Identification Using Revealed Preferences in Linearly Separable Models

Working Paper: NBER ID: w31868

Authors: Nikhil Agarwal; Pearl Z. Li; Paulo J. Somaini

Abstract: Revealed preference arguments are commonly used when identifying models of both single-agent decisions and non-cooperative games. We develop general identification results for a large class of models that have a linearly separable payoff structure. Our model allows for both discrete and continuous choice sets. It incorporates widely studied models such as discrete and hedonic choice models, auctions, school choice mechanisms, oligopoly pricing and trading games. We characterize the identified set and show that point identification can be achieved either if the choice set is sufficiently rich or if a variable that shifts preferences is available. Our identification results also suggests an estimation approach. Finally, we implement this approach to estimate values in a combinatorial procurement auction for school lunches in Chile.

Keywords: No keywords provided

JEL Codes: C51; C57


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
rich choice set (D10)identification of payoffs (C72)
observable variable that shifts preferences (D11)identification of payoff distribution (D39)
rich choice set (D10)unique optimal choices for different payoff types (C72)
identification of payoffs (C72)tracing the distribution of payoffs based on observed actions (D39)
identified set of distributions (C46)inform estimation approaches (C51)
revealed preferences (D11)identification of payoffs in economic decision-making (D91)

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