Estimating food demand and the impact of market shocks on food expenditures: The case for the Philippines and missing price data

Harold Glenn Valera, Joaquin Mayorga, Valerien O. Pede, Ashok K. Mishra

Research output: Contribution to journalArticlepeer-review

Abstract

This study uses the Quadratic Almost Ideal Demand System to estimate food demand among Filipino households. Our study uses the recently released 2018 Family Income and Expenditure Survey and the Stone-Lewbel price index in the absence of price data on food groups. Results show that demand for rice with respect to prices and expenditures is relatively inelastic compared with that for other food groups. The income elasticity for rice is inelastic (0.26), slightly higher than the income elasticity for sugar. Demand for rice is generally less elastic for higher-income Filipinos and families residing in urban areas than for their counterparts. The findings reveal that, in the short term, a 15 per cent decrease in income or a 20 per cent increase in rice prices induces families to spend more of their income on rice at the expense of other cereals, meat, fish, and other food groups. Income and rice price shocks have differential impacts on low-income and high-income Filipino families. Policymakers may be able to moderate the food price impacts of market shocks through targeted interventions and programs that improve the accessibility to and availability of quality agri-fishery products.

Original languageEnglish (US)
Article numberqoac030
JournalQ Open
Volume2
Issue number2
DOIs
StatePublished - 2022
Externally publishedYes

Keywords

  • Demand analysis
  • Expenditure elasticity
  • Income categories
  • Income elasticity
  • QUAIDS
  • Stone-Lewbel prices

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Economics and Econometrics
  • Agricultural and Biological Sciences (miscellaneous)
  • Food Science
  • Development

Fingerprint

Dive into the research topics of 'Estimating food demand and the impact of market shocks on food expenditures: The case for the Philippines and missing price data'. Together they form a unique fingerprint.

Cite this