Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Choosing the Balance between Human Development and Infrastructure Spending in Malawi Carolina Diaz-Bonilla DECPG, World Bank Malawi, June 20, 2007 Joint work with: Hans Lofgren, Pavel Lukyantsau, and Antonio Nucifora Introduction • The Malawi Growth and Development Strategy (MGDS) marks a policy shift towards economic growth and infrastructure development, and away from investments in human development (HD): – Belief that resource allocations in previous strategies were tilted towards general administration and social services at the expense of infrastructure services; – MDGS thus emphasizes the need to adjust these allocations. • Simulation analysis will: – Create a base scenario in line with the GoM’s macro program – Explore the consequences of changing the balance of expenditures between infrastructure and HD sectors. Introduction (cont) • Use MAMS: Maquette for MDG Simulations. – Economywide simulation model to analyze development strategies. – For Malawi: not targeting MDGs, but monitor them. • Rationale for economywide approach: – Economic effects at different levels: macro, sectors, labor market. – Sector-by-sector approach (partial equilibrium) analysis is not sufficient on its own • Results provide an indication of the broad direction of changes in the economy and the likely trade-offs. Outline • • • • Model Structure Database Simulations: Assumptions Simulations: Results Model Structure • Standard dynamic recursive computable general equilibrium (CGE) model AND • Additional module that links specific MDG or poverty-related interventions to poverty and other MDG achievements. • Requires relatively detailed treatment of government activities to make the link possible: – Malawi: 9 government activities. Model Structure (cont) • Some features of open-economy, dynamicrecursive CGE models: – Optimizing producers and consumers. – Supply-demand balance in factor and commodity markets (with flexible prices clearing most markets) – Expenditures = receipts for the three macro balances: government, savings-investment, rest of world – Imperfect transformation/substitutability in trade. – Updating of factor and population stocks and TFP; endogenous/exogenous mix. Table: Model Disaggregation Activities/Commodities (12) Non-government (3) Agriculture Industry Private Services Government (9) Education primary Education secondary Education tertiary Health Government agriculture Irrigation Water & sanitation Public infrastructure Other government Factors (14) Labor with less than completed secondary education Labor with completed secondary education Labor with completed tertiary education Capital (10) - one stock for each model gov activity Land Institutions (3) Household Government Rest of the World Model Structure (cont) • MAMS treatment of government spending: – Government purchases public services, disaggregated by function. – Government services produced using labor, intermediate inputs, and capital. – Provision of education, health, and water-sanitation services contribute directly to MDGs and influence factor productivity. – HD (education) influences size and composition of labor force. – Sources of government income: taxes, domestic borrowing, foreign borrowing, and foreign grants Model Structure (cont) • Education: – Disaggregated by cycle. – Endogenous student behavior: • Shares of relevant totals that enter first grade; • In a grade: shares that pass, continue, repeat, or drop out within or between cycles. – Within each cycle and between cycles, student behavior determined by logistic-CE structure (for arguments, see Table) – Enrollment in each cycle = old students that continue/repeat + graduates from earlier cycle + new entrants to school system. Model Structure (cont) • Labor (by level of education) defined as the sum of: – Remaining stocks from last year – Graduates and dropouts who enter the labor force – Net entrants from outside the school system Table: Determinants of MDG achievements Other Determinants MDG Per-capita real service delivery Poverty Rate Net primary completion Under-5 mortality rate Maternal mortality rate Access to safe water Access to basic sanitation Per-capita Public household infrastructure consumption Wage Incentives Other MDGs X 4 X X X X X X X 7a,7b X X X 7a,7b X X X X X X Database • Social Accounting Matrix (SAM): fiscal year 2004 • Macro SAM: – National Accounts data averaged over calendar years 2003 and 2004 (SIMA, World Bank) – Balance of Payment information for last two quarters of 2003 and first two quarters of 2004 (IMF data), and – Government Budget for fiscal year 2004. • Micro SAM: created from macro SAM above and 1998 Malawi micro SAM from IFPRI • Government sectors: – Disaggregated using recurrent and development expenditure information from several Malawi Ministries. Figure. SAM Structure Expenditures Receipts Activities Market sales Domestic Institutions Home consumption Intermediate Commodities inputs Transactions costs Final market demands Factors Domestic Institutions Activities Factors Value added Taxes Rest of World Totals Commodities Tariffs, Taxes Income, Taxes Rest of World Activity income Exports Commodity demand Transfers Factor income Transfers, Transfers, Taxes, Savings Savings Commodity supply Institution income Foreign exchange outflow Imports Activity spending Totals Factor spending Institution spending Foreign exchange inflow Database (cont) • Also need more detailed data related to different MDGs in the labor market; ex: – – – – Levels of service delivery to meet MDGs. Stocks of students at different educational levels. Stocks of labor by educational level. Student behavioral patterns (ex: graduation rates) • Elasticities in production, trade, consumption, and in the different MDG functions. GDP Growth in MAMS • GDP growth is determined by: – growth in factor employment – growth in productivity or efficiency of factor use (TFP) GDP Growth in MAMS • Factor employment – Labor: • Stock growth depends on functioning of education sector • Un/underemployment responds to wage pressures. – Capital: • Government capital: grows in parallel with increases in government services • Private capital: investment ( stock growth) driven by funding = [private savings] + [FDI] – [gov. borrowing] – Land: • Stock growth is exogenous. GDP Growth in MAMS (cont.) • TFP – Endogenous part depends on economic openness and growth in government infrastructure stocks. – Exogenous part captures what is not explained in model (institutions, new technologies, ….) Quality of Expenditures • “Quality” is implicitly assumed constant: i.e. efficiency in the use of expenditures does not change • The degree of efficiency is determined by the assumptions in the model (elasticities) • Simulations of the impact of improvements in efficiency can be carried out by: – Changing elasticities – Decreasing the share of “Other Government Services”, which is assumed as ‘non-productive’ expenditure in MAMS Simulations • BASE: projection of economic program pursued by current government, which is underpinned by the IMF PRGF. • Trade-off simulations: – SIM-INFRA: reallocation of public expenditure toward infrastructure, agricultural, and irrigation services (less HD) – SIM-SOCIAL: reallocation of public expenditure toward human development (education, health, and water-sanitation) services (less infra). • SIM-HISTORICAL • Robustness simulation: Simulations under lower GDP growth assumption. BASE Simulation • Based on the implementation of the economic program pursued by the current government. • Projects into the future the consequences of continuing current policies and growth rates GDP Population Growth Assumptions 6% 1.95% --> 2008 1.4-1.7% --> 2015 • Note: Assumption that adequate reforms adopted and Malawi is not hit by exogenous shocks. BASE Simulation (cont) • All sources of financing for government are exogenous and follow projections of GoM economic program. Growth Assumptions Foreign Borrowing 3% Foreign Grants 5% Direct and indirect taxes Domestic Borrowing Fixed share of GDP 0% Note: Complete foreign debt relief occurs in 2007 BASE Simulation (cont) • Endogenous government expenditure; clears fiscal account. • No changes in the current composition of expenditures; shares across sectors are maintained constant (as in 2003/04 fiscal year). • Special functioning of education sector: – government expenditure set to grow at a rate such that spending per enrolled student (“educational quality”) remains constant between 2004 and 2015. BASE Simulation (cont) • Government infrastructure capital stock (roads) has an effect on the productivity of other sectors in the economy: – Elasticity of TFP generated such that, ceteris paribus, the sum of the GDP changes across all activities linked to the public infrastructure capital stock per additional Kwacha spent on investments in this capital stock is equal to 0.2 (an implicit rate of return on public capital) • Agriculture activity also affected in all simulations by the productivity in both the government agriculture and irrigation sectors. – Assumption linked to GoM strategy assumption that Malawi would increase its efficiency to help with macroeconomic stability. • Elasticity of factor productivity for labor with respect to health: – Linked to under-5 and maternal mortality rates relative to base year. BASE: Some Results (annual growth rates) 2004 Household consumption Government consumption (total) Government investment Private investment Exports Imports Real exchange rate - Kwacha per Foreign Curr. Unit GDP at factor cost Base Values Units growth 178.7 30.8 21.0 6.3 49.9 98.2 100.0 bn Kwacha 4.9 5.9 5.1 8.2 7.6 5.1 0.02 167.3 bn Kwacha bn Kwacha bn Kwacha bn Kwacha bn Kwacha indexed to 100 bn Kwacha 6.0 BASE: Some Results (annual growth rates) 2004 Base Values Units growth Wage of labor with less than secondary education** Wage of labor with secondary education Wage of labor with tertiary education 14584.8 69027.4 167075.8 Kwacha Kwacha Kwacha MDG 1: headcount poverty rate MDG 2: primary (1st cycle) net completion rate*** MDG 4: under-5 mortality rate (share of live births) MDG 5: maternal mortality rate (share of live births) MDG 7a: acess to safe drinking water MDG 7b:acess to safe sanitation 52.4 8.0 133.0 960.0 66.1 63.7 % % per 1000 per 100000 % % 4.0 6.3 7.6 2015 value 31.4 15.4 108.1 499.0 67.9 64.9 Trade-Off Simulations • Public expenditures in infrastructure vs. HD sectors. • SIM-INFRA simulation: – Growth in spending on infrastructure sectors is exogenously set higher by 1.5 times the growth rate in BASE. – Implies that expenditure growth rates for the HD sectors are endogenously scaled down to stay within fiscal space limits. – Fiscal space defined by foreign inflows and domestic revenue rules that are unchanged across the simulations. • SIM-SOCIAL simulation: – Growth in spending on infrastructure sectors is exogenously set lower by 1.5 times the growth rate in BASE. – Implies that expenditure growth rates for the HD sectors are endogenously scaled up to stay within fiscal space limits. • In both, public expenditure on the remaining sector (“other gov services”) grows at the same rate as in BASE. Infra vs HD: Some Results (annual growth rates) 2004 Government consumption (total) Total Education Primary Education services Health services Irrigation services Gov agriculture services Water-sanitation services Public infrastructure services Other services Government investment Values Units 30.8 7.5 5.1 3.6 0.2 1.3 0.2 2.2 15.9 21.0 bn K bn K bn K bn K bn K bn K bn K bn K bn K bn K SIMULATIONS Base Sim-Infra Sim-HD Annual growth 2005-2015 (%) 5.9 8.6 2.2 4.8 4.8 4.8 4.8 4.8 4.8 5.1 5.8 7.2 0.7 3.3 9.0 9.0 3.3 9.0 4.8 5.6 5.8 9.5 3.0 5.6 -0.1 -0.1 5.6 -0.1 4.8 4.6 Infra vs HD: Some Results (annual growth rates) 2004 Household consumption Government consumption (total) Government investment Private investment Exports Imports Real exchange rate - Kwacha per Foreign Curr. Unit GDP at factor cost Values Units 178.7 30.8 21.0 6.3 49.9 98.2 100.0 bn K 167.3 bn K bn K bn K bn K bn K indexed to 100 bn K SIMULATIONS Base Sim-Infra Sim-HD Annual grw 2005-2015 (%) 4.9 5.9 5.1 8.2 7.6 5.1 0.0 5.2 5.8 5.6 8.4 8.3 5.5 -0.2 4.6 5.8 4.6 7.9 6.7 4.6 0.2 6.0 6.3 5.6 Infra vs HD: Some Results (annual growth rates) 2004 Values MDG 1: headcount poverty rate MDG 2: primary (1st cycle) net completion rate*** MDG 4: under-5 mortality rate (shr of live births) MDG 5: maternal mortality rate (shr of live births) MDG 7a: acess to safe drinking water MDG 7b:acess to safe sanitation Units Simulations Base Sim-Infra Sim-HD 2015 Values 52.4 % 31.4 8.0 % 15.4 133.0 per 1000 108.1 960.0 per 100000 499.0 66.1 % 67.9 63.7 % 64.9 29.6 10.8 113.4 587.0 67.4 64.7 33.9 18.5 106.4 472.6 68.1 64.8 MDG 1: Headcount Poverty Rate 55 50 45 % 40 base-prgf 35 sim-infra sim-social 30 25 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 MDG 2: Net Primary School Completion Rate (%) 20 18 base-prgf 16 sim-infra 14 sim-social 12 10 8 6 4 2 0 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Real GDP at Factor Cost (2003/04 bn Kwacha) 350 base-prgf sim-infra 300 sim-social 250 200 150 100 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Trade-Off Simulations (cont) • Focus on infrastructure results in an increase in the growth rate of real GDP at factor cost from 6% to 6.3% per year. • Faster growth rate, exports, investments and (monetary) poverty reduction, but slower progress in other human development indicators. • Focus on social sectors leads to a slower economic growth rate and slower poverty reduction, but more rapid progress on human development indicators. • GDP decreases to 5.6% per year SIM-HISTORICAL Simulation • Analyzes the expected economywide outcomes of continuing with pre-2004 trends and unchanged policies. • Results: scenario is unsustainable – High amount of government expenditure (holding constant the trends in net foreign borrowing, foreign grants) results in high levels of domestic debt and interest payments that are unsustainable. – Household per capita consumption plummets, and therefore poverty rises rapidly. Robustness Simulation Lower Growth • Repeat BASE, SIM-INFRA, and SIM-SOCIAL simulations under lower growth assumptions. – BASE 4% rather than 6% • Lower growth in all macro aggregates. • Smaller budget for government => lower government expenditure per sector. • Improvements in poverty and all other HD indices are more modest. Summary • Sound macroeconomic policies are critical for both growth and human development indicators. • Higher infrastructure spending leads to faster GDP growth (and reductions in monetary poverty), but at the expense of slower improvements in HD indicators • Higher HD sector spending leads to faster growth in health, education, and other HD indicators, but at the cost of a slower growth rate and poverty reduction. • Note: we assume that “quality” of expenditures and investments does not change. Thank You All analysis has limitations. If we limited presentations to analysis without limitations, then we would live in a world without presentations.