Transcript MAMS: A Tool for Public Finance and Development

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
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, mediumto-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.
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.
Introduction
•
Outline:
1.
2.
3.
4.
5.
6.
7.
8.
9.
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
1. Issues in MDG strategy analysis
•
A framework for analysis of MDG strategies
should consider the following factors:
1. Synergies between different MDGs
2. Role of non-government service providers
3. Demand-side conditions (incentives, infrastructure,
incomes)
4. Role of economic growth
5. Macro consequences of increased government
spending under different financing scenarios
6. Diminishing marginal returns (in terms of MDG
indicators) to services and other determinants
7. Role of efficiency and input prices (e.g. wages) in
determining unit service costs
2. Model Structure
•
MAMS may be described as an extended, dynamicrecursive 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'.
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.
2. Model Structure
Figure. Aggregate payments in MAMS
Factor
Costs
Activities
Factor
Markets
Intermediate
Input Cost
Domestic Private Savings
Wages
& Rents
Gov. Savings
Taxes
Households
Government
Sav./Inv.
Transfers
Com’ty
Domestic Markets
Private
Consumption
Government
Consumption
Investment
Demand
Sales
Imports
Exports
Rest of the
World
Foreign Transfers
Foreign Savings
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.
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…..
Government recurrent revenue
 TINS h , YI h ; taa , tvaa ,PAa , PVAa , QAa ;

YG  f 
tmc , pwmc , QM c ; tec , pwec , QEc ;
 tq , PQ , QQ ; trnsfr
c
c
gov , row , EXR; YIFgov,f
 c





  direct tax   activity and VA 

  rates,  , tax rates, activity 

  household   and VA prices, 

  incomes   activity levels 



  import tariff   export tax 

 govern- 

 ment  = f   rates, import  ,  rates, export 
  prices (FCU),   prices (FCU), 

 recurrent 
 import quantities   export quantities 

 revenue 


  sales tax  transfers from   government  
  rates, composite   rest of world   income  
  supply prices  ,  (FCU),  ,  from  
  and quantities   exchange rate   factor f  


Government recurrent expenditure
 PQc , QGc ; trnsfrh , gov ;



EG  f  dintrath , GDEBTh ;

 fintrat , FDEBT , EXR 
gov
gov


 govern- 
 ment 
 recurrent  =f
 expen- 
 diture 
  government   trans-  
  consump    fers to  
 tion of c,   house-  
  price of c   holds  
 interest on domestic

  and foreign debt: debt  
  levels and interest  
  rates; exchange rate  
 
 
Government savings
GSAV  YG  EG
govern- 

govern- 

 govern  ment re-  ment re- 
 current


ment
 savings  current


expen  revenue 

 ditures 
Government investment value

f FCAP
PK f  DKINS gov , f  GSAV  BORgov ,h
 government fixed investment   govern-   government 
 value: sum over product of    ment    direct

 prices and investments
  savings   borrowing from 
 in different capital goods 
 household h 
 BORMS h  BOR gov , row  EXRt
 net borrowing of   net borrowing from RoW 
  monetary system   (net of lending to RoWand in- 
 from household h   creases in foreign reserces 
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:
1. Constant-elasticity function at the bottom: Z = f(X)
2. Logistic function at the top: MDG = g(Z)
2. Model Structure
Determinants of MDG outcomes
Service
per capita or
student
Consumption per
Capita
Wage
incentives
Public infrastructure
Other MDGs
2–Primary
schooling
X
X
X
X
4
4-Under-five
mortality
X
X
X
7a,7b
5-Maternal
mortality
X
X
X
7a,7b
7a-Water
X
X
X
7b-Sanitation
X
X
X
MDG
2. Model Structure
Logistic function
1.0
MDG
0.8
0.6
0.4
0.2
0.0
0
2
4
Z
6
8
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.
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)
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).
2. Model Structure
Macro Closures
•
Mechanisms for clearing (assuring that
receipts = outlays) of:
1. Balance of Payments – real exchange rate
2. Savings-Investment Balance – private
investment
3. Government budget → next slide
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)
2. Model Structure
Market-clearing variables for
factors and commodities
•
Factors. Two alternatives:
1. exogenous unemployment: wage clears
2. endogenous unemployment. Two regimes:
a. unemployment above minimum rate: unemployment rate
clears (influencing reservation and market wage)
b. 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
2. Model Structure
Factor market with endogenous unemployment
5
Wage
4
3
Supply
2
Demand
1
0
85
90
100 - unemployment rate (%)
95
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.
2. Model Structure
Digression: MAMS vs. RMSM-X
Table. MAMS vs. RMSM-X
MAMS
medium- to long-run
Time frame
Accounting consistency yes
more emphasized
Economic behavior
labor, capital, land
Production function
intermediates
no
Monetary sector
more
Disaggregation
more
Data requirements
GAMS/Excel
Software
RMSM-X
short- to medium-run
yes
less emphasized
capital
yes
less
less
Excel
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.
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.
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, watersanitation, public infrastructure)
– Existing SAMs and input-output tables
– Surveys (household, labor, DHS)
4. Examples of Scenarios
•
Questions commonly addressed by non-BASE
scenarios: What happens if the government …
1. expands services sufficiently to reach the MDGs with
additional financing provided by (a) foreign grants; (b)
domestic taxes; (c) domestic borrowing?
2. contracts in one area (e.g. human development or
other government) and expands in another (e.g.
infrastructure) with unchanged aid and domestic
policies?
3. in one or more areas, expands services sufficiently to
make use of additional financing from a, b, or c (as
defined under 1)?
4. becomes more/less productive, adjusting one or more
types of spending or financing in response?
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
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.
5. Uganda case study
Uganda SAM for MAMS Macro Version
[Unit: % of GDP at market prices; Year: FY2003]
a-prv
a-gov
c-prv
c-gov
f-lab
f-capprv
hhd
gov
row
tax-dom
tax-imp
int-dom
int-row
cap-hhd
cap-gov
cap-row
inv-prv
inv-gov
dstk
total
v
m
hd gov row
w
rv
ov
pr
om imp
o
v
v
h
o
v
v
p
g
p
d
d
r
r
o
r
o
b
a
d
v
tk
p
p
p
w
a
ta
x
x
p
g
p
g
ttv
v
aaccf-l
f-c
hh
go
ro
ta
ta
in
in
ca
ca
ca
in
in
ds
to
145.5
145.5
22.7
22.7
60.8 9.5
71.6
12.2
16.0 4.7 0.0 174.9
1.4
6.2 15.2 0.1
0.0 0.0
22.9
41.0 10.7
51.7
37.8 2.2
40.0
50.6 39.1
1.2 1.7
1.0
93.6
7.0 7.7 3.5
18.3
25.8 0.2 1.1 0.9
0.5
28.4
4.5 0.3
3.0
7.7
3.5
3.5
1.0
1.0
0.5
0.5
12.8
12.8
0.5
-0.2
4.3
4.7
7.4
7.4
13.0
3.0
16.0
4.7
4.7
0.0
0.0
145.5 22.7 174.9 22.9 51.7 40.0 93.6 18.3 28.4 7.7 3.5 1.0 0.5 12.8 4.7 7.4 16.0 4.7 0.0
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%
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.
6. Uganda: base scenario and results
Table 1a. BASE Results
Indicator
Real
macro
Absorption
Private consumption
Government consumption
Private investment
Government investment
Exports
Imports
GDP at factor cost
Real exchange rate index
Real government
services
Primary education
Secondary education
Tertiary education
Health
Water
Agriculture**
Roads**
Other government
Government Taxes
revenue
Foreign aid
2003
bn
13,484
9,232
1,799
1,903
553
1,463
3,088
10,871
100
base
% growth py
6.0
5.7
7.1
6.0
6.1
7.0
5.7
6.1
0.224
260.2
75.2
85.7
192.3
2.9
15.6
57.6
1,109.6
% of GDP
11.3
11.3
4.9
14.3
12.9
6.2
6.2
6.2
6.2
6.2
% in 2020
14.4
11.0
6. Uganda: base scenario and results
Table 1b. BASE Results
Indicator
Real household consumption
per capita
Rural
Urban
Quartiles 1-2
Quartiles 3-4
Total
2003
'000
281.7
901.9
168.1
547.5
357.8
%
MDG
1 (headcount poverty
indicators*** 2 (primary completion)
4 (under-5 mortality)
7a (improved water access)
37.7
15.5
14.0
56.0
base
% growth py
2.1
1.9
2.2
2.0
2.1
% in 2020
17.2
76.0
7.9
64.0
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 1314%.
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.
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)
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
7. Uganda: policy scenarios and results
Table 1. Policy scenarios -- description
Name
infcut
ogovcut
fgexp
taxexp
Description
90% growth cut for infrastructure (roads and
agriculture) and expansion of MDG-related HD
within fiscal space limits.
50% growth cut for other government and
expansion of infrastructure and MDG-related HD
within fiscal space limits.
doubled foreign aid increase and expansion of
infrastructure and MDG-related HD within fiscal
space limits.
Same expansion of government as FGEXP and same
foreign aid as BASE; government expansion
financed by extra direct taxes.
7. Uganda: policy scenarios and results
Table 2a. Results for policy scenarios
Indicator
2003
bn
Real
Absorption
13,484
macro
Private consumption
9,232
Government consumption 1,799
Private investment
1,903
Government investment
553
Stock change
-3
Exports
1,463
Imports
3,088
GDP at factor cost
10,871
Real exchange rate index
100
bn
Real govPrimary education
260.2
ernment
Secondary education
75.2
services
Tertiary education
85.7
Health
192.3
Water
2.9
Agriculture**
15.6
Roads**
57.6
Other government
1,109.6
% of GDP
Government Taxes
11.3
revenue
Foreign aid
11.3
base
6.0
5.7
7.1
6.0
6.1
7.0
5.7
6.1
0.2
4.9
14.3
12.9
6.2
6.2
6.2
6.2
6.2
14.4
11.0
Simulations*
infcut ogovcut
fgexp
% annual growth
5.6
6.2
6.6
5.4
5.9
6.1
7.2
6.9
8.2
5.7
6.2
6.5
4.2
8.1
9.0
6.4
7.5
5.9
5.4
6.0
6.6
5.8
6.3
6.5
0.1
0.4
-0.3
% annual growth
5.4
6.9
7.1
14.6
15.7
15.9
13.0
14.6
15.1
6.9
9.0
8.9
7.0
8.8
8.6
0.9
8.8
8.6
0.9
8.8
8.6
6.2
3.1
6.2
% of GDP in final year
14.2
14.6
14.3
11.2
11.0
15.2
taxexp
5.9
5.2
8.4
5.3
9.0
7.3
5.7
6.2
0.5
7.1
16.7
15.8
8.9
8.6
8.6
8.6
6.2
21.7
10.5
7. Uganda: policy scenarios and results
Table 2b. Results for policy scenarios
Indicator
Real household consumption
per capita
Rural
Urban
Quartiles 1-2
Quartiles 3-4
Total
MDG
1 (headcount poverty
indicators*** 2 (primary completion)
4 (Under-5 mortality)
5 (Maternal mortality)
7a (Water access)
2003
'000
281.7
901.9
168.1
547.5
357.8
%
35.0
15.5
14.0
56.0
56.0
base
2.11
1.90
2.24
1.97
2.07
17.2
76.0
7.9
64.0
64.0
Simulations*
infcut ogovcut
fgexp
% annual growth
1.78
2.28
2.45
1.62
2.02
2.29
1.89
2.44
2.55
1.65
2.10
2.32
1.75
2.23
2.43
% in final year
19.9
16.1
14.7
76.4
89.8
92.5
8.0
6.6
6.6
65.5
73.8
73.2
65.5
73.8
73.2
taxexp
1.67
1.27
2.25
1.29
1.58
21.7
91.4
6.9
72.8
72.8
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.
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).
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.
7. Uganda: policy scenarios and results
Figure 1. Poverty-HD trade-offs
% of HD goal
Figure 1. Poverty - Human Development Trade-Offs
75
70
65
60
55
50
45
40
129
131
133
135
137
139
% of poverty goal
141
143
145
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.
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.
7. Uganda: policy scenarios and results
Results for TAXEXP
• By 2020, the required increase in taxes > 7% of GDP.
• Higher taxes give rise to declines in private consumption,
and investment growth by 0.5-0.7 %-age points.
• Growth in GDP and absorption are unchanged – decline
in private capital stock growth is balanced by productivity
effects of government spending on HD and
infrastructure.
• Private consumption: no change for bottom two quartiles
(who pay for the direct tax increase); decline by 0.4 %age points for top two quartiles.
• MDG results compared to FGEXP:
– similar (slightly weaker) gains for MDGs 2, 4, and 7a;
– much weaker outcome for MDG 1, also compared to BASE.
8. Uganda: conclusions
• Within a given foreign aid envelope, switching
spending between HD and infrastructure
involves difficult trade-offs; no scope to make
progress along one dimension without hurting
the other.
• If the government is able to cut down on
unproductive activities and/or become more
efficient, then it can make more rapid progress
across all MDGs, making trade-offs less difficult.
8. Uganda: conclusions
Conclusions (cont)
• More rapid government growth in the
absence of a parallel increase in foreign
aid brings difficult trade-offs to the fore:
human development services and the
stocks of public infrastructure capital
increase more rapidly while the private
sector is left with less resources for its
consumption and investment.
9. Concluding remarks
• MAMS has evolved into a flexible
framework for analysis of fiscal policy in
the medium- to long-run:
– Aggregated versions with limited data needs
can be used for simple macro analysis
– Disaggregated version with stronger data
demands can address a wider range of issues
relevant to development strategies, including
human development.
Key References
• Bourguignon, Francois, Carolina Diaz-Bonilla,
and Hans Lofgren. 2008. “Aid, service delivery
and the MDGs in an economy-wide framework.”
Draft. Forthcoming in eds. François
Bourguignon, Luiz Pereira da Silva and Maurizio
Bussolo. The impact of economic policies on
poverty and income distribution: Macro-Micro
Evaluation Techniques and Tools. New York:
Palgrave.
• Lofgren, Hans, Carolina Diaz-Bonilla, Jouko
Kinnunen, and Dino Merotto. 2008. “Patterns of
Growth and Public Spending in Uganda:
Alternative Scenarios for 2003-2020.”