Policy Options Beyond 2015 Achieving the MDGs in Bangladesh Background Paper for European Development Report 2015 Jörgen Levin Örebro University School of Business
1. Introduction Official Development Assistance (ODA) to Bangladesh,has not kept pace with GDP growth. As illustrated in Figure 1 this means that ODA as a share of Gross Domestic Product (GDP) is in decline. At the same time, however, according to a recent progress report on the Millennium Development Goals (MDGs), Bangladesh has made significant progress in the areas of reducing poverty, reducing the prevalence of underweight children, increasing primary school enrolment, and lowering the infant mortality and maternal mortality rates (Planning Commission, 2013). The MDG target of halving the population living below the poverty line was achieved in 2012. Progress in under-five mortality and maternal mortality rates was impressive during the 1990 2010 period (Table 1). The proportion of the population with access to safe drinking water was, however, only 86% in 2010 far below the target of 97.5%. 1 Access to improved sanitation has increased both in urban and rural areas and may be achieved in 2015. The only target that is unlikely to be achieved is the education target of 100% completion. Compared to other developing countries, performance in Bangladesh has been impressive, especially in view of the declining aid-to-gdp ratio and relatively low public spending. Figure 1: ODA flows to Bangladesh 1992 2009 (% of GDP) 3.00 2.50 2.00 1.50 1.00 0.50 Total grants as % of GDP 0.00 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Asian Development Bank (2010) 1 This does not take arsenic contamination into account, which is also our assumption in the various scenarios presented in this paper. 1
Table 1: Selected MDG indicators and Targets MDG Indicator 1990 2005 2010 Target 2015 MDG 1: Prop of pop below 2122kcal (%)(HIES) 59.0 40.0 31.5 29.5 MDG 2: First-cycle primary net completion rate (%) 43.0 54.0 79.5* 100.0 MDG 4: Under-5 mortality rate (per 1,000 live births) 146.0 120.0 44.0* 48.7 MDG 5: Maternal mortality rate (per 100,000 live births) 574.0 250.0 194.0 143.0 MDG 7a: access to safe drinking water 79.0 61.0 98.2 89.5 MDG 7b: access to improved sanitation 39.0 43.0 63.6 69.5 Source: Planning Commission (2013) */2011 This paper addresses the question of whether Bangladesh could achieve the remaining MDG targets within an extended timeframe. We present various scenarios in a consistent macromicro framework and provide some insights on the relative merits of various public expenditure strategies, other external shock scenarios and different financing scenarios. Part of Bangladesh s success is the relative long period of high GDP growth and in the final part of the paper we present shock scenarios on the vulnerability of achievements to date. We have chosen 2021 as the final year, which coincides with Bangladesh s current aim to become a middle-income country (MIC). The outline of the paper is as follows. Section 2 briefly summarises the methodology and data used, and Section 3 presents the results of different sets of scenarios. Section 4 concludes. 2. Methodology and data 2.1 Methodology Although the situation in Bangladesh is better than in many other developing countries and despite the downward trend in aid-to-gdp ratio we look at alternative financing options to reach the MDGs in an extended timeframe. Many of the key MDG-related policies and required public expenditure have economy-wide and feedback effects into the processes that determine whether the MDGs will be achieved. For instance, the provision of health and education has spillover effects and synergies with other MDGs (including per-capita household consumption and MDG achievements in related areas). In this process, the need for external financing depends on general economic performance, including growth in domestic government revenues. In this paper we use a version of the MAMS model (Bourguignon et al., 2008) calibrated for Bangladesh to cover the period from 2005 to 2021. MAMS is an extended CGE 2
model with a focus on policies related to the achievement of social development targets, such as the MDGs and the Sustainable Development Goals (SDGs) that are likely to succeed them. The starting points in terms of structure and computer code for MAMS are the static IFPRI Standard Model and dynamic extensions of it. For each time period, the core CGE module gives a comprehensive and consistent account of decisions and related payments involving production (activities producing outputs using factors and intermediate inputs), consumption (by households and the government), investment (private and government), trade (domestic and foreign), taxation, transfers between institutions (households, government, and the rest of the world), and the distribution of factor incomes to institutions (reflecting endowments). This module also considers the constraints under which the economy operates (the budget constraints of institutions and producers; macro balances; and market constraints for factors and commodities). In addition to these standard features of a static CGE model, the core CGE module in MAMS also updates selected parameters (including factor supplies, population, and factor productivity) on the basis of exogenous trends and past endogenous variables. In the model, growth depends on the accumulation of production factors (labour at different educational levels, private capital, and other factors such as land, if singled out in the database) and changes in factor productivity, which may be influenced by the accumulation of government capital stocks and openness to foreign trade. The structure is recursive: the decisions of economic agents depend on the past and the present, not the future; in other words, the model does not consider forward-looking behaviour. The MDG module captures the processes that determine MDG achievement in the areas of education, health, and water and sanitation. Specifically, the MDG module covers MDG 2 (primary education completion), MDG 4 (under-five mortality rate), MDG 5 (maternal mortality rate), and MDG 7 (access to safe water and improved sanitation). The MDGs are covered in an additional set of functions that link the level of each MDG indicator to a set of determinants. The determinants include the delivery of relevant services (in education, health, and water and sanitation) and other indicators, also allowing for the presence of synergies between MDGs, i.e. the fact that achievements in one MDG can have an impact on other MDGs. In education, the model tracks base-year stocks of students and new entrants through the three cycles. In each year, students will successfully complete their grade, repeat it, or drop out of their cycle. Student performance depends on educational quality (quantity of services per student), household welfare (measured by per-capita household consumption), 3
and level of public infrastructure, wage incentives and health status (approximated by MDG 4). The model includes several links between the MDG module and the rest of the economy. An important link is that the provision of the additional government services needed to reach the MDGs requires additional resources capital and investment, labour, and intermediate inputs that are therefore unavailable to the rest of the economy. Increased ODA may lead to exchange-rate appreciation with economy-wide repercussions, including consumers benefiting from lower prices of imports and a loss of competitiveness for producers of tradable goods (exporters or producers of import substitutes). At the same time, the pursuit of the MDGs generates additional resources for instance, it tends to improve the average educational level of the labour force. The performance of the rest of the economy will also influence the ease with which various MDGs can be achieved. Higher private incomes provide additional resources that enable households to draw more benefit from government health and education programmes. More rapid growth raises government revenues, strengthening the ability of governments to finance and operate efficient social services. The core data source for MAMS model calibration is the Social Accounting Matrix (SAM) 2005 for Bangladesh (Dorosh and Thurlow, 2008). The SAM specifies key production sectors along with disaggregated accounts for social services. Since our primary focus is on government policies as these affect achievement of the MDGs, the SAM is restructured in such a way that we aggregate the rest of the economy into five activities. These are agriculture, industry, services, infrastructure and other government expenditure. The MDG-relevant sectors are water and sanitation, health and education, bearing in mind that health services and education at the primary, secondary and tertiary level are provided by both the public and private sectors. Each of these sectors/services has direct link to the labour market, which is also divided according to primary, secondary and tertiary skill levels. The growth in the labour force will partly depend on the success of the education sector. There are three types of institutions: households, the government and the rest of the world, with households separated by urban and rural. Each institution has a current and a capital account linked to investment accounts and the capital accounts of other institutions. 3. Achieving the MDGs by 2021 4
Achieving a set of social development targets is dependent not only on how much is invested in various sectors but also on economic growth. This implies that policies such as openness to trade and a business-friendly regulatory regime are also important. Increased trade, remittances and foreign direct investment (FDI) inflows are likely to have a positive impact on growth and revenue mobilisation and hence affect performance in achieving the MDGs. In this section we present two sets of scenarios. The first presents a baselinescenario, four financing scenarios and two public spending re-allocation scenarios. The financing options available to the government are to increase taxes, or to increase domestic and/or foreign borrowing or grant aid. The public spending re-allocation scenarios should be seen as an alternative strategy to achieve the MDGs. Comparing the results from the baseline scenario to the alternative scenarios makes it possible to say something about the economywide impact of the latter. The second set of scenarios analyses productivity and external shocks, such as a change in world market prices, a change in remittance flows and accelerated growth in FDI inflows, and how they affect MDG achievement. In our final scenarios we discuss the impact of a combined package of external shocks. 3.1 Baseline and financing scenarios A baseline scenario (base) has been developed for the period 2005 2021, which can be characterised as a fiscal-conservative scenario. A series of assumptions were retained to simulate this scenario: An annual growth rate of 6% for real GDP between 2005 and 2021. An annual population growth rate of close to 1% between 2005 and 2021 (source: UN population projections). The small country assumption: world prices of exports and imports are exogenous and assumed to be constant with respect to the model s numéraire, the consumer price index in 2005. FDI is constant as a share of GDP. ODA declines from 1% of GDP in 2005 to 0.4% in 2021, reflecting actual trends in (grant) aid disbursements. External debt declines as a share of GDP from 27% in 2005 to 24% in 2021. The domestic debt ratio falls from 16% of GDP in 2005 to 13% in 2021. Public primary spending (consumption, investment, transfers to households and interest payments) is in nominal terms averaging around 16% of GDP and public investment is on average 6% of GDP over the period. Tax revenue increases from 9% of GDP in 2005 to around 11% in 2021. The deficit is financed by foreign and domestic borrowing, but since the deficit is lower than GDP growth the debt ratio declines over time. Although we have tried to mimic some recent macro trends the baseline scenario will not be exactly the same as actual developments. This would require a more detailed calibration of the model, which is beyond the scope of this exercise. However, our model-predicted targets 5
are not that far from actual performance (Table 2). In our baseline scenario the MDG poverty target is likely to be achieved before 2015. With regard to primary education we estimate that the net primary completion rate could go up to 85.4% in 2021 in the baseline scenario, yet short of the universal 100% target. It should be noted that we use the primary completion rate as the target, which is more ambitious than enrolment rates. Regarding the health-related MDGs, both MDG 4 and MDG 5 will be achieved before 2021. The proportion of the population with access to water and sanitation will almost reach the targets. To summarise, in our baseline scenario all MDGs will be achievable before 2021, except the education target. Recall also that the baseline is what we would call a fiscalconservative scenario in which public spending is held constant (as a share of GDP) and debt ratios are slightly falling. A question is then how much additional finance would be needed to achieve the education target by 2021? Table 3 summarises the fiscal developments between the initial year and the final year (2021). Table 2: Financing and re-allocation scenarios 2005 2010 2015 2021 Target Base scenario National Poverty headcount (%) 40.0 34.2 28.5 23.2 29.5 Primary education completion rate (%) 39.9 57.0 72.8 85.3 100.0 Under-5 mortality (per 1,000 children) 120.0 81.9 57.9 42.1 48.7 Maternal mortality (per 100,000 live births) 250.0 197.3 159.3 130.5 143.0 Access to water (%) 61.0 69.4 78.1 88.1 89.5 Access to sanitation (%) 43.0 49.7 57.2 67.8 69.5 Tax-financed scenario (mdg 2-tax) National Poverty headcount (%) 40.0 34.2 28.9 23.8 29.5 Primary education completion rate (%) 39.9 74.2 93.9 99.4 100.0 Under-5 mortality (per 1,000 children) 120.0 82.3 59.1 43.3 48.7 Maternal mortality (per 100,000 live births) 250.0 197.9 161.4 132.8 143.0 Access to water (%) 61.0 69.4 77.8 87.7 89.5 Access to sanitation (%) 43.0 49.7 56.9 67.2 69.5 Domestic borrowing scenario (mdg 2-db) National Poverty headcount (%) 40.0 34.2 28.6 23.7 29.5 Primary education completion rate (%) 39.9 74.2 93.9 99.4 100.0 Under-5 mortality (per 1,000 children) 120.0 82.3 59.1 43.9 48.7 Maternal mortality (per 100,000 live births) 250.0 197.9 161.4 133.9 143.0 Access to water (%) 61.0 69.4 77.8 87.4 89.5 Access to sanitation (%) 43.0 49.7 56.9 66.9 69.5 Foreign-borrowing scenario (mdg 2-fb) National Poverty headcount (%) 40.0 34.2 28.5 23.2 29.5 Primary education completion rate (%) 39.9 74.2 93.9 99.4 100.0 Under-5 mortality (per 1,000 children) 120.0 82.1 58.4 42.4 48.7 6
Maternal mortality (per 100,000 live births) 250.0 197.6 160.2 131.2 143.0 Access to water (%) 61.0 69.4 78.0 88.1 89.5 Access to sanitation (%) 43.0 49.7 57.1 67.6 69.5 Foreign grant scenario (mdg 2-ftr) National Poverty headcount (%) 40.0 34.2 28.5 23.2 29.5 Primary education completion rate (%) 39.9 74.2 93.9 99.4 100.0 Under-5 mortality (per 1,000 children) 120.0 82.1 58.4 42.4 48.7 Maternal mortality (per 100,000 live births) 250.0 197.6 160.2 131.2 143.0 Access to water (%) 61.0 69.4 78.0 88.1 89.5 Access to sanitation (%) 43.0 49.7 57.1 67.6 69.5 Public spending re-allocation scenario (human) National Poverty headcount (%) 40.0 34.2 28.5 23.3 29.5 Primary education completion rate (%) 39.9 63.9 83.5 91.9 100.0 Under-5 mortality (per 1,000 children) 120.0 79.1 54.3 39.5 48.7 Maternal mortality (per 10,.000 live births) 250.0 193.1 153.2 125.4 143.0 Access to water (%) 61.0 71.2 82.3 92.5 89.5 Access to sanitation (%) 43.0 51.1 61.2 73.8 69.5 Public spending re-allocation scenario (infra) National Poverty headcount (%) 40.0 34.0 28.2 22.8 29.5 Primary education completion rate (%) 39.9 59.5 77.8 90.6 100.0 Under-5 mortality (per 1,000 children) 120.0 79.9 55.5 40.1 48.7 Maternal mortality (per 100,000 live births) 250.0 194.3 155.3 126.5 143.0 Access to water (%) 61.0 70.0 79.5 89.9 89.5 Access to sanitation (%) 43.0 50.2 58.5 70.1 69.5 Source: Results from scenarios Table 3: Government receipts and spending in final report year (% of nominal GDP) 2005 base MDG 2-ftr MDG 2-tax MDG 2-fb MDG 2-db human infra Direct taxes 2.4 3.4 3.4 4.0 3.4 3.5 3.4 3.4 Import tariffs 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 Other indirect taxes 2.6 4.0 4.0 4.8 4.0 4.0 4.0 4.0 Foreign transfers 1.0 0.4 2.0 0.4 0.4 0.5 0.4 0.4 Factor income 1.1 1.3 1.3 1.3 1.3 1.3 1.2 1.2 Domestic borrowing 3.5 1.3 1.3 1.3 1.3 5.3 1.3 1.3 Foreign borrowing 0.9 1.4 1.3 1.4 3.1 1.4 1.4 1.3 Total 15.6 16.0 17.6 17.4 17.8 20.1 15.9 15.8 Consumption 5.1 5.4 6.4 6.5 6.4 6.5 5.5 4.8 Fixed investment 5.6 6.0 6.6 6.3 6.6 6.7 5.8 6.4 Private transfers 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 Domestic interest payments 1.5 1.3 1.3 1.3 1.3 3.6 1.3 1.2 Foreign interest payments 0.4 0.3 0.3 0.3 0.5 0.3 0.3 0.3 Total 15.6 16.0 17.6 17.4 17.8 20.1 15.9 15.8 In all financing scenarios the expenditure-to-gdp ratio increases compared to the baseline scenario. In the borrowing scenario this implies that external debt increases from 27% of GDP 7
in 2005 to 37% in 2021 (Table 4). A domestic borrowing scenario will increase domestic debt from 16% to 38% of GDP. A tax-financing scenario implies that the tax-to-gdp ratio increases from around 9% of GDP in 2005 to 13% in the final year. Approximately half of the increase comes from higher income taxes while the other half is due to higher indirect taxes such as value-added tax (VAT). The ODA-financed scenario shows that aid needs to increase significantly, reaching 2% of GDP towards the end of the period. The macroeconomic impact would be different as taxation and domestic borrowing tend to lower investments and hence reduce GDP growth compared to the foreignborrowing and ODA-financing scenarios. A tax-financed or domestic-borrowing scenario would lead to lower average growth across the period and hence depress poverty reduction (Table 2). The effect on domestic demand will also depend on who carries the additional tax burden. If indirect taxes have greater impact on low-income groups, then reforms to increase VAT and other indirect taxes may offset the welfare gains the poor receive from greater public spending. On the other hand, a distributional-neutral tax reform combining income and indirect tax reform is likely to benefit poorer households in the long run (Vos et al., 2007). The drawbacks of the foreign-borrowing and aid-financed scenarios, besides increasing the external debt in the borrowing scenario, is that both would lead to a stronger appreciation of the real exchange rate (RER) (which would also be the case in an ODA-financed scenario) compared to the tax- and baseline scenarios. This would negatively affect export growth, which would be reduced from an annual average of 5.8% in the baseline scenario to around 5.2% in the external borrowing and ODA scenario. The commonly discussed problems associated with scaled-up capital inflows are RER 2 appreciation and fiscal sustainability. If RER appreciation prevails for a long period it can lead to the problem of Dutch disease (DD). One of the circumstances for Dutch disease is when large capital inflows (borrowing or ODA) increase government consumption, which leads to increased demand for non-tradable goods (Bourguignon and Sundberg, 2006). Prices for non-tradable goods increase more than for tradable goods, leading to the appreciation of RER. As a result the export competitiveness of the country decreases. To summarise the major differences in the financing scenarios, we note that debt financing leads to a significant increase in the debt ratios. Domestic debt financing also has the drawback of slowing down GDP growth. Accumulated over time this GDP loss is around 2 One way to define RER is the relative price of tradable to non-tradable goods. Government expenditure regarding MDG-related services is seen as non-tradable. Rising costs for non-tradable services will shift relative prices against tradable, thus leading to RER appreciation no matter how the increased expenditure is financed (Vos et al., 2007). 8
two times higher (in net present value) than a tax-financed scenario. 3 In the longer term and assuming reduced dependency on aid, mobilising more tax revenue seems to be the key to finance future development programmes. The tax-to-gdp ratio for Bangladesh has been around 10% in recent years, which is low compared to other LICs. The excessive use of tax holidays, basic design flaws in the tax laws, and weak tax administration are the main reasons behind this low tax intake (IMF, 2008). Thus, a first policy lesson would be to continue deepening tax-reform efforts. If Bangladesh were as efficient as the average LIC, that would imply an additional VAT revenue in the order of 2% of GDP (IMF, 2011). This could be achieved without changing the standard rate, but by broadening the base and improving compliance. Table 4: Macro indicators by simulation (% annual growth from first to final report year) base mdg-ftr mdg-tax mdg-fb mdg-db human infra Consumption - private 5.6 5.6 5.4 5.6 5.4 5.5 5.7 Consumption - government 4.4 5.3 5.4 5.3 5.3 4.5 3.8 Fixed investment - private 8.7 8.6 8.3 8.6 7.2 8.6 8.9 Fixed investment - government 6.4 6.9 6.6 6.9 6.7 6.1 6.9 Exports 5.8 5.2 5.5 5.2 5.4 5.7 6.0 Imports 6.3 6.5 6.1 6.5 6.0 6.3 6.5 GDP at factor cost 6.0 5.9 5.8 5.9 5.6 5.9 6.1 Total factor employment (index) 3.5 3.4 3.4 3.4 3.3 3.4 3.5 Total factor productivity (index) 2.5 2.5 2.4 2.5 2.4 2.5 2.6 Real exchange rate (index) -0.6-0.8-0.6-0.8-0.6-0.6-0.6 Unemployment rate (%) 4.3 4.3 4.3 4.3 4.3 4.3 4.3 Headcount poverty rate (%) 23.2 23.2 23.8 23.2 23.7 23.3 22.8 Gross national savings 28.3 28.8 27.9 27.0 25.2 28.0 28.9 Gross domestic savings 22.1 21.0 21.7 21.0 19.1 21.8 22.7 Foreign government debt 24.1 23.4 24.4 37.0 25.4 24.3 23.6 Domestic government debt 13.4 13.5 13.7 13.5 38.4 13.5 13.2 In our last scenario we have assumed that growth in other government expenditures is reduced by half and invested in the primary education sector (human) and infrastructure investment (infra), respectively. All other public sectors retain their share of GDP. This policy change makes it possible to move closer to achieving the education target in 2021 but at the cost of 3 We sum up for each year the GDP loss for each scenario compared to the baseline scenario and calculate Net Present Value (NPV). 9
depressing the rate of poverty reduction. If we instead target infrastructure investment there is less progress with regard to human development but more in terms of poverty reduction. At the margin, however, the impact of re-allocating public spending in Bangladesh is low. This is explained by the significant progress Bangladesh has already achieved, which means that the unit costs of reaching the most remote population are high. In sum, the finance needed to achieve the MDGs in Bangladesh in 2021 are not overwhelming. A combination of reforms, which include further deepening of tax reforms and re-allocation of public spending, would be important components of such a strategy. Perhaps more critically, considering the global crisis, is whether there are shocks that might have a negative impact on the macroeconomic environment and GDP growth and hence exert a negative effect on achieving the MDGs. In the next section we discuss the impact of external shocks on the achievement of the MDGs up to 2021. In addition, we also discuss the impact of positive shocks on the financing requirements. 3.2 Additional non-financing scenarios In this section we discuss a set of non-financing scenarios where we target MDG 2 (Table 5). We focus our discussion on the tax-financing scenario and compare the revenue-to-gdp ratios that are needed to achieve MDG 2 across the various scenarios. The question we ask is whether additional non-financing shocks could reduce the revenue requirements in order to achieve MDG 2. We analyse the impact of a productivity shocks across the three private non- MDG sectors agriculture, manufacturing and services (tfp-all-mdg2 and tfp-all-fin-mdg2). In the baseline scenario the annual productivity growth rate is 2%, 1.4% and 0.5% in the agriculture, manufacturing and service sectors respectively. The productivity shock applied across all sectors is a 1.5% change in total factor productivity (TFP) compared to the baseline scenario. 4 In the second scenario we assume an additional change of TFP growth of 8% in the financial sector. 5 Remittances have become an important source of external capital inflows to Bangladesh. Remittance inflows represented around 2.6% of GDP in the early 1990s, which had risen to around 8% of GDP in mid-2000 (World Bank, 2012). In the third and fourth 4 TFP growth in the model follows an exogenous trend and an endogenous part that depends on the trade-to- GDP ratio. Thus, it is the exogenous trend we change in our scenarios. 5 The financial sector is included in the service sector. We have assumed that the financial sector has a weight of 1/6, which is approximately the value-added share of the financial sector in the service sector. Thus the overall TFP growth rate in the service sector is 1.05%/60.8% when we assume 5% TFP growth in the financial sector. 10
scenario we look at a 10% reduction (rem1-mdg2) and 10% increase in remittances (rem2- mdg2) to both urban and rural households. In the fifth scenario (fdi-mdg2) we scale up growth of FDI in Bangladesh. We also look at changes in world market prices, both for imports (pwm- 5-mdg2) and exports (pwe-5-mdg2). In the final scenarios we run four combined shock scenarios where we target MDG 2. Combi1-mdg2 is an adverse shock scenario where we have included higher world market prices on imported goods and declining growth in remittances and FDI inflows. The second combined scenario (combi2-mdg2) is a positive shock scenario with a higher world market price for export goods and higher growth in remittances and FDI inflows. In the third combined scenario (combi3-mdg2) we add to the positive shock scenario (combi2-mdg2) TFP growth of 1.5% across all sectors. The final scenario (combi-4-mdg2) is similar except that we assume additional productivity growth in the financial sector. Table 5: Additional scenarios Scenarios Description tfp-all-mdg2 Productivity increase of 1.5% in agriculture sector, industry and service sectors + MDG 2 targeting tfp-all-fin-mdg2 tfp-all-mdg2 + 5% TFP growth in the financial sector + MDG 2 targeting rem1-mdg2 Reduction in remittances to households (annual 10% increase over simulation period) + MDG 2 targeting rem2-mdg2 Increase in remittances to households (annual 10% decrease over simulation period) + MDG 2 targeting fdi-mdg2 Change in FDI inflows (10% annual increase over simulation period) + MDG 2 targeting pwm-5-mdg2 Change in import world market price (5% annual increase over simulation period) + MDG 2 targeting pwe-5-mdg2 Change in export world market price (5% annual increase over simulation period) + MDG 2 targeting combi1-mdg2 Combined adverse shock scenario (remit2+fdi decline (10% annual)+pwm-2) + MDG 2 targeting combi2-mdg2 Combined positive shock scenario (remit1+pwe-2+fdi 10% annual increase) + MDG 2 targeting combi3-mdg2 Combi2 + tfp-all-mdg2 combi4-mdg2 Combi2 + tfp-all-fin-mdg2 As the productivity shocks is a combined scenario of targeting MDG 2 we should compare the results with the tax-financed scenario targeting mdg-2 discussed above. Compared to the tax-financing scenario the productivity shocks leads to slightly higher GDP growth (0.5 percentage units higher), which leads to a small but positive effect on poverty reduction and further progress on the other MDGs (Table 6). The difference between the tfp-all-mdg2 and tfp-all-fin-mdg2 scenarios reveals the impact of additional financial sector TFP growth. Accelerated TFP growth in the financial sector would add another 0.1 percentage unit increase in average GDP growth. 11
In the positive shock scenarios with additional inflows of remittances, higher world market price on exports and accelerated growth in FDIs, MDG achievement improves (compared to the tax-mdg2 scenario). The opposite occurs during negative shocks. The macroeconomic impact varies between a percentage point lower average GDP growth (pwm- 5-mdg2) to a percentage point higher average GDP growth (pwe-5-mdg2) compared to the tax scenario. This implies a different outcome in poverty reduction. A positive terms-of-trade shock (pwe-5-mdg2) lowers the headcount rate to 17% while a negative shock (pwm-5-mdg2) increases poverty to 31.4%, which is above the target. In a similar way changes in remittances affect GDP growth and the targets. Higher remittances lead to a positive change across all targets compared to the tax scenario while a negative shock affects the achievement of the targets negatively. Accelerated FDI inflows have a positive but small impact on MDG achievement. 6 In the positive shock scenarios we also note that resources required to reach MDG 2 will be less than in the tax-financing scenario, the opposite would occur in the negative shock scenarios. Table 6: MDG indicators end year targets and results from scenarios mdg1 mdg2 mdg4 mdg5 mdg7w mdg7s Base 23.2 85.3 42.1 130.5 88.1 67.8 mdg2-tax 23.8 99.4 43.3 132.8 87.7 67.2 pwm-5-mdg2 31.4 99.4 57.6 158.8 82.4 61.3 pwe-5-mdg2 17.0 99.4 34.7 115.4 93.2 75.0 fdi-mdg2 23.8 99.4 43.2 132.7 87.7 67.2 rem1-mdg2 25.5 99.4 44.4 135.0 86.8 66.2 rem2-mdg2 22.4 99.4 42.3 130.8 88.3 67.9 combi1-mdg2 32.0 99.4 40.0 126.3 82.4 61.3 combi2-mdg2 17.4 99.4 40.7 127.8 92.9 74.6 tfp-all-mdg2 22.6 99.4 41.3 128.9 89.1 69.0 tfp-fin-all-mdg2 22.6 99.4 41.3 128.9 89.1 69.0 combi3-mdg2 16.6 99.4 39.5 125.4 94.0 76.4 combi4-mdg2 16.6 99.4 39.5 125.3 94.0 76.4 A preliminary conclusion is that sustained high growth in Bangladesh is necessary in order to achieve the MDGs in 2021. In the turmoil following the global financial crisis export growth slowed down, and remittances could be adversely affected in the future as well as further reductions in ODA (Rahman et al., 2009). This could affect GDP growth performance in Bangladesh and hence make it more difficult to achieve the MDG targets even with an extended timeframe. In our final scenarios we look at two external shocks scenarios where the 6 The impact is small partly due to the low initial value placed on FDIs in the SAM. 12
first one is a negative scenario in the sense that terms of trade deteriorate, export prices decline and world import prices increase, and both FDI flows and remittances decline by an annual rate of 10%. The positive scenario is the opposite, namely that there are improvements in terms of trade and an annual 10% increase in FDI and remittances. In both scenarios we target MDG 2. Our last two scenarios add a positive TFP shock to the previous combined scenarios. We distinguish between uniform TFP growth and a scenario where we assume higher TFP growth in the financial sector. The macroeconomic impact is quite significant, since an adverse scenario would lower GDP growth to an average rate of 4.8% and in the positive scenario the average (annual) GDP growth rate will be around 6.9% (Table A.1). An adverse shock would have a negative impact on the MDGs and the targets regarding poverty reduction and water and sanitation would not be reached (Table 6). A negative shock scenario also implies that public spending needs to be increased in order to achieve MDG 2 (Table A.2), compared to the tax-financing scenario the average spending ratio increases from 17% to 20% of GDP. However, in the positive shock scenario we would again achieve all the MDGs and there would be reductions compared to the tax-financing scenario. In addition, the financing requirements would be 1.7 percentage units (share of GDP) lower compared to the tax-financing scenario. Adding TFP growth to the positive combined scenario leads to accelerated progress in the targets and a further reduction in the resource requirements to achieve MDG 2. In fact, the resource requirements are less compared to the baseline scenario and are close to the current (2005) spending. The impact of additional TFP growth in the financial sector does not imply any significant change compared to the scenario with uniform TFP growth. 4. Conclusions Bangladesh has made significant progress towards achieving the MDGs. The education target seems to be the only one that will not be reached until 2015. The question we address in this paper is whether Bangladesh will be able to achieve MDG 2 within an extended timeframe and whether there are policies beyond additional ODA that would support this process. The financial needs to achieve the MDGs in Bangladesh in 2021 are not overwhelming. We find that full achievement of the MDGs would have led to a GDP loss which is significantly larger in the domestic-financing scenario compared to the tax- scenario. The tax-financing alternative is thus the better option for financing large development programmes. A combination of reforms, which include further deepening of tax reforms and 13
reallocation of public spending towards primary education, would be important components in such strategy. External shocks such as changes in terms of trade, FDI and remittances have potentially strong effects on the macro economy and hence on the MDG targets. Combined, adverse shocks could be detrimental to progress achieved, but on the other hand a combination of favourable shocks would make a significant contribution to further progress towards achieving the MDGs and move the targets beyond what had been aimed for in 2015. In addition, the resource requirements to achieve MDG 2 would further be reduced during positive shocks and policies that would accelerate TFP growth. References Planning Commission (2008) Moving Ahead: National Strategy for Accelerated Poverty Reduction II (FY 2009-11). Dhaka: Planning Commission. Bourguignon, F, Diaz-Bonilla, C. and Lofgren, H. (2008) Aid Service Delivery, and the Millennium Development Goals in an economy-wide Framework. Policy Research Working Paper. Washington, DC: Development Economics Prospects Group, World Bank. Bussolo, M. and Medvedev, D. (2007) Challenges to MDG Achievement in Low Income Countries: Lessons from Ghana and Honduras. Policy Research Working Paper. Washington, DC: Development Economics Prospects Group, World Bank. Dorosh, P. and Thurlow, J. (2008) A 2005 Social Accounting Matrix (SAM) for Bangladesh. Washington, DC: International Food Policy Research Institute (IFPRI). IMF (2011) Revenue Mobilization in Developing Countries. Fiscal Affairs Department. Washington, DC: International Monetary Fund. World Bank (2012) Bangladesh: Towards Accelerated, Inclusive and Sustainable Growth- Opportunities and Challenges. Poverty Reduction and Economic Management Sector Unit, South Asia Region, vol.1. Washington, DC: World Bank. 14
Vos, R., Sánchez, M.V. and Inoue, K. (2007) Constraints to achieving MDGs through domestic resource mobilization. DESA Working Paper No. 36. New York: UN DESA. 15
Table A1: Real macro indicators by simulation (% annual growth from first to final report year) base pwm-2 pwe-2 fdi remit1 remit2 combi1 combi2 Absorption 6.1 3.7 8.5 6.0 5.4 6.4 3.7 8.3 6.4 6.4 8.7 8.7 Consumption - private 5.6 3.1 8.0 5.365 4.804 5.829 3.162 7.754 5.761 5.765 8.143 8.147 Consumption - government 4.4 5.4 5.5 5.4 5.4 5.3 5.4 5.5 5.4 5.4 5.5 5.5 Fixed investment - private 8.7 5.3 11.3 8.4 7.4 9.0 4.9 11.1 8.9 8.9 11.7 11.7 Fixed investment - government 6.4 5.2 8.3 6.6 6.3 6.7 5.1 8.2 6.9 6.9 8.5 8.5 Exports 5.8 3.7 8.2 5.5 6.1 4.8 3.1 8.5 6.0 6.0 9.0 9.1 Imports 6.3-0.5 13.5 6.1 5.1 7.1-0.6 13.1 6.6 6.6 13.6 13.6 GDP at factor cost 6.0 4.9 6.9 5.8 5.6 6.0 4.8 6.9 6.2 6.3 7.3 7.3 Total factor employment (index) 3.5 3.0 3.9 3.4 3.3 3.5 2.9 3.8 3.5 3.5 3.9 3.9 Total factor productivity (index) 2.5 1.9 3.1 2.4 2.3 2.5 1.9 3.0 2.8 2.8 3.4 3.4 Real exchange rate (index) -0.6-1.0-4.9-0.6-0.2-1.1 4.0-4.7-0.6-0.6-4.8-4.8 Unemployment rate (%) 4.3 4.3 4.3 4.3 4.3 4.3 4.3 4.3 4.3 4.3 4.3 4.3 Headcount poverty rate (%) 23.2 31.4 17.0 23.8 25.5 22.4 32.0 17.4 22.6 22.6 16.6 16.6 tfp-allmdg2 tfpfinallmdg2 com-tfpallmdg2 com-tfpall-finmdg2
Table A.2: Government receipts and spending in first report year and by simulation in final report year (% of nominal GDP) 2005 base pwm-2 pwe-2 fdi remit1 remit2 combi1 combi2 Direct taxes 2.4 3.4 4.4 4.1 4.0 4.0 4.0 3.5 4.0 3.9 3.9 3.9 3.9 Import tariffs 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 Other indirect taxes 2.6 4.0 6.5 4.1 4.8 4.9 4.6 5.0 4.1 4.6 4.6 4.0 4.0 Foreign transfers 1.0 0.4 0.5 0.2 0.4 0.5 0.4 1.2 0.2 0.4 0.4 0.2 0.2 Factor income 1.1 1.3 1.2 1.4 1.3 1.3 1.3 1.2 1.4 1.4 1.4 1.5 1.5 Domestic borrowing 3.5 1.3 1.3 1.4 1.3 1.4 1.3 1.4 1.4 1.3 1.3 1.4 1.4 Foreign borrowing 0.9 1.4 1.4 0.5 1.4 1.5 1.2 3.8 0.5 1.3 1.3 0.5 0.5 Total 15.6 16.0 19.5 15.7 17.4 17.8 17.1 20.2 15.7 17.1 17.1 15.5 15.5 Consumption 5.1 5.4 7.4 5.7 6.5 6.7 6.3 7.5 5.7 6.3 6.3 5.6 5.6 Fixed investment 5.6 6.0 7.0 5.9 6.3 6.4 6.3 7.1 5.9 6.2 6.2 5.8 5.8 Private transfers 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 Domestic interest payments 1.5 1.3 1.7 1.0 1.3 1.3 1.2 1.7 1.0 1.2 1.2 0.9 0.9 Foreign interest payments 0.4 0.3 0.4 0.1 0.3 0.4 0.3 0.9 0.1 0.3 0.3 0.1 0.1 Total 15.6 16.0 19.5 15.7 17.4 17.8 17.1 20.2 15.7 17.1 17.1 15.5 15.5 tfp-allmdg2 tfpfinallmdg2 comtfp-allmdg2 comtfp-allfinmdg2 1