Foreign direct investment in the energy and power sector in Bangladesh: Implications for economic growth

Renewable and Sustainable Energy Reviews 52 (2015) 1369–1377

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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Foreign direct investment in the energy and power sector in Bangladesh: Implications for economic growth Fahmida Khatun a, Mazbahul Ahamad a,b,n a b

Centre for Policy Dialogue (CPD), House 40C, Road 32, Dhanmondi RA, Dhaka 1209, Bangladesh Department of Agricultural Economics, University of Nebraska-Lincoln, 312 Filley Hall, Lincoln, NE 68583-0922, USA

art ic l e i nf o

a b s t r a c t

Article history: Received 15 July 2014 Received in revised form 29 June 2015 Accepted 5 August 2015

In this paper we present a discussion on current energy and power situation of the country, and examines the causal relationship between FDI in the energy and power sector, and economic growth in Bangladesh for the period 1972–2010. Related trend reveals a considerable gap between energy production and energy use during this period. Moreover, inflow trend of FDI was also fluctuating over the studied period. We also find that there are robust positive and unidirectional short-run causal relationships running from FDI to energy use and from energy use to GDP growth. Empirical results also confirm a causal relationship for the energy use equation in the long run. Considering the resource and technology gap and requirements for the development of the energy and power sector, FDI should be encouraged to this sector that would be imperative to the targeted GDP growth. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Foreign direct investment Energy and power sector Economic growth Bangladesh

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overview of the energy and power sector, and FDI Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FDI, energy consumption and economic growth in south Asia: Empirical evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. FDI and economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Energy consumption and economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Causality analysis of FDI in energy and power sector, and economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Conceptual framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Data and empirical strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Empirical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Summary and concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction The integration of developing and least developed countries with the global economy increased sharply in the 1990s with change in their economic policies and lowering of barriers to trade and investment. Foreign direct investment (FDI) is expected to

n

Corresponding author. Office: þ 1 402 472 9143. E-mail addresses: [email protected] (F. Khatun), [email protected] (M. Ahamad). http://dx.doi.org/10.1016/j.rser.2015.08.017 1364-0321/& 2015 Elsevier Ltd. All rights reserved.

1 2 3 3 4 5 5 6 6 7 8 8

benefit lease developed countries like Bangladesh in a number of ways. First, it supplements domestic investment which is low due to lack of resources in these countries. Second, FDI is expected to generate employment, increase domestic competition and bring other positive externalities such as transfer of technological knowhow, good practices. Bangladesh offers attractive investment opportunities to foreign investors and has adopted policies to attract FDI into the country. In fact Bangladesh seems to offer one of the most liberal FDI regimes in South Asia. Energy and power sector is one of those sectors in Bangladesh for which FDI has been encouraged through various policy supports

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Nomenclature ADF ADP AIC ARDL ECM ECT FDI FDII FY GDP

augmented Dickey–Fuller Annual Development Programme Akaike information criteria autoregressive distributed lag error correction model error correction term foreign direct investment FDI inflow fiscal year gross domestic product

as large investment is required to meet the energy demands of the country. Ref. [20] estimated that the average electricity generation has to increase by 12.5 to 14.5 percent per year to achieve a growth of 8 percent as targeted for FY (Fiscal Year) 2014–15 in the Sixth Five Year Plan (SFYP) ([27]). The Government of Bangladesh (GoB) has to allocate its limited resources among several competing priorities including the social sectors. Thus the major source of investment for energy and power sector1 is the private sector, both domestic and foreign. The extraction of natural gas and local coal and the installation of power plants in the country require large-scale investments. Given the capital intensive nature of the energy and power sector and the technological requirements for the sector, the inflow of FDI has been encouraged by the government through various supportive policies. However, FDI inflow to Bangladesh has not been satisfactory. Lack of good governance, corruption, political instability and turbulence, bureaucratic inertia, and poor law and order situation have been identified as major reasons for the less attractive investment climate in the country. How far government policies have been useful to bring in adequate FDI in the energy and power sector, and to what extent such investments have contributed to the economic growth of the country are issues to be investigated in order to take an objective view on FDI in the sector. In the context of Bangladesh, very few empirical studies are available which delve into the relationship between FDI in the energy and power sector and economic growth. Most studies looked into the relationship between the overall FDI and economic growth of the country. This paper analyses the trend of FDI flow towards the energy and power sector in Bangladesh, and examines the responsiveness of economic growth to FDI in this sector by estimating an econometric analysis based on long-term data gathered from various official sources. It also discusses issues on governance in the energy and power sector which may influence the flow of FDI in this sector, and suggests policy recommendations for its development through higher investment. The paper is organized in the following manner. Following the introduction, Section 2 presents the outlook of the energy and power sector. This section describes the capacity and reserves of the energy and power sector in Bangladesh. Various plans and policies on the sector and resource flow towards the development of the sector and resources allocated for the sector through both government channel and FDI are also discussed in this section. Review of literature on the relationship between energy FDI and economic growth in South Asia is presented in Section 3. The contribution of FDI in the energy and power sector towards economic growth in Bangladesh is examined in Section 4. Data and methodology for causality analysis and empirical results of econometric analyses are

1 Generally, energy sector includes both renewable and nonrenewable energy sources, e.g., fossil fuels, gas that used to produce electricity in power plants.

GNP GoB IEA PCEC PCGDP PP PPP SAARC SFYP VECM WDI

gross national product Government of Bangladesh International Energy Agency per capita energy consumption per capita GDP Philips–Perron Public–Private partnership South Asian Association for Regional Cooperation Sixth Five Year Plan vector error correction model World Development Indicator

also presented in this section. Finally, the paper concludes in Section 5 by presenting a few policy recommendations for the development of the sector based on the findings of the study.

2. Overview of the energy and power sector, and FDI Scenarios Total energy use in Bangladesh has been doubled between 1994 (14,611.2 kilo-tons of oil equivalent) and 2010 (29,599.33 kilo-tons of oil equivalent) [56]. Increased energy use has led to higher imports of energy as domestic sources could not meet the demand. During 1971– 2009, the average growth rate of energy import was 17.35 percent. In 2008, total import of refined petroleum products amounted to 69.97 thousand barrels per day, that was twice the quantity of imports in 1998 (36.47 thousand barrels per day). Total import of coal in 2008 (881.85 thousand tones) was four times higher than that of 1998 (205.03 thousand tones) [31]. Figs. 1 and 2 indicate the energy use, production and imports by Bangladesh. In Bangladesh, natural gas is the major source of primary energy, supplying about 75 percent of the commercial energy demand. At its current level of reserves, natural gas will not be able to meet the projected future demand unless new explorations are undertaken. The other source of primary energy is coal, which is mainly imported at present. In order to minimize the risk of price hike and reduce the burden of the government exchequer, domestic sources of coal should be explored through investing resources for coal development. The GoB has scaled up the budget allocation for energy and power sector, indicating a stronger commitment from their part for improving the power situation of the country. Allocation for the energy and power sector in the National Budget for FY2013–14 is 5 percent of the total budget and 15.6 percent of the Annual Development Programme (ADP), indicating an increase over the years. For example, in FY2008-09 allocation for fuel and electricity was 4.2 percent of the total budget, while allocation for power sector was 11.6 percent of the Revised ADP of FY2008-09. It may however, be mentioned that a large part of the government resources goes as subsidy for the energy and power sector [28]. The energy sector also receives FDI as the GoB has been promoting FDI into the country through various policy incentives, such as: (i) tax exemption on royalties, technical assistance fees and facilities for their repatriation; (ii) tax exemption on interest on foreign loans; (iii) tax exemption on capital gains from the transfer of shares by the investing company; (iv) safeguards to protect foreign investors from double taxation stemming from the multiple bilateral agreements; (v) exemption from income tax for up to three years for expatriate personnel employed under the approved industry; (vi) remittance of up to 50 percent of the salary of foreigners employed in Bangladesh and facilities for repatriation of their savings and retirement benefits at the time of their departure; (vii) no restrictions on issuance of work granted to

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Fig. 1. Primary energy use and energy production. Source: WDI [56].

Fig. 2. Energy use from domestic sources and energy imports. Source: WDI [56].

Notwithstanding various policies, development of the energy and power sector of Bangladesh has remained an issue of great concern for decades. One of the major obstacles responsible for the power shortage is the lack of adequate maintenance of existing power plants and institutional and managerial skills. Poorly managed public–private partnership (PPP) and lack of local investment inhibit the development of the energy and power sector. Due to poor physical infrastructure and lack of political commitment, energy trade with neighboring countries could not be materialized.

Fig. 3. Sectoral share of FDI inflow during 1996–2010. Source: Bangladesh Bank [12].

3. FDI, energy consumption and economic growth in south Asia: Empirical evidence

project-related foreign nationals and employees; and (viii) facilities for repatriation of invested capital, profits and dividends2. During 1996–2010, the largest share of total FDI inflows went to the ‘manufacturing’ sector followed by ‘transport, storage and communication’ and ‘power, gas and petroleum’, i.e., the energy sector (Fig. 3). The highest flow of FDI was during the period between 1997 and 2001 and between 2005 and 2007. Since 2008 onwards the FDI flow has, however, been decreasing which appears to be a major concern for the development of the energy and power sector of Bangladesh. Between 2008 and 2010, the share of FDI in the energy and power sector plummeted to approximately 10 percent or lower from as high as 36 percent in the last half of the 1990s and 30 percent in the first half of the 2000s. Unlike the power sub-sector which underwent a stable yet low level of inflow, FDI flow towards gas and petroleum development had been erratic. Interestingly, during 1996–2010, the growth of FDI flow to the energy and power sector and the growth of GDP of Bangladesh followed the similar trend (Fig. 4).

3.1. FDI and economic growth

2 For details: Private Sector Power Generation Policy of Bangladesh 1996, Government of Bangladesh (GoB).

In economic literature, discussions on FDI are centered around two major theories; these are modernization and dependency theories. In the modernization theory FDI is considered to promote economic growth on the assumption that growth requires capital investment [2] In recent times, the importance of FDI has been tagged with a number of other necessary conditions. Hence, the new growth theories emphasized the role of technology transfer through FDI since poor countries suffer from lack of necessary infrastructure, developed and open financial markets, socio-economic and political stability [2]. It has also been argued that FDI could bring along organizational and managerial skills, marketing know-how and market access opportunities [2,11,37]. FDI can also contribute to the capital accumulation and increase total factor productivity [44]. On the other hand, dependency theories suggest that FDI is not always a blessing. According to these theories, dependency on foreign investment could produce negative impact on growth and income distribution since FDI creates monopolies in the industrial sector that leads to underutilization of domestic resources [2,13]. The economy may also be controlled by foreigners instead of being

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Fig. 4. Trends of energy and power FDI, and economic growth. Source: WDI [56].

developed on its own [9]. Thus, the multiplier effect of FDI can be weak and may lead to stagnant growth in recipient countries [2]. As is the case with the theoretical view, empirical results on the role of FDI in promoting economic growth of poor countries have been mixed as well. Findings of those studies on the relationship between FDI and economic growth vary across countries depending on their domestic trade policies and the level of infrastructure, including the level of education of the labor force. A few studies also conclude that FDI can exert a positive and significant impact only when there is technology transfer, while the others found that FDI do not have any positive impact on economic growth. The heterogeneity of the effect of FDI on growth has been mentioned by many, which in turn call for host country-specific studies in this area. Some of the studies that look into the relationship between FDI and economic growth along the lines discussed above include Zhang [58], Balasubramanyam et al. [11], Campos and Kinoshita [14], Carkovic and Levine [15], Hermes and Lensink [29], Fry [26], Agosin and Mayer [3], Sylwester [54], Elias [23], De Mello [21], Nair-Reichert and Weinhold [41], and Choe [18]. Studies on the relationship between FDI in the energy sector and economic growth are almost non-existent. Most studies focus on the impact of FDI on economic development of countries. Several studies seek to examine the FDI-growth nexus in South Asian countries to test the causality and investigate short-run and long-run relationships. In most cases, the association is found to be positive, but the direction, apparently, is found to be ambiguous. Srinivasan et al. [51] for example, showed the existence of long-run relationship between FDI and gross domestic product (GDP) for Bangladesh, India, Pakistan, Sri Lanka and Nepal. While the causality depicts two way directions for all countries except India; in case of India, it is rather a one way relationship running from GDP to FDI. Agrawal [4] explored the economic impact of FDI in South Asia by undertaking time-series, cross-section analysis of panel data from five South Asian countries, namely India, Pakistan, Bangladesh, Sri Lanka and Nepal. His findings on the relationship between these two variables vary during various time periods. For example, the impact of FDI inflows on GDP growth rate is negative prior to the 1980, slightly positive for the 1980s, and strongly positive over the late 1980s and 1990s. Kundan and Qingliang [38] indicate that FDI had a positive impact on economic growth in Nepal. Using the Granger causality test, Unit Root test and cointegration test with data for the period 1980–2006, their results show that there exists a long-term relationship between the variable and direction of causality runs from FDI to GDP growth rate. In case of Pakistan, it is found that FDI has an impact on output in the long-run [35]. Using the framework of Granger causality and Panel cointegration for Pakistan over the period 1981–2008, authors have established an empirical relationship between industry-specific FDI and output. The study found bidirectional relationship in the short-run, but unidirectional relationship in the long-run from GDP to FDI. However, the impact of FDI on economic growth varies across sectors – FDI causes growth in the primary and services sectors, while growth causes FDI in the manufacturing sector.

3.2. Energy consumption and economic growth The mainstream neoclassical theory of economic growth does not pay much attention to energy resources [53]. The theory of production and growth considered energy as an intermediate input. The basic model for economic growth suggested by Solow [50] does not include resources at all. Ecological economists emphasized the need for energy as a fundamental factor for economic production. Cleveland et al. [19] argue that energy availability drives economic growth as opposed to economic growth resulting in increased energy use. Stern [52] considers energy as an essential factor of production since all production involves transformation or movement of matter for which energy is required. In the 1980s and 1990s several views existed on the potential linkages between energy and economic growth which had been tested empirically. For example, studies such as Kraft and Kraft [36], Akarca and Long [7], Yu and Hwang [57], Jorgenson [33], Erol and Yu [24], and Cheng and Lai [16] undertook empirical investigations to see whether there is any causal relationship between energy and economic growth. In case of FDI in the energy sector and economic growth, studies have tried to establish their relationships through examining the linkage between energy consumption and economic growth. Lau et al. [39] empirically examined the direction of causality and sign (in the panel sense) between energy consumption and real GDP for 17 Asian countries. These countries include Bangladesh, Bhutan, Brunei, China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Maldives, Nepal, Pakistan, Philippines, Singapore, Sri Lanka and Thailand. The panel cointegration results reveal a long-run equilibrium relationship between energy consumption and GDP. This indicates that an increase in GDP would lead to a greater use of energy. They found that energy consumption is a result of economic activity in the long run. The Granger causality test also shows that in the short-run there is a unidirectional causal relationship running from energy consumption to GDP in case of these countries. This means that energy consumption leads to economic growth in the short run. This is mainly due to the fact that these 17 Asian countries have energy-dependent economies. Pradhan [48] investigated the nexus between oil and electricity consumption and economic growth in the five countries of the South Asian Association for Regional Cooperation (SAARC) over the period 1970–2006. Using cointegration and Error Correction Model (ECM), the paper finds a unidirectional short-run and long-run causality from oil consumption to economic growth in Bangladesh and Nepal, a unidirectional short-run and long-run causality from electricity consumption to economic growth in Pakistan and Sri Lanka, a unidirectional short-run and long-run causality from economic growth to oil consumption in India and Sri Lanka, and a unidirectional causality from economic growth to electricity consumption in India and Nepal. This study finds bidirectional causality between electricity consumption and economic growth in Bangladesh, and between oil consumption and economic growth in Pakistan. Possible causal link between energy use and economic growth for five South Asian countries over the period 1971–2006 also

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examined by Noor and Siddiqi [45]. To explore the short and longrun impacts, various econometric techniques such as panel cointegration, and ECM are applied in the study. In the short-run there exists unidirectional causality from per capita GDP to per capita energy consumption. They estimate that in the long-run one percent increase in per capita energy consumption tend to decrease 0.13 percent per capita GDP. Their findings indicate that short and long-run relationship pattern between energy consumption and growth indicates that the energy shortage in South Asian countries is the consequence of increased energy use, coupled with insufficient energy supply. In the same manner, Dhungel [22] examined the causal relationship between per capita consumption of coal, electricity, oil and total commercial energy and the per capita real GDP in Nepal. Using a cointegration and Vector Error Correction Model (VECM) he finds that the increase in real GDP indicates a higher demand for a large quantity of commercial energy such as coal, oil and electricity. Empirical findings of this study indicate that there is a unidirectional causality running from coal, oil and commercial energy consumption to per capita real GDP, whereas a unidirectional causality running from per capita real GDP to per capita electricity consumption is found. Aqeel and Butt [10] used cointegration and Granger tests to study the causal relationship between energy consumption and economic growth in Pakistan. Their findings show unidirectional causality running from economic growth to petroleum consumption and causality running from economic growth to gas consumption. They also found unidirectional causality running from electricity consumption to economic growth. The causality between energy consumption to GDP in India, Indonesia, the Philippines and Thailand was examined by Fatai et al. [25]. They used both Granger and Toda–Yamamoto methodologies to assess the causality between energy consumption and economic growth over the period 1960– 1999 in these countries. It was found that Granger causality was running from GDP to energy consumption in Australia and New Zealand. The causal association among energy consumption and income in case of the four Asian developing countries was investigated by Adjaye [1]. The study found unidirectional causality from energy consumption to income in India and Indonesia and bidirectional causality in the case of Thailand and the Philippines. In case of India, Cheng [17] estimated Granger causality between energy consumption and economic growth for the period 1952– 1995 by using cointegration and ECMs. He found that the Granger causality was running from gross national product (GNP) to energy consumption. Masih and Masih [40] considered six Asian economies, namely India, Indonesia, Malaysia, Pakistan, the Philippines and Singapore to examine the temporal causality between energy consumption and income. Applying a Vector Error Correction, their findings show that energy consumption was causing income in India, income was causing energy consumption in Indonesia, and that a bi-directional causality existed in Pakistan. For the other three countries (Malaysia, Philippines and Singapore), they used an Ordinary Vector Autoregressive model. In case of these countries, no causality between energy consumption and income was revealed. For Bangladesh, Alam and Mian [8] explored the similar causal relationships between FDI and long-term economic growth. Kabir [34] also investigated about FDI and sustainable growth of Bangladesh, and found that inflows of foreign investment can expand economic production and growth. It is economic growth that attracts FDI. Tanin et al. [55] examined the relationship between FDI and GDP in the context of Bangladesh using time series data during 1970– 2006. They find that economic growth attracts FDI. By using cointegration techniques, Hye and Mashkoor [30] attempted to determine relationship between energy consumption and economic growth in Bangladesh. The causality test undertaken in the study confirms bidirectional causality in the long-run. The estimated coefficients demonstrate that both economic growth and energy

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consumption impact each other positively. Using panel data from 88 countries including Bangladesh, India, Pakistan and Sri Lanka to examine the relationship between per capita GDP and per capita energy consumption Sinha [49] found a two-way (bidirectional) short-term and long-term relationship between energy consumption (demand) and per capita GDP. Ahamad and Islam [5], Ahamad and Tanin [6] and Paul and Uddin [47] also found similar findings for Bangladesh. The above literature review indicates that FDI is not an unmixed blessing, and there is no consensus on the dynamic effects of FDI on growth. Some studies argue that the impact of FDI on growth varies across countries and relatively open economies have statistically significant results. On the contrary, some studies show that the direction of causality between FDI and growth depends on trade policies of recipient countries. Only a few studies explored the possibility of a bidirectional link between FDI and economic growth. The causal relationship between energy consumption and economic growth is found to be both unidirectional and bidirectional running from energy consumption to economic growth.

4. Causality analysis of FDI in energy and power sector, and economic growth 4.1. Conceptual framework Possible sources and directions of any causal relationship, if exists, between economic growth, FDI and energy consumption in Bangladesh can be found by examining the Granger causality. This study employs Augmented Dickey–Fuller (ADF) and Philips–Perron (PP) unit root tests to identify the order of integration of explanatory variables. The Johansen cointegration test is then employed to examine the existence of a long-run equilibrium relationship between the series of the model. The sources and directions of the causal relationship between the model variables from the Vector Error Correction Model (VECM) specified Granger causality procedures are also explored following the approach of Oh and Lee [46] and Narayan and Singh [43]. The study considers the following equations for VECM specified Granger causality analysis:

ΔPCGDPt ¼

k11 X

β11i ΔPCGDPt  i þ

i¼1

þ

k13 X

k12 X

β12j ΔPCECt  j

j¼1

β13l ΔFDIIt  l þ β13 ECTt  1 þ u1t þ β10

ð1Þ

l¼1

ΔPCECt ¼

k21 X

β21i ΔPCECt  i þ

i¼1

þ

k22 X

β22j ΔFDIIt  j

j¼1

k23 X

β23l ΔPCGDPt  l þ β23 ECTt  1 þ u2t þ β20

ð2Þ

l¼1

ΔFDIIt ¼

k31 X

β31i ΔFDIIt  i þ

i¼1

þ

k33 X

k32 X

β32j ΔPCGDPt  j

i¼1

β33l ΔPCECt  l þ β33 ECTt  1 þ u3t þ β30

ð3Þ

i¼1

In Eqs. (1)–(3), PCGDP, PCEC and FDII represent per capita GDP, per capita energy consumption and FDI inflow in Bangladesh, respectively. ΔPCGDP3, ΔPCEC and ΔFDII are the differences in these variables that capture their short-run disturbances. κs are 3

Δ Denotes first difference operator.

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Fig. 5. Trends of per capita energy consumption, per capita GDP and FDI inflow. Source: Bangladesh Bank [12] and WDI [56].

the numbers of lags; and ECT’s are the error correction terms4 to capture the long-run effects. In addition, u1t, u2t and u3t are the serially uncorrelated error terms which are derived from residuals of the estimated cointegration and measure the magnitudes of the past disequilibria. ECTs are generally measured for the long-run. If three series are out of equilibrium, the dependent variable will adjust to reduce the equilibrium error. It refers to the speed of adjustment or correction from the deviation of the dependent variable that will adjust to minimize the long-run equilibrium error. In Eqs. (1)–(3), changes in the endogenous variable are caused not only by their lags, but also by the previous period’s disequilibrium in level. In general, considering Eq. (1), per capita GDP Granger causes per capita electricity consumption and/or FDI inflow in the short-run, if the estimated coefficients on lagged values of GDP are statistically significant. In contrast, if the lagged disequilibrium term is found to be significant, then the long-run causality can be confirmed by the Granger causality test.

4.2. Data and empirical strategy This study uses data for the period 1972–2010 from Bangladesh Bank (on FDI) and from the World Development Indicators (WDI) (on per capita energy consumption and per capita GDP). For time series data, linear combinations of two or more non-stationary series may be stationary if it is integrated at same order, i.e., integrated in order one, I(1); or in order two I(2). If such a stationary combination exists, the series are considered to be cointegrated with long-run equilibrium relationships [32]. Incorporating these cointegration properties, a VECM can test the Granger causality of the series. To do so, the VECM is specifically adopted to examine the Granger causality between per capita GDP (PCGDP), FDI inflow (FDII) and per capita energy consumption (PCEC) of Bangladesh. In this process, PCEC (FDII) Granger causes PCGDP if either: i) the estimated coefficients on lagged values of PCEC (FDII); or, ii) the estimated coefficient on lagged value of error term (ECTt  1) from co-integrated regression is statistically significant. Likewise, PCGDP Granger causes PCEC (FDII), if either the estimated coefficients on lagged values of PCGDP or the estimated coefficient on lagged value of error term (ECTt  2) from co-integrated regression is statistically significant [42]. The existence of cointegration relationship indicates that there are long-run equilibrium relationships between model variables, and at least one causal relationship exists between the selected variables. But, it does not indicate the direction of the causal relationship. Moreover, the possibility of ‘spurious correlation’ may be found for the presence of cointegration between model 4 It is called the error correction term, since the deviation from long-run equilibrium is corrected gradually through a series of partial short-run adjustments.

Table 1 Summary statistics of the series. Variable

Obs.

Mean

Min.

Max.

Std. dev.

Skewness

Kurtosis

PCGDP PCEC FDII

39 39 39

277.29 117.62 229.06

674.90 185.70 1086.31

86.20 80.50  8.01

122.75 29.90 323.15

1.08 0.76 1.13

4.56 2.47 2.97

variables. In this way, the VECM can be employed to detect the sources and directions of causal relationships. In this way, the VECM allows the possibility of distinguishing between long and short-run relationships for the variables. 4.3. Empirical results This section presents the empirical results derived from stepby-step estimation of Granger causality using VECM specification. The trend of three variables for the model shows a fluctuating inflow of per capita FDI against an increasing per capita GDP in the country (Fig. 5). Summary statistics are presented in the Table 1. Results of the unit root test results for log of PCGDP, log of PCEC and log of FDII are presented in the Table 2. The ADF and PP tests are performed to check the possible unit root. The decision on series stationarity is taken based on all the test statistics and respective probability (p) values. Based on the ADF test, all series are found to be non-stationary in level, but stationary in first difference (integrated of order one, I (1)). The PP test reveals the same. In sum, results from unit root tests explore that the model variables are non-stationary in level, but stationary in first difference, I(1). This paper uses Granger causality test over other alternative techniques, i.e., Autoregressive Distributed Lag (ARDL), because of the favorable unit root properties of the series. The subsequent section explores the long-run equilibrium relationship between the series using Johansen’s maximum likelihood procedure, namely the Johansen cointegration test. To find out whether the three model variables are co-integrated, the paper employed the Johansen cointegration test. In Table 3, trace statistics and maximum Eigen value statistics reveal that the three variables, e.g., PCGDP, PCEC and FDII have at least one cointegrating relation or long-run equilibrium relationship at 1 percent level of significance. Determination of optimum lag length for cointegration test is based on Akaike Information Criterion (AIC) through the VECM procedure. As the three considered model variables are co-integrated in the long-run, the VECM specified Granger causality test is employed to find out the sources of causation and directions of the causal relationships. The VECM contains the co-integrating relations to assess the long-run behavior of the endogenous variables to congregate for their equilibrium with short-run speed of adjustment (Table 4).

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Table 2 Results of unit root tests. Variable Augmented Dickey Fuller (ADF) test Constant Level PCGDP PCEU FDII

Philips–Perron (PP) test

Constant & linear trend 1st diff.

 1.462 (0.542)  5.700 (0.000) 2.575 (1.000)  8.040 (0.000)  8.729 (0.000) 

Constant

1st diff.

Level

Order of integration Constant & linear trend

1st diff.

Level

1st diff.

Level

 4.522 (0.005)  5.596 (0.000)  1.329 (0.606)  9.813 (0.000)  4.431 (0.006)  1.208 (0.895)

 9.211 (0.000)

 3.081 (0.145)

 5.071 (0.006)  1.470 (0.536)  6.612 (0.000)  2.341 (0.402)

4.333 (1.000)

 9.559 (0.000) I (1)

 8.105 (0.000)  0.630 (0.971)  31.165 (0.000) I (1)  6.363 (0.000) I (1)

Note: Corresponding p-values are in parentheses. Table 3 Results of Johansen cointegration tests. Hypothesised no. of cointegrating equation

nn

H0 :

r¼0 rr1

None At most 1

H1:

r ¼1 r ¼2

Eigen value

0.629 0.119

Trace test

Max. eigen value test

λtrace

5% Critical value

Prob.

λmax.

5% Critical value

Prob.

35.556 5.840

29.797 15.495

0.010 0.714

29.716 3.791

21.132 14.265

0.002 0.881

Note: ‘r’ denotes the number of cointegrating vectors. nn

Denotes rejection of the hypothesis at 5% level.

Table 4 Results of VECM specified Granger causality tests. Dependent variable

Sources of causation Short-run

ΔPCGDP ΔPCEC ΔFDII

Short-run relationship

Long-run relationship

EC causes GDP FDII causes EC No causality

No Yes No

Long-run

ΔPCGDP

ΔPCEC

ΔFDII

ECTt  i

– 0.191 (0.662) 0.136 (0.712)

2.507n (0.100) – 0.923 (0.337)

0.251 (0.616) 3.942nn (0.047) –

 1.071 (  0.340)  0.003n (  0.089)  0.666 (  0.437)

Note: Generally, ‘short-run’ and ‘long-run’ causality known as ‘weak Granger causality’ and ‘feedback effect’, respectively. nn n , Implies significance at 5% and 10% level, respectively. Corresponding p-values are in parentheses.

Table 4 shows the test statistics including χ2 Wald tests and t-tests. According to the short-run causality test statistics, there is evidence of positive short-run, and a linear causal relation running from per capita energy consumption to per capita GDP (proxy of economic growth) at 10 percent significance level. This indicates past PCEC helps to predict PCGDP. The positive sign of this relation implies that an increase in PCEC leads to an increase in PCGDP. But, the reverse short-run causality does not exist. Additionally, FDI causes energy consumption in the short-run. Coefficients of the error correction term (ECTt  2) are found to be significant in the energy consumption equation (Eq. (2)), which indicates that given any deviation of per capita GDP and per capita EC from the longrun equilibrium relationship between ECTt  1 and ECTt  2 with EPC and GDP respectively, where both variables in the VECM would interact dynamically to restore the long-run equilibrium5. The short-run results provide evidence in support of the proposition 5 For additional check, modified Granger Wald test is also employed to check the group causality. Test 1 examines the causality between PCET and FDII as group 2 and PCGDP as group 1. Test 2 also examines the causality between PCGDP and FDII as group 2 and PCET as group 1. Test 3 further examines the causality between PCET and PCGDP as group 2 and FDII as group 1. The null hypothesis of these Granger causality tests state that group 1 variable is influenced only by itself, and not by group 2 variables. The calculated Chi-squares and corresponding probability values of three tests are χ2 ¼ 9.14(0.014), χ2 ¼14.90(0.000) and χ2 ¼2.31(0.281), respectively. From Test 1 and 2, we reject that group 1 variable is influenced by itself and accept alternative hypothesis that it is influenced by group 2 variables at

that economic activity is the result of energy consumption. That is, energy is an essential input to production. However, it found that economic growth is less dependent on energy consumption in the long-run.

5. Summary and concluding remarks In this paper, we examined the trends and causal relations between FDI, energy use and economic growth for Bangladesh using time series data for the period 1972–2010. It also conveys some short-run and long-run policy implications for energy demand, FDI requirement in the energy sector, and consequent economic growth. Empirical findings lead to important policy implications for the energy and power sector of Bangladesh. First, the evidence of a positive and unidirectional causality running from energy consumption to growth (GDP) implies that the reduction of energy consumption could lead to a fall in economic growth, ceteris paribus. In other words, higher energy consumption will imply higher GDP. Therefore, efforts should be made to increase the availability of per capita energy. Hence, more inflow of FDI (either direct investment, or Govt.-to-Govt. partnership) and (footnote continued) the 5% significance level. On contrary, we accept that group 1 variable is influenced by itself and not by group 2 variables for Test 3 at the 10% significance level.

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resource allocation from domestic sources (either private, or public–private partnership) for the energy and power sector are essential. Second, increased inflow of FDI is found to have positive impact on energy consumption implying that higher FDI leads to higher energy consumption. This is due to the possibility that when there is FDI flow into a country, economic activities are expected to increase, which in turn requires more energy. This underscores the need for higher FDI in the energy sector. Since present investment policy is necessary but not sufficient enough to attract FDI; policymakers have to focus on minimizing other non-policy level barriers such as political instability, delay in decision making, human resource inefficiency, corruption and lack of governance. In addition, policy makers should be critical on profit repatriation, rate of reinvestment and inclusion of domestic ownership in the investment. Third, since energy efficiency is considered least costly approach of addressing environment friendly energy security in the long run, Bangladesh can peruse aggregate energy efficient policy. However, given that Bangladesh is vulnerable to the impact of global warming it may pursue efforts towards higher use of renewable energy. Solar energy could be one of the ways not only for reduction of carbon emission, but also to protect the country from facing high fuel prices in the international market. Bangladesh has to play an active role in bringing advanced technology and resources from the developed countries in this respect. This paper only considers energy use rather than disaggregated sources, e.g., renewable and nonrenewable energy which would be a potential idea for future research.

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