tailieunhanh - Handbook of Econometrics Vols1-5 _ Chapter 43

Chapter 43 ANALOG ESTIMATION OF ECONOMETRIC Suppose that one wants to estimate a parameter characterizing some feature of a specified population. One has some prior information about the population and a random sample of observations. | Chapter 43 ANALOG ESTIMATION OF ECONOMETRIC MODELS CHARLES F. MANSKI University of Wisconsin-Madison Contents Abstract 2560 1. Introduction 2560 2. Preliminaries 2561 . The analogy principle 2561 . Moment problems 2563 . Econometric models 2565 3. Method-of-moments estimation of separable models 2566 . Mean independence 2567 . Median independence 2568 . Conditional symmetry 2569 . Variance independence 2570 . Statistical independence 2570 . A historical note 2571 4. Method-of-moments estimation of response models 2571 . Likelihood models 2572 . Invertible models 2574 . Mean independent linear models 2574 . Quantile independent monotone models 2575 5. Estimation of general separable and response models 2577 . Closest-empirical-distribution estimation of separable models 2577 . Minimum-distance estimation of response models 2580 6. Conclusion 2581 References 2581 I am grateful for the comments of Rosa Matzkin and Jim Powell. Handbook of Econometrics Volume IV Edited by . Engle and . McFadden 1994 Elsevier Science . All rights reserved 2560 . Manski Abstract Suppose that one wants to estimate a parameter characterizing some feature of a specified population. One has some prior information about the population and a random sample of observations. A widely applicable approach is to estimate the parameter by a sample analog that is by a statistic having the same properties in the sample as the parameter does in the population. If there is no such statistic then one may choose an estimate that in some well-defined sense makes the known properties of the population hold as closely as possible in the sample. These are analog estimation methods. This chapter surveys some uses of analog methods to estimate two classes of econometric models the separable and the response models. 1. Introduction Suppose that one wants to estimate a parameter characterizing some feature of a specified population. One has some prior .