Non-Parametric Demand Analysis with an Application to the Demand for Fish
49 Pages Posted: 20 May 2005 Last revised: 29 Jun 2023
Date Written: April 1995
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.
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
By Joshua D. Angrist and Alan B. Krueger
-
How Large are the Social Returns to Education? Evidence from Compulsory Schooling Laws
By Daron Acemoglu and Joshua D. Angrist
-
Workers' Compensation and Injury Duration: Evidence from a Natural Experiment
By Bruce D. Meyer, W. Kip Viscusi, ...
-
Can Higher Cigarette Taxes Improve Birth Outcomes?
By William N. Evans and Jeanne S. Ringel
-
Hierarchical Bayes Models with Many Instrumental Variables
By Gary Chamberlain and Guido W. Imbens
-
The Effects of Unemployment Insurance Taxes and Benefits on Layoffs Using Firm and Individual Data
-
Labor Retrenchment Laws and Their Effect on Wages and Employment: A Theoretical Investigation
By Kaushik Basu, Gary Fields, ...
-
By Kaushik Basu, Gary Fields, ...