Download or read book Three Essays on Instrumental Variables Estimators written by Rodrigo A. Alfaro and published by . This book was released on 2008 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: This dissertation is a collection of three independent essays in theoretical and applied econometrics, organized in the form of three chapters. In the first chapter, I analyze the properties of the Symmetrically Normalized Instrumental Variables estimator (SN1V), proposed by Alonso-Borrego and Arellano (1999), using Edgeworth expansions. I find that this estimator is second order biased. In an empirical application, I compare the results of SNIV with Two Stage Least Squares and Limited Information Maximum Likelihood estimators. The second chapter is an empirical application of a Dynamic Panel Data model with a large number of firms and periods. With a firm level panel data set from Chile, I estimate an investment equation using the Within Groups estimator as well as the Arellano and Bond (1991) Generalized Method of Moments estimator (AB/GMM). The specification of the equation follows Gilchrist and Himmelberg (1998), and the results show that investment is positively related to the marginal profit of capital and liquidity of the firms. Moreover, I generalize Lemma 2 in Alvarez and Arellano (2003), showing that when the maximum number of lags used as instruments is truncated, then the AB/GMM estimator is asymptotically unbiased. The third chapter studies the properties of Instrumental Variables Estimators in situations where the error terms are heteroskedastic and there are many instrumental variables. In particular, I compare the performance of the Robust Limited Information Maximum Likelihood estimator proposed by Hausman, Newey, Woutersen, Chao and Swanson (2007) with the robust version of the Jackknife Instrumental Variable Estimator proposed by Angrist, Imbens and Krueger (1999). Theoretical results are presented for the robust t -statistics.