Introduction

Chapter 5.

misalignment depresses trade flows in SSA countries. Some empirical implications arise out of our contri-bution in this chapter. First, maintaining an undervalued real exchange rate through monitoring exchange rates relative to trading partners may be important. However, persistent real exchange rate misalignment may provide incentives to the recurrence to non-traditional protectionist policies. Thus, strategies to avoid trade protectionist measures including multilateral cooperation related to the stabilization of exchange rates towards their equilibrium levels should be at the fore. Second, our findings show that the real ex-change rate volatility has a depressing effect on trade. Therefore, policies to avoid the problems caused by volatile exchange rates, such as putting in place financial instruments to hedge against the exchange rate risk is crucial, especially for SSA countries where these instruments are not well developed. Finally, implementing sound macroeconomic policies to provide a stable economic environment is important for trade to thrive, for instance, maintaining the real exchange rate undervaluation requires higher savings relative to investment or lower expenditure relative to income. This can be achieved through prudent fiscal policy as part of a wider macroeconomic policy package.

Chapter 3 examines the link between real exchange rate undervaluation and economic growth in SSA countries. Its key contribution lies in the fact that it exclusively focuses on SSA countries and our data set starts in 1995 to capture the impact of structural adjustment programs and the resultant economic liberalization that was experienced by most SSA Countries on the real exchange rate. Our analysis started with generating real exchange rate volatility and real exchange rate misalignment indicators. For the real exchange rate misalignment, we constructed both the misalignment based on purchasing power parity and misalignment based on the behavioral equilibrium exchange rate (BEER) model.

In the first step, we estimated BEER model using dynamic panel cointegration based estimators, particularly DOLS. The results show that RER is influenced by economic fundamentals. The estimated coefficients together with HP filter are based on to derive sustainable values of economic fundamentals by decomposing the RER into their permanent and cyclical components and compute the misalignment indicator, especially RER undervaluation indicator. The constructed RER undervaluation is thus used in baseline growth regressions, along with relevant control variables. The obtained results provide strong evi-dence that the RER undervaluation fosters economic growth in SSA countries. We also checked whether the impact of RER undervaluation on economic growth in SSA countries depends on the RER undervaluation measure used by also employing Balassa-Samuelson (BS) adjusted undervaluation measure and checked whether the effect is asymmetric (non-linear). We first generated the purchasing power parity adjusted real exchange rate, which was then regressed on real per capita GDP growth to test for BS hypothesis and the results indicate that the BS hypothesis holds for SSA countries. This finding is in line withGala (2008), Rodrik (2008),Glüzmann et al.(2012)andMacDonald and Vieira (2012)given that the we find a negative and statistically significant coefficient of per capita real GDP growth. After establishing the BS hypothesis, we proceeded to construct the RER undervaluation measure to assess whether real undervaluation of the exchange rate spurs economic growth in SSA countries. The result of BS adjusted RER undervaluation indicates that the coefficient of the BS adjusted RER undervaluation measure is positive and statistically significant, suggesting a positive effect of the real exchange rate undervaluation on economic growth. This implies that both the measure based on reduced form equilibrium exchange rate model and BS effect adjusted RER undervaluation measure significantly influence economic growth in SSA, implying that these measures are not competing but rather complementary.

Finally, checking for non-linear effects of RER undervaluation on growth by using the squared term of RER undervaluation shows that the coefficient of the squared term is positive and statistically significant, pointing to no evidence of asymmetric effects and thus non-linearity, a result that corroborates those obtained byRodrik (2008).

However, the results of a non-linear regression based panel threshold autoregressive (PTAR) model point to a significantly positive non-linear relationship between RER undervaluation and economic growth in SSA countries. These contrasting results support the view that there is no consensus in the empiri-cal literature on the asymmetric link between RER and economic growth given that whileRodrik (2008) finds only symmetric relationship between RER undervaluation and growth, other recent studies such as Aguirre and Calderon (2005), Béreau (2012) and Couharde and Sallenave (2013) find the existence of non-linearities in the exchange rate-growth nexus. Important policy implications emerge from the obtained empirical results. Results confirm the presence of BS effect for the selected SSA countries, suggesting that there are significant differences in prices between tradable and non-tradable sectors, pointing to the fact that the non-tradable sectors are vulnerable, a phenomenon that is linked to the unskilled labour in the non-tradable sector of the SSA countries. To mitigate these disparities in prices and wages, respec-tive governments should put in place policies that induce productivity in the non-tradable sectors of these countries, including putting emphasis on vocational education and training. Secondly, results indicate that RER undervaluation is essential for growth, pointing to the need to revisit the exchange rate as a policy instrument given that it favors growth. However, when currencies are highly undervalued, the impact on growth becomes minimal. For instance for SSA countries that have large foreign denominated liabilities such as external debts, extremely undervalued currencies impede growth, nonetheless policies that sustain the exchange rate at a competitive level determined by forces of demand and supply and limit RER volatility should be pursued as part of the broader macroeconomic stability package conducive to productivity and growth.

Chapter 4 focuses on modeling non-linear dynamics in the real exchange rate in Rwanda using regime switching models. The study is country specific and it is an area that has not been explored for the case of Rwanda. Its novelty lies in the use of model confidence set procedure to evaluate the predictive ability of competing models, a procedure that is quite new in forecast performance evaluation, particularly in the case of Rwanda, thus the conclusions of this study extend the existing stock of literature. Our empirical analysis began with the estimation of the linear model (Autoregressive Integrated Moving Average) as the benchmark model and proceeded with the estimation of the competing non-linear models. We performed both the in-sample and out-of-sample forecast evaluations of these models. The results of the ARIMA model show that the coefficient is positive and statistically significant and the AR, MA and sigma components are also positive and statistically significant, confirming that the model is well specified. The results of the TAR model show that the parameter estimates for the two regimes is 4.36, with the asymptotic confidence interval ranging between 4.34 and 4.36, pointing to the evidence of two regime specification. For the Markov Switching autoregressive model, the parameter estimates for the state dependent intercepts are 4.33 and 4.42 for state 1 and state 2, respectively. These results are consistent with the TAR estimates.

The results of expected duration indicate that the appreciation regime lasts for 25.4 quarters on average and the depreciation regime lasts for 13.69 quarters, suggesting that the appreciation regime dominates its counterpart (depreciation) in most data points within our sample. Regarding the forecasting ability of models, the results indicate that in terms of in-sample forecasting the TAR model outperforms the ARIMA, which is a linear model, while TAR and MS-AR models, non-linear models, emerge the best in the out-of-sample forecasting. The empirical implication arising out of these results is that Rwanda’s real exchange rate dynamics can be best characterized as non-linear and, thus, non-linear models, particularly TAR and MS-AR are the appropriate models to predict real exchange rate patterns.

113