Nonparametric Approaches to Empirical Welfare Analysis.

Welfare analysis of policy interventions is ubiquitous in economic research. It plays an important role in merger analysis and antitrust litigation, design of tax and subsidies, and informs the current debate on a universal basic income. This paper provides a survey of existing empirical methods, ba...

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Publicado en:Journal of Economic Literature Vol. 62; no. 2; pp. 554 - 594
Autor principal: Bhattacharya, Debopam
Formato: Literature Review
Publicado: American Economic Association Jun2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2024
      vid: 62
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      pub: American Economic Association
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        177658369
        10.1257/jel.20221534
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      formats:
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        atl: Nonparametric Approaches to Empirical Welfare Analysis.
      aug:
        au: Bhattacharya, Debopam
        affil: University of Cambridge.
      su:
        Public welfare policy
        Subsidies
        Basic income
        Economic research
        Antitrust violation lawsuits
        Demand function
        Tax incentives
      sug:
        subj:
          Public welfare policy
          Subsidies
          Research and Development in the Social Sciences and Humanities
          Administration of Human Resource Programs (except Education, Public Health, and Veterans' Affairs Programs)
          Emergency and Other Relief Services
          Other Individual and Family Services
          Basic income
          Economic research
          Antitrust violation lawsuits
          Demand function
          Tax incentives
      ab: Welfare analysis of policy interventions is ubiquitous in economic research. It plays an important role in merger analysis and antitrust litigation, design of tax and subsidies, and informs the current debate on a universal basic income. This paper provides a survey of existing empirical methods, based on cross-sectional microdata, for calculating welfare effects and deadweight loss resulting from realized or hypothetical policy change. We briefly outline classical parametric methods that are computationally tractable, then discuss recent nonparametric approaches that avoid making statistical and functional-form restrictions on individual preferences. This makes the welfare estimates theoretically more credible, and clarifies exactly what welfare-relevant information is contained in demand distribution in various choice settings. However, these methods also demand greater in-sample variation in the data for practical implementation than classical parametric approaches. We then cover settings with externalities. The above results are theoretical, and take the demand function as known; therefore, we briefly discuss empirical problems around demand estimation. We conclude by suggesting areas for future research. (JEL C14, C35, D11, D60, D62)
      pubtype: Academic Journal
      doctype: Literature Review
      src: R
    language: English
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