The impact of policy reversal on economic performance in Sub-Saharan Africa

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European Journal of Political Economy 24 (2008) 88 – 106 www.elsevier.com/locate/ejpe

The impact of policy reversal on economic performance in Sub-Saharan Africa Milton Yago a,⁎, Wyn Morgan b a

Department of Economics & International Business, Bronte Hall, Leeds Business School, Headingley Campus, Beckett Park, Leeds LS6 3SQ, UK b School of Economics, Sir Clive Granger Building, University of Nottingham, Nottingham NG7, 2RD, UK Received 31 August 2006; received in revised form 21 August 2007; accepted 22 August 2007 Available online 7 September 2007

Abstract The literature suggests that investment and economic growth respond very slowly to economic reform due to uncertainty about the permanence of reform. Despite clear theoretical underpinnings for the idea that policy reversal significantly impedes economic performance, there is limited empirical evidence on this topic. This paper derives empirical proxies for the probabilities of different types of policy reversal and investigates their impact on investment and growth in Sub-Saharan African countries. The results show that trade, fiscal, savings and financial policy reversals have been very damaging to investment and economic growth. The paper also finds that it is the prediction or expectation that reversal will occur that hurts performance. There is no evidence that exchange rate policy reversal has damaged performance. © 2007 Elsevier B.V. All rights reserved. JEL classification: E22; E61; F13; F41; F43; O11 Keywords: Economic growth; Investment; Economic reform; Policy reversal; Sub-Saharan Africa

1. Introduction Sub-Saharan African countries (SSA) have experienced poor economic growth and performance since the early 1980s, a period characterised by declining national incomes (GNP) per capita and a slowdown in gross domestic product (GDP) growth and decreasing investment1 (Easterly, 2001a,b; Hillman, 20022 ). The period between 1980 and 1996 was characterised by poor economic performances. In terms of investment, the average annual rates of private and gross fixed domestic investments as a percentage of GDP were 12.4 and 20.1 percentage points, which were similar to the rates in Latin America (LAM)3 and South Asia (SA) but much lower than the 22.5 and 32.6 ⁎ Corresponding author. Tel.: +44 113 812 5364; fax: +44 113 812 8604. E-mail address: [email protected] (M. Yago). 1 There has been an attempt by international organisations including the World Bank to help to increase the volume of gross domestic investment in Africa to 23% of GDP by the year 2000 (African Development Bank, 1997). The current volume is only 20% of GDP a year. 2 Hillman (2002) provides a review of Easterly's (2001a) book providing explanations for the development failures experienced in poor countries in Africa and elsewhere in the developing world. 3 The Latin America (LAM) averages are based on data from Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Mexico, Paraguay, Peru and Uruguay. The East Asian (EAS) averages are based on data from Indonesia, Korea (South), Malaysia, Singapore and Thailand. While the South Asian (SA) nations included are Bangladesh, India, Pakistan, Nepal and Sri Lanka. 0176-2680/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.ejpoleco.2007.08.004

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Fig. 1. Regional average growth rates of per capita income: 1980–1996.

percentage points in East Asia (EAS). This pattern of performance is manifested generally in other outcome indicators (World Bank, 1999). The average growth rate of GDP of 3% which translated into growth rate of per capita income of only 0.3% a year was worse than in any other region of the developing world (Yago, 2001; World Bank, 1999)4 . These compare poorly with growth rates of GDP and per capita income of 7.5 and 5.6 percentage points, respectively in the EAS region. Although the rates of growth of GDP and per capita income were 2.7 and 0.9 percentage points in LAM, 5 and 3.1 percentage points in South Asia (SA), respectively, the contrast is made clear by the relative growth of per capita national income as depicted in Fig. 1 below. This implies that in 1996 the region was as poor as it was 15 years before. Unsurprisingly, there has been a great deal of effort exerted in trying to explain this performance. While there is clearly a wide range of hypotheses that could be (and have been) tested to explain poor economic performance in SSA in the 1980s and 1990s, the focus of this paper is on the impact of economic policy reversal on investment and growth. In particular we develop the work of Rodrik (1991) who provides a theoretical basis on which policy reversal can be empirically tested. This paper makes an empirical contribution by investigating the impact of policy reversal on investment and growth in SSA. Section 2 provides an overview of the various explanations of poor economic performance in SSA while Section 3 explains policy reversal in SSA countries. A model of investment and growth under reform reversal is presented in Section 4, while Section 5 discusses the empirical results of the impact of reform reversal on performance. Section 6 offers some conclusions. 2. Explaining economic performance in Sub-Saharan Africa The principle focus of much empirical work in this area has been on economic policy and many studies have attributed poor economic performance to failure in domestic economic policies, including inter alia, lack of openness to international trade (Sachs and Warner, 1997), overvalued real exchange rates (Ghura and Grennes, 1993) and lack of financial deepening (Collier and Gunning, 1999). The link between bad policy design and policy reversal is discussed in Section 3 below. Macroeconomic as well as political instabilities have also been indicted (Collier and Gunning, 1999; Ghura and Hadjimichael, 1995; Fosu, 1992, 2001; Ghura and Grennes, 1993). Some studies, such as Easterly and Levine (1997), Sachs and Warner (1997), and Gallup et al. (1998) have focused on the vagaries of geography,

4

This performance analysis is based only on data for the sample of 24 SSA countries that have been used in the study over the period 1980–1996.

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while others (including Sachs and Warner, 1997; Easterly and Levine, 1997; Easterly, 2001a,b) have also found that ethnic fractionalisation, inadequate institutions and graft have significantly contributed to the economic malaise in the region. Other studies that provide similar evidence include Bardhan (1997), Méndez and Sepúlveda (2006), and Egger and Winner (2005). Hillman's (2004) review of Abed and Gupta (2002) provides an extensive overview of several studies both theoretical and empirical which explain how corruption has negatively affected growth and investment in developing countries by rendering public finance ineffective. A large number of recent empirical studies offer evidence of a positive relationship between institutional developments and economic growth including De Haan et al. (2006).5 Rodrik (2000) presents a thorough analysis of the role and kinds of institutions that matter in providing the environment for long-term economic growth. Rodrik et al. (2004) argue for the primacy of the quality of institutions over other determinants of growth, meanwhile the evidence in Alesina et al. (2003), Montalvo and Reynal-Querol (2005), Bluedorn (2001), Collier and Hoeffler (2002) and Rodrik (1999) generally confirm the negative relationship between ethnic diversity and growth. In addition, another theme in the literature is that external shocks, such as adverse terms of trade for Africa's exports, have contributed more to the economic slump than domestic economic policy failures (for example, Tarp, 1993). Easterly (2001b) reiterates that the role of external shocks needs be given more prominence relative to national economic policies in explaining growth slowdown in developing countries in the 1980s and 1990s. However, Hadjimichael et al. (1995), Rodrik (1999, 2000) and Borrmann et al. (2006) argue that those countries which were able to adjust to such external shocks by adopting the appropriate domestic policy responses or have the proper and adequate institutional setups were able to achieve better economic performance than those that did not. Only recently, failings associated with the World Bank's insistence on using inappropriate models even when they were not working, and which were then exploited by corrupt governments have also been documented as a contributor to the dismal growth performance in developing economies (Easterly, 2001b; Hillman, 2002). As far as economic reforms are concerned, some studies maintain that their implementations including in Africa have been limited in many countries (Milner and Morrissey, 1999; Easterly, 2001b; Rodrik, 1999; Hillman, 2002). Others point out that the gestation period for reform to stimulate performance in the region is much longer than normally expected and therefore the results will take much longer to realise (Collier and Gunning, 1999).6 Empirical evidence shows that developing countries' outcomes to policy reforms of the 1980s and 1990s has been disappointing despite many years of reform (see Easterly, 2001b, 2005; Hillman, 2002). While several studies have made mention of episodes of policy reversal in Africa (Collier and Gunning, 1999; Bouton et al., 1994; Jenkins, 1997; Rodrik, 2000), and there is an established theoretical basis for the adverse impact of policy reversal on economic performance (Rodrik, 1991), there is limited macroeconomic empirical evidence on this issue. Empirical testing of the impact of policy reversal would be of value to governments pursuing credibility enhancing public policies to convince economic agents that reforms would be sustained in the long term. In turn, this would limit the adverse impact of policy reversal on economic performance. Between the mid 1980s and early 1990s, many SSA countries with the financial and technical involvement of the IMF (International Monetary Fund) and the World Bank, embarked on structural adjustment programmes7 (Easterly, 2005). The object of the liberalisation programmes was to achieve more sound economic policies and consequently realise improved and sustained economic performance. After many years of structural adjustment programmes in the region, performances have been disappointing, which some studies suggest can be attributed partly to limited implementation of reform programmes. Also reasons other than economic policy improvements including inadequate institutions, external shocks or the effects of very high risks in the region are suggested (Easterly, 2001b; Hillman, 2002; Rodrik, 2000; Redek and Sušjan, 2005). Insufficient gestation period for reforms is also advanced as a reason for lack of positive response to reform (Collier and Gunning, 1999). Frequently it is argued, and sometimes supported by evidence, that where economic policies have improved, performance has also been superior (Easterly, 2005; Yago, 2001). Whatever the explanation, it is still a huge concern

5 De Haan et al. (2006) provide an extensive review of empirical studies on the relationships between market-oriented institutions and economic growth over the last decade or so. 6 Many SSA countries embarked on economic policy reform during the middle of the 1980s and early 1990s. However, empirical evidence from Chile and Mexico suggests that reform takes about 5 to 15 years to have significant impact on sustained economic performance (Solimano, 1992; Cardoso, 1993). 7 Structural adjustment programmes involve medium- to long-term changing of the structures of the economy to improve production, as opposed to stabilisation programmes which, are short-term measures designed to ensure macroeconomic stability. In practice the difference is obscure.

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that economic performance has not yet responded robustly to structural adjustments. The attempt to offer some explanation for the lack of response to reform in the region is the main object of this study. The theoretical literature and empirical evidence suggest that investment in particular responds slowly to reform due to uncertainty surrounding potential reversal of policy changes (Pindyck, 1988, 1991; Rodrik, 1991). Solimano (1992) shows that it took about five years for investment to respond to policy reform in Chile in the 1980s. Cardoso (1993) on the other hand asserts that it took Chile about 15 years of reform to achieve a recovery in economic performances and a stable development path, and that it took Mexico much longer to achieve the same. A survey of actual and potential investors in East Africa (Bhinda and Martin, 1994) found that the most important impediment to investment in the region was non-commercial risk (e.g. fear of policy reversal and currency inconvertibility). This was closely followed by fear of civil war or social disturbance (African Development Bank, 1997). Despite the strength of the theoretical underpinnings of these ideas there has been a lack of any empirical testing of it. The few existing empirical studies on the impact of reforms for SSA countries are based on data up to 1992/93. However, as mentioned earlier many countries in the region started implementing adjustment programmes seriously in late 1980s and early 1990s. There is therefore very little empirical evidence on the effects of reform on economic performance in SSA to reflect later experience and understanding. 3. Policy reversal in Sub-Saharan Africa: 1980–1996 African economies needed to reform as a precondition to the improvement of economic performance. Those restrictions and official interventions in the working of the economy, which needed reforming, and their manifestations have been reviewed and discussed in detail in studies including Lensink (1996), World Bank (1994a), Easterly (2001a, 2005) and Hillman (2002). For example, these restrictions were manifested in overvalued exchange rates, foreign exchange rationing, high and extremely variable import tariffs and numerous non-tariff barriers (NTB), and often high (implicit and explicit) export taxes. Policy regimes were also typified by poor property rights and bureaucratic investment codes, high government deficits, small volumes of domestic savings (which is an indication of financial repression), macroeconomic instability, inward orientation, an overextended public sector and lack of financial deepening. All these created an environment hostile to investment and growth and contributed to stagnation and decline in economic performance. In a deliberate attempt to reverse the economic decline, many of the countries with the help of the World Bank and the International Monetary Fund (IMF) started to initiate and implement different policy reform programmes in the 1980s and 1990s many of which continued for a long period of time (Easterly, 2005). Rodrik (1991) formally shows that private investment can fail to respond to reform if the permanence of the reform is not credible. The failure of adjustment programmes to produce observable performance improvements elsewhere in the world has also exacerbated the reluctance of economic agents in many countries to believe in the permanence of reform. Policy reversal in developing countries, which we endeavour to define as regression in policy reform is not uncommon Bouton et al. (1994), Dean et al. (1994), McPherson (2000), Reinikka (1996), Collier and Gunning (1999) and Jenkins (1997). Table 1 below shows some episodes of trade and exchange rate policy reversals in the region in a study that reviewed the character and extent of trade liberalisation in 32 developing countries and included 13 SSA countries (Dean et al., 1994). It is obvious from the table that the reform attempts in the region have been prone to reversal. Rodrik (1991) shows that a reform might be reversed if it is expected it will not be permanent even if the expectation is not based on any underlying fundamental reason. A policy reversal may occur because when a reform is introduced, the public may view it as unsustainable. This is probably because reform takes a country into uncharted territory where there will be a legitimate fear that unexpected consequences could lead to reform abandonment. For example, the political economy configuration that supported the earlier undesirable or unsustainable policy regime might reappear. Credibility problems might also arise because of dynamic inconsistency — the government might have an incentive for whatever reason to deviate ex-post from the optimal policy announced ex-ante. Reform might fail simply because there is inadequate institutional foundation to support it from a backlash against reform fuelled by the economic and social uncertainty and instability caused in the early stages of a reform (Rodrik, 2000). Economic agents in the private sector take into account such incentives, which

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Table 1 Dates and episodes of trade and exchange rate policy reversals in SSA: 1985–1994 Country

Commencement of reform Date and episodes of policy reversal

Cameroon 1989 Côte D'Ivoire 1984–86

Ghana

1983, 1987

Kenya

1987–88

Malawi

1988

Madagascar

1986

Mali Nigeria

1986 1986

Senegal

1986

South Africa Tanzania

1989 1986

Uganda

1987

Zaire

1984, 1990

No reversal identified in literature 1987 • Import duties increased by 30% 1988 • Reference prices re-established • Quantitative restrictions returned on many goods 1989 • Special import duty of 10% and statistical royalty of2.5% were introduced 1988 • Imposition of special import taxes on some consumer goods • The range of rates widened to 25% minimum and 95% maximum 1990 • Super sales tax introduced with rates ranging from75%–500% after making great strides in cutting formal tariffs 1993 • Retention scheme privileges for exporters introduced in 1991 were revoked 1991 • By this time the real exchange rate had been allowed from 1988 to appreciate in real terms to reach its pre-reform level of 1984 1991 •Tariff reduction suspended and partially reversed in some cases in October 1991 •The OGL (Open General Licences) system introduced in 1988 was suspended and replaced with a rationing system No reversal episode cited 1988 •The schedule for tariffs for 1988–1999 announced in 1988 with rates higher than the 1986 schedule and programmed to gradually rise until 1994 • There was also a 7% surcharge on all imports • Exports of some primary products were banned, extended to several food crops and raw cocoa in 1989 • Exports of some primary products were banned, extended to several food crops and raw cocoa in 1989–90 1990 • The number of import items banned increased after initial reduction from 72 to 17 in 1986 • Unweighted tariffs had risen by 33%, dispersion had increased and tariffs escalated considerably 1993 • Exchange rate policy reversed as black market premium rose from 34.6 to 128.5% (Bouton et al., 1994) 1988 • Reference prices were reintroduced which effectively protected domestic industries although quantitative restrictions (QRs) were almost completely removed by February1988 1989 • In August custom duties were raised from 10% to 15%. • In addition the government reintroduced some of the previously abolished or new QRs, and specific minimum rates of import duties were introduced 1990 • A stamp duty of 3% was introduced 1991 • As a result of the above reversals, overall statutory rate of import taxes which had been reduced from 98% in 1986 to 68% in 1988 rose again to 90% in 1991 No reversal episode identified in the study 1990 • By this year the changes made increased the average nominal tariff from 28.2% to 29.7% and the dispersion of tariffs from a standard deviation of 16.7 to 17.3 1993 • There was exchange rate policy reversal indicated by increased in black market exchange rate premium from 13.2 to 33.6% (Bouton et al., 1994) 1990 • Use was made of reference prices with tariff equivalents ranging from 150% to 400% even though tariff range and dispersion were reduced significantly

Source: Compiled by authors from Dean et al. (1994), and Bouton et al. (1994).

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may cause a lack of credibility. Political uncertainty about the future could also potentially create incredulity of the long-term survival of reform. The private sector might not know whether liberalisation would still be the objective of the government in the future probably because a new government in a democracy does not support a liberalisation programme as its policy in its bid for election (Ibarra, 1995). It is worth emphasising that policy reversal itself is a consequence of bad policy choices. Credibility problems about the permanence of reform sometimes have resulted when reforms generate unsustainable imbalances in the economy and the government fails to respond appropriately to those imbalances and to support the success of the reform, or refuse to stay the course and abandon the reform altogether. Private agents then would expect policy reversal and therefore act in manners that would enable them to benefit from policy reversal rather than in terms of rational response to a credible and sustainable policy change (Oyejide, 2002). 4. Modelling policy reversal Direct information on episodes of different types of policy reversals in SSA in particular and in developing countries generally is not readily available. Instead, we could determine policy reversals implicitly by defining them as a function of factors that could potentially determine them. Such a limited dependent variable model has been used in a number of studies before including Savvides (1992) and Feder and Just (1977) to derive the probability of debt rescheduling in developing countries. Also of relevance to this study is Ibarra (1995, pp. 45–50) which uses a similar (probit) model to derive empirically a probability of trade policy reform reversal for 19 developing countries8 . In such a model a number of economic indicators determine a latent variable, that is, the sustainability of trade or any other liberalisation programme. As described in more detail in Table 2, changes in the time series determined the binary values such that if the change is negative or positive then an appropriate binary value is assigned. The latent variable is continuous but unobserved. Instead the observed variable is dichotomous (binary). It takes the value of one if a reversal has occurred and zero otherwise. The latent variable is our proxy of policy reversal. This proxy is later used as an explanatory variable in investment and growth equations. The probit model is as follows: y⁎it ¼ bvit þ eit yit ¼ 1 if y⁎it N 0 ð reversal occursÞ yit ¼ 0 ðOtherwiseÞ eit ¼ li þ mit :

ð1Þ

Where yit⁎ is the unobserved probability of policy reversal while yit is observed, χit is a vector of factors influencing policy reversal and β is a vector of parameters to be estimated. The composite error term εit comprises the country- and time-specific error components μI and νt, respectively. From Eq. (1) we obtain Probðyit ¼ 1Þ ¼ Probðuit N  b Vvit Þ ¼ 1  Fðb Vvit Þ

ð2Þ

Where, F is the cumulative distribution function for u. Hence, the likelihood function is; L ¼ jni¼1 ½Uðb Vvit Þyi ½1  UðbVvit Þ1yi

ð3Þ

Where Φ(..) is the distribution function. The maximum likelihood estimators can be shown to be consistent, asymptotically unbiased and efficient (Maddala, 1983). Ibarra (1995) argues that the reversal of trade reform is associated with the collapse of the balance of payments, declining trends of the real exchange rate, and types of inappropriate fiscal and monetary policies, which is similarly presented in Van Wijnbergen (1992). Other characteristics of an economy associated with imbalances in the economy which may lead to reform reversals include external deterioration of the terms of trade, small and falling volumes of capital inflows and weak and 8

Ibarra (1995) uses a probit regression model to derive the probability of trade policy reversal for 19 developing countries not including Mexico. The paper then uses the estimated results to predict the probability of trade policy reversal for Mexico.

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Table 2 Definition of variables used in the probit regression Variable

Value taken 0

1

Sustainability of exchange rate reform SUST_RER Sustainability of trade reform SUST_TRADE Sustainability of savings policy SUST_GDS Sustainability of monetary policy SUST_MON Sustainability of fiscal reform SUST_GCS Change in trade (OPEN) Change in log terms of trade Δlog(TOT) Change in the real exchange rate (Log(RER)) Change in money supply (M2) Change in general govt. consumption (GCS) Change in private investment (IP) Change in growth of GDP (ΔGDP) Change in inflation (INF) Change in bank credit to private sector ratio (BC) Change in total debt service to GDP ratio (TDS) Change in gross domestic savings to GDP ratio (GDS)

Sustained or partially sustained Sustained or partially sustained Sustained or partially sustained Sustained or partially sustained Sustained or partially sustained Up or no change Up or no change Up or no change Up or no change Decrease or no change Increase or no change Expanded or no change Decelerated or no change Up or no change Decreased or no change Up or no change

Reversed Reversed Reversed Reversed Reversed Down Down Down Down Increase Decrease Contracted Accelerated Down Up Down

unstable export performances. These are the kinds of explanatory variables that determine the probability of reversal. A similar procedure to Ibarra (1995) is followed here to predict reversals in other policy indicators including the real exchange rate, trade, fiscal, financial and reversal in policies that encourage mobilisation of resources and increase of domestic savings. We have time series data available on the policy variables or indicators of interest for which we compute annual changes yielding the binary values that are used to derive the probabilities of different policy reversal. We use a probit model to predict policy reversal given a set of the binary explanatory variables, which are explained in Table 2 below. Sustainability of a reform (SUST (..)) is the dependent binary variable with all others being independent. According to the definitions in Table 2 therefore, the dependent variable is 0 if the policy reform is sustained or partially sustained and 1 if it is reversed. From the information in the equation and Table 2, a probit9 model employing binary variables on both the left and right hand sides is used where the value of the fitted dependent variable proxies or predicts the probability of policy reversal (Ibarra, 1995; pp. 49). The empirical probit equation for the probability of exchange rate policy reversal is: SUST RERit ¼ a0i þ a1 DGDPit þ a2 TDSit þ a3 DlogTOTit þ a4 M 2it þ a5 GCSit þ a6 OPENit þ a7 INFit þ lit ð4Þ SUST_RER is the sustainability of exchange rate policy and uit is the error term. The explanatory and the dependent variables are binary according to the definitions in Table 2. The dependent variable, starting from the date reform was initiated, is zero if the real exchange rate increases (depreciates) or is unchanged, and 1 if it decreases (appreciates), and zero elsewhere. The sustainability of the other policy reforms is estimated separately using Eqs. (5)–(8) below. SUST_GCS is the sustainability of fiscal policy, SUST_TRADE is for trade policy sustainability, SUST_GDS represents the sustainability of policy to encourage savings and lastly SUST_FIN is the sustainability of financial reform. The estimation procedure in every case is the same as for Eq. (4). The variables used also have binary values both on the left and right sides consistent with the definitions in Table 2. For example, in Eq. (5) as it was in Eq. (4), the dependent 9 The probit and logit estimates are unlikely to produce significantly different results for a sample the size of ours since the cumulative normal and logistic distributions are very close to each other except at the tails. We will not have enough observations at the tails, hence the indifference in the choice of method (See Maddala, 1983).

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Table 3 Maximum likelihood estimates of the probabilities of reform reversal 10 Dependent variable: sustainability of reforms (SUST_(.)) Policy reform

RER

GCS

OPEN

GDS

M2

Regression number

(1)

(2)

(3)

(4)

(5)

0.092 (0.45) – – – – 0.028 (0.13) 0.58 (3.051) 0.61 (3.13) – – 0.46 (2.25) – – – – − 1.79 (− 10.92) 5 − 136.74 40.4 87 354

0.94 (5.28) 0.61 (3.35) 0.26 (1.37) 0.64 (3.51) – – – – – – – – – – – – −1.61 (− 11.57) 4 −193.97 103.96 79 354

– – – – 0.65 (3.71) – – 0.55 (3.31) – – – – 0.59 (3.45) – – – – − 1.21 (− 10.72) 3 − 197.4 52.099 75 354

0.79 (4.23) – – – – 0.33 (1.74) 0.34 (1.89) 0.55 (3.096) 0.206 (1.09) 0.49 (2.59) – – – – − 1.56 (− 10.84) 6 − 202.82 102.19 79 354

– – – – 0.26 (1.36) 0.22 (1.16) – – 0.39 (2.092) 0.67 (3.52) − 0.13 (−1.21) 0.21 (1.13) 1.054 (6.004) − 1.54 (−10.71) 7 − 205.89 114.69 79 354

Independent variables ΔGDP TDS IP Δlog(TOT) M2 OPEN INF GCS GDS BC Constant Degrees of freedom Log likelihood χ2 Percentage of successful predictions Number of observations

Notes: t-statistics are in parentheses. The columns represent the estimates of the sustainability of each of the policy reforms. For example column 1 represents the probit estimate of the sustainability of exchange rate (RER) policy reform and so on.

variable (SUST_GCS), starting from the date reform was initiated, is zero if government consumption ratio decreases or is unchanged, and 1 if it increases, and zero elsewhere. SUST GCSit ¼ b0i þ b1 DGDPit þ b2 TDSit þ b3 IPit þ b4 Dlog TOTit þ lit

ð5Þ

SUST TRADEit ¼ d0i þ d1 DGDPit þ d2 IPit þ d3 Dlog TOTit þ d4 M 2it þ d5 GCSit þ lit

ð6Þ

SUST GDSit ¼ g0i þ g1 DGDPit þ g2 DlogTOTit þ g3 M 2it þ g4 OPENit þ g5 INFit þ g6 GCSit þ lit

ð7Þ

SUST FINit ¼ u0i þ u1 IPit þ u2 DlogTOTit þ u3 OPENit þ u4 INFit þu5 GCSit þ u6 GDSit þ u7 BCit þ lit ð8Þ However, the explanatory variables differ in the different probit equations depending on the underlying economic theory. For example, real exchange rate appreciation is a function of an increase in growth and terms of 10

We have also experimented with deriving probabilities of reversal when a policy regresses for at least two, and also three consecutive years. The impacts of both these more restricted definitions of policy reversal were also tested in the investment and growth equations. However, there were no significant differences in the impact of reversals even if we restrict the definition of reversal to at least two or three consecutive years of policy regression. The intuition in these results is that it is the expectation or the prediction that reversal will likely occur that is damaging to economic performance rather than the duration of policy regression. We therefore present only the results for the least restrictive definition of reversal (i.e. policy regression for at least one year).

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Table 4 Impact of policy reversals on investment and growth in SSA Dependent variables:

Private investment

Regression number (1) Type of policy reversal Fiscal

− 0.99 (−1.63) Trade – – Savings – – Financial – – Real exchange rate – –

Gross domestic investment

(2)

(3)

(4)

(5)

(6)

(7)

– – − 1.79 (− 2.69) – – – – – –

– – – – −0.15 (− 0.29) – – – –

– – – – – – − 0.73 (− 1.42) – –

– – – – – – – – 0.094 0.025

− 0.56 – (− 1.15) – − 1.21 – (−2.23) – – – – – – – – – – – –

Growth of gross domestic product

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

– – – – − 0.43 (− 1.05) – – – –

– – – – – – − 0.84 (−2.05) – –

– – – – – – – – − 0.45 (− 0.15)

−3.52 (− 4.53) – – – – – – – –

– – − 3.27 (− 3.73) – – – – – –

– – – – −2.45 (− 3.73) – – – –

– – – – – – 0.17 0.26 – –

– – – – – – – – 0.77 (0.15)

Notes: t-ratios are parenthesis below coefficient estimates for the impact of the probability of different policy reversal. The complete regressions including the other explanatory variables for investment and growth are presented in the Appendix.

trade improvement, but fiscal policy reversal is a function of a contraction in growth and deteriorating terms of trade. The model is estimated first by OLS and then by Maximum likelihood methods. This two-staged limited dependent variable method provides consistent and efficient estimates of the parameters of the probit model (Maddala, 1983). The results for the estimation of the predicted probabilities of different policy reversals are presented in Table 3 below. Estimation is via LIMDEP 8.0. The table includes probabilities of reversal when a policy regresses for at least one year as defined in Bouton et al. (1994). The probit maximum likelihood estimates show that all the explanatory variables in the models that are significant have the expected signs. For example in regression 2, contraction in GDP is positively correlated with fiscal policy reversal and in regression 1 a decrease in international trade (openness) is positively and significantly correlated with real exchange rate appreciation (reversal). The models are successful in that between 75 to 87% of the predictions of the model are correct. 5. Impact of policy reversal on investment and growth To test the impact of different types of policy reversals, the proxies for the predicted probabilities of trade, exchange rate, fiscal, financial and savings policy reversals which are derived from the estimation of the probit Eqs. (4)–(8) using definitions in Table 2 in Section 4 are inserted separately as explanatory variables in the investment and growth equations. The information on the data used in the models come mainly from the World Bank (World Bank, 1994b, 1997, 1999) except for terms of trade and private investment ratios which come from the IMF (IMF, 1997, 2000). Structural adjustment commencement dates are compiled from Lensink (1996) and Dean et al. (1994). The empirical investment and growth Eqs. (9)–(11) below11 are estimated in the second stage by the OLS procedure with unbalanced panel data for 24 SSA countries12 , over the period 1980–1996. All the variables are defined as before in Table 2, where Xit−j represents the xth variable in the ith country in year t. Also μi, νt and εit are the country-specific, time-specific and overall equation error terms, respectively. The variable θit is the predicted 11 Empirical research shows that in the long-run, both investment and growth of gross domestic product are determined generally by the same factors (Fisher, 1991). 12 The 24 SSA countries in the model are Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cóte D’ Ivoire, Central African Republic, Ethiopia, Gabon, Ghana, Kenya, Madagascar, Malawi, Mauritius, Nigeria, Senegal, Seychelles, Sierra Leone, South Africa, Swaziland, Tanzania, Togo, Uganda, and Zimbabwe.

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Table 5 Private investment equations with adjustment dummies and policy reversals Dependent variable: private investment ratio Regression number:

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

Savings policy reversal

− 0.28 (−0.46) – – – –

− 0.19 (−0.33) – – – –

– – − 2.02 (−2.63) – –

– – − 1.89 (−2.55) – –

– – – – −0.81 (− 1.18)

– – – – – –

– – – – – –

– – – – – –

– – – – – 0.83 (1.42) – – 0.66 64.15

– – – 1.51 (2.58) – – – – 0.67 65.43

– – – – – – −0.93 (− 1.603) – – 1.65 (2.73) – – – – 0.66 64.35

– – – – −0.69 (− 0.99)

– – – – – – – 0.51 (0.79) 0.66 62.22

– – – – – – − 0.701 (−1.204) – – – – 0.65 (1.11) – – 0.66 62.65

– – – – – 0.65 (1.096) – – 0.66 62.52

– – – 1.55 (2.60) – – – – 0.66 64.03

– 0.005 (1.18) 1.42 (2.42) – – – – 0.66 64.02

– 0.005 (1.18) – – 0.51 (0.88) – – 0.66 62.63

– 0.005 (1.18) – – – – 0.46 (0.74) 0.66 62.57

Trade policy reversal Fiscal policy reversal Monetary policy reversal

– – – Trade reform programme – – Structural adjustment programme 0.59 (0.98) Enhanced structural adjustment programme – – Adjusted R-squared 0.66 F(11,342) 62.31 Exchange rate policy reversal

probability of different policy reversals. Initially we estimate the empirical models below with the predicted probability of real exchange rate policy reversal (θit), and then alternatively with the other probabilities of policy reversal one at a time. IPit ¼ k1 DGDPi;t1 þ k2 IPi;t1 þ k3 logRERi;tj þ k4 OPENi;t þ k5 GDSi;tj þ k6 TDSi;tj þ k7 DlogTOTi;tj þ k8 hit þ li þ mt þ eit

ð9Þ

GDIit ¼ g1 DGDPi;t1 þ g2 GDIi;t1 þ g3 logRERi;tj þ g4 OPENi;t þ g5 GDSi;tj þ g6 TDSi;tj þ g7 M 2i;tj þ g8 GCSi;tj þ g9 DlogTOTi;tj þ g10 hit þ li þ mt þ eit

ð10Þ

DGDPit ¼ ϖ1 DGDPi;t1 þ ϖ2 IPi;tj þ ϖ3 INFi;t þ ϖ4 OPENi;t þ ϖ5 GDSi;tj þ ϖ6 M2i;tj þ ϖ7 GCSi;t þ ϖ8 hit þ :li þ mt þ eit

ð11Þ

Where: i = 1,…, 24; j = 0, 1 We present only the coefficients and t-ratios for the policy reversal variables in Table 4 below. The full estimates including all the other variables as well as the policy reversal variables are presented in the Appendix for the interested reader. The intercept terms are not included in the regression results. Columns 1 to 5 in Table 4 are coefficients and t-ratios for the policy reversal variables from the private investment regressions from Table A1 in the Appendix. Columns 6 to 10 and 11–15 are coefficients for gross investment and growth regressions, respectively, from the same table. The empirical growth equation is estimated first with private investment on the right and alternatively with gross investment. All the coefficients for the probabilities of reform reversals that are statistically significantly different from zero have the expected negative signs. The results show that lack of credibility in the permanence of fiscal, trade, and financial policy reforms have adversely and significantly affected private investment in SSA since the beginning of structural adjustment programmes in the mid 1980s. Gross domestic investment has also been adversely and significantly reduced by a lack of belief in the sustainability of trade and financial policy reforms, while growth has been significantly reduced by a lack of credibility that fiscal, trade and policies aimed at mobilising domestic savings would be sustained in the long term.

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Table 6 Gross domestic investment equations with adjustment dummies and policy reversals Dependent variable: gross domestic investment ratio Regression number

(1)

– – Trade policy reversal – – Fiscal policy reversal −0.97 (− 1.82) Monetary policy – reversal – Exchange rate – policy reversal – Trade reform – programme – Structural adjustment 0.85 programme (1.97) Enhanced structural – adjustment programme – Adjusted R-squared 0.77 F(11,342) 105.8 Savings policy reversal

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

– – – – − 0.82 (− 1.57) – – – – – – – – 0.75 (1.64) 0.77 105.4

– – – – – – − 0.88 (− 2.00) – – – – 0.85 (1.93) – – 0.77 94.14

– – – – – – − 0.82 (− 1.90) – – – – – – 0.87 (1.84) 0.77 94.02

– – – – – – − 0.86 (−1.96) – – 0.71 (1.57) – – – – 0.77 93.69

−0.90 (− 1.93) – – – – – – – – – – 0.93 (2.09) – – 0.77 106.1

−0.76 (− 1.68) – – – – – – – – – – – – 0.81 (1.75) 0.77 105.5

– – − 1.27 (− 2.23) – – – – – – 0.67 (1.61) – – – – 0.77 101.9

– – − 1.52 (− 2.63) – – – – – – – – 1.01 (2.41) – – 0.78 103.2

– – − 1.30 (− 2.29) – – – – – – – – – – 0.92 (2.07) 0.78 102.6

– – – – – – – – 0.003 (0.91) – – – – 0.63 (1.39) 0.76 104.7

– – – – – – – – 0.003 (0.902) – – 0.64 (1.51) – – 0.76 104.9

– – – – – – – – 0.0031 (0.93) 0.22 (0.53) – – – – 0.76 104.11

A 1% decrease in uncertainty about the permanence of fiscal reform would increase private investment by about 1% of GDP a year13. A one percentage reduction in credibility of trade policy reform decreased gross domestic investment by 1.2% of GDP a year. Considering that the average ratio of private investment in the region is 12% of GDP a year during the period, a percentage decrease in uncertainty about permanence of fiscal reform would have increased IP to over 20% of GDP over ten years. This investment rate would have been comparable to the ratio in East Asia (EAS) over the same period. Trade policy reversal seems to have had a more direct adverse impact on growth than on investments. Growth was reduced by up to 3.5% a year compared to 1.8 and 1.2 percentage points of GDP a year, for private and gross domestic investments, respectively. This result seems to suggest that trade policy reversal effects were felt more on the domestic demand side and external sectors of the economy. On the external sector the impacts may have come from uncertainty about the future of reform of the trade sector such as restructuring of agricultural marketing organisations, liberalisation of agricultural prices and price setting, trade taxes, high and complex tariffs systems, exchange rate allocation policies, import quotas and other non-tariff restrictions. Economic agents may have remained suspicious of the ability and intentions of governments to dismantle such restrictiveness in the long-term. This is consistent with the evidence in World Bank (1994a) and Lensink (1996) which show that trade reforms have not been very successful in SSA. This uncertainty about the future of trade reforms may have also stifled capital inflows from abroad into the region especially in the mid 1980s and early 1990s (Easterly, 2001b). The above argument is affirmed by the fact that trade policy has been the least credible of all the policy reforms, and it reduced all the three performance indexes significantly by at least a percentage point a year. The empirical results show no significant evidence that there has been a lack of credibility of exchange rate policy reform. This result is consistent with a number of other studies including the World Bank (1994a) and Easterly (2001b), which show that exchange rate reform has been one of the relatively more successful liberalisation achievements in the region. The implication of this result is that reform actually works; at least the short-term policy reforms like exchange rate liberalisation, if implemented. This however, does not imply that exchange rate reforms

13 These interpretations of the estimated coefficients as elasticities are consistent with the interpretations in similar studies including Ibarra (1995) and Savvides (1992). In Ibarra (1995), a 1 percentage increase in probability of trade policy reversal leads to a 0.004 percentage decrease in 1investment and consequently a 50 percentage (10%–60%) rise in the probability of reversal leading to a 2% fall in investment.

M. Yago, W. Morgan / European Journal of Political Economy 24 (2008) 88–106

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Table 7 Gross domestic product equations with adjustment dummies and policy reversals Dependent variable: growth of gross domestic product Regression number

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Savings policy reversal Trade policy reversal Fiscal policy reversal Monetary policy reversal Exchange rate policy reversal Trade reform programme Structural adjustment programme Enhanced structural adjustment programme Adjusted R-squared F(11,342)

– –

– –

– –

– –

– –

– –

– – − 3.82 (−4.76) – –

– – − 3.65 (− 4.65) – –

– – −3.76 (− 4.75) – –

− 3.30 (−3.75) – – – –

− 3.44 (− 3.81) – – – –

– –

– –

– –

– –

– –

– –

0.73 (1.14)

0.76 (1.16)

– –

– –

(8)

(9)

(10)

(11)

(12)

(13)

(14)

−2.79 − 2.63 − 2.82 – (− 4.02) (−3.90) (− 4.09) –

– –

– –

– –

– –

− 3.29 (− 3.73) – – – –

– – – – – –

– – – – – –

– – – – – –

– – – – 0.15 (0.21)

– – – – 0.19 (0.28)

– – – – – –

– – – – – –

– – – – – –

– –

– –

– –

– –

– –

– –

– –

−0.003 − 0.003 −0.031 (− 0.62) (−0.62) (− 0.62)

– –

0.303 (0.48)

– –

– –

– –

0.94 (1.42)

0.083 – (0.12) –

– –

– –

0.53 (0.79)

– –

0.81 (1.20)

– –

– –

– –

− 0.103 – (− 0.15) –

− 0.047 – (−0.07) –

0.41 (0.59)

– –

– –

– –

0.13 (0.19)

– –

0.51 (0.73)

– –

– –

– –

– –

– –

−0.087 (− 0.12)

0.15

0.15

0.15

0.13

0.13

0.13

0.14

0.14

0.14

0.10

0.10

0.1

0.1

0.1

6.82

6.71

6.81

5.93

5.97

5.91

6.14

6.04

6.20

4.47

4.47

4.5

4.5

4.5

0.13 – (0.202) –

– –

have gone far enough. There seems to be a long way yet for the real exchange rates to move closer to their equilibrium levels. It is asserted by Dean et al. (1994) that the non-achievement of full convertibility of the currency by most of the countries in SSA shows that the real exchange rates are far from equilibrium. Also, although most of the countries achieved real depreciations, unfortunately evidence shows that most floating exchange rates across SSA are subject to considerable official interference (Dean et al., 1994; McPherson, 2000). McPherson argues further that adverse outcomes common in these economies such as chronic balance of payment deficits, slow growth, rising external debt, continued dependence on aid and slow export growth (World Bank, 1999; Yago, 2001) are symptomatic of persistent overvalued real exchange rates. Despite the evidence from other studies that GCS as a proportion of GDP in most SSA countries has fallen significantly since the 1980s, the empirical results here suggest that the ability of the governments in the region for competent fiscal management has not won credibility among economic agents. The results also seem to suggest that change in the period means of GCS is a poor proxy for fiscal policy improvement14. We need to investigate whether other aspects of reform programmes did help to reduce the adverse impact of the likelihood of policy reversal on performance in the region. Including adjustment year dummies (derived from the years in which reforms commenced) in the models offer tests for whether the adverse impacts of reversal on performance were meliorated by aspects of ongoing reform activities. These activities include the granting and disbursement of credit and the expectation of future inflows of credit to support the reform programme. Other aspects of the liberalisation programme include the size of the loan, donor's

By using a “before and after” method of evaluating reform impact (see Lensink, 1996), Yago (2001) shows that there was a significant reduction in the GCS ratio in almost all the countries in SSA between the periods 1980–98 and 1990–97. 14

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preparation and supervision of loans, the number of conditionalities attached to the programme as well as the sequencing of the conditionalities (see Dollar and Svensson, 2000). The results for the regressions and those tests are presented in Tables 5–7) below. The tables only show coefficients for reform and reversal variables, but the full regressions are presented in the Appendix. In the private investment equations the magnitude and significance of the coefficients for the fiscal policy reversal indicator are reduced, and the trade policy reform year dummy is positive and significantly different from zero in all the regressions. This is contrary to Bleaney and Fielding (1995) who find no significant impact of reform on private investment in a panel of 22 developing countries. Our result suggests that increase in the "volume"15 of trade reform positively affect private investment by reducing the adverse impact of fiscal policy reversal. A liberalised trade sector might stimulate production for exports and therefore increase foreign exchange earnings, which in turn improves government finances hence adding credibility to fiscal policy sustainability over the long term. Trade reform is associated with an increase in all performance indicators although it does not seem to lessen the likelihood that all the other types of policies including trade policy would be reversed. This also suggests that trade reform should be a priority in stimulating investment and growth in the region which is consistent with the results in Table 4 where we have found that trade reform reversal has been the most damaging to performance than any other policy regression. Adjustment programmes and deeper adjustment programmes (enhanced structural adjustment programmes) in the gross investment models are positively and significantly associated with an increase in all performance variables without significantly lessening the magnitude and significance of the coefficients of the reversal variables. This seems to suggest that the size of the loans, donors supervision of programmes, the number of conditionalities and all other aspects of reform programmes do not affect the probability of the reform failing. It also suggests that external influence does not make structural reform more or less credible and successful. This is consistent with Dollar and Svensson (2000) who find no evidence that donors' influence affects the success of a reform significantly. In the growth equations in Table 7, all the adjustment variables have no explanatory power even though almost all of them have the expected positive sign. However, the policy reversal variables have more or less unchanged magnitude and significance of coefficients from the equations without adjustment dummies (Table 4). This implies that the likelihood of reform reversal other than for exchange rate and financial liberalisation has reduced growth, and that other aspects of reform have not lessened these significant adverse effects. 6. Conclusions and policy implications The primary motivation of this piece of work has been to investigate empirically the impacts of policy reversal on economic performance in SSA, especially investment and economic growth. The evidence shows that trade policy reversal has been the most damaging policy regression, and has reduced private and gross domestic investments, as well as growth, markedly. Fiscal policy reversal has significantly impeded growth of national product or income much more than it has reduced private investment, while financial policy reversal has reduced gross domestic investment very significantly. Policies aimed at mobilising domestic savings have also been reversed and these have impacted negatively and significantly on the growth of national product. Fiscal and trade policy reversals reduced private investment by about 1% and 2% of GDP, respectively. Trade and financial policy reversals also each reduced gross domestic investment by about 1% of GDP, and fiscal, trade and savings policy reversals all reduced growth by up to 3 percentage points a year. Exchange rate policy has been (relatively) the most credible reform endeavour and has had no significant adverse impact on performance. This result is consistent with other empirical studies which show that exchange rate policy reform has been one of the most successful liberalisation exercises in the region. Policy reversals have directly and adversely affected growth of national income much more severely than investments. This seems to suggest a lack of credibility of the governments' ability to sustain policy reforms affecting the external sector of the economy, especially the trade sector. A significant result from the study is that what is 15

See inter alia Kormendi and Meguire (1985), Fisher (1991), Ghura and Hadjimichael (1995), Bleaney (1996), Redek and Sušjan (2005). This argument is parallel to the assertion that if an investment variable is added to a growth equation and both the magnitude and significance of the coefficient of the policy variable fall, then the policy variable affects growth through the volume rather than efficiency of investment.

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101

damaging to economic performance is the likelihood of policy reversal occurring rather than its length. This supports the conclusion of the theoretical study mentioned earlier that motivated this empirical research. Once reversal has occurred the length of the period of policy regression does not affect performance, at least over the time period sampled. These results imply that SSA and developing countries generally, as well as donor organisations and policy makers, should seek to pursue credibility-enhancing reform measures during adjustment programmes. Such measures would include a clear and an unambiguous pronouncement of intent and commitment by the government to irreversible liberalisation. Beyond intent and commitment, the governments may also enhance reform credibility by investing in projects and establishing institutions with externalities that stimulate private investment activity. Encouraging investment might require adoption of investment codes and institutions to safeguard against non-commercial risks and certainly it could be encouraged by governments signing up to regional or multilateral trade commitments such as membership of the WTO. Such moves might induce greater confidence in economic agents that policy reform will not be reversed and thus encourage greater levels of risk taking and investment. Acknowledgments The authors would like to thank Michael Bleaney, Arye Hillman, Chris Milner and two anonymous referees for encouragement and comments on an early draft which significantly improved this piece of work. Any remaining errors are ours. Appendix A. Complete regression results Table A1 Impacts of policy reversal on investments and growth in SSA Dependent variables

Private investment ratio

Regression number

(1)

ΔGDP_1

– – – – – – – – – – 0.082 0.12 0.081 0.088 0.089 – – – – – – – – – – (1.92) (2.68) (1.91) (2.11) (2.13) – – – – – – – – – – 0.074 0.12 0.074 0.063 0.046 – – – – – – – – – – (1.75) (2.03) (1.73) (1.52) (1.08) 0.32 0.31 0.32 0.31 0.31 – – – – – – − 0.058 – – – (7.079) (6.96) (7.19) (6.97) (6.98) – – – – – – (−1.10) – – – – – – – – 0.46 0.53 0.54 0.54 0.55 – – – – – – – – – – (11.56) (14.28) (14.55) (14.6) (14.7) – – – – – 0.049 0.053 0.047 0.052 0.048 0.088 0.053 0.052 0.052 0.051 0.021 0.022 0.022 0.025 0.023 (2.22) (2.401) (2.14) (2.29) (2.17) (5.97) (5.41) (5.38) (5.37) (5.27) (2.054) (2.18) (2.10) (2.42) (2.24) – – – – – – – – – – −0.026 − 0.021 − 0.025 − 0.026 −0.24 – – – – – – – – – – (− 1.82) (−1.59) (− 1.79) (− 1.90) (− 1.77) – – – – – 0.25 0.24 0.26 0.26 0.26 −0.078 − 0.074 − 0.079 − 0.083 −0.081 – – – – – (5.45) (5.44) (6.039) (6.11) (5.78) (− 1.57) (−1.54) (− 1.61) (− 1.72) (− 1.68) – – – – – − 0.29 −0.27 − 0.31 − 0.32 − 0.29 – – – – – – – – – – (7.304) (− 6.82) (−8.41) (− 8.48) (− 7.20) – – – – – 0.059 0.062 0.062 0.061 0.063 0.17 0.19 0.19 0.19 0.19 0.18 0.16 0.18 0.18 0.19 (1.41) (1.49) (1.51) (1.45) (1.504) (4.81) (6.45) (6.82) (6.69) (6.40) (4.61) (3.85) (4.61) (4.52) (4.78) − 0.078 − 0.078 −0.075 − 0.078 − 0.081 − 0.101 −0.093 − 0.11 − 0.11 − 0.089 −0.16 − 0.15 − 0.16 − 0.16 −0.16 (− 2.37) (− 2.39) (− 2.304) (−2.36) (− 2.48) (− 3.79) (− 3.42) (−4.31) (− 4.24) (− 3.29) (− 4.31) (−3.56) (− 4.32) (− 4.32) (− 4.22) − 0.22 − 0.022 −0.23 − 0.22 − 0.23 – – – – – – – – – – (− 2.93) (− 2.93) (− 3.012) (−2.94) (− 3.025) – – – – – – – – – – – – – – – – −0.094 – – − 0.085 – – – – – – – – – – – (− 2.43) – – (− 2.22) – – – – – – – – – – 0.14 0.11 0.13 0.13 0.12 −0.102 − 0.11 − 0.103 − 0.102 −0.087 – – – – – (3.064) (2.602) (3.36) (3.29) (2.83) (− 2.06) (−2.05) (− 2.09) (− 2.11) (− 1.81) – – – – – − 0.089 −0.084 − 0.12 − 0.12 − 0.093 0.082 0.088 0.084 0.073 0.07 – – – – – (− 2.55) (− 2.32) (−3.55) (− 3.48) (2.61) (1.93) (1.85) (1.97) (1.76) (1.67)

IP IP_1 GDI_1 OPEN INF GCS GCS_1 GDS GDS_1 TDS TDS_1 M2 M2_1

(2)

(3)

Gross domestic investment ratio (4)

(5)

(6)

(7)

(8)

(9)

Growth of gross domestic product (10)

(11)

(12)

(13)

(14)

(15)

(continued on next page)

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M. Yago, W. Morgan / European Journal of Political Economy 24 (2008) 88–106

Table A1 (continued ) Dependent variables

Private investment ratio

Regression number

(1)

(2)

(3)

Gross domestic investment ratio (4)

(5)

− 1.405 −1.57 − 1.38 − 1.53 − 1.37 (− 3.08) (− 3.52) (−3.084) (− 3.31) (− 2.94) Log(RER)_1 1.95 1.94 1.97 1.94 1.93 (5.66) (5.58) (5.75) (5.59) (5.59) Δlog(TOT) − 6.55 −5.64 − 6.28 − 5.81 − 6.081 (− 1.91) (− 1.66) (−1.87) (− 1.69) (− 1.79) Δlog(TOT)_1 − 2.19 −2.17 − 2.22 − 2.18 −2.17 (− 6.08) (− 5.99) (−6.19) (− 6.00) (− 5.99) Fiscal policy − 0.99 – – – – reversal (− 1.63) – – – – Trade policy – – − 1.79 – – reversal – – (−2.69) – – Savings policy – – – − 0.15 – reversal – – – (− 0.29) – Financial policy – – – – − 0.73 reversal – – – – (− 1.42) Exchange rate – 0.094 – – – policy reversal – (0.025) – – – Adjusted0.75 0.75 0.76 0.75 0.75 R-squared F-statistics 33.77 33.41 34.39 33.43 33.68 LM statistics 19.08 18.33 19.86 18.32 18.9 Hausman statistics 49.61 48.85 48.27 49.06 49.75 Number of 354 354 354 354 354 observations

Log(RER)

(6)

(7)

(8)

(9)

Growth of gross domestic product (10)

(11)

(12)

(13)

(14)

(15)

– 0.48 – – 0.43 – – (2.066) – – (1.91) – – – – – – – – – – – – – − 14.01 − 14.49 − 13.63 − 14.1 −14.32 – (− 5.02) (− 5.29) (−4.98) (− 5.09) (− 5.25) – – – – – – – – – – – – – − 0.56 – – – – – (− 1.15) – – – – – – – – – −1.21 – – – – – (− 2.23) – – – – − 0.43 – – – – – (− 1.05) – – − 0.84 – – – 0.17 – (− 2.05) – – – (0.26) – – − 0.45 – – – – – (−0.15) – – – 0.80 0.81 0.80 0.80 0.81 0.10

– – – – – – – – – – – – – – – – − 3.52 – (− 4.53) – – – – – – – – – – – – – 0.77 – (0.15) 0.15 0.10

– – – – – – – – – – – – – – – – – – – – −3.27 – (− 3.73) – – − 2.45 – (−3.73) – – – – – – – – 0.14 0.14

45.04 14.67 32.35 354

6.79 4.30 18.62 354

6.51 3.53 17.81 354

42.92 8.82 27.43 354

44.81 14.7 32.35 354

44.92 13.91 32.06 354

42.92 7.75 27.23 354

4.93 3.07 18.66 354

4.92 2.98 18.2 354

6.39 1.89 16.49 354

Table A2 Private investment ratio equation with adjustment dummies and policy reversals Private investment_1

0.69 (19.01) Openness 0.017 (2.22) Gross domestic savings 0.19 (5.28) Gross domestic savings_1 −0.11 (− 2.99) Debt service ratio −0.16 (− 2.58) Real exchange rate −1.82 (− 4.54) Real exchange rate_1 2.05 (5.34) Change in the log of terms −5.90 of trade (− 1.50) Change in log of terms of trade_1 −2.64 (− 6.69) Savings policy reversal −0.28 (− 0.46) Trade policy reversal – – Fiscal policy reversal – –

0.696 (18.93) 0.016 (2.14) 0.19 (5.26) −0.11 (− 3.079) −0.16 (− 2.704) −1.79 (− 4.51) 2.031 (5.29) −5.84 (− 1.49) −2.62 (− 6.64) −0.19 (− 0.33) – – – –

0.699 (19.25) 0.019 (2.45) 0.19 (5.30) −0.11 (− 2.99) −0.16 (− 2.702) −1.80 (− 4.53) 2.032 (5.35) −6.15 (− 1.60) −2.63 (− 6.72) – – −2.02 (− 2.63) – –

0.69 (19.01) 0.022 (2.85) 0.19 (5.24) − 0.11 (− 3.092) − 0.21 (− 3.39) − 1.85 (− 4.76) 2.023 (5.37) − 6.38 (− 1.67) − 2.61 (− 6.73) – – − 1.89 (− 2.55) – –

0.696 (18.99) 0.017 (2.26) 0.198 (5.38) − 0.11 (− 3.12) − 0.15 (− 2.57) − 1.76 (− 4.36) 2.025 (5.28) − 5.97 (− 1.54) − 2.61 (− 6.61) – – – – – –

0.68 (18.73) 0.021 (2.73) 0.195 (5.37) − 0.12 (− 3.19) − 0.202 (− 3.30) − 1.83 (− 4.64) 2.01 (5.29) − 6.37 (− 1.65) − 2.58 (− 6.61) – – – – – –

0.70 (19.05) 0.017 (2.24) 0.19 (5.29) − 0.11 (− 3.04) − 0.15 (− 2.53) − 1.82 (− 4.53) 2.043 (5.33) − 6.17 (− 1.58) − 2.63 (− 6.69) – – – – − 0.69 (− 0.99)

0.69 (18.86) 0.021 (2.47) 0.19 (5.24) − 0.11 (− 3.09) − 0.20 (− 3.22) − 1.89 (− 4.84) 2.036 (5.36) − 6.53 (− 1.68) − 2.62 (− 6.71) – – – – − 0.81 (− 1.18)

0.69 (18.79) 0.019 (2.58) 0.19 (5.31) − 0.11 (−3.09) − 0.19 (−3.22) − 2.051 (−5.048) 2.19 (5.52) − 5.86 (−1.52) − 2.77 (−6.81) – – – – – –

0.69 (19.01) 0.017 (2.180) 0.196 (5.33) − 0.11 (−3.06) − 0.16 (−2.61) − 1.96 (−4.71) 2.19 (5.48) − 5.62 (−1.45) − 2.78 (−6.78) – – – – – –

0.69 (18.94) 0.016 (2.11) 0.19 (5.31) − 0.11 (−3.12) − 0.16 (−2.71) − 1.93 (−4.69) 2.17 (5.44) − 5.65 (−1.46) − 2.76 (−6.73) – – – – – –

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Table A2 (continued ) Monetary policy reversal Exchange rate policy reversal Trade reform Structural adjustment reform Enhanced structural adjustment Adjusted R-squared F(11,342)

– – – – – – 0.59 (0.98) – – 0.66 62.31

– – – – – – – – 0.51 (0.79) 0.66 62.22

– – – – – – 0.83 (1.42) – – 0.66 64.15

– – – – 1.51 (2.58) – – – – 0.67 65.43

− 0.701 (−1.204) – – – – 0.65 (1.11) – – 0.66 62.65

− 0.93 (−1.603) – – 1.65 (2.73) – – – – 0.66 64.35

– – – – – – 0.65 (1.096) – – 0.66 62.52

– – – – 1.55 (2.60) – – – – 0.66 64.03

– – 0.0052 (1.18) 1.42 (2.42) – – – – 0.66 64.02

– – 0.005 (1.18) – – 0.51 (0.88) – – 0.66 62.63

– – 0.005 (1.18) – – – – 0.46 (0.74) 0.66 62.57

0.67 (19.45) 0.031 (4.57) 0.31 (7.21) − 0.35 (−8.87) 0.24 (8.98) − 0.15 (−5.50) − 13.35 (−4.51) 0.18 (4.76) − 0.18 (−5.05) – – – – – – – – – – – – 0.003 (0.902) – – 0.64 (1.51) – – 0.76 104.9

0.67 (19.63) 0.032 (4.66) 0.29 (7.05) − 0.35 (−8.88) 0.23 (8.84) − 0.16 (−5.66) − 13.33 (−4.49) 0.17 (4.63) − 0.18 (−5.03) – – – – – – – – – – – – 0.0031 (0.93) 0.22 (0.53) – – – – 0.76 104.11

Table A3 Gross domestic investment ratio equation with adjustment dummies and policy reversals Gross domestic investment_1 Openness

0.67 (19.6) 0.031 (4.65) Government 0.32 consumption (7.39) Government − 0.35 consumption_1 (−9.06) Gross domestic 0.24 savings (8.95) Gross domestic − 0.15 savings_1 (−5.43) Change in log of − 14.3 terms of trade (−4.79) Financial depth 0.17 (4.71) Financial depth_1 − 0.18 (−4.98) Log of real – exchange rate – Debt service ratio – – Savings policy – reversal – Trade policy – reversal – Fiscal policy − 0.97 reversal (−1.82) Monetary policy – reversal – Exchange rate – policy reversal – Trade reform – – Structural 0.85 adjustment (1.97) Enhanced – structural adjustment – Adjusted R-squared 0.77 F(11,342) 105.8

0.67 (19.5) 0.031 (4.57) 0.31 (7.31) −0.35 (− 8.97) 0.23 (8.85) −0.15 (− 5.49) −14.2 (− 4.75) 0.17 (4.60) −0.18 (− 4.96) – – – – – – – – −0.82 (− 1.57) – – – – – – – – 0.75 (1.64) 0.77 105.4

0.65 (19.2) 0.035 (5.27) 0.27 (6.09) − 0.29 (− 6.96) 0.22 (8.21) − 0.12 (− 4.09) − 14.3 (− 4.92) 0.13 (3.45) − 0.12 (− 3.29) 0.18 (1.005) − 0.14 (− 3.85) – – – – – – − 0.88 (− 2.00) – – – – 0.85 (1.93) – – 0.77 94.14

0.65 (19.1) 0.035 (5.17) 0.27 (6.05) − 0.28 (− 6.86) 0.22 (8.11) − 0.12 (− 4.08) − 14.3 (− 4.91) 0.13 (3.34) − 0.12 (− 3.27) 0.18 (0.97) − 0.14 (− 3.91) – – – – – – − 0.82 (− 1.90) – – – – – – 0.87 (1.84) 0.77 94.02

0.65 (19.4) 0.037 (5.48) 0.26 (5.82) − 0.28 (− 6.86) 0.21 (7.91) − 0.12 (− 4.18) − 14.3 (− 4.92) 0.13 (3.31) − 0.12 (− 3.22) 0.20 (1.11) − 0.14 (− 4.02) – – – – – – − 0.86 (− 1.96) – – 0.71 (1.57) – – – – 0.77 93.69

0.66 (19.51) 0.031 (4.59) 0.32 (7.46) − 0.36 (− 9.12) 0.24 (8.88) − 0.14 (− 5.23) − 14.5 (− 4.84) 0.17 (4.61) − 0.17 (− 4.82) – – – – − 0.90 (− 1.93) – – – – – – – – – – 0.93 (2.09) – – 0.77 106.06

0.66 (19.39) 0.03 (4.51) 0.32 (7.37) − 0.35 (− 9.02) 0.23 (8.78) − 0.15 (− 5.32) − 14.3 (− 4.78) 0.17 (4.50) − 0.17 (− 4.82) – – – – − 0.76 (− 1.68) – – – – – – – – – – – – 0.81 (1.75) 0.77 105.54

0.67 (20.08) 0.037 (5.49) 0.26 (6.09) − 0.30 (− 7.30) 0.20 (7.62) − 0.12 (− 4.08) − 14.0 (− 4.84) 0.13 (3.36) − 0.13 (− 3.47) – – – – – – − 1.27 (− 2.23) – – – – – – 0.67 (1.61) – – – – 0.77 101.96

0.66 (19.89) 0.035 (5.31) 0.28 (6.41) − 0.31 (−7.45) 0.21 (7.96) − 0.11 (−3.91) − 14.1 (−4.89) 0.132 (3.53) − 0.13 (−3.53) – – – – – – − 1.52 (−2.63) – – – – – – – – 1.01 (2.41) – – 0.78 103.18

0.66 (19.7) 0.035 (5.19) 0.27 (6.30) − 0.30 (−7.28) 0.21 (7.83) − 0.11 (−3.96) − 14.0 (−4.85) 0.13 (3.39) − 0.13 (−3.50) – – – – – – − 1.30 (−2.29) – – – – – – – – – – 0.92 (2.07) 0.78 102.6

0.67 (19.35) 0.031 (4.49) 0.31 (7.18) − 0.34 (−8.82) 0.24 (8.94) − 0.15 (−5.53) − 13.34 (−4.51) 0.17 (4.69) − 0.18 (−5.04) – – – – – – – – – – – – – – – – – – 0.63 (1.39) 0.76 104.76

104

Table A4 Growth of gross domestic product equation with adjustment dummies and policy reversals Growth of GDP_1 Private investment ratio

Inflation Government consumption Gross domestic savings Gross domestic savings_1 Financial depth Financial depth_1 Savings policy reversal Trade policy reversal Fiscal policy reversal Monetary policy reversal Exchange rate policy reversal Trade reform Structural adjustment Enhanced structural adjustment Adjusted R-squared F(11,342)

0.101 (2.44) 0.072 (1.76) 0.021 (2.06) − 0.021 (− 1.52) − 0.07 (− 1.42) 0.18 (4.57) − 0.16 (− 4.39) − 0.083 (− 1.72) 0.062 (1.50) – – – – − 3.65 (− 4.65) – – – – – – – – 0.41 (0.59) 0.15 6.71

0.103 (2.48) 0.07 (1.70) 0.023 (2.24) − 0.022 (− 1.65) − 0.072 (− 1.49) 0.17 (4.53) − 0.16 (− 4.42) − 0.081 (− 1.68) 0.061 (1.48) – – – – − 3.76 (− 4.75) – – – – 0.73 (1.14) – – – – 0.15 6.81

0.088 (2.10) 0.062 (1.48) 0.025 (2.45) − 0.027 (− 1.94) − 0.081 (1.66) 0.18 (4.51) − 0.16 (− 4.29) − 0.10 (− 2.07) 0.073 (1.75) – – − 3.30 (− 3.75) – – – – – – 0.303 (0.48) – – – – 0.13 5.93

0.086 2.064 0.061 (1.46) 0.024 (2.38) − 0.027 (−1.95) − 0.074 (−1.50) 0.18 (4.58) − 0.16 (−4.21) − 0.097 (−1.99) 0.072 (1.73) – – − 3.44 (−3.81) – – – – – – – – 0.53 (0.79) – – 0.13 5.97

0.088 (2.094) 0.063 (1.51) 0.024 (2.38) −0.026 (− 1.89) −0.081 (− 1.62) 0.18 (4.51) −0.16 (− 4.28) −0.10 (− 2.08) 0.074 (1.76) – – −3.29 (− 3.73) – – – – – – – – – – 0.13 (0.19) 0.13 5.91

0.093 (2.23) 0.065 (1.56) 0.019 (1.86) − 0.026 (− 1.89) − 0.064 (− 1.29) 0.18 (4.68) − 0.16 (− 4.19) − 0.08 (− 1.64) 0.065 (1.54) − 2.79 (− 4.02) – – – – – – – – – – 0.81 (1.20) – – 0.14 6.14

0.094 (2.24) 0.066 (1.59) 0.019 (1.85) − 0.024 (− 1.78) − 0.069 (− 1.39) 0.18 (4.59) − 0.16 (− 4.25) − 0.086 (− 1.77) 0.067 (1.59) − 2.63 (− 3.90) – – – – – – – – – – – – 0.51 (0.73) 0.14 6.04

0.095 (2.29) 0.063 (1.52) 0.021 (2.071) − 0.027 (− 1.95) − 0.071 (− 1.47) 0.18 (4.54) − 0.16 (− 4.28) − 0.083 (− 1.71) 0.065 (1.55) − 2.82 (− 4.09) – – – – – – – – 0.94 (1.42) – – – – 0.14 6.20

0.081 (1.91) 0.074 (1.72) 0.021 (2.052) − 0.026 (−1.82) − 0.077 (−1.55) 0.18 (4.60) − 0.16 (−4.30) − 0.102 (−2.05) 0.083 (1.93) – – – – – 0.15 (0.21) – – 0.083 (0.12) – – – – 0.10 4.47

0.082 (1.92) 0.075 (1.75) 0.021 (2.056) −0.026 (− 1.82) −0.079 (− 1.56) 0.18 (4.52) −0.16 (− 4.30) −0.103 (− 2.06) 0.082 (1.92) – – – – – – 0.19 (0.28) – – – – −0.103 (− 0.15) – – 0.10 4.47

0.078 (1.82) 0.074 (1.73) 0.022 (2.12) −0.026 (− 1.83) −0.079 (− 1.60) 0.18 (4.61) −0.16 (− 4.32) −0.11 (− 2.14) 0.087 (2.021) – – – – – – – – −0.003 (− 0.62) 0.13 (0.202) – – – – 0.1 4.5

0.078 (1.83) 0.074 (1.75) 0.022 (2.11) − 0.025 (− 1.81) − 0.081 (− 1.60) 0.18 (4.55) − 0.17 (− 4.32) − 0.11 (− 2.15) 0.087 (2.025) – – – – – – – – − 0.003 (− 0.62) – − 0.047 (− 0.07) – – 0.1 4.5

0.079 (1.83) 0.075 (1.75) 0.022 (2.11) − 0.025 (− 1.82) − 0.082 (− 1.61) 0.18 (4.58) − 0.17 (− 4.33) − 0.11 (− 2.16) 0.087 (2.03) – – – – – – – – − 0.031 (− 0.62) – – – – − 0.087 (− 0.12) 0.1 4.5

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Openness

0.10 (2.43) 0.071 (1.73) 0.021 (2.064) −0.022 (− 1.61) −0.064 (− 1.30) 0.18 (4.66) −0.16 (− 4.33) −0.077 (− 1.59) 0.06 (1.46) – – – – −3.82 (− 4.76) – – – – – – 0.76 (1.16) – – 0.15 6.82

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