Determinants of Foreign Direct Investment (FDI): Evidence from Bangladesh

Md. Qamruzzaman Assistant Professor Department of Business Administration University of Asia Pacific Email: qzamanfindu@gmail.com

Abstract

The aim of this paper is to assess the relative importance of trade and foreign exchange liberalization, infrastructure availability and economic and political stability in Bangladesh with respect to FDI. The analysis is conducted for total FDI and for FDI in manufacturing for period 2000-2013. The results show that trade and foreign exchange liberalization, infrastructure availability and sound economic and political conditions increase FDI inflows. Their effects are much higher for FDI in the manufacturing sector than for total FDI. This result is robust to alternative indicators of trade and foreign exchange liberalization, and to change in the specification. The message to Bangladesh’s policy makers is twofold. First, efforts toward trade and foreign exchange liberalization should be initiated or further increased in order to make the region attractive to foreign investors. Second improvements in other aspects of the investment climate are important complements to liberalization and result in additional and sensitive increase of FDI inflows .

Keywords: FDI, Reforms, Liberalization.

JEL classifications: F1; O11

Introduction

FDI inflows can represent additional resources a country needs to improve its economic performance. By increasing capital stock, FDI can increase country’s output and productivity through a more efficient use of existing resources and by absorbing unemployed resources. For instance, De Gregorio (1992) shows, in a panel of 12 SAARC countries, that FDI is about three times more efficient than domestic investment (see also UNCTAD, 1992 and Blomstrom et al, 1992). FDI can also act as a catalyst for local investment by complementing local resources and providing a signal of confidence in investment opportunities. Agosin and Mayer (2000), using a panel of 32 countries over the period 1970-96, finds that FDI crowds-out domestic investment in South-Asia and crowds-in in Asia. Finally, FDI can stimulate the development and dispersion of technological skills through transnational corporations’ internal transfers and through linkages and spillovers among firms. Borensztein et al (1998), focusing on 69 developing countries, supports the effect of FDI flows on economic growth through a “catch-up” process in the level of technology. It also reveals a strong complementarily between FDI and human capital. FDI has an overall positive effect but its magnitude depends on the stock of human capital available in the host country.

The reason for the high export and FDI performance in the South Asian region has been related to prolonged application of inward-looking strategies based on import-substitution (Nabli and De Kleine, 2000). This is why, during the 1980s, some of the South Asian countries engaged in a process of economic reform, involving a more outward orientation of their economies, the lowering of trade barriers, privatization of many industries and reform of the foreign-exchange market. However, other Asian countries are still lagging behind (Nabli and Veganzones, 2003). Moreover, international evidence (see Dasgupta et al, 2002) suggests that trade and foreign exchange policies might not be sufficient and companion policies would be needed to further increase the attractiveness of a country. Such policies aim at strengthening the investment climate. They include the availability of adequate infrastructure and the quality of the economic, the political and the institutional framework.

The paper addresses two questions. First, whether the reforms undertaken by Bangladesh can help improving the record in term of FDI attractiveness. Second, can improvement of other aspects of the business climate (physical infrastructures and political and economic stability) further increase, and to what extent, FDI attractiveness of the country. For this purpose, an econometric model of the determinants of FDI has been set up and estimated over a large sample. The results show that Bangladesh has undertaken trade and foreign-exchange market reforms are able to attract more FDI. The improvement in other aspects of the business climate can result in an increase of FDI inflows that is comparable to the one resulting from trade and foreign exchange policies.

The paper goes a step further by conducting a similar exercise using FDI in manufacturing instead of total FDI. This is motivated by two facts. First, in some countries FDI may be due to natural resource abundance and their inflows may be little affected by the business climate. Second, the manufacturing industry is more conductive to growth than agriculture or mining. The results suggest that the impact of trade and foreign exchange market reforms and of improvement of the business climate is higher for FDI in manufacturing than for total FDI.

The paper is organized as follows. Section 2 introduces the literature. Section 3 presents the econometric analysis. Section 4 assesses the likely impact of reforms on Bangladesh’s FDI inflows. Section 5 concludes.

Determinants of FDI Inflows

Various motivations of FDI were put forward in the literature. The eclectic theory of FDI groups them into three categories (Dunning 1981 and 1988). First, ownership-specific advantages that allow firms to compete with the other firms in the markets it serves regardless of the disadvantages of being foreign. Second, transaction costs associated with trade and licensing that make the internalized transactions through FDI more efficient. Third, location advantages that make the chosen foreign country a more attractive site for FDI than the others. Given the objective of the study, it will focus on the latter. In this study, the group is made through country’s advantages into three categories: basic economic factors, trade and foreign exchange policy and other aspects of the business climate.

1. Basic Economic Factors

An early survey by Agarwal (1980) summarized the basic economic determinants of country attractiveness with respect to FDI: the difference in the rate of return on capital across countries, portfolio diversification strategy of investors and market size of the host country. The difference in the rate of return is dependent on incentives for foreign investors and supply of cheap labor. Empirical evidence shows that the effect of incentives provided by the host country on FDI is only marginal however. Agarwal explains this unexpected finding by the fact that incentives are generally accompanied by a set of restrictions and requirements. The supply of cheap labor appears as a more convincing explanation of FDI. Overall, empirical evidence on the relationship between inter-country differences in the rates of return and FDI does not provide any conclusive results. This ambiguous finding is due, according to Agarwal, to statistical and conceptual problems. Theoretically, FDI is a function of expected profits but available data are on reported profits. In addition, reported profits may not be similar to actual profits since transactions between the parent company and its affiliates are subject to intra-company pricing rather than to market pricing.

Finally, FDI is considered to be a function of output or sales on the host market. Most empirical studies reviewed by Agarwal have lent support to the relationship between FDI and market size of the host countries. This view is, however, challenged by Lucas (1993). Focusing on seven Asian countries (Indonesia, Malaysia, Philippines, Singapore, South Korea, Thailand and Taiwan) over the period 1960-87, he considered two measures of market size. One concerns the export market and the other concerns the domestic market. The results revealed a weak relationship between the size of domestic market and the volume of FDI and a high degree of responsiveness of FDI to incomes in major export markets. This may reflect the outward orientation of foreign firms located in this region. FDI inflows are also found to be more responsive to wages than to costs of capital including taxes.

2.Trade and Foreign Exchange Policy

The impact of trade and foreign exchange policy was examined, among others, by Hufbauer et al. (1994), Froot and Stein (1991), Cushman (1985) and Goldberg and Kolstad (1995). Hufbauer et al. (1994) show that the size and openness of the host country are important determinants of FDI flows from the United States and Japan. The relationship between FDI flows and exchange rate was examined by Froot and Stein (1991) who found that FDI inflows are negatively correlated with the value of the dollar. This implies that a depreciated currency can stimulate in buying control of productive corporate assets. Cushman (1985) focused on the effects of real exchange rate risk and expectations on FDI. The results show significant reductions in US direct investment associated with increases in the current real value of foreign exchange, and very strong reductions associated with the expected appreciation of real foreign exchange. Goldberg and Kolstad (1995) explore the implications of short-term exchange rate variability on FDI flows and support the hypothesis that volatility contributes to the internationalization of production.

Some studies focused on other policies such as grants, subsidies, tax abatement, loan's guarantees and interest subsidies. Gubert and Mutti (1991) found that incentive schemes designed to attract FDI flows were effective in altering foreign investment decisions. Brewer (1993) points out that these policies can either increase or decrease market imperfections and therefore increase or decrease levels of FDI. Loree and Guisinger (1995) suggest that the effect of policies on FDI may differ between developing and developed countries. Finally, Castanaga et al (1998) found that exchange rate distortions in the host country do not have a negative effect on FDI flows while growth expectations exert a positive effect and corruption a negative one.

3. Other Aspects of the Business Climate

Economists generally acknowledge the important role of infrastructure in stimulating growth and investment. Wheeler and Mody (1992) found that infrastructure quality is an important determinant of FDI inflows to LDCs. Labor costs and the existing foreign investment also play an important role. Their results also suggested that incentive variables to attract more FDI flows such as tax breaks or short run grants have only a limited effect because transfer pricing and deduction of foreign taxes provide alternative ways to reduce the amount of paid taxes. Richaud et al (1999) provided additional support to the positive impact of infrastructure on FDI. Drawing on endogenous growth theory, they set up a four-equation model to investigate the impact of infrastructure on growth, trade, domestic investment and FDI. Their estimates confirmed the positive impact of infrastructure on FDI.

Political instability is expected to have a negative effect on FDI flows through its impact on profit uncertainty. Root and Ahmed (1979) tested for the effect of economic, social and political variables on FDI. They found that four economic (per capita GDP, GDP growth rate, economic integration, importance of transport, commerce and communication) one social (degree of urbanization) and one political (the number of constitutional changes in government leadership) variables have an effect on FDI. Schneider and Frey (1985) reexamined the issue and concluded that both economic and political factors are crucial for FDI flows to LDCs. As far as economic factors are concerned, FDI reacts positively to per capita GNP and negatively to the balance of payments deficit. Growth of GNP and the workers' skill level are found to have weak effects on FDI decisions. Regarding political determinants, the amount of bilateral aid coming from Western countries has a strong positive effect on FDI flows, while the government’s ideological position (right or left wing position) does not have any significant effect.

The role of institutions is crucial in terms of commitments to and enforcement of rules. Corruption is generally put at the heart of the non-enforcement of rules in LDCs. It is found to depress growth and domestic investment and to contribute to an unfair wealth distribution (Mauro, 1995). Wei (2000) carefully examined the relationship between FDI and corruption. He used three measures of corruption, all of which are based on surveys of international entrepreneurs. The estimation results showed the existence of a negative relationship between corruption level in the host country and inward foreign direct investment. Henisz (2000a) examined the effect of commitment to rules on growth and investment. He focused on the effect of frequent or arbitrary changes in taxation, regulation and other relevant economic policies. He found that commitment to rules has a statistically and economically significant impact on growth and that this result is robust to various specifications. Henisz (2000b) focused on the effects of political hazard and contractual hazard on investment decision of multinational corporations. The results confirm that firms are more likely to enter wealthier countries with large population and credible political rules.

Analysis and Interpretation

1. Trade and Foreign Exchange Liberalization

Empirical studies differ with respect to FDI specifications. The differences concern both the variables to be included in the specification and their definition (nominal versus real measures and levels versus growth rates). A common specification relates nominal FDI to GDP, per capita GDP and the growth rate of GDP (UNCTAD, 2010). Here, the following basic specification is adopted to which it add indicators of trade and foreign exchange liberalization:

Log ( (1)

With

FDI : nominal FDI

GDP : nominal GDP of the host country

GDPpc : real per capita GDP

RGDP : real GDP growth rate of the host country

Lib : trade and foreign exchange liberalization indicator

: Error term.

GDP captures the size of the host country’s internal market. A higher GDP is assumed to imply better market opportunity and more attractiveness for FDI . GDPpc is related to the wealth of the resident of the host country and then to demand effectiveness. A higher real GDP per capita is also supposed to increase the attractiveness for FDI . The RGDP reflects the dynamism of the host country and its future market size. An increase in the growth rate of real GDP characterizes a dynamic economy which may be more attractive for investors .

Finally, the expectation of trade and foreign exchange liberalization to participate in a friendly climate for business and investment and to lead to more FDI inflows . A synthetic indicator of trade and foreign exchange liberalization is provided by Sachs and Warner (1995). This is a dummy variable ( S-W ) taking the value one for the years during which a country was classified as liberalized and the value zero otherwise. A country is classified as liberalized according to the following criteria: (a) Non-tariff barriers covering less than 40 percent of traded goods, (b) average tariff rates below 40 percent, (c) a BMP of less than 20 percent, (d) no extreme controls in the form of taxes, quotas or state monopolies on exports and (e) the country is not considered a socialist country.

Equation (1) was first estimated using the above indicator ( S-W ). Then, split this indicator into four components: one concerns openness to trade and the others concern foreign exchange market.

Trade openness measured as the ratio of trade to GDP has been used extensively in the literature. This study therefore uses an indicator which correct for this bias. The indicator chosen is calculated as the ratio of imports plus exports to GDP from which is deducted the “Natural Trade Openness” of the economies calculated by Frankel and Romer (1999), as well as the exports of oil and mining products. This indicator reflects better the trade policy ( TPol ) of a country than the simple trade openness ratio.

Regarding exchange market, this study uses the dollar real exchange ( RER ), its volatility ( RERVol ) and the Black Market Premium ( BMP ). The latter — which is a widely used measure of distortion in foreign exchange market — as well as RER volatility and appreciation are expected to affect negatively FDI flows.

(1’)

Equations (1) and (1’) were estimated using a sample of cross-section and time series data. The sample includes annual data from 1980 to 2010 for Bangladesh. This Study used panel data econometric methodology. Tests of fixed and random effects were conducted to select the most adequate models. The estimates are heteroskedastic consistent.

Table 1: Trade and Foreign Exchange Liberalization

(Dependent variable Logarithm of total FDI)

Specifications	Specification 1		Specification 2		Specification 3		Specification 4		Specification 5
Variables	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.
GDP	1.57*	(6.95)	2.35*	(7.35)	1.90*	(4.76)	2.06*	(6.23)	1.57*	(3.99)
GDP per capita	1.37*	(2.72)	0.06	(0.08)	0.41	(0.50)	0.05	(0.06)	0.79	(0.90)
GDP growth	0.01	(1.33)	0.01	(1.35)	0.02	(1.24)	0.01	(1.19)	0.02	(1.13)
Indicator S-W	0.49*	(2.01)
Trade Policy			1.00*	(2.57)	1.00*	(2.18)	0.99*	(2.47)	0.99*	(2.12)
Real Exchange Rate			-0.50**	(-1.64)	-0.28	(-0.47)	-0.41	(-1.39)	-0.21	(-0.36)
Black Market Prem.					-0.18*	(-2.80)			-0.18*	(-2.57)
RER Volatility							-0.30*	(-2.94)	-0.26*	(-2.25)
Number of countries	72		49		48		49		48
Number of observations.	646		434		298		428		295
Adjusted R2	0.84		0.84		0.83		0.85		0.83
Fixed effects	F(71,570)=12.7		F(48,380) = 13.2		F(47,244) = 7.5		F(48,373) = 13.6		F(47,240) = 7.4
Random effects	CHISQ(3)=39.1		CHISQ(5)=45.7		CHISQ(6)=148.5		CHISQ(5)=23.4		CHISQ(6)=16.9

Note : Data have been compiled from WDI (2010).

* and **: significant at the 5% and the 10% respectively.

Table 1 reports the estimation results. There are four specifications: the first one incorporates the Sachs-Warner indicator; the remaining three include trade policy and various combinations of exchange market indicators. The fixed effects and the random effects tests support the focus on the fixed effects model.

In specification 1, all the coefficients are significant (except for GDP growth, RGDP ) with the expected sign. This is the case of the coefficient of the Sachs-Warner indicator of trade and foreign exchange liberalization ( S-W ). This indicates that trade and foreign exchange reforms increase total FDI inflows. In the other specifications, the coefficients of per capita GDP ( GDPpc ), GDP growth ( RGDP ) and real exchange rate ( RER ) are never significant (at the 5% level) while having the expected sign. In contrast, the coefficients of trade policy ( TPol ), BMP and exchange rate volatility ( RERVol ) are consistently significant across specifications.

In other words, a high degree of trade openness of the host country has clearly increased total FDI inflows. As well, exchange rate volatility and distortions in the foreign exchange market had a negative impact on total FDI inflows. These results are consistent with Lucas (1993) who found high degree of responsiveness of FDI to incomes in major export markets for Asian countries and related it to the outward orientation of foreign firms located in this region. Note also that Hufbauer et al (1994) have found that the size and trade openness of the host countries are important determinants of FDI flows.

2. Investment Climate

The above results lend clear support to the positive impact of trade and foreign exchange liberalization on total FDI inflows. However, international evidence (Dasgupta et al, 2002) suggests that companion policies aiming at strengthening the investment climate would be needed to further increase the attractiveness of a country. To disentangle the role of the various determinants, this manuscript augmented and re-estimated equation 1 with indicators of infrastructure availability, economic and political stability. Given the reported strong complementarily between FDI and human capital (Borensztein et al, 1998) an indicator of the availability of adequate human capital is also considered. The indicators were first introduced separately and then simultaneously (Equation (2)).

This study used the aggregate Sachs and Warner (1995) index of trade and foreign exchange liberalization ( S-W ) and did not use a similar split as in Table 1. Otherwise — given the missing observation for exchange rate variables ( RER and RER Vol ) and BMP on the one hand and those for the additional variables.

As an indicator of human capital this study used the secondary school enrolment ratio ( Enrol2 ). The number of fixed phones per capita proxies the availability of infrastructure ( Phone ). The indicators of economic and political stability were drawn from the International Country Risk Guide (1999) where a numerical value is assigned to a predetermined range of risk components. The scale awards the highest value to the lowest risk and the lowest value to the highest risk. The economic risk rating ( EcoStab ) provides an assessment of a country’s current economic strengths and weaknesses while the aim of the political risk rating ( PolStab ) is to provide a mean of assessing the political and institutional framework of the countries [1] (see ICRG, 1999).

(2)

Table 2: Trade and Foreign Exchange Liberalization and Business Environment

(Dependant variable Logarithm of total FDI)

Specifications	Specification 1		Specification 2		Specification 3		Specification 4		Specification 5
Variables	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.
GDP	1.39*	(5.77)	1.04*	(3.58)	1.22*	(5.00)	1.53*	(6.26)	0.75*	(2.44)
GDP per capita	1.12*	(2.14)	0.12	(0.19)	1.10*	(2.22)	1.37*	(2.66)	0.35	(0.52)
GDP growth	0.01	(1.19)	0.01**	(1.73)	0.00	(1.03)	0.01	(1.52)	0.01*	(2.23)
Indicator S-W	0.64*	(2.49)	0.50**	(1.99)	0.44	(1.43)	0.51**	(1.71)	0.59**	(1.74)
Education	1.19*	(2.24)							0.85	(1.42)
Fixed Phones			0.79*	(3.59)					0.45**	(1.90)
Political Stability					0.03*	(4.61)			0.02*	(2.24)
Economic Stability							0.03**	(1.88)	0.03*	(2.31)
Number of countries	70		71		64		63		62
Number of observations.	624		548		572		554		469
Adjusted R2	0.85		0.87		0.85		0.85		0.87
Fixed effects	F(69,549)=13.3		F(70,472)=12.9		F(63,503)=13		F(62,486) = 14		F(61,399) = 13.6
Random effects	CHISQ(4)=39.0		CHISQ(4)=20.1		CHISQ(4)=16.7		CHISQ(4) = 35.7		CHISQ(7) = 22.7

Note : Data have been compiled from the WDI (2010) and from ICRG (2010) for political and macroeconomic stability.

* and **: significant at the 5% and the 10% respectively.

The results are those of the fixed effect model.

The estimates are heteroskedastic consistent.

The estimation results are presented in Table 2. A first interesting result concerns the liberalization index ( S-W ). This variable is always significant (except in the third specification) and its coefficient level is broadly similar across specifications (i.e. between 0.44 and 0.64, see Tables 1 and 2).

When additional determinants of FDI are introduced separately (i.e. human capital ( Enrol2 ), fixed phones ( Phone ), political ( PolStab ) and economic stability ( EcoStab )), their coefficients are always significant with the expected positive sign. When these are introduced simultaneously, the coefficient of human capital ( Enrol2 ) become insignificant — due to possible co-linearity.

At this stage of the empirical analysis, I can conclude that the impact of trade and foreign exchange liberalization is robust and consistent across specifications. This impact is rather strong: one standard deviation of the S-W indicator leads to an increase of 0.2 point of the log of FDI. The results also confirm that a friendly business climate complements trade and foreign exchange reform in further attracting FDI [2] . For instance, one standard deviation improvement of physical infrastructures leads to an increase of 0.11 point of the log of FDI.

3. FDI in Manufacturing

In the previous section, this study have empirically validated the positive role of trade and foreign exchange liberalization, as well as of the investment climate on total FDI flows to the developing world. FDI in manufacturing being more productive than total FDI, it is interesting to ask the question of its determinants.

In this section, I have investigated if trade and foreign exchange liberalization, as well as the investment climate have constituted pertinent explanatory factors of the attractiveness of a country in terms of FDI flows to the manufacturing industry. Equation (2) has been tested by replacing total FDI by FDI in manufacturing.

The equation has been estimated using a sample of 20 to 26 countries from 1990 to 1999. Due to the lack of information on FDI in manufacturing, our sample has been substantially reduced. As before, the panel data is used for econometric techniques.

The estimation results are presented in Table 3. As previously, the liberalization index ( S-W ) is positive and significant in all specifications. The impact of trade and foreign exchange liberalization on FDI inflows (total and in manufacturing) is therefore robust and consistent.

Table 3: Trade and Foreign Exchange Liberalization and Business Environment

(Dependant variable Logarithm of FDI in the manufacturing industry)

Specifications	Specification 1		Specification 2		Specification 3		Specification 4		Specification 5		Specification 6
Variables	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.	Coef.	t-stat.
GDP	1.22*	(3.05)	1.33*	(3.05)	0.77	(1.55)	0.24	(0.55)	1.15*	(2.66)	0.48	(0.74)
GDP per capita	1.08	(1.13)	1.40	(1.35)	0.47	(0.36)	1.11	(1.33)	1.12	(1.17)	1.41	(1.07)
GDP growth	-0.01	(0.74)	-0.01	(1.04)	-0.01	(0.41)	-0.02**	(1.68)	-0.01	(0.61)	-0.02	(1.51)
Indicator S-W	1.04*	(2.31)	0.93**	(1.98)	1.1*	(2.41)	1.09*	(2.59)	1.06*	(2.27)	0.87*	(2.1)
Education			0.77	(0.88)							-1.36	(1.56)
Fixed Phones					0.79*	(2.2)					0.21	(0.55)
Political Stability							0.05*	(4.25)			0.05*	(3.7)
Economic Stability									0.01	(0.4)	-0.03	(1.3)
Number of countries	21		21		21		20		20		20
Number of observations.	148		148		139		144		144		135
Adjusted R2	0.9		0.9		0.91		0.91		0.89		0.92
Fixed effects	F(20,123)=18.3		F(20,122)=18.2		F(20,113) = 19.4		F(19,119) = 18.2		F(19,119) = 18.2		F(19,107)=19.2
Random effects	CHISQ(3)= 6.3		CHISQ(4)=17.2		CHISQ(4)=0.65		CHISQ(4)=4.7		CHISQ(4)=6.0		CHISQ(4)=8.3

Note : Data have been compiled from the WDI (2002), from UNCTAD for the FDI in the manufacturing industry and from ICRG (1999) for political and macroeconomic stability.

* and **: significant at the 5% and the 10% respectively.

The results are those of the fixed effect model.

The estimates are heteroskedastic consistent.

Source : Authors’ estimations

Another important finding consists in the magnitude of the coefficient of the liberalization index. This coefficient is almost double than in the case of total FDI (0.9 to 1.1 compared to 0.44 to 0.64). This makes trade and foreign exchange liberalization an even more important factor for the attractiveness of a country when more productive FDI is concerned. This can be justified by the fact that trade and foreign exchange liberalization introduces more competition, provides more market opportunities and allows for more technology transfers. These conditions can be considered as good incentives for the manufacturing sector to invest — especially when export oriented.

When additional determinants of FDI are introduced separately in the equation (i.e. human capital ( Enrol2 ), fixed phones ( Phone ), political ( PolStab ) and economic stability ( EcoStab )), their coefficients have the expected positive sign but are not always significant. This is the case of education ( Enrol2 ) and of economic stability ( EcoStab ). When these indicators are introduced simultaneously, only the coefficient of political stability ( PolStab ) remains significant.

In summary, the estimation of the determinants of FDI in the manufacturing industry has revealed to be more difficult than the one of total FDI. Some results seem, however, robust. This is the case of the size of the market (which gives to the foreign investors a positive signal to invest in a country), of trade and foreign exchange liberalization (which impact on FDI flows is always significant), as well as of political stability. These are interesting findings which should not be neglected if a country wants to attract more productive FDI.

Conclusion

The paper shows, for a panel of specific Time 2000 to 2013 that trade and foreign exchange liberalization has constituted a key factor for the attractiveness of Bangladesh in terms of FDI. This result is robust regardless the type of FDI (total or in manufacturing), the indicator of trade and foreign exchange liberalization, and the specification used. The findings also highlight the important role of various aspects of the investment climate in increasing countries’ attractiveness in term of FDI.

This analysis supports the argument that the weak FDI record of the in some of the years of Bangladesh can largely be explained by the lack of reforms of the economies. This is the case of trade and foreign exchange reforms which has been insufficient compared to other more successful countries in Asia. This impact is even stronger if one considers FDI in the manufacturing sector. Similar conclusions were reached regarding the quality of governance and the availability of physical infrastructures.

The message to Bangladesh’s policy makers is twofold. First, trade and foreign exchange liberalization are key factors to the attractiveness of the region in terms of FDI. Second improvements in other aspects of the investment climate are important complements to liberalization and can result in a sensitive increase of FDI inflows. The latter is comparable to the one resulting from liberalization policies. Hence, although institutional reforms can take time, it deserves the necessary efforts given their outcomes as compared to other reforms. When liberalization, governance and infrastructures effects are taken together, FDI flows to Bangladesh catch up with some developed countries in the world.

References

Achy, L. and Kh. Sekkat, (2003),”The European Single Currency and ASIA’s Exports to Europe,” Review of Development Economics , 7, 563-583.

Agosin M. R. and R. Mayer (2000), “Foreign investment in developing countries: Does it crowd in domestic investment?”, UNCTAD working paper 146.

Agarwal, J. P. (1980), “Determinants of foreign direct investment: A survey”, Weltwirtschaftliches Archiv 116, 739-773.

Blomstrom, M., Lipsey, R. and R., Zejan (1992), “What explains developing country growth”, NBER working paper 4132.

Borensztein, J., J. De Gregorio and J-W. Lee (1998), “How does foreign direct investment affect economic growth?”, Journal of International Economics 45, 115-135.

Brewer Th. L. (1993), Government policies, market imperfections, and foreign direct investment, Journal of International Business studies 24 (1), 101-120.

Castanaga V., J. Nugent and B. Pashamova (1998), Host country reforms and FDI inflows: how much difference do they make?, World Development 26(7), 1299-1314.

Cushman, D. O. (1985), Real exchange rate risk, expectations, and the level of direct investment, The Review of Economics and Statistics 67 (2), 297-308.

Dasgupta, D., M. Nabli, C. Pissarides and A. Varoudakis (2002), “Making Trade Work for Jobs: International Evidence and Lessons for Bangladesh”, World Bank mimeo

De Gregorio, J. (1992), Economic growth in Latin America, Journal of Development Economics 39, 58-84.

Dunning, J. D. (1981), “Explaining the international direct investment position of countries toward a dynamic or development approach”, Weltwirtschaftliches Archiv 117, 30-64.

Dunning, J. D. (1988),”The eclectic paradigm of international production: a restatement and some possible extensions”, Journal of International Business studies 19(1), 1-31.

Frankel, J.A. and D. Romer (1999),“Does Trade Cause Growth?”, The American Economic Review, Vol 89, NO 3.

Froot K. A. and J. C. Stein (1991), “Exchange rates and foreign direct investment: An imperfect capital markets approach”, Quarterly Journal of Economics 106 (4), 1191-1217.

Goldberg L. S. and Ch. D. Kolstad (1995), “Foreign direct investment, exchange rate variability and demand uncertainty”, Journal of International Economics 36, 855-873.

Grubert, H. and J. Mutti (1991), Taxes, tariffs and transfer pricing in multinational corporate decision making, Review of Economics and Statistics 5, 285-293.

Henisz J. W. (2000a), The institutional environment for economic growth, Economics and Politics 12 (1), 1-31.

Henisz J. W. (2000b), The institutional environment for multinational investment, Working paper of the Reginald H. Jones Center, The Wharton School, Yniversity of Pennsylvania.

Hufbauer G., D. Lakdawalla and A. Malani (1994), Determinants of direct foreign investment and its connection to trade, UNCTAD Review, 39-51.

International Country Risk Guide (1999), Brief Guide to the Ratings System.

Loree D. W. and S. E. Guisinger (1995), Policy and non-policy determinants of U.S. equity foreign direct investment, Journal of International Business Studies 26 (2), 281-299.

Lucas, R. E. B. (1993), On the determinants of direct foreign investment: Evidence from East and Southeast Asia, World Development 21 (3), 391-406.

Makdisi S., Z. Fattah and I. Limam (2000), Determinants of Growth in The Asian Countries, the Global Development Network

Mauro, P. (1995), Corruption and growth, Quarterly Journal of Economics 110, 681-712

Nabli M. K. and A. I. De Kleine (2000) , Managing Global Integration in the Middle East and North Africa, in B. Hoekman and H. Kheir-El-Din (Ed.) "Trade Policy Developments in the Asia", published by the World Bank.

Nabli, M. K. and M.A. Veganzones-Varoudakis (2003), “Reforms and Growth in the SAARC Countries: New empirical evidences”, Middle East and North Africa Working Paper Series, the World Bank, Washington D.C (forthcoming).

Richaud, C., Kh. Sekkat and A. Varoudakis (1999), Infrastructure and Growth Spillovers: A Case for a Regional Infrastructure Policy in Africa, Mimeo, University of Brussels.

Root, F. and A. Ahmed. 1979, Empirical determinants of manufacturing direct foreign investment in developing countries, Economic Development and Cultural Change 27: 751-67.

Sachs, J. and A. Warner (1995), Economic reform and the process of global integration, Brookings Papers on Economic Activity 1, 1-117.

Schneider, F. and B. Frey (1985), Economic and political determinants of foreign direct investment, World Development 13(2), 161-175.

Sekkat Kh. and A. Varoudakis (2002), The Impact of Exchange and Trade Policy Reforms on Manufactured Exports in North Africa, Development Policy Review, 20,177-191.

UNCTAD (1992), World Investment Reports.

UNCTAD (1998), World Investment Reports

WDI (2002), World Development Indicators, World Bank, Washington, D.C..

Wei S-J. (2000), How taxing is corruption on international investors?, The Review of Economics and Statistics 82 (1) 1-11.

Wheeler, D. and A. Mody (1992), International investment location decisions: The case of U.S. firms, Journal of International Economics 33, 57-76.