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How to Collect Individual A sset data? Implications for Data Collection

How to Collect Individual A sset data? Implications for Data Collection. Gero Carletto DECPI. On selection of respondents …. It makes a difference! Truth? Measurement error? Different respondent or same twice (tables 4a and 4b) Principal respondent: Best informed

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How to Collect Individual A sset data? Implications for Data Collection

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  1. How to Collect Individual Asset data? Implications for Data Collection GeroCarletto 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

  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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