Port Econ J DOI 10.1007/s10258-017-0136-y O R I G I N A L A RT I C L E

Exchange rate volatility and capital inflows: role of financial development Zainab Jehan 1 & Azooba Hamid 1

Received: 18 March 2016 / Accepted: 30 August 2017 # ISEG 2017

Abstract There is vast literature examining the impact of exchange rate volatility on various macroeconomic aggregates such as economic growth, trade flows, domestic investment, and more recently capital flows. However, these studies have ignored the role of financial development while examining the impact of exchange rate volatility on capital flows. This study aims to analyze the impact of exchange rate volatility on capital inflows towards developing countries by incorporating the role of financial development over the time period 1980–2013. In this regard, the behavior of two types of capital flows is examined: physical capital inflows measured as foreign direct investment, and financial inflows quantified through remittance inflows. The empirical investigation comprises the direct as well as indirect effect of exchange rate volatility on capital inflows. The study employs dynamic system GMM estimation technique to empirically estimate the effect of exchange rate volatility on capital inflows. The empirical results of the study identify that exchange rate volatility dampens both physical and financial inflows towards developing countries. The indirect impact of exchange rate volatility through financial development, however, turns out positive and statistically significant. This finding reflects that financial development helps in reducing the harmful impact of exchange rate volatility on capital inflows. Hence, the study concludes that a developed financial system is an important channel through which developing countries may improve capital inflows in the long run. Keywords Capital inflows . Foreign direct investment . Remittances . Financial development . Exchange rate volatility JEL classification F310 . F41 . F24 Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10258-0170136-y) contains supplementary material, which is available to authorized users.

* Zainab Jehan [email protected]

1

Department of Economics, Fatima Jinnah Women University, Rawalpindi, Pakistan

A. Hamid, Z. Jehan

1 Introduction The failure of the Bretton Woods System (BWS) in 1973 has changed the world economic scene in various aspects in general, whereas exchange rate determination and international capital movement are affected, in particular. The consequent adoption of flexible exchange rate arrangements not only introduces troublesome episodes of exchange rate volatility which hampers the movement of capital flows across countries but it also challenges the development associated with the inflows of the capital. This puts the developing world into a dilemma of how to interpret these changes in exchange rate with respect to capital inflows (Choi et al. 2013). Given its significance, both developed and developing countries have been challenged to maintain the reasonable predictability in the movement of either exchange rate or capital flows. Thus, since the adoption of flexible exchange rate system, the world economy has witnessed a considerable change in response of capital flows towards the change in exchange rate and vice versa (Choi et al. 2013). Being the important part of domestic investment and major source of finance, it appeared challenging for the developing countries, in particular, to not only maintain the existing level of capital inflows but also to adopt strategies that stimulate these inflows (Ghose 2004). The classical theories of capital flows, specifically FDI, relate the emergence of FDI to the return that an investment enjoys in a foreign market. These theories are based on the popular assumption of perfect market and risk neutrality in undertaking investment abroad. The origin of the relationship between FDI and exchange rates lies in Aliber’s hypothesis given by Aliber (1970). According to this hypothesis, countries with stronger currencies can influence FDI inflows as compared to the countries having weaker currencies. Later on, the theory of Relative Labor Cost proposed by Cushman (1985, 1988) explains that the destination country’s depreciation can attract FDI due to low production cost as compared to the foreign cost of production especially the labor cost. More recently, wealth position hypothesis by Froot and Stein (1991) explains that FDI, through the movements of exchange rate, can affect the relative wealth of both host and domestic countries. The theoretical explanation of the adverse impact of exchange rate volatility on capital inflows, on the other hand, is well explained by Lucas (1967). In addition, the irreversible nature of investment as explained by Nickell (1978) portrays a negative relationship between uncertainty and investment. Nonetheless, the impact of exchange rate and its volatility depends on the type of capital flows i.e. whether the capital flows are long term or short term. Froot and Stein (1991) explain that under asymmetric information, the impact of exchange rate on capital flows depends on the level of information intensity of capital flows. For instance, the FDI flows are more information intensive than portfolio investment; consequently, they are more sensitive to exchange rate fluctuations. The most recent development in this relationship is explained by “options to wait” approach proposed by Dixit and Pindyck (1994). This approach entails that in the presence of investment irreversibility under uncertainty, firms will only operate if the expected value of investment is above some threshold level. However, this threshold level changes with the change in the level of uncertainty the firm faces, the discount rate, and the drift term in the evolution of the expected rate of return on investment. In

Exchange rate volatility and capital inflows: role of financial...

addition, as exchange rate uncertainty makes returns to investment indeterminate, the value of an investment strategy plays an important role in determining the level of capital flows because each investment includes both certain and uncertain elements. Therefore, exchange rate uncertainty restrains capital inflows even if the investors do not portray risk-averse behavior (Dixit 1989). The theoretical background provides a baseline conclusion that the extent to which exchange rate affects capital inflows depends not only on the volatility of exchange rate but also on the irreversible nature of investment. These theoretical underpinnings provide an impetus to empirically test the impact of exchange rate and its volatility on capital inflows. The empirical work linking exchange rate volatility and capital inflows has largely focused on physical capital flows namely FDI. In this regard, the studies by Cushman (1985), and Goldberg and Kolstad (1995) are considered pioneering. These studies endeavor to identify a distinctive, favorable impact of exchange rate uncertainty on FDI inflows. Goldberg and Kolstad (1995), in particular, argue that firms buy an option to shift the investment in response to exchange rate uncertainty. Building upon the idea that option value is positively related to the risk attached to exchange rate, they conclude that uncertainty leads to higher FDI inflows. On the other hand, Campa (1993) states that devaluation of the currency hinders FDI because foreign investment decisions depend on the expectation of future profits. Goldberg and Kolstad (1995) state that depreciation of the currency does not have any significant impact on FDI, however, intensity of fluctuation in exchange rate positively affects FDI flows. The literature has also pointed out the disincentive that the investors face in times of volatile exchange rate (Dixit and Pindyck 1994). In addition, the investors prefer to wait as the option value of waiting increases with the increase in uncertainty; thus, avoid any loss from volatile exchange rate (Aizenman 1991). Further, exchange rate uncertainty discourages FDI flows as there is a chance to carry out the investment in future in the absence of exchange rate volatility (Furceri and Borelli 2008). Del Bo (2009) states that the risk of the insecurity of venture, the economic environment of the destination country, and the macroeconomic instability (broadly including exchange rate volatility) are all important factors affecting the level of FDI. Recent literature has identified various factors which affect capital inflows towards developing countries such as return to investment, market size, inflation (Ajayi 2006), openness (Ajayi 2006 and Asiedu 2002), political instability, infrastructure development, and macroeconomic instability (Asiedu 2002). Overall, the empirical research validates the adverse impact of volatility on capital inflows as explained by theories of exchange rate and investment (Sharifi-Renani and Mirfatah 2012; Ngowani 2012; Ellahi 2011, and Furceri and Borelli 2008). To overcome the barriers levied by exchange rate uncertainty on capital flows, countries (particularly the recipient of capital flows) are in the process of improving the mechanisms which can diminish the adverse impact of exchange rate volatility. In this regard, the role of financial sector’s development has gained considerable importance in recent years. Financial sector’s development helps reduce the risk factor attached to uncertainty, and offers better hedging facilities to investors; hence, provides a better investment environment which in return encourages capital inflows of all types (Aghion et al. 2009). Financial development is considered a prerequisite for the inflows of capital as it improves the absorption capacity, ensures efficient utilization of

A. Hamid, Z. Jehan

incoming resources, and adds to the process of technological diffusion associated with FDI. Moreover, a developed financial system facilitates investors by providing low cost information regarding investment opportunities, and also by monitoring the investment. So, it is a paramount in facilitating the diversification of risk and institutionalizing the savings (Otker et al. 2007). Despite the importance of financial development, the empirical literature is silent in estimating its role in determining the impact of exchange rate volatility on capital inflows. Since the developed financial sector provides better hedging facilities to solve the problem of asymmetric information, it encourages capital inflows (Aghion et al. 2009). Mishra et al. (2001) impart that the development of domestic capital market is associated with capital inflows as it helps diversify risks and raise the returns on capital, which in return increases investment activities, and boosts economic growth. To bridge this gap in the literature, we aim to investigate the direct and indirect impact of exchange rate volatility on capital inflows through financial development. In doing so, we cover the sample of 114 developing countries from 1980 to 2013. 1 Our empirical analysis is executed by considering two types of capital inflows; FDI net inflows towards developing countries extensively used in the existing empirical literature, and financial inflows measured by remittance inflows. 2 Remittances as financial inflows to recipient countries serve in various aspects. For instance, these are the steadiest financial flows in nature, acquire irrefutable importance at the time of vulnerable shocks in the recipient economy, aid the economy in vulnerable shocks, and exert a stabilizing impact on the recipient economy by being counter cyclical in nature (Ratha 2003). In addition, Ratha (2003) explains that investment climate in the recipient country affects the remittance inflows but not to the same degree as the other types of capital flows. Lucas and Stark (1985), and Bourdet and Falck (2006) document that remittances are influenced by macroeconomic uncertainty. However, there is not much empirical literature which estimates the uncertainty impact, particularly exchange rate uncertainty, on remittance inflows. Therefore, it is important to include a risk variable such as exchange rate risk to analyze the behavior of remittance inflows. This will provide an interesting insight to the existing literature. To incorporate the role of financial sector’s development, we use two alternate measures of financial development: domestic credit by banks as percentage of GDP, and private sector credit as percentage of GDP. The use of alternative proxies of financial development provides us with robustness check of our estimates. By doing this, we estimate the direct and indirect impact of exchange rate volatility on capital inflows while incorporating the role of financial development. To carry out the empirical analysis, we use dynamic system GMM estimation technique. Our empirical results report a direct negative impact of exchange rate volatility on both types of capital inflows. However, financial development helps reduce the adverse impact of exchange rate volatility on capital inflows across all empirical models. This finding proves the hypothesis that the financial development helps investors diversify 1

The selection of countries is based on the availability of data. List of countries is provided in the Appendix. Due to lack of data availability on Portfolio Investment, we use remittance inflows as a proxy of financial flows.

2

Exchange rate volatility and capital inflows: role of financial...

risk, and provides better hedging facilities, hence, reduces the intensity of the adverse impact imposed by exchange rate volatility.

2 Methodology and data Following Kogut and Chang (1996), Blonigen (1997), Darby et al. (1999), BénassyQuéré et al. (2001), Ellahi (2011), and Sharifi-Renani and Mirfatah (2012), the econometric model for FDI inflows is as follows: FDI it ¼ β0it þ β 1 FDI it−1 þ β 2 GDPit þ β3 TOit þ β4 Infd it þ β 5 Invit þ β6 RERit * RER þ β7 σRER it−1 þ β 8 FDit þ β 9 FDit σit−1 þ μit

ð2:1Þ

and, using the models of Higgins et al. (2004) and Ratha (2003), the following model of remittance inflows is estimated: Remit ¼ γ 0it þ γ 1 Remit−1 þ γ 2 GDPit þ γ 3 Intd it þ γ 4 RERit þ γ 5 σRER it−1 þ γ 6 FDit þ γ 7 FDit * σRER it−1 þ εit

ð2:2Þ

where the subscript `i′ refers to the ith country (i = 1 , … , 114) and `t′ to time period (t = 1980, … , 2013), while lagged dependent variable has been introduced to analyze the dynamics across countries and over time; FDI denotes the log of real net foreign direct investment inflows; GDP is the growth rate of per capital gross domestic product; TO is trade openness measured as sum of exports and imports as percentage of GDP; Infd is infrastructural development measured as 100 fixed telephone lines (per 1000 person); GFCF is gross fixed capital formation as percentage of GDP to measure domestic investment; RER is real exchange rate measured as official exchange rate adjusted for the inflation of the domestic and foreign country3; σRER refers to the volatility of real exchange rate. Following Aizenman and Marion (1999), and Turnovsky and Chattopadhyay (2003), we estimate a first order autoregressive model to generate the residuals of RER for each country for the period 1980–2013. Later, one-period ahead residuals are saved for each country. Finally, using these residuals, we compute the cumulative-volatility of the underlying series; FD represents financial development measured through two alternative proxies: domestic credit by banks (DCB) as percentage of GDP (it mainly includes non-equity security purchases, private sector credit to trade and loans provided to financial resources), and private sector credit (DCP) as percentage of GDP; Rem is the log of real remittance inflows; and FD∗σRER is an interaction term between each measure of financial development and the volatility of the real exchange rate. The interaction term will capture the indirect/conditional impact of RER volatility on capital inflows. Finally, by following Aghion et al. (2009), we also aim to test whether the impact of volatility decreases as the level of financial development increases.

3

In accordance with the literature, we use USA as the foreign country.

A. Hamid, Z. Jehan

The models given in Eqs. 2.1 and 2.2 are estimated by using two-step dynamic system GMM estimation technique. Since both models are dynamic and the number of countries considered is significantly greater than the number of time periods, therefore, GMM estimation technique is the best suitable to estimate these models. The GMM estimators will be consistent provided that the instruments are valid. Arellano and Bond (1991), and Arellano and Bover (1995) suggest two diagnostic tests: the Hansen test of instrument validity, and the Arellano and Bond AR (2) test for the second order autocorrelation.

3 Discussion of empirical results To analyze the impact of exchange rate volatility on capital inflows, we carry out our discussion in two steps. First, the direct impact of exchange rate, its volatility and financial development on capital inflows is discussed. Later, an interaction term of RER volatility with each measure of financial development is introduced to examine how financial development affects the impact of volatility on capital inflows. Columns 2 and 3 display the findings for the first measure of financial development i.e. DCB, while Columns 4 and 5 show the empirical results for the second measure of financial development i.e. DCP. The interaction terms capture the indirect/conditional impact of exchange rate volatility on capital inflows in the presence of financial development. 3.1 Exchange rate volatility and FDI: role of financial development Table 1 shows the empirical estimates for the impact of volatility of real exchange rate on FDI inflows by using both measures of financial development. The table reports both the direct and the indirect impact of exchange rate volatility. The columns presenting the conditional impact are embodied by an interaction term while keeping the list of other regressors the same as in the unconditional impact. The lagged FDI has been used to test the persistence of FDI inflows towards developing countries. The coefficient appears as positive and statistically significant in all models. The findings are in line with Kariuki (2015) who states that foreign investors prefer to invest in countries showing persistent pattern of foreign investment previously. Infrastructure is the main source of communication within and across countries. A market friendly environment created by the wide network of telecommunication encourages FDI (Sekkat and Veganzones-Varoudakis 2007). Our findings predict that infrastructure development increases FDI inflows significantly and are supported by Khadaroo and Seetanah (2010). According to their study, infrastructure is a precondition for foreign investors as it helps foreign investors to perform their operations successfully. Also, the infrastructural development is a key factor to attract FDI inflows as it reduces the cost of business and increases the potential productivity of investment in the country resultantly increasing FDI (Wheeler and Mody 1992). Domestic investment may act as a compliment or a substitute for FDI. McMillan (1999) states that domestic investors have more information about the investment

Exchange rate volatility and capital inflows: role of financial... Table 1 GMM estimates of FDI and exchange rate volatility: role of financial development

Regressors

FD measured as DCB

FD measured as DCP

Direct impact

Direct impact

Indirect impact

Indirect impact

Panel A: Estimation results: dependent variable FD FDIit − 1 GDPit TOit Infdit Invit RERit σRER it−1 DCBit DCBit * σRER it−1

0.297**

0.323***

0.293*

0.326***

(0.151)

(0.097)

(0.151)

(0.101)

0.015

−0.013

−0.015

−0.013

(0.017)

(0.011)

(0.017)

(0.018)

0.010

0.028

0.013

0.031

(0.019)

(0.018)

(0.018)

(0.023)

0.048***

0.041

0.048***

0.039

(0.017)

(0.041)

(0.016)

(0.032)

0.046**

0.064

−0.045**

0.077

(0.019)

(0.075)

(0.018)

(0.072)

0.093***

0.063***

0.097***

0.063***

(0.032)

(0.021)

(0.034)

(0.023)

−0.023***

−0.036***

−0.023***-

−0.035***

(0.064)

(0.083)

(0.006)

(0.006)

0.013**

0.018***

–

–

(0.053)

(0.058)

–

0.066*

–

–

0.013**

0.018***

(0.005)

(0.005)

(0.038) DCPit

–

–

DCPit * σRER it−1

–

–

–

0.063**

C

0.041**

0.099**

0.048**

0.010*

(0.018)

(0.048)

(0 .021)

(0.004)

Year dummies

Yes

Yes

Yes

Yes

(0.031)

Panel B: Diagnostic tests Hansen Test (P value) AR(2) (P value) No of observations

102.03

101.51

102.43

101.08

(0.644)

(0.922)

(0.633)

(0.935)

−1.500

−1.360

−1.480

−1.340

(0.134)

(0.174)

(0.140)

(0.181)

2487

2394

2488

2393

Segregation of columns shows estimation with different proxies of financial development. The FDI estimation with two proxies of financial development namely, domestic credit by banks as % of GDP and private sector credit as percentage of GDP respectively. Values in parenthesis refer to standard errors of the respective coefficients (in Panel A) and p-values of the respective diagnostic tests (in Panel B). Significance at 10%, 5% and 1% are indicated by *, ** and** * respectively. The sample includes 114 countries for the time period 1980–2013. The instruments include 1–4 lagged values of regressors such as FDI, Inv, TO, FD, GDP, RER and its volatility. Also, some exogenous variables are used as regressors, namely money supply as percentage of GDP AR(2) and Hansen tests are reported in the panel B of Table 1 with following null hypothesis. Hansen test: (Ho = all instruments are valid), Arellano-Bond test for AR(2): (Ho = No autocorrelation)

A. Hamid, Z. Jehan

climate of their own country as compared to foreign investors. When foreign investors find incomplete information about the investment climate, it can be seen that domestic investment outruns FDI. Ndikumana and Verick (2008) use “Signal Theory” to examine the influence of domestic investment on FDI and report a positive impact of domestic investment on FDI. Our empirical findings, however, are in contrast to this theoretical argument and confirm a negative impact of domestic investment on FDI. It shows that the relationship between domestic investment and FDI is not complementary but substitutive. Domestic investment dominates the production sector instead of infrastructure in developing countries. This finding is similar to Lautier and Moreaub (2012). Theoretically, FDI in developing countries increases with the depreciation of the respective country’s currency. Countries with the depreciated currencies provide incentives to foreign investors because it not only increases the relative wealth of foreigners but also the worth of their assets. Our estimation framework reveals a positive impact of real exchange rate on FDI inflows. The estimates are significant at conventional levels of significance in all the specifications presented in Table 1. These findings are in line with Udomkerdmongkol et al. (2009), Blonigen (1997), and Froot and Stein (1991). In addition, according to Ang (2008), larger FDI inflows are allied to the depreciation of currency and as a result the relative wealth of foreign investors increases. This, in turn, lowers the cost of capital and accelerates FDI. The “Risk Averse Argument” presented by Bénassy-Quéré et al. (2001) explains that exchange rate volatility negatively influences FDI inflows. They document that RER volatility adversely affects FDI flows as exchange rate introduces additional risk to the returns on investment, and foreign investors always require compensation on risk. Our results also confirm the Risk Averse Argument in all specifications, implying that risk associated with exchange rate affects the investment decisions of foreigners. Ruiz and Pozo (2008) explain that exchange rate volatility in the source country induces foreign investors to curtail the investment which confirms the negative affiliation between volatility and FDI. It is evident from the previous literature that changes in FDI are associated with the profitability of the location and risks associated with that location (Oliva and Rivera-Batiz 2002). Recently, Tchorek et al. (2017) also reported that uncertainty in the host country adversely affects capital flows. According to Alfaro et al. (2004), domestic financial conditions not only maximize the benefits of foreign investment but also help to attract multinational corporations. Similarly, Lee and Chang (2009) confirm the positive impact of domestic financial development on FDI inflows. Our results also illustrate, in all specifications and across alternative measures, that financial development attracts FDI. This confirms the findings of the existing empirical studies such as Ezeoha and Cattaneo (2012). These studies report that developed financial system increases liquidity and facilitates investors, thus lifts the level of FDI. Having discussed the direct impact of exchange rate volatility, we now turn to discuss the indirect impact. The indirect impact is captured through the interaction of exchange rate volatility with financial development. The objective of introducing this interaction term is to analyze whether financial development mitigates the adverse effect of exchange rate volatility on FDI or not. The results reveal a

Exchange rate volatility and capital inflows: role of financial...

positive and statistically significant coefficient of all the interaction terms introduced. This implies that the negative influence of volatility diminishes when the role of financial development is taken into consideration. This finding strengthens the theoretical explanations which report favorable impact of financial sector development not only on capital inflows but also in reducing the risk associated with exchange rate movements. While discussing the indirect impact, it is important to note that the magnitude of indirect impact of exchange rate volatility (interaction term) is positive whereas the direct impact of RER volatility is negative in both specifications. By combining the direct and indirect impact, our results propose that the stronger financial sector helps countries to mitigate the adverse impact of uncertainty imposed by exchange rate. Alternatively, at higher level of financial development, the adverse impact of RER volatility on capital flows will be less and vice versa (Aghion et al. 2009).4 Financial development is a process of improving the efficiency of services of financial intermediaries along with the expansion of quantity and quality of services offered by financial arbitrator (Abu-Bader and Abu-Qarn (2008)). Therefore, development of the financial sector improves allocation of resources, enhances the absorptive capacity and thus, promotes FDI inflows (Hermes and Lensink 2003). The estimates for GDP growth report an insignificant impact on FDI which is consistent with Asiedu (2002) but in contrast with ÇEviŞ and Camurdan (2007). In addition, Demirhan and Masca (2008) report both significant and insignificant impact of GDP growth on FDI inflows. These studies rationalize that countries having expanded markets and greater purchasing power are able to attract more FDI. Moreover, the coefficient of trade openness (TO) is insignificant in affecting FDI in the selected set of countries. Our results contradict with the previous literature which proposes that trade openness is the largest contributor and significantly attracts FDI to a country (Asiedu 2002). 3.2 Exchange rate volatility and remittances: role of financial development Remittances are an important source of foreign exchange, particularly, in developing countries. However, the fluctuations in exchange rate since the collapse of the Bretton Woods System have adversely affected the remittance inflows. To examine the impact of exchange rate volatility on remittance flows, we not only estimate the direct impact of exchange rate volatility on remittance inflows but also the indirect impact through financial development, namely domestic credit by banks as percentage of GDP and private sector credit as percentage of GDP. The empirical estimates are presented in Table 2. Table 2 reveals that the current remittances are positively affected by previous year’s remittances in all specifications. This finding is consistent with Kemegue et al. (2011) who empirically estimate the drivers of remittance inflows. Interest rate differential (domestic interest rate minus foreign interest rate) is used to

4

This explanation of the impact of RER volatility and the role of financial development is in accordance with Aghion et al. (2009).

A. Hamid, Z. Jehan Table 2 GMM estimates of remittances and exchange rate volatility: role of financial development Regressors

FD measured as DCB

FD measured as DCP

Direct impact

Direct impact

Indirect impact

Indirect impact

Panel A: Estimation results: dependent variable remittances Remit − 1 GDPit Intdit RERit σRER it−1 DCBit DCBit * σRER it−1

0.876***

0.866***

0.885***

0.089***

(0.032)

(0.058)

(0.029)

(0.003)

0.076

−0.014

−0.076

0.012

(0.120)

(0.022)

(0.183)

(0.020)

0.026**

0.029***

0.024**

0.031***

(0.009)

(0.008)

(0.010)

(0.010)

0.032**

0.019**

0.042**

0.015*

(0.016)

(0.008)

(0.016)

(0.008)

−0.020*

−0.088*

−0.019*

−0.071*

(0.012)

(0.047)

(0.009)

(0.039)

0.076**

0.054**

–

–

(0.035)

(0.022)

–

0.028**

–

–

(0.014) DCPit

–

–

0.091**

0.044**

(0.031)

(0.020)

DCPit * σRER it−1

–

–

–

0.022*

C

−0.035*

−0.018

−0.040**

−0.015*

(0.015)

(0.008)

(0.015)

(0.008)

Year dummies

Yes

Yes

Yes

Yes

98.47

97.91

95.61

93.76

(0.635)

(0.650)

(0.659)

(0.834)

0.380

0.360

0.320

0.330

(0.704)

(0.715)

(0.749)

(0.739)

1865

1858

1872

1867

(0.012)

Panel B: Diagnostic tests Hansen test (P value) AR(2) (P value) No of observations

Segregation of columns shows estimation with different proxies of financial development. The FDI estimation with two proxies of financial development namely, domestic credit by banks as % of GDP private sector credit as percentage of GDP, respectively. Values in parenthesis refer to standard errors of the respective coefficients (in Panel A) and p-values of the respective diagnostic tests (in Panel B). Significance at 10%, 5% and 1% are indicated by *, ** and*** respectively. The sample includes114 countries for the time period 1980–2013. The instruments include the 1–4 lagged values of regressors namely remittances, GDP, RER, volatility of RER, and Financial development measures. Some exogenous variables are also used as instruments, namely trade openness AR(2) and Hansen tests are reported in the panel B of Table 2 with following null hypothesis. Hansen test: (Ho = all instruments are valid), Arellano-Bond test for AR(2): (Ho = No autocorrelation)

measure the impact of rate of return for investment. If the investment motive dominates other motives, a positive interest differential is likely to attract more

Exchange rate volatility and capital inflows: role of financial...

remittance inflows. Our empirical findings also report that higher interest rate differential encourages remittance inflows just as reckoned by Ricketts (2011). Turning towards the real exchange rate, it is seen that depreciation of exchange rate has the potential to increase remittance inflows. Exchange rate depreciation increases the foreign wealth which is the driving force for increasing remittance inflows to depreciating countries (Amuedo-Dorantes and Pozo 2004). The real exchange rate coefficient in all specifications turns out positive and is in consonance with the empirical work of Higgins et al. (2004), which states that devaluation of a currency increases remittance inflows. In contrast, exchange rate volatility appears as negative and statistically significant in all specifications. This finding confirms that volatility contracts remittance inflows by making the returns on remittances uncertain. This result is confirmed by the findings of Ratha (2003), and Higgins et al. (2004) who propose that remittances behave in the same way as other types of capital inflows. Therefore, it is essential to include the risk variable in the empirical analysis of remittances. According to Kemegue et al. (2011), the degree of market sophistication or deposit gathering ability of financial system helps increase the remittance flows. Countries with a developed financial system have a better chance of attracting more remittances through formal channels and directing it more prolifically. Our results, across all measures of financial development, verify that financial development helps in improving the remittance inflows towards developing countries. This positive impact of financial development on remittance inflows is in line with the findings of Kemegue et al. (2011). To estimate the indirect effect of real exchange rate volatility on remittance inflows, we use an interaction term of real exchange rate volatility with each measure of financial development. The empirical estimates reveal a positive and statistically significant coefficient for all the interaction terms. The positive sign of these interaction terms imply that financial development contributes in reducing the adverse impact of exchange rate volatility on remittance inflows in selected developing countries. By combining the direct and indirect impact, we conclude that the adverse impact of RER volatility is low at higher level of financial development. Notably, in case of remittances, the impact of exchange rate volatility i.e. the direct negative impact of uncertainty dominates the indirect positive impact. It is important to note that the intensity of the adverse impact, however, is reduced due to the role of financial development. Therefore, developing countries need to improve the performance and efficiency of their financial sector in order to fully alleviate the adverse impact of RER uncertainty. To check the validity of instruments, Panel B of Tables 1 and 2 report results for the Sargan/Hansen test of instruments validity. The p-value of the test, in all specifications, confirms the validity of the instruments used in the model. Furthermore, the p-value of AR(2) shows that models have no second order autocorrelation and we do not reject the null hypothesis of no autocorrelation in the regression. In conclusion, the analysis shows consistency and confirms the theoretical as well as empirical literature. The estimation results presented by our study portray the adverse

A. Hamid, Z. Jehan

impact of exchange rate volatility on both types of capital inflow. However, the financial development reduces the adverse impact of exchange rate volatility on capital inflows. This confirms the hypothesis that financial development helps developing countries to diversify the risk attached with exchange rate movements and also provides better hedging facilities.

4 Conclusions and policy implications During the last few decades, the impact of exchange rate volatility on capital inflows has gained considerable attention in theoretical as well as empirical literature. The literature has shown the negative effect of exchange rate volatility on capital inflows. Specifically, the radical contribution by Udomkerdmongkol et al. (2009), and Higgins et al. (2004) highlights that a volatile exchange rate makes the decision of investment uncertain which in turn dampens capital inflows. The recent empirical literature explains that capital inflows have been affected by the investment climate of the host countries, and state that favorable economic conditions encourage capital inflows. Therefore, they assure the negative impact of exchange rate volatility on capital inflows (Cushman 1988, and Ratha 2003). The present study intends to analyze the impact of exchange rate volatility on capital inflows in the presence of financial development. In this regard, we select a panel of developing countries over the period 1980–2013. The study contributes in the existing set of empirical literature by estimating an indirect impact of volatility on capital inflows along with direct impact. To estimate the indirect impact, we use the channel of financial development by using two alternate measures of financial development. For empirical analysis, we employ GMM estimation techniques. The results reveal that exchange rate depreciation induces both FDI as well as remittance inflows. In contrast, a negative impact of exchange rate volatility on capital inflows has been reported. These results are in line with Sharifi-Renani and Mirfatah (2012), and Solomon (2009). However, this negative relationship of exchange rate volatility diminishes if the role of financial development is incorporated. To sum up, it is concluded that capital inflows are adversely affected by volatile exchange rates. However, improvement in financial development can offset the adverse effect of exchange rate volatility. The results attained from the present study suggest that countries need policies to stabilize their exchange rates which may help attract foreign investors. In addition, there is also a need to improve financial sector development to provide a conducive environment for business. Furthermore, since infrastructure development plays an important role in attracting FDI so improvement in its quality by developing countries can help increase FDI inflows. Likewise, these countries need to create opportunities and devise policies in such a way that remittances may be used for investment rather than for demonstration purposes. Finally, the study concludes that mechanization of remittances should be ensured through the development of the financial sector.

Exchange rate volatility and capital inflows: role of financial...

Appendix Annexure 1 Algeria

Cambodia

Georgia

Malaysia

St. Kitten

Uruguay

Angola

Cameroon

Ghana

Mali

St. Lucia

Vanuatu

Armenia

Central Africa

Grenada

Mauritania

St. Vincent

Vietnam

Azerbaijan

Chad

Guatemala

Mexico

Samoa

Zambia

Bahamas

China

Guinea

Moldova

Sao

Bahrain

Colombia

Guyana

Mongolia

Senegal

Bangladesh

Congo Demographic

Haiti

Mozambique

Serbia

Barbados

Congo Republic

Hungary

Morocco

Seychelles Solomon Island

Bahrain

Cot d’ivore

Honduras

Nepal

Bangladesh

Croatia

India

Nicaragua

South Africa

Barbados

Costa Rica

Indonesia

Niger

Sri Lanka

Belarus

Djibouti

Jamaica

Nigeria

Suriname

Belize

Dominica

Kaghazastan

Oman

Swaziland

Benin

Dominican Republic

Kenya

Pakistan

Syria

Bhutan

Ecuador

Kuwait

Panama

Tanzania

Bolivia

Egypt

Kyrgyzstan

Papua

Thailand

Bostwana

El Salvador

Lao PDR

Paraguay

Togo

Brazil

Equatorial

Lesotho

Peru

Tonga

Brunei Darussalam

Ethiopia

Libya

Philippines

Tunisia

Bulgaria

Fiji

Macedonia

Poland

Turkey

Burkina Faso

Gabon

Madagascar

Romania

Ugana

Brundi

Gambia

Malawi

Rwanda

Ukraine

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