Tapping on the trade-investment nexus for improving bilateral economic cooperation between Bangladesh and India

Selim Raihan and Farazi Binti Ferdous

Bangladesh and India have long bonds in culture and history. Despite such bonds and neighborly proximity, economic cooperation between the two countries has remained far below potential. A number of studies have shown that bilateral trade and investment offer immense opportunities for accelerating growth and reducing poverty in Bangladesh and India. These studies suggest that India could become a major player for accelerating the growth of intra-industry trade and uplifting foreign direct investment (FDI) inflow to Bangladesh. Also, for India, Bangladesh could become an additional source of trade as well as a critical destination for investment thus addressing many concerns relating to the economic isolation of its backward Eastern and North-Eastern states. Furthermore, better connectivity between Bangladesh and India through multi-modal transport and transit facilities will further enhance the strength of the economic relations between these two countries.

Although it experiences annual volatility, the overall trade between Bangladesh and India has increased over time, and the balance of trade remained heavily in favor of India. Total exports from Bangladesh to India increased from US$ 50.2 million in 2001-02 to US$ 527.2 million in 2014-15 (which was only 0.1% of India’s total import). The share of Bangladesh’s exports to India in the country’s overall export increased from 0.3% to around 1.5% during the same period. On the other hand, India’s exports to Bangladesh increased from about US$ 1019 million in 2001-02 to US$ 5.8 billion in 2014-15 (around 2% of India’s total export). At present, India is the second largest import source for Bangladesh. In 2014-15, the share of Bangladesh’s import from India was around 16% of the country’s total import from the world.

Looking at the product details we find that in recent years Bangladesh’s exports to India (Figure 1) have been dominated by readymade garments (RMG) (HS code 6) and jute products (HS code 5). Bangladesh also exports products like textile articles, edible fruit and nuts, salt, fish, inorganic chemicals, mineral fuels and raw hides and skins. In contrast, large parts of Bangladesh’s import from India have been raw materials and capital machineries (HS codes 5 and 8) (Figure 2) which are used in Bangladesh’s export oriented and domestic industries. At the product details, Bangladesh’s import from India for last decade were chiefly cotton, vehicles and parts and accessories, machinery, cereals, man-made staple fibres, iron and steel, electrical machinery, organic chemicals, tanning or dyeing extracts and plastics.




Though exports from Bangladesh were supposed to increase significantly as the Indian government offered Bangladesh duty-free benefit for all products except 25 alcoholic and beverage items since November 2012, exports did not increase much after 2012. A number of challenges can be made responsible for such weak export response which are related to Bangladesh’s limited export capacity, lack of diversification of export baskets, and various non-tariff measures (NTMs) and procedural obstacles (POs) due to inadequate infrastructure and lack of support facilities both at home and in the Indian market.

It is noteworthy that readymade garments (RMG) has become the major item in Bangladesh’s export to India on account of duty-free market access granted by India. In 2009-10, the share of RMG was more than 28% in total export of Bangladesh to India, which rose to 34.3% by 2014-15. However, studies have shown that there are many products in which Bangladesh has large export capacities, but actual exports to India are either very low or zero. For example, Figure 3 shows that though for products in the HS categories of 02, 16, 24, 41, 46, 64, 65 and 67, Bangladesh has either the full or significantly partial export capacities to meet India’s import demand, actual exports to India are zero. Similar observation also holds for Indian exports to Bangladesh. Therefore, there is enormous scope for raising bilateral trade between the two countries. There is a need to explore carefully, how different NTMs and POs and lack of trade facilitation affect such prospects. Necessary measures should be taken to improve the scenario. In order to address the trade infrastructural problems at the border, lately, there are some initiatives by the Government of India to set up Integrated Check Posts (ICPs) at major entry points on the land borders between Bangladesh and India. Two such ICPs have been launched recently, and they are expected to boost bilateral trade.

Bangladesh and India have to tap on the trade-investment nexus for improving their bilateral economic cooperation. The horizontal and vertical integration of Indian and Bangladeshi industries could help to improve scale economies, especially for Bangladesh, and help Indian firms gain from the use of cheap labor in Bangladesh. However, in terms of sources of FDI inflow in Bangladesh, the US, the UK, and South Korea top the list of countries, and FDI from India is still very low.

Lately, there have been a number of initiatives between Bangladesh and Indian governments to improve the investment situation. The Bangladesh Power Development Board and the Indian National Thermal Power Corporation have signed a memorandum of understanding in 2010 to set up two coal-fired power plants, each of which will have a capacity of 1,320MW, with partnership shared equally between them. Furthermore, recently, Bangladesh has offered India to establish two Special Economic Zones (SEZ) for Indian companies. Launching of these SEZs is expected to substantially increase Indian FDI into Bangladesh.

In 2015, Prime Ministers of India and Bangladesh contracted international gateway of internet service in Agartala and supply of 100MW power to Bangladesh from Tripura. India is already supplying 500 MW of power to Bangladesh, and supply of another 500 MW was also announced during Indian Prime Minister’s visit to Bangladesh in 2015. On the other hand, the bandwidth connection came as Bharat Sanchar Nigam Limited (BSNL) and Bangladesh Submarine Cable Company Limited (BSCCL) signed an agreement for leasing of international bandwidth for Internet at Akhaura. As a result, Agartala has become third station connected to submarine cable for Internet bandwidth after Chennai and Mumbai. The internet bandwidth export to India from Bangladesh will enable reliable and fast Internet connectivity for the people of Tripura as well as other parts of India’s northeastern region.

It is expected that the latest shipping arrangement between Bangladesh and India would make faster movement of goods between these two countries. Currently, such shipments are routed via Colombo or Singapore. Also, it takes around 20 days for a shipment by land. However, the direct shipping is expected to reduce the time to around 7 days, as there is no longer a need for transshipment at Colombo. The service will play a vital role in decongesting the border points and bringing down the cost and transit time involved. This improved arrangement of connectivity would bring better efficiency and thus provide the best competitive freight rates to the advantage of the industries.

The aforementioned analyses point to the fact that there are heightened political commitments among the governments of both Bangladesh and India to improve bilateral economic cooperation through different initiatives. Such initiatives need to be materialized at the earliest. As for Bangladesh, to make the most out of such initiatives, there are a number of challenges though. The country needs to significantly improve the business environment for attracting FDI, as the latest World Bank’s ranking of the ease of doing business shows that Bangladesh’s position dropped two steps to 174 out of 189 countries due to stalled regulatory reforms.

Finally, besides abovementioned economic issues, still there are some bilateral issues between Bangladesh and India, which need to be resolved for enriching mutual trust and confidence for greater economic cooperation. For example, border killing is an issue that strains India-Bangladesh relations as the victims are often ordinary people of Bangladesh living in border areas. This needs to stop, for which a political decision at the highest level is necessary. Also, the water-sharing issue between India and Bangladesh is yet to be solved properly, which undermines a lot of the developmental prospects. However, it can be hoped that these issues will be solved with the heightened commitment among political elites of the two countries for a deeper economic cooperation.

Sub-regional cooperation can be the answer to the deadlock of regional integration in South Asia

Though there is a strong demand for a deeper regional integration in South Asia, the progress has been rather slow. Actual implementation of agreements often does not match the declared ambitions, and in this context, lack of political will and leadership, institutional weaknesses and capacity and resource constraints have been argued to be the major impeding factors. The political rivalry between India and Pakistan has often constrained the SAARC to be a functional regional forum. The recent cancellation of the SAARC summit is such an example.

In order to take forward the regional integration process in South Asia a good and effective initiative is the Bangladesh, Bhutan, India, Nepal (BBIN) initiative, which is a sub-regional coordinative architecture of countries in South Asia. BBIN operates through Joint Working Groups (JWG) comprising official representation from each member state to formulate, implement and review quadrilateral agreements. Areas of cooperation include water resources management, connectivity of power grids, multi-modal transport, freight and trade infrastructure. Focused on the subcontinent’s north east, it endeavored to cooperate on trade, investment, communication, tourism, energy and natural resources development. Its objectives have been expanded over years to incorporate substantial land and port connectivity.

The economic needs and drivers for a deeper integration in the BBIN sub-region are more prominent compared to these countries’ integration with the rest of South Asia. Especially, a deeper integration among the BBIN countries is very important to place BBIN as the gateway for further integration with China and Southeast Asian countries. The political economy drivers also seem to be more favorable. In the context of some structural factors, especially the political rivalry between India and Pakistan which has confined the progress of SAARC, and landlockedness of Nepal and Bhutan, the BBIN sub-regional initiative has seen a great interest from the political elites from these four countries. The extra-regional drivers for BBIN are also favorable as there are growing interests from the international organizations like the Asian Development Bank (ADB) and the World Bank for improvement in connectivity and infrastructural development in this sub-region.

As far as intra-BBIN trade is concerned, there are substantial potentials for the rise in intra-regional trade. However, despite that India has already provided almost full duty-free-quota-free of its market access to exports from South Asian LDCs, Bangladesh, Nepal and Bhutan are facing escalated challenges to at least secure and then to increase their exports to the Indian market. These challenges are related to their limited export capacities, lack of diversification of their export baskets, and various non-tariff measures (NTMs) and procedural obstacles (POs) due to inadequate infrastructure and lack of support facilities both at home and in the Indian market. However, streamlining of NTMs and removal of associated POs are very important as such actions are likely to intensify further market integration in the BBIN sub-region through development of regional value chains. These will also encourage larger intra and extra regional investments in the BBIN sub-region which can be instrumental for growth integration among these countries. To make these happen there is a need for policy integration among the BBIN countries.

Domestic capacities of the exporters in Bangladesh, Bhutan and Nepal need to be improved to meet different international standard requirements. Unless and until these exporters develop their capacities, they will not be able to diversify exports and become competitive in the regional and international markets. A number of supply side factors at home can actually undermine the exporters’ competitiveness and constrain economic and export diversification. These factors are directly associated with the domestic production and investment environment. Most prominent of these factors are access to finance, weak physical infrastructure, inefficient ports and high transport costs, shortage of skilled workers, technological bottlenecks, lack of entrepreneurship and management skills, lack of information, and high costs of doing business.

There are some signs of heightened ‘new’ commitment among political elites of the BBIN countries. The recent speedy resolution of land boundary agreement (LBA) between Bangladesh and India, the positive reception of the India-Bangladesh Maritime Arbitration Award announced in July 2014, establishment of border haats along the border between India and Bangladesh, and the BBIN Motor Vehicle Agreement are signs of such ‘new’ political commitments.

However, the aforementioned ‘new’ commitments have not yet been translated much to resolve the issues related to NTMs and POs discussed above. There is a need to put renewed emphasis on this. There are some recent initiatives by the Government of India to solve the trade infrastructural problems at the border by setting up of Integrated Check Posts (ICPs) at major entry points on the land borders between Bangladesh and India. Two such ICPs have been put in place recently. Such ICPs need to be established at the borders between India and Nepal and India and Bhutan.

There is also a need for cooperation among different institutions in the BBIN countries to deal with NTMs and removal of POs. Cooperation is needed in a number of areas for harmonization of TBT and SPS measures, Mutual Recognition Agreements (MRAs) among respective organizations of these countries, and for introduction of increased automation of their customs clearance procedure.

Does employment status matter for the wellbeing of rural households in Bangladesh?

Selim Raihan and Fatima Tuz Zohora

In rural Bangladesh, a great challenge is to tackle the low pay, poor-quality jobs that are unrecognized and unprotected by law, widespread underemployment, the absence of rights at work, inadequate social protection, and the lack of representative voice. There remains a big question whether poverty in rural Bangladesh is concentrated in certain employment categories.

Our paper uses the data from the Bangladesh Integrated Household Survey (BIHS) of IFPRI. This data are nationally representative data of rural Bangladesh for the year 2011-2012 where the sample size is 6,500 households in 325 primary sampling units (PSUs). The reason for using the BIHS database for this study is that this is the latest available survey data on rural Bangladesh. Our paper has attempted systematic analysis in understanding the association between employment status and wellbeing of rural households in Bangladesh.

From the BIHS data, our study has used consumption expenditures as the principal indicator of household economic status or wellbeing, and has used per capita consumption expenditure as the proxy for income. The total consumption expenditure is measured as the sum of total food consumption and total non-food expenses excluding lumpy expenditures. Income (expenditure) deciles have been created by dividing the households into ten groups from the lowest to the highest in terms of households’ total income. Employment statuses have been constructed for those household heads who are able and eligible to participate in the labor market. By definition, the labor force consists of everyone above the age of 15 who is employed (including individuals working without pay) or unemployed but actively seeking employment. Household head, not counted in the labor force, includes students, retired people, disabled people, and discouraged workers who are not seeking work.

The distribution of the different employment categories in the labor force is shown in Figure 1. In the x-axis, 10 deciles are organized in ascending order on the basis of monthly consumption expenditure of the rural households. Therefore, first decile is the poorest one and the 10th decile is the richest one. The figure summarizes that, while wage employment is mostly concentrated in the poorer deciles, self-employment is concentrated mostly in the richer deciles. Salaried employed maintains smaller shares among poorer deciles.




Figures 2 and 3 show the educational status of the male and female workers by employment categories in the rural areas. Males with no education seem to be highly concentrated in the wage employment in both farm and nonfarm sector. They are also densely present in the self-employment activities. In the salaried employment category, the dominant share is of the males with less than secondary level but higher than primary education. However, males with HSC and beyond HSC account for around 25% of the salaried employment. Females with no education also seem to be highly concentrated in wage employment (Figure 3). Females with less than primary education has a dominant share in the case of unemployed (55.56 %). In the case of the unpaid family job for the female adults, around 28% of them are with less than secondary but higher than primary education.

In order to investigate the factors affecting wellbeing of rural household in Bangladesh we have used the cross section multinomial logistic regression models. The income status of the household is considered as the dependent variable, where per capita consumption expenditure is used as a proxy for households’ income status. For the explanatory variables, we have used different categories of employment of household head e.g. wage labor in the farm and nonfarm sector, self-employed in the farm and nonfarm sector, salaried worker and unpaid worker. All of these variables are dummy variables, where ‘unemployed’ has been considered as the base employment status. Other explanatory variables are age of household head, years of education of the head, number of dependent members per household, per capita landholding and a dummy variable on whether the household receives international remittance or not.

The major findings from multinomial logistic regressions can be summarized as follows. First, wage employment in the farm sector has statistically significant association with all income declies between 6 and 10. However, such employment status doesn’t have any statistically significant association with income deciles between 2 and 5. For a wage worker in the farm sector, relative probabilities to be in deciles 6, 7, 8, 9 and 10 are respectively 39 percent, 44 percent, 75 percent, 85 percent and 90 percent lower than to be in decile 1. The result depicts the fact that wage employment in the farm sector are more concentrated among the poorer households and doesn’t play any pivotal role in shifting up the status of a household. The result is quite analogous for the wage-employed in the nonfarm sector too: if the household head is employed in nonfarm activities, the relative probability to be in the deciles 9 and 10 are 62 percent and 78 percent lower (respectively) than to be in decile 1.

Second, in case of self-employment, if the household head is engaged in the farm sector, the relative probability of that household to be in decile 10 is 44 percent lower than to be in the base decile 1. This association is insignificant for all other deciles meaning that, self-employment in the farm sector does not necessarily improve the income status. On the contrary, if the household head is self-employed in the nonfarm sector, the relative probabilities to be in deciles 3, 4, 5, 6, 7, and 8 compared to the base category are higher by 90 percent, 86 percent, 124 percent, 84 percent and 72 percent respectively. It shows that, self-employment in nonfarm sector has a strong transitory power to improve household wellbeing.

Third, when considering salaried employment, the study finds no significant influence of salaried employment over shifting the well-being status from income decile 1 to higher income deciles. On the other hand, if the household head is employed as an unpaid worker the relative probability to be in deciles 8, 9 or 10 is more than 80 percent lower than to be in the decile 1.

Among other variables, household characteristics like age of the head, dependent member per household, per capita land holding and remittance status hold significant impact on the nature of economic status of the household. If the age of the household head increases by one additional year, the relative probability to be in the top four deciles compared to the decile 1 increases by around 1.2 percentage points. It is also seen that, with the rise in number of dependents in a family the relative probability of the household to be in a higher decile compared to decile 1 becomes lower. The regression results also suggest that, education and international remittances play a role of pull factor in case of shifting household status from the lowest decile to upper deciles. An increase in the years of education of the household head by one additional year increases the relative probability to be in decile 2 compared to decile 1 by 10 percentage points; whereas, for the same increment, the relative probability to be in decile 10 compared to decile 1 increases by 35 percentage points. In case of remittances, households that receive remittance have more than 3 fold relative probability to be in decile 4 or above. For the remittance receiving households, the relative probability to be in decile 10 compared to the decile 1 is more than 25 times higher than a household that does not receive remittances.  Along with these, per capita land holding is appeared as an important household characteristics that can help a household to be on the higher deciles.

The findings of this paper provide a significant indication that rural nonfarm sector has a crucial role in reducing poverty and increasing the wellbeing of the rural household in Bangladesh. The study also specifies the importance of addressing the concern in the national policy making that poverty in rural Bangladesh is highly linked with certain employment categories.

Cross-country differences in income inequality: Where do South Asian countries stand?


In recent years, there has been a growing interest among general people, researchers and policy makers in income inequality, its causes, and its effects. The most popular index of income inequality is the ‘Gini index’ which measures the inequality among levels of income of the people of any country. A Gini coefficient of zero means perfect equality, where everyone has the same income, and a Gini coefficient of 1 (or 100%) expresses maximum inequality.

For meaningful comparisons among different countries with respect to their levels and trends in income inequality we need comparable data. National surveys on households’ incomes and expenditures in different countries provide data on the Gini index of these countries for some years. However, we are not in a position to use these data for cross-country comparisons due to various reasons. In those surveys there are differences in the population covered, differences in coverage on geography, age and employment status, differences in the definition on welfare (whether to use market income or consumption data), differences in the use of equivalence scale (whether to use household per capita or household adult equivalence), and differences in the treatment of various other items, such as non-monetary income and imputed rents. The Standardized World Income Inequality Database (SWIID), introduced in 2008, provides a dataset on income inequality that facilitates comparability for the largest possible sample of countries and years. A custom missing-data algorithm is used to standardize data on cross-country income inequality using the data from national surveys (Solt, 2016). Using the SWIID database, the World Economy Database (WED) version 9.1 has generated a time series database on the “Gini index” for 207 countries over the period between 1970 and 2015 by filling missing observations with the help of different estimation methods.

Using the WED 9.1, we have produced a scatter plot diagram with data on Gini indices for 207 countries in 1980 in the horizontal axis and data on Gini indices of the same countries in 2015 in the vertical axis. In the scatter plot, dots around the 45 degree line are the countries with ‘no or very small’ changes in Gini indices during 1980-2015; dots above the 45 degree line are the countries which experienced an increase in the Gini index; and finally, dots below the 45 degree line are the countries which experienced a decline in the Gini index. Out of those 207 countries, 18 experienced ‘no or very small’ changes in Gini indices, 109 experienced increases and 80 experienced declines. Among the 8 south Asian countries, 5 countries (Afghanistan, Bangladesh, India, Pakistan and Sri Lanka) observed rises while the rest 3 countries (Bhutan, Maldives and Nepal) experienced declines. We also brought China and South Korea into the picture, and it appears that the Gini index in China increased quite astonishingly, whereas that of South Korea declined.

We have also categorized the values of Gini index as follows: a Gini index value lower than 30 is considered low; an index value between 30 and less than 40 is considered medium; an index value between 40 and less than 50 is considered high; and an index value above 50 is considered very high. Depending on these classifications, we can observe some interesting movements of the South Asian countries during 1980 and 2015. Afghanistan moved from a status of low inequality to medium inequality; Bangladesh moved from medium inequality to high inequality; though Nepal, Pakistan and Sri Lanka remained within the medium inequality range, Sri Lanka was at the border of high inequality; India moved from high inequality to very high inequality; and both Bhutan and Maldives moved from very high inequality to medium inequality. In comparison, China moved from low inequality to very high inequality, whereas South Korea moved from medium inequality to very close to low inequality.

We also explored the factors affecting inequality in the cross-country and over time contexts. Results from a fixed effect panel regression suggest that while rise in the real GDP per capita tends to have a small negative association with the Gini index, an increase in both life expectancy at birth and net secondary school enrollment are strongly associated with the decline in the Gini index. These suggest that, an increase in per capita real GDP is not a guarantee for the reduction in income inequality, whereas investment in social infrastructure with the aim of raising the life expectancy at birth and a rise in secondary school enrollment can be very instrumental in reducing income inequality.

Reference: Solt, F. (2016). “The Standardized World Income Inequality Database”. Social Science Quarterly.

First published at the Thinking Aloud on 1 September 2016

Published at The Daily Star on 1 September 2016

Dynamics of economic growth in Bangladesh

Selim Raihan and Wahid Ferdous Ibon

Rapid and sustained economic growth is very critical for Bangladesh economy in its way towards a middle income country. In this article, we have investigated the major determinants of economic growth in Bangladesh using time series data for 44 years (1972-2015). We start with a production function approach, which incorporates the features of neo classical and new-growth theories. Subsequently, we have investigated the impacts of trade policies, fiscal policies, FDI, interest rate, inflation, infant mortality rate, enrolment in secondary education, infrastructure and institution on growth in Bangladesh’s real GDP (gross domestic product). A new database (World Economy Database, version 9.1) has been used, which is complemented by data from the Peen World Table (PWT8.1) and World Bank’s World Development Indicators (WDI). Most of the variables under consideration are found to be non-stationary (integrated of order one). Two non-stationary time series may lead to a spurious relationship between them if they are not co-integrated. Therefore, we checked for the possibility of co-integrating relationship, using the Johansen co-integration test, and found at least one co-integrating relationship in all the regressions, which confirms that the long run estimates show causal relationships. We ignore bi-directional causality in the regression model, as this is not what we want to explore in this analysis.

The basic production function

With the aim of identifying the determinants of economic growth in Bangladesh, we start with a Cobb-Douglas production function. Along with employment and physical capital stock, we have incorporated human capital into the production function. We multiply the data on human capital with employment data to create the human capital adjusted employment variable. The regression results suggests that, in the long run, on average, one percent increase in the human capital adjusted employment leads to 0.25% increase in the real GDP. Furthermore, one percent increase in the physical capital stock leads to 0.12% increase in the real GDP. As the variables of the production function are co-integrated, there must be an Error Correction representation which shows the short run adjustments of the variables under consideration if there is any deviation from the long run equilibrium relationship. Error Correction term is -0.0197 which is statistically significant, negative and less than unity, as expected. About 1.97% error is thus being corrected each year following any deviation from the long run equilibrium.

Secondary school enrolment helps

There are both theoretical and empirical literature which provide evidence that the educational level and its quality are important causal determinant of income, both at the individual and national levels. A highly educated labor is more productive relative to his/her less educated counterpart, and this increased labor productivity helps a nation grow faster. Education is a key component of human capital. In terms of the net secondary school enrolment, though Bangladesh made a progress during 1972 and 2015 from around 16% to 52%, still there is a need for substantial further improvement. Here, we have investigated the effect of the net enrolment in secondary school on real GDP and have found positive effect, as expected. One percentage point rise in the net secondary school enrolment ratio leads to, on average, 0.013% increase in the real GDP.

Reduction in the infant mortality rate helps

Bangladesh has shown its capacity to reduce infant mortality rate rapidly over the past four decades. Among 1000 live births, the rate came down from 148 in 1972 to 30.7 in 2015. In the regression, the infant mortality rate appears with a negative and significant coefficient. On average, one point reduction in the infant mortality rate contributes to the rise in real GDP by 0.01%.

Greater trade-orientation promotes growth

Theoretically, trade liberalization results in productivity gains through increased competition, efficiency, innovation and acquisition of new technology. Trade policy works by inducing substitution effects in the production and consumption of goods and services through changes in prices. These effects, in turn, change the level and composition of exports and imports. In particular, the changing relative prices induced by trade liberalization cause a re-allocation of resources from less efficient to more efficient uses. Trade liberalization is also thought to expand the set of economic opportunities by enlarging the market size and increasing the effects of knowledge spill over.

Since its independence, Bangladesh underwent a variety of trade policy reforms, which resulted in the rise in trade-GDP ratio, import-GDP ratio and export-GDP ratio from 10.6%, 6.5% and 4.1% respectively in 1972 to 41.7%, 23.3% and 18.4% respectively in 2015. To identify the growth effects of these three trade-orientation variables, we incorporated them into the production function through three separate regressions. The regression results indicate that, these variables are statistically significant with positive signs. One percentage point increase in trade-GDP ratio, import-GDP ratio, and export-GDP ratio account for, on average, 0.014%, 0.023% and 0.029% increase in the real GDP respectively.

Larger FDI-orientation propels growth

Foreign direct investment (FDI) is another driver of economic growth, particularly for a least developed country (LDC) like Bangladesh. FDI contributes to transfer the technical knowhow from advanced countries to the less developed countries. In 2015, the FDI inflow in Bangladesh was only US$ 2.2 billion which was about 1% the GDP, whereas government, as stated in the 7th five year plan, aims to achieve a level of FDI inflow of US$ 9.6 billion by 2020. In the regression, the coefficient of the FDI-GDP ratio is found to be statistically significant and positive, as expected. One percentage point increase in the FDI-GDP ratio leads to the rise in real GDP, on average, by 0.12%. In order to attract more FDI, there is a need to maintain political stability, improvement in infrastructure and reduction in the cost of doing business. The planned 100 special economic zones, if they are implemented successfully, can be helpful in attracting FDI.

Positive effect of government transfer payments

The regression result confirms a positive significant impact of government transfer (social security payments, safety net programs, pension payments etc.) on the rise in real GDP in Bangladesh economy. On average, one percentage point rise in the ratio of government transfer to GDP leads to a rise in real GDP by 0.05%.

Reduction in lending interest rate helps

Interest rate is the price of fund that private investors lend from the banks. Therefore, more private investment takes place following a reduction in lending rate, which in turn promotes economic growth. This is evident from our regression analysis that one percentage point reduction in the lending rate, on average, increases real GDP by 0.03%.

Inflation hurts growth

Rise in the general price level hurts Bangladesh’s growth. An increase in the price level decreases the real wage earned by the laborers. This lower real wage is followed by a lower aggregate private consumption demand, which in turn affects national income badly. Our regression analysis suggests, one point increase in consumer price index accounts for, on average, 0.001% reduction in real GDP.

Infrastructure promotes growth

Infrastructure is a key ingredient for high and sustained economic growth. Better infrastructure helps total factor productivity to rise by lowering transaction cost and a more efficient use of inputs of production. Due to the lack of time-series data on different dimensions of infrastructure, here we consider total number of mobile and fixed line telephone subscriptions as a proxy for infrastructure. In the regression analysis, we find that one percent increase in total telephone subscription results in, on average, 0.12% rise in real GDP.

Quality of institution matters

We have considered an index of institution in the regression. We have constructed the index of institution using the data of six major ICRG (www.prsgroup.com) variables, namely bureaucracy quality, control of corruption, investment profile, democratic accountability, government stability, and law and order. As values of these six ICRG variables have different scales, we have rescaled them between 0 and 10. The aggregate institution index is the average of these six indicators with the range between 0 and 10, where 0 and 10 respectively indicate the lowest and highest levels of quality of institution. In 1980, the index value was 2.15, which increased to 5.5 by 2015. The regression suggests a positive significant role of institution on real GDP in Bangladesh. On average, one point rise in the institution index leads to the rise in real GDP by 0.05%.

What do we learn?

The analysis in this article suggests that, for further economic growth acceleration in Bangladesh, there is a need for reforms in economic policies and institutions, investment in infrastructure, and making most of the demographic dividend through investment in public health, education, and human capital development. All these will require increased domestic private investment and FDI targeting broader economic and export diversification. Reform of economic and political institutions for efficiency gains is critically important.

Transitions between growth episodes: Do institutions matter and do some institutions matter more?

Selim Raihan, Sabyasachi Kar and Kunal Sen

A large literature has examined the role of institutions in explaining economic growth. While the earlier literature has examined the role of institutions in determining long-run per capita income, a new literature examines the determinants of growth accelerations and deceleration episodes – which are large discrete changes in medium term growth rates that are common in developing countries. Some of these studies examine the onset of growth accelerations while others examine the onset of growth decelerations. However, these studies look at only the timing of the shift in the growth rate (either as an acceleration or a deceleration), and the econometric methodology they use are probit models (where the year of the break is taken as one, with other years as zero) to study the likelihood a growth break occurring in a given year, for a set of correlates. An important limitation of these studies is that they do not differentiate between the different growth episodes that a country is transitioning from or to. For example, when a country moves from a growth collapse to rapid growth, it is a different growth transition qualitatively than when it moves to an episode with slightly positive but slow growth rates.

In this paper, we investigate the role of economic and political institutions in determining the likelihood of a country transitioning from one growth episode to another. In contrast to the previous literature, in this paper, we provide a richer characterisation of the growth process where a country may move between six different types of growth episodes, ranging from growth collapses to rapid growth episodes. By doing so, we are better able to capture the episodic nature of growth and that many countries tend to switch frequently between growth collapses to slow growth episodes to rapid growth episodes.

We differentiate between six types of growth episodes – from growth collapses (where the episode specific per capita real GDP growth rate, g, is -2 per year), to negative growth (g between -2 and 0), stagnation (g between 0 and +2), stable growth (g between +2 and +4), moderate growth (g between +4 and +6), and rapid growth (g over +6). Using multinomial logit models, in the context of a panel dataset of 125 countries from 1984 to 2010, we examine the likelihood of switching from one growth episode to another growth episode. We examine the role of contract viability (as a measure of the quality of economic institutions) and the role of democracy and bureaucratic quality (as measures of political institutions) in explaining the switches that countries experience between different types of growth episodes. The data on contract viability, democracy and bureaucratic quality are derived from the ICRG database (www.prsgroup.com).

We find that though bureaucracy quality has a positive effect while switching from negative growth episode to positive growth episodes, it doesn’t matter in most of the cases while switching from lower order growth episodes to higher order growth episodes. Both contract viability and democratization can explain the switching from negative growth episode to positive growth episodes. Contract viability and democracy can also explain the movements from lower positive growth episodes to higher positive growth episodes. However, while contract viability is important for moving from stable growth episode to rapid growth episodes, democracy is not important in explaining this switch. This suggests that while better economic and political institutions matter in taking a country from growth collapses to stable growth, economic institutions matter more than the political institutions for the switching from stable growth to rapid growth.

Our results suggest that, democratic episodes do not necessarily witness transitions to rapid growth episodes from moderately positive growth episodes. However, democratic episodes do witness a transition from negative to positive growth episodes, indicating that democratization does prevent the worst type of growth episode that a country can experience. We also find that improving state capacity in the form of the quality of the bureaucracy can help in taking a country out of negative growth episodes but that higher state capacity does not increase the likelihood of rapid growth episodes. This finding suggests that previous research that has found a positive role of bureaucratic quality in fostering economic growth need to differentiate between phases of growth, and that the relationship between bureaucratic quality and economic growth may not be monotonic.

We find that the most important institutional determinant of switching to higher order growth episodes from lower ones, and in particular, to rapid growth episodes, is the nature of property rights institutions – that is, the extent to which investors trust the viability of contracts. In contrast to the previous literature on the determinants of growth accelerations, we find that not only does institutional quality matter in bringing about a growth acceleration, it is the case that the greater the quality of property rights institutions, the higher is the likelihood of a transition to a rapid growth phase.

Our findings have clear policy implications. For a country in a growth decline or collapse, it is important to stress improvements in both political and economic institutions, such as bureaucratic quality, viability of contracts and democratization to move into an episode of positive growth. However, once the country is in a stable or moderate positive growth episode, further movements into rapid growth episodes need larger emphasis on improving the quality of property rights institutions than enhanced democratization or state capacity. Economic institutions trump political institutions in bringing about rapid growth episodes, though they both matter in reversing growth collapses.

Dr. Selim Raihan (Professor, Department of Economics, Dhaka University, Bangladesh; Email: selim.raihan@gmail.com), Dr. Sabyasachi Kar (Research Fellow, Institute of Economic Growth, Delhi, India), Dr. Kunal Sen (Professor, IDPM, University of Manchester, UK)

First published at the Thinking Aloud on 1 August 2016

Published at The Financial Express on 2 August 2016

Published at ESID blog on 1 August 2016



Does institution matter for human capital development?

graph_human capital

A fundamental proposition of new growth theories is that human capital is a key driver of economic growth. Development of human capital for the people of a country encompasses not only the diffusion and assimilation of available knowledge, but also the generation of new knowledge – the source of innovation and technological change – which boosts economic growth.

It is rather a challenging task to measure a country’s stock of human capital. Popular indicators, used to measure human capital, include adult literacy rate, school enrolment rates, average years of schooling, quality of schooling etc. The Penn World Table version 8.1 provides a dataset on an index of human capital (HCI) for 134 countries over a period of 6 decades. HCI is an index of human capital per person which is related to the average years of schooling and the return to education. In 2010, United States had the highest HCI value (3.62) and Mozambique had the lowest one (1.27). In that year, among the 134 countries, 33 countries had HCI values higher than 3; 48 countries had values between 2.5 and 2.99; 28 countries had values between 2 and 2.49; and 25 countries had values less than 2. In South Asia, in 2010, the HCI values for Bangladesh, India, Nepal, Pakistan and Sri Lanka were 2.07, 1.93, 1.71, 1.99 and 3.16 respectively.

Why do some countries have higher level of human capital than others? Empirical literature have looked at different factors such as spending (both public and private) on education and health, and differences in income levels; but hardly there has been any emphasis on differences in institutional capabilities among the countries. However, quality of institution, as it affects economic growth process, can also have a bearing on the quality of human capital. Therefore, a valid question can be asked: does institution matter for human capital development? Of course there could be a bi-directional causality between human capital and quality of institution, where quality of institution could also be influenced by the level of human capital. Nevertheless, leaving aside the causality, here we are more interested to know about the association between these two.

The scatter-plot, as presented in the graph, has been generated using the data of index of human capital and index of institution for 93 countries over a period of 1984-2010 with over 2500 observations. We have constructed the index of institution using the data of six major ICRG (www.prsgroup.com) variables, namely bureaucracy quality, control of corruption, investment profile, democratic accountability, government stability, and law and order. As values of these six ICRG variables have different scales, we have rescaled them between 0 and 10. The aggregate institution index is the average of these six indicators with the range between 0 and 10, where 0 and 10 respectively indicate the lowest and highest levels of quality of institution.

The scatter-plot suggests a very strong positive association between quality of institution and level of human capital, which signifies the importance of better institution for higher level of human capital. Interestingly, if we compare Bangladesh with Malaysia, levels of both institution and human capital of Bangladesh in 1990 (1.62 and 1.52 respectively) were much lower than those of Malaysia in 1990 (6.05 and 2.31 respectively). Despite the fact that during 1990 and 2010, Bangladesh made some notable progresses in both fronts, by 2010, the levels of these two indices of Bangladesh (5.52 and 2.07 respectively) were below than what Malaysia had in 1990!

Results from a more sophisticated cross-country panel econometric regression reinforces this association. In this regression, the index of human capital has been considered as the dependent variable. We have also created two institutional indices: economic institution and political institution. The economic institution index is comprised of three ICRG indicators – bureaucracy quality, control of corruption and investment profile; whereas the political institution index consists of other three ICRG indicators – democratic accountability, government stability and law and order. Other explanatory variables include initial GDP per capita, public expenditure on education as a percentage of GDP, and under-five mortality rate. The regression results indicates that after controlling for initial GDP per capita (which has a positive significant association with human capital index), public expenditure on education has a statistically significant positive association and under-five mortality rate has a statistically significant negative association with the human capital index. The highly significant and positive coefficients of both economic and political institution indices suggest strong positive associations between these institutional variables and human capital index. The z-score regression analysis, however, refers to larger importance of political institution over economic institution in human capital development.

The aforementioned analysis points to the fact that better economic and political institutions matter for human capital development. While countries need to make critical spending for human capital development, improvement in institutional environment is unequivocally essential.

Published at the Thinking Aloud on 1 July 2016

Published at The Financial Express on 18 July 2016