II. Investment and Growth in Cameroon 30

International Monetary Fund

doi:10.5089/9781451807998.002.A002

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II. Investment and Growth in Cameroon ³⁰

Author: International Monetary Fund

Publication Date:: 03 Dec 1996

eISBN:: 9781451807998

Language:: English

Keywords:: ISCR; CR; enterprise; export; GDP ratio; export commodity; Cameroonian authorities; commodity export; CFA franc; Public enterprises; Agricultural commodities; Exports; Private investment; Sub-Saharan Africa; Southeast Asia; velocity of circulation; government revenue; private sector investment; production function; Human capital; Public investment spending; Government debt management

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Notwithstanding the secular decline in real GDP experienced during the period 1987–93, the Cameroonian economy was the largest in the CFA franc zone in 1995, with a GDP of about US$9 billion.31 Compared with other sub-Saharan African countries, Cameroon has one of the most diversified production and resource bases, as it produces and exports a broad range of commodities, including oil, coffee, cocoa, cotton, bananas, natural rubber, palm oil, timber, and aluminum. Cameroon is a net oil exporter, and although oil production has been declining steadily since 1986, it still amounted to 37 million metric tons in 1996 and represented 13 percent of GDP. Nevertheless, agriculture has remained the mainstay of the economy and employs over 70 percent of the labor force. Cameroon is a member of the French franc zone and its currency, the franc de la Communauté Financière en Afrique Centrale (CFAF), issued by the Banque des Etats de l’Afrique Centrale (BEAC),32 is pegged to the CFA franc at the rate of CFAF 1 = F 0.01.33 Cameroon is also a member of several regional organizations, including the Customs Union of Central African States (UDEAC) and the Central African Monetary and Economic Union (UMOEA).

Abstract

A. Introduction

Notwithstanding the secular decline in real GDP experienced during the period 1987–93, the Cameroonian economy was the largest in the CFA franc zone in 1995, with a GDP of about US$9 billion.³¹ Compared with other sub-Saharan African countries, Cameroon has one of the most diversified production and resource bases, as it produces and exports a broad range of commodities, including oil, coffee, cocoa, cotton, bananas, natural rubber, palm oil, timber, and aluminum. Cameroon is a net oil exporter, and although oil production has been declining steadily since 1986, it still amounted to 37 million metric tons in 1996 and represented 13 percent of GDP. Nevertheless, agriculture has remained the mainstay of the economy and employs over 70 percent of the labor force. Cameroon is a member of the French franc zone and its currency, the franc de la Communauté Financière en Afrique Centrale (CFAF), issued by the Banque des Etats de l’Afrique Centrale (BEAC),³² is pegged to the CFA franc at the rate of CFAF 1 = F 0.01.³³ Cameroon is also a member of several regional organizations, including the Customs Union of Central African States (UDEAC) and the Central African Monetary and Economic Union (UMOEA).

The recent history of Cameroon’s economic development is characterized by two sharply diverging periods in economic performance. Most of the period from independence to 1986 was characterized by a rising investment/GDP ratio and expanding real GDP, whereas the period 1987–93 was marked by a deep recession, reflected inter alia in a declining investment/GDP ratio and shrinking output. A number of recent studies have investigated the relationship between investment and economic growth either with cross-country data or with panel data. These studies have typically found positive, significant, and robust effects of increases in the investment/GDP ratio on economic growth.³⁴ In fact, the sensitivity analysis performed by Levine and Renelt (1992) with cross-country data indicates that the investment/GDP ratio is among the few variables that are robustly correlated with growth for a diverse group of countries. In this study, the empirical investigation of the linkage between investment and economic growth in developing countries is extended in three ways.

First, following Tallman and Wang (1994), an extended version of the Solow-Swan type aggregate production function is applied to an analysis of growth for an individual country—Cameroon—with data spanning more than three decades (1963–95). Cameroon, along with Côte d’voire, Gabon, and Senegal have traditionally been viewed as the engines of growth and prosperity in the CFA franc zone, as well as other neighboring countries.³⁵ Thus, an investigation of the determinants of growth in Cameroon would be informative in the design of policies that could foster subregional economic growth. In addition, as noted by Tallman and Wang (1994), an investigation of the growth determinants for an individual economy has the advantage that the analysis can focus on a detailed examination of the institutional and historical aspects of the country. Second, following Ghura and Hadjimichael (1996), Khan and Kumar (1993), and Khan and Reinhart (1990), the contributions of private and government investments to economic growth are investigated. Finally, the robustness of the effects of private investment on growth is examined by augmenting the estimating growth equations by variables representing human capital development, monetary and fiscal policies, external competitiveness, financial deepening, the terms of trade, and external debt service and debt overhang.³⁶

The analysis indicates that the standard results that hold with cross-country data also hold for Cameroon. In particular, increases in private investment are a key determinant of output growth. A 1 percent increase in the private investment/GDP ratio raises real GDP by about 0.8 percentage point; this positive effect is robust to various empirical specifications. The impact of changes in government investment, however, although positive, is not robust. Furthermore, improvements in external competitiveness are found to stimulate growth, while expansionary fiscal policies are harmful to economic growth. The effects of variables related to government size, monetary policy, the terms of trade, and external debt are not statistically significant.

The rest of this study is organized as follows: Section B presents a brief history of Cameroon’s recent economic development. Section C discusses the empirical model and testable hypotheses. Section D presents the empirical framework and summarizes the estimation results, and the last section summarizes the main conclusions of the study.

B. Recent History of Cameroon’s Economic Development

Cameroon’s recent history of economic development may be subdivided into four distinct subperiods (Chart 1): the period 1965–77, or the pre-oil era; the period 1978–86, during which the oil sector played a major role; the period 1987–93, during which the economy experienced a deep recession; and the period 1994–95, just after the CFA franc devaluation. Table 1 provides the averages of selected economic and social indicators during these subperiods. The rest of this section discusses the evolution of these indicators.

^{Table 1.}

CAMEROON: Selected Social and Economic Indicators, 1965–95

(Period avenges, in units indicated)

Sources: The social and infrastructural indicators were obtained from the World Bank, Social Indicators of Development database. See Appendix I for the sources of the other variables.

^{^1/}Percentage of total population of age 15 and above.

^{^2/}Percentage of female population of age 15 and above.

^{^3/}Based on annual average percentage change of the relevant variable expressed in level.

^{^4/}In percent.

^{^5/}Following Edwards (1989), defined as CPI/(EI.WPIUS), where CPI is the consumer price index, EI is an index of the nominal exchange rate (CFAF per U.S. dollar), and WPIUS is the U.S. wholesale price index.

^{^6/}French francs per U.S. dollar.

^{Table 1.}

CAMEROON: Selected Social and Economic Indicators, 1965–95

(Period avenges, in units indicated)

			1965–77	1978–86	1987–93	1994–95
Social indicators
	Primary school enrollment ratio
		Total	96	104	103	…
		Female	83	95	95	…
	Secondary school enrollment ratio
		Total	11	21	27	…
		Female	7	15	21	…
	Illiteracy rate
		Total ^1/	59	52	46	…
		Female ^2/	…	64	57	…
	Life expectancy at birth (in years)		45	0	55	…
	Infant mortality rate (per thousand)		124	88	66	…
	Population per physician		23,408	13,958	12,099	…
	Population per nurse		7,452	1,948	1,845	…
Infrastructure indicators
	Road length (in thousands of kilometers)		40	61	61	…
	Area of irrigated land (percent of agricultural land)		4.8	11.0	18.8	…
National amounts and prices
	Real ODP growth rate ^3/		4.7	8.8	-4.0	0.4
	Per capita real GDP
		Level (in thousands of 1979/80 CFA francs)	129	188	174	134
		Growth ^3/	1.3	5.6	-6.5	-2.4
	Gross domestic investment/GDP ^4/		18.8	24.9	18.2	14.9
	Private investment/GDP ^4/		16.7	16.2	11.4	12.7
	Government investment/GDP ^4/		2.1	8.7	6.8	2.2
	Consumer price
		Level (index, 1979/80=100)	45.2	131.8	225.5	289.5
		Inflation ^3/	6.9	11.3	2.1	21.8
Central government operations
	Total revenue/GDP ^4/		16.5	21.3	15.8	11.7
	Current expenditure/GDP ^4/		15.5	11.8	16.3	16.3
	Capital expenditure/GDP ^4/		2.1	8.7	6.8	2.2
	Overall budget balance/GDP ^4/		-1.0	0.8	-7.3	-6.9
Monetary developments
	Real money balances
		Level (in thousands of 1979/80 CFA francs)	118	329	327	216
		Growth ^3/	8.4	9.5	-6.8	-15.1
	Income velocity of circulation		6.5	5.2	4.7	6.1
	BEAC’s discount rate		4.6	8.1	9.9	10.6
	French money market rate		7.1	11.4	8.8	6.6
External sector
	Real effective exchange rate (index, 1979/80=100)		…	93.6	123.6	83.3
	Relative price of nontraded goods (index, 1979/80=100) ^5/		78.5	82.3	121.0	93.4
	French consumer price
		Level (index, 1979/80=100)	47.5	127.0	193.0	215.3
		Inflation ^3/	6.5	9.8	2.9	1.8
	Terms of trade (index, 1979/80=100)		87.2	91.2	60.0	57.8
	French exchange rate ^6/		4.9	6.3	5.8	5.5
	External debt stock/GDP ^4/		…	31.1	48.6	119.5
	External debt service/Exports ^4/		…	14.5	18.5	24.1

Sources: The social and infrastructural indicators were obtained from the World Bank, Social Indicators of Development database. See Appendix I for the sources of the other variables.

^{^1/}Percentage of total population of age 15 and above.

^{^2/}Percentage of female population of age 15 and above.

^{^3/}Based on annual average percentage change of the relevant variable expressed in level.

^{^4/}In percent.

^{^6/}French francs per U.S. dollar.

^{Table 1.}

CAMEROON: Selected Social and Economic Indicators, 1965–95

(Period avenges, in units indicated)

			1965–77	1978–86	1987–93	1994–95
Social indicators
	Primary school enrollment ratio
		Total	96	104	103	…
		Female	83	95	95	…
	Secondary school enrollment ratio
		Total	11	21	27	…
		Female	7	15	21	…
	Illiteracy rate
		Total ^1/	59	52	46	…
		Female ^2/	…	64	57	…
	Life expectancy at birth (in years)		45	0	55	…
	Infant mortality rate (per thousand)		124	88	66	…
	Population per physician		23,408	13,958	12,099	…
	Population per nurse		7,452	1,948	1,845	…
Infrastructure indicators
	Road length (in thousands of kilometers)		40	61	61	…
	Area of irrigated land (percent of agricultural land)		4.8	11.0	18.8	…
National amounts and prices
	Real ODP growth rate ^3/		4.7	8.8	-4.0	0.4
	Per capita real GDP
		Level (in thousands of 1979/80 CFA francs)	129	188	174	134
		Growth ^3/	1.3	5.6	-6.5	-2.4
	Gross domestic investment/GDP ^4/		18.8	24.9	18.2	14.9
	Private investment/GDP ^4/		16.7	16.2	11.4	12.7
	Government investment/GDP ^4/		2.1	8.7	6.8	2.2
	Consumer price
		Level (index, 1979/80=100)	45.2	131.8	225.5	289.5
		Inflation ^3/	6.9	11.3	2.1	21.8
Central government operations
	Total revenue/GDP ^4/		16.5	21.3	15.8	11.7
	Current expenditure/GDP ^4/		15.5	11.8	16.3	16.3
	Capital expenditure/GDP ^4/		2.1	8.7	6.8	2.2
	Overall budget balance/GDP ^4/		-1.0	0.8	-7.3	-6.9
Monetary developments
	Real money balances
		Level (in thousands of 1979/80 CFA francs)	118	329	327	216
		Growth ^3/	8.4	9.5	-6.8	-15.1
	Income velocity of circulation		6.5	5.2	4.7	6.1
	BEAC’s discount rate		4.6	8.1	9.9	10.6
	French money market rate		7.1	11.4	8.8	6.6
External sector
	Real effective exchange rate (index, 1979/80=100)		…	93.6	123.6	83.3
	Relative price of nontraded goods (index, 1979/80=100) ^5/		78.5	82.3	121.0	93.4
	French consumer price
		Level (index, 1979/80=100)	47.5	127.0	193.0	215.3
		Inflation ^3/	6.5	9.8	2.9	1.8
	Terms of trade (index, 1979/80=100)		87.2	91.2	60.0	57.8
	French exchange rate ^6/		4.9	6.3	5.8	5.5
	External debt stock/GDP ^4/		…	31.1	48.6	119.5
	External debt service/Exports ^4/		…	14.5	18.5	24.1

Sources: The social and infrastructural indicators were obtained from the World Bank, Social Indicators of Development database. See Appendix I for the sources of the other variables.

^{^1/}Percentage of total population of age 15 and above.

^{^2/}Percentage of female population of age 15 and above.

^{^3/}Based on annual average percentage change of the relevant variable expressed in level.

^{^4/}In percent.

^{^6/}French francs per U.S. dollar.

Pre-oil era (1965–77)

Agriculture played a dominant role until 1978, when oil production started. The primary sector (including agriculture, forestry, and fishing) accounted for 34 percent of total value added on average during 1965–77, employed a large fraction of the labor force, and was a main source of economic growth and foreign exchange earnings. Real GDP grew on average by 4.7 percent a year during this period (Chart 1). The private investment/GDP ratio rose from 11 percent in 1963 to about 19 percent in 1977; government investment, however, remained low as a share of GDP, averaging 2 percent during 1965–77 (Chart 2). The government revenue/GDP ratio averaged 17 percent of GDP during the period, and with average total government expenditure running at about 18 percent of GDP, the average overall budget deficit remained low, at 1 percent of GDP (Chart 3).

Oil boom era (1978–86)

Beginning in 1978, Cameroon’s economy experienced a substantial structural change when oil assumed a major role and became the main source of foreign exchange earnings. Oil was discovered in 1975, but production and exports started the following year. The share in GDP of the secondary sector (including mining, manufacturing, electricity, housing, and public works) rose from 19 percent on average during 1965–77 to an average of 28 percent during 1978–86. The economy experienced a real GDP growth rate of about 8.8 percent a year during this period, reflecting in part the oil sector’s rising output. Oil production grew from less than 5 million barrels in 1978 to more than 66 million barrels in 1986. Per capita real GDP grew by 52 percent (on a cumulative basis) during 1978–86. The oil sector also contributed significantly to the government’s budget, with oil revenue growing from less than CFAF 20 billion (1.4 percent of GDP, and 9 percent of total revenue) in 1980 to CFAF 330 billion in 1985 (9 percent of GDP, and 41 percent of total revenue). Total government revenue increased from an average of about 17 percent of GDP during 1965–77 to an average of 21 percent during 1978–86, but rising government outlays kept the budget broadly in balance.

With booming economic conditions during 1978–86, the government adopted a development strategy that centered on expanding the public sector in three ways. First, it shifted its expenditure priorities by expanding the capital budget from an average of 2 percent of GDP during 1965–77 to an average of 9 percent during 1978–86, while current outlays were reduced from an average of 16 percent of GDP to 12 percent. Thus, the total investment/GDP ratio increased significantly, but the private investment/GDP ratio remained broadly unchanged. Second, a large number of public agencies, marketing boards, and public enterprises were set up or expanded in all sectors of the economy, which were often supported by government subsidies. Third, a complex system of regulations on prices, including interest rates, was put in place. External trade was regulated through import licensing and marketing boards, while quantitative import restrictions were imposed on goods that competed with domestic production.

The increased emphasis on capital expenditure during 1978–86 was reflected in substantial improvements in the nation’s infrastructure and indicators of human capital development (Table 1). Both total and female primary and secondary school enrollment ratios improved and the overall literacy rate rose. Also, health indicators (life expectancy at birth and the infant mortality rate) improved markedly, reflecting inter alia an increase in the number of physicians and nurses relative to the population. Improvements in the nation’s physical infrastructure, including roads and irrigated land, testified to the emphasis on capital expenditure.

In principle, the oil boom experienced by Cameroon during 1978–86 should have given rise to the “Dutch disease” problem, characterized by a rise in the relative price of nontraded to traded goods…or a substantial appreciation of the real exchange rate.³⁷ However, the Dutch disease was largely averted, as the real exchange rate depreciated by about 50 percent on a cumulative basis between 1979 and 1984, reflecting largely the depreciation of the French franc (Chart 5). In addition, Benjamin and others (1989) note that the government saved a large portion of the windfall income from oil since it perceived the oil boom as a temporary phenomenon, thus avoiding a spending boom. According to Tshibaka (1986), the real exchange rate was actually undervalued during 1980–84, a factor that would have actually provided an implicit subsidy to the producers of traded goods.

Recession period (1987–93)

The period 1987–93 was marked by a severe economic crisis that manifested itself in a 40 percent drop in per capita real GDP. Economic activity shrank in most areas, particularly in construction and public works, but also in the production of cash crops, retail trade, and the petroleum sector. The deterioration in Cameroon’s economic and financial situation during this period can be explained by three main factors: a significant deterioration in the world market prices of its main export commodities and external terms of trade (Chart 5); an appreciation of its real effective exchange rate (Chart 4); and the decline in oil output. Between 1986 and 1988, the international price of crude oil fell by two thirds, while the prices of coffee and cocoa dropped by one half and one third, respectively. Overall, during 1986–92, the terms of trade declined by nearly 40 percent. At the same time, the real effective exchange rate appreciated by some 40 percent on a cumulative basis between 1985 and 1992, reflecting not only the appreciation of the French franc, but also an increase in inflation, triggered by expansionary fiscal policies.

The fiscal balance turned into an average deficit of 7 percent of GDP during 1986–93, compared with an average surplus of 1 percent of GDP during 1978–86 (Chart 3). This deficit was financed from two main sources—external borrowings, as well as the accumulation of domestic and external arrears. The external debt/GDP ratio rose to 49 percent during 1987–93, from 31 percent during 1978–86 (Chart 6). Sizable stocks of arrears were accumulated to external creditors, as well as to domestic suppliers, which prompted several local companies to halt work and default on their obligations to domestic banks, as well as on their tax obligations. The deteriorating financial conditions during 1986–93 exposed the problems of several local banks, which were undercapitalized, poorly managed, and marginally profitable.³⁸ Reflecting the lack of confidence in the domestic banking sector, money demand fell sharply starting in 1986, and the currency/broad money ratio rose from 17 percent in 1985 to 22 percent by 1993 (Chart 7).

The economic crisis in Cameroon during 1987–93 would have been even more pronounced, if human capital development had not been maintained. Despite the crisis, indicators of human capital development either remained broadly stable or even improved somewhat, compared with the earlier period. Total and female enrollment ratios in secondary schools, as well as measures of illiteracy, life expectancy, infant mortality and population per physician improved on average between 1978–86 and 1987–93.

In order to reverse the declining trends, the government attempted in the late 1980s and early 1990s to jump start the economy following a strategy that was based solely on internal adjustment measures. This strategy consisted mainly of maintaining the fixed common peg, reducing the fiscal deficit through increases in tax rates and cuts in the wage bill and public enterprise subsidies, as well as attempts to restore external competitiveness by reducing domestic costs and by restructuring public enterprises. Nevertheless, given the magnitude of the initial macroeconomic imbalances, it became clear by end-1993 that strategies based exclusively on internal adjustment would not be sufficient to set the economy back on a sustainable economic recovery track. The internal adjustment strategy alone was unable to restore external competitiveness, as nominal domestic prices (including wages and producer prices) showed considerable downward rigidity. In addition, owing to declining government revenue,³⁹ fiscal adjustment consisted mainly of cuts in the investment budget and outlays on nonwage maintenance and other essential services.

C Empirical Model and Testable Hypotheses

Empirical model

A Solow-Swan type aggregate production function is used to investigate the effects of physical and human capital, and economic policies on growth in Cameroon. The production function takes the following form:

\begin{matrix} Y_{t} = A_{t} {(K_{t}^{P})}^{α} {(K_{t}^{g})}^{β} {(Z_{t})}^{γ}, & Z_{t} = H_{t} L_{t}, & (1) \end{matrix}

where Y is real output; K^p and K^g are the private and government physical capital stock, respectively; Z represents labor (L), adjusted for human capital development (H); and t is a time index. Taking the natural logarithm of equation (1) gives:

\begin{matrix} \ln (Y_{t}) = \ln (A_{t}) + α \ln (K_{t}^{P}) + β \ln (K_{t}^{g}) + γ \ln (Z_{t}) . & (2) \end{matrix}

Next, taking a one-period lag of equation (2) and subtracting it from equation (2), equation (1) is transformed into its growth-rate equivalent as follows:

\begin{matrix} y = a + α k^{P} + β k^{g} + γ z, & (3) \end{matrix}

where a small letter for a variable denotes its growth rate.

Equation (3), which represents a long-run economic growth equation, can be estimated provided that data are available for human and physical capital stock. Unfortunately, such data are typically unavailable for developing economies, including Cameroon. Nevertheless, equation (3) can be transformed into an estimable equation with some simplifying assumptions regarding physical and human capital stocks. Consider the following growth equations for the stocks of private and government capital, which are simple transformations of the perpetual inventory accumulation equations:

\begin{matrix} \frac{Δ K_{t}^{P}}{K_{t - 1}^{P}} = \frac{I_{t}^{P}}{K_{t - 1}^{P}} - δ_{P}, & (4 a) \end{matrix}

and

\begin{matrix} \frac{Δ K_{t}^{g}}{K_{t - 1}^{g}} = \frac{I_{t}^{g}}{K_{t - 1}^{g}} - δ_{g}, & (4 b) \end{matrix}

where I^P and I^g are private and government investments, respectively; and δ_p and δ_g are the respective rates of depreciation on the private and government capital stocks. Assuming that:

\begin{matrix} K^{P} = θ_{P} Y, & (5 a) \end{matrix}

and

\begin{matrix} K^{g} = θ_{g} Y, & (5 b) \end{matrix}

where θ_p and θ_g are fixed coefficients, equation (3) can be rewritten as:

\begin{matrix} y = a ’ + α ’ (\frac{I_{t}^{P}}{Y_{t - 1}}) + β ’ (\frac{I_{t}^{g}}{Y_{t - 1}}) + γ z, & (6) \end{matrix}

where $a ’ = (a - α δ_{P} - β δ_{g}), α ’ = α / θ_{P}, a n d β ’ = β / θ_{g} .$

As regards the measurement of human capital stock, Tallman and Wang (1994) used data on educational achievement for the case of Taiwan, which closely approximates the stock of human capital. Similar data are not available for Cameroon. In addition, in the absence of complete series for the primary and secondary school enrollment ratios during 1963–95, it is assumed that the level of human capital stock can be proxied by an index of life expectancy at birth (LIFE), following Barro (1991), Ghura (1995a) and Ghura and Hadjimichael (1996).

Testable hypotheses

While the recent literature on growth provides a set of testable hypotheses, this study focuses on those that can be implemented using available data for Cameroon.⁴⁰ The discussion of the hypotheses relates to the actual variables used.⁴¹

Human capital development (LIFE)

Recent endogenous growth models have shown that human capital accumulation can contribute significantly to steady-state growth, either because it is a direct input into research (Romer (1990)) or owing to its positive externalities (Lucas (1988), and Becker, Murphy, and Tamura (1990)). Hence, policies that enhance public and private investment in human capital affect long-run economic growth. In a theoretical model of endogenous growth for Côte d’lvoire, Azam (1993) has shown that output in the steady state is boosted by increased government investment in human capital. Also, Tallman and Wang (1994) have demonstrated empirically that human capital development has been a key factor in determining output growth in Taiwan. The importance of human capital development in boosting economic growth was also emphasized in the literature in the 1960s and 1970s (e.g., Schultz (1961), Rosen (1976), and Uzawa (1965). As noted earlier, given data limitations, the effects of human capital development are measured by life expectancy at birth (LIFE).

Monetary policy (RDR, RDCG)

Monetary policy, which is implemented at the regional level by the Bank of Central African States (BEAC), aims at supporting the government’s fiscal policy, with a view to controlling domestic credit and protecting the central bank’s net foreign assets position. By accepting the conduct of monetary policy by the regional central bank, each member country forgoes the option of financing fiscal deficits through unlimited monetary financing, thus bringing credibility to its commitment to maintaining low inflation.⁴² The main tools used to achieve these objectives during the period of analysis (1963–95) included adjustments in the discount rate (taux d’escompte normal-TEN) and changes in domestic credit. In this study, the variables used to capture the effects of monetary policy are the real discount rate (RDR) and growth in the real domestic credit (RDCG).

Throughout its history, the BEAC has formulated its interest rate policy foremost with a view to promoting economic development, and not necessarily to controlling domestic credit expansion or protecting its net foreign assets. Thus, the BEAC maintained its discount rate at levels lower than in the French money market for the period through 1985 (Chart 7). During 1964–85, the discount rate was changed only six times.⁴³ Nevertheless, with the onset of the economic crisis in 1986 and the ensuing rapid deterioration of the net foreign assets position of the banking system, the BEAC used the discount rate relatively more actively than in the past, with frequent rate changes. These changes resulted generally in rates that were more favorable in the BEAC zone than in the French money market.

Changes in credit may affect economic growth directly by influencing the implicit cost of working capital, as well as indirectly by influencing interest rates in the “curb” market. The relatively free informal market for loanable funds in Cameroon plays an important role in the transmission between monetary policy and economic growth.⁴⁴ A cutback in domestic credit to the private sector would be expected to raise the demand for credit in the informal market, and the resulting rise in the curb market interest rate would lower private investment and growth.

Fiscal policy (GIY, BDY, GCY)

The role of fiscal policy in influencing economic growth is typically captured by the following variables (as ratios to GDP) related to government activity or policy: the budget deficit (BDY), investment (GIY), and consumption (GCY).⁴⁵ In the context of a country that is a member of a currency union, fiscal policy is the most effective instrument of macroeconomic policy, given that monetary policy is conducted at the union-wide level. A burgeoning government budget deficit would be expected to crowd out the private sector, owing to lower access to bank credit, a higher real interest rate, and a more appreciated real exchange rate.

The effect of changes in government investment on growth, however, is ambiguous. On the one hand, public investment in social and physical infrastructure, by raising private and social rates of return, can boost private sector investment (Blejer and Khan (1984)). On the other hand, increases in government investment may crowd out private investment, if the additional government borrowing requirements raise domestic interest rates and the future tax burden. Also, government consumption relative to GDP (GCY) would be expected to capture the prediction that higher government spending creates expectations of future tax liabilities, which, in turn, distort production incentives and lower economic growth (e.g., Kormendi and Meguire (1985)). The variable GCY has also been used to capture the effect of government size on growth (e.g., Barro (1989)).

External competitiveness (RERG)

Given the fixed exchange rate arrangement among the member countries of the CFA franc zone, there is limited scope for the conduct of independent monetary policy in Cameroon. In this context, expansionary financial policies are reflected in deteriorations in external competitiveness and the balance of payments, as well as the accumulation of internal and external arrears, but not necessarily in high rates of inflation. An excess aggregate demand manifests itself in a deterioration in the balance of payments, either because the pressure on the demand for nontraded goods raises the demand of traded goods, or because a fall in the domestic interest rate causes a net capital outflow, which in turn causes the capital account to deteriorate. The pressure on the domestic prices of nontraded goods stemming from expansionary fiscal policies would have a tendency to induce a loss in external competitiveness, reflected in an appreciation of the real exchange rate.

The effects of changes in the real exchange rate on economic growth are ambiguous (Lizondo and Montiel (1989)). On the one hand, a real exchange rate depreciation, by raising the profitability of the tradable goods sector, would be expected to stimulate private sector investment and growth. On the other hand, by raising the cost of imported capital goods, a real depreciation may depress private investment, thereby lowering growth. The real exchange rate (RER) is defined as the relative price of nontraded to traded goods:

\begin{matrix} R E R = \frac{P_{N}}{P_{T}}, & (7) \end{matrix}

where P_T and P_N are the domestic price indices of tradable and nontradable goods, respectively. In the absence of data for the domestic price of tradables (P_T), an index of the world market price for traded goods ( $P_{T}^{W}$

) is used. Following the empirical literature on the measurement of RER in less developed economies, the proxies used for P_N and

P_{T}^{W}

, respectively are Cameroon’s consumer price index (CPI) and the U.S. wholesale price index (WPI^US).⁴⁶ Hence,

\begin{matrix} R E R = \frac{P_{N}}{E I . P_{T}^{W}} = \frac{C P I}{E I . W P I^{U S}}, & (8) \end{matrix}

where EI is an index of the official nominal exchange rate measured as the local currency price of the U.S. dollar.

Financial intermediation (M2Y)

Economic growth is also influenced by the process of financial deepening (McKinnon (1973) and Shaw (1973))—measured in this study by the ratio of broad money to GDP (M2Y). If this process raises the expected profitability of capital, it would also be expected to encourage investment and growth. Recent endogenous growth models have emphasized the important role played by financial intermediation in improving the efficiency of investment, and thus in stimulating economic growth (e.g., Roubini and Sala-i-Martin (1991)).⁴⁷

External debt (DETY, DETSX)

It has been argued that growth is adversely affected by the existence of an external debt burden, measured either by the ratio of external debt stock to GDP (DETY) or by the ratio of debt service on external debt to exports of goods and services (DETSX). The resources used for servicing foreign debt crowd out public investment, which in turn discourages private investment and lowers growth. Also, the external debt/GDP ratio could be indicative of a “debt overhang,” whereby the presence of a high external debt/GDP ratio leads economic agents to anticipate future tax liabilities for its servicing (Borensztein (1990a and 1990b) and Eaton (1987)). An increasing external debt/GDP ratio could induce these agents to transfer funds abroad, thus raising the implicit domestic cost of capital. In addition, it has been argued that uncertainty regarding the future stance on economic policies in response to an uncertain debt service profile would also have deleterious effects on private capital formation.

D. Empirical Methodology and Results

Equation (6) may be estimated using a standard regression framework, provided that account is taken of the time-series properties of the variables used.⁴⁸ The strategy used for the empirical investigation is as follows: first, the simple correlations between pairs of variables are presented; second, the time-series properties of the variables used in the regressions are discussed; and finally, the regression results that account for these properties are discussed. The base regression presents the effects of private and government investments, and human capital development, on economic growth. The robustness of the effect of private investment is investigated by augmenting the estimating equation by other explanatory variables.

Preliminary results

Table 2 gives the matrix of correlation coefficients between pairs of variables. A number of the conventional and policy-related variables are significantly correlated with economic growth, with the signs being broadly as expected. The empirical linkage between private investment and growth is positive and statistically significant, while that between government investment and growth, although positive, is not significant. Also, the simple correlations between growth, on the one hand, and the budget deficit/GDP ratio, the government consumption/GDP ratio, the broad money/GDP ratio, the real discount rate, changes in real domestic credit, the external debt stock/GDP ratio, and the debt service/exports ratio, on the other hand, are significant.

^{Table 2.}

Matrix of Correlation Coefficients for Pairs of Variables ^1/

^{^1/}See Appendix I for the definitions and sources of variables. The symbols ***, ** and * beside the estimated coefficients denote statistical significance at the 0.01, 0.05, and 0.10 levels, respectively.

^{Table 2.}

Matrix of Correlation Coefficients for Pairs of Variables ^1/

	PIY	GIY	PGHC	RERG	BDY	GCY	M2Y	RDR	RDCG	TTG	DETY	DETSX	OIL
YG	0.67 ***	0.19	0.29 *	-0.11	-0.75 ***	-0.42 **	-0.31 *	-0.35 ***	0.42 **	0.04	-0.40 **	-0.41 **	0.57 ***
PIY	1	-0.25	0.20	-0.10	-0.75 ***	-0.05	-0.46 ***	-0.38 ***	0.40 **	0.28	-0.37 ***	-0.58 ***	0.39 **
GIY		1	-0.14	0.06	0.07	0.09	0.50 ***	-0.10	0.01	-0.25	-0.11	0.53 **	0.57 **
PGHC			1	-0.19	0.21	0.47 ***	-0.11	0.09	0	0.35 **	-0.16	-0.29	0.02
RERG				1	0.15	0.15	0.12	0.12	0.09	0.03	-0.26	0.21	-0.25
BDY					1	0.36 ***	0.42 ***	0.21	-0.40 **	-0.13	0.50 ***	0.54 ***	0.51 ***
GCY						1	0.41 **	0.10	-0.04	-0.09	0.12	0.15	-0.41
M2Y							1	0.49 **	-0.08	-0.10	0.30	0.55 ***	0.27
RDR								1	-0.08	-0.15	0.01	0.14	-0.14
RDCG									1	-0.13	-0.69 ***	-0.63 ***	0.18
TTG										1	0.04	-0.13 ***	-0.22
DETY											1	0.57 ***	-0.10
DETSX												1	0.07

^{Table 2.}

Matrix of Correlation Coefficients for Pairs of Variables ^1/

	PIY	GIY	PGHC	RERG	BDY	GCY	M2Y	RDR	RDCG	TTG	DETY	DETSX	OIL
YG	0.67 ***	0.19	0.29 *	-0.11	-0.75 ***	-0.42 **	-0.31 *	-0.35 ***	0.42 **	0.04	-0.40 **	-0.41 **	0.57 ***
PIY	1	-0.25	0.20	-0.10	-0.75 ***	-0.05	-0.46 ***	-0.38 ***	0.40 **	0.28	-0.37 ***	-0.58 ***	0.39 **
GIY		1	-0.14	0.06	0.07	0.09	0.50 ***	-0.10	0.01	-0.25	-0.11	0.53 **	0.57 **
PGHC			1	-0.19	0.21	0.47 ***	-0.11	0.09	0	0.35 **	-0.16	-0.29	0.02
RERG				1	0.15	0.15	0.12	0.12	0.09	0.03	-0.26	0.21	-0.25
BDY					1	0.36 ***	0.42 ***	0.21	-0.40 **	-0.13	0.50 ***	0.54 ***	0.51 ***
GCY						1	0.41 **	0.10	-0.04	-0.09	0.12	0.15	-0.41
M2Y							1	0.49 **	-0.08	-0.10	0.30	0.55 ***	0.27
RDR								1	-0.08	-0.15	0.01	0.14	-0.14
RDCG									1	-0.13	-0.69 ***	-0.63 ***	0.18
TTG										1	0.04	-0.13 ***	-0.22
DETY											1	0.57 ***	-0.10
DETSX												1	0.07

There is evidence from these correlations that point to significant external debt overhang and adverse external debt liquidity effects on growth. In addition, the negative correlation between the real discount rate and economic growth, as well as the positive correlation between real credit expansion and economic growth provide evidence in favor of the contractionary effects of monetary policy on private investment and economic growth. It is interesting to note that the correlation between the budget deficit ratio and government investment is not significant, while that between the budget deficit and government consumption is positive and statistically significant, which is partly due to the positive and significant correlation between the budget deficit ratio and the external debt service. In general, there is no evidence supporting the potential for significant multicollinearity problem among the variables, except between the budget deficit ratio and private investment. It should be noted, however, that the correlations presented in Table 2 may be spurious, as they do not account for the time-series properties of the variables used. The next subsection investigates these properties, and the following subsection presents regression results that take account of these properties.

Time-series properties of the data

In order to avoid the problem of spurious correlations in the regression analysis, the time-series properties of the variables used in the regression analysis are investigated using the standard Augmented Dickey-Fuller (ADF) and the Phillips-Perron (PP) unit root tests under two alternative hypotheses.⁴⁹ First, it is assumed that there were no structural breaks in the series, and second it is assumed that there was a one-time break in both the mean and the trend at a specific point in time (Perron (1989)).⁵⁰ The form of the ADF test employed is given by:

\begin{matrix} Δ w_{t} = μ + β t + α w_{t - 1} + \sum_{i = 1}^{k} δ_{i} Δ w_{t - i} + e_{t}, & (9) \end{matrix}

where w is the logarithm of the variable of interest. Equation (9) allows for the presence of a nonzero mean and a constant deterministic drift. To ensure that the residuals from (9) are serially uncorrelated, lagged differences of the variable are included. The number of lags are determined by a general-to-specific method, whereby a generous lag structure is allowed and the insignificant lags are eliminated sequentially; the optimal lag turns out to be one for all the series.

The variables that are tested for stationarity are real GDP growth (YG), the ratio of private investment to lagged GDP (PIY), the ratio of government investment to lagged GDP (GIY), population growth (PG), population growth augmented with a measure of human capital development (PGHC), the percentage change in the real exchange rate (RERG), the ratio of the budget deficit to GDP (BDY), the ratio of government consumption to GDP (GCY), the ratio of broad money to GDP (M2Y), the real discount rate (RDR), the percentage change in real total domestic credit (RDCG), the percentage change on the terms of trade (TTG), the ratio of external debt stock to GDP (DETY), and the ratio of external debt service to exports of goods and services (DETSX). The results of the unit root tests are given in Table 3. The ADF test statistics indicate that most variables, including real GDP growth, are nonstationary.⁵¹ Nevertheless, once a one-time structural break is accounted for, a number of variables (YG, PIY, RERG, BDY, RDR, and TTG) are stationary, that is, they are integrated of order zero—I(O). Of the remaining variables (GIY, GCY, M2Y, RDCG, DETY, and DETSX), three are I(1)—GIY, GCY and RDCG-and the others are I(2).⁵²

^{Table 3.}

Unit Root Test Results

Alternative hypothesis: No structural breaks

Regression: $Δ w_{t} = μ + β t + α w_{i - 1} + \sum_{i = 1}^{k} δ_{i} Δ w_{i - 1} + e_{t}$

^{Table 3.}

Unit Root Test Results

Alternative hypothesis: No structural breaks

Regression: $Δ w_{t} = μ + β t + α w_{i - 1} + \sum_{i = 1}^{k} δ_{i} Δ w_{i - 1} + e_{t}$

Series ^1/	N ^2/	t-statistic on α (ADF statistic)
YG	33	-2.16
PIY	33	-2.03
GIY	33	-1.27
PG	33	-4.05 **
PGHC	33	-3.98 **
RERG	33	-3.85 **
BDY	33	-2.27
GCY	33	-2.35
M2Y	33	-2.11
RDR	33	-2.61
RDCG	33	-3.21
TTG	33	-3.42
DETY	29	1.45
DETSX	29	-2.34
The critical value at the 5 percent significance is −3.51 for N = 50.^3/

^{Table 3.}

Unit Root Test Results

Alternative hypothesis: No structural breaks

Regression: $Δ w_{t} = μ + β t + α w_{i - 1} + \sum_{i = 1}^{k} δ_{i} Δ w_{i - 1} + e_{t}$

Series ^1/	N ^2/	t-statistic on α (ADF statistic)
YG	33	-2.16
PIY	33	-2.03
GIY	33	-1.27
PG	33	-4.05 **
PGHC	33	-3.98 **
RERG	33	-3.85 **
BDY	33	-2.27
GCY	33	-2.35
M2Y	33	-2.11
RDR	33	-2.61
RDCG	33	-3.21
TTG	33	-3.42
DETY	29	1.45
DETSX	29	-2.34
The critical value at the 5 percent significance is −3.51 for N = 50.^3/

Alternative hypothesis: One-time structural break occurring at T_b

Alternative hypothesis: $w_{t} = μ_{1} + β_{1} t + (μ_{2} - μ_{1}) D U_{1} (β_{2} - β_{1}) D T_{i} + e_{t}$

where DU = DT = 0 if t ≤ T_b and DU = l, DT = t if t ≥ T_b,

Regression: $Δ {\hat{w}}_{t} = α {\hat{w}}_{i - 1} + \sum_{i = 1}^{k} δ_{t} Δ {\hat{w}}_{t - i} + e_{t}$

^{^1/}See Appendix I for the definitions and sources of the variables.

^{^2/}Number of observations.

^{^3/}Taken from Guilkey and Schmidt (1989).

^{^4/}Taken from Perron (1989).

Alternative hypothesis: One-time structural break occurring at T_b

Alternative hypothesis: $w_{t} = μ_{1} + β_{1} t + (μ_{2} - μ_{1}) D U_{1} (β_{2} - β_{1}) D T_{i} + e_{t}$

where DU = DT = 0 if t ≤ T_b and DU = l, DT = t if t ≥ T_b,

Regression: $Δ {\hat{w}}_{t} = α {\hat{w}}_{i - 1} + \sum_{i = 1}^{k} δ_{t} Δ {\hat{w}}_{t - i} + e_{t}$

Series ^1/	T_b	Phillips-Perron	λ	Critical values at the 5 percent level ^4/
YG	1986	-4.98 **	0.7	-4.18
PIY	1981	-4.91 **	0.6	-4.24
GIY	1986	-2.95	0.7	-4.18
PG	no break	…	…	…
PGHC	no break	…	…	…
RERG	1985	-5.67 **	0.7	-4.18
BDY	1983	-4.57 **	0.6	-4.24
GCY	1969	-3.48	0.2	-3.99
M2Y	1992	-3.10	0.9	-3.46
RDR	1987	-5.50 **	0.8	-4.04
RDCG	no break	…	…	…
TTG	1975	-4.79 **	0.4	-4.22
DETY	no break	…	…	…
DETSX	1988	-2.73	0.7	-4.18

^{^1/}See Appendix I for the definitions and sources of the variables.

^{^2/}Number of observations.

^{^3/}Taken from Guilkey and Schmidt (1989).

^{^4/}Taken from Perron (1989).

Alternative hypothesis: One-time structural break occurring at T_b

Alternative hypothesis: $w_{t} = μ_{1} + β_{1} t + (μ_{2} - μ_{1}) D U_{1} (β_{2} - β_{1}) D T_{i} + e_{t}$

where DU = DT = 0 if t ≤ T_b and DU = l, DT = t if t ≥ T_b,

Regression: $Δ {\hat{w}}_{t} = α {\hat{w}}_{i - 1} + \sum_{i = 1}^{k} δ_{t} Δ {\hat{w}}_{t - i} + e_{t}$

Series ^1/	T_b	Phillips-Perron	λ	Critical values at the 5 percent level ^4/
YG	1986	-4.98 **	0.7	-4.18
PIY	1981	-4.91 **	0.6	-4.24
GIY	1986	-2.95	0.7	-4.18
PG	no break	…	…	…
PGHC	no break	…	…	…
RERG	1985	-5.67 **	0.7	-4.18
BDY	1983	-4.57 **	0.6	-4.24
GCY	1969	-3.48	0.2	-3.99
M2Y	1992	-3.10	0.9	-3.46
RDR	1987	-5.50 **	0.8	-4.04
RDCG	no break	…	…	…
TTG	1975	-4.79 **	0.4	-4.22
DETY	no break	…	…	…
DETSX	1988	-2.73	0.7	-4.18

^{^1/}See Appendix I for the definitions and sources of the variables.

^{^2/}Number of observations.

^{^3/}Taken from Guilkey and Schmidt (1989).

^{^4/}Taken from Perron (1989).

Alternative hypothesis: No structural breaks

Regression: $Δ^{2} w_{t} = μ + β t + α Δ w_{t - 1} + \sum_{i = 1}^{k} δ_{t} Δ^{2} w_{i - 1} + e_{t}$

Alternative hypothesis: No structural breaks

Regression: $Δ^{2} w_{t} = μ + β t + α Δ w_{t - 1} + \sum_{i = 1}^{k} δ_{t} Δ^{2} w_{i - 1} + e_{t}$

Series ^1/	t-statistic on λ (ADF statistic)
ΔGIY	-4.44 **
ΔGCY	-4.10 **
ΔM2Y	-3.34
ΔRDCG	-5.52 **
ΔDETY	-1.48
ΔDETSX	-2.69
The critical value at the 5 percent significance is −3.51 for N = 50. ^2/

Alternative hypothesis: No structural breaks

Regression: $Δ^{2} w_{t} = μ + β t + α Δ w_{t - 1} + \sum_{i = 1}^{k} δ_{t} Δ^{2} w_{i - 1} + e_{t}$

Series ^1/	t-statistic on λ (ADF statistic)
ΔGIY	-4.44 **
ΔGCY	-4.10 **
ΔM2Y	-3.34
ΔRDCG	-5.52 **
ΔDETY	-1.48
ΔDETSX	-2.69
The critical value at the 5 percent significance is −3.51 for N = 50. ^2/

Alternative hypothesis: No structural breaks

Regression: $Δ^{3} w_{t} = μ + β t + α Δ^{2} w_{t - 1} + \sum_{i = 1}^{k} δ_{t} Δ^{3} w_{t - 1} + e_{t}$

^{^1/}See Appendix I for the definitions and sources of the variables.

^{^2/}Taken from Guilkey and Schmidt (1989).

Alternative hypothesis: No structural breaks

Regression: $Δ^{3} w_{t} = μ + β t + α Δ^{2} w_{t - 1} + \sum_{i = 1}^{k} δ_{t} Δ^{3} w_{t - 1} + e_{t}$

Series ^1/	t-statistic on α (ADF statistic)
ΔΔM2Y	-5.16 **
ΔΔDETY	-5.96 **
ΔΔDETSX	-5.70 **
The critical value at the 5 percent significance is −3.51 for N = 50. ^2/

^{^1/}See Appendix I for the definitions and sources of the variables.

^{^2/}Taken from Guilkey and Schmidt (1989).

Alternative hypothesis: No structural breaks

Regression: $Δ^{3} w_{t} = μ + β t + α Δ^{2} w_{t - 1} + \sum_{i = 1}^{k} δ_{t} Δ^{3} w_{t - 1} + e_{t}$

Series ^1/	t-statistic on α (ADF statistic)
ΔΔM2Y	-5.16 **
ΔΔDETY	-5.96 **
ΔΔDETSX	-5.70 **
The critical value at the 5 percent significance is −3.51 for N = 50. ^2/

^{^1/}See Appendix I for the definitions and sources of the variables.

^{^2/}Taken from Guilkey and Schmidt (1989).

Regression results

Given that the dependent variable—real GDP growth (YG)—is stationary, equation (6) can be estimated using the standard Ordinary Least Squares (OLS) procedure, provided that the explanatory variables are made I(o).⁵³ As explained above, PIY, PG, PGHC, RERG, BDY, RDR, TTG, ∆GIY, ∆GCY, ∆RDCG, ∆∆M2Y, ∆∆DETY, and ∆∆DETSX are stationary, that is, integrated of order zero (I(0)). The regression results—using OLS with the stationary variables—are summarized in Table 4. All explanatory variables (except PG and PGHC) are lagged at least once to avoid the problem of simultaneity bias. The Durbin-Watson statistics for all regressions (l)−(13) indicate that there is no problem with serial correlation, and that the equations broadly are well specified.

^{Table 4.}

Estimates of the Growth Equation ^1/

^{^1/}The numbers in parentheses below the estimated coefficients are the absolute values of the t-ratios. The symbols ***, **, and * beside the estimated coefficients denote statistical significance at the 0.01, 0.05, and 0.10 levels, respectively.

^{^2/}See Appends I for the definitions and sources of the variables used. The variables X(t), X(t−l), and X(t−2), denote the contemporaneous, lagged once, lagged twice values of X.

^{^3/}GIYD, GCYD, and RDCGD denote the first difference of GIY, GCY, and RDCG, respectively.

^{^4/}M2YDD, DETYDD, and DETSXDD denote the second difference of M2Y, DETY, and DETSX, respectively.

^{^5/}RSQ is the coefficient of determinantion.

^{^6/}Durbin-Watson statistic for serial correlation.

^{^7/}Number of observations used in the regression, after making the variables stationary—I(0).

^{Table 4.}

Estimates of the Growth Equation ^1/

	Regression Number
Explanatory variables ^2/		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)
Conventional variables
	PIY(t−l)	0.800 ^***	0.790 ^***	0.763 ^***	0.488 ^*	—	0.827 ^***	0.801 ^***	0.740 ^***	0.791 ^***	0.799 ^***	0.647 ^***	0.804 ^***	0.819 ^***
		(5.37)	(5.34)	(5.58)	(1.98)		(5.44)	(5.58)	(4.60)	(5.23)	(5.03)	(3.96)	(5.21)	(5.26)
	GIYD(t−2) ^3/	0.421 ^*	0.419 ^*	0.420 ^*	0.340	0.296	0.359 ^*	0.420 ^*	0.393 ^*	0.415	0.419 ^*	0.318	0.427 ^*	0.224
		(1.73)	(1.74)	(l.89)	(1.41)	(1.17)	(1.45)	(1.80)	(1.61)	(1.64)	(1.70)	(1.33)	(1.71)	(0.85)
	PG(t)	0.693 ^*	—	—	—	—	—	—	—	—	—	—	—	—
	PGHC(t)	—	0.672 ^**	0.635 ^**	0.677 ^**	0.688 ^*	0.662 ^*	0.677 ^**	0.657 ^*	0.674 ^*	0.686 ^*	0.692 ^**	0.940	0.702
			(2.05)	(2.10)	(2.11)	(2.03)	(2.02)	(2.13)	(1.98)	(2.01)	(2.00)	(2.20)	(1.30)	(0.92)
Policy-related variables
	RERG(t−l)	—	—	-0.117 ^**	—	—	—	—	—	—	—	—	—	—
				(2.35)
	BDY(t−l)	—	—	—	-0.117	-0.983 ^***	—	—	—	—	—	—	—	—
					(1.52)	(5.03)
	GCYD(t−l) ^3/	—	—	—	—	—	-0.351	—	—	—	—	—	—	—
							(1.05)
	M2YDD(t−2) ^4/	—	—	—	—	—	—	0.556	—	—	—	—	—	—
								(1.63)
	RDR(t−l)	—	—	—	—	—	—	—	-0.081	—	—	—	—	—
									(0.83)
	RDCGD(t−l) ^3/	—	—	—	—	—	—	—	—	-0.004	—	—	—	—
										(0.08)
Other variables
	TTG(t−l)	—	—	—	—	—	—	—	—	—	-0.011	—	—	—
											(0.18)
	OIL	—	—	—	—	—	—	—	—	—	—	0.031 ^*	—	—
												(1.77)
	DETYDD(t−l) ^4/	—	—	—	—	—	—	—	—	—	—	—	-0.02	—
													(0.04)
	DETSXDD(t−l) ^4/	—	—	—	—	—	—	—	—	—	—	—	—	0.081
														(0.61)
Intercept		-0.124 ^***	-0.129 ^***	-0.122 ^***	-0.066 ^***	0.029 ^*	-0.135 ^***	-0.130 ^***	-0.119 ^***	-0.129 ^***	-0.131 ^***	-0.113 ^***	-0.143 ^***	-0.137 ^***
		(4.29)	(4.36)	(4.45)	(1.31)	(1.75)	(4.49)	(4.55)	(3.77)	(4.26)	(4.01)	(3.83)	(3.77)	(3.37)
RSQ ^5/		0.612	0.617	0.689	0.650	0.593	0.634	0.655	0.627	0.617	0.617	0.661	0.638	0.609
DW ^6/		2.01	2.00	2.19	2.18	2.02	1.95	1.86	1.94	1.99	2.01	2.13	2.16	2.18
N ^7/		32	32	32	32	32	32	31	32	52	32	32	27	27

^{^2/}See Appends I for the definitions and sources of the variables used. The variables X(t), X(t−l), and X(t−2), denote the contemporaneous, lagged once, lagged twice values of X.

^{^3/}GIYD, GCYD, and RDCGD denote the first difference of GIY, GCY, and RDCG, respectively.

^{^4/}M2YDD, DETYDD, and DETSXDD denote the second difference of M2Y, DETY, and DETSX, respectively.

^{^5/}RSQ is the coefficient of determinantion.

^{^6/}Durbin-Watson statistic for serial correlation.

^{^7/}Number of observations used in the regression, after making the variables stationary—I(0).

^{Table 4.}

Estimates of the Growth Equation ^1/

	Regression Number
Explanatory variables ^2/		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)
Conventional variables
	PIY(t−l)	0.800 ^***	0.790 ^***	0.763 ^***	0.488 ^*	—	0.827 ^***	0.801 ^***	0.740 ^***	0.791 ^***	0.799 ^***	0.647 ^***	0.804 ^***	0.819 ^***
		(5.37)	(5.34)	(5.58)	(1.98)		(5.44)	(5.58)	(4.60)	(5.23)	(5.03)	(3.96)	(5.21)	(5.26)
	GIYD(t−2) ^3/	0.421 ^*	0.419 ^*	0.420 ^*	0.340	0.296	0.359 ^*	0.420 ^*	0.393 ^*	0.415	0.419 ^*	0.318	0.427 ^*	0.224
		(1.73)	(1.74)	(l.89)	(1.41)	(1.17)	(1.45)	(1.80)	(1.61)	(1.64)	(1.70)	(1.33)	(1.71)	(0.85)
	PG(t)	0.693 ^*	—	—	—	—	—	—	—	—	—	—	—	—
	PGHC(t)	—	0.672 ^**	0.635 ^**	0.677 ^**	0.688 ^*	0.662 ^*	0.677 ^**	0.657 ^*	0.674 ^*	0.686 ^*	0.692 ^**	0.940	0.702
			(2.05)	(2.10)	(2.11)	(2.03)	(2.02)	(2.13)	(1.98)	(2.01)	(2.00)	(2.20)	(1.30)	(0.92)
Policy-related variables
	RERG(t−l)	—	—	-0.117 ^**	—	—	—	—	—	—	—	—	—	—
				(2.35)
	BDY(t−l)	—	—	—	-0.117	-0.983 ^***	—	—	—	—	—	—	—	—
					(1.52)	(5.03)
	GCYD(t−l) ^3/	—	—	—	—	—	-0.351	—	—	—	—	—	—	—
							(1.05)
	M2YDD(t−2) ^4/	—	—	—	—	—	—	0.556	—	—	—	—	—	—
								(1.63)
	RDR(t−l)	—	—	—	—	—	—	—	-0.081	—	—	—	—	—
									(0.83)
	RDCGD(t−l) ^3/	—	—	—	—	—	—	—	—	-0.004	—	—	—	—
										(0.08)
Other variables
	TTG(t−l)	—	—	—	—	—	—	—	—	—	-0.011	—	—	—
											(0.18)
	OIL	—	—	—	—	—	—	—	—	—	—	0.031 ^*	—	—
												(1.77)
	DETYDD(t−l) ^4/	—	—	—	—	—	—	—	—	—	—	—	-0.02	—
													(0.04)
	DETSXDD(t−l) ^4/	—	—	—	—	—	—	—	—	—	—	—	—	0.081
														(0.61)
Intercept		-0.124 ^***	-0.129 ^***	-0.122 ^***	-0.066 ^***	0.029 ^*	-0.135 ^***	-0.130 ^***	-0.119 ^***	-0.129 ^***	-0.131 ^***	-0.113 ^***	-0.143 ^***	-0.137 ^***
		(4.29)	(4.36)	(4.45)	(1.31)	(1.75)	(4.49)	(4.55)	(3.77)	(4.26)	(4.01)	(3.83)	(3.77)	(3.37)
RSQ ^5/		0.612	0.617	0.689	0.650	0.593	0.634	0.655	0.627	0.617	0.617	0.661	0.638	0.609
DW ^6/		2.01	2.00	2.19	2.18	2.02	1.95	1.86	1.94	1.99	2.01	2.13	2.16	2.18
N ^7/		32	32	32	32	32	32	31	32	52	32	32	27	27

^{^2/}See Appends I for the definitions and sources of the variables used. The variables X(t), X(t−l), and X(t−2), denote the contemporaneous, lagged once, lagged twice values of X.

^{^3/}GIYD, GCYD, and RDCGD denote the first difference of GIY, GCY, and RDCG, respectively.

^{^4/}M2YDD, DETYDD, and DETSXDD denote the second difference of M2Y, DETY, and DETSX, respectively.

^{^5/}RSQ is the coefficient of determinantion.

^{^6/}Durbin-Watson statistic for serial correlation.

^{^7/}Number of observations used in the regression, after making the variables stationary—I(0).

Regression (1) gives the estimation results, excluding human capital, and regression (2) gives the results, augmented with human capital development. From both regressions it is clear that private investment plays a crucial role in driving economic growth in Cameroon, thus confirming similar results by Khan and Kumar (1993) and Khan and Reinhart (1990) for a diverse group of developing economies, and Ghura and Hadjimichael (1996) for sub-Saharan African countries. The impact of a 1 percent increase in the private investment ratio is estimated to raise growth by about 0.8 percentage point. The effect of government investment on growth, which is positive and significant only at the 10 percent level, occurs with substantial delay. The results of regression (1) and (2) are not much different, with the exception that the effect of population growth augmented by human capital is significant at the 5 percent level in regression (2) versus being significant at the 10 percent level in the regression (1).

The primary aim of regressions (3)−(13) is to test the robustness of the effect of private and government investments on growth. It is clear that the positive effect of private investment on growth is robust, in contrast with the effect of government investment on growth. Improvements in external competitiveness—represented by a decline in RERG—are found to stimulate growth, confirming similar results by Ghura and Hadjimichael (1996) for the case of sub-Saharan Africa. Expansionary fiscal policy—represented by an increase in BDY in regressions (4) and (5)—is harmful to economic growth, confirming similar results by Barro (1991) and Fischer (1991) for a diverse group of countries, and Easterly and Levine (1994), Ghura (1995b), and Ghura and Hadjimichael (1996) for sub-Saharan Africa. It should be noted that the effect of BDY is not significant for the two-tailed test when included together with private investment (regression (4)), owing to the high correlation between PIY and BDY.⁵⁴ Nevertheless, the effect of private investment remains positive, although the magnitude and significance level of this effect fall. From regression (5)—in which PIY is excluded—it is clear that the deleterious effect of expansionary fiscal policy is large; an increase in the budget deficit ratio of 1 percentage point lowers growth by about 1 percentage point.

In addition, the oil sector’s contribution—captured by the variable OIL⁵⁵—was positive and significant, providing evidence pointing to positive externalities from the oil sector to the overall economy and against a Dutch disease type effect. Furthermore, improvements in financial intermediation and deepening—captured by M2Y–are beneficial to economic growth, although this effect is significant at the 5 percent level only for the one-tailed test.⁵⁶ The variables related to government size (GCY), monetary policy (RDR, RDCG), the terms of trade (TTG), and external debt (DETY, DETX) do not have a statistically significant impact on growth.

E. Conclusions and Policy Implications

The determinants of economic growth have been widely investigated by a number of recent studies with cross-sectional data. The current study has contributed to the growth literature with an investigation of the determinants of growth for an individual developing economy—Cameroon—with data for the period 1963–95. The empirical investigation shows that standard results that hold with cross-country data also hold also for Cameroon. In particular, an increase in private investment has a relatively large positive impact on growth. This result, which is robust to various empirical specifications, reinforces the crucial role played by private investment in the growth process. In addition, improvements in external competitiveness are found to stimulate growth in Cameroon. Nevertheless, the effects of variables related to government size, monetary policy, the terms of trade, and external debt are not significant. The results also indicate that inferences based on simple correlations between real GDP growth and its explanatory variables may be misleading, owing to the spurious nature of these correlations. For example, while the correlation coefficients indicate adverse effects on economic growth of restrictive monetary policy and rising external debt burden, the regression analysis, which accounted for the time-series properties of these data, indicates that these effects are not statistically significant.

As increases in private investment stimulate growth, the government should formulate and implement appropriate policies that encourage private sector investment and development. The paper by Hadjimichael and Ghura (1995) has shown that broad-based adjustment policies that emphasize macroeconomic stability and the implementation of structural reforms are likely to stimulate private sector saving and investment. The effect of government investment, however, although positive, is not statistically robust. In the case of Cameroon—a member of a currency union—restrictive fiscal policy plays a crucial role in boosting economic growth, in contrast with the effect of monetary policy, which is not statistically significant. However, while lowering the budget deficit is beneficial to economic growth, doing so by cutting government investment would be counterproductive. Thus, alternative ways of lowering the budget deficit would be needed. In this regard, the ongoing efforts by Cameroon to raise tax receipts by broadening the tax base and improving tax administration represent an important step in the right direction. These reforms are expected to raise government revenue without necessarily raising tax rates, which would tend to undermine private investment. The reallocation of government expenditure to investment in education and health would help raise human capital and contribute to growth.

In addition, policies geared toward maintaining external competitiveness would be expected to significantly boost economic growth. These policies include restrictive fiscal policies, which reduce unproductive government expenditure, while safeguarding investment in infrastructure and human capital development; measures to enhance the efficiency of key public enterprises and utilities, either through privatization and/or the association of private management contracts; the streamlining of the civil service; and measures to safeguard a sound banking sector. Finally, the results indicated, albeit at a low level of statistical significance, that measures to enhance financial deepening would be beneficial to economic growth. Thus, the ongoing efforts to restructure the banking system in Cameroon would be expected to enhance private sector confidence in the domestic financial sector, and boost economic growth.

APPENDIX I

Table 1.

Definitions and Sources of Variables¹

^{^1/}All data series are measured on a fiscal year (July/June) basis.

Table 1.

Definitions and Sources of Variables¹

The sources of the variables will be denoted as (A) various issues of the Article IV consultation document entitled Recent Economic Developments; (B) various issues of Comptes Nationaux du Cameroun and Note Annuelle de Statistique published by the Direction de la Statistique et de la Comptabilité Nationale, Ministry of Planning and Territorial Administration, Yaoundé, Cameroun; (C) various issues of the International Monetary Fund, International Financial Statistics; (D) International Monetary Fund, International Financial Statistics database; (E) International Monetary Fund, World Economic Outlook database; (F) World Bank, Social Indicators of Development database; (G) various issues of World Bank, World Tables; (H) various issues of World Bank, World Debt Tables; and (I) directly from Cameroonian authorities.
YG	Real GDP growth rate. Sources: for the period 1963–68, from (A); for the period 1969–79, from (C); for the period 1980–93, from (B); for the period 1994–95 from (I).
TIY	Total investment (TI) as a ratio to GDP. Sources: for both TI and GDP; for the period 1963–64 from (A); for the period 1965–93, from (B), and for the period 1994–95, from (I).
GIY	Central government investment (GI) as a ratio to GDP. Sources: same as for TI (see TIY above).
PIY	Private investment (PI) as a ratio to GDP, measured as TIY–GIY.
PG	Population growth. Source: data for the population level was obtained from (I).
PGHC	Population growth augmented with human capital development, where the latter is proxied by life expectancy at birth (LIFE). Sources: for population (I); for LIFE from (F).
RERG	Percentage change in the real exchange rate (RER). Following, Edwards (1989), the RER is defined as CPI/(EI. WPIUS), where CPI is the consumer price index (1980=100), EI is an index (1980=100) of the nominal exchange rate (CFAF per U.S. dollar), and WPIUS is the wholesale price index (1980=100) of the U.S. A positive value for RERG denotes an appreciation of the RER. Sources: the monthly series for CPI, E, and WPIUS obtained from (D) were converted into fiscal year (July/June) series. Owing to lack of data, the French monthly consumer price inflation rates were used to construct the monthly CPI for Cameroon for the period 1963–68.
BDY	Government budget deficit (BD) as a ratio to GDP. Source: for GDP, same as for TI (see TIY above); for BD from (A) for the period 1963–84, and from (H) for the period 1985–95.
GCY	Government consumption (GC) as ratio to GDP. Sources: same as for TI (see TIY above).
M2Y	Broad money (M2) as a ratio to GDP. Source: (D). For each fiscal year, the four-quarterly average (for the quarters ending September, December, March, and June) of broad money is taken for M2.
RDR	DR–INF, where DR is BEAC’s end-June discount rate minus the CPI inflation rate for the 12-monthly period to ending June. Sources: DR was obtained from (D); for CPI see above.
RDCG	Percentage change in RDC, where RDC=DC/CPI, DC is total domestic credit. Source: DC was obtained from (D); for CPI see above. For each fiscal year, the four-quarterly average (for the quarters ending September, December, March, and June) of domestic credit is taken for DC.
TTG	Percentage change in the terms of trade. Sources: for the period 1963–93, from (G), and for 1994–95 from (H).
DETY	Total external debt stock (DEBTSTOCK) as a ratio to GDP. Sources: for DEBTSTOCK for the period 1967–69, from (A), and for the period (1970–95), from (E).
DETSX	External debt service (DEBTSERV) as a ratio to exports of goods and services (XGS). Sources: for DEBTSERV, for the period 1967–69, from (A), and for the period (1970–95), from (H); for XGS, for the period 1963–84, from (E), and for the period 1985–95, from (G).
OIL	Dummy variable that takes a value of 1 in the oil boom era (1978–86) and zero otherwise.

^{^1/}All data series are measured on a fiscal year (July/June) basis.

Table 1.

Definitions and Sources of Variables¹

The sources of the variables will be denoted as (A) various issues of the Article IV consultation document entitled Recent Economic Developments; (B) various issues of Comptes Nationaux du Cameroun and Note Annuelle de Statistique published by the Direction de la Statistique et de la Comptabilité Nationale, Ministry of Planning and Territorial Administration, Yaoundé, Cameroun; (C) various issues of the International Monetary Fund, International Financial Statistics; (D) International Monetary Fund, International Financial Statistics database; (E) International Monetary Fund, World Economic Outlook database; (F) World Bank, Social Indicators of Development database; (G) various issues of World Bank, World Tables; (H) various issues of World Bank, World Debt Tables; and (I) directly from Cameroonian authorities.
YG	Real GDP growth rate. Sources: for the period 1963–68, from (A); for the period 1969–79, from (C); for the period 1980–93, from (B); for the period 1994–95 from (I).
TIY	Total investment (TI) as a ratio to GDP. Sources: for both TI and GDP; for the period 1963–64 from (A); for the period 1965–93, from (B), and for the period 1994–95, from (I).
GIY	Central government investment (GI) as a ratio to GDP. Sources: same as for TI (see TIY above).
PIY	Private investment (PI) as a ratio to GDP, measured as TIY–GIY.
PG	Population growth. Source: data for the population level was obtained from (I).
PGHC	Population growth augmented with human capital development, where the latter is proxied by life expectancy at birth (LIFE). Sources: for population (I); for LIFE from (F).
RERG	Percentage change in the real exchange rate (RER). Following, Edwards (1989), the RER is defined as CPI/(EI. WPIUS), where CPI is the consumer price index (1980=100), EI is an index (1980=100) of the nominal exchange rate (CFAF per U.S. dollar), and WPIUS is the wholesale price index (1980=100) of the U.S. A positive value for RERG denotes an appreciation of the RER. Sources: the monthly series for CPI, E, and WPIUS obtained from (D) were converted into fiscal year (July/June) series. Owing to lack of data, the French monthly consumer price inflation rates were used to construct the monthly CPI for Cameroon for the period 1963–68.
BDY	Government budget deficit (BD) as a ratio to GDP. Source: for GDP, same as for TI (see TIY above); for BD from (A) for the period 1963–84, and from (H) for the period 1985–95.
GCY	Government consumption (GC) as ratio to GDP. Sources: same as for TI (see TIY above).
M2Y	Broad money (M2) as a ratio to GDP. Source: (D). For each fiscal year, the four-quarterly average (for the quarters ending September, December, March, and June) of broad money is taken for M2.
RDR	DR–INF, where DR is BEAC’s end-June discount rate minus the CPI inflation rate for the 12-monthly period to ending June. Sources: DR was obtained from (D); for CPI see above.
RDCG	Percentage change in RDC, where RDC=DC/CPI, DC is total domestic credit. Source: DC was obtained from (D); for CPI see above. For each fiscal year, the four-quarterly average (for the quarters ending September, December, March, and June) of domestic credit is taken for DC.
TTG	Percentage change in the terms of trade. Sources: for the period 1963–93, from (G), and for 1994–95 from (H).
DETY	Total external debt stock (DEBTSTOCK) as a ratio to GDP. Sources: for DEBTSTOCK for the period 1967–69, from (A), and for the period (1970–95), from (E).
DETSX	External debt service (DEBTSERV) as a ratio to exports of goods and services (XGS). Sources: for DEBTSERV, for the period 1967–69, from (A), and for the period (1970–95), from (H); for XGS, for the period 1963–84, from (E), and for the period 1985–95, from (G).
OIL	Dummy variable that takes a value of 1 in the oil boom era (1978–86) and zero otherwise.

^{^1/}All data series are measured on a fiscal year (July/June) basis.

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Prepared by Dhaneshwar Ghura.

Throughout this study, fiscal year data are used in the analysis; for example, the year denoted 1994 relates to the fiscal year July 1993-June 1994.

The BEAC is the central bank for six African countries—Cameroon, Central African Republic (CAR), Chad, Congo, Equatorial Guinea, and Gabon. The other members of the CFA franc zone are Benin, Burkina Faso, Côte d’lvoire, Niger, Senegal, Togo, and since 1984 Mali, whose common central bank is the Banque Centrale des Etats de l’Afrique de l’Ouest (BCEAO).

The exchange rate of the CFA franc in terms of the French franc, which had been fixed since 1948, was devalued by 50 percent in foreign currency terms in January 1994, thus changing the parity from CFAF 1 = F 0.02 to CFAF 1 = F 0.01. The CFA franc’s convertibility is ensured by a common operations account maintained by the BEAC and BCEAO with the French Treasury. Under this agreement, a minimum of 65 percent of the two central bank’s foreign reserves must be held in this account. The parity and convertibility of the CFA franc are supported by the French Treasury through overdraft facilities.

See, for example, the papers by Fosu (1990), Ghura (1995a), Ghura and Hadjimichael (1996), Gyimah-Brempong (1991), Ojo and Oshikoya (1995), and Savvides (1995) for the case of Africa; De Gregorio (1993) for the case of Latin America; and Barro (1989, 1991), Fischer (1991, 1993), Grier and Tullock (1989), Knight and others (1993), Khan and Kumar (1993), Khan and Reinhart (1990), Kormendi and Meguire (1985), and Mankiw and others (1992), among others, for more diversified sets of countries.

The paper by Easterly and Levine (1994) found significant “spillover” effects on economic growth in sub-Saharan African countries, whereby economic growth in a particular country has a large significant effect on growth in neighboring countries.

Mbaku’s analysis (1993) focused on the impact of foreign aid on economic growth in Cameroon during 1971–90, and found it to be statistically insignificant.

This problem arises from both a resource-movement effect and a spending effect (Corden (1984)). The spending effect is attributed to the increase in purchasing power, reflected in an increased demand for both traded and nontraded goods. As noted by Benjamin (1990, p. 78), the “new demand for traded goods is met by imports at constant world prices, but the excess demand for nontraded goods causes their price to rise relative to those of traded goods.” The resource-movement effect stems from the upward pressure on the domestic resource costs associated with the production of nontraded goods. In the case of Cameroon, Benjamin and others (1989) note that the oil sector is an enclave with respect to the rest of the economy, as it uses mainly imported factors of production, including labor. Thus, movements in the relative price of nontraded good would most likely have been dominated by the spending effect.

For a detailed discussion of the difficulties in Cameroon’s banking sector in the late 1980s and early 1990s, see Doe (1995).

The weak revenue collection represented mainly the decline in economic activity, as well as extensive exemptions and fraud and weaknesses in tax administration.

See the papers by Renelt (1991) and Easterly and others (1991), which provide surveys of the theoretical and empirical issues related to the neoclassical and endogenous growth models. See also the paper by Otani and Villanueva (1989).

The definitions and sources of the variables used are given in Appendix I.

Under the zone’s institutional arrangement, each member’s monetary financing of the central government’s deficit is limited to a credit ceiling equivalent to 20 percent of the fiill previous year’s total revenue. The limit on government financing applies only to central government credit, and not to that of autonomous government agencies and nonfinancial public enterprises.

See Ntang (1990) for a brief description of interest rate policy in the BEAC region and its effect on money demand during 1970–85.

See Bekolo-Ebe (1989) for an analysis of the widespread informal financial market in Cameroon.

See Easterly and Rebelo (1993) for a detailed discussion of the effects of fiscal policy on growth.

See, for example, the papers by Cottani and others (1990), Edwards (1989), and Ghura and Grennes (1993).

King and Levine (1993) provide a survey of studies investigating the empirical linkages between financial indicators (including the ratio of money to GDP) and economic growth.

Annual data for the period 1963–95 are used for the analysis.

See the paper by Reinhart and Wickham (1994) for a recent application of this methodology to commodity prices.

If a time-series has a break point that is not accounted for in the unit root tests, the tendency would be to over-difference the series to achieve stationarity.

If a variable is nonstationary, it has nonconstant mean and variance. The test statistics from regressions with such variables do not have the standard distributions and conventional interpretations.

If a variable is I(k), it has to be differenced k times for it to achieve stationarity, that is, to be made I(0).

If YG had been I(k), where k > 0, an error correction estimation method would have been required.

The results of regression (4) suffer from multicollinearity, as evidenced from the relatively high R² in the presence of low explanatory power of the included variables.

This variable takes a value of 1 during the oil boom era (1978–86) and zero otherwise.

The positive effect of financial intermediation on economic growth has been documented by De Gregorio and Guidotti (1992) and King and Levine (1993), among others.

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About

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Abstract

A. Introduction

B. Recent History of Cameroon’s Economic Development

Pre-oil era (1965–77)

Oil boom era (1978–86)

Recession period (1987–93)

Recent post-devaluation period (1994–95)

C Empirical Model and Testable Hypotheses

Empirical model

Testable hypotheses

Human capital development (LIFE)

Monetary policy (RDR, RDCG)

Fiscal policy (GIY, BDY, GCY)

External competitiveness (RERG)

Financial intermediation (M2Y)

External debt (DETY, DETSX)

D. Empirical Methodology and Results

Preliminary results

Time-series properties of the data

Regression results

E. Conclusions and Policy Implications

APPENDIX I

References

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