Portugal
Selected Issues Paper
Author: International Monetary Fund. European Dept.
Publication Date:
18 Jan 2013
eISBN:
9781475589498
Language:
English
Keywords:
ISCR; CR; firm; GDP; IMF staff calculation; exchange rate; structural unemployment; potential GDP; physical capital; capital stock; allocative efficiency; Labor productivity; Capacity utilization
Download PDF (909.8 KB)

Portugal’s economy is in deep recession, and the crisis has opened up a large output gap, with severe consequences for employment and government revenue. While the focus is on the medium- and long-term, this analysis also offers insights on how deep the output gap is. It also highlights ways in which policies and reforms can promote growth over the longer haul and suggests that achieving a 2-percent growth rate over the long term—consistent with moderate convergence growth—is a realistic objective.

Abstract

Portugal’s economy is in deep recession, and the crisis has opened up a large output gap, with severe consequences for employment and government revenue. While the focus is on the medium- and long-term, this analysis also offers insights on how deep the output gap is. It also highlights ways in which policies and reforms can promote growth over the longer haul and suggests that achieving a 2-percent growth rate over the long term—consistent with moderate convergence growth—is a realistic objective.

I. How Fast Can Portugal Grow? 1

A. Introduction

1. Higher growth is a matter of urgency in Portugal. The economy is in deep recession, and the crisis has opened up a large output gap, with severe consequences for employment and government revenue. While a cyclical recovery would help alleviate these problems, ensuring sustained high growth is critical to raise incomes to peer levels and facilitate a return to sustainable public finances.

2. This paper aims at assessing Portugal’s potential growth performance. While the focus is on the medium- and long-term, the analysis also offers insights on how deep the output gap is—something important for near-term policy considerations as well as growth perspectives. It also highlights ways in which policies and reforms can—if implemented now—promote growth over the longer haul.

3. The assessment is conducted under an augmented growth-accounting framework and makes use of a variant of the best-practice frontier approach to compare Portugal’s growth performance to peers’. Section B reviews stylized facts about growth and convergence over the past forty years, with a particular focus on developments since the early 90s, when Portugal’s relative growth performance started deteriorating. Section C takes stock of the current situation of Portugal in the cycle and relative to peers. Building up on this historical perspective, the forward-looking analysis (Section D) discusses scenarios for medium- and long–term growth, taking into account the potential impact of structural reforms.

4. The analysis suggests that achieving a 2-percent growth rate over the long term—consistent with moderate convergence growth—is a realistic objective. Based on relatively conservative assumptions for investment, this requires boosting TFP growth to about 1 percent a year. While this implies a significant improvement over the zero-TFP growth experienced since the early 90s, it can be achieved through effective implementation of wide-raging reforms aimed at reducing wage and profit mark-ups and enhancing the business environment. The challenge is that reaching the 2-percent growth mark in the medium-term implies both a rapid turnaround in underlying TFP growth and a recovery (even if modest) in investment, despite strong headwinds from public and private sector deleveraging.

B. Stylized Facts on Portugal’s Growth and Convergence

This section reviews Portugal’s growth and convergence performance over the past forty years. It makes a distinction between the following two phases: (i) solid growth and convergence (mid 70s to early 90s); and (ii) increasingly anemic growth and relative income decline (since the early 90s). It also outlines a set of explanations for the weaker performance during the latter period.

From Solid to Dismal Growth

5. In spite of significant economic difficulties, Portugal’s growth was generally strong from the mid 70s to early 90s.

  • In the wake of the 1974 revolution, Portugal had to deal with a particularly difficult economic and institutional environment. This period, which began on the heels of the first oil shock, was marked by a revolution and increased government intervention, including nationalization of a large part of the production system, price and wage controls, and a non-market-based agrarian reform. Policies turned more market friendly after 1975, and the economy benefited from an IMF-supported program to address external imbalances. This allowed GDP growth to average about 3½ percent over 1974–79, supported by a rapid expansion of the labor force and capital accumulation, and in spite of declining TFP (Box I-1).

  • The 80s were marked by a second IMF-supported stabilization program (1983–85) and the entry into the European Economic Community in 1986. After that, the economy benefited from further opening-up and liberalization and deepening of European integration. Real GDP growth also averaged about 3½ percent over this period, supported by TFP growth of about ½ percent per year.

Portugal. Growth Accounting (1974-1991)

article image
Sources: Des Neves (1995); and IMF staff calculations.

6. Over this period, the country experienced some labor productivity convergence. Output per (full-time) employee grew by close to 2½ percent per year on average over 1974-91, compared to annual average growth rates of about 1¼ percent in the US and 2 percent in the EU’s best performing countries (EU-9).2 Consequently, the large convergence setback in the early 70s was more than made up for over this period, with relative labor productivity peaking at its highest level (about 50 percent relative to EU countries) around 1990.

Growth Accounting and Best-Practice Production Frontier Frameworks

The paper uses an augmented growth-accounting framework to study production factors’ contributions to growth and the best-practice production frontier approach to assess convergence in a cross-country context.

The growth accounting framework is based on the following traditional Cobb-Douglas production function augmented with human capital (Mankiw et al, 1992) and capacity utilization rates

ln(Y)⁢ = α⁢ ln(K×C⁢U⁢R)⁢ + (1 −α)⁢ln(W⁢A⁢P ×L⁢P×(1 −U)×H⁢o⁢u⁢r ×h)⁢ + ε

where Y denotes output, α is the capital share for the sample period (about 37 percent), K is the capital stock, CUR stands for the capacity utilization rate, WAP is the working age population, LP the labor participation rate, u the unemployment rate, Hour is a conversion factor to full-time employment, and h denotes human capital per labor. Total factor productivity (ε) is derived as the residual.

Following Hall and Jones (1999), the growth of human capital, dln(h), is assumed to follow a piecewise-linear function of schooling, where the slope of each linear piece is based on Psacharopoulos’ (1994) survey of return-to-schooling. A 13.4-percent rate of return is assumed for the first four years of education; 10.1 percent for the following four years—corresponding to world average; and education beyond the eighth year is assumed to yield OECD-type returns (6.8 percent).

Capacity utilization fluctuates along the business cycles, capturing the impact of demand shocks on the flow of services provided by a given capital stock. Therefore, including capacity utilization rates helps isolate the permanent change in productivity from the impact of cyclical downturns. This is particularly useful for analysis during short time spans, such as during the current crisis.

Due to data availability constraints for the longer time period, the evolution of TFP for the cross-country analysis is estimated using a simplified model without taking into account the capacity utilization: ln(Y) = α ln(K) + (1 – α) ln(L × h) + ε

Best-practice production frontiers are equivalent to curves that depict—for a given year and a given level of human capital—the highest possible level of labor productivity (Y/L) for varying stocks of capital per unit of labor (K/L). These are based on the idea that TFP can be divided into (i) technical efficiency—representing the knowledge ex ante as to how best combine factors of production; assumed to be common to all countries and increasing exogenously through time with the global pace of technological innovation; and (ii) allocative efficiency—representing how effectively factors are actually used in practice depending on country-specific circumstances. Lower efficiency in the use of capital and labor may arise from various sources, such as poor functioning of market institutions or a low level of human capital that prevents profitable use of the best available technologies.

Instead of estimating the best-practice frontiers econometrically, the paper uses the US TFP as the benchmark. Since the technical efficiency component is common to all countries, the differences in country-level TFP relative to the US are assumed to reflect primarily relative allocative efficiency. Production frontiers for different levels of relative efficiency are derived, where for a given level of capital per unit of labor, the vertical difference with the US (benchmark) frontier reflects the difference in labor productivity due to (i) human capital and (ii) allocative efficiency. Although the U.S. may not be the country with the best allocative efficiency at all points in time, it seems to be a reasonable approximation in view of its particularly high TFP and technological advancement. This approach also has the advantage of being easier to replicate; and results do not differ significantly than those proposed by other authors.1

1 See for instance Tiffin (2006 and 2012) who estimates best-practice production frontiers stochastically, including to study growth prospects, respectively for Ukraine and the euro area periphery

7. However, convergence over 1974–91 was mainly the result of the Portuguese economy rapidly becoming more capital intensive. Allocative efficiency—measured as relative TFP—remained virtually at the same level over the period, with the exception of a few sub-periods of ups and downs reflecting economic difficulties. Convergence in income levels was mainly driven by the accumulation of physical capital, with the relative stock of capital per employee growing strongly (see charts) as a result of strong growth of public and private sector investment growth. An increase in relative human capital also contributed to the convergence process (Figure I-1).3

Figure I-1:
Figure I-1:

Contributions to Relative Labor Productivity 1/

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; Eurostat; Bank of Portugal; INE; Barro and Lee (2010); and IMF staff calculations.1/ EU-9 includes a group of 9 EU member countries: Austria, Belgium, Denmark, Finland, France, Germany, Netherlands, Sweden and UK.
uA01fig01

Relative Output per Labor

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; and IMF staff calculations.
uA01fig02

Relative Capital Per Labor

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO: and IMF staff calculations.
uA01fig03

Relative TFP

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

8. Growth became increasingly weak from the early 90s, marking the end of the convergence process. Since the early 90s, labor productivity has remained broadly stable vis-à-vis that of the best performing EU countries—reflecting some convergence in the stock of capital per employee—while declining substantially with respect to the US’. This turnaround reflected mainly a decline in relative TFP. In particular, average real GDP growth gradually declined to only about 1½ over 2000–07. The contributions of capital and labor both dropped, and TFP growth turned negative.

uA01fig04

Contribution to Growth

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; Barro and Lee (2010); and IMF staff estimates.

Why Did the Economy Run Out of Steam Since the Early 90s?

9. The weaker growth performance and lack of convergence over the past two decades can be explained by several self-reinforcing factors. In the face of shocks that brought both challenges and opportunities, weak institutions and failed policies prevented the economy from adapting quickly and maintaining strong productivity growth.

10. A domestic demand boom was fueled by strong capital inflows in the run up to the euro adoption. The new era of exchange rate stability in the run-up to the euro adoption in 1999 led to a strong surge in capital flows. This surge served to amplify the impact of Portugal’s existing distortions—weak financial supervision and risk management, inflexible labor market, and lack of competition in non-tradable sectors—contributing to growing macroeconomic imbalances. With a financial sector mostly liberalized and increased bank competition, higher inflows quickly turned into lower funding costs for enterprises and consumers (Almeida et al., 2009). In combination with a marked increase in official inflows (including in the form of EU structural funds), these developments led to a strong domestic demand growth—particularly directed toward non-tradable goods and services, a decrease in unemployment and rapid attendant increases in wage, unit labor costs, and inflation. Consequently, the real effective exchange rate further appreciated—following a marked appreciation after EU membership—which, in turn, favored domestic demand over exports, leading to growing macroeconomic imbalances.

uA01fig05

Capital Inflows

(Percent of GDP, 5-year MA)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: IFS; WEO; and IMF staff calculations.

11. With a low degree of competition and high mark-ups in network industries, construction, real estate, and wholesale/retail trade, capital flows were increasingly directed towards these sectors, where productivity growth was lagging. There was also under-investment in machinery and equipment where returns are known to be higher. Excessive profit markups in non-tradables also weighed on tradable sector profitability directly through high intermediate input costs. In addition, the lack of labor market flexibility encouraged wage increases not sufficiently sensitive to the competitive requirements of the tradable sector. Portugal’s uniquely strong labor protection may also have prevented the more productive firms from growing to their optimal size, thereby constraining output per capita (Braguinsky et al., 2011). Finally, the government ran a pro-cyclical fiscal policy over the period, which exacerbated the pressures on domestic demand. Expenditure was geared toward nonproductive investments, particularly in non-tradable sectors.

uA01fig06

Tradables and Non-Tradables, 1992-2007

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; and IMf staff calculations.

12. Externally, further liberalization of world trade—notably China’s entry into the global supply chain and the gradual dismantling of the quotas under the Multi-Fiber Arrangement by end 2004—as well as the European Union’s expansion into Eastern Europe meant that that Portugal had to face more intense competition, particularly in the manufacturing and agriculture sectors. This weighed on the country’s competitive advantage but also meant that Portugal had to compete for foreign investment with the new EU members.

13. Portugal’s significant human capital gap prevented the country from moving up the global value-added chain to tackle this increased competition and to benefit from new technologies. Despite its gradual modernization and relative expansion since the 1960s, the education system remained underdeveloped until the 2000s when it finally reached some of the developed world’s best practices and trends.4However, the secondary education graduation rates and the overall labor force education level remain low (see chart). And while the difference in stocks of human capital has been shown to explain a large part in difference in per-capita income level across countries, there is also evidence that the stock of human capital can influence the TFP convergence speed (see chart). The relatively low level of education may have hindered the adoption of the information and communications technologies (ICTs), especially during the 1995–2005 decade, when there was a global boom in the use of ICTs (see chart).5

uA01fig07

Convergence in Human Capital 1/ (1992–2007)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; Barroand Lee (2010);and IMF staff estimates.1/ A larger ballloon denotes a higher level of humancapital per labor, constructed based on Barro and Lee (2010).
uA01fig08

Proportion of Labor Force with Secondary and Tertiary Education

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Source: World Development Indicators
uA01fig09

Internet Users

(Per 100 People)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

14. The business climate was especially weak, with high incidental costs of doing business reflecting, among other things, inefficient judiciary, bureaucratic red tape, and governance and business climate indicators ranking among the lowest compared to peers. This further discouraged investment in non-protected sectors. Generally speaking, TFP convergence tends to be faster when market institutions are more developed (see chart).

uA01fig10

Convergence in TFP and Institutions 1/ (1992-2007)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: OECD; AMECO; and IMF staff estimates.1/ A larger ballloon denotes more difficulty in starting a business, according to OECD 2004 ranking.

15. Finally, an increasingly leveraged economy hindered investment and productivity gains, contributing to the dismal growth performance. With a tax system favoring debt over equity financing, much of the capital inflows during the pre- and post-euro adoption period were in the form of debt, leading to a high corporate leverage. While capital inflows increasingly supported consumption, excess leverage may in turn have had a negative impact on investment, as over-indebted firms tend to pass up on new investment opportunities, particularly those with limited short-term benefits but higher long-term productivity gains.6 The negative relationship between leverage and investment is well established in the literature.7 In the case of Portugal, investment growth peaked in 1997 and then gradually declined to turn negative, as leverage was increasing (see chart). Excess leverage may also have directly hindered productivity growth (Pal et al., 2012).8

uA01fig11

Portugal: Investment Growth and Corporate Debt, 1995-2011

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: Eurostat and WEO.

16. In contrast to Portugal, many other euro area countries managed to reap the full benefits of monetary integration and the technological advances. Ireland, for example, experienced a remarkable performance over the past two decades (Amador et al., 2007). Modern economic institutions and a highly educated and flexible workforce allowed the country to orient inflows toward the most promising activities and benefit from an acceleration of TFP.

uA01fig12

Relative TFP

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; and IMF staff estimates.

C. Taking Stock—Where Does Portugal Stand in 2012?

17. The financial crisis has opened a large output gap. Domestic demand collapsed during 2008–12 (with an average contribution to growth of -4 percent). At the same time, the unemployment rate rose from 8 percent in 2007 to some 16 percent in the third quarter of 2012. These developments partly reflect structural changes, as the economy rebalances toward tradables. And the deep contraction in non-tradables forces a difficult re-allocation of the labor force, with tradables not yet able to absorb these flows. The output gap is estimated to have reached some 4 percent in 2012, with a structural unemployment rate of close to 13 percent (Box I-2).

18. There is uncertainty as to how quickly the output gap can be closed, particularly in view of the strong headwinds to the cyclical recovery. The still large competitiveness gap is an immediate constraint. The ongoing public and private sector deleveraging—necessary to reduce the high debt burdens and thus pre-conditions for sustained future growth—also represents a strong impediment to output growth in the next few years.

19. But there are also reasons for optimism. External adjustment has taken place at a faster pace than expected, even in the absence of significant improvements in price-competitiveness indicators. As these materialize and economic activity in the euro area normalizes, the export sector is likely to provide some persistent support to growth. Moreover, private sector investment is estimated to have declined by about 35 percent cumulatively since the peak in 2007, leading to a reduction in the capital stock of about 1 percent. A further expansion of exports would soon hit capacity constraints providing impetus for a modest increase in investment in the medium-term.

Potential Output and Output Gap

Potential output is estimated under the augmented growth accounting framework presented in Box I-1, by stripping cyclical components out of the factor inputs and total factor productivity.1 The model is estimated for a sample period from 1987 through 2017 (based on IMF staff medium-term projections).

  • Factor inputs. The structural unemployment rate is estimated by the European Commission. It is derived by estimating a Phillips curve with a Kalman filter technique where the NAIRU is treated as an unobserved variable. And the equilibrium labor market participation rate and equilibrium capacity utilization rate are derived through HP filter.

  • Trend TFP. By construction, the TFP derived from the capacity utilization augmented growth model should not be affected by cyclical factors.2 It is further smoothed by HP filter to remove any remaining cyclical factors to be used for trend TFP.

  • Potential output is the aggreate of these smoothed factor inputs.

The output gap is estimated to have reached some 4 percent in 2012, with a structural unemployment rate of close to 13 percent.

uA01fig13

Output Gap

(Percent of potential GDP)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; INE; and IMf staff estimates.
uA01fig14

Structural Unemployment

(Percent)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

1 Compared to pure HP-filter, this method attends more to potential relevant economic information. However, the trend developments of most factors are derived using HP filter. This method thus potentially suffers from same shortcomings as the HP-filter, such as being slow in discovering structural breaks (which during a recession would overestimate potential GDP and the output gap) as well as the “end-point problem”.2 Some caution is warranted when interpreting these results. Manufacturing capacity utilization may be more volatile than the whole economy capacity utilization. In this case, the TFP derived using only manufacturing capacity utilization may be overestimated. HP-filter series would then overestimate the trend TFP, leading to an overestimated negative gap.

20. Beyond cyclical developments, Portugal’s labor productivity gap compared to its peers is very large, making it more likely that a strong reform effort will indeed foster income convergence. Even after adjusting for capacity utilization—which dropped from some 82 percent to close to 75 percent during 2008–12, TFP declined by an annual 0.2 percent over the period. As a result, notwithstanding the convergence until the early 90s, Portugal is left with one of the largest gaps of per-capita income among EA countries:

uA01fig15

Portugal vs Best Practice Frontier

(Thousands of constant 2006 euros)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; Eurostat; Bank of Portugal; INE; Barro and Lee (2010); and IMF staff calculations.

  • Labor productivity in Portugal represents only 45 percent of the US’s and about half of productivity in the richer EU countries.

  • About one-third of the gap with the US is attributable to a gap in the stock of physical capital;

  • One-third of this cross-country difference in labor productivity is explained directly by the difference in the stock of human capital;

  • And the rest of the labor productivity gap (some 40 percent) reflecting allocative inefficiencies, in turn related to the human capital and structural policy gap.

These gaps vis-à-vis the peers and the lagging business environment should make it even easier to engineer a rapid catch up.

D. Prospect for Medium- to Long-Term Growth: Potential Gains from Structural Reforms

In response to the massive TFP shortfall and the need to resume convergence growth, the Portuguese authorities have embarked on an ambitious set of structural reforms. This section considers the effect these reforms can have on medium- and long–term growth.

The Impact of Structural Reforms on Growth: Empirical Evidence

21. Portugal has launched a wide-ranging structural reform program aimed at boosting competitiveness and growth (Table I-1):

Table I-1.

Portugal: Labor and Product Markets Since 2011

article image

  • Labor market reforms. Steps are being taken to reduce severance payments and unemployment benefits, and rationalize automatic extension of collective bargaining agreements. These should increase labor mobility and help wages adapt to firm- or sector-level conditions, with a positive bearing on employment and productivity.

  • Product market reforms. Excessive product market regulation has contributed to high mark-ups and low output, investment, and employment. As noted earlier, high profit mark-ups in the non-tradable sector have impeded the competitiveness of the tradable sector. To address these problems, reforms to reduce the regulatory burden and improve competition are in train. Significant steps have already been taken, including to abolish the state’s special rights in companies, revise the Competition Law, liberalize restricted professions, and reduce mark-ups in network industries, particularly in the electricity and telecommunications sectors.

  • Improved business environment. Licensing procedures are being streamlined. Judicial reforms are also advancing, aimed at addressing slow judicial processes, weak court management, and the severe backlog of cases that have created serious obstacles to efficient economic activity. A new corporate insolvency framework should also facilitate private sector debt workouts. Over time, these reforms are expected to make Portugal a more attractive destination for investment and facilitate convergence in the allocative efficiency (see paragraph 6).

22. Empirical evidence points to potentially significant long-term pay-offs from a package of comprehensive structural reforms along the lines described above. Four key findings emerge from the recent empirical studies (Table I-2):

Table I-2.

Selected Studies on the Impact of Labor and Product Market Reforms

article image

  • In the long run, product and labor market reforms can enhance TFP, labor productivity, and employment rate (Barnes et al., 2011), and the overall potential GDP gain for the average OECD country could reach 4½ and 10 percent at 5- and 10-year horizons, respectively (Bouis and Duval, 2011). Reforms aimed at deregulating product markets, especially network industries, could increase the probability of exiting a low-growth spell (Lusinyan and Muir, 2012).

  • In the short run, the impact of reforms is mixed. While reforms could generate positive confidence, income and wealth effects via expected reform-driven changes in future incomes, households may perceive higher income insecurity in the wake of certain reforms, leading to higher precautionary savings and lower demand. In addition, some labor market reforms (e.g. of unemployment benefit and job protection) can even entail short-term losses in severely depressed economies (Bouis et al., 2012; Cacciatore et al., 2012).

  • A broad reform package is more beneficial than individual reforms as the former can help minimize or even alleviate the transitional costs (Cacciatore et al., 2012).

  • Cross-country coordination of reforms could produce larger and more evenly distributed positive effects (Gomes et al., 2011; IMF, 2012).

23. Portugal-specific empirical studies confirm potentially sizable positive effects of structural reforms on GDP and productivity. In particular:

  • Barnes et al. (2011) link together a range of empirical studies (mostly carried out by the OECD) under an accounting framework of reduced-form equations that explain individual sub-components of GDP per capita. The findings suggest that, out of the 35 percent income gap in 2009 between Portugal and the OECD average, some 7 and 9 points are due to gaps in labor and product market policies, respectively, with the rest is due to the gap in human capital. The results also point to potentially sizable positive effects from various structural reforms (see table).

  • Under a similar framework, Bouis and Duval (2011) find that, with a broad package of reforms implemented within a five-year time period, per capita GDP could be boosted by 6 percent in the first five years and 14 percent after 10 years.

  • Finally, Gomes et al. (2011) simulate EAGLE (Euro Area and Global Economy model)—a large scale DSGE model—calibrated for Portugal. The results suggest that the real output could be close to 8 percent higher by lowering mark-ups by 15 percentage points in Portuguese labor and services markets.

Long-term Effect of Structural Reforms on GDP Per Capita

(Percent deviation from the baseline)

article image
Source: Barnes, et al. (2011) “The GDP impact of reform: A simple simulation framework”. (OECD Economic Depeartment Working Paper No. 834.)

Four Long-Term Scenarios

Four long-term growth scenarios are considered, assuming various degrees of impact of structural reforms. Reforms are assumed to have an impact through three main channels: (i) improving TFP growth; (ii) increasing labor participation and employment rates; and (iii) allowing for a more rapid improvement in the structural unemployment rate. The quantitative impact of reforms is calibrated so as to be broadly consistent with the studies mentioned above.

Key Assumptions

24. Investment and capital stock accumulation dynamics play an important role in these four scenarios. On the one hand, the crisis has brought the investment ratio down to a level unseen since the mid-1980s. On the other hand, the debt overhang is now more acute, raising questions as to how the necessary investments can be financed, especially in view of the deleveraging process and related tight credit conditions. The simulations are based on the assumption of a gradual recovery in investment rate to about 20 percent by 2032 across all four scenarios. This is below the 20-year average of 21¼ percent and above the projected medium-term average of 16½ percent. In view of the current account projections (balanced by end of medium term), this implies a gradual increase in the saving rate to about 20 percent, compared to the 20-year average of 16 percent. Keeping the investment ratio constant across scenarios implies self-reinforcing positive capital-accumulation-growth dynamics at play.

uA01fig16

Investment

(Percent of GDP)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Source: AMECO
uA01fig17

National Saving

(Percent of GDP)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

25. Working age population is assumed to decline over the long term, based on the Eurostat projection which reflects a possible scenario of trends in fertility, mortality, and migration. However, the projection does not assume that the recent pickup in the emigration will continue into the medium and long term. Therefore, in the less optimistic scenarios with worse growth prospects, the risk of higher emigration than currently envisaged is non-trivial, in particular that of younger and better educated Potuguese. Should this risk materialize, it would put downward pressure on growth. On the other hand, if the optimistic scenario becomes more likely, the country may attract more immigrants which would further enhance the growth.

26. Human capital accumulation is assumed to contribute 0.4 percentage points to growth annually, broadly in line with what has been experienced in the past two decades. This is yet another conservative assumption considering the still very large gap with other OECD economies. However, education reforms take several generations to make a significant difference for all age cohorts, because policies can only directly influence the length of education and PISA scores for the 15–24 age cohort (e.g., Barnes et al., 2011). In the case of Portugal, progress has been made in raising both the level and the quality of education, particularly in the younger cohort, but the investment in this area was made less efficiently than it should be (see charts). In view of this and in the context of severely constrained public finances, human capital reforms have to be phased in gradually and can only rely on increasing efficiency rather than additional budget allocations (Lemgruber and Soto, 2012).

uA01fig18

Total education spending to average PISA Score

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: OECD; Eurostat; and IMF staff calculations
uA01fig19

Total Education Spending to Secondary School Graduation Rates

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Main Results

27. The starting point of the simulation is a moderately pessimistic scenario in which reforms have a limited impact—TFP increases by ½ percent a year, so at a slightly faster pace than since the early 90s, but there are no gains in allocative efficiency (Box I-3). In this case, real GDP growth averages 1.2 percent over the long term, with relative labor productivity remaining broadly stable compared to the US and falling back to its low levels in the 1980s. Should reforms be delayed or should actual implementation lag, long-run growth could also end up much lower. Assuming zero TFP growth (as experienced since the early 90s) in the pessimistic scenario would imply growth of about ½ percent a year and a continuation of the relative decline compared to peers.

28. But assuming a moderate impact of the ongoing structural reforms, a real output growth of about 2 percent on average in the long run appears to be a reasonable conjecture. Staff’s baseline scenario assumes that all the reforms planned under the program are fully implemented and bear fruits over the long term, although to a lesser extent than suggested by the literature reviewed above (Figure I-5).

Figure I-2.
Figure I-2.

Relative Labor Productivity – Key Sectors 1/

(Average percent change)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; and IMF staff calculations.1/ EU-9 includes a group of 9 EU member countries: Austria, Belgium, Denmark, Finland, France, Germany, Netherlands, Sweden and UK.
Figure I-3.
Figure I-3.

Contribution to Growth – Key Sectors 1/

(average percent change)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; and IMF staff calculations.1/ EU-9 includes a group of 9 EU member countries: Austria, Belgium, Denmark, Finland, France, Germany, Netherlands, Sweden and UK.
Figure I-4.
Figure I-4.

Contribution to Growth – Demand Side 1/

(Percentage points)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; Eurostat; Bank of Portugal; INE; Barro and Lee (2010); and IMF staff calculations.1/ EU-9 includes a group of 9 EU member countries: Austria, Belgium, Denmark, Finland France, Germany, Netherlands, Sweden and UK.
Figure I-5.
Figure I-5.

Four Scenarios Under Structural Reforms

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; Eurostat; Bank of Portugal; INE; and IMF staff calculations, projections and estimation.

  • Reflecting the positive impact of structural reforms, TFP is assumed to grow at 1 percent in the long run. This is slightly higher than the projected 0.8 percent for the US (based on OECD projections—see Box I-3), but less than half that experienced by Portugal immediately after the EU accession (2¼ percent over 1986–92). In comparison, over 2000–07, Netherlands and Sweden experienced average TFP growth rates of 0.7 percent and 1.6 percent, respectively, after a comprehensive package of reforms in labor and product markets during 1980s–90s.

  • Capital stock accumulation is projected to resume by the end of medium term—a somewhat conservative assumption, contributing 0.5 point to the annual growth, while the increase in labor participation and employment are assumed to offset the decline in working age population—leading to zero contribution from labor input.

  • Human capital accumulates at the same rate as during 1999–2007, contributing 0.4 point to the annual growth.

  • As a result, the cumulative increase of GDP per capita compared to the no-reform (or lack of impact thereof) scenario amounts to about 5 percent by 2022, and 8 percent by 2027. This is much less than implied by the literature on average.

  • Under the baseline, the labor productivity gap with the US narrows only very gradually over the long term (see chart below).

Level of GDP per capita, relative to moderately pessimistic

article image

29. In a somewhat more optimistic scenario where the structural reforms unleash an even higher potential TFP growth, real output grows by some 2½ percent per year. The higher TFP growth (at 1½ percent on average) also encourages firms to hire more and invest more, especially in machinery and equipments, which as some empirical studies suggest leads to higher output growth (De Long and Summers, 1991). The labor productivity gap with the US narrows at a faster pace—although, at this pace, it would still take some 15 years (by 2028) to bring Portugal’s relative labor productivity to the level achieved in the early 1990s. Growth could even be higher under a less conservative assumptions regarding capital accumulation.

uA01fig20

Contribution to Growth: 2018–32

(Percentage point)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Source: IMF staff estimates.
uA01fig21

Output per worker

(EU-9=100)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: AMECO; and IMF staff estimates.
uA01fig22

TFP

(EU-9=100)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Four Scenarios for the Steady State

Key Common Assumptions

  • US long-term growth: The paper uses OECD projections of long-term real GDP growth (2.4 percent), investment-GDP ratio (16½ percent), and employment growth (0.9 percent).

  • US technical progress: For a given initial capital stock, long-term growth projections imply TFP growth of about 0.8 percent per year. We assume (ad hoc) this can be split between 0.4 percentage point from technical progress and 0.4 point from improvement in allocative efficiency.

  • Total and working age population in Portugal: Based on Eurostat projections and reflecting demographic trends, total population growth is flat, while working age population (age 15–64) declines by 0.3 percent per year on average in the long run.

  • Human capital accumulation in US and Portugal: Human capital accumulates at the same pace as in the past 20 years, at 0.3 percent in the US and 0.6 percent in Portugal.

Four Scenarios

Pessimistic Scenario

  • Reforms do not bear fruit (or reform implementation encounters major setback).

  • TFP remains flat—not only aren’t there efficiency gains, but Portugal does not enjoy the benefit of the global technical progress. Relative TFP vis-à-vis the US continues to decline at the same pace as experienced in the past 20 years.

  • The average growth rate is 0.6 percent, based equally on physical and human capital accumulation.

Moderately Pessimistic Scenario

  • Some positive spillover from the ongoing rebalancing of the economy towards net exports-led growth—or economy moving towards sectors with higher productivity growth—although, similar to the pessimistic scenario, it assumes no structural reforms.

  • TFP grows faster at around ½ percent a year—the relative efficiency continues to decline, although at a slower pace than what was experienced in the past 20 years.

  • The downward trend in relative labor productivity is stopped by 2032.

  • The contribution to the 1.2 percent average growth is equally shared by physical and human capital accumulations, and TFP growth.

Baseline Scenario

  • This scenario incorporates the impact of the structural reforms currently taking place. It assumes that the ongoing reforms will be fully implemented within a 5-year time period.

  • TFP grows faster at around 1 percent a year—the relative efficiency starts increasing, although at a slow pace. TFP growth contributes half to the growth of 1.9 percent, with the rest contribution shared by physical and human capital accumulation.

  • Structural unemployment is to decline to 11–12 percent, supported by labor market reforms that reduce severance payments and unemployment benefits.

Optimistic scenario

  • This scenario is even more optimistic regarding the impact of structural reforms—broadly consistent with the more optimistic views/estimates about the potential impact of reforms.

  • TFP grows at around 1½ percent a year—the relative efficiency increases faster than in the baseline. TFP growth contributes more than half to the growth of 2.7 percent, with the remaining contribution due to physical and human capital accumulation.

  • Structural unemployment is to decline to below 10 percent, supported by labor market reforms that reduce severance payments and unemployment benefits, as well as stronger TFP growth, which spurs more hiring by firms.

Medium-Term Growth Prospects

30. While a 2-percent growth appears feasible in the long-term, reaching this mark in the medium-term implies a rapid turnaround in TFP growth and a modest recovery in investment. Taking into account a pickup in the capacity utilization and employment over the next 3–4 years, TFP growth would need to rapidly converge toward about 0.7 percent a year, and investment rates toward about 17 percent. This would imply investment growth of about 4 percent (Figure I-6); and in these circumstances, investment growth would still not be sufficient to generate a positive contribution of capital accumulation to growth. Under staff’s baseline scenario, output would bottom out in 2014 and growth would gradually pick up to near 2 percent—implying an average growth of about 1.5 percent over 2014–17—and the output gap would be closed by 2017. Depending on confidence effects and the headwinds to growth from deleveraging in the public and private sectors, various scenarios can be envisaged for the TFP and investment growth implying average output growth rates of between 1 and 2 percent (see chart).

Figure I-6.
Figure I-6.

Baseline: Potential Output—Capital and TFP

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Sources: Ameco; Eurostat; INE; and IMF staff estimates, calculations and projections.
uA01fig23

Contribution to Growth: 2014-17

(Percentage points)

Citation: IMF Staff Country Reports 2013, 019; 10.5089/9781475589498.002.A001

Source: IMF staff estimates.

E. Conclusion

31. The paper aims to assess Portugal’s potential growth performance over the medium- to long-term. The evaluation is underpinned by a backward-looking analysis of growth and convergence, and in particular of the massive TFP shortfall and lack of convergence experienced since the early 90s. It outlines how the institutional set-up and policy response were inadequate to absorb the various shocks faced by the economy over this period and how the large human capital gap prevented the country from moving up the global value-added chain to tackle increased competition and benefit from new technologies.

32. The forward-looking analysis, however, assumes that the authorities’ ambitious structural reform agenda delivers on its promise to address these institutional and policy gaps and boost TFP growth significantly. On this basis, achieving a 2-percent growth rate over the long-term—consistent with resumption of moderate convergence growth—appears to be a realistic objective. The challenge is that reaching the 2-percent growth mark in the medium-term implies both a rapid turnaround in underlying TFP growth and a recovery in investment.

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1

Prepared by Huidan Lin and Stéphane Roudet. Upaasna Gupta provided excellent research assistance. We are grateful to the staffs from Banco de Portugal, the Ministry of Economy and Employment, and the Ministry of Finance for their helpful comments. The usual disclaimer applies.

2

This includes a group of 9 EU member countries: Austria, Belgium, Denmark, Finland, France, Germany, Netherlands, Sweden, and UK.

3

Taking into account the relative increase in the number of hours worked in Portugal—which can generate a bias in the TFP calculations if not accounted for—does not fundamentally affect these results.

4

In particular, the new generation possesses education comparable to other advanced economies. According to the OECD’s Programme for International Student Assessment (PISA) for 2009, the average Portuguese 15-years old student, when rated in terms of reading literacy, mathematics and science knowledge, is placed at the same level as those students from the United States, Sweden, Germany, Ireland, France, Denmark, United Kingdom, Hungary and Taiwan Province of China.

5

This argument is also often cited as a reason for the difference in productivity growth between the U.S. and Europe during this period (Van Ark et al., 2008).

6

This reflects for instance higher funding costs stemming for asymmetric information between firm managers and lenders, as well as fear of bankruptcy when leverage is high and investment opportunities riskier. Stein (2001) provides a comprehensive review of the modern finance literature on this topic.

7

See Jaeger (2003) and Goretti and Souto (2012) for recent examples.

8

Pal et al. (2012) estimate a threshold regression model on a sample of Central and Eastern European countries. The study confirms that TFP growth increases with leverage until the latter reaches a critical threshold beyond which leverage lowers TFP growth.

Same Series

Other IMF Content

Other Publishers

Cover IMF Staff Country Reports
Portugal: Selected Issues Paper
Author: International Monetary Fund. European Dept.
Volume/Issue:
Volume 2013: Issue 019
Publisher:
International Monetary Fund
ISBN:
9781475589498
ISSN:
1934-7685
Pages:
103
DOI:
https://doi.org/10.5089/9781475589498.002

Contributions to Relative Labor Productivity 1/

Relative Output per Labor

(Percent)

Relative Capital Per Labor

(Percent)

Relative TFP

(Percent)

Contribution to Growth

(Percent)

Capital Inflows

(Percent of GDP, 5-year MA)

Tradables and Non-Tradables, 1992-2007

(Percent)

Convergence in Human Capital 1/ (1992–2007)

Proportion of Labor Force with Secondary and Tertiary Education

(Percent)

Internet Users

(Per 100 People)

Convergence in TFP and Institutions 1/ (1992-2007)

Portugal: Investment Growth and Corporate Debt, 1995-2011

(Percent)

Relative TFP

(Percent)

Output Gap

(Percent of potential GDP)

Structural Unemployment

(Percent)

Portugal vs Best Practice Frontier

(Thousands of constant 2006 euros)

Investment

(Percent of GDP)

National Saving

(Percent of GDP)

Total education spending to average PISA Score

Total Education Spending to Secondary School Graduation Rates

Relative Labor Productivity – Key Sectors 1/

(Average percent change)

Contribution to Growth – Key Sectors 1/

(average percent change)

Contribution to Growth – Demand Side 1/

(Percentage points)

Four Scenarios Under Structural Reforms

Contribution to Growth: 2018–32

(Percentage point)

Output per worker

(EU-9=100)

TFP

(EU-9=100)

Baseline: Potential Output—Capital and TFP

Contribution to Growth: 2014-17

(Percentage points)