.9 | 3.6 | 3.4 | 3.4 | 3.9 | |
45–54 | 4.3 | 4.6 | 5.1 | 5.6 | 6.1 | 6.4 | 6.5 | 6.2 | 4.6 | 3.7 | 3.4 | |
55+ | 1.7 | 1.9 | 2.0 | 2.2 | 2.3 | 2.5 | 2.7 | 3.1 | 4.5 | 5.2 | 5.0 | |
Memorandum items: | ||||||||||||
Working-age population2 | 1,463.6 | 1,518.1 | 1,575.4 | 1,635.6 | 1,699.0 | 1,765.6 | 1,835.2 | 2,227.1 | 2.695.8 | 3.218.4 | 3.780.7 | |
Growth in percent | 3.7 | 3.7 | 3.8 | 3.8 | 3.9 | 3.9 | 3.9 | 3.9 | 3.9 | 3.6 | 3.3 | |
In percent of total population | 53.1 | 53.1 | 53.1 | 53.2 | 53.4 | 53.6 | 53.9 | 55.8 | 58.4 | 61.0 | 63.6 |
Growth rates shown for 2010, 2015, 2020, and 2025 are the average annual growth rate in the five-year period ending that year.
Population of 15 years of age and older, in thousands.
Projected Labor Supply Growth
Over the medium term, labor supply growth will be affected by three factors. First, labor supply will expand as the large youth cohort enters working age. The lower right panel of Figure 2.4 shows the youth cohort and how its size dwarfs that of the population currently employed. Second, the overall labor force participation rate is projected to rise because more people will enter age groups with relatively higher participation rates. The combined effect of these two factors is shown as Average 1 in Table 2.6. Lastly, the labor force participation rate for women is assumed to increase. Female labor force participation is low (at 11 percent in 1999) by international comparison, and it would be reasonable to expect the decline in the fertility rate to be accompanied by a rise in the female labor force participation rate, even though the link between fertility rates and labor force participation rates is admittedly difficult to predict since it is heavily influenced not only by economic but also by cultural and social factors.28 For the purpose of this analysis, we assume that the average female labor force participation rate in the West Bank and Gaza increases gradually to 24 percent by year 2025 and that the increased labor force participation rate is concentrated among women aged 15–34. Under the combined effect of these three factors, the overall labor force participation rate—for men and women—would rise from 41.0 percent on average in 1999 to 43.3 percent in 2010 and further to 47.6 percent by 2025, and labor force growth would be 4.4 percent per year for the period 2000–10, after which it would slow down modestly (Average II in Table 2.6; and Table 2.7). In the end, the actual evolution of labor force participation rates will also be influenced by the prospects for employment, and, as will be discussed later, even under ambitious targets for growth in output and employment, the West Bank and Gaza is likely to experience a prolonged period of high unemployment and this in turn might reduce labor force participation rates. This analysis ignores this possible feedback effect since its purpose is to assess the requirements for growth and TFP for a given labor force growth.
Labor Force Participation Rates in the West Bank and Gaza by Age and Gender, 1999–2025
Constant age-gender cohort specific labor force participation rates.
Assumes that the average labor force participation rate for women converges to the rate in Jordan (23.7 percent) by 2025. and that the increase is concentrated in the 15–34 age groups.
Labor Force Participation Rates in the West Bank and Gaza by Age and Gender, 1999–2025
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | 2015 | 2020 | 2025 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|
(In percent of working-age population) | ||||||||||||
Average 1 (constant age-gender specific rates)1 | 41.0 | 41.1 | 41.2 | 41.3 | 41.3 | 41.4 | 41.4 | 41.4 | 41.4 | 41.4 | 41.5 | |
For men | 70.5 | 70.7 | 70.8 | 70.9 | 71.0 | 71.0 | 71.1 | 71.0 | 70.8 | 70.7 | 70.9 | |
For women | 11.3 | 11.3 | 11.3 | 11.3 | 11.3 | 11.4 | 11.4 | 11.4 | 11.4 | 11.4 | 11.5 | |
Average II (increasing female labor force participation)2 | 41.0 | 41.2 | 41.5 | 41.7 | 41.9 | 42.1 | 42.3 | 43.3 | 44.3 | 45.7 | 47.6 | |
15–14 | 30.8 | 31.0 | 31.1 | 31.3 | 31.4 | 31.6 | 31.7 | 32.6 | 33.8 | 35.4 | 37.3 | |
25–34 | 54.7 | 54.9 | 55.2 | 55.5 | 55.9 | 56.3 | 56.7 | 59.2 | 61.9 | 65.2 | 69.5 | |
35–44 | 54.6 | 54.6 | 54.6 | 54.6 | 54.6 | 54.5 | 54.5 | 54.0 | S4.0 | 54.2 | 54.1 | |
45–54 | 47.7 | 43.0 | 48.3 | 48.6 | 48.8 | 49.0 | 49.1 | 49.6 | 49.5 | 49.1 | 49.0 | |
55+ | 19.0 | 18.9 | 18.9 | 18.9 | 18.9 | 18.9 | 19.0 | 19.4 | 19.9 | 20.3 | 20.5 | |
Men | 70.5 | 70.7 | 70.8 | 70.9 | 71.0 | 71.0 | 71.1 | 71.0 | 70.8 | 70.7 | 70.9 | |
15–24 | 53.3 | S3.3 | 53.3 | 53.3 | 53.3 | 53.3 | 53.3 | 53.3 | S3.3 | S3.3 | S3.3 | |
25–34 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | |
35–44 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | |
45–54 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | |
55+ | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 364 | 36.4 | 36.4 | |
Women1 | 11.3 | 11.6 | 11.9 | 12.2 | 12.5 | 12.8 | 13.2 | 15.0 | 17.3 | 20.3 | 23.7 | |
15–24 | 7.2 | 7.5 | 7.8 | 8.1 | 8.5 | 8.8 | 9.2 | 11.3 | 13.8 | 16.9 | 20.7 | |
25–34 | 16.3 | 17.0 | 17.7 | 18.4 | 19.2 | 20.0 | 20.8 | 25.5 | 31.2 | 38.3 | 46.9 | |
35–44 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | |
45–54 | 14.6 | 14.6 | 146 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | |
55+ | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 |
Constant age-gender cohort specific labor force participation rates.
Assumes that the average labor force participation rate for women converges to the rate in Jordan (23.7 percent) by 2025. and that the increase is concentrated in the 15–34 age groups.
Labor Force Participation Rates in the West Bank and Gaza by Age and Gender, 1999–2025
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | 2015 | 2020 | 2025 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|
(In percent of working-age population) | ||||||||||||
Average 1 (constant age-gender specific rates)1 | 41.0 | 41.1 | 41.2 | 41.3 | 41.3 | 41.4 | 41.4 | 41.4 | 41.4 | 41.4 | 41.5 | |
For men | 70.5 | 70.7 | 70.8 | 70.9 | 71.0 | 71.0 | 71.1 | 71.0 | 70.8 | 70.7 | 70.9 | |
For women | 11.3 | 11.3 | 11.3 | 11.3 | 11.3 | 11.4 | 11.4 | 11.4 | 11.4 | 11.4 | 11.5 | |
Average II (increasing female labor force participation)2 | 41.0 | 41.2 | 41.5 | 41.7 | 41.9 | 42.1 | 42.3 | 43.3 | 44.3 | 45.7 | 47.6 | |
15–14 | 30.8 | 31.0 | 31.1 | 31.3 | 31.4 | 31.6 | 31.7 | 32.6 | 33.8 | 35.4 | 37.3 | |
25–34 | 54.7 | 54.9 | 55.2 | 55.5 | 55.9 | 56.3 | 56.7 | 59.2 | 61.9 | 65.2 | 69.5 | |
35–44 | 54.6 | 54.6 | 54.6 | 54.6 | 54.6 | 54.5 | 54.5 | 54.0 | S4.0 | 54.2 | 54.1 | |
45–54 | 47.7 | 43.0 | 48.3 | 48.6 | 48.8 | 49.0 | 49.1 | 49.6 | 49.5 | 49.1 | 49.0 | |
55+ | 19.0 | 18.9 | 18.9 | 18.9 | 18.9 | 18.9 | 19.0 | 19.4 | 19.9 | 20.3 | 20.5 | |
Men | 70.5 | 70.7 | 70.8 | 70.9 | 71.0 | 71.0 | 71.1 | 71.0 | 70.8 | 70.7 | 70.9 | |
15–24 | 53.3 | S3.3 | 53.3 | 53.3 | 53.3 | 53.3 | 53.3 | 53.3 | S3.3 | S3.3 | S3.3 | |
25–34 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | 91.4 | |
35–44 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | 91.2 | |
45–54 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | 82.5 | |
55+ | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 36.4 | 364 | 36.4 | 36.4 | |
Women1 | 11.3 | 11.6 | 11.9 | 12.2 | 12.5 | 12.8 | 13.2 | 15.0 | 17.3 | 20.3 | 23.7 | |
15–24 | 7.2 | 7.5 | 7.8 | 8.1 | 8.5 | 8.8 | 9.2 | 11.3 | 13.8 | 16.9 | 20.7 | |
25–34 | 16.3 | 17.0 | 17.7 | 18.4 | 19.2 | 20.0 | 20.8 | 25.5 | 31.2 | 38.3 | 46.9 | |
35–44 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | 15.5 | |
45–54 | 14.6 | 14.6 | 146 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | 14.6 | |
55+ | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 | 5.3 |
Constant age-gender cohort specific labor force participation rates.
Assumes that the average labor force participation rate for women converges to the rate in Jordan (23.7 percent) by 2025. and that the increase is concentrated in the 15–34 age groups.
Labor Force Projections for the West Bank and Gaza by Age Group, 1999–2025
(Change in percent, unless otherwise indicated) 1
Growth rates shown for 2010, 2015, 2020, and 2025 are the average annual growth late in the five-year period.
Population of 15 years older.
Assumes chat the average labor force participation race for women converges to the rate in Jordan (23.7 percent) by 2025, and that the increase is concentrated in the 15–34 age groups. See Table 2.3.
Labor Force Projections for the West Bank and Gaza by Age Group, 1999–2025
(Change in percent, unless otherwise indicated) 1
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | 2015 | 2020 | 2025 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Population | 3.8 | 3.7 | 3.7 | 3.6 | 3.5 | 3.5 | 3.4 | 3.2 | 3.0 | 2.7 | 2.4 | ||
Working-age population2 | 3.7 | 3.7 | 3.8 | 3.8 | 3.9 | 3.9 | 3.9 | 3.9 | 3.9 | 3.6 | 3.3 | ||
15–24 | 3.3 | 3.4 | 3.5 | 3.7 | 3.9 | 4.0 | 4.1 | 4.1 | 3.7 | 2.8 | 0.9 | ||
25–34 | 3.5 | 3.5 | 3.4 | 3.4 | 3.4 | 3.3 | 3.3 | 3.3 | 3.8 | 4.1 | 3.8 | ||
35–44 | 6.1 | 5.8 | 5.4 | 5.0 | 4.5 | 4.2 | 3.9 | 3.6 | 3.4 | 3.4 | 3.9 | ||
45–54 | 4.3 | 4.6 | 5.1 | 5.6 | 6.1 | 6.4 | 6.5 | 6.2 | 4.6 | 3.7 | 3.4 | ||
55+ | 1.7 | 1.9 | 2.0 | 2.2 | 2.3 | 2.5 | 2.7 | 3.1 | 4.5 | 5.2 | 5.0 | ||
Labor force participation rates3 | 41.0 | 41.2 | 41.5 | 41.7 | 41.9 | 42.1 | 42.3 | 43.3 | 44.3 | 45.7 | 47.6 | ||
15–24 | 30.8 | 31.0 | 31.1 | 31.3 | 31.4 | 31.6 | 31.7 | 32.6 | 33.8 | 35.4 | 37.3 | ||
25–34 | 54.7 | 54.9 | 55.2 | 55.5 | 55.9 | 56.3 | 56.7 | 59.2 | 61.9 | 65.2 | 69.5 | ||
35–44 | 54.6 | 54.6 | 54.6 | 54.6 | 54.6 | 54.5 | 54.5 | 54.0 | 54.0 | 54.2 | 54.1 | ||
45–54 | 47.7 | 48.0 | 48.3 | 48.6 | 48.8 | 49.0 | 49.1 | 49.6 | 49.5 | 49.1 | 49.0 | ||
55+ | 19.0 | 18.9 | 18.9 | 18.9 | 18.9 | 18.9 | 19.0 | 19.4 | 19.9 | 20.3 | 20.5 | ||
Labor force (in thousands)3 | 599.3 | 625.7 | 653.2 | 681.9 | 712.0 | 743.5 | 776.3 | 963.3 | 1,194.8 | 1,472.0 | 1,798.2 | ||
Growth in percent | 4.1 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.3 | 4.1 | ||
Men | 4.1 | 4.1 | 4.1 | 4.0 | 4.0 | 4.0 | 4.0 | 4.0 | 3.9 | 3.6 | 3.3 | ||
Women | 3.9 | 6.5 | 6.5 | 6.5 | 6.6 | 6.6 | 6.6 | 6.7 | 6.9 | 6.8 | 6.6 | ||
Labor force/population, in percent | 21.7 | 21.9 | 22.0 | 22.2 | 22.4 | 22.6 | 22.8 | 24.1 | 25.9 | 27.9 | 30.2 |
Growth rates shown for 2010, 2015, 2020, and 2025 are the average annual growth late in the five-year period.
Population of 15 years older.
Assumes chat the average labor force participation race for women converges to the rate in Jordan (23.7 percent) by 2025, and that the increase is concentrated in the 15–34 age groups. See Table 2.3.
Labor Force Projections for the West Bank and Gaza by Age Group, 1999–2025
(Change in percent, unless otherwise indicated) 1
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | 2015 | 2020 | 2025 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Population | 3.8 | 3.7 | 3.7 | 3.6 | 3.5 | 3.5 | 3.4 | 3.2 | 3.0 | 2.7 | 2.4 | ||
Working-age population2 | 3.7 | 3.7 | 3.8 | 3.8 | 3.9 | 3.9 | 3.9 | 3.9 | 3.9 | 3.6 | 3.3 | ||
15–24 | 3.3 | 3.4 | 3.5 | 3.7 | 3.9 | 4.0 | 4.1 | 4.1 | 3.7 | 2.8 | 0.9 | ||
25–34 | 3.5 | 3.5 | 3.4 | 3.4 | 3.4 | 3.3 | 3.3 | 3.3 | 3.8 | 4.1 | 3.8 | ||
35–44 | 6.1 | 5.8 | 5.4 | 5.0 | 4.5 | 4.2 | 3.9 | 3.6 | 3.4 | 3.4 | 3.9 | ||
45–54 | 4.3 | 4.6 | 5.1 | 5.6 | 6.1 | 6.4 | 6.5 | 6.2 | 4.6 | 3.7 | 3.4 | ||
55+ | 1.7 | 1.9 | 2.0 | 2.2 | 2.3 | 2.5 | 2.7 | 3.1 | 4.5 | 5.2 | 5.0 | ||
Labor force participation rates3 | 41.0 | 41.2 | 41.5 | 41.7 | 41.9 | 42.1 | 42.3 | 43.3 | 44.3 | 45.7 | 47.6 | ||
15–24 | 30.8 | 31.0 | 31.1 | 31.3 | 31.4 | 31.6 | 31.7 | 32.6 | 33.8 | 35.4 | 37.3 | ||
25–34 | 54.7 | 54.9 | 55.2 | 55.5 | 55.9 | 56.3 | 56.7 | 59.2 | 61.9 | 65.2 | 69.5 | ||
35–44 | 54.6 | 54.6 | 54.6 | 54.6 | 54.6 | 54.5 | 54.5 | 54.0 | 54.0 | 54.2 | 54.1 | ||
45–54 | 47.7 | 48.0 | 48.3 | 48.6 | 48.8 | 49.0 | 49.1 | 49.6 | 49.5 | 49.1 | 49.0 | ||
55+ | 19.0 | 18.9 | 18.9 | 18.9 | 18.9 | 18.9 | 19.0 | 19.4 | 19.9 | 20.3 | 20.5 | ||
Labor force (in thousands)3 | 599.3 | 625.7 | 653.2 | 681.9 | 712.0 | 743.5 | 776.3 | 963.3 | 1,194.8 | 1,472.0 | 1,798.2 | ||
Growth in percent | 4.1 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.4 | 4.3 | 4.1 | ||
Men | 4.1 | 4.1 | 4.1 | 4.0 | 4.0 | 4.0 | 4.0 | 4.0 | 3.9 | 3.6 | 3.3 | ||
Women | 3.9 | 6.5 | 6.5 | 6.5 | 6.6 | 6.6 | 6.6 | 6.7 | 6.9 | 6.8 | 6.6 | ||
Labor force/population, in percent | 21.7 | 21.9 | 22.0 | 22.2 | 22.4 | 22.6 | 22.8 | 24.1 | 25.9 | 27.9 | 30.2 |
Growth rates shown for 2010, 2015, 2020, and 2025 are the average annual growth late in the five-year period.
Population of 15 years older.
Assumes chat the average labor force participation race for women converges to the rate in Jordan (23.7 percent) by 2025, and that the increase is concentrated in the 15–34 age groups. See Table 2.3.
Employment Growth
The challenge for the Palestinian economy is to absorb the expanding labor force into productive employment, at reasonable wages, while at the same time reduce unemployment. The previous section showed that, under plausible assumptions, labor supply could be expected to grow by about 4.4 percent a year through 2010 without taking into account any effects from possible migration.
Before the turmoil and closures that started in late September 2000, Palestinian unemployment was on a downward trend reaching 8.8 percent of the labor force in June 2000, the lowest level since 1993. The medium-term outlook then was dominated by the challenge to absorb the projected inflows to the labor market at growing real wages and to achieve some further reduction in the unemployment rate. With a target of reducing the unemployment rate by half (to 4.4 percent) by 2010, the Palestinian economy would have had to generate domestic employment growth of 6 percent a year, a significant challenge in view of the 3 percent a year expansion in domestic employment that the Palestinian economy achieved over the past 30 years (Scenario 1 in Table 2.8).
Employment and Unemployment Scenarios, 1999–2010
Consists mostly of private sector but also local authorities and public enterprises (unless paid through the PA budget).
In percent of labor force, annual average.
Employment and Unemployment Scenarios, 1999–2010
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | ||
---|---|---|---|---|---|---|---|---|---|
Scenario 1—Baseline Before Crisis | |||||||||
Labor force (thousands) | 599 | 626 | 653 | 682 | 712 | 743 | 776 | 963 | |
Unemployment rate1 | 12 | 9 | 8 | 8 | 7 | 7 | 7 | 4 | |
Employment (thousands) | 529 | 571 | 599 | 628 | 659 | 691 | 725 | 921 | |
Of which: In Israel | 122 | 125 | 126 | 127 | 128 | 129 | 130 | 135 | |
Of which: In the West Bank and Gaza | 406 | 446 | 473 | 501 | 531 | 562 | 595 | 786 | |
Domestic employment growth, percent | … | 10 | 6 | 6 | 6 | 6 | 6 | 6 | |
Domestic employment growth, private sector, in percent2 | … | 10 | 7 | 7 | 7 | 7 | 7 | 7 | |
Scenario 2 - Baseline After Crisis | |||||||||
Labor force (thousands) | 599 | 626 | 653 | 682 | 712 | 743 | 776 | 963 | |
Unemployment rate 1 | 12 | 15 | 29 | 20 | 14 | 14 | 13 | 9 | |
Employment (thousands) | 529 | 532 | 463 | 549 | 611 | 643 | 677 | 879 | |
Of which: In Israel | 122 | 96 | 36 | 98 | 130 | 130 | 130 | 130 | |
Of which: In the West Bank and Gaza | 406 | 436 | 427 | 451 | 481 | 513 | 547 | 749 | |
Domestic employment growth, percent | … | 7 | -2 | 6 | 7 | 7 | 7 | 6 | |
Domestic employment growth, private sector, in percent2 | 6 | -4 | 7 | 8 | 8 | 8 | 8 | ||
Scenario 3–After Crisis, Lower Employment In Israel | |||||||||
Unemployment rate1 | 12 | 15 | 29 | 27 | 26 | 25 | 24 | 18 | |
Employment (thousands) | 529 | 532 | 463 | 496 | 526 | 558 | 592 | 794 | |
Of which: In Israel | 122 | 96 | 36 | 45 | 45 | 45 | 45 | 45 | |
Of which: In the West Bank and Gaza | 406 | 436 | 427 | 451 | 481 | 513 | 547 | 749 | |
Domestic employment growth, percent | … | 7 | -2 | 6 | 7 | 7 | 7 | 6 | |
Domestic employment growth, private sector, in percent2 | … | 6 | -4 | 7 | 8 | 8 | 8 | 8 | |
Scenario 4–Immigration | |||||||||
Labor force (thousands) | 599 | 626 | 673 | 715 | 758 | 804 | 852 | 1,123 | |
Unemployment rate1 | 12 | 15 | 29 | 20 | 14 | 14 | 13 | 9 | |
Employment (thousands) | 529 | 532 | 477 | 575 | 651 | 696 | 743 | 1,024 | |
Of which: In Israel | 122 | 96 | 36 | 98 | 130 | 130 | 130 | 130 | |
Of which: In the West Bank and Gaza | 406 | 436 | 441 | 477 | 521 | 566 | 613 | 894 | |
Domestic employment growth, percent | 7 | 1 | 8 | 9 | 9 | 8 | 8 | ||
Domestic employment growth, private sector, in percent2 | … | 6 | 1 | 9 | 11 | 10 | 10 | 9 |
Consists mostly of private sector but also local authorities and public enterprises (unless paid through the PA budget).
In percent of labor force, annual average.
Employment and Unemployment Scenarios, 1999–2010
1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2010 | ||
---|---|---|---|---|---|---|---|---|---|
Scenario 1—Baseline Before Crisis | |||||||||
Labor force (thousands) | 599 | 626 | 653 | 682 | 712 | 743 | 776 | 963 | |
Unemployment rate1 | 12 | 9 | 8 | 8 | 7 | 7 | 7 | 4 | |
Employment (thousands) | 529 | 571 | 599 | 628 | 659 | 691 | 725 | 921 | |
Of which: In Israel | 122 | 125 | 126 | 127 | 128 | 129 | 130 | 135 | |
Of which: In the West Bank and Gaza | 406 | 446 | 473 | 501 | 531 | 562 | 595 | 786 | |
Domestic employment growth, percent | … | 10 | 6 | 6 | 6 | 6 | 6 | 6 | |
Domestic employment growth, private sector, in percent2 | … | 10 | 7 | 7 | 7 | 7 | 7 | 7 | |
Scenario 2 - Baseline After Crisis | |||||||||
Labor force (thousands) | 599 | 626 | 653 | 682 | 712 | 743 | 776 | 963 | |
Unemployment rate 1 | 12 | 15 | 29 | 20 | 14 | 14 | 13 | 9 | |
Employment (thousands) | 529 | 532 | 463 | 549 | 611 | 643 | 677 | 879 | |
Of which: In Israel | 122 | 96 | 36 | 98 | 130 | 130 | 130 | 130 | |
Of which: In the West Bank and Gaza | 406 | 436 | 427 | 451 | 481 | 513 | 547 | 749 | |
Domestic employment growth, percent | … | 7 | -2 | 6 | 7 | 7 | 7 | 6 | |
Domestic employment growth, private sector, in percent2 | 6 | -4 | 7 | 8 | 8 | 8 | 8 | ||
Scenario 3–After Crisis, Lower Employment In Israel | |||||||||
Unemployment rate1 | 12 | 15 | 29 | 27 | 26 | 25 | 24 | 18 | |
Employment (thousands) | 529 | 532 | 463 | 496 | 526 | 558 | 592 | 794 | |
Of which: In Israel | 122 | 96 | 36 | 45 | 45 | 45 | 45 | 45 | |
Of which: In the West Bank and Gaza | 406 | 436 | 427 | 451 | 481 | 513 | 547 | 749 | |
Domestic employment growth, percent | … | 7 | -2 | 6 | 7 | 7 | 7 | 6 | |
Domestic employment growth, private sector, in percent2 | … | 6 | -4 | 7 | 8 | 8 | 8 | 8 | |
Scenario 4–Immigration | |||||||||
Labor force (thousands) | 599 | 626 | 673 | 715 | 758 | 804 | 852 | 1,123 | |
Unemployment rate1 | 12 | 15 | 29 | 20 | 14 | 14 | 13 | 9 | |
Employment (thousands) | 529 | 532 | 477 | 575 | 651 | 696 | 743 | 1,024 | |
Of which: In Israel | 122 | 96 | 36 | 98 | 130 | 130 | 130 | 130 | |
Of which: In the West Bank and Gaza | 406 | 436 | 441 | 477 | 521 | 566 | 613 | 894 | |
Domestic employment growth, percent | 7 | 1 | 8 | 9 | 9 | 8 | 8 | ||
Domestic employment growth, private sector, in percent2 | … | 6 | 1 | 9 | 11 | 10 | 10 | 9 |
Consists mostly of private sector but also local authorities and public enterprises (unless paid through the PA budget).
In percent of labor force, annual average.
The situation now is vastly more difficult, because the crisis that began in late September 2000 has led to a sharp increase in the unemployment rate. Before the crisis, roughly 130,000 Palestinians (20 percent of the labor force) commuted daily to work in Israel and the settlements; employment that was severely reduced with the closures in the fourth quarter of 2000. In addition, the output loss that occurred in the fourth quarter of 2000 led to a reduction in domestic employment. At the time of this publication, the extent of the output decline and the rise in unemployment remains highly uncertain (see Chapter 1), and for the purpose of this analysis it is assumed that the unemployment rate peaked at 35 percent in the first quarter of 2001. This rate of unemployment does not seem unrealistic, given that almost 20 percent of the Palestinian labor force lost their employment in Israel and given the sharp contraction in output in the fourth quarter of 2000. For 2001 and the medium term, it is an open question how many Palestinian workers will be allowed to return to work in Israel once the Conditions normalize, and the extent of recovery in Palestinian employment in Israel will greatly affect the outlook for Palestinian income, consumption, and unemployment over the coming years. The following scenarios are purely illustrative and should not be seen as projections.
Scenario 2 in Table 2.8 assumes that the number of Palestinians working in Israel recovers gradually to its pre-crisis level of 130,000, by the end of 2002. Palestinian domestic employment would then have to grow by 6.5 percent a year on average in 2001–10, in order to bring unemployment back to 8.8 percent by 2010, the level that prevailed before the crisis.29 With growth in PA employment limited to 3,000 a year (basically to meet the needs in priority sectors like education), employment growth in the Palestinian private sector would have to amount to as much as 7.6 percent a year on average, a formidable challenge for any economy. Put differently, employment in the private sector in 2010 would have to be almost twice as high as it was in 1999. This is not to say that it will take 10 years to bring down unemployment to its precrisis level. If Palestinian employment in Israel were to go back to 130,000 by the end of 2002, this would most likely be associated with a strong recovery in the economy and with a sharper reduction in unemployment in those years than what is shown in this scenario. But even if the 8.8 percent unemployment rate was achieved earlier than what is shown in Scenario 2, domestic employment growth would nevertheless have to average about 6.5 percent a year over the 10-year period to keep unemployment at that level.
Population Projections
Over the past couple of years, the Palestinian Central Bureau of Statistics (PCBS) has made major progress in establishing a population database for the West Bank and Gaza.1 In 1998, the PCBS published a survey of population, housing, and establishments that put the population in the West Bank and Gaza (excluding east Jerusalem) at around 2.7 million at the end of 1997 (PCBS, 1998c). In 1999, the PCBS published detailed population projections for 1997–2025 based on three different scenarios for fertility rates (PCBS, 1999). Common for the three scenarios were the assumptions of a fall in the infant mortality rate by 50 percent between 1997 and 2025 and the inflow of 500,000 immigrants to the West Bank and Gaza between 1997 and 2010 (and zero thereafter). The series differed only with respect to the assumption for the decline in the fertility rate from its level of around 6.1 in 1997. The low series assumed that it would drop to 2.1 by 2025, the medium series that it would fall to 3, and the high series that it would fall to 4.2. Thus, under the PCBS medium series, population growth would average 4.6 percent a year in 2000–10, and about 2.7 percent in 2011–2025.
The projections presented in this chapter are based on the PCBS’s medium scenario, but we assume net migration to be zero in our baseline scenario. This assumption is made simply to enhance the tractability of the demographic dynamics from the existing population. Under this scenario, population growth in the West Bank and Gaza is projected to average 3.4 percent in the period 2000–10 and 2.7 percent thereafter (Table 2.7). A migration scenario has also been developed that takes into account the migration flows projected by the PCBS in 2001–10. Under this scenario, population growth averages 4.7 percent a year in 2001–10 and 2.7 percent thereafter. It is assumed that the immigration and the existing population in the West Bank and Gaza would have similar age structure and age-gender specific labor force participation rates.
1 We are grateful for the assistance from Dr. Abu-Libdeh and his staff at the PCBS in preparing the population projections.Scenario 3 in Table 2.8 is more pessimistic and assumes that Palestinian employment in Israel, after reaching 45,000 by the end of 2001 (roughly the number of Palestinian workers with permits to work in Israel before the crisis), would remain at this level over the medium term. The domestic employment growth rates from Scenario 2 have been maintained, and the difference between the two scenarios is reflected entirely in unemployment. The difference here is purely arithmetic; the important demandside effects of Palestinian employment in Israel are not taken into account. The purpose of Scenario 3 simply to show that with Palestinian employment in Israel recovering to 45,000 and remaining at that level over the medium term, unemployment in the West Bank and Gaza would be almost 18 percent of the labor force in 2010, twice the level prevailing before the crisis and twice as high as in Scenario 2 Put differently, this would be the outcome even if the Palestinian economy were to achieve domestic employment growth at 6.5 percent, which is over twice the historical growth rate of the West Bank and Gaza. Another way to look at it is that in order to reduce the unemployment rate to 8.8 percent by 2010, with Palestinian employment in Israel limited to 45,0000, domestic Palestinian employment growth would have to average 7.7 percent a year on average in 2001–10, and domestic private sector employment growth would have to average 9 percent a year.30
For the sake of illustration, Scenarios 1, 2, and 3 all assume that employment in the PA will increase by 3,000 a year, which would seem enough to accommodate staffing demands in key sectors like education, health and the judiciary. The PA has expanded rapidly since its creation in 1994, and in recent years (certainly since 1997) the expansion in public employment has become excessive, beyond what can reasonably be justified on the grounds that the PA has increased the range or quality of its services and responsibilities (see Chapter 1). In fact, the burgeoning wage bill is now a major fiscal concern since it is crowding out other important expenditure, notably in the areas of health, education, and infrastructure, making it exceedingly difficult for the PA to ensure adequate remuneration of its staff. Bringing PA hiring under control is therefore a key policy priority for the coming years.31
The challenge to create domestic employment over the coming years should not be misinterpreted as if further PA employment growth might be needed to absorb some of the labor inflows and to help reduce unemployment. As later discussion will show, while continued large-scale hiring by the PA might provide some very short-term, temporary relief, it will cause considerable damage to the long-term growth prospects of the Palestinian economy. A continued rapid expansion of the PA wage bill will make it impossible for the PA to allocate sufficient resources to nonwage expenditures in the areas of health, education, and infrastructure—areas where international evidence shows that public expenditure can help bolster long term economic growth and development.
Immigration
The population of the West Bank and Gaza was around 2.7 million in 1999, or roughly 3 million if the Palestinians living in east Jerusalem are included. In addition, there are approximately 2.3 million Palestinian refugees (stemming from the 1948 war) living in Jordan, Lebanon, and Syria.1 To this should be added the large number of Palestinians displaced following the 1967 war. Many Palestinians also live outside the West Bank and Gaza without being classified as refugees or displaced persons. It remains an open question how many would be able and want to migrate to the West Bank and Gaza following a final status agreement with Israel. PCBS (1999) assumes that total net immigration in the period 1997–2010 would amount to 500,000 people, with 45,000 people annually coming in 2001–10.
An exogenous increase in immigration obviously boosts population growth, but its demographic impact is different from, say, an acceleration in population growth caused by a rise in fertility or a drop in infant mortality. In the latter cases, the impact on labor supply would be lagged, whereas with immigration it is instantaneous. The PCBS assumes that the age structure of the immigrants is the same as, or very similar to, the age composition of the population already living in the West Bank and Gaza. The immigration assumed in the PCBS’s projection would thus lead to higher population growth across all ages while leaving the age structure basically unchanged from our projection. Therefore, the macroeconomic analysis in this chapter of a changing age structure still holds, but in some respects, the projected effects would be more pronounced. For example, labor supply growth would be stronger as would the demand for health and education services. An increase in the labor supply due to an inflow of Palestinians from abroad would, as a first order effect, reduce the capital/labor ratio, thereby increasing the return on capital and lowering the return on labor. Further, and also in line with neoclassical theory, real interest rates would rise, and real wages would fall. Cohen and Hsieh (2000) find that this is also what happened in Israel in the early 1990s following the very large Russian immigration. Average effective wages of native Israelis declined by 20 percent and real interest rates rose sharply during the peak of Russian immigration in 1990–91. After this initial impact, the rise in real interest rates led to an investment boom largely financed by external borrowing. The capital/labor ratio recovered, and by 1997 real wages and interest rates had returned to their pre-immigration levels. Brezis and Krugman (1996) argue that with an endogenous investment response and increasing returns in the economy, the long run impact of immigration will often be higher rather than lower real wages.
1 The number comes from UNRWA and includes refugees that do not live in refugee campsFinally, over the medium term, the West Bank and Gaza could experience large inflows of Palestinians from abroad, including refugees, especially after a final status agreement with Israel. Immigration would lead to a step-increase in the population across all ages, without (necessarily) affecting the age structure, and would lead to an outward shift in the labor supply curve. For 2001–10, PCBS (1999) assumes that net immigration would amount to 45,000 people per year (Box 2.1). A full analysis of the effects from possible migration is beyond the purpose of this chapter, but Box 2.2 discusses the issues involved. Scenario 4 in Table 2.8 shows that with such immigration, and with a target of reducing the unemployment rate to 8.8 percent by 2010 and further assuming that Palestinian employment in Israel goes back to 130,000 by the end of 2002 (like Scenario 2), the required annual rate of domestic employment growth would be 8.2 percent.32
Required TFP Growth Over the Next Ten Years
What does it take to generate domestic employment growth of 6.5 percent a year (Scenario 2 in the previous section) without a reduction in real wages, or even at rising real wages? Indeed, real wage growth over the medium term is important in order to raise the standard of living. This section uses the growth accounting framework presented earlier to compute the required growth rates for TFP (and real GDP) over the coming 10 years to achieve such annual employment growth under various assumptions for the real wage. For this exercise, it is useful to rewrite equation (2) above as:
or
where yt – lt represents labor productivity growth, which is assumed to equal real wage growth, wt; in other words, workers are paid the value of their marginal product.33 Admittedly, this assumption does not necessarily hold in the short run and the exercise should be seen as an attempt to illustrate the magnitudes involved and to identify some of the tradeoffs that policymakers will face between employment expansion and increases in investment and TFP growth. One main attraction of this alternative formulation of the growth accounting equation is that it regards TFP growth, much like factor accumulation, as an endogenous variable and subject to policy influences and policy analysis.
The required TFP (and GDP) growth rates are computed for three scenarios for the real wage (keeping investment constant as a share of GDP at its 1999 level in all scenarios): zero real wage growth (the low growth scenario), 1.5 percent annual increase (the medium-growth scenario), and 3 percent annual increase (the high growth scenario). The results, which are summarized in Table 2.9, show that, in order to reduce unemployment to 8.8 percent by 2010 while allowing real wages to increase by 1.5 percent a year, the Palestinian economy would have to generate real GDP and TFP growth rates of 8 and 1.2 percent a year, respectively.
Scenarios for Growth in Total Factor Productivity and Real GDP, 2001–10
(Average annual percent)
Under the migration scenario, population growth in 2001–10 is 600,000 higher than in the scenario without migration.
Scenarios for Growth in Total Factor Productivity and Real GDP, 2001–10
(Average annual percent)
Real Wage Growth Scenarios | Zero Migration | Migration1 | Memorandum Items: | ||
---|---|---|---|---|---|
TFP | Real GDP | TFP | Real GDP | Investment/GDP (%) | |
Low (0% real wage growth) | -0.1 | 6.5 | 0.3 | 8.2 | 34 |
Medium (1.5% real wage growth) | 1.2 | 8.0 | 1.5 | 9.7 | 34 |
High (3% real wage growth) | 2.5 | 9.5 | 2.8 | 11.2 | 34 |
Under the migration scenario, population growth in 2001–10 is 600,000 higher than in the scenario without migration.
Scenarios for Growth in Total Factor Productivity and Real GDP, 2001–10
(Average annual percent)
Real Wage Growth Scenarios | Zero Migration | Migration1 | Memorandum Items: | ||
---|---|---|---|---|---|
TFP | Real GDP | TFP | Real GDP | Investment/GDP (%) | |
Low (0% real wage growth) | -0.1 | 6.5 | 0.3 | 8.2 | 34 |
Medium (1.5% real wage growth) | 1.2 | 8.0 | 1.5 | 9.7 | 34 |
High (3% real wage growth) | 2.5 | 9.5 | 2.8 | 11.2 | 34 |
Under the migration scenario, population growth in 2001–10 is 600,000 higher than in the scenario without migration.
The required rates of growth in TFP and GDP have also been computed for the case in which the West Bank and Gaza experience large-scale immigration in 2001–10 (Scenario 4 in Table 2.8.) As discussed above, under this scenario, domestic Palestinian employment growth would need to exceed 8 percent a year in order to bring unemployment down to 8.8 percent in 2010 and the required annual real GDP and TFP growth rates would be 9.7 and 1.5 percent under the assumption of real wages increasing by 1.5 percent a year.
A couple of points deserve mentioning. It is clear that strong growth in GDP, TFP, and capital accumulation will be needed for the next ten years in order to generate employment growth at a rate that allows a significant reduction in the unemployment rate without causing compression in real wages. This finding holds for all the scenarios in Table 2.9 with positive real wage growth and for either of the two migration scenarios.34 Naturally, the highest required TFP growth (2.8 percent annual increase) occurs under the scenario with 3 percent annual real wage growth and with migration; the required TFP growth rate is approximately twice as high as the TFP growth the West Bank and Gaza experienced on average over the past 30 years. At the same time, it is essentially the same as the average TFP growth recorded in the 1970s and the 1980s (Table 2.1), and should there be a sustainable improvement in the regional political climate, there is no reason why the West Bank and Gaza should not be able to generate such growth rates again. Furthermore, the required growth rate in the capital stock ranges from 6.7 to 8.9 percent a year, which is high but not astronomic compared with the historical average of 7.2 percent. Finally, it is clear that high and sustained TFP growth would raise the standards of living as measured by real per capita GDP. Over the next 10 years, annual growth in real per capita GDP would range from 3.1 to 6.6 percent.
The key policy issue for the PA is to create conditions for the Palestinian economy to generate high TFP and GDP growth and capital accumulation on a sustained basis over the next ten years. The main factors that affect long-term real GDP growth are examined in the following section.
Factors for Long-Term Growth of the Palestinian Economy
This section undertakes a cross-country growth regression to gain insights into the long-term (ultimate) growth factors, as shown in figure 2.1.
A Model of Growth
A majority of the empirical work on cross-country growth builds on the extended neoclassical growth model as specified in Barro and Sala-ì-Martin (1995), which can be summarized by the following relationship:
where Dyt the growth rate of real per capita output in period t, is a function of yt–1 the initial level of real per capita output, and yt*, the long-run or steady-state level of real per capita output. In the neoclassical model, the assumption of diminishing returns to (actors of production implies that Dyt is inversely related to the initial level of real per capita output. In the above framework, this property implies a negative relationship between growth of real per capita output and initial level of real per capita output, conditional on values of yt*. This inverse relationship is known as conditional convergence. Another property of the above model is that the growth rate, Dyt rises with yt*, for a given value of yt–1. The value yt* is determined by, among other things, government policies, institutions, and demographic factors. Improvement in these factors can increase the growth rate of per capita output in the transition to the new steady-state level of income and permanently raise the level of real per capita output. During the transition, however, diminishing returns will eventually set in, and output growth will slow down to a rate that is consistent with the exogenous rate of technological progress.
The empirical literature on long-term economic growth has found that the transitional dynamics can be rather lengthy, and, consequently, the impact of government policies, the quality of institutions, and the demographic factors on growth can be persistent. This literature has also found evidence of conditional convergence whereby poorer countries tend to grow faster than richer countries for given values of government policies, institutions, and demographic factors as well as evidence of absolute divergence whereby growth differentials persist without controlling for differences in policies, institutions, and other factors.35 One important implication of conditional convergence is that growth rate differentials between poor and rich countries can persist so long as richer countries are endowed with better policies, better institutions, and a more favorable demographic structure.36
In the empirical analysis of growth, the above model is used in a cross-country regression analysis. Growth is specified as a function of a set of initial conditions, various measures of geographic location, macroeconomic policies, financial depth, infrastructure, demographic variables, and quality of institutions and governance.
Economic growth is measured by growth in real per capita GDP and is cast in purchasing power parity (PPP) terms. Initial conditions consist of: the level of real per capita GDP (also in PPP terms); the level of schooling (both measured at the start of the sample period (1970)); and dummies for whether a country is landlocked, located in the tropical parts of the world, or endowed with natural resources. The indicators to capture the macroeconomic environment and polices consist of inflation, volatility of inflation, budget surplus, the ratio of broad money (M2) to GDP (a commonly used measure of financial development), and the degree of openness to foreign trade measured by the ratio of trade (exports plus imports) to GDP. 37 The measure of infrastructure used in the regression is the number of connected telephone lines per worker, with a higher value expected to be associated with higher growth.
Two demographic variables are included in the regression as well: growth in total population and growth in the working-age population. Earlier empirical studies of growth included only total population growth (see Levine and Renelt, 1992), and therefore assumed away any role for the age structure of the population and productivity differentials among individuals with different age and labor market experiences.38 As discussed in the introduction, studies have generally found growth in the working-age population to have a positive impact on per capita GDP growth and population growth to have a negative impact once an allowance is made for growth in working-age population.39
Finally, the degree of regulatory burden is used as a measure of the quality of institutions and governance (see Box 2.3). Unlike the previous variables, this indicator is subjective and is based on public and private individuals’ perception of the burden of regulations and delays involved in government bureaucracy in its dealings with the private sector red tape. A higher value of this indicator can be interpreted as a higher cost of doing business in a country. There are many other indicators of governance that measure various aspects of political, legal, and economic institutions. These indicators generally produce similar findings.40
The Regression Results
The objective of the regression analysis in this section is to ascertain to what degree policies, institutions, and demographic factors can account for the growth performance of the Palestinian economy over the last 30 years, so as to set the stage for the forward-looking policy discussion in the next section. A careful attempt has been made to put together time-series data for the West Bank and Gaza that are internally consistent and consistent with data from other countries. As is the case with all cross-country analyses, however, such consistency is far from perfect (see Appendix I for a description of the data). The regressions are estimated over the period 1970–99 and include 85 countries. Except for the data on the initial conditions, which are either time invariant (for example, the geography variables) or refer to the value of a variable at the beginning of the sample period, data are averages for 1970–99. Thus, each country is represented by one observation in the regression.
Table 2.10 reports the regression results for various specifications of the model. The results are consistent with the hypothesis that countries with high per capita GDP growth tend to have a low initial income level and a high level of schooling, be open to trade, have a low population growth rate and a high working-age population growth rate, have small fiscal deficits, low inflation, and low inflation volatility, a high number of telephones per worker, a low burden of regulations, and a high ratio of M2 to GDP. These countries also are typically not landlocked, nor are they located in areas with a tropical climate. Lastly, they are generally not endowed with rich natural resources. These findings are consistent with studies of growth that use different countries, sample periods, variables, and estimation techniques. Except for one or two variables, depending on the specification, all variables in the regressions are statistically significant at conventional statistical levels. The variables taken together account for about 68 percent of the variation in growth rates across countries, and this conforms favorably with other growth studies.41
Determinants of Real Per Capita GDP Growth, 1970–99
Growth In working age population minus growth in the total population in 1970–99.
Multiplied by 100.
Test of the null hypothesis that the coefficient on growth in total population equals the negative of the coefficient on growth in working age population.
Determinants of Real Per Capita GDP Growth, 1970–99
Independent variables | (1) | (2) | (3) | (4) | ||||
---|---|---|---|---|---|---|---|---|
Constant | 0.110 | *** | 0.121 | *** | 0.111 | *** | 0.121 | *** |
(7.093) | (7.82) | (7.207) | (7.806) | |||||
Log of real per capita GDP in 1970 | -0.014 | *** | -0.014 | *** | -0.014 | *** | -0.014 | *** |
(–6.914) | (–7.477) | (–7.006) | (–7.374) | |||||
Log of years of schooling in 1970 | 0.003 | ** | 0.002 | 0.004 | * | 0.002 | ||
(1.832) | (1.352) | (1.864) | (1.375) | |||||
Openness | 0.007 | ** | 0.008 | *** | 0.007 | *** | 0.008 | *** |
(2.337) | (2.791) | (2.509) | (2.881) | |||||
Growth in total population | -2.624 | *** | -2.550 | *** | ||||
(–6.352) | (–5.966) | |||||||
Growth in working age population | 2.293 | *** | 2.243 | *** | ||||
(5.910) | (5.688) | |||||||
Differences in population growth1 | 2.201 | *** | 2150 | *** | ||||
(5.436) | (5.262) | |||||||
Budget surplus | 0.064 | 0.058 | 0.063 | 0.058 | ||||
(1.536) | (1.407) | (1.565) | (1.430) | |||||
Inflation | -0.010 | ** | -0.008 | |||||
(–1.998) | (–1.487) | |||||||
Standard deviation of inflation | -0.011 | *** | -0.008 | ** | ||||
(–2,951) | (–2.001) | |||||||
Telephones per worker2 | 0.012 | *** | 0.011 | *** | 0.013 | *** | 0.012 | *** |
(3.526) | (3.347) | (3.704) | (3.402) | |||||
Landlock dummy | -0.006 | * | -0.006 | -0.006 | -0.006 | |||
(–1.630) | (–1.511) | (–1.583) | (–1.486) | |||||
Tropics dummy | -0.010 | *** | -0.010 | *** | -0.009 | *** | -0.010 | *** |
(–3.741) | (–3.814) | (–3.572) | (–3.642) | |||||
Natural resource abundance dummy | -0.016 | *** | -0.012 | *** | -0.015 | *** | -0.012 | ** |
(–3.098) | (–2.380) | (–3.099) | (–2.393) | |||||
Regulatory burden | -0.008 | *** | -0.007 | *** | -0.008 | ** | -0.007 | *** |
(–2.964) | (–2.544) | (–2.939) | (–2.541) | |||||
M2 to GDP ratio | 0.005 | 0.004 | 0.006 | * | 0.004 | |||
(1.542) | (1.218) | (1.769) | (1.393) | |||||
Adjusted R-squared | 0.680 | 0.690 | 0.684 | 0.691 | ||||
Number of observations | 85 | 85 | 85 | 85 | ||||
Prob (F-statistic)3 | 0.08 | 0.11 |
Growth In working age population minus growth in the total population in 1970–99.
Multiplied by 100.
Test of the null hypothesis that the coefficient on growth in total population equals the negative of the coefficient on growth in working age population.
Determinants of Real Per Capita GDP Growth, 1970–99
Independent variables | (1) | (2) | (3) | (4) | ||||
---|---|---|---|---|---|---|---|---|
Constant | 0.110 | *** | 0.121 | *** | 0.111 | *** | 0.121 | *** |
(7.093) | (7.82) | (7.207) | (7.806) | |||||
Log of real per capita GDP in 1970 | -0.014 | *** | -0.014 | *** | -0.014 | *** | -0.014 | *** |
(–6.914) | (–7.477) | (–7.006) | (–7.374) | |||||
Log of years of schooling in 1970 | 0.003 | ** | 0.002 | 0.004 | * | 0.002 | ||
(1.832) | (1.352) | (1.864) | (1.375) | |||||
Openness | 0.007 | ** | 0.008 | *** | 0.007 | *** | 0.008 | *** |
(2.337) | (2.791) | (2.509) | (2.881) | |||||
Growth in total population | -2.624 | *** | -2.550 | *** | ||||
(–6.352) | (–5.966) | |||||||
Growth in working age population | 2.293 | *** | 2.243 | *** | ||||
(5.910) | (5.688) | |||||||
Differences in population growth1 | 2.201 | *** | 2150 | *** | ||||
(5.436) | (5.262) | |||||||
Budget surplus | 0.064 | 0.058 | 0.063 | 0.058 | ||||
(1.536) | (1.407) | (1.565) | (1.430) | |||||
Inflation | -0.010 | ** | -0.008 | |||||
(–1.998) | (–1.487) | |||||||
Standard deviation of inflation | -0.011 | *** | -0.008 | ** | ||||
(–2,951) | (–2.001) | |||||||
Telephones per worker2 | 0.012 | *** | 0.011 | *** | 0.013 | *** | 0.012 | *** |
(3.526) | (3.347) | (3.704) | (3.402) | |||||
Landlock dummy | -0.006 | * | -0.006 | -0.006 | -0.006 | |||
(–1.630) | (–1.511) | (–1.583) | (–1.486) | |||||
Tropics dummy | -0.010 | *** | -0.010 | *** | -0.009 | *** | -0.010 | *** |
(–3.741) | (–3.814) | (–3.572) | (–3.642) | |||||
Natural resource abundance dummy | -0.016 | *** | -0.012 | *** | -0.015 | *** | -0.012 | ** |
(–3.098) | (–2.380) | (–3.099) | (–2.393) | |||||
Regulatory burden | -0.008 | *** | -0.007 | *** | -0.008 | ** | -0.007 | *** |
(–2.964) | (–2.544) | (–2.939) | (–2.541) | |||||
M2 to GDP ratio | 0.005 | 0.004 | 0.006 | * | 0.004 | |||
(1.542) | (1.218) | (1.769) | (1.393) | |||||
Adjusted R-squared | 0.680 | 0.690 | 0.684 | 0.691 | ||||
Number of observations | 85 | 85 | 85 | 85 | ||||
Prob (F-statistic)3 | 0.08 | 0.11 |
Growth In working age population minus growth in the total population in 1970–99.
Multiplied by 100.
Test of the null hypothesis that the coefficient on growth in total population equals the negative of the coefficient on growth in working age population.
The Quality of the Institutional Framework and Economic Growth
There is ample international evidence that the quality of the institutional framework—the legal and regulatory framework, judiciary system, policy institutions, economic governance, and other public policies and institutions that affect incentives in the economy—has profound implications for the country’s long-term growth prospects. Hall and Jones (1999) note that while governments are usually the most efficient provider of an institutional framework that protects property rights, in practice they are often a primary agent of diversion through expropriation, confiscation, and corruption.1 Government policy also might unintentionally contribute to corruption and rent-seeking activities if it provides for a high degree of bureaucratic discretion in the application of regulations. The scope for rent-seeking activities and corruption is larger the more prevalent are trade and business regulations and government subsidies (including protection of certain industries), and a bloated civil service with low wages tends to be more corrupt than a small cadre of relatively well paid civil servants (see, for example, Van Rijckeghem and Weder, 1997).
The mechanism through which the institutional framework affects economic development can be summarized as follows (drawing on Bates, 1996, and Caballero and Hammour, 2000). People save to form capital, and capital is central to the process of economic development. The prospects of future rewards motivate current sacrifices (saving), but such rewards are uncertain. One of the risks is nonperformance. Another risk is opportunistic actions by other people, including the government, which, because of its monopoly power, can attract talented individuals away from productive activities (Murphy, Shleifer, and Vishny, 1991). Faced with such risks, individuals may fail to save and make investments that would render them, and indeed all people, better off in the future. A strong, market-oriented institutional framework, with an independent judiciary that upholds laws and regulations, together with sound governance can significantly reduce such uncertainty and thereby support private investment. The quality of the institutional framework thus determines the degree to which the private sector will want to engage in productive activities and long-term investments as opposed to rent seeking and other directly unproductive activities. In contrast, a weak institutional framework lowers the return on capital and thereby also total factor productivity and the investment in productive capital. In an environment of weak governance and ineffective protection of property rights, people would rather engage in short-term commercial transactions, which are less risky since they are largely reversible, than in transactions relating to long-term investment projects that are largely irreversible.2 The macroeconomic symptoms of a weak institutional framework include reduced cooperation (as described above), unemployment, market segmentation, and weak technological development.3
1 See also Tanzi and Davoodi (1998). 2 Data on the investment and the composition and level of hank credit—with little credit to long-term investment—suggest that this description might apply to the Palestinian economy. 3 Concerns over the legal and regulatory framework and governance deter private investors but can also have adverse effects on public investment (Isham and Kaufmann, 1999).Conditional convergence holds across all specifications. The magnitude of the coefficient on initial income suggests a convergence rate of about 1.4 percent per year, about half of what Barro and Sala-ì-Martin (1995) find using Summers-Heston data on level and growth of real per capita GDP, but it coincides exactly with their estimated convergence rate when World Bank constant U.S. dollar data are used; the latter data are closer in their construction to the data used in the regressions in Table 2.10.42 The coefficients on initial schooling show that additional two years of schooling (within one standard deviation of the sample average) on average is associated with an increase in the growth rate of between 0.1 and 0.2 percentage points a year.43
With respect to the demographic variables, the regression includes the difference in growth rate between the working-age population and total population as an explanatory variable, rather than the two variables separately (Table 2.10, columns 1 and 3).44 The results (Table 2.10, columns 1 and 3) show that 1 percentage point higher growth in the workingage population than in total population is associated with higher real per capita GDP growth by around 2.2 percentage points a year.45 This result, which is close to those found in other studies, implies that the demographic transition the West Bank and Gaza is projected to undergo over the medium term can be expected to contribute to a higher growth rate in per capita GDP of between 1.1 and 1.5 percentage points a year between 2005 and 2010 and almost 2 percentage points by 2025. Of course, other factors can reinforce or reduce the contribution from demographic dynamics.
The estimated impact of trade, defined as the ratio of trade to GDP, and referred to as openness in Table 2.10, shows that a 20 percentage point increase in the trade to GDP ratio (one-half the standard deviation increase in this variable) is associated with a higher real per capita GDP growth rate of about 0.1 percentage points per year. This is still low compared with findings in some other studies. For example, Sachs and Warner (1997) use a more complex measure of openness, which, among other things, takes into account the importance of trade monopolies, quotas, and tariff levels, and finds trade to be the single most important factor determining differences in economic growth across countries.
With respect to the macroeconomic variables, the regression results show that an improvement in the fiscal balance by 3 percentage points of GDP, which is within one standard deviation, is associated with an increase in annual real per capita GDP growth by 0.2 percentage points, while an increase of 10 percentage points in the inflation rate is associated with 0.1 percentage points lower annual per capita GDP growth.46 Furthermore, an increase in inflation volatility of 16 percentage points, which is about the average for the sample of 85 countries and within one standard deviation of the volatility measure, is associated with a 0.2 percentage point reduction in annual per capita GDP growth.47
As regards the impact of the legal and regulatory framework, a higher regulatory burden equal to an increase of one unit on a scale of–2.5 to 2.5 is associated with a 0.8 percentage point reduction in average annual real per capita GDP growth.
Furthermore, the estimated coefficient on the dummy variable for landlocked countries—a proxy for the cost of conducting trade—implies that real GDP per capita growth in landlocked countries, on average, was lower by 0.6 percentage points. The West Bank and Gaza can be considered landlocked even though it is situated at the sea, because it does not have direct access to port facilities and has to rely on the Israeli ports in Ashdod and Haifa. The infrastructure variable is also very important and highly significant statistically. An increase of 10 connected telephone mainlines per worker per year (well within one standard deviation of the sample average) is associated with higher per capita real GDP growth of 0.1 percentage points a year. The estimated coefficient on the ratio of M2 to GDP shows that a 25 percent increase in the stock of M2 relative to GDP (well within one standard deviation of the sample average) is associated with a 0.1 percentage point increase in annual per capita GDP growth. Finally, the estimated coefficients on the dummies for tropical climate and the availability of natural resources show that countries located in the tropical climate zones have on average a growth rate that is lower by 1 percentage point a year, while those endowed with natural resources actually grow at a lower rate of 1.5 percent per year.48
How does the West Bank and Gaza’s growth performance compare with that of other economies? Table 2.11 attempts to answer this question by looking at growth differentials between the West Bank and Gaza and some comparator economies but with a focus on 1995–99 rather than the past 30 years. More detailed data for the West Bank and Gaza are available for the recent period, for example, on macroeconomic variables and some structural variables.49 Several results are noteworthy. First, per capita GDP growth in the West Bank and Gaza in 1995–99 was significantly lower than in all of the comparators in Table 2.11 (top line). Second, on the basis of the variables included in the regression, the West Bank and Gaza could have been expected to grow considerably faster than these comparators. Recall from the previous section that the growth performance of the Palestinian economy over the past 30 years compared very well with the performance of other economies, except for the period since 1994. The regression results suggest that the poor growth performance in 1995–99 cannot be attributed to the fundamental economic factors included in the regression; rather, the difference is entirely accounted for by the residual. The poor growth performance in 1995–99 is primarily due to the output collapse in 1995 and 1996, a period when the Palestinian economy was subject to extensive closures.50 Finally, the regression results show that the convergence effect was positive and large for the West Bank and Gaza (due to its lower initial income) and that the West Bank and Gaza also scored well with respect to schooling and openness. The landlocked variable and, more importantly, the demographic variable, were negative and large, however, meaning that in other economies, such as those of MENA and East Asia—that are further along their demographic transition than West Bank and Gaza—the working-age population relative to total population grew faster than in the West Bank and Gaza (where the ratio did not change much). The demographic variable accounted for about 75 percent of the growth differential between the West Bank and Gaza and MENA, about 50 percent vis-à-vis lower middle income countries and 30 percent vis-à-vis East Asia.
Decomposition of Growth Differential Between the West Bank and Gaza and Various Benchmarks, 1995–991
(Annual percent)
Based on regression (1) in Table 2.10, and data for the period 1995–99.
Excludes the West Bank and Gaza.
Defined as the West Bank and Gaza’s growth rate minus the growth rate of the relevant group.
Defined as actual minus predicted growth rates.
Decomposition of Growth Differential Between the West Bank and Gaza and Various Benchmarks, 1995–991
(Annual percent)
Middle East and North Africa2 | East Asia | Lower Middle-Income Countries | Upper Middle-Income Countries | High-Income OECD Countries | World | ||
---|---|---|---|---|---|---|---|
Actual growth differential3 | -3.20 | -2.79 | -3.44 | -4.84 | -5.00 | -4.25 | |
Predicted growth differential3 due to: | -0.01 | 0.05 | -0.12 | 0.44 | 0.98 | 0.52 | |
Log of real per capita GDP in 1995 | 2.19 | 2.14 | 1.38 | 2.45 | 3.70 | 1.77 | |
Log of years of schooling in 1995 | 0.16 | 0.12 | 0.17 | 0.09 | -0.01 | 0.18 | |
Openness | 0.13 | -0.24 | 0.17 | 0.14 | 0.26 | 0.19 | |
Differences in population growth | -2.45 | -0.86 | -1.78 | -1.32 | 0.02 | -1.08 | |
Budget surplus | -0.43 | -0.55 | -0.33 | -0.36 | -0.39 | -0.34 | |
Inflation | -0.02 | 0.00 | 0.03 | 0.06 | -0.06 | 0.01 | |
Telephones per worker | 0.31 | -0.18 | 0.28 | -0.30 | -0.99 | 0.09 | |
Landlock dummy | -0.64 | -0.64 | -0.52 | -0.56 | -0.58 | -0.52 | |
Tropics dummy | 0.00 | 0.98 | 0.54 | 0.52 | 0.00 | 0.48 | |
Natural resource abundance dummy | 0.78 | 0.00 | 0.16 | 0.31 | 0.00 | 0.11 | |
Regulatory burden | 0.03 | -0.53 | -0.25 | -0.58 | -0.84 | -0.36 | |
M2 to GDP ratio | -0.07 | -0.19 | 0.03 | -0.01 | -0.11 | 0.00 | |
Residual4 | 3.19 | -2.84 | -3.32 | -5.29 | -5.98 | -4.77 |
Based on regression (1) in Table 2.10, and data for the period 1995–99.
Excludes the West Bank and Gaza.
Defined as the West Bank and Gaza’s growth rate minus the growth rate of the relevant group.
Defined as actual minus predicted growth rates.
Decomposition of Growth Differential Between the West Bank and Gaza and Various Benchmarks, 1995–991
(Annual percent)
Middle East and North Africa2 | East Asia | Lower Middle-Income Countries | Upper Middle-Income Countries | High-Income OECD Countries | World | ||
---|---|---|---|---|---|---|---|
Actual growth differential3 | -3.20 | -2.79 | -3.44 | -4.84 | -5.00 | -4.25 | |
Predicted growth differential3 due to: | -0.01 | 0.05 | -0.12 | 0.44 | 0.98 | 0.52 | |
Log of real per capita GDP in 1995 | 2.19 | 2.14 | 1.38 | 2.45 | 3.70 | 1.77 | |
Log of years of schooling in 1995 | 0.16 | 0.12 | 0.17 | 0.09 | -0.01 | 0.18 | |
Openness | 0.13 | -0.24 | 0.17 | 0.14 | 0.26 | 0.19 | |
Differences in population growth | -2.45 | -0.86 | -1.78 | -1.32 | 0.02 | -1.08 | |
Budget surplus | -0.43 | -0.55 | -0.33 | -0.36 | -0.39 | -0.34 | |
Inflation | -0.02 | 0.00 | 0.03 | 0.06 | -0.06 | 0.01 | |
Telephones per worker | 0.31 | -0.18 | 0.28 | -0.30 | -0.99 | 0.09 | |
Landlock dummy | -0.64 | -0.64 | -0.52 | -0.56 | -0.58 | -0.52 | |
Tropics dummy | 0.00 | 0.98 | 0.54 | 0.52 | 0.00 | 0.48 | |
Natural resource abundance dummy | 0.78 | 0.00 | 0.16 | 0.31 | 0.00 | 0.11 | |
Regulatory burden | 0.03 | -0.53 | -0.25 | -0.58 | -0.84 | -0.36 | |
M2 to GDP ratio | -0.07 | -0.19 | 0.03 | -0.01 | -0.11 | 0.00 | |
Residual4 | 3.19 | -2.84 | -3.32 | -5.29 | -5.98 | -4.77 |
Based on regression (1) in Table 2.10, and data for the period 1995–99.
Excludes the West Bank and Gaza.
Defined as the West Bank and Gaza’s growth rate minus the growth rate of the relevant group.
Defined as actual minus predicted growth rates.
How does the regression fare in explaining the Palestinian economy’s performance in 1995–99? Table 2.12 compares actual and predicted growth in the West Bank and Gaza, as well as in some comparator economies. The model—which can explain a large share of cross-country growth differences—predicted the real per capita GDP growth in the West Bank and Gaza to average 2.9 percent a year in 1995–99, with the most important positive contribution coming from the convergence effect, the level of schooling, the expansion in the telephone network (or physical infrastructure more generally), the increase in trade to GDP, and the expansion in the banking system. The governance variable (regulatory burden) and the size of the fiscal deficit reduced the predicted growth rate; the demographic factor was not important in 1995–99 because the working-age population and total population grew at about the same rate.51 Instead of growing as predicted by the model, however, real per capita GDP declined by 2.5 percent per year on average in 1995–99. The Palestinian economy underperformed by a margin of 5.5 percentage points. The difference between predicted and actual growth rates is likely to reflect many things, including problems in making inferences for one economy based on cross-country regressions and weaknesses in the data, but it also reflects the importance of the negative shock the Palestinian economy experienced in 1995–96—when it was subject to prolonged and extensive closures because of a deterioration in the security situation, and the overall impediments to growth caused by a high degree of uncertainty and high transactions costs in 1995–99.
Actual Versus Predicted Growth in the West Bank and Gaza and Selected Regions, 1995–991
(Annual percent)
Based on regression (1) in Table 2.10.
Excludes the West Bank and Gaza.
Includes constant of the regression.
Defined as actual minus predicted growth rates.
Actual Versus Predicted Growth in the West Bank and Gaza and Selected Regions, 1995–991
(Annual percent)
West Sank and Gaza | Middle East and North Africa2 | East Asia | Lower Middle-Income Countries | Upper Middle-Income Countries | High-Income OECD Countries | World | |||
---|---|---|---|---|---|---|---|---|---|
Actual growth | -2.5 | 0.7 | 0.3 | 0.9 | 2.3 | 2.5 | 1.7 | ||
Predicted growth3 | 2.9 | 2.9 | 2.9 | 3.1 | 2.5 | 2.0 | 2.4 | ||
due to: | |||||||||
Log of real per capita GDP in 19953 | 1.1 | -1.1 | -1.0 | -0.3 | -1.4 | -2.6 | -0.7 | ||
Log of years of schooling in 1995 | 0.8 | 0.6 | 0.6 | 0.6 | 0.7 | 0.8 | 0.6 | ||
Openness | 0.6 | 0.5 | 0.8 | 0.4 | 0.4 | 0.3 | 0.4 | ||
Differences in population growth | 0.1 | 2.5 | 0.9 | 1.8 | 1.4 | 0.0 | l.1 | ||
Budget surplus | -0.5 | -0.1 | 0.1 | -0.2 | -0.1 | -0.1 | -0.2 | ||
Inflation | -0.1 | -0.1 | -0.1 | -0.1 | -0.1 | 0.0 | -0.1 | ||
Telephones per worker | 1.5 | 1.2 | 1.7 | 1.2 | 1.8 | 2.5 | 1.4 | ||
Land lock dummy | -0.6 | 0.0 | 0.0 | -0.1 | -0.1 | -0.1 | -0.1 | ||
Tropics dummy | 0.0 | 0.0 | -1.0 | -0.5 | -0.5 | 0.0 | -0.5 | ||
Natural resource abundance dummy | 0.0 | -0.8 | 0.0 | -0.2 | -0.3 | 0.0 | -0.1 | ||
Regulatory burden | -0.1 | -0.2 | 0.4 | 0.1 | 0.5 | 0.7 | 0.2 | ||
M2 to GDP ratio | 0.3 | 0.3 | 0.5 | 0.2 | 0.3 | 0.4 | 0.3 | ||
Residual4 | -5.47 | -2.3 | -2.6 | -2.2 | -0.2 | 0.5 | -0.7 |
Based on regression (1) in Table 2.10.
Excludes the West Bank and Gaza.
Includes constant of the regression.
Defined as actual minus predicted growth rates.
Actual Versus Predicted Growth in the West Bank and Gaza and Selected Regions, 1995–991
(Annual percent)
West Sank and Gaza | Middle East and North Africa2 | East Asia | Lower Middle-Income Countries | Upper Middle-Income Countries | High-Income OECD Countries | World | |||
---|---|---|---|---|---|---|---|---|---|
Actual growth | -2.5 | 0.7 | 0.3 | 0.9 | 2.3 | 2.5 | 1.7 | ||
Predicted growth3 | 2.9 | 2.9 | 2.9 | 3.1 | 2.5 | 2.0 | 2.4 | ||
due to: | |||||||||
Log of real per capita GDP in 19953 | 1.1 | -1.1 | -1.0 | -0.3 | -1.4 | -2.6 | -0.7 | ||
Log of years of schooling in 1995 | 0.8 | 0.6 | 0.6 | 0.6 | 0.7 | 0.8 | 0.6 | ||
Openness | 0.6 | 0.5 | 0.8 | 0.4 | 0.4 | 0.3 | 0.4 | ||
Differences in population growth | 0.1 | 2.5 | 0.9 | 1.8 | 1.4 | 0.0 | l.1 | ||
Budget surplus | -0.5 | -0.1 | 0.1 | -0.2 | -0.1 | -0.1 | -0.2 | ||
Inflation | -0.1 | -0.1 | -0.1 | -0.1 | -0.1 | 0.0 | -0.1 | ||
Telephones per worker | 1.5 | 1.2 | 1.7 | 1.2 | 1.8 | 2.5 | 1.4 | ||
Land lock dummy | -0.6 | 0.0 | 0.0 | -0.1 | -0.1 | -0.1 | -0.1 | ||
Tropics dummy | 0.0 | 0.0 | -1.0 | -0.5 | -0.5 | 0.0 | -0.5 | ||
Natural resource abundance dummy | 0.0 | -0.8 | 0.0 | -0.2 | -0.3 | 0.0 | -0.1 | ||
Regulatory burden | -0.1 | -0.2 | 0.4 | 0.1 | 0.5 | 0.7 | 0.2 | ||
M2 to GDP ratio | 0.3 | 0.3 | 0.5 | 0.2 | 0.3 | 0.4 | 0.3 | ||
Residual4 | -5.47 | -2.3 | -2.6 | -2.2 | -0.2 | 0.5 | -0.7 |
Based on regression (1) in Table 2.10.
Excludes the West Bank and Gaza.
Includes constant of the regression.
Defined as actual minus predicted growth rates.
Policy Implications
The previous sections have shown that over the next 10 years the Palestinian economy will have to generate and sustain very high growth rates in real GDP, investment, and TFP in order to absorb the projected inflows to the labor market at rising real wages while at the same time reducing unemployment. Although the required growth rates—summarized in Table 2.9—are well above the historical average of the West Bank and Gaza, they have been achieved during extended periods in the past.
The immediate priority must, of course, be to halt the fall in output and income caused by the turmoil and closures, and to restore growth and recover as quickly as possible the output loss that occurred in the fourth quarter of 2000 and the first half of 2001. Particularly important to this end is the restoration of open access to foreign markets. The extent to which Palestinian employment in Israel can attain its pre-crisis levels will also have an important bearing on the recovery of the Palestinian economy (see Chapter 1).
For the medium and long term—the focus of this chapter—the previous section showed that the initial conditions for economic growth are generally good: the population is young and relatively well educated; the projected change to the age structure of the Palestinian population can be expected to provide an important (but temporary) impetus to long-term per capita income growth, and the West Bank and Gaza has a long tradition of commercial entrepreneurship—the economy is dominated by the private sector, and policymakers do not have to deal with a troubled and bloated state-owned enterprise sector, in marked contrast to the countries that emerged from the break-up of the Soviet Union. Nor do policy makers have to undertake serious and problematic macroeconomic stabilization policies—inflation is relatively low and stable, and the government is not encumbered with debt. The exchange system is also quite open. Thus, once the political and security situation improves and once the main obstacles and distortions to the Palestinian economy are addressed—especially those that cause the high costs for foreign trade and the deficiencies in the judiciary and legal framework—it should be able to enjoy an extended period of high growth, with supporting policies and continued improvements in infrastructure.
A frequent question is: which sectors in the Palestinian economy can be expected to be the engines for future growth? Although a detailed consideration of this question is beyond the scope of this chapter, it is safe to assume that residential construction will continue to be a key sector, given the demographic dynamics, while the agricultural sector will probably diminish over the long run because of water constraints and shrinking land availability (due to house construction). Other possible sources for future growth include tourism, consumer electronics, cut flowers, olive oil processing, plastics, software, and stone and marble processing (see The Services Group, 1999). In trying to identify sectors of future growth, it is tempting to focus on the existing production structure and see how it can develop in response to certain changes in the economic environment. The Palestinian economy is operating under significant restrictions, and once they are eased (especially those that make the transportation procedures so cumbersome and costly, and with improvements in the supply of energy), the economy might undergo a significant transformation during which entirely new sectors could emerge. The world is full of examples of countries successfully producing goods that a few years earlier no one would have considered to be their comparative advantage, such as Finland and Nokia. Thus, there is no reason to be pessimistic regarding future growth simply because the current production structure is limited and the West Bank and Gaza possesses few natural resources that can form the basis for industrial development.52
This section focuses on the policies that are important for the long-term prosperity of the Palestinian economy, drawing on the cross-country regressions in the previous section.53 Again, since investment in productive capital, such as machinery and equipment, is closely intertwined with growth in productivity, many of the policies that can spur investment also galvanize productivity, so in what follows, no distinction is made between policies that primarily affect investment from those that primarily affect TFP. This section focuses on: macroeconomic policy, access to foreign trade, governance and the legal and regulatory framework, competitive infrastructure, and access to capital. Several of the issues touched upon in the following sections are dealt with at greater length in subsequent chapters. When assessing the importance of policies for growth, it is also important to bear in mind that the positive effects on long-run growth that the West Bank and Gaza could expect to receive from the convergence effect and from the demographic transition are conditional on the macroeconomic and structural variables in the regression.
One issue that cuts across many of the topics discussed below is the crucial need to reduce output volatility and the overall level of uncertainty in the Palestinian economy. As shown previously, output volatility was extraordinarily high in 1970–99. In the past, part of the fluctuations could be explained by the so-called olive cycles, but since 1994 output volatility has mainly been induced by changes in the political and security environment. Significant output (and income) volatility reduces welfare directly when most households have little means to undertake consumption smoothing, but output volatility can also reduce economic growth prospects, as it might reduce investment in productive capital when investment decisions are difficult to reverse; investors prefer to wait and see.54
In addition to the negative effects on growth from output volatility, the cumulative effect stemming from the mere risk of closures, the lack of unimpeded access to world markets, and uncertainty over the direction of domestic policies has created an environment of exceptionally high uncertainty with negative repercussions on investment and growth more generally.55 In particular, investors will avoid the Palestinian export sector because of the uncertain access to world markets. Furthermore, the PA’s own policies inject a considerable degree of uncertainty. The PA’s view of its role in the economy is not clear, progress in legal and institutional reforms has been uneven, and the judiciary remains weak. One concrete example of how economic policy adversely affects investment and growth is the partial and haphazard way in which the PA implements VAT refunds; a practice that is particularly harmful to new, small enterprises. While the damage that these domestic policies inflict on the Palestinian economy cannot be compared with the devastating effects of closures, they do have significant negative effects on investment and long-term economic growth prospects.
The Role of Macroeconomic Policy
Macroeconomic policy can significantly affect long-term economic growth by ensuring stable prices and external viability by raising public savings and investment and through the use of taxation and public expenditure.
Price Stability
The results from the cross-country regressions show a negative relationship between, on the one hand, long-run economic growth and, on the other hand, inflation and inflation volatility, confirming the results of other studies, particularly those for middle- and low-income countries.56 The main policy tools for price stability are monetary and exchange rate policies, supported by fiscal and income policies. The absence of a Palestinian currency means, of course, that the PMA lacks the exchange rate policy instrument, and the scope for monetary policy is very limited.57 Nevertheless, in recent years, the present currency arrangement—with no Palestinian currency and with the new Israeli shequel, the U.S. dollar, and the Jordanian dinar circulating freely—has delivered relatively low inflation rates in the West Bank and Gaza so that, at least over the past 10 years, economic growth cannot be said to have been harmed by excessive inflation. Exchange rate (and monetary) policy options are discussed in greater detail in Chapter 6.
Fiscal Policy
Fiscal policy is the only macroeconomic policy instrument currently available to the PA. Although its role is constrained by the limited capacity of the Ministry of Finance, the PA can support long-term growth of the Palestinian economy with fiscal policy through several channels. First, by building up a surplus on the recurrent budget over the medium term, as envisioned in the PA’s budget for 2000, the PA can help raise national savings, which in turn can support growth by allowing for higher private (and public) investment. Evidence from other crosscountry regressions (for example, Barro, 1991; Barro and Sala-ì-Martin, 1995; and Sachs and Warner, 1995b) shows that higher public saving (smaller deficit or higher surplus on the recurrent budget) is significantly associated with stronger growth in per capita GDP. Of course, it would not be realistic for the PA to aim for a surplus on the recurrent budget in 2001 because of the sharp decline in tax revenue in the aftermath of the turmoil and closures.
Second, fiscal policy can be a key source of macroeconomic instability and uncertainty, which in turn can deter investment and growth (see, for example, Lensink, Bo, and Sterken, 1999). Thus, the PA can support long-term economic growth by simply pursuing a predictable and sound fiscal policy, including by avoiding large, debt-financed fiscal deficits. To this end, the PA needs to strengthen the budget preparation, monitoring, and execution process, as weak fiscal control creates uncertainty about future taxes, expenditure, and deficits. The PA must also become more efficient in paying VAT refunds.
Third, fiscal policy of the PA can support long-term growth by improving the composition of expenditure. There is ample evidence that some expenditure—in particular infrastructure investment and maintenance, and outlays on education and health—can be conducive to growth, whereas other expenditure, for example rapid growth in the wage bill (except in education and health) can hurt growth prospects (Barro and Sala-ì-Martin, 1995). Thus, by allocating an increasing share of fiscal resources to education, health and investment (including maintenance of existing infrastructure), and by reining in the rapid growth in the wage bill in general, the PA can help support long-term economic growth prospects.
Finally, the level and composition of taxation can affect long-term growth prospects. In early 1999, the PA implemented a tax reform, which significantly reduced corporate and personal income tax rates. The corporate tax rate was unified and reduced to a flat 20 percent from 38.5 percent in the West Bank and 37.5 percent in Gaza. The number of personal income tax brackets was reduced from eight to four. The reduction of taxes has helped reduce the cost of conducting business in the West Bank and Gaza. Furthermore, tax exemptions are provided under the Investment Encouragement Law of 1998. While it is possible that such exemptions might induce some investment that otherwise would not have taken place, it will be important to monitor developments to ensure that the tax base is not undermined.
Foreign Trade
Open and secure access to foreign trade is crucial for the development of the Palestinian economy, as it is for any small economy. It is also a key factor for attracting foreign direct investment. The future performance of the Palestinian economy in general and the tradable sector in particular will be heavily influenced by the future trade policy of the PA and the extent to which the current high transactions costs (including transport costs) can be reduced Transactions costs are covered in greater detail in Chapter 3, while the trade regime is discussed in more depth in Chapter 4.
Trade Regime
The West Bank and Gaza is currently in a customs union with Israel as set out in the Protocol on Economic Relations of 1994 (or the Paris Protocol). The external tariff and non-tariff barriers, quality and health requirements, and import licensing are decided by Israel, with a few exceptions.58 An important issue for the future is the type of trade regime the PA will adopt, including the type of trade arrangement it will have with Israel.
As Chapter 4 argues, the Palestinian economy would benefit most from an open and transparent trade regime with a low uniform tariff rate together with the absence of quotas and trade monopolies. To keep the trade regime simple and transparent, it will also be important to avoid entering into a series of bilateral free trade arrangements and instead limit such arrangements to key markets for Palestinian exporters. Israel will remain an important trading partner for the Palestinian economy over the medium term regardless of the trade regime between the two entities, because it is the largest and most developed economy in the region and because of its proximity to the West Bank and Gaza. At the same time, there is considerable potential to increase trade with the rest of the world. The results from the gravity model in Chapter 4 show that while Israel’s share in Palestinian trade is high, this observation should be interpreted as an indication that the West Bank and Gaza undertrades with the rest of the world rather than overtrades with Israel.
Transaction Costs
The performance of Palestinian trade and the economy in general is hampered by the recondite system of permits, security checks, transportation procedures and fees, and the considerable uncertainty surrounding their implementation. The various rules are complex, do not exist in written form, and are subject to frequent and unannounced changes, all of which contribute to uncertainty and transactions costs. While it is difficult to estimate the damage that this system has inflicted on the Palestinian economy, especially the tradable sector (particularly in Gaza), there can be no doubt that a reduction in the transactions costs is crucial for enhancing Palestinian economic growth performance. A recent study of the business environment in the West Bank and Gaza (Sewell, 2001), found the regulatory and administrative burden created by the Israeli security procedures to be the single most important obstacle to private sector development. A study by the Federation of Palestinian Chambers of Commerce, Industry, and Agriculture (1998) estimates that export and import costs, on average, are 30 percent higher for a Palestinian company than an Israeli company, and the clearance time required to process exports and imports is between 20 and 80 percent longer for Palestinian goods.59 The cumbersome transport restrictions and security checks also cause delays in export shipments that, in today’s global economy where businesses keep small inventory holdings, are likely to cause an exporter to lose a contract regardless of the price discount it can offer.
Transaction costs in the West Bank and Gaza can be reduced with improvements to the trade infrastructure to enhance the access to world markets. The Gaza Airport will become more important for exports and imports once cargo facilities have been established. The construction of the Gaza seaport, which has begun and was initially scheduled for completion in 2002, will also facilitate trade with the rest of the world. The regression results presented earlier—which showed that landlocked countries tend to grow significantly slower than those that are not landlocked—suggest that a seaport in Gaza can play an important role in promoting trade and long-term economic development. Three conditions would seem crucial, though, for the seaport (as well as the Gaza airport) to have a major positive impact on the Palestinian economy: (i) the West Bank must become better linked to the Gaza Strip so that it too can benefit form the seaport and the airport; (ii) the movement of goods and people through the two ports and between the Gaza Strip and the West Bank must not be subject to the current cumbersome system of security checks and permits; and (iii) the ports (and customs operations at the ports) must be operated efficiently.
Legal and Regulatory Framework and Governance
The PA has made significant progress since its creation in 1994 in establishing a functioning economic administration and in developing a basic Palestinian institutional framework. Key economic policy institutions have been set up, and there has been considerable progress in legal reform, although much more is needed to strengthen the capacity and independence of the judiciary system in order for it to be a positive factor in the development of the Palestinian economy and increase the effectiveness of the Palestinian Legislative Council (PLC) and its oversight functions. The quality of the institutional framework—the legal and regulatory framework and economic governance—is crucial for achieving economic success, and differences in it explain a large part of the differences in economic development across countries (see Box 2.3).60 Good governance, including ensuring the rule of law, improving efficiency and accountability of the public sector, and tackling corruption are all real issues that need to be addressed in the West Bank and Gaza.
Polls conducted regularly by the Center for Palestinian Research and Studies in Nablus show that a large share (about 60 percent) of those asked believe that there is corruption in the PA, although these polls do not ask people how important they think corruption is. However, Sewell (2001) finds that while there is a concern over corruption, this concern is likely to reflect a more general unhappiness with how the PA operates, including the lack of transparency. By contrast, this study find very little concern among Palestinian businesses over petty bribery or corruption in the PA procurement accounts, so concerns over corruption should not be overstated. One important governance concern related to the operations of the Palestinian Commercial Services Company (PCSC) and its equity holdings in private companies. In a somewhat older international study of governance (Kaufman, Kraay, and Zoido-Lobaton, 1999), the West Bank and Gaza also scored better than the average for the MENA region on six measures of governance, of which outright corruption is one measure.61
One way for the PA to allay some of the concerns over governance is to be more transparent in its own fiscal and other financial operations. The PA took important steps in this direction in the spring of 2000, as described in Chapter 1, with the consolidation of tax revenue under the Ministry of Finance, and the audit and public disclosure of key financial data for the PCSC.62 These reforms will have to be accompanied by a further strengthening of the legal framework and the judiciary in the West Bank and Gaza. In the survey reported in Sewell (2001), the courts and the judiciary were ranked the worst among the PA public institutions in terms of quality of services. While some important laws have been approved by the PLC and ratified by the president (for example, the Organic Budget Law), many, including the draft banking and competition laws, have been delayed excessively. It will be important to accelerate the process of approving and ratifying laws, but strengthening the legal and regulatory framework involves more than just passing laws. Once a law is approved, the necessary regulations need to be prepared and adopted as well, and the Palestinian judiciary system must be strengthened to ensure that the legal framework is implemented in an effective and independent manner.
Financial Development and Access to Financing
A healthy and efficient financial system is important for effective resource allocation and mobilization of savings. Investment also requires access to financing, domestic or foreign. While the West Bank and Gaza does not have any capital account restrictions that prevent private sector financing from abroad, the only realistic sources of foreign financing in the medium term are foreign direct investment, multilateral institutions, and the Palestinian diaspora. The two main sources of domestic financing are the Palestinian banking system and the Palestinian Securities Exchange (PSE).
The past seven years have witnessed a rapid development of the Palestinian banking system, with strong growth in deposits and credit to the private sector (see Chapter 1, Figure 1.3). Table 2.12 shows that these developments made a positive contribution to economic growth in 1995–99, and the banking system should play an increasingly important role in the economic growth process in the future. A sound and efficient banking sector performs many functions that support economic growth, including mobilizing and efficiently allocating savings, facilitating trade and risk management, and exerting discipline on corporations. To ensure the soundness and effectiveness of the Palestinian banking system, it is crucial that the PMA step up efforts to strengthen bank supervision, that the banking law be passed without further delay, and that the legal, accounting, and auditing system be improved.63 The latter is particularly important for banks to be able to make sound credit assessments and reduce their requirement for collateral. Levine, Loayza, and Beck (2000) find that differences across countries in their systems of accounting, creditor rights, and contract enforcement explain a significant part of differences in financial development that in turn affects GDP growth.
The fledgling stock market, the PSE, can also be expected to become an increasingly important source of financing over the long run. The PSE, a private company that began operations in 1997, has 24 listed companies and a market capitalization of roughly US$1 billion (both as of June 2000). At 25 percent of GDP, the stock market capitalization is lower than in most developed economies but on par with many emerging markets, (for example, Argentina, Brazil, and Mexico), and the turnover ratio (at 50 percent of the market capitalization) is high even when compared with many developed economies; thus the PSE is already quite large and liquid. The approval of the Capital Market Law and the implementation of the PA’s privatization strategy will be important steps for the further development of the stock exchange.
As regards financing of the private sector from bilateral and multilateral sources, for example, the European Investment Bank (EIB) provides such financing, directly and through local banks. In addition, the European Union financed the initial capital for the Palestinian Development Fund (PDF) and several smaller credit extension projects. The PDF, now a private firm, targets small- and medium-sized enterprises and has a lending portfolio of roughly US$30 million.
An important source of financing is foreign direct investment from foreign companies and Palestinian expatriates. Data from the PCBS show that foreign direct investment amounted to US$218 million in 1998 (5.6 percent of GDP) up from around US$143 million in 1995. A large part of foreign direct investment has gone into real estate, but there are also several examples of foreign companies buying equity positions in local companies. Such investments are important not only because of the financing they bring but also because of the transfer of technological and management expertise. The Investment Promotion Law of 1998 and the Industrial Estates Law of 1998, together with the establishment of industrial estates in the West Bank and Gaza can be expected to help attract more foreign direct investment.
Competitive Infrastructure
A modern and properly maintained infrastructure is essential for the development of the Palestinian economy, and in the past six years there have been major improvements in the physical infrastructure in the West Bank and Gaza, with important assistance from donors. According to the survey reported in Sewell (2001), Palestinian businesses view the quality of the physical infrastructure as much less of an important constraint for their activity than they did a few years ago. Most noticeable are probably the improvements in basic infrastructure like roads and sewage systems, while much remains to be done in particular in the areas of water and power. In the growth regressions performed earlier in this chapter, two variables were included that can signify the importance of infrastructure for the West Bank and Gaza: telephone lines and lack of direct access to a seaport. Both variables were highly significant and had large coefficients. With respect to telephone lines, the telecommunications company, PALTEL, has made considerable investments in the past few years that have led to a major expansion in the Palestinian telecommunications network. In the West Bank and Gaza, the number of installed telephones has increased to 314,221 at the end of 1999, from 89,958 three years earlier, reducing the waiting list by 80 percent. PALTEL’s target is to have 400,000 lines by the end of 2003. There has also been rapid expansion in cellular services provided by Al-Jawwal (of which PALTEL owns 65 percent).
Major concerns for the future are power, electricity, roads, and, but to a lesser extent, telecommunications. The power infrastructure is insufficient to support industrial development and power outages are common. Similarly, water supply is problematic and is also insufficient for large-scale industrial development.64 Per capita consumption of energy and water in the West Bank and Gaza is low compared with other countries in the region. Several factors explain the insufficient development of the power, telecommunications, and water infrastructure (even if telecommunications services are improving rapidly), and some of them (like water supply) can only be resolved as part of a final peace agreement with Israel and will probably need regional cooperation. The Interim Agreement restricts the development of water resources and the construction of power plants, as well as the extent of telecommunications operations. This has led to dependence on the Israeli supply of services in these three sectors. The development of power, telecommunications, and water infrastructure has also been hampered by the limited administrative and regulatory capacity of the PA and the dilapidated conditions of the infrastructure because of under investment and lack of maintenance before 1994. Lastly, the road networks have not kept pace with the rapid expansion in commercial centers like Ramallah, leading to serious congestion problems.
The PA is trying to address some of the enormous infrastructure needs by concentrating its efforts in a few places—the industrial estates. The industrial estates can offer modern infrastructure, simplified bureaucratic procedures, even simplified and less costly security restrictions, as well as lower taxes. At the same time, industrial estates can offer a good environment for investors in certain type of industries, but for the Palestinian economy to flourish, significant improvements must occur to the infrastructure throughout the West Bank and Gaza.
Concluding Remarks
This analysis of the Palestinian economy takes a long-term perspective, recognizing that the most immediate concern must obviously be to ensure a rapid recovery from the output collapse that occurred in the fourth quarter of 2000 and the first half of 2001. But it is important not to lose sight of the medium-term challenges and opportunities. The projected demographic changes over the medium term will come about irrespective of how the current conflict evolves, and risk causing a further deterioration in social conditions.
Over the medium term, population growth is expected to slow, leading to a rise in the share of the population at working age. Under plausible assumptions regarding demographics and labor force participation rates, the labor supply would increase by 4.4 percent a year in 2001–10. In order to absorb these inflows into productive employment, while at the same time reducing the high unemployment rate, domestic employment must expand by approximately 6–7 percent a year. This would translate into required rates of growth in real GDP of 8 percent a year and in TFP of 1.2 percent that is consistent with an annual increase in real wages of 1.5 percent a year. If the West Bank and Gaza were to experience large-scale immigration, higher growth in GDP and TFP would be needed for any given real wage scenario. It is no doubt a considerable challenge for the Palestinian economy to achieve such growth rates on a sustained basis, but such growth rates have been attained in the past. Real GDP growth is estimated to have averaged 6 percent and TFP growth 1.4 percent over the past 30 years albeit with substantial annual variations.
The initial conditions for medium-term economic growth are generally good. The population is young and relatively well educated and the projected change to the age structure of the Palestinian population can be expected to provide an important (but temporary) impetus to long-term per capita income growth. While it is of course essential to improve the political and security situation, sustained medium-term growth will also require that the main obstacles and distortions in the Palestinian economy are tackled and that the PA undertakes supporting policies and reforms. The growth regressions presented in this chapter show that the changing demographics in the West Bank and Gaza can provide an important boost to growth in per capita GDP. This boost is not automatic, however, and it is not too difficult to envision a scenario where the large inflows to the labor market lead to higher unemployment and lower real wages. The regressions also provide some insights as to what factors can help ensure that the demographic changes make a positive contribution to growth. It is critically important to reduce political risk, which has induced major output volatility in the past. Sustained medium-term growth will also require better access to foreign trade, sound macroeconomic policies and governance, a competitive infrastructure, financial development, and a strengthening of the legal and regulatory framework.
Appendix I: Growth Accounting and Cross-Country Growth Regression: Methodology and Data Sources
Growth Accounting and TFP
This appendix describes the methodology that lies behind the calculations reported in the chapter, shortcomings and strengths of the methodology, the concept of TFP growth, and the relevant data needed for the application of the methodology to the Palestinian economy.65 The appendix also provides a description of the data and their sources used in the cross-country growth regressions.
The starting point of growth accounting is the aggregate production function for the economy where real output (Yt) is specified as a function of the physical capital stock (Kt), labor (Lt), and technology (At). Tire most widely used specification of the production function is of a Cobb-Douglas form:66
where α is the elasticity of output with respect to capital stock, and the production function incorporates the assumptions mentioned earlier. Output growth and TFP growth are then given by the following expressions:
or
where yt, kt, lt, and at represent growth in output, TFP, the capital stock, and labor, respectively. Growth can increase on account of faster accumulation of factors of production, TFP growth, or both.
The growth accounting methodology relies on several crucial assumptions: (1) the existence of a stable aggregate production function for the economy as a whole characterized by constant returns to scale; hence, output will double when all inputs are doubled; (2) that factor markets are characterized by perfect competition so that each factor is paid its value of marginal product; and (3) the absence of externalities in factor inputs. These assumptions allow payments to factors of production equal to the value of output produced. Thus, with two inputs (capital and labor), the share of total national income accrued to each input will add up to one. This result is used in calculating most measures of TFP growth, including those reported in the chapter. Under these assumptions, the elasticity of output with respect to the capital stock, α, is the share of capital income in national income.
If the production function is subject to diminishing returns to scale, as assumed above, growth cannot increase indefinitely and cannot be sustained purely on account of high accumulation of factors of production.67 In fact, under the above assumptions growth will eventually slow down and can even turn negative without a sustained and positive TFP growth. Within a growth accounting exercise and given the above assumptions, it is TFP growth, not labor productivity or capital productivity, that is the economically more meaningful concept of productivity. TFP growth is derived as the weighted average of the growth in factor inputs (see equation (3)).
Growth accounting has several limitations, however, which need to be taken into account when conducting policy analysis. First, as described above, the accounting decomposition is based on a number of assumptions about the industrial structure of the economy, which may not apply to a particular economic setting. It should be pointed out, though, that perfect competition is not a strict requirement for growth accounting. Rather, what is needed at minimum is that factor earnings be proportional to factor productivities. Second, the decomposition identifies the residual growth component with a measure of productivity, while in reality, the residual is likely to also reflect other factors besides technical progress such as mismeasurement of the factors of production, political uncertainty, and public policies. Third, as its name suggests, the methodology is purely an accounting exercise. It cannot, for example, identify the fundamental determinants of accumulation of factors of production and TFP growth. Nor can it determine by itself if factor accumulation causes TFP growth or vice versa, or whether both are caused by some other factors. In defense of the methodology, it should be noted, however, that these are not the objectives of growth accounting.
Some studies use econometric techniques which take into account the endogeneity of factors of production in order to derive an estimate of TFP growth (for example, Senhadji, 1999; and IMF, 1998) while others use variance decomposition methods to derive TFP growth (e.g., Klenow and Rodriguez-Clare, 1997; and Easterly and Levine, 2000). Applying the methods from these latter two studies to the West Bank and Gaza over the 1970–99 period increases the share of output growth that is attributable to TFP growth to well in excess of 80 percent as compared with the 23 percent implied by Table 2.1.
Despite the foregoing limitations, which have been known for some 40 years, growth accounting continues to be widely used since it provides a useful benchmark and a simple and internally consistent framework for understanding key aspects of economic growth. A broad set of sensitivity analyses are routinely conducted, as the chapter illustrates, in order to verify the robustness of the implied policy implications to changes in the underlying assumptions. The sensitivity analysis usually consists of variations in: (i) the depreciation rate of the capital stock, (ii) the assumptions regarding the initial capital-output ratio, (iii) the sample period to check for the stability of the underlying production function, and (iv) the capital share of income. Among these factors, the capital share of income (a) has the greatest effect on the estimates of TFP growth.
Computing Required TFP Growth
Growth accounting is not just a methodology for accounting for past sources of growth; it can also be used for policy analysis, subject to the caveats mentioned above. One particular policy analysis involves calculating the TFP growth that is required in order to meet certain policy objectives, and ascertaining if the required TFP growth could be achieved in the light of the past TFP growth performance as well as past and future direction of policies.68 In this sense, some policies may be regarded as exogenous and some endogenous to TFP growth and its sources. An alternative formulation of growth accounting has been used in order to address these issues. Under this formulation, equation (3) can be rewritten as
or
where yt – lt represents labor productivity growth, which, under the assumptions indicated above, is w, equal to real wage growth. In other words, workers are paid the value of their marginal product. In practice, real wage growth and labor productivity growth may not coincide since any one of the assumptions indicated above can be violated. Therefore, the analysis is simply illustrative, but it is nevertheless useful since it brings out the trade offs faced by policymakers between employment expansion, hence, reduction in unemployment, and increases in investment and TFP growth that are needed in order to have a sustained rise in real per capita income while maintaining a desired path for real wages at the same time. In this connection, it should be emphasized that the information content of the methodology has not changed—it is the same accounting relationship that is being manipulated—and the attraction of this alternative formulation is that it regards TFP growth, much like factor accumulation, as an endogenous variable that is subject to policy influences and policy analysis. In contrast, fertility rates, for example, which affect the population growth rate and ultimately the growth of the working-age population may be more influenced in the short run by cultural factors and the choices of parents and their immediate needs rather than economic policy at the national level.
The required TFP growth can be calculated from (4) or (5), given assumptions on value of α growth of real wages (labor productivity), capital stock, and employment. Expression (4) is used in the calculations reported in Table 2.11 in the chapter.
Data Requirements for TFP Growth
The calculation of TFP growth requires estimates of α and data on output, the capital stock, and employment. The value of α is crucial to estimates of TFP growth; the higher α is, the lower TFP growth is since the capital stock tends to grow fester than employment in most economies. This is also the case for the West Bank and Gaza where the capital stock grew taster than employment over the period 1970–99.
In general, estimates of α are obtained from national income accounts, studies of growth accounting for other economies, or regression analysis.69 Each approach has its own weaknesses and strengths and would result in different estimates of a, and, hence, different TFP growth. For example, the estimates obtained from national income accounts may not be suitable for cross-country comparison of TFP growth since differences in α may account for much of the cross-country differences in TFP growth. The reliability of national income accounts-based estimates also depends on the quality of national account statistics. In many developing countries, including the West Bank and Gaza, estimates of the components of output from the income side of the national accounts statistics are not very reliable and often significantly exceed those for developed countries. The estimates for developed countries range from 0.3 to 0.4 compared with over 0.4 for developing countries.70 The higher estimate for developing countries can reflect the role played by a sizable in formal sector and the self-employed and unpaid family workers whose income is allocated to the residual gross operating surplus (GOS), hence, lumped with income of capital.71
In this study, two estimates of α are relied on to calculate TFP growth for the West Bank and Gaza. The first estimate (0.35) was taken from other studies of growth accounting.72 This allows comparison of the West Bank and Gaza’s TFP growth with that of other economies.
The second estimate (0.58) is constructed from the West Bank and Gaza’s national income accounts from the PCBS. The closest proxy for income from capital in the PCBS data is the concept of GOS, which is the sum of the net operating surplus and consumption of fixed capital; or defined as a residual, GDP less compensation of employees, less taxes on production and subsidies. The capital share of income is thus obtained by dividing GOS by GDP for each year and averaging the result.73 The use of a time average is preferable to the use of a single-year observation to ensure that the estimates of TFP are not overly influenced by short-run economic fluctuations. Available information from the PCBS allows computation of capital share of income only for 1995, 1996, and 1997, however.74 Interestingly, despite the large fluctuations in output growth during this period (induced by the closures in 1995 and 1996) the capital share of income has been quite stable: it was 0.60 in 1995; 0.58 in 1996 and 0.55 in 1997. The average of these three estimates is 0.58.
In addition to the capital share of income, data on real output, employment, and the capital stock are also needed in order to calculate TFP growth. For the period 1968–92, data on real GDP (in 1986 NIS prices), employment, and real investment are taken from the ICBS (1996) and World Bank (1993), and for the period 1993–99, they are IMF staff estimates based on the PCBS data. The coverage of employment is an important issue in the calculation of TFP growth for the West Bank and Gaza. Because the focus is on real GDP growth as the measure of real output growth, the employment data exclude the Palestinians who work in Israel and the settlements and the underemployed as defined by the PCBS. For the period prior to 1993, Palestinians working in Israel, as defined by ICBS (1996), are netted out from total employment as reported in the same ICBS document, and the resulting series is spliced to post—1993 employment data that exclude Palestinians working in Israel and the underemployed.
Data on the capital stock are obtained using the perpetual inventory method that requires an estimate of the initial value of the physical capital stock, a rate of depreciation of the capital stock, and real investment in physical capital. In the West Bank and Gaza, as in many developing countries, data on the physical capital, the depreciation rate, and the initial capital stock are not available and have to be assumed. This study assumes that the initial capital stock is 2.5, which is the estimate used in many cross-country estimations of the capital stock.75 This value together with data on real GDP in 1968, which is the initial year for which data on investment and GDP are available, give the estimated initial capital stock.76 The depreciation rate is assumed to be 4 percent, which is also the value used in many cross-country studies of capital stock.77 Alternative and reasonable assumptions of the depreciation rate (for example, 6–7 percent) resulted in the same estimates of capital stock in the outer years, as the impact of the depreciation rate declines geometrically because of the use of perpetual inventory method. This is a common finding in studies of growth accounting. Finally, the investment data since 1994 include domestically financed as well as donor-financed investment.
Data Requirements for Cross-Country Growth Regressions
The data used in the regressions reported in Table 2.10 and the source of each variable are as follows:
Growth in Real PPP Per Capita GDP in U.S. Dollars
This is the dependent variable in the regression and is obtained as the compounded growth rate of real purchasing power parity (PPP) per capita GDP in U.S. dollars over the 1970–99 period. Data on real PPP per capita GDP in U.S. dollars are obtained in two steps. First, nominal PPP per capita GDP in U.S. dollars, taken from the IMF’s World Economic Outlook (WEO), is multiplied by total population from the WEO. The result is then divided by total population data taken from the World Bank’s World Development Indicators (WDI) database. Population data from the WDI are used because of their consistency with the data on working-age population, which are also used in the regression; WEO does not report data on working-age population. Second, real PPP per capita GDP in U.S. dollars is obtained by deflating each country’s nominal PPP per capita GDP in U.S. dollars by the U.S. implicit GDP price deflator with the base of 1995. Data on the West Bank and Gaza are obtained by using GDP in constant 1995 U.S. dollars from the WDI over the 1994–99 period; the data for the period 1970–93 are obtained by applying annual growth rate of real GDP in constant 1986 New Israeli Shequel (NIS) prices over the period 1970–94 to the 1994 data from the WDI.
Real PPP Per Capita GDP in U.S. Dollars
Described as above. The value of this variable in 1970 is used in the regression.
Years of Schooling
This variable represents average years of schooling in the population over 15 years of age and is taken from Barro and Lee (2000). The data for the West Bank and Gaza refer to the population over 14 years of age and is constructed using the same methodology as that of Barro and Lee (2000) with the raw data taken from the Israel Central Bureau of Statistics (1984; pp. 786–787, Table VII/42).
Openness
This variable is constructed as the ratio of real trade, which is the sum of real export and real imports, to real GDP. Data for all countries except for the West Bank and Gaza are taken from the WEO The data on real export and real import (in 1986 NIS prices) for the West Bank and Gaza over the period 1970–91 are taken from World Bank (1993) and ICBS (1996); the data over the period 1992–99 are IMF staff estimates based on ICBS (1996) and PCBS.
Growth in Total Population
WDI is the source for all countries except for the West Bank and Gaza. For the West Bank and Gaza, data for 1993–99 refer to population data (excluding East Jerusalem) and are IMF staff estimates based on PCBS with zero migration assumption over 1997–99. The data prior to 1993 are obtained by applying the growth rate implicit in population data from ICBS (1996) over the period 1970–93 to the 1993 estimate.
Growth in Working-Age Population
WDI is the source for all countries which refer to population between 15 and 64 years of age. For the West Bank and Gaza, data refer to population during 14 years of age for the period 1970–93 and over 15 years of age for the period 1993–99. The two series are spliced by applying the growth rate implicit in the over 14 years of age population over the period 1970–93, taken from ICBS (1996), to the estimate of the population over 15 years of age in 1993. The data on population over 15 years of age over the period 1993–99 are IMF staff estimates based on the PCBS.
Budget Surplus
Data for all countries are taken from WEO. The budget surplus figure refers to the difference between revenue and grants and expenditures and net lending. For the West Bank and Gaza, data are IMF staff estimates for the period 1993–99. Data for the period prior to 1993 are not considered reliable and are not therefore used in the regression.
Inflation
This is defined as growth in consumer price index (year over year) for all countries and taken from the WEO. West Bank and Gaza’s data refer to inflation for the West Bank only over the period 1977–94, taken from Israel Central Bureau of Statistics (1996, p. 582, Table 27.11). The data over the period 1995–99 are taken from the PCBS and refer to the West Bank and Gaza.
Standard Deviation of Inflation
This is calculated as the standard deviation of inflation for every country that has non-missing annual data on inflation rate.
Telephones Per Worker
WDI is the source for all countries. For the West Bank and Gaza data are taken from PALTEL. For the West Bank and Gaza, data are available from 1996 only.
Landlock
This is a dummy variable that takes a value of 1 when a country is landlocked and zero otherwise. These data are taken from the World Bank’s Economic Growth home page.
Tropics
This is a dummy variable that takes a value of 1 when a country is located in the tropics and zero otherwise. These data are taken from the World Bank’s Economic Growth home page.
Natural Resource Abundance
This is a dummy variable takes a value of 1 when the country is a primary exporter of fuel and zero otherwise. The data source is World Economic Outlook, May 2000 (Table C, p. 194).
Regulatory Burden
This variable measures the extent of regulatory burden and delays in government beaureacracy in granting licenses, etc. It ranges from a low of -2.5 to a high of 2.5. A higher value indicates lower degree of regulatory burden. The data source is Kaufmann, Kraay, and Zoido-Lobaton (1999). For ease of interpretation, this variable has been multiplied by a negative sign in the regression reported in Table 2.10. Therefore, a higher value would represent higher regulatory burden.
Ratio of M2 to GDP
This is the ratio of nominal broad money to nominal GDP and is taken from the World Economic Outlook. For the West Bank and Gaza, the data refer to deposits of the Palestinian Authority and the private resident held in the domestic banking system.
Unless otherwise mentioned, population growth refers to the natural population growth rate, or the difference between birth and death rates; the effects from migration are discussed separately.
Galor and Weil (1999 and 2000) present a unified model that encompasses different views on economic development and population growth.
See for example, Barro and Sala-ì-Martin (1995), Bloom and Freeman (1986), and Sarel (1994). There is also reverse causality, with the level of economic development affecting fertility and mortality rates, but with different time lags.
See Williamson (1997) for an overview of the links between demographic change and economic growth.
The effect would be different if the expansion in the labor supply were due to an increase in labor force participation rates. Labor force participation is to some extent endogenous to economic growth, whereas this is not the case for population growth in the short run.
See Solow (1957) for the first application of growth accounting, and Barro (2000) and Hulten (2000) for reviews of the methodology and a variety of approaches to measure productivity growth. Arnon, Luski, Spivak, and Weinblatt (1997) undertake a growth accounting exercise for Gaza and the West Bank (separately) for the period 1970–90. While not directly comparable (because we treat the West Bank and Gaza as one unit and the focus is on a longer time period) the results are nevertheless similar.
‘There are also TFP-induced changes in factor accumulation, and vice versa, which could result in different estimates of the importance of TFP in growth. This chapter abstracts from these considerations, as is standard practice in growth accounting (see Appendix I).
The volatility in output as measured by the coefficient of variation (the standard deviation of annual growth rates divided by the average growth rate for the period) increased after 1994. Part of the high volatility in output prior to 1994 has been attributed to the presence of cycles in olive production (see Arnon, Luski, Spivak, and Weinblatt, 1997). After 1994, the closure-induced drop in output dwarfed the effect of these cycles in 1995–96.
According to data from Israel Central Bureau of Statistics (ICBS, 1996, Table 2, p. 64), the Palestinian economy’s dependence on factor income from abroad (mainly labor income from Israel) grew from I percent of gross national income (GNI) in 1968 to 25 percent in 1973.
Part of the slowdown has also been attributed to regulatory constraints imposed in response to Israeli farmers’ fear of competition from Palestinian agricultural producers and to the lack of investment in infrastructure (Arnon, Luski, Spivak, and Weinblatt, 1997).
See the section entitled “Total Factor Productivity” for a discussion of the elasticity of output with respect to capital, used in this calculation.
In this section, unless otherwise noted, the employment data refer to domestic employment only, that is, Palestinians who work in Israel and the settlements are excluded from these data and the underemployed are counted as unemployed. This is the definition of employment most relevant to the growth accounting exercise. In other parts of the chapter as well as in the other chapters, employment includes those working in Israel and the settlements as well as the underemployed, in line with the definition used by PCBS in its labor force surveys.
‘Over the 30-year period, the labor force participation rate has increased, with a U-shaped pattern in 1975–85 and a much higher participation rate after the mid-1980s.
The decline in employment of Palestinian workers in Israel was also due to employment of non-Palestinian foreign workers and further immigration into Israel.
The decline in labor productivity (and TFP) since 1994 might also reflect an underestimation of real GDP growth.
See, in particular, Collins and Bosworth (1996) and Crafts (1999) and Dhonte, Bhattacharya, and Yousef (2000). This estimate was also used in a study of growth accounting for the West Bank and Gaza by Arnon, Luski, Spivak, and Weinblatt (1997).
As explained in Appendix 1, the reliability of national income accounts-based estimates is weakened by the often poor quality of national account statistics in developing countries, including in the West Bank and Gaza.
Calculations based on a capital share of 0.58 yield a lower TIT growth (0.4 percent versus 1 -1 percent for the period 1970–99), but qualitatively, the movements in TFP growth remain unchanged. These results are not surprising since the capital stock has expanded faster than employment. The largest divergence between the two estimates of TFP growth occurred in 1970–79, the period with the most rapid increase in the capital-labor ratio.
There are significant annual variations in TFP growth after 1994: TFP fell by 7 and 18 percent in 1995 and 1996. respectively, but has since recorded a (modest) turnaround.
The assumptions are: an initial capital-output ratio of 2.5. capital share of income of 0.35 and depreciation rate of 4 percent (the same in the top panel of Table 2.1). Appendix I explains the Assumptions.
The regional classification follows that of the World Bank-To be consistent with the rest of the literature, however, EAP excludes Australia. Japan, Myanmar, and New Zealand (see Crafts, 1999).
The 3.7 percent is the difference between the birth and death rates, and calculated as the average of the available observations for the period 1990–97 from the World Bank Development Indicators Data Base. It is higher than that for any of the other 200 economies in that database. It is slightly lower, however, than the 3.8 percent reported by the PCBS for more recent years and the latter are used in this chapter.
The natural population growth rate in the West Bank rose to 3.5 percent in 1987, from 2.2 percent in 1968 and 3.1 percent in 1978. In Gaza, the corresponding rates were 4.3, 3.7, and 2.3 percent. The growth rates stabilized in the 1990s, even declined somewhat, at around 3.5 percent in the West Bank and 4 percent in Gaza. According to PCBS (1998b) the desired fertility rate among women is considerably lower than the prevailing rates.
This change in the age structure is the same as in PCBS (1999), implying that the age structure of immigrants is similar to that of the existing population living in the West Bank and Gaza.
For the region as a whole, working-age population is expected to grow by 2.7 percent per year over the period 2000–15. compared with population growth of 2.2 percent (Dhonte, Bhattacharya, and Yousef, 2000). The corresponding fates for the West Bank and Gaza are 4 percent and 3.2 percent, if, for comparability, working age is defined as the ages 15 to 64 years old. This chapter uses the PCBS’s definition of working age as those over 15 years old.
Daoud (1999) analyzes female labor force participation and employment in the West Bank and Gaza. His results suggest that the probability of a woman participating in the labor force is negatively affected by the number of children under the age of six. He also finds that Palestinian women do have a preference for working and that female employment and wages rise with years of schooling. He discusses cultural and other factors that might affect female labor force participation.
The numbers for 2001 are influenced by the carryover effects from 2000. That is why the domestic employment in Scenario 2 in Table 2.8 declines by 2 percent even though it grows during the course of the year by 6.7 percent (December 2001 over December 2000).
Of course, labor force participation rates, which ate in part endogenous to employment prospects, might be lower than what the scenarios assume.
See Palestinian Authority (2000), a document prepared with assistance from IMF staff.
Scenario 4 allows for somewhat faster growth in PA employment to accommodate the higher demand for public services that higher population growth would give rise to.
This analysis follows that of Dhonte, Bhattacharya and Yousef (2000). See Appendix I for an explanation of the methodology, including the link between the marginal product of labor and the real wage.
As explained in Appendix I, this does not mean that awarding higher wages would raise productivity.
For example, see Pritchett (1997)
Conditional convergence is also consistent with mean reversion (i.e., reversion of growth to its mean) which casts doubt on whether presence of convergence can be easily established (see Quah, 1993, 1997)
These variables as well as those representing initial conditions have been used by many studies including Levine and Renelt (1992), Barro and Sala-ì-Martin (1995), Easterly and Levine (1997). Bloom and Williamson (1998), and Bloom, Canning, and Malaney (1999). Another commonly used measure of openness is a composite measure created by Sachs and Warner (1995b), but no data on this indicator is available for the West Bank and Gaza.
Productivity might also vary across age-groups (see, for example, Sarel, 1994). This effect is partly taken care of by including initial schooling in the regression analysis.
These two variables have been used by Radelet, Sachs, and Lee (1997), Bloom and Williamson (1998) and Bloom, Canning, and Malaney (1999). Other studies include total fertility rate instead of these two variables (e.g., Barro and Sala-ì-Martin, 1995: and Barro, 1997). The problem with this latter approach is that it focuses on the birth rate and ignores the dynamics arising from infant mortality, both of which affect the demographic transition.
See Kaufmann, Kraay and Zoido-Labaton (1999). These indicators have also been used by Knack and Keefer (1995), Barro (1997), and Commander, Davoodi and Lee (1997).
Subject to the caveat that comparison of variation (through R-squared) is only valid with identical dependent variables, the reported R-squared of 68 percent is higher than what is reported in Barro and Sala-ì-Martin (1995) but lower than that found in Bloom and Williamson (1998). In general, variation in growth is better accounted for by the included variables when using Summers-Heston PPP data for growth and level of per capita GDP than when using the World Bank constant U.S. dollar or the version of PPP data used in this chapter (see Barro and Sala-ì-Martin, 1995; and Commander, Davoodi, and Lee, 1997). The main reason is that Summers and Heston have better managed to account for international price differences in non-traded goods The PPP data used in the regressions in this chapter are nominal PPP per capita GDP in U.S. dollars, taken from the IMF’s World Economic Outlook database, and converted to 1995 U.S. dollars using U.S. implicit GDP price deflator with the base of 1995.
Recent studies show that the rate of convergence can vary from zero to 30 percent a year (see Temple, 1999),
Unless otherwise noted, the impact of each variable on growth is evaluated around the sample average of the variables for the 85 countries. For example, the impact of two years of schooling is obtained as 0.004 × [ln (4.2 + 2) – ln (4.2)] where 4.2 is average years of schooling, and 0.004 is the estimated coefficient on schooling
This is because statistical tests could not reject the hypothesis that the estimated coefficients on the two variables are equal but of opposite sign. For comparison, however, Table 2.10 (columns 2 and 4) shows the results when the two population variables are entered separately. Focusing on the difference in growth rates also makes the analysis of the demographic impact somewhat more intuitive.
The estimate lies between the two sets of estimates reported by Bloom and Williamson (1998) and is the same as that found in Bloom, Canning, and Malaney (1999, Table 5), which uses a smaller sample of countries (70 countries), a different time period (1965–90), and a different estimation technique. They use instrumental variable technique, which allows for possible endogeneity of the population variables whereas the regression analysis in this chapter uses ordinary least squares. The point estimate obtained by Bloom and Williamson (1998) on differences in population growth rate ranges from 1.7 to 3.3.
Half of the countries in the sample had an inflation rate in excess of 10 percent per year.
Including both average inflation and inflation volatility renders both variables insignificant since the two are highly correlated (the correlation coefficient is 0.94); see Fischer (1993). Inflation volatility is defined as the standard deviation of annual inflation in 1970–99.
The coefficient on tropical climate is close to that of Bloom and Williamson (1998), but slightly higher than that of Sachs and Warner (1997). As for the natural resource variable, Sachs and Warner (1995a) also find robust evidence for a negative relation between natural resource intensity and subsequent growth and argue that the growth difference might reflect dynamic Hutch disease effects. Rodriguez and Sachs (1999) suggest that one reason why resource-abundant economies grow more slowly is that they are likely to be living beyond their means. The will converge to their steady-state growth rates from above, displaying negative growth rates in the transition.
Governance data for the West Bank and Gaza exist for 1997 only and not for the entire 1970–99 period. Even though governance-type indicators do not change in the short run, they are quite likely to change over a 30-year period. The regressions shown in Table 2.10 use the sparse data for the West Bank and Gaza, including that of the governance variable. However, eliminating West Bank and Gaza from the sample of 85 Countries and estimating the regressions over the period 1970–99 produces results identical to those shown in Table 2.10.
This finding also holds when using the data for 1970–99, with the difference that the residual is smaller because the output collapse in 1995–96 does not dominate the data.
By contrast, for the period 1970–99. faster growth of total population than working-age population in the West Bank and Gaza reduced real per capita GDP growth by as much as I percentage point each year. It is interesting to note that the demographic factors account for much of the predicted growth in regions that are well into their demographic transition. For example, 85 percent and 32 percent of predicted real per capita GDP growth rate in the MENA region and East Asia, respectively, are due to demographic factors.
As mentioned, a common finding is that countries with ample natural resources tend to grow more slowly than those without such resources, see Sachs and Warner (1995a), and Rodriguez and Sachs (1999).
The policy discussion also builds on the IMF study Alonso-Gamo, Alier, Baunsgaard, and Erickson von Allmen (1999), and Fischer, Alonso-Gamo, and Erickson von Allmen (2001).
In a study of growth in 92 countries, Ramey and Ramey (1995) found evidence that countries with high volatility have significantly lower output growth.
See Kanaan (1998) for private investment and uncertainty in the West Bank and Gaza.
See, for example, Fischer (1993), Ghosh and Phillips (1998), and Sarel (1996). While the results in our regression suggest a negative linear relationship between growth and inflation, in reality the relationship is likely to be nonlinear. Studies focusing specifically on the relationship between inflation and growth have found no evidence that inflation in the very low single digits (1–2 percent) hurts growth, hut the studies do show that higher inflation rates are likely to harm growth. Ghosh and Phillips (1998) put the threshold inflation rate at about 3 percent, above which inflation is considered harmful to economic growth, while Sarel (1996) finds the threshold inflation to be somewhat higher at 8 percent.
See Alonso-Gamo, Alier, Baunsgaard, and Erickson von All-men (1999) and, in particular, Barnett (1998) for discussion of monetary policy under the current exchange rate regime.
Calika (1998) and Kessler provide detailed descriptions of the trade regime under the Paris Protocol. Palestinian Authority Ministry of Economy and Trade (1999) provides a comprehensive description of the export and import procedure as of May 1999.
Amjadi and Yeats (1995) find that high transport costs have caused competitiveness problems for exporters and a consequent erosion in exports in sub-Saharan Africa despite generally favorable tariff preferences awarded by OECD countries.
See, for example, Barro and Sala-ì-Martin (1995), Knack and Keefer (1995), and Hall and Jones (1999).
The study included only one survey for the West Bank and Gaza, whereas the results for other countries are based on six surveys and are therefore more reliable.
See Palestinian Authority (2000). The report Economic Policy Framework—Status Report, May 31, 2000 was prepared by the PA with assistance of IMF staff and is available on the PA’s website www.pna.net.
Furthermore, the absence of clear land titles impedes financial development.
In addition to cross-country applications of growth accounting (for example, Senhadji, 1999; Bosworth and Collins, 1999; and Easterly and Levine, 2000), there are also applications to individual economies in the Middle East and North Africa region: 10 countries in the Middle East and North Africa region (Bisat, El-Erian, and Helbling, 1997); West Bank and Gaza economy over the 1970–90 period (Arnon, Luski, Spivak, and Weinblatt, 1997); Jordan (IMF, 1998); Israel (Sarel, 1999); and Iran, Pakistan and four Arab countries (Dhonte, Bhattacharya, and Yousef, 2000).
Alternative specifications are also possible (see Islam, 1999; Hulten, 2000), which would produce alternative measures of TFP growth rates and TFP levels. A majority of studies, however, rely on a Hicks-neutral specification of technical progress, that is, as in the Cobb-Douglas specification.
Under this formulation, any contributions arising from increasing returns to scale is included in the TFP growth. Similarly, the formulation abstracts from contribution of human capital to output, which will lead to an overestimation of TFP growth to the extent that human capital accumulation makes a positive contribution to growth.
Dhonte, Bhattacharya, and Yousef (2000) do a similar analysis for the MENA region.
In the case of regression analysis, α is estimated based on three types of data: time series data for a given country, data on a panel of countries, or a cross section of countries. Each type of data has its own weaknesses and strengths; see Islam (1999) for details.
See Collins and Bosworth (1996). Estimates for seven Latin American countries range from 0.45 to 0.69 (Elias, 1990) and from 0.52 to 0.86 for 13 Arab countries (Bisat, El-Erian, and Helbling, 1997). Regression analysis has also produced estimates for developing countries well in excess of 0.4; see Kim and Lau (1994) for newly industrialized Asian countries; Bisat, El-Erian, and Helbling (1997) for 13 Arab countries, and Senhadji (1999) for a larger set of developing countries.
See Young (1995) for a study of growth accounting in East Asian countries in which adjustments, for the self employed lower the estimates of the capital share of income.
See Collins and Bosworth (1996); Crafts (1999); and Dhonte, Bhattacharya, and Yousef (2000). This estimate has also been used in a previous study of growth accounting for the West Bank and Gaza in Arnon, Luski, Spivak, and Weinblatt (1997).
A similar calculation of the capital share of income was carried out for 13 Arab countries in Bisat, El-Erian, and Helbling (1997).
The 1995 and 1996 data on GDP and GOS are taken from PCBS (1998a) and the 1997 data from the website of the PCBS.
See Nehru and Dhareshwar (1993), and Collins and Bosworth (1996). The typical values for a sample of 15 OECD countries in recent years (1979–90) is about 4 with estimates ranging from 3 in France and Spain to 5.8 in Finland and Denmark (Mas, Perez, and Uriel, 2000). The rate of return on physical capital stock in developing countries is higher, given these ratios for developed countries, a given value of capital share of income for developed and developing countries, and the assumptions indicated earlier. This finding is consistent with the conventional wisdom about the comparison of the rate of return in developing and developed countries.
The initial year can be set much further back in time, as some studies have done, for example, back to 1900 (for example, Sarel, 1995: and IMF, 1998). This would require generating investment data that are not otherwise available. No independent and reliable source of checking the accuracy of the auxiliary assumptions needed to generate such data is currently available. It is therefore often recommended (see Barro and Sala-ì-Martin, 1995) to rely on an available “long” historical investment series to generate data on capital stock and use only the latter part of the series for growth accounting analysis. The use of different time periods in the chapter is motivated by this consideration.
See Nehru and Dhareshwar (1991), Benhabib and Spiegel (1994), and Collins and Bosworth (1996).