How do public education and health spending reduce poverty?

Selim Raihan and Mehzabeen Ahmad

In recent decades, the developing world has made important progress in reducing extreme poverty. The data from the World Bank shows that the number of people living below the international poverty line of US$ 1.9 a day dwindled down from 1.85 billion people in 1990 to 768.5 million in 2016. However, the global share of the extreme poor population stands at over 10%, and there is uneven progress across different regions in the world. Therefore, eradicating poverty in all its forms and dimensions, including extreme poverty, remains the greatest global challenge and the most significant hurdle in the path of attaining sustainable development goals (SDGs) worldwide.

A majority of the global decline in poverty is explained by the reduction of poverty rates in East Asia and Pacific and even South Asia to an extent, due to the thriving economic growth experienced by these regions. However, a large population continues to suffer from poverty and a major portion of the rest remains vulnerable and at risk of falling back below the poverty line. A glaring spatial disparity can be perceived, accompanied by low levels of human development. If the qualities of health, education, employment and overall standard of living continually fail to cope with income growth, it may ultimately further hinder the capability of the masses; reinforce poverty and impede the process of growth. A similar picture can be admonished for Sub-Saharan Africa, which currently hosts the largest number of poor compared to other regions. This region’s multidimensional aspect of poverty is reflected in economic, human and social deprivation, explained by the very slow progress in Human Development Index (HDI) from the 1990s and the elevated rate of income poverty. Inequality also remains a significant crisis in the Latin American countries, in the form of chronic and transitory poverty, despite the recent upsurge of economic development in this region.

As the gap between the rich and poor widens, across and within nations, it becomes imperative to ensure a sustained resilience and global initiative against all dimensions of poverty. With that aim, the first SDG is assigned to “end poverty in all its forms everywhere” and its seven associated targets focus on various approaches to universal eradication of poverty and inequality, with a special attention to implementing necessary social protection programs, ensuring equal access to basic utilities, mobilizing global resources to extend cooperation towards the developing countries and constructing national and international policy and strategy frameworks.

In order to understand the current state of the cross-country differences in the poverty rates, we compared poverty rates across 72 developing countries (for which data is available from the World Bank’s World Development Indicators database) for the time period of 2010-15. Table 1 and Table 2 present the top 10 and bottom 10 performing countries with respect to poverty rates based on US$ 1.9 and US$ 3.2 poverty lines respectively.

Table1

Table2

Table3

According to Table 1, all the 10 countries with highest rates of poverty, in terms of US$ 1.9 poverty line, are from the Sub-Saharan African region, with Madagascar displaying the staggeringly highest rate of 77.8%. In contrast, the list of top countries with lowest poverty rates is dominated by the European countries, with countries such as Belarus, Poland, and Romania displaying almost no population below the US$ 1.9 poverty line. Few countries from Asia also make it to the top with minimal levels of poverty.

Table 2 provides a similar scenario for poverty rates calculated at a poverty line of US$ 3.2. Most countries on the list of bottom 10 or highest poverty rates remained unchanged. Madagascar and Burundi have almost 90% of the population below poverty line. Among the countries which possess the lowest rates of poverty at US$ 3.2, Belarus again tops the list, while Malaysia and Hungary make an entry in the top 10 rankings.

Table 3 illustrates the situation of all South Asian countries (except Afghanistan, due to unavailability of data), in terms of poverty. The countries have been ranked from the lowest to the highest rate of poverty for US$ 1.9 and US$ 3.2 poverty lines. Sri Lanka and Bhutan top both the lists, while India and Bangladesh stand at the bottom of the list with the highest share of the population living below the poverty line.

It has long been argued in the economic literature that public spending on education and health can be a powerful policy tool in the developing countries to reduce poverty, as these expenditures not only address the symptoms of poverty but also the causes of poverty. Public spending on education and health is argued to contribute to economic growth of a country by strengthening the human capabilities of the poor people. However, empirical literature to support this view has been limited due to the unavailability of time-series data on poverty. In this article, we use a cross-country panel data of poverty, constructed by Raihan (2017), to explore how public spending on education and health can affect poverty. This dataset has been constructed by considering periodic poverty rates (of US$ 1.9 poverty line) and average values of other variables for those corresponding periods. The constructed data has seven periods between 1981 and 2015. These are 1981-1985, 1986-1990, 1991-1995, 1996-2000, 2001-2005, 2006-2010 and 2011-2015. The missing values of the poverty rates have been filled-in using extrapolation and interpolation methods. This constructed data has 72 countries and the source of the data is the World Development Indicators of the World Bank.

The fixed effect panel regression results suggest that the coefficient of the per capita GDP is negative and significant suggesting that increase in the per capita GDP is strongly associated with a reduction in the poverty rate. Also, the ratio of remittance to GDP appears to have a positive and statistically significant association with the reduction in the poverty rate. After controlling for differences in per capita GDP and remittance-GDP ratios, one percentage point rise in the share of public spending on education in GDP is associated with 1.33 percentage points fall in the head-count poverty rate, and one percentage point rise in the share of public spending on health in GDP is associated with 2.4 percentage points fall in the head-count poverty rate. Both the fixed effect coefficients of public education and health spending are highly statistically significant.

Results from the aforementioned empirical exercises have important policy implications. A large number of developing countries, with the incidence of high poverty rates, are seriously lagging behind in terms of ensuring the critical levels of public spending on education and health in proportion to their GDPs. The business-as-usual scenarios of public education and health spending will not help these countries achieve the first SDG of ‘no poverty’ by 2030. There is thus a need for some extraordinary efforts in bringing large positive changes in the business-as-usual scenarios.

Raihan, S. (2017). “A cross-country panel dataset on poverty”, mimeo. SANEM

Dr. Selim Raihan, Professor, Department of Economics, University of Dhaka & Executive Director, SANEM: selim.raihan@gmail.com

Mehzabeen Ahmad, Research Associate, SANEM: mehzabeenahmad@gmail.com

First published in the Thinking Aloud on 1 December 2017

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The arithmetic of poverty in Bangladesh

Selim Raihan

Bangladesh has made important progress in reducing poverty over the past one and half decades. According to the national estimates, the overall head-count poverty fell from as high as 48.9% in 2000 to 24.3% in 2016. Also, the extreme poverty fell from 34.3% to 12.9% during the same period.

Despite its progress in reducing poverty, there are some major concerns regarding whether Bangladesh will be able to achieve the targets set by Goal 1 of the Sustainable Development Goals (SDGs) by 2030 with the business-as-usual scenarios. Goal 1 of SDGs sets the targets of eradicating extreme poverty and reducing at least by half the proportion of people living in poverty according to national definitions.

First, Bangladesh still remains a country with a very high incidence of poverty. In 2016, there were about 40 million poor people as per the national poverty line income. The number of extreme poor is also staggering with about 21 million people living below extreme poverty line in 2016. If we consider World Bank’s Lower Middle Income Class Poverty Line, which has a value of US$3.2 (PPP, in 2010), in 2010, 59.2% people in Bangladesh were under the poverty line income in contrast to 31.5% poor people as per the national poverty line income. This suggests that small adjustments in the poverty line income can change the poverty statistics quite significantly.

graph_poverty

table-poverty

Second, the annual average reduction in poverty rates has declined gradually over the past one and half decades. During 2000-2005, the annual reduction in overall poverty rate was 1.8 percentage points, which declined to 1.7 percentage points during 2005-2010, and further declined to 1.2 percentage points during 2010-2016. The most alarming trend is that while during 2000-2005, the annual reduction in extreme poverty rate was 1.8 percentage points, the rate declined to 1.5 percentage points during 2005-2010 and to 0.8 percentage points during 2010-2016. This suggests that the scope and success in reducing overall and extreme poverty rates in Bangladesh have become limited in recent years.

Third, the poverty elasticity of economic growth declined over the past one and half decades, indicating a declining effectiveness of economic growth in reducing poverty. The poverty elasticity of economic growth shows the percentage point change in poverty rate due to a percent change in real GDP (gross domestic product). In case of overall poverty, such elasticity declined from 0.32 in 2000-2005 to 0.16 in 2010-2016. For extreme poverty, the elasticity had a larger fall as it declined from 0.33 to 0.1 during the same period.

Fourth, despite that during 2010-2016, the country witnessed the highest average annual growth rate in GDP, both the annual reduction in poverty rates and poverty elasticity of economic growth had the lowest values. This suggests that economic growth alone cannot take care of reduction in poverty. As per the calculated elasticity values of 2010-2016, and with the business-as-usual growth rate of GDP, Bangladesh will have an overall and extreme poverty rates of around 10% and 4% respectively by 2030. Even with an accelerated average growth rate of GDP of 8%, overall and extreme poverty rates, by 2030, will be around 6.5% and 2% respectively. This means that, though there will be some progress in reducing overall poverty, neither the business-as-usual nor the accelerated growth scenarios will be able to eliminate extreme poverty by 2030. Under the business-as-usual growth scenario, there will still be around 8 million extreme poor, and under the accelerated growth scenario, there will still be around 4 million extreme poor by 2030.

Despite accelerated economic growth in recent years, why has there been much slower progress in poverty reduction? Three critical factors can be attributed to this. First, the annual average number of generation of employment declined from 1.7 million in 2000-2005 to 1.3 million in 2005-2010 and further to 0.9 million in 2010-2016. This means the accelerated economic growth during 2010-2016 was not ‘employment-friendly’. Second, the annual average share of public expenditure on education in GDP remained frustratingly unchanged at around 2% throughout 2000-2016. Bangladesh is among the bottom list of countries in the world with the lowest ratio of public expenditure on education to the GDP. In contrast, such ratio is around 5% for most of the Southeast Asian countries. Third, the annual average share of public expenditure on health in GDP declined from around 1% in 2000-2005 to 0.9% in 2010-2016. The public health expenditure as the percentage of GDP in Bangladesh is one of the lowest in the world, whereas, such ratio is around 2.5% for most of the Southeast Asian countries. All these three factors contributed to a rising inequality too in Bangladesh over this period. While in 2000, the ‘gini’ coefficient, a measure of income inequality, was around 0.45, it increased to as high as 0.48 by 2016. There are now strong global evidence that the effectiveness of economic growth in lowering poverty falls with the rise in income inequality.

What needs to be done? In order to increase the effectiveness of economic growth in reducing poverty, the ‘jobless’ growth phenomenon needs to be avoided. For this, the economic growth momentum needs to be tuned for ‘meaningful’ structural transformations of the economy where promotion of labor-intensive and high-productivity sectors would be fundamental. Also, poverty reduction is not simply about raising household income, but also about expanding human capabilities. In this context, Bangladesh has to increase the shares of public expenditure on health and education in GDP quite substantially in the coming years.

Dr. Selim Raihan. Executive Director, SANEM. Email: selim.raihan@gmail.com

First published in the Thinking Aloud on 1 December 2017

Can Bangladesh continue to grow without ‘good governance’?

Selim Raihan

If we look at the growth pattern of Bangladesh from 1990, we discover two specific characteristics: first, the growth rate has been on the rise, and second, it is less volatile compared to those of many other countries (for example, India, Vietnam, Cambodia, China, Malaysia, Thailand and Ghana) which are known as ‘high growth performing countries’. Bangladesh’s growth experience has often been termed as ‘Bangladesh paradox’ given that the country has been able to perform well despite ‘weak governance’. Now, the big question is: can Bangladesh continue to grow without ‘good governance’? If we look over the last three decades, obviously, Bangladesh had been growing without the so-called ‘good governance’. Then what does this ‘good governance’ mean?

Four contemporary analytical approaches can be linked to the discussion on ‘good governance’. The new institutional economics (contemporary lead presenters are Daron Acemoglu and James Robinson), representing a variant of the neo-liberal orthodoxy, argue for specific and well-defined rules and property right systems (‘good governance’) for economic growth. There are three alternative approaches to this new institutional economics. The approach by Douglass North, Joseph Wallis and Barry Weingast argues for ‘limited access order’ in a large number of developing countries in contrast to ‘open access order’ in the advanced economies. In ‘limited access orders’, political elites divide up control of the economy, each getting some share of the rents; and since outbreaks of ‘violence’ (conflicts among the elites) reduce the rents, the elite groups have incentives to reduce conflicts among them. The approach by Mushtaq Khan stresses on ‘political settlement’, which highlights on the relative holding of the power of different groups and organizations contesting the distribution of resources, and a ‘political settlement’ emerges when the distribution of benefits supported by its institutions is consistent with the distribution of power in society. Mushtaq Khan also emphasizes on ‘growth-enhancing governance’ (un-orthodox institutional arrangements) in contrast to ‘market-enhancing governance’ (orthodox institutional arrangements, as signified by new institutional economics). Finally, the approach by Lant Pritchett, Kunal Sen and Eric Werker emphasizes on ‘deals space’, ‘rents space’ and ‘political settlements’ for growth acceleration and growth maintenance in developing countries. The rents space is characterized by private sector firms who can be rentiers (securing rent from the export of natural resources), powerbrokers (securing rent from the regulated domestic market), magicians (firms participate in competitive export markets), and workhorses (firms participate in unregulated domestic markets). Deals, in contrast to rules, among the political and economic elites, can be open (access is open to all) or closed (access is restricted); and also they can be ordered (deals are respected) or disordered (deals are not respected). The countries are likely to exhibit high growth when deals are open and ordered.

Can we explain the growth experience of Bangladesh through these four approaches? The approach by new institutional economics cannot explain the growth of Bangladesh, since Bangladesh never had the so-called ‘good governance’ but the economy continued to grow. Furthermore, all these approaches have three major problems. First, approaches of ‘limited access order’ and ‘political settlement’ emphasize more on the ‘elite agreement’ at the macro level, thus ignore the perspectives at the sectoral level. However, the ‘deals-rent space’ approach has a better holding on the sectoral level analysis. Second, all these approaches emphasize on the process of ‘elite agreement’ rather than on the outcome, which does not convincingly show how such process affects economic growth. Third and most importantly, all these approaches emphasize on ‘elite agreement’, and overlook the critical nexus between elites and non-elites within the society. Only in ‘limited access order’ approach, such nexus is shown through the ‘power of violence’ of non-elites.

Empirical research suggests that there are four major drivers of growth in Bangladesh: exports of readymade garments (RMG), remittances, growth in agriculture, and microfinance.  Now, it is clear that we cannot explain these growth drivers of Bangladesh with the usual definition of governance or politics by the aforementioned four approaches.

From a political economy perspective, in my view, there must be some substances by which these growth drivers are fueled; and I want to name these substances as ‘political capital’. The usual meaning of ‘political capital’ is a feeling of trust that politicians build among the common people through which they exert their influence in the society. But, according to my opinion, ‘political capital’ is an outcome of agreements among the political elites and support from the non-elites on such agreements over certain growth drivers in the economy. In order to source such support, elites ensure some critical benefits for non-elites. Over the last three decades, Bangladesh has been able to generate crucial stock and flow of ‘political capital’ in favor of the aforementioned growth drivers. Bangladesh is not rich in natural resources, which did not help to generate substantial rents for the political elites. Elites, thus, found the RMG sector as a source of generation of rents, and they were able to draw support from the non-elite through the creation of large-scale employment opportunities in the RMG sector. In the case of remittances, international migration of a large number of people helped alleviation of poverty, and thus gathered support from the non-elites. For the agricultural sector, this ‘political capital’ is generated from the experience of the 1974 famine, as the political elites realized that the country like Bangladesh cannot afford anything like this in the future. Therefore, subsequent governments, focused on the development of the agricultural sector to ensure food security. Finally, as microfinance, another example of elite and non-elite nexus, played important roles in generating growth and alleviating poverty in Bangladesh, there had been a construction of significant stock of ‘political capital’ around microfinance over the last three decades.

Therefore, Bangladesh can continue to grow until the ‘political capital’ provides returns over the existing drivers of growth. Given the fact that there are growing challenges for these existing drivers, political elites in Bangladesh also need to find new drivers for growth acceleration. There are two new prospective drivers, for which critical ‘political capital’ is yet to be formed. The first one relates to the comprehensive economic and trade integration with neighboring countries, and the second one is government’s initiative of setting up 100 special economic zones (SEZs) by 2030 for rapid industrialization of the country through large-scale domestic and foreign investments. It is a high time that political elites in Bangladesh come out from their comfort zone of old drivers towards the journey of building ‘political capital’ for new drivers.

Dr. Selim Raihan. Executive Director, SANEM. Email: selim.raihan@gmail.com

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.

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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.

Fig1

Fig2

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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?

inequality_graph

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