Constructing the Welfare Aggregate Part 2: Adjusting for Differences Across Individuals Bosnia and Herzegovina Poverty Analysis Workshop September 17-21,

Slides:



Advertisements
Similar presentations
1 Alternative measures of well-being Joint work by ECO/ELSA/STD.
Advertisements

The Bulgarian CPI And The Index Of A Small Basket Of Goods And Services Joint UNECE/ILO Meeting on Consumer Price Indices Geneva, May 2006 National.
Methodological approaches to recording certain types of services in the Consumer Price Index in Belarus Ekaterina Grikhanova, National Statistical Committee.
ADePT Automated DECs Poverty Tables Michael Lokshin, Zurab Sajaia and Sergiy Radyakin DECRG-PO The World Bank.
William Fallon May 08, 2012 Brown University Department of Economics A Theoretical and Empirical Analysis of Cross-Country Welfare.
Day 2: Poverty and Health Measurements Takashi Yamano Development Problems in Africa Spring 2006.
1.2.1 Measurement of Poverty 1 MEASUREMENT AND POVERTY MAPPING UPA Package 1, Module 2.
UNECE Workshop on Consumer Price Indices Session 1: The Concept, Scope and Coverage of the CPI Presentation by Cengiz Erdoğan, TurkStat October Istanbul,
Learning objectives In this chapter, you will learn about how we define and measure: Gross Domestic Product (GDP) the Consumer Price Index (CPI) the Unemployment.
Introduction The macroeconomic approach National accounting.
Measuring the State of the Economy
© 2008 Pearson Addison Wesley. All rights reserved Chapter Four Demand.
EC 204 Slides to Accompany Chapters 1 and 2
Learning objectives In this chapter, you will learn about how we define and measure: Gross Domestic Product (GDP) the Consumer Price Index (CPI) the Unemployment.
Exploring Poverty Indicators 5th - 9th December 2011, Rome.
Gagik GevorgyanGagik Gevorgyan Member of State Council on Statistics of the Republic of ArmeniaMember of State Council on Statistics of the Republic of.
Poverty Lines Michael Lokshin DECRG-PO The World Bank.
Chapter 6 Measuring the price level
UNECE Workshop on Consumer Price Indices Session 3: Calculation Expenditure Weight Presentation by Cengiz Erdoğan, TurkStat October Istanbul, Turkey.
2000/2001 Household Budget Survey (HBS) Conducted by The National Bureau of Statistics.
UK POVERTY GCSE ECONOMICS: UNIT 12 Measurement of standards of living.
GIS in Prevention, County Profiles, Series 3 (2006) A. Census Definitions The following is an excellent source of definitions and explanations of geography-related.
Measuring poverty and inequality in the Republic of Belarus Inna Konoshonok Head of the Living Standards Statistics and Household Survey Department NATIONAL.
Measurement of Poverty: a Case Study of Pakistan Ambar Narayan (World Bank) Regional Poverty Analysis and Monitoring Workshop Islamabad, Pakistan March.
The new HBS Chisinau, 26 October Outline 1.How the HBS changed 2.Assessment of data quality 3.Data comparability 4.Conclusions.
Allocating Spending Afternoon Session Part I. Topics Allocating Spending to Children –Direct methods: Per Capita and USDA –Indirect methods: Engel and.
Welfare economics Outline Expressing changes in human well-being (utility) in monetary terms Deciding between monetary measures that are equally theoretically.
Demand Elasticities and Related Coefficients. Demand Curve Demand curves are assumed to be downward sloping, but the responsiveness of quantity (Q) to.
1 Measuring Economic Aggregates and the Circular Flow of Income CHAPTER 7 © 2003 South-Western/Thomson Learning.
Poverty Ms. C. Rughoobur Africa Statistics Day 18 November 2013.
Slide 1 © 2002 McGraw-Hill Australia, PPTs t/a Introductory Mathematics & Statistics for Business 4e by John S. Croucher 1 Index numbers n Learning Objectives.
Adjustment of benefit Size and composition of transfer in Kenya’s CT-OVC program Carlo Azzarri & Ana Paula de la O Food and Agriculture Organization.
Applications of Semiparametric Modeling Methods ECON 721.
Integrating a Gender Perspective into Statistics Selected topic: Poverty Statistics S. Nunhuck Statistics Mauritius.
Estimating Living Wage Globally Martin Guzi Masaryk University, Czech Republic WTO Public Forum 2014.
DFID: STATISTICS TRAINING DAY LONDON, NOVEMBER 11, 2013 JONATHAN HAUGHTON Measuring.
Monitoring Jobs and the Price Level CHAPTER 6. After studying this chapter you will be able to Define the unemployment rate, the labor force participation.
5 CHAPTER Measuring GDP and Economic Growth.
PRICE AND VOLUME MEASURES NATIONAL ACCOUNTS STATISTICS WORKSHOP PRICE AND VOLUME MEASURES Workshop on national accounts for Asian member countries of the.
Poverty measurement: experience of the Republic of Moldova UNECE, Measuring poverty, 4 May 2015.
Adjusting for Family Composition and Size Module 4: Poverty Measurement and Analysis February, 2008.
Workshop on Price Index Compilation Issues February 23-27, 2015 Market Basket Items and Weights Gefinor Rotana Hotel, Beirut, Lebanon.
1. 2 Introduction Purpose of the ICP UN System of National Accounts calls for comparisons of GDP across countries be using PPPs The Approach Collection.
United Nations Economic Commission for Europe Statistical Division UNECE Workshop on Consumer Price Indices Istanbul, Turkey,10-13 October 2011 Session.
Data and Construction of Economic Table Washington Child Support Group December 2007 Session I.
Peter Lanjouw, DECPI PREM Knowledge and Learning Weeks “Exploring the Intersections between Poverty and Gender” World Bank, May 8, 2012.
Statistics Division Beijing, China 25 October, 2007 EC-FAO Food Security Information for Action Programme Side Event Food Security Statistics and Information.
Data Weighting Issues Adult Equivalent Scales, Stratified Sampling and general Population Weighting Issues.
Index numbers Value-, price-, quantity indices. Measuring changes in time Indices: relative change in price, quantity and value of products or services.
Constructing the Welfare Aggregate Part 2: Adjusting for Differences Across Individuals Salman Zaidi Washington DC, January 19th,
CPI Measurement Problems The Case of Malawi By Charles Machinjili National Statistical Office Malawi.
United Nations Economic Commission for Europe Statistical Division UNECE Workshop on Consumer Price Indices Istanbul, Turkey,10-13 October 2011 Session.
Slide 0 Chapter 2: The Data of Macroeconomics. slide 1 Gross Domestic Product (GDP) the Consumer Price Index (CPI Unemployment rate.
1 ICP 2004 Workshop for Regional Coordinators Eurostat, Luxembourg March 24 to 28, 2003 Chapter 4 Price concepts and quality.
1 Measuring Poverty: Inequality Measures Charting Inequality Share of Expenditure of Poor Dispersion Ratios Lorenz Curve Gini Coefficient Theil Index Comparisons.
Statistical Inference: Poverty Indices and Poverty Decompositions Michael Lokshin DECRG-PO The World Bank.
Global extreme poverty rates for children, adults and the elderly 2013 CSAE conference / March 19 / Oxford / Cockburn Yélé Batana, Maurizio Bussolo and.
How do we know when we are better off?.  Satisfy our wants and needs  We do this through purchasing goods and services  Goods and services gives us.
1 Presentation to Georgia Child Support Commission September 9, 2005 Jane C. Venohr, Ph.D. Policy Studies Inc Wynkoop St, Suite 300 Denver, CO
POVERTY IN KENYA, 1994 – 1997: A STOCHASTIC DOMINANCE APPROACH.
HBS 2000/01: March National Bureau of Statistics ANALYSIS OF THE HBS 2000/01 INCOME POVERTY.
AN ANALYSIS OF HOUSEHOLD EXPENDITURE AND INCOME DATA
PROVIDING INTERNATIONAL COMPARABILITY OF POVERTY ASSESSMENTS
Real Personal Income and Regional Price Parities
Module 1 Measuring Poverty
ECON 201 Indices Week
Value-, price-, quantity indices
REGIONAL POVERTY ANALYSIS TECHNICAL WORKSHOP
Lifecycle Deficit (Consumption & Labor Income)
Economic Performance Chapter 13.
Presentation transcript:

Constructing the Welfare Aggregate Part 2: Adjusting for Differences Across Individuals Bosnia and Herzegovina Poverty Analysis Workshop September 17-21, 2007

Topics Introduction 1.Aggregation Issues 2.Adjusting for differences across individuals a)Cost of living differences – across regions – over time b)Differences in household composition – economies of scale – equivalence scales Concluding Observations

2a. Differences in cost of living (across regions ) Price indices summarize prices in different locations. One can use existing regional Consumer Price Indices or construct such indices: 1.Specify a basket for which prices should be compared. The choice of basket depends on the type of analysis: Basket for the poverty line Average quantities or values of selected food items in the country as a whole. Specific baskets for each region or each household.

Differences in cost of living (regions, cont. ) 2.Define “regions” for which indices are to be calculated (could be each entity; or could be larger groups such as urban North, urban South, rural North, rural South). 3.Calculate the cost of the basket for each region, using average prices observed in the region (either from household consumption data, or from community data which collects local level price information). Also calculate the national cost, with averages.

Differences in cost of living (regions, cont.) 4.Calculate the relative price index for each region, by taking the ratio of the regional index to the national index.

Differences in cost of living (over time) When comparing two points in time, similarly, indices are based on the cost of the same basket of goods over time. The choice of the basket can either be that of any period, depending on the analysis.

2b. Differences in household composition A series of issues arise when calculating the aggregate, related to both the size and the composition of households. For instance, 1. Does a household of 4 need twice as much as a household of 2? 2. Do two households with the same number of members, but different composition (e.g. one with 5 adult men, and the other one with one adult woman and 4 little children) need the same amount to reach a certain level of welfare? Some form of “normalization” should be used to allow comparison of households, in light of both size and composition.

Issue 1: Household size & economies of scale a: Some goods and services are shared between members, like public goods within the household. (e.g. heating, cooking oil, housing, transportation means, etc.). The shared goods within the household are the root of economies of scale. Question 1: Should we adjust the consumption or expenditure aggregate for household size, in order to be able to compare households and to compare the aggregate with the poverty line? Question 2: How to adjust?

Household size & economies of scale (cont.) Problem: Should we adjust for economies of scale? When a high share of budget is devoted to “private” goods, such as food, the scope for economies of scale is small. When a high share of budget is devoted to “public” goods (if price and quantity of housing, utilities, durable goods are high), economies of scale are likely to be larger.

Household size & economies of scale (cont.)  Look at the shares in the data, and decide whether to adjust. Note that in poorer countries, the economies of scale tend to be very small and no adjustments are usually made for economies of scale. Note that, when not adjusting, one might overestimate the poverty of large households and underestimate that of small households. Need for sensitivity analysis

Household size & economies of scale (cont.) Solution: How to adjust for economies of scale? If no adjustments are to be made for economies of scale, divide the total household consumption or expenditure by the number of members. Total consumption is assumed to be equally divided, with no ‘gains’ from sharing consumption.  This is typically preferred in low or middle income countries.

Household size & economies of scale (cont.) If adjustments are to be made, then, one can divide the total consumption of expenditure by N , where  takes a value between 0 and 1. 0 if all goods consumed are public in the household, in which case each individual is assumed to consume the total consumption of the household 1 if we assume that no goods consumed are public in the household, in which case we fall back on the previous case.

Issue 2: Household composition & equivalence scales Problem: It is usually assumed that children and the elderly need less than working age adults. Similarly, it is sometimes considered that women need less consumption than men. Question 1: Should we adjust the consumption or expenditure aggregate for household composition in order to compare households and to compare the aggregate with the poverty line? Question 2: How to adjust?

Household composition (equivalence scales) Solution: Should we adjust for household composition? If children/elderly are as “expensive” as adults despite their lower nutritional requirement (e.g. because of very high costs for education or health), less need for adjustment. If a high share of the expenses go to goods that are needed by all in the same quantity (heat, housing, etc.), less need for adjustment. If a high share of the expenses go to goods that are needed in different quantities, more need for adjustment.

Household composition (equivalence scales)  Look at the information available and decide whether to adjust.  Note that in low-income countries, the differences in needs tend to be higher than in high or middle income countries. Note that, when not adjusting, one might overestimate the poverty of households with numerous children and underestimate that of households with few children. Need for sensitivity analysis

Household composition (equivalence scales) Solution: How to adjust? If no adjustments are to be made for differences in need, then simply divide the total household consumption or expenditure by the number of members. Total consumption is assumed to be equally divided, with all members having the same gains.

Household composition (equivalence scales) If adjustments are to be made, one uses equivalence scales. The scales calculates the number of “equivalent adult” in the household. One then divides the total consumption by the “number of adult equivalent”. One can decide on the different categories and calculate the “weight” given to each category on different basis. An equivalence scale typically looks like:

Household size and composition: Summary There are also scales that take both household size and household composition into account. An example is the OECD scale. The first adult is given a weight of 1. The other adults are given a weight of 0.7, to reflect economies of scale. Children are given a weight of 0.5 to reflect their presumably lower needs.

Equivalence scales in practice Several choices: Normative (e.g., nutritionists) Empirical (subjective/ behavioral) Arbitrary (e.g., administrative, per capita)

Equivalence scales - empirical The general formula N = (A+  *C)  where A is the number of adults in the household, K is the number of children,  is the cost of children relative to an adult and  is the economies of scale parameter

Equivalence scales – empirical To estimate economies of scale: Behavioral - Lanjouw and Ravallion based on the distinction between public and private goods within the household: x/n  =  *x/n + (1-  )*x The average welfare is the weighted sum of two parts: (a) average consumption of private goods, rival in consumption; and (b) total consumption of public goods, non-rival in consumption. Solving for , the equation becomes:  = -ln(1-  +  /n)/ln(n)

Equivalence scales – empirical To estimate the cost of children relative to adults: Rothbarth - households with the same level of per adult expenditures on goods consumed only by adults are equally well- off

Concluding Observations 1.Sensitivity Analysis: Are conclusions robust to choices made? (components of consumption, cost of living adjustments, equivalence scales? etc.) 2.Supplementary Indicators: Non-income measures (e.g. health status, education, access to services, empowerment, etc.)