Session 9Assessing Welfare Impact of PBL

Operations: Applications

Introductory Course on Economic Analysis of Policy-Based Lending Operations

7 June 2007

Guntur SugiyartoEconomics and Research Department

• Program design should begin with proposed reforms,sector analysis, and expected benefits

• Problem: proposing a policy reform measure as part ofprogram design; since it implicitly assumes reformmeasures and their benefits are already been linked.

OED’s Special Evaluation Study:Program Lending

Example:

A project proposal implies the underlying assessment ofthe relative priority and the incremental benefits of theproject could generate, including justification forallocating scarce resources.

Implication:This calls for refining and further developing the conceptual and analytical framework for understanding ex-ante economic analysis of policy and institutional reforms.

Different Paths to Achieve the Goal

Path 3

Path 1

Path 2

Path influences:- Policy- Institution- Investment patterns

t0 tn

Sectorindicator

time

Objective: Assess and present viable options to facilitate theselection of the least-cost and best sequence mix withverifiable and valid assumptions.

This means:

• Rely on quantitative and qualitative assessments to identifyand measure the impact.

• Descriptive analysis is required to assess the economic andsocial situation as starting point to assessing possibleimpacts. It also provide guidance for further analyses, suchas partial or general equilibrium analysis.

• Applications of methods require a clear statement ofassumptions.

• Increasingly rigorous analytical techniques require greateruse of data, resources, and capacity.

Different Paths to Achieve the Goal

Coverage of PBL and Possible Impact Measures

Coverage:

• Agriculture Sector: Price, income/consumption/poverty, effectiveness

• Financial Sector: Rate, income, effectiveness of programs.

• Economic Reform: Price, income, effectiveness of programs.

• Public Sector: Revenue, income, effectiveness of programs.

• Education: Access, Attendance, Grade, effectiveness of delivery.

• Health: Access, Health Condition, effectiveness of delivery.

• Governance: Revenue, income, effectiveness of programs.

• Capital Market: Price, rate, effectiveness of programs.

Examples: Descriptive Statistics

0

50

100

150

200

Days for Starting a Business

Duration (days) 8 30 31 42 46 59 63 88 94 168

Sing

Ban

Mal

Thai

Chi

Phili

Viet

Indi

Ca

Indo

0

500

1,000

1,500

2,000

Costs of Starting a Business

US$ Cost 103 129 135 144 239 244 249 272 961 1,551

Indo

Viet

Chin

Thail

India

Phili

Sing

Ban

Mala

Cam

• Average

• Standard Deviation or Variation

• Other descriptive measures

Note: Notice the vulnerability of poverty across countries

Source: Poverty in Asia: Measurement, Estimates and Prospects. KI 2004

Estimating population parameters

Examples: Inference Statistics

Examples: Non-parametric Statistics

-0.20.40.60.81.01.21.41.61.82.0

Business Obstacles 1.81 1.42 1.40 1.34 1.30 1.03

Stability Business Operat'n

Labor Financing Taxation Infra

Business Constraints

Source: ICS INO 2004

Effects of Decentralization Program

Source: ICS INO 2004

Hasty and big bang approach of decentralization in Indonesia has contributed to the worsening of main aspects of IC, especially in

creating more uncertainty and corruption.

Examples: Non-parametric Statistics

Examples: Index and ClassificationMicrosoft Excel

Worksheet

1

East AsiaChina, People's Rep. of 56.79 63.04 3.85 88.67 83.76 59.22 20Hong Kong, China … … 11.54 … … 11.54 35Korea, Rep. of … … 44.87 … 100.00 72.44 10Mongolia 26.47 17.39 15.38 78.00 56.41 38.73 28Taipei,China … … … … … … …

Southeast Asia

Brunei Darussalam … … … … 99.15 99.15 1Cambodia 5.59 0.00 32.05 7.19 47.86 18.54 34Indonesia 83.82 95.65 51.28 44.23 94.02 73.80 9Lao PDR 26.47 39.13 47.44 18.52 68.38 39.99 27Malaysia 100.00 100.00 0.00 82.57 99.15 76.34 8Myanmar … … … 36.38 95.73 66.05 16Philippines 60.29 72.83 12.82 45.53 71.79 52.65 24Singapore … … 7.69 … … 7.69 36Thailand 100.00 100.00 24.36 65.14 68.38 71.58 12Viet Nam 99.41 100.00 39.74 43.79 75.21 71.63 11

South Asia

Bangladesh 0.00 17.39 58.97 2.18 52.99 26.31 31Bhutan … … … 64.92 … 64.92 17India 0.00 11.96 57.69 0.00 70.09 27.95 30Maldives … … … 39.43 85.47 62.45 19Nepal 35.00 46.74 20.51 0.44 75.21 35.58 29Sri Lanka 89.41 96.74 50.00 41.61 66.67 68.89 14

Traffic Lights Indicating Relative Attainment Index

Proportion of Population Below $1 Purchasing Power

Parity (PPP) Per Day

Poverty Gap Ratio (Incidence Multiplied by Depth of Poverty)

Share of Poorest Quintile in National

Consumption

Region/Country Rank

Indicator 1 Indicator 2 Indicator 3 Indicator 4 Indicator 5

Prevalence of Underweight

Children Under 5 Years of Age

Proportion of the Population Below Minimum Level of

Dietary Energy Consumption

Goal 1

Eradicate extreme

poverty and hunger

Lower - % in the Red light

Upper - % in the Green light25

25

Change all at the same time

25

Lower - % in the Red lightUpper - % in the Green lightChange Individually

25

25 25 25 25

25 2525 25

25

25

Back to Summary

Lower 25% Between 25% and 75% Upper 25%

Figure 2. Goal 1 Index: Eradicate extreme poverty and hunger

0 5 10 15 20 25 30 35 40 45

Singapore

Hong Kong,China

Cambodia

Afghanistan

Bangladesh

India

Nepal

Mongolia

Lao PDR

%40 45 50 55 60 65 70 75 80 85 90

Papua New Guinea

Timor-Leste

Philippines

Tajikistan

Pakistan

China

Maldives

Uzbekistan

Bhutan

Myanmar

Turkmenistan

Sri Lanka

Solomon Is.

Thailand

Viet Nam

Korea, Rep. of

Indonesia

%0 20 40 60 80 100 120

Malaysia

Armenia

Kazakhstan

Kyrgyz Rep.

Fiji Islands

Kiribati a

Azerbaijan

Brunei

%

Examples: Index and Classification

Examples: RegressionRegression Results of Individual Investment Climate Indicators

Explanatory Variables Labor Productivity Sales Growth Export

Share TFP

Labor

Share of workers with more than 12 years of schooling -0.002 0.000 0.070 -0.002

(1.35) (0.58) (2.04)** (1.17)

Share of workers who use computer in their work 0.013 0.001 0.15 0.008

(4.18)*** (0.85) (2.32)** (2.55)**

Share of temporary workers 0.004 0.009 0.291 0.009

(0.75) (3.06)*** (2.37)** (1.59)

Share of workers with training 0.004 0.000 0.155 0.000

(1.72)* (0.27) (2.83)*** (0.19)

Firm provides either in-house or outside training to its workers 0.509 0.009 12.206 0.210

(3.76)*** (0.12) (3.94)*** (1.55)

Labor quality index 0.171 0.001 5.568 0.053

(3.07)*** (0.04) (4.34)*** (0.94)

Poverty Predictor Modeling

A. General Variables: Scoring Types oh house (options with different score) Living area Type of roof Type of wall Type of floor Type of WC Source of drinking water Cooking facility Frequency of eating Ownership of sofa Ownership of refrigerator assets Ownership of refrigerator assets Saving etc

B. Policy/Project Concerned Variables Schooling of school age children Proportion of Illiterate Head unemployed Head/wife Illiterate Diploma/university graduate

Total Score 100 %

Examples: IO Modeling

1998 UK Germany

France Italy Netherlands

Other Total

GNP Direct 0.437 0.443 0.448 0.447 0.446 0.423 0.437 D+I 0.559 0.561 0.572 0.568 0.564 0.503 0.556 D+I+H 0.706 0.708 0.720 0.716 0.711 0.681 0.702 D+I+H+G 1.022 1.020 1.041 1.036 1.030 0.985 1.015 EMPLOYMENT (per million expenditure) Direct 61.093 60.761 58.936 61.486 65.413 59.042 60.603 D+I 80.640 79.996 79.321 81.298 84.440 78.129 80.034 D+I+H 95.477 94.619 94.239 96.157 99.263 92.300 94.679 D+I+H+G 130.775 129.790 130.231 131.981 135.029 126.361 129.741 GOVERNMENT INCOME Direct 0.137 0.138 0.141 0.140 0.141 0.133 0.137 D+I 0.165 0.166 0.169 0.169 0.168 0.160 0.165 D+I+H 0.233 0.232 0.238 0.237 0.236 0.225 0.232 D+I+H+G 0.344 0.343 0.351 0.349 0.349 0.332 0.342

0

50

100

150

200

Total Effects on GNP

1998 131.91 54.43 21.15 24.26 13.97

2001 194.33 64.80 28.65 39.33 18.98

UK Germany

France

Italy Netherlands

0

20

40

60

80

Total Effects on Government Income

1998 44.47 18.29 7.12 8.18 4.73

2001 66.01 21.85 9.64 13.16 6.48

UK Germa France Italy Nether

0

5,000

10,000

15,000

20,000

Total Effects on Employment (FTE)

1998 16,887 6,923 2,645 3,091 1,831

2001 16,349 5,478 2,431 3,334 1,598

UK Germa France Italy Nether

Microsoft Excel Worksheet

Effects of Exports

Examples: SAM Multiplier AnalysisSouth-KoreaDefourny and Thorbecke (1984) : relative importance of paths of the multipliereffects on households headed by unskilled workers that arise from an injection inthe processed foods sector.IndonesiaKeuning and Thorbecke (1992): higher income rural and urban households weremore influenced by government current expenditure injections than by exports.Thorbecke and Jung (1996): growth in agriculture and agriculture-related activitiestend to do more to alleviate poverty than growth in industrial, or even serviceactivities, even after accommodating the various multiplier effects.IndiaSAM Multiplier Analysis of Informal Households: Application to an Indian ArchetypeEconomy (Sinha, 2000).ChinaSAM-based Multiplier Analysis for China’s Economy (Li Shantong et al. 2004).OthersAgriculture-based Development: A Sam Perspective On Central Viet Nam (Bautista2000), Distributional Impacts of Agricultural Growth in Pakistan: A MultiplierAnalysis, Dorosh et al. mimeo; Structural Characteristics of the Economy ofMozambique: A SAM-based Analysis (Arndt, et al. 2000). Distributive impacts ofalternative agricultural policies: a SAM-based analysis (ROCCHI et al. 2005); etchttp://www.iioa.org

Economy-wide multipurpose, open economy, based on SAM for 1993,comparative static and real sector.

Consist of 18 sectors/commodities, 8 types of labour, 5 kinds of capital,10 categories of household, a firm, the government, and the rest of theworld (ROW).

Wage stickiness (for agriculture & production workers), flexible capitalprices, Armington specifications, and imperfect substitutability betweenfactors and capitals.

A downward sloping demand curve for exports and price taker forimports.

Fixed aggregate investment and a ‘planned government consumption’.

Current account deficits residual, clearing S-I balance.

A fixed exchange rate and price of the ROW as the numéraire.

Examples: CGE ModelCGE Model for Indonesia : Main Features

Welfare Costs of Indirect Taxation and Tariffs

Value (%)Sectoral Output

Total Output

Sectoral Tax Total Tax

Food Crops 485.8 2.4 1.4 0.1 193.7 3.0Other Agriculture 499.6 2.5 1.2 0.1 139.0 3.1Mining 145.9 0.7 0.4 0.0 45.6 0.9Food Processing 10427.7 51.8 16.4 1.8 168.0 65.3Textile 741.3 3.7 0.9 0.1 54.4 4.6Construction 282.2 1.4 1.4 0.1 101.6 1.8Papers and Metals 1018.8 5.1 3.1 0.2 87.5 6.4Chemical -620.2 -3.1 -1.0 -0.1 80.4 -3.9Utilities 45.7 0.2 0.6 0.0 106.5 0.3Trades 2959.4 14.7 5.4 0.5 78.5 18.5Restaurant 1025.1 5.1 5.6 0.2 128.2 6.4Hotel 138.5 0.7 4.0 0.0 94.2 0.9Land Transport 279.8 1.4 1.5 0.1 89.3 1.8Other Trans & Com. 114.4 0.6 0.7 0.0 90.9 0.7Bank and Insurance 168.6 0.8 0.9 0.0 104.7 1.1Real estate 839.2 4.2 4.9 0.2 104.5 5.3Public services 322.6 1.6 1.2 0.1 106.0 2.0Personal services 401.5 2.0 2.4 0.1 123.5 2.5Total 20151.1 100.0 3.5 3.5 126.2 126.2

Welfare Costs Welfare Costs as % ofSectoral Indirect Taxation

Value (%) Sectoral Output

Total Output

Sectoral Tax Total Tax

Food Crops 13.93 0.28 0.98 0.02 25.11 0.22Other Agriculture 40.12 0.80 8.92 0.06 84.44 0.63Mining 30.97 0.61 1.28 0.04 80.50 0.48Food Processing 365.03 7.24 13.96 0.52 117.57 5.71Textile 2.70 0.05 3.09 0.00 13.45 0.04Construction 280.93 5.58 5.73 0.40 100.99 4.39Papers and Metals 2408.84 47.81 6.89 3.42 71.70 37.68Chemical 1870.88 37.13 9.91 2.66 83.43 29.27Total 5038.63 100.00 7.16 7.16 78.83 78.83

Welfare Costs as % ofWelfare CostsSectoral Tariffs

Effects of 2% Tariff Reduction

E conom ic Ind icators A T B (% ) M acroeconom ic A ggregates G ross D om estic Product 0.017 E m ploym ent 0.035 E xternal C ondition R eal Export -0 .050 R eal im port 0 .197 Trade B alance -2 .874 W elfare of H ouseholds D om estic A bsorption 0 .078 H ousehold Incom e 0 .063 H ousehold R eal C onsum ption 0 .051 E quivalent V ariation (E V ) EV -A ll H ousehold 123.677 EV -Farm er 37.435 EV -R ural H ousehold 31.883 EV -U rban H ousehold 54.856

CGE Application in Nepal

CGE Micro simulation in the Philippines

CGE Micro simulation in the Philippines

Thank You !