Non-Parametric Demand Analysis with an Application to the Demand for Fish

Joshua Angrist, Kathryn Graddy () and Guido Imbens

No 178, NBER Technical Working Papers from National Bureau of Economic Research, Inc

Abstract: Instrumental variables (IV) estimation of a demand equation using time series data is shown to produce a weighted average derivative of heterogeneous potential demand functions. This result adapts recent work on the causal interpretation of two-stage least squares estimates to the simultaneous equations context and generalizes earlier research on average derivative estimation to models with endogenous regressors. The paper also shows how to compute the weights underlying IV estimates of average derivatives in a simultaneous equations model. These ideas are illustrated using data from the Fulton Fish market in New York City to estimate an average elasticity of wholesale demand for fresh fish. The weighting function underlying IV estimates of the demand equation is graphed and interpreted. The empirical example illustrates the essentially local and context-specific nature of instrumental variables estimates of structural parameters in simultaneous equations models.

JEL-codes: C30 L66 (search for similar items in EconPapers)
Date: 1995-04
Note: LS
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Published as Review of Economic Studies, Vol. 67, No. 3, pp. 499-527, July 2000.

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