Asia-Pacific Journal of Regional Science

, Volume 2, Issue 1, pp 65–77 | Cite as

Exchange rate uncertainty and private investment in BRICS economies

  • Martin Ruzima
  • Micheal Kofi Boachie


Macroeconomic uncertainty is a major challenge facing policymakers. Exchange rate is usually associated with high level of volatility in developing economies. This has potential effect on other economic variables such as investment. This paper empirically examines the impact of exchange rate uncertainty on private investment in the BRICS bloc. Using cross-country time series data from World Development Indicators, for 1997–2015, we built an ARCH-based measure of exchange rate volatility to proxy uncertainty. The results show that uncertainty resulting from exchange rate volatility has a negative effect on private investment in both random and fixed effects as well as GMM estimations. Therefore, policy may focus on stabilizing domestic currencies in BRICS countries.


Private investment Exchange rate Uncertainty BRICS 

JEL Classification

E22 E44 F31 

1 Introduction

In many developing countries, high degree of macroeconomic uncertainty is a major challenge facing policymakers. Variables such as inflation, growth, and exchange rates are usually associated with high levels of volatility in developing economies than in the developed world (IMF 2002; Serven 2003). The impact of these macroeconomic uncertainties on investment behavior continues to attract attention (see Huizinga 1993; Serven 2002, 2003; Byrne and Davis 2005). This interest is, perhaps, due to the sensitivity of domestic economic variables to changes in both internal and external markets (Chowdhury and Wheeler 2015).

While there are many sources of uncertainty, the one arising from the volatility of exchange rate is crucial, due to its potential to influence many other financial and economic variables like interest rate, trade, output, and stock or equity prices (Cote 1994; McKinnon and Ohno 1997; Byrne and Davis 2005). These uncertainties may put cost of capital and future profitability in an unpredictable position, which can influence investment decisions though the direction of the effect of the uncertainty is ambiguous (Caballero 1991; Abel and Eberly 1994; Serven 2003; Chowdhury and Wheeler 2015). Thus, as countries adopt strategies to boost output, concerns are usually raised about how macroeconomic uncertainties resulting from volatility in variables such as exchange rates affect investment, especially private investment.

In the last few decades, the determinants of investment, particularly private component, have received attention due to its significant contribution to output (Khan and Rhenihart 1990). It is argued that private investment is associated with higher efficiency, and its ability to create jobs is large. In view of this, many countries and development partners support and promote policies focusing on private investment to propel economic growth for job creation. Many studies analyzing the factors affecting private investment have devoted their analyses to the effects of exchange rate volatility on the private sector (Goldberg 1993; Serven 2003; Bhandari and Upadhyaya 2010; Chowdhury and Wheeler 2015). Exchange rate volatility results in erratic swings in the profitability of investment in the traded and non-traded goods sectors of the economy, and may consequently make the cost of capital unpredictable (Serven 1999; Chowdhury and Wheeler 2015).

Many studies have examined the effect of exchange rate uncertainty on private investment on various economies and/or blocs. However, none of these studies has focused on the BRICS1 bloc which is emerging as a powerful economic force. In 2010, about 25% of global output emanated from the BRICS bloc (GoI 2012). By 2050, the contribution to global output from the bloc is expected to surpass that of current world economic powers like G7 countries (Wilson and Purushothaman 2003), and they are working assiduously towards this target. Trade (merchandise and invisible) with the rest of the world has been growing at a faster rate. The high economic performance of these economies has been attributed to the high level of investment, especially in the private sector (GoI 2012). However, currency uncertainty (volatility) in the BRICS has been listed as one of the major challenges facing these economies (GoI 2012), as volatility influences investment decisions. Therefore, the significance of an investigation into the impact of exchange rate uncertainty on private investment cannot be overstated. Thus, the present study aims to explore the effect of exchange rate uncertainty on private investment in BRICS economies.

Having introduced the theme, the rest of the paper is structured as follows: In Sect. 2, we briefly review related literature on the link between uncertainty and investment. The first part of the review relates to theory, while the second part focuses on empirical studies on the effect of exchange rate uncertainty on private investment. Section 3 explains our methodological techniques, whereas Sect. 4 presents and discusses the results. We conclude the study in Sect. 5.

2 Review of related literature

2.1 Theoretical review

The relationship between uncertainty and investment has been analyzed from several dimensions: risk-aversion, risk-neutral, adjustment cost, net present value of investment project, and irreversibility (Hartman 1972; Pindyck 1982, 1991; Abel 1983; Bernanke 1983; Dixit and Pindyck 1994). Theoretical assumptions and empirical findings on the effect of uncertainty on investment are still a matter of contention in financial economics literature. Thus, a model’s assumptions will determine the direction of the effect of uncertainty on investment (Chowdhury and Wheeler 2015). For instance, uncertainty increases investment when the production function exhibits constant returns to scale, or when firms operate under perfect competition, and zero adjustment cost (Abel 1983). When adjustment cost is zero, firms can reverse their investment decisions and uncertainty may increase investment (Hartman 1972; Abel 1983). Conversely, if one assumes that investment decisions are irreversible, such irreversibility of investments may induce firms to postpone their capital expenditures for the current period, due to the enhanced value of the firm or even higher adjustment cost (Pindyck 1991; Dixit and Pindyck 1994). Greenwald et al. (1984), Craine (1989), and Serven (1998) have argued that risk aversion, credit rationing, imperfect competition, and/or decreasing returns to scale explain the negative link between uncertainty and investment.

Some of the studies investigating the effect of exchange rate uncertainty on private investment do so through the adjustment cost theory, where firms operate under imperfect uncertain markets. The basic assumption is that acquisition of new capital is associated with cost. Thus, firms incur cost in the installation of new equipment or training employees on how to use such equipment. These costs may be influenced by exchange rates (Campa and Goldberg 1999; Nucci and Pozzolo 2001; Harchaoui et al. 2005). The channels through which exchange rate affects private investment, or investments in general, are outlined elsewhere (Diallo 2015; Serven 2003; Darby et al. 1999).

2.2 Previous empirical studies

Empirical literature on the effect of uncertainties such as those emanating from exchange rate volatility is vast, and the literature continues to grow. For instance, Darby et al. (1999) found a mixed effect of exchange rate uncertainty on investment. Specifically, the effect of uncertainty on investment was significantly negative for Germany and France unlike Italy and the UK where the effect was weak. An earlier study on developing and developed countries by Pindyck and Solimano (1993) found that real exchange rate uncertainty affects investment negatively. Chou (2000) also examined the impact of exchange rate volatility on China’s exports using quarterly data from 1981 to 1996. After using autoregressive conditional heteroskedasticity model (ARCH) to obtain volatility, a co-integration analysis was conducted. The analysis showed that exchange rate volatility impacted negatively on exports of manufactured goods and total exports. This suggests that exchange rate uncertainty reduced private investment in China during the study period.

The findings reported by Serven (2003) are not different from that of Pindyck and Solimano (1993). Serven (2003) also used data on 61 developing countries for 1970–1995 to investigate the effect of real exchange rate uncertainty on private investment while using GARCH to obtain uncertainty. Serven found, from Generalized Methods of Moments (GMM) estimations, that real exchange rate uncertainty has a negative and statistically significant effect on private investment in developing countries. Besides, the results showed the existence of threshold effect, suggesting that the effect of exchange rate uncertainty varies. Countries with weak financial systems and open economies were significantly affected by exchange rate uncertainty. Also, Atella et al. (2003) examined the effect of exchange rate uncertainty on firm’s innovation process in Italy. Their results showed that exchange rate uncertainty (measured by volatility) decreases investment in innovation process by firms in Italy. Similar to the cross-country analysis by Darby et al. (1999), Hallett et al. (2004) found that exchange rate uncertainty impacts negatively on some industries while enhancing investment in other industries in 9 OECD countries.

Moreover, Clausen (2008) investigated the threshold level effect between exchange rate uncertainty and aggregate investment for 6 Latin American countries. The results showed that higher (real) exchange rate uncertainty has negative and significant effect on private investment in these countries. The findings from Bloom et al. (2007) also suggest that higher uncertainty reduces the responsiveness of investment to a firm-level demand shock under assumptions of partial irreversibility of investment. Again, Diallo (2015) suggests that the effect of exchange rate uncertainty on investment is negative and nonlinear. Further, Demir (2009) found that an increase in exchange rate uncertainty reduces new fixed investment of industries in Argentina, Mexico, and Turkey when they used unbalanced panel data. Thus, firms reduce their investment when there is increased volatility in the exchange rate.

For South-East Asian economies, Bhandari and Upadhyaya (2010) analyzed the effect of real exchange rate uncertainty on the private investment. Their results indicated that exchange rate uncertainty enhances investment. Recent empirical panel studies on the impacts of exchange rate volatility on investment for 15 sub-Saharan African countries by Soleymani and Akbari (2011) and for East and North African countries by Safdari and Soleymani (2011) found that exchange rate uncertainty is detrimental to domestic investment. Country-specific studies such as those conducted on Iran by Dahmarde and Bashiri (2012) and Zardashty (2014) found that real exchange rate uncertainty resulting from volatility does not promote private investment. Similar results have been reported earlier by Byrne and Davis (2005) for G7 countries and Bekoe and Adom (2013) for Ghana. Byrne and Davis (2005) examined the effect of exchange rate uncertainty on investment in G7 countries using GARCH and Pooled Mean Group Panel Estimation techniques, and found that exchange rate uncertainty impacts negatively on investment.

Héricourt and Poncet (2013) also studied how firm-level export performance is affected by real exchange rate volatility and investigated whether this effect depends on existing financial constraints. The authors used export data on more than 100,000 Chinese exporters over the 2000–2006 period. Their analysis revealed that the decision to export was negatively affected by exchange rate volatility; the exported value decrease for destinations that show higher volatility. This suggests that if firms are not able to sell domestically, accumulation of large inventory may reduce their future investment. In India, Cheung and Sengupta (2013) studied the impact of real effective exchange rate volatility on the share of exports-to-sales ratio for a sample of a few thousand Indian non-financial sector firms using data from 2000 to 2010. The authors found a negative effect of exchange rate uncertainty on Indian non-financial firms.

Chowdhury and Wheeler (2015) examined the effects of output and exchange rate volatility on fixed private investment in selected G7 countries. The authors used vector autoregressive models containing variables like price level, real output, volatility of real output, real exchange rate, and volatility of real exchange rate. The results showed that volatility shocks, measured by output volatility and exchange rate volatility, have no significant impact on private investment for any of the countries considered. A more recent study on Switzerland by Binding and Dibiasi (2017) used both micro and macro level data to examine the impact of exchange rate uncertainty on firms investment decisions. On the one hand, they found that exchange rate uncertainty negatively affects firms’ investment in machinery and equipment. On the other hand, firms increased their research and development expenditures due to uncertainty.

From the foregoing review of the empirical literature, exchange rate volatility has mixed effects, though many studies report negative link between exchange rate uncertainty and private investment. While there are many studies on the theme, none has considered how the fluctuations in exchange rate affect private sector capital formation in BRICS economies. Accordingly, there is a need to explore how uncertainty regarding exchange rate affect private sector capital formation in BRICS countries.

3 Methodology

3.1 Data and variables

We abstracted data from the World Bank’s (2016) World Development Indicators (WDI). The data span between 1997 and 2015 inclusive. The variables under study include nominal exchange rate uncertainty, private investment, real interest rate, domestic credit to private sector, general government spending, and a dummy variable taking values of 1 if a country is on fixed exchange rate and 0 otherwise. The inclusion of this dummy was particularly necessary since China was on fixed exchange rate prior to 2005.

3.2 Private investment model

In order to explore the effect of nominal exchange rate uncertainty on private investment, a general model with private investment as a dependent variable is set up and a conditioning set of independent variables including exchange rate uncertainty. Following Sakyi et al. (2016) and other literature on the theme, we present private investment model as:
$$ {\text{PI}}_{it} = \beta_{0} + \beta_{1} {\text{PI}}_{it - 1} + \beta_{2} {\text{ERVOL}}_{it} + \beta_{3} {\text{DCP}}_{it} + \beta_{4} {\text{GS}}_{it} + \beta_{5} {\text{RIR}}_{it} + \beta_{6} {\text{IGS}}_{it} + \beta_{7} D_{it} + \varepsilon_{it} $$
where PI it is private investment measured by gross fixed capital formation by the private (percentage of GDP) for country i at time t. ERVOL is nominal exchange rate uncertainty calculated with ARCH model; theoretically its sign is unknown. Further, we include the import of goods and services (IGS) and domestic credit to private sector (DCP). DCP captures the flow of funds to the private sector. Similarly, general government spending (GS) is included in the model to measure the effect of fiscal policy on private investment; its sign is unknown a priori since government’s fiscal policy may have different impact on the private sector. IGS, DCP, and GS are measured as percentage of GDP.

Cost of capital is an important factor identified to influence investment decisions, as postulated in neoclassical economics. Therefore, we include real interest rate (RIR), and it is expected to have a negative effect on private investment. The dummy variable, D it , accounts for the effect of fixed exchange rate regime. For instance, China practised fixed exchange rate prior to 2005, and this could affect the direction of exchange rate movements. β 0 is intercept; β 1β 2β 3β 4β 5β 6, and β 7 are the slope coefficients whereas ɛ it it is an error term.

3.3 Empirical estimation strategy

The Autoregressive Conditional Heteroskedasticity (ARCH) model was chosen to obtain exchange rate volatility because of its popularity. This ARCH based exchange rate volatility was then used as a proxy for uncertainty. The ARCH model has two equations: mean and variance. The mean equation models the behavior of the average of the series, while the variance equation describes the behavior of the variance in the error terms. Thus, we use the ARCH (1) technique to obtain the conditional variance of nominal exchange rate as measure of volatility, which is then used as uncertainty about the future in our analysis. The ARCH equations are presented below:
$$ y_{it} = \beta_{i} + e_{it} $$
Equation (2) models the mean of the series, and it consists of intercept and error term. The equation implies that time series data vary randomly around their mean. Similarly, the variance equation is given as:
$$ z_{it} = \alpha_{0} + \alpha_{1} e_{it - 1}^{2} $$

Equation (3) shows how the error variance behaves. After obtaining the proxy for uncertainty, we proceeded to estimate our private investment model, Eq. (1). The present study uses three estimators, namely fixed effects (FE), random effects (RE), and GMM estimators.

The FE is used to analyze data that changes over time. It removes individual effects by imposing time independent effect for each entity. By this, it allows only the net effects to be estimated, and it influences outcome variables. The FE estimator (also known as within estimator) uses two methods to eliminate unobservable time-invariant individual effect. These methods include differentiation and within transformation. The above scenario can be explained by Eq. (4) which contains unobservable effects and one independent variable with N observations and T time periods.
$$ y_{it} = X_{it} \beta + \alpha_{i} + u_{it} $$

Where y it is the dependent variable, X it represents the vector independent variables influencing the evolution of private investment, α i is an unobserved effect for each entity, and u i is an error term for each country. The FE model provides better options for eliminating unobservable effects (α i ) by demeaning the variables with the help of within transformation.

Further, granting the assumption that unobserved individual country effects are not correlated with any regressor, random effects estimator was also employed. We attempt to address endogeneity issues and other problems associated with the fixed and random effects estimators by using instrumental variables approach, based on the GMM due to Arellano and Bond (1991) and Arellano and Bover (1995). The GMM estimator also helps to address the problem of correlation between lagged PI and the error term. It was also used to check the robustness of the fixed and random effects estimates. We used Stata 11.2 for the model estimation.

4 Results and discussion

This section presents and discusses the results from the regressions. The descriptive statistics are presented first followed by the regression results.

4.1 Descriptive statistics

There were 89 observations for private investment, and the independent variables had 95 observations. The panel was unbalanced due to missing data. Therefore, 84 observations were used for estimation. The pooled statistics suggest that private investment in the BRICS bloc averaged 16.26% of GDP (SD = 4.82%) for the period 1997–2015. During the same period, the average real interest rate was 11.16% with a standard deviation of 17.65%. Table 1 presents the summary statistics of the variables in this study.
Table 1

Summary statistics of the variables









σ 2


























Std. Dev.














σ 2 denotes conditional variance. Source: Based on World Bank (2016)

There was less fluctuation in private investment as suggested by the low standard deviation. There was high volatility in exchange rate in the bloc during 1997–2015.

4.2 Regression results

To establish the relationship between exchange rate uncertainty and private investment in BRICS countries, Eq. (1) was estimated using panel data econometrics techniques. Other independent variables in the regression were real interest rate, domestic credit to private sector, imports, and dummy variable for fixed exchange regime.

The coefficients of the variables carry the expected signs and are statistically significant at conventional levels. This means that the selected variables are key determinants of private investment in the BRICS bloc. The results indicate that the variables used in our model explain 90% of the changes in private investment in BRICS countries. Table 2 depicts the summarised results from the estimated equations.
Table 2

Estimation results (Eq. 1)













PI (− 1)





















































R 2




Standard errors in square brackets

***, **, * denote significance at 1, 5, and 10% levels, respectively

As seen from Table 2, the coefficient of exchange rate uncertainty is statistically significant at 1% level and negative in all the models. The coefficient, which ranges between − 0.0027 and − 0.0031, means that 10% increase in exchange rate uncertainty will cause private investment to decrease by about 0.03%. Thus, rising levels of exchange rate uncertainty causes private investment to fall in BRICS countries. However, the effect is small. This finding is consistent with earlier results reported by, for example, Serven (2003), Demir (2009), Bhandari and Upadhyaya (2010), and Dahmarde and Bashiri (2012) where exchange rate uncertainty caused private investment to fall. This finding can be attributed to the fact that fluctuations in nominal exchange rate make firms adopt wait-and-see attitude. Most firms import capital goods so that fluctuations in exchange rate, in most cases, make the cost of these capital goods as well as export revenue volatile. This makes planning difficult for firms. Hence, firms reduce their expenditure on new machinery and equipment.

On the control variables, some were statistically significant in influencing private investment: 1 year lag of private investment, general government expenditure, domestic credit to private sector, and trade (import of goods and services). Specifically, domestic credit flows to the private sector impacts private investment positively. Its coefficient lies between 0.0469 and 0.0487, and statistically significant at conventional levels. This implies that 10% increase in domestic credit flows to the private sector increases private investment by about 0.487%. This result agrees with those found earlier (Serven 2003; Clausen 2008 [for Brazil, Colombia, Mexico, and Peru]) while deviating from Clausen (2008) for Ecuador and Sakyi et al. (2016) for Ghana. This positive significant effect of domestic credit to the private sector indicates that financial institutions play a crucial role in promoting private investment in BRICS countries.

Furthermore, government spending affects private investment level negatively. Its coefficient lies between − 0.2342 and − 0.3737, and statistically significant at conventional levels. This effect implies that 10% increase in government spending reduces private investment by about 3.737%. The findings corroborate with those found by Clausen (2008) for Brazil and Mexico while deviating from his findings for Chile, Colombia, and Ecuador. The reason for this negative relationship could be due to crowding-out effect of government spending. This may happen when the government borrows from the public through selling of securities such as bonds. As a consequence, interest rate rises so that more people invest in these securities than in other kinds of portfolio investment such as stocks. Also, higher interest rate for bonds leads to increased cost of borrowing for investors; and reduces funds for the private sector. Another possible reason is that government spending needs higher tax revenue. This could reduce consumption through lower disposable income.

Imports of goods and services have been found to be positive and statistically significant in determining private investment in the BRICS bloc; it is significant at 5% level. Its coefficient shows that, ceteris paribus, 10% increase in imports of goods and services increases private investment by 0.812 and 0.923% as shown respectively by FE and GMM estimates. This positive relationship indicates perhaps that BRICS countries’ imports promote private sector capital formation. A possible reason for this relationship is that these imports are of capital nature which contribute to the production process. Therefore, the imports lead to high productivity and higher income. Thus, one can argue that imports in the BRICS countries were investment goods. These findings deviate from Diallo (2015).

Real interest rate is found to be positive but its effect on private investment is small. In particular, a 10% increase in real interest rate will increase private investment by 0.447% for FE and 0.549% for GMM estimation. The positive coefficient of real interest rate contradicts the cost of capital theory, while agreeing with the McKinnon (1973) “complementarity” hypothesis. This positive relationship corroborates with the findings reported by Frimpong and Marbuah (2010), though disagrees with that reported by Serven (2003). The reason for this positive relationship between private investment and real interest rate could be that the lower interest reduces a cost of lending and makes funds available to many investors which raises expected future profits.

Finally, the dummy variable for fixed exchange rate was negative and statistically significant in determining private investment in BRICS countries. The coefficient ranges from − 4.1777 to − 4.3268 as shown, respectively, by FE and GMM estimates. Thus, fixed exchange rate leads to low productivity of private investment. The reason for this negative relationship is that fixed exchange rate does not promote export, and may encourage imports. Hence, the private sector may reduce their capital formation.

5 Conclusion

This paper investigated the effect of exchange rate uncertainty on private investment in BRICS countries using panel data econometric tools. Annual data for the period 1997–2015 were used. We employed ARCH model to measure nominal exchange rate volatility to proxy uncertainty; afterwards random and fixed effects as well as generalized method of moments estimators were used to estimate the private investment model. We find that exchange rate uncertainty had a negative effect on private investment in the BRICS bloc between 1997 and 2015. Therefore, policy should focus on stabilizing domestic currencies in BRICS economies. The results of the study should be interpreted with caution. The study did not take into account all the factors that affect private investment. Further, the sample used in this study is relatively small due to data paucity. These and other issues present scope for further research on the impact of exchange rate uncertainty on private investment in the BRICS bloc.


  1. 1.

    BRICS refers to emerging market economies, namely Brazil, Russia, India, China, and South Africa.



We would like to thank the anonymous referees for their insightful comments on earlier versions of this paper. We are also grateful for the valuable suggestions from the participants at the Statistical Methods in Finance Conference (December 19–22, 2016) held at Chennai Mathematical Institute. The usual caveat applies.


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Copyright information

© The Japan Section of the Regional Science Association International 2017

Authors and Affiliations

  1. 1.Department of EconomicsAnnamalai UniversityAnnamalai NagarIndia

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