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Counterfactual and Welfare Analysis with an Approximate Model

Roy Allen, John Rehbeck

arXiv 7 Sep 2020 · Econometrics · 3 citations (OpenAlex)

arXiv:2009.03379 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose a conceptual framework for counterfactual and welfare analysis for approximate models. Our key assumption is that model approximation error is the same magnitude at new choices as the observed data. Applying the framework to quasilinear utility, we obtain bounds on quantities at new prices using an approximate law of demand. We then bound utility differences between bundles and welfare differences between prices. All bounds are computable as linear programs. We provide detailed analytical results describing how the data map to the bounds including shape restrictions that provide a foundation for plug-in estimation. An application to gasoline demand illustrates the methodology.

Citation extraction

69
references
128
in-text mentions
69
distinct cited
3
self-citations
13,525
main-text words

appendix boundary found by appendix_command · 47% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Richard Blundell, Joel L Horowitz, and Matthias Parey (2012) Measuring the price responsiveness of gasoline demand: Economic shape restrictions and nonparametric demand estimation0.874122100%
2Roy Allen and John Rehbeck (2020) Satisficing, aggregation, and quasilinear utility self0.84315960%
3Roy Allen and John Rehbeck (2019) Identification with additively separable heterogeneity self0.8435360%
4Herbert A Simon (1947) Administrative Behavior0.84333100%
5Hal R Varian (1990) Goodness-of-fit in optimizing models0.6444250%
6Raj Chetty (2012) Bounds on elasticities with optimization frictions: A synthesis of micro and macro evidence on labor supply0.64422100%
7Matthew Masten and Alexandre Poirier (2019) Inference on breakdown frontiers0.64422100%
8Daniel McFadden (1981) Econometric models of probabilistic choice0.64422100%
9Hal R Varian (1982) The nonparametric approach to demand analysis0.58531100%
10K Chiong, YW Hsieh, and Matthew Shum (2017) Counterfactual estimation in semiparametric discrete choice models0.5113233%

Showing the top 10 of 69 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Consumer Welfare Under Individual Heterogeneity0.40511