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: 34 Survey 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. RIGA Issues and Lessons Learned Income Estimation

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

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. Total Household Income Agwage Nonagwage Crop Livestock Selfemp TransferOther On-farm Agricultural 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. RIGA 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 frequency of 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. RIGA Lessons Learned From Key RIGA Results

16. RIGA Results: Main Components of Rural Household Income  For 9 out of the 16 countries analyzed, agriculture is the major source of income (ag wage labour + crop + livestock)  However, share of rural non-agricultural income rises with GDP  Off-farm income account for 50% in Latin America, Eastern-Europe and Asia (except Viet Nam).  On-farm income tends to be more important for the African countries.

17. RIGA Results: Main Components of Rural Household Income

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

19. 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

20. Rural income diversification is the trend

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

22. 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

23. Lessons Learned: Definition of “Rural” Issues:  Lack of a cross-country comparable definition of “rural”  Rural Household vs. Location of Job RIGA uses survey-specific definition because it:  reflects local information about what constitutes “rural”  is used to administer government programs

24. RIGA Results: S ensitivity and Criteria in Agricultural Households Definition Source: Aksoy, et al. (2009)

25. 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 frequency of 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

26. Thank You! Questions?