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Testing the Infrequent Purchases Model Using Direct Measurement of Hidden Consumption from Food Stocks

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  • John Gibson
  • Bonggeun Kim

Abstract

Survey reports of zero expenditure result from either genuine non-consumption, or purchases undertaken too infrequently to observe during a survey, with hidden consumption from stocks. Infrequent purchase models rely on untested hypotheses to distinguish these types of zeros. We test such models with data from an unusual survey where food stocks are measured at the start and end of the survey reference period. Parameter estimates using these direct measures of hidden consumption out of stocks are compared with estimates from infrequent purchase models that attempt to recover this hidden consumption. The results suggest considerable bias when using the infrequent purchase models. Copyright 2012, Oxford University Press.

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Bibliographic Info

Article provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.

Volume (Year): 94 (2012)
Issue (Month): 1 ()
Pages: 257-270

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Handle: RePEc:oup:ajagec:v:94:y:2012:i:1:p:257-270

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Cited by:
  1. Bardsley, Nicholas & Buechs, Milena, 2013. "Exploiting Zero-Inflated Consumption Data using Propensity Score Matching and the Infrequency of Purchase Model, with Application to Climate Change Policy," MPRA Paper 48727, University Library of Munich, Germany.
  2. De Weerdt, Joachim & Beegle, Kathleen & Friedman,, Jed & Gibson, John, 2014. "The challenge of measuring hunger," Policy Research Working Paper Series 6736, The World Bank.
  3. Buchs, Milena & Schnepf, Sylke V., 2013. "UK Households' Carbon Footprint: A Comparison of the Association between Household Characteristics and Emissions from Home Energy, Transport and Other Goods and Services," IZA Discussion Papers 7204, Institute for the Study of Labor (IZA).
  4. Leffler, Kristyn K. & Carpio, Carlos E. & Boonsaeng, Tullaya, 2012. "Temporal Aggregation and Treatment of Zero Dependent Variables in the Estimation of Food Demand using Cross-Sectional Data," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124913, Agricultural and Applied Economics Association.

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