Aggregarion Without the Aggravation? Nonparametric Analysis of the Representative Consumer

AbstractWe critically assess the representative consumer with quadratic aggregate utility function which forms the foundation of a well-known class of linear oligopoly demand structures. It is argued that this approach is problematic and redundant. Regarding the latter, we show how the same demand system can be derived directly from a population of heterogeneous buyers for any number of products. Welfare analyses based on aggregate demand is shown to be sensitive to the underlying microfoundation.

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Cost efficiency in the US steel industry: A nonparametric analysis using data envelopment analysis

European Journal of Operational Research ◽

10.1016/0377-2217(94)00143-z ◽

1995 ◽

Vol 80 (3) ◽

pp. 654-671 ◽

Cited By ~ 21

Author(s):

Subhash C. Ray ◽

Hiung Joon Kim

Keyword(s):

Data Envelopment Analysis ◽

Steel Industry ◽

Cost Efficiency ◽

Nonparametric Analysis ◽

Data Envelopment ◽

The Us ◽

Using Data

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Nonparametric Analysis of Time-Inconsistent Preferences

The Review of Economic Studies ◽

10.1093/restud/rdaa089 ◽

2021 ◽

Author(s):

Laura Blow ◽

Martin Browning ◽

Ian Crawford

Keyword(s):

Sufficient Conditions ◽

Revealed Preference ◽

Hyperbolic Discounting ◽

Time Preferences ◽

Hyperbolic Model ◽

Nonparametric Analysis ◽

Time Horizons ◽

Time Inconsistent ◽

Using Data ◽

Necessary And Sufficient

Abstract This paper provides a revealed preference characterisation of quasi-hyperbolic discounting which is designed to be applied to readily-available expenditure surveys. We describe necessary and sufficient conditions for the leading forms of the model and also study the consequences of the restrictions on preferences popularly used in empirical lifecycle consumption models. Using data from a household consumption panel dataset we explore the prevalence of time-inconsistent behaviour. The quasi-hyperbolic model provides a significantly more successful account of behaviour than the alternatives considered. We estimate the joint distribution of time preferences and the distribution of discount functions at various time horizons.

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