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How to Collect Individual Asset data? Implications for Data Collection Gero Carletto DECPI.

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Presentation on theme: "How to Collect Individual Asset data? Implications for Data Collection Gero Carletto DECPI."— Presentation transcript:

1 How to Collect Individual Asset data? Implications for Data Collection Gero Carletto DECPI

2 On selection of respondents … It makes a difference! Truth? Measurement error? Different respondent or same twice (tables 4a and 4b) Principal respondent: Best informed – For what? Implications for instrument/survey design of using different respondent for different item Secondary respondent: Spouse (if married), or another “well- informed” adult of opposite sex Analyze discrepancies bet/w spouses and “Well-informed” adult of different sex? Why differences across surveys? Karnakata: always head of household (blamed on training!) Who chooses respondent? Supervision? Controlling for “contamination” – Joint vs. separate, not clear cut – Metadata – Enumerator/supervisor fixed effects

3 On valuation of assets … Difficult, regardless … gross guesstimates, simply don’t know … Purchase price (how far back?) vs. WTP/WTA – Imputed values difficult (impossible?) in presence of no/thin market Implications of using GAG vs. GWG – Worth the trouble? – Alternative valuation methods? Financial Assets – High non-response and large under-reporting Feasible? – Requires high level of trust Implications for survey design and training – Exclude from GWG: implications?

4 Other issues … Collect detailed metadata on choice of respondent and interview – CAPI? Collecting changes in assets in panel data – Feed forward vs. no feed forward? Most assets jointly owned – Focus on fewer items? Perception vs. knowledge Implications of multiple respondents for survey design … and costs! – In LSMS tradition

5 Living Standards Measurement Study – Integrated Surveys on Agriculture 2009-2015 7 countries (Tanzania, Uganda, Ethiopia, Nigeria, Malawi, Niger and Mali) Panel multi-topic household surveys Best informed respondent Geo-referencing (hh and plots) Publicly-available microdata – geovariables CAPI

6 Survey Schedule Tanzania 2008/092010/112012/13 Uganda 2009/102010/112011/122012/132013/14 Malawi 2010/11 2012/13 Nigeria 2010/11 2012/13 Mali 2013/14 Ethiopia 2011/122013/14 Niger 2011/122013/14

7 LSMS-ISA: Collecting More Comprehensive & Standardized Individual-Disaggregated Data Agriculture – Ownership, Management vs. Control, Extension Livestock Source of income – Wage Employment – Non-Farm Self Employment – Social Assistance – Remittances – Other Income Asset Ownership – Land, and Ag/Lvst productive assets – Durables – No financial assets Access to credit


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