Key issues in incorporating MDG-consistency in
the Macroeconomic Models

Expert Group Meeting on MDG-consistent Macroecono...
Pakistan MDG Costing based on Revised
Macroeconomic Framework
• Project completed in 2012
• Housed at Ministry of Finance
...
Key Steps
A. Macro Model
– Understanding on model specifications and parameters
– Interviews were conducted to assess capa...
Key Steps-II
B. MDG Costing
–
–
–
–

Identified the MDGs to use
Identified indicators
Literature review to identify driver...
Past Modeling Efforts
• Public Sector
• Macro-consistency Framework: Planning Commission of Pakistan
• Financial Programmi...
Macro Model for Government’s Use
• By 2012 the old models were dormant
• Due to frequent transfers of civil servants, capa...
Model Development
• The underlying principles for development of the model were:
–
–
–
–

Ease of data gathering (use of a...
MDG Costing in Macro Model

Sectoral Production
Agriculture
Industry
Private Services
Public Services
GDP(fc) real prices
...
Needs Assessment – Model Usages
Examples of kind of analysis we can do with this model:
• Result on GDP, if:
–
–
–
–
–
–
–...
Needs Assessment – Model Usages
Examples of kind of analysis we can do with this model:
• Government Tax Revenue, if:
– Na...
Demonstration - BAU
Forecast for 2014-15 (called baseline) on a business as
usual (no policy change) scenario
GDP Growth (...
Demonstration - Simulations
Example Scenarios:
• Impact on key macroeconomic indicators, if:
• Credit to Private Sector Im...
Demonstration – Scenarios
2014-15

GDP Growth (%)
Total Investment (% of GDP)
Private Investment (% of GDP)
National Savin...
Opening up MDG Costing
• MDGs selected for costing
• Costing methodology
• Integrating MDG Costing in Macro Model

14
Choice of MDGs
• We have 7 MDGs and 14 indicators in this study

• We have chosen these MDGs because:
– These MDGs can be ...
Costing Methodology
• A top-down costing methodology as opposed to ‘needs based’
analysis
• ‘Needs based’ analysis are not...
Costing Methodology - II
• Once we have MDG functions we can determine the cost
required to achieve a given MDG target
• W...
MDG Production Function
• Inspired from “MAMS Model” (World Bank)
• Each MDG produced by a combination of
determinants per...
Integration Issues
– Only limited pro-poor spending categories to work with
so one spending line drives many MDGs making i...
MDG Drivers-Poverty and Hunger
• Poverty
– GDP growth and the share of share of the lowest quintile in total
consumption
•...
MDG Drivers- Education (1)
• Net Primary enrolment rates are affected by
– Public education spending
– The share of the lo...
MDG Drivers- Education (2)
• The adult literacy rate is affected by
– Public education spending
– The share of the lowest ...
MDG Drivers-Health (1)
• Infant/child mortality is affected by
– Public health spending
– Share of the Lowest quartile in ...
MDG Drivers- Health (2)
• the % deliveries attended by qualified health personnel are affected by
– Public health spending...
MDG Drivers- Environmental sustainability
• The % households able to access to safe water is affected by
– Infrastructure ...
Components in generating MDG costs

MDG
Parameters
α,β γ

Elasticities

MDG
base

MDG Cost of
Inputs MDG
Inputs
base addit...
Way Forward
• Disaggregating local-level sectoral and public finance data
• Localizing MDGs
• Improving specifications yet...
Thank You

www.sdpi.org, www.sdpi.tv

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MDG-consistency in the Macroeconomic Models

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  • MDG-consistency in the Macroeconomic Models

    1. 1. Key issues in incorporating MDG-consistency in the Macroeconomic Models Expert Group Meeting on MDG-consistent Macroeconomic Modeling for Planning in South Asia 1-2 October 2013, Nepal
    2. 2. Pakistan MDG Costing based on Revised Macroeconomic Framework • Project completed in 2012 • Housed at Ministry of Finance • For use by: – Ministry of Finance – Planning Commission – Provincial Departments of Planning
    3. 3. Key Steps A. Macro Model – Understanding on model specifications and parameters – Interviews were conducted to assess capacity in economic Ministries towards model building and management – A complete literature review of existing models – We relied on official published data from various sources – Model equations and identities were specified in line with macroeconomic theory – Model output was validated using internal (sensitivity analysis) and external (other comparable model results) methods
    4. 4. Key Steps-II B. MDG Costing – – – – Identified the MDGs to use Identified indicators Literature review to identify drivers for indicators Collected / calculated appropriate data for identified indicators – Calculated stock of development spending – Review of MDG elasticities used in literature – Integrated MDG relationships into Macro model
    5. 5. Past Modeling Efforts • Public Sector • Macro-consistency Framework: Planning Commission of Pakistan • Financial Programming Framework: Ministry of Finance • Financial Programming Framework: State Bank of Pakistan • Non-Governmental Sector • Integrated Financial Programming-CGE-microsimulation model: Sustainable Development Policy Institute • Integrated Social Sector Planning Model: Social Policy Development Centre 5
    6. 6. Macro Model for Government’s Use • By 2012 the old models were dormant • Due to frequent transfers of civil servants, capacity could not be retained • The result is that informed policy decisions are hampered • Executive branch has no support tool to evaluate morningafter impact of public policy decisions • In the face of external shocks there is no early warning alarm system to preempt Government’s response – hence difficulty in risk management 6
    7. 7. Model Development • The underlying principles for development of the model were: – – – – Ease of data gathering (use of available data) Tractability Parsimony in updating of model Ease of training • The model developed is based on 34 behavioral equations apart from fundamental accounting identities Current State of Macroeconomic Data: • Real Sector Accounts: No recent supply and use or input output table– model works with published data • Fiscal Sector Statistics: – For development spending reliance on pro-poor data – Service delivery based data not available 7
    8. 8. MDG Costing in Macro Model Sectoral Production Agriculture Industry Private Services Public Services GDP(fc) real prices Fiscal Balance Direct Taxes Indirect Taxes Customs Duty Non-Tax Revenue Current Expenditure Development Expenditure Transfers to Provinces Inputs Fertilizer, Water, Area Labour, Capital, Capacity Investment-Savings GDP-current prices Net Foreign Income Foreign Savings Total Resources Consumption Private Investment Public investment National Savings Balance of Payments Current Account Exports Imports Incomes (net) Current Transfers Capital Account Financing Gap Global GDP GDP Deflator NFC Award Formulae Pro-poor current & Development spending MDGs
    9. 9. Needs Assessment – Model Usages Examples of kind of analysis we can do with this model: • Result on GDP, if: – – – – – – – Productivity of Agriculture sector improves / reduces Employment changes Credit to private sector increases / decreases Inflation increases / decreases Industrial capacity utilisation (energy availability) changes Population growth rate Public sector investment changes • Result on Current Account Balance, if: – – – – GDP of trading partners changes Diaspora patterns change Domestic GDP changes Rate of Taxation changes 9
    10. 10. Needs Assessment – Model Usages Examples of kind of analysis we can do with this model: • Government Tax Revenue, if: – National GDP changes – Imports increase / decrease – LSM improves / reduces • MDG attainment, if: – Finances are available / not available (gap analysis) 10
    11. 11. Demonstration - BAU Forecast for 2014-15 (called baseline) on a business as usual (no policy change) scenario GDP Growth (%) Total Investment (% of GDP) Private Investment (% of GDP) National Savings (% of GDP) Labour Demand (%) Tax Revenues (Rs. Billion) Fiscal Deficit (% of GDP) Tax Revenues (% of GDP) Exports ($ Million) Import ($ Million) Current Account Balance ($ Million) Financing Gap ($ Million) 2014 4.6 15.8 9.4 14.0 2.1 3094 -5.0 10.6 29397 45155 -5761 -5601 2015 5.0 17.1 10.6 15.5 2.3 3548 -4.4 10.3 31937 48328 -5949 -5789 11
    12. 12. Demonstration - Simulations Example Scenarios: • Impact on key macroeconomic indicators, if: • Credit to Private Sector Improves by 10% • Oil import bill increases by 10% 12
    13. 13. Demonstration – Scenarios 2014-15 GDP Growth (%) Total Investment (% of GDP) Private Investment (% of GDP) National Savings (% of GDP) Labour Demand (%) Tax Revenues (Rs. Billion) Fiscal Deficit (% of GDP) Tax Revenues (% of GDP) Exports ($ Million) Import ($ Million) Current Account Balance ($ Million) Financing Gap ($ Million) Credit to Private Oil import Sector bill Improves by increases by BAU 10% 10% 5.0 5.2 4.5 17.0 17.6 15.5 10.4 11.1 8.9 15.4 16.0 13.5 2.2 2.3 2.0 3540 3537 3556 -4.5 -4.4 -4.6 10.3 10.3 10.4 31935 32233 31934 48195 48302 49771 -5798 -5919 -7341 13 -5638 -5759 -7181
    14. 14. Opening up MDG Costing • MDGs selected for costing • Costing methodology • Integrating MDG Costing in Macro Model 14
    15. 15. Choice of MDGs • We have 7 MDGs and 14 indicators in this study • We have chosen these MDGs because: – These MDGs can be affected through government budgetary allocations, – Survey data is available for these MDGs at both national and provincial level – Targets have been developed for these MDGs for Pakistan DD MonthYear © 2012 Oxford Policy Management Ltd 15
    16. 16. Costing Methodology • A top-down costing methodology as opposed to ‘needs based’ analysis • ‘Needs based’ analysis are not sufficient because they only provides an estimate of the cost of reaching a target MDG value – so we are not able to estimate the costs of reaching another MDG value or the MDG outcome from the inputs which we actually have or expect to have in the future. Therefore, a ‘needs based’ analysis cannot be integrated into a macro model • ‘Needs based’ analysis have proved extremely complicated to implement DD MonthYear © 2012 Oxford Policy Management Ltd 16
    17. 17. Costing Methodology - II • Once we have MDG functions we can determine the cost required to achieve a given MDG target • We are fitting a relationship between inputs and the MDGs • Each MDG “produced” by a combination of determinants – MDG value is dependent on a composite input variable – Composite input variable is dependent on values of inputs (government spending, private consumption, etc.) DD MonthYear © 2012 Oxford Policy Management Ltd 17
    18. 18. MDG Production Function • Inspired from “MAMS Model” (World Bank) • Each MDG produced by a combination of determinants permits: – – – – Imposition of a limit for the mdg variable Replication of base-year values and elasticities Calibration to an “additional point” Diminishing marginal returns to the inputs • Two-level function: 1. Logistic function at the top: MDGVALUE = LOGIT(Z) 2. Constant-elasticity function at the bottom: Z = Constant Elasticity of Substitution Function of govt spending , private consumption, public infrastructure, and other mdgs
    19. 19. Integration Issues – Only limited pro-poor spending categories to work with so one spending line drives many MDGs making it impossible to “cost” them independently – Pro-poor spending for mother and child health is infeasibly low so need to combine it with health facilities spending – Elasticities information very sparse in literature so need to test robustness DD MonthYear © 2012 Oxford Policy Management Ltd 19
    20. 20. MDG Drivers-Poverty and Hunger • Poverty – GDP growth and the share of share of the lowest quintile in total consumption • Hunger – the proportion of children U5 who are underweight is affected by • • • • • DD MonthYear Public health spending The adult literacy rate Girls’ primary enrolment rate Access to clean water Access to sanitation © 2012 Oxford Policy Management Ltd 20
    21. 21. MDG Drivers- Education (1) • Net Primary enrolment rates are affected by – Public education spending – The share of the lowest quintile in consumption – The % children U5 under weight – The adult literacy rate • Girls primary enrolment is affected by – Public education spending – The share of the lowest quintile in consumption – % children U5 under weight – Net primary enrolment rate – The adult literacy rate DD MonthYear © 2012 Oxford Policy Management Ltd 21
    22. 22. MDG Drivers- Education (2) • The adult literacy rate is affected by – Public education spending – The share of the lowest quintile in consumption – % children U5 under weight – Net primary enrolment rate – Girls primary enrolment DD MonthYear © 2012 Oxford Policy Management Ltd 22
    23. 23. MDG Drivers-Health (1) • Infant/child mortality is affected by – Public health spending – Share of the Lowest quartile in consumption – Adult literacy rate – Infant vaccination rates – % deliveries attended by qualified personnel – % treatment of malaria – Incidence of TB – % access to safe water – % access to sanitation DD MonthYear © 2012 Oxford Policy Management Ltd 23
    24. 24. MDG Drivers- Health (2) • the % deliveries attended by qualified health personnel are affected by – Public health spending • the contraceptive prevalence rate is affected by – Public health spending – Adult literacy • The Incidence of Malaria (% under treatment) is affected by – Public health spending – % access to safe water • The Incidence of TB is affected by – Public health spending DD MonthYear © 2012 Oxford Policy Management Ltd 24
    25. 25. MDG Drivers- Environmental sustainability • The % households able to access to safe water is affected by – Infrastructure spending – Adult literacy rate • The % of households with access to sanitation is affected by – Infrastructure spending – Adult literacy rate DD MonthYear © 2012 Oxford Policy Management Ltd 25
    26. 26. Components in generating MDG costs MDG Parameters α,β γ Elasticities MDG base MDG Cost of Inputs MDG Inputs base additional additional target target point point 26
    27. 27. Way Forward • Disaggregating local-level sectoral and public finance data • Localizing MDGs • Improving specifications yet not complicating computational processes DD MonthYear © 2012 Oxford Policy Management Ltd 27
    28. 28. Thank You www.sdpi.org, www.sdpi.tv 28

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