Essays On Identification Estimation And Inference Of Economic Models With Testable Assumptions
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Essays on Identification, Estimation and Inference of Economic Models with Testable Assumptions
I study identification, estimation, and hypothesis testing in complete and incomplete economic models with testable assumptions. Testable assumptions ($A$) give strong and interpretable empirical content to the model but they also carry the possibility that some distribution of observed outcomes may reject these assumptions. A natural way to avoid this is to find a set of relaxed assumptions ($\tilde{A}$) that cannot be rejected by any distribution of observed outcomes and such that the identified set for the parameter of interest is not changed when the original assumption holds. The main contribution of this thesis is to characterize the properties of such a relaxed assumption $\tilde{A}$ using notions of refutability and confirmability. In Chapter 1, I establish the theoretical framework for analyzing econometric structures and econometric assumptions. This framework unifies the theory of identification of complete economic structures and the theory of refutability. I propose a general method to construct such $\tilde{A}$. A general estimation and inference procedure is proposed and can be applied to a large class of incomplete economic models. I apply my methodology to the instrument monotonicity assumption in Local Average Treatment Effect (LATE) estimation and to the sector selection assumption in a binary outcome Roy model of employment sector choice. In the LATE application, I use my general method to construct a set of relaxed assumptions $\tilde{A}$ that can never be rejected, and the identified set for LATE is unchanged when $A$ holds. LATE is point identified under my extension $\tilde{A}$ in the application. I also provide an estimation and inference method on the LATE value. In Chapter 2, I generalize the framework to incomplete economic structures. I show that the general method for constructing a relaxed assumption in Chapter 1 may fail to work in incomplete economic structures. Therefore, I propose a completion procedure that is without loss of generality. With this completion procedure, we can get completed economic structures, and the method in Chapter 1 can be applied. I then look at the application to a binary outcome Roy model. I use my method to relax Roy's sector selection assumption and characterize the identified set for the binary potential outcomes as a polyhedron. In Chapter 3, I propose a dilation estimation and inference method that can be applied to a wide class of complete and incomplete economic structures. My method can easily deal with an observed variable that is of dimension greater than two.
Essays in Honor of Joon Y. Park
Author: Yoosoon Chang
language: en
Publisher: Emerald Group Publishing
Release Date: 2023-04-24
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Identification and Inference for Econometric Models
Author: Donald W. K. Andrews
language: en
Publisher: Cambridge University Press
Release Date: 2005-07-04
This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.