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Replication Data for 'Does Rationing Increase Welfare?'

Version
1
Resource Type
Dataset : survey data
Creator
  • Gadenne, Lucie (University of Warwick)
Publication Date
2020-10-26
Free Keywords
Taxation; Development; Redistribution
Description
  • Abstract

    In many developing countries households can purchase limited quantities of good at a fixed subsidized price through ration shops. This paper asks whether the characteristics of developing countries explain why governments use such systems. I find an equity-efficiency trade-off: an efficiency-maximizing government will never use ration shops but a welfare-maximizing one might, to redistribute and provide insurance. Welfare gains of ration shops will be highest for necessity goods and goods with high price risk. I calibrate the model for India and find that ration shops are welfare improving for three of the four goods sold through the system today.
  • Weighting

    See http://catalog.ihsn.org/index.php/catalog/3281
  • Methods

    Response Rates: See http://catalog.ihsn.org/index.php/catalog/3281
Temporal Coverage
  • 2011-01-01 / 2012-01-01
    Time Period: Sat Jan 01 00:00:00 EST 2011--Sun Jan 01 00:00:00 EST 2012 (2011-2012)
Geographic Coverage
  • India
Sampled Universe
Household_level_data contains household level data. The data is representative of all Indian households at the regional level.
District_levels contains district level data.
Sampling
See http://catalog.ihsn.org/index.php/catalog/3281
Availability
Download
This study is freely available to the general public via web download.
Relations
  • Is version of
    DOI: 10.3886/E115209
Publications
  • Gadenne, Lucie. “Can Rationing Increase Welfare? Theory and An Application to India’s Ration Shop System.” American Economic Journal: Economic Policy, n.d.

Update Metadata: 2020-10-26 | Issue Number: 1 | Registration Date: 2020-10-26

Gadenne, Lucie (2020): Replication Data for 'Does Rationing Increase Welfare?'. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E115209V1