Accounting for the Diversity of Rural Income Sources in Developing Countries: The Experience of t h e RIGA Project

1. Accounting for the Diversity of Rural Income Sources in Developing Countries: The Experience of the RIGA Project Katia Covarrubias, Ana Paula de la O & Alberto Zezza ESA Wye City Group Meeting on Statistics on Rural Development and Agriculture Household Income Rome, June 11-12, 2009

2. The Rural Income Generating Activities Project • Database of 34 living standards surveys • Outputs: • Income Aggregates • Household Level Indicators • Access to capital • Demographic indicators • Additional analysis-specific indicators • Methodological Goal: Consistency and Comparability

3. RIGA Data: 34Survey Countries • Africa • Ghana GLSS (1992, 1998*) • Kenya KIHBS (2005) • Madagascar EPM (1993, 2001) • Malawi IHS (2004*) • Nigeria (2004*) • Asia • Bangladesh IHS (2000*, 2005) • Cambodia SES (2004) • Indonesia FLS (1992, 2000*) • Nepal LSS (1996, 2003*) • Pakistan HIES (1991, 2001) • Vietnam LSS (1992, 1998*, 2002*) • Eastern Europe/Central Asia • Albania LSMS (2002, 2005*) • Bulgaria IHS (1995, 2001*) • Tajikistan LSMS (2003*, 2007) • Latin America • Bolivia EH (2005) • Ecuador ECV (1995*, 1998) • Guatemala ENCOVI (2000*, 2006) • Nicaragua EMNV (1998*,2001*) • Panama ENV (1997, 2003*) * Labor Data also Available at the Individual and Job Levels

4. Income Aggregates: Defining Income Income must: • Occur regularly • Contribute to current economic well-being (available for current consumption) Income must not: • Arise from a reduction in current net-worth • Arise from an increase in household liabilities Source: ILO, Resolution I “Resolution concerning household income and expenditure statistics” Available from: http://www.ilo.org/public/english/bureau/stat/download/res/hiestat.pdf

5. Income Aggregates: Basic Characteristics • Household-level • Labor data also available at the Job and Individual levels • Annual • Wage income data: also for daily and monthly time frames • Net of costs • Purchases and sales of durables, investments and windfall gains excluded • Local currency units • Rural (and urban) • Outlier checks

6. Issues and Lessons Learned Income Estimation

7. Dependent Wage Income agricultural non-agricultural Independent Crop Livestock Self Employment Transfers public private Other Sources Components of Total Household Income

8. Total Household Income Classifications Total Income: Agricultural: Agwge + Crop + Livestock Non-agricultural: Nonagwge + Selfemp + Transfers + Other On-farm: Crop + Livestock Off-farm: Agwage + Nonagwge + Selfemp + Transfers + Other Non-farm: Nonagwge + Selfemp

9. Crop Agwage Livestock Transfer Other Nonagwage Selfemp Total Household Income Agricultural On-farm Off-farm Non-Agricultural Non-farm

10. Dealing with Costs Issue: Dealing with investment/durables expenditures • Misclassification: bias total income • Example: raw materials purchases (Albania; Vietnam) Recommendations: • Clear classification of costs in survey instrument • Appropriate choice of reference periods and frequencies

11. Gross versus Net Issue: Inconsistent reporting & estimation of gross/net income Recommendations: • In Qx: deductions and taxes should be asked about and reported • In income estimation: • Net: agricultural, self-employment and wage income • Gross: rental income and transfer income

12. Issues and Lessons Learned Questionnaire Design

13. Reference Periods Issue: Defining appropriate reference periods • Choice of Short v. Long • seasonal fluctuations • relevance to recall error • link to survey timing • phrasing of questions Recommendations: • Reference periods should reflect frequencyof Inc/Exp • Short: Regular or frequent sources (food exp, wages, etc.) • Long: Infrequent sources (business costs; ag inputs, etc.)

14. Units & Coding Issue: Comparability and Standardization of Units and Coding • Variability of unit reporting • Lack of equivalence scales in data and documentation • Inconsistency in units and codification of items across survey modules • Agricultural Production and Food Expenditure modules Recommendations: YES to local unit reporting but: • Inclusion of equivalence scales • Consistency in codification within/across survey modules

15. Lessons Learned From Key RIGA Results

16. RIGA Results: Main Components of Rural Household Income

17. On-farm income falls and Non-farm rises... ...with increasing per capita GDP levels.

18. RIGA Results:Diversification of Rural Household Income Defining Specialization and Diversification: • Specialization >= 75% • Diversification <75% Influenced by survey timing and reference period: • seasonal diversification • individuals member diversification

19. Rural income diversification is the trend

20. On-farm specialization falls with PCGDP ...but Non-agricultural wage specialization rises.

21. RIGA Results: Defining the Agricultural Household • “Rural” as “Agricultural” • lack of data to create comparable rural definition • urban agriculture • dwelling versus job location • diversity of rural economy • Thresholds of income • Non-zero (basic participation) • Higher cut-offs • Occupation of the household head

22. RIGA Results: Sensitivity and Criteria in Agricultural Households Definition Source: Aksoy, et al. (2009)

23. Summary and Conclusions • Estimation of Income • Various approaches for characterizing household income • Costs classification • Reporting of deductions/taxes relevant • Questionnaire Design: • Reference periods should reflect frequencyof income and expenditures • Need for equivalence scales/conversion factors • Unit and coding consistency within surveys. • Analysis: • Different definitions of agricultural household exist; generate differing characterization of results

24. Thank You!Questions?