EconPapers    
Economics at your fingertips  
 

Heterogeneity in food expenditure among US families: evidence from longitudinal quantile regression

Arjun Gupta (), Soudeh Mirghasemi () and Mohammad Arshad Rahman ()
Additional contact information
Arjun Gupta: Indian Institute of Technology, Kanpur
Soudeh Mirghasemi: Hofstra University

Indian Economic Review, 2021, vol. 56, issue 1, No 2, 25-48

Abstract: Abstract Empirical studies on food expenditure are largely based on cross-section data and for a few studies based on longitudinal (or panel) data the focus has been on the conditional mean. While the former, by construction, cannot model the dependencies between observations across time, the latter cannot look at the relationship between food expenditure and covariates (such as income, education, etc.) at lower (or upper) quantiles, which are of interest to policymakers. This paper analyzes expenditures on total food (TF), food at home (FAH), and food away from home (FAFH) using mean regression and quantile regression models for longitudinal data to examine the impact of economic recession and various demographic, socioeconomic, and geographic factors. The data are taken from the Panel Study of Income Dynamics (PSID) and comprise of 2174 families in the United States (US) observed between 2001 and 2015. Results indicate that age and education of the head, family income, female-headed family, marital status, and economic recession are important determinants for all three types of food expenditure. Spouse education, family size, and some regional indicators are important for expenditures on TF and FAH, but not for FAFH. Quantile analysis reveals considerable heterogeneity in the covariate effects for all types of food expenditure, which cannot be captured by models focused on conditional mean. The study ends by showing that modeling conditional dependence between observations across time for the same family unit is crucial to reducing/avoiding heterogeneity bias and better model fitting.

Keywords: Bayesian quantile regression; Great Recession; Heterogeneity bias; Longitudinal data; Mixed-effects; Mortgage (search for similar items in EconPapers)
JEL-codes: C11 C31 C33 D10 D12 R20 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s41775-020-00101-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
Working Paper: Heterogeneity in Food Expenditure amongst US families: Evidence from Longitudinal Quantile Regression (2020) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:inecre:v:56:y:2021:i:1:d:10.1007_s41775-020-00101-6

Ordering information: This journal article can be ordered from
https://www.springer.com/economics/journal/41775

DOI: 10.1007/s41775-020-00101-6

Access Statistics for this article

Indian Economic Review is currently edited by Uday Bhanu Sinha, Abhijit Banerji, Shreekant Gupta and J.V. Meenakshi

More articles in Indian Economic Review from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2022-09-06
Handle: RePEc:spr:inecre:v:56:y:2021:i:1:d:10.1007_s41775-020-00101-6