MAMS: A Tool for Public Finance and Development Strategy Analysis

1. MAMS: A Tool for Public Finance and Development Strategy Analysis Hans Lofgren, DECPG Presentation for the Public Finance Analysis and Management Core Course, PREM Learning Week, April 23, 2008

2. Introduction • Presentation prepared with Carolina Diaz-Bonilla, LCSPP. • MAMS • Maquette for MDG Simulations • Initial motivation: need to address country-level MDG strategies: How can government policies, with foreign aid providing part of the financing, be designed for achievement of the MDGs? • Evolved into a general framework for country-level, medium-to-long-run development policy analysis, with an emphasis on fiscal issues and MDG indicators. • Different versions (differing in data needs and issues they can address) ranging from aggregated macro to disaggregated MDG.

3. Introduction • Applications in many countries: • 18 in Latin America and the Caribbean • 9 in Sub-Saharan Africa • 5 in MENA region • Used in the context World Bank country analysis (including Country Economic Memoranda, Public Expenditure Reviews, Poverty Assessments) as well as in joint work with the UN.

4. Introduction • Outline: • Issues in MDG strategy analysis • Model structure • Data • Examples of scenarios • Uganda case study • Uganda: base scenario and results • Uganda: policy scenarios and results • Uganda: conclusions • Concluding Remarks

5. 1. Issues in MDG strategy analysis • A framework for analysis of MDG strategies should consider the following factors: • Synergies between different MDGs • Role of non-government service providers • Demand-side conditions (incentives, infrastructure, incomes) • Role of economic growth • Macro consequences of increased government spending under different financing scenarios • Diminishing marginal returns (in terms of MDG indicators) to services and other determinants • Role of efficiency and input prices (e.g. wages) in determining unit service costs

6. 2. Model Structure • MAMS may be described as an extended, dynamic-recursive computable general equilibrium (CGE) model designed for MDG analysis. • MAMS is complementary to and draws extensively on sector and econometric research on MDGs. • Motivation behind the design of MAMS: • An economywide, flexible-price model is required for development strategy analysis. • Standard CGE models provide a good starting point. • But Standard CGE approach must be complemented by a satisfactory representation of 'social sectors'.

7. 2. Model Structure General Features • Many features are familiar from other CGE models: • Computable  solvable numerically • General  economy-wide • Equilibrium  • optimizing agents have found their best solutions subject to their budget constraints • quantities demanded = quantities supplied in factor and commodity markets • macroeconomic balance • Dynamic-recursive  the solution in any time period depends on current and past periods, not the future. • A “real” model: only relative prices matter; no modeling of inflation or the monetary sector.

8. 2. Model Structure Figure. Aggregate payments in MAMS Factor Domestic Private Savings Markets Factor Wages Costs & Rents Gov. Savings Taxes Intermediate Input Cost Households Government Sav./Inv. Activities Transfers Private Government Consumption Investment Com’ty Consumption Demand Markets Domestic Sales Foreign Transfers Imports Exports Foreign Savings Rest of the World

9. 2. Model Structure MDGs • Extended to capture the generation of MDG outcomes. • MAMS covers MDGs 1 (poverty), 2 (primary school completion), 4 (under-five mortality rate), 5 (maternal mortality rate), 7a (water access), and 7b (sanitation access). • The main originality of MAMS compared to standard CGE models is the inclusion of (MDG-related) social services and their impact on the rest of the economy. • Social services may be produced by the government and the private sector.

10. 2. Model Structure Government • Government services are produced using labor, capital, and intermediates (fixed coefficients for capital, intermediate inputs, and aggregate labor; flexible coefficients for disaggregated labor). • Government spending is split into • Recurrent: consumption, transfers, interest • Capital (investment) • Government demand (consumption and investment) is classified by function: social services (education, health, water-sanitation), infrastructure and “other government”. • Government spending is financed by taxes, domestic borrowing, foreign borrowing, and foreign grants. • Model tracks government domestic and foreign debt stocks (including foreign debt relief) and related interest payments. • Simplified versions of equations for government recurrent receipts, recurrent expenditure, savings, and investment expenditure…..

11. Government recurrent revenue

12. Government recurrent expenditure

13. Government savings

14. Government investment value

15. 2. Model Structure MDG “production” • Together with other determinants, government social services determine the "production" of MDGs. • MDGs are modeled as being “produced” by a combination of factors or determinants (table following) using a (reduced) functional form that permits: • Imposition of limits (maximum or minimum) given by logic or country experiences • Replication of base-year values and elasticities • Calibration of a reference time path for achieving MDGs • Diminishing marginal returns to the inputs • Two-level function: • Constant-elasticity function at the bottom: Z = f(X) • Logistic function at the top: MDG = g(Z)

16. 2. Model Structure Determinants of MDG outcomes

17. 2. Model Structure Logistic function

18. 2. Model Structure Education • Service measured per student in each teaching cycle (primary, secondary, tertiary). • Model tracks evolution of enrollment in each cycle • Educational outcomes as functions of a set of determinants: for each cycle, rates of entry, pass, repeat, and drop out; between cycles, share that continues • MDG 2 (net primary completion rate) computed as product of 1st grade entry rate and primary cycle pass rates for the relevant series of years.

19. 2. Model Structure Dynamics • Updating of stocks of • factors (endogenous for different types of labor and capital, exogenous for other factors); and • debt (domestic and foreign; both endogenous) • TFP (Total Factor Productivity) • Endogenous part depends on economic openness and growth in government infrastructure stocks. • Exogenous part captures what is not explained in model (institutions, new technologies, ….) • GDP growth is determined by: • growth in economywide TFP (influenced by labor-force composition) • growth in factor employment (mostly endogenous)

20. 2. Model Structure Performance indicators • Key performance indicators include the evolution of: • Private and government consumption and investment, exports, imports, value-added, taxes; all indicators may be national totals or disaggregated • Domestic and foreign debt stocks • MDG indicators (poverty, non-poverty MDGs) • Educational composition of labor force • MAMS can generate poverty and inequality indicators using standard approaches (aggregate poverty elasticity; representative household; microsimulation).

21. 2. Model Structure Macro Closures • Mechanisms for clearing (assuring that receipts = outlays) of: • Balance of Payments – real exchange rate • Savings-Investment Balance – private investment • Government budget → next slide

22. 2. Model Structure Government Closures • The selection of variable clearing the government budget is an important part of many counterfactual scenarios. Common options: • Domestic tax rates • Foreign grants • Domestic borrowing • Scaling of government spending item(s)

23. 2. Model Structure Market-clearing variables for factors and commodities • Factors. Two alternatives: • exogenous unemployment: wage clears • endogenous unemployment. Two regimes: • unemployment above minimum rate: unemployment rate clears (influencing reservation and market wage) • unemployment at minimum rate (= full employment): wage clears • Commodities. Three categories: • Domestic output sold at home: prices • Exports: quantities demanded (or international demand function) • Imports: quantities supplied

24. 2. Model Structure Factor market with endogenous unemployment

25. 2. Model Structure Steps in Simulation Analysis • Run base (business-as-usual) scenario: • Purpose: a plausible benchmark for comparisons • GDP growth calibrated to trend from last 5-15 years; • Balanced and sustainable evolution of macro flows and stocks; many of these items may have unchanged GDP shares. • Run alternative (counter-factual) scenarios. For example: • Change one or more parameters (policy tools or parameters beyond government control, e.g. aid, world prices, productivity) • Fix an indicator that represents a policy target (ex: a health MDG); flex a policy tool (ex: government health services). • Analyze and validate: • explain results for individual scenarios and across scenarios; • if needed, adjust data, model, or simulation design.

26. 2. Model Structure Digression: MAMS vs. RMSM-X

27. 3. Data • Core needs are similar to other CGE models: • Social Accounting Matrix (SAM); stocks of factors, population, and debts (foreign and domestic); elasticities in trade, production, and consumption; • They depend on the (flexible) disaggregation of the model. • The SAM is used to define most of these parameters.

28. 3. Data Data for MDG version • Requirements specific to MDG version: • In SAM: government consumption and investment disaggregated by MDG-related functions; labor disaggregated by educational achievement; • Education parameters: stocks of students by educational cycle; student behavioral patterns (ex: rates of passing, repetition, dropout); population data with some disaggregation by age; • MDG data: indicators for base-year and 1990; elasticities; calibration scenario for achieving each MDG.

29. 3. Data Data sources • Database draws on a wide range of sources. • Likely key sources: • Standard national data publications (national accounts, government budget, balance of payments) • World Development Indicators (WDI) (labor stocks; value-added in agr/ind/ser; population) • Public Expenditure Reviews and Country Economic Memoranda • Sectoral MDG studies (health, education, water-sanitation, public infrastructure) • Existing SAMs and input-output tables • Surveys (household, labor, DHS)

30. 4. Examples of Scenarios • Questions commonly addressed by non-BASE scenarios: What happens if the government … • expands services sufficiently to reach the MDGs with additional financing provided by (a) foreign grants; (b) domestic taxes; (c) domestic borrowing? • contracts in one area (e.g. human development or other government) and expands in another (e.g. infrastructure) with unchanged aid and domestic policies? • in one or more areas, expands services sufficiently to make use of additional financing from a, b, or c (as defined under 1)? • becomes more/less productive, adjusting one or more types of spending or financing in response?

31. 4. Examples of Scenarios Other Scenarios • Many other scenarios are possible: • changes in tax policy (VAT, tariffs, direct taxes) • alternative patterns of productivity growth in non-government activities • changes in world export and/or import prices • foreign debt relief • changes in population growth and age structure (with or without extra government spending on family planning) • requirements to reach GDP growth target: national savings, FDI, aid, TFP

32. 5. Uganda Case Study • Context: Input into World Bank “Country Economic Memorandum” and “Public Expenditure Review” addressing the long-run growth and poverty reduction impacts of alternative expenditure patterns and fiscal financing scenarios. • The MDG version of MAMS was applied to a Ugandan database; micro-simulation used for poverty-inequality analysis.

33. 5. Uganda case study Uganda SAM for MAMS Macro Version[Unit: % of GDP at market prices; Year: FY2003]

34. 6. Uganda: base scenario and results Assumptions • Simulations run for FY2003-2020. • 6.1% GDP growth – close to the actual rate for 1990-2003; • TFP growth (reaching 1.4% per year) adjusted as needed. • Government consumption growth: • Primary education: sufficient to gradually raise services per student by 80% • Secondary and tertiary education: sufficient to maintain unchanged services per student • Other government functions: 6.2%

35. 6. Uganda: base scenario and results More Assumptions • Taxation: • increase from 11% to 14% of GDP via increased domestic rates; • no change in tariff rates (and the tariff GDP share) • Government borrowing: • Domestic: around 1% of GDP; growing at close to 6.2% per year • Foreign: set to ensure that the base-year foreign debt – GDP ratio (71%) is unchanged except for a minor decline reflecting foreign debt relief. • Grant aid: • grows at the same pace as GDP. • for the full period 63% of the aid is in grant form with the rest being borrowed.

36. 6. Uganda: base scenario and results Table 1a. BASE Results

37. 6. Uganda: base scenario and results Table 1b. BASE Results

38. 6. Uganda: base scenario and results BASE Results – Table 1a • Most national account aggregates and parts of government consumption grow at rates of 6-7%. • Primary education: Moderate growth in government demand (5%) due to demography and a gradual decline to zero for out-of-cohort entrants to first grade. • Drastic increase in the net primary completion rate (MDG 2), from 16% in 2003 to 76% in 2020. • Secondary and tertiary education: Given very rapid enrollment growth (8-9% for both levels), and the policy of maintaining unchanged resources per student, government demand grows rapidly, at 13-14%.

39. 6. Uganda: base scenario and results BASE Results – Table 1b • Household consumption per capita: • aggregate growth at 2% • moderate pro-poor and pro-rural bias (reflecting differences in endowments) • MDG indicators: • substantial improvements for MDGs 1, 2, and 4; smaller improvement for 7a; • except for MDG 1, the 2015 targets are not reached.

40. 6. Uganda: base scenario and results Other selected BASE Results • Factors: • switch in labor composition to higher education • decline in labor unemployment • especially rapid rent (wage) growth for land • Real GDP growth for disaggregated production activities • 5-7% per year except for post-primary education • very similar for total private vs. total government GDP • in private sector: transportation services > other private services > industry > agriculture • Annual TFP growth is highest for transportation services followed by agriculture (due to positive influence of government investments in roads and agriculture)

41. 7. Uganda: policy scenarios and results • Scenarios address the consequences of • alternative allocations of government spending across different functions, including HD, infrastructure and non-productive activities; • increased government efficiency; • scaled-up programs with and without additional foreign aid. Note: • foreign aid = foreign borrowing + foreign transfers (grants) received by the government; • any increase in foreign aid is entirely in grant form

42. 7. Uganda: policy scenarios and results Table 1. Policy scenarios -- description

43. 7. Uganda: policy scenarios and results Table 2a. Results for policy scenarios

44. 7. Uganda: policy scenarios and results Table 2b. Results for policy scenarios

45. 7. Uganda: policy scenarios and results Results for INFCUT • Effects are quite limited given the fact that total budget spending on infrastructure (agriculture and roads) is only around 2% of GDP; spending on MDG-related HD is >5% of GDP. • Growth rates for MDG-related HD spending increase by 0.5-0.8% per year. • Real GDP growth decreases by 0.4% per year (instigated by productivity loss in the agricultural and transportation sectors due to slower growth in government infrastructure capital stocks); • Similar decreases in total absorption, private consumption, and private investment.

46. 7. Uganda: policy scenarios and results Results for INFCUT (cont) • Reduced tax revenues and need for a slight increase in government spending on higher education (to make up for less household spending) reduces the scope for increases in MDG-related HD spending. • Growth in total government consumption accelerates whereas growth in total government investment slows down (given that HD is more consumption-oriented). • Factor wage growth decelerates across the board (by 0.2-0.4%). • Noticeably weaker progress for MDG 1; smaller changes for the other MDGs (more progress for MDGs 2 and 7 but less for MDG 4).

47. 7. Uganda: policy scenarios and results HD-Infrastructure Trade-Offs • Additional exploration: gradual variation of the real growth rate for government infrastructure capital stocks between -90% and +90% compared to BASE, with endogenous adjustments in MDG HD spending within fiscal space limits (i.e. the simulation INFCUT provided the first in a series of simulations). • Factors influencing the results: • Growth in HD services has a positive impact on HD MDGs. • Growth in infrastructure capital stocks raises TFP, GDP and private consumption. • The marginal returns from infrastructure capital stocks are diminishing • Slower growth in more educated labor reduces GDP growth.

48. 7. Uganda: policy scenarios and results Figure 1. Poverty-HD trade-offs

49. 7. Uganda: policy scenarios and results Results for OGOVCUT • Annual growth rates in HD and infrastructure services increase by 2-3 %-age points. • Government investment growth is boosted relative to consumption growth, since “other government” is tilted towards consumption. • GDP growth is 0.2% higher, with a similar expansion in private consumption and investment. • Growth expands for higher levels of education as more students proceed from the primary level. • MDG indicators improve significantly.

50. 7. Uganda: policy scenarios and results Results for FGEXP • Exchange rate appreciation and an increased trade deficit with slower export growth (by 1.0 %-age points) and more rapid import growth (by 0.9 %-age points). • Increased growth in absorption (+0.6%-age points), especially for government investment (generates the capital needed for increased service production. • Private consumption and investment growth expand by 0.4-0.5 %-age points. • GDP growth increases by around 0.3%, boosted by more rapid growth in investment (private, government infrastructure) and more rapid expansion for the educated labor force. • Positive effects on all MDG indicators, similar to those of the GOVEFF scenario.