Using Stata For Principles of Econometrics . Third Edition I ·1· I ! t . i: f‚ I Lee Adkins dedicates this work to his lovely and loving wife‚ Kathy ‚ Carter Hill dedicates this work to Stan Johnson and George Judge - ’ ‚ . Bicentennial Logo Design: Richard 1. Pacifico Copyright @ 2008 John Wiley & Sons‚ Inc. All rights reserved. No part of this publication may be reproduced‚ stored in a retrieval system or transmitted in any form or by any means‚ electronic‚ mechanical
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Introduction to Stata Christopher F Baum Faculty Micro Resource Center Boston College August 2011 Christopher F Baum (Boston College FMRC) Introduction to Stata August 2011 1 / 157 Strengths of Stata What is Stata? Overview of the Stata environment Stata is a full-featured statistical programming language for Windows‚ Mac OS X‚ Unix and Linux. It can be considered a “stat package‚” like SAS‚ SPSS‚ RATS‚ or eViews. Stata is available in several versions: Stata/IC (the standard
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BEDRIJFSKUNDE UNIVERSITEIT VAN AMSTERDAM Short Guide to Stata 1. Introduction This guide gives an overview of some basic commands of Stata. Stata contains many more commands. Some of these will be used in the computer exercises of Econometrics‚ but lots will not be used at all. With Stata you will be able to perform complex statistical and econometrical calculations and estimations. It is even possible to program your own routines. Below‚ Stata commands are set in lettertype Courier. Options are
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Question1 Equation1 We are interested in investigating the relationship between income among countries in trade liberalization period and not in trade liberalization period. This equation 1 accommodates different intercepts and slopes for years after and before trade liberalization. Sigma‚ is the standard deviation of the natural logarithm of real per worker income and t for year. Dr is dummy-variable regressor or an indicator variable‚ is coded 1 for all years after the trade liberalization
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ECON 140 Section 13‚ November 28‚ 2013 ECON 140 - Section 13 1 The IV Estimator with a Single Regressor and a Single Instrument 1.1 The IV Model and Assumptions Consider the univariate linear regression framework: Yi = β0 + β1 Xi + ui Until now‚ it was assumed that E (ui |Xi ) = 0‚ i.e. conditional mean independence. Let’s relax this assumption and allow the covariance between Xi and ui to be dierent from zero. Our problem here is that ui is not observed. Doing OLS
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Mostly Harmless Econometrics: An Empiricist’ Companion s Joshua D. Angrist Massachusetts Institute of Technology Jörn-Ste¤en Pischke The London School of Economics March 2008 ii Contents Preface Acknowledgments Organization of this Book xi xiii xv I Introduction 1 3 9 10 12 16 1 Questions about Questions 2 The Experimental Ideal 2.1 2.2 2.3 The Selection Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Random Assignment Solves the Selection
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Applied Econometrics Applied Econometrics Introduction Outline FEM11090-12 Applied Econometrics Nalan Basturk Erasmus University Rotterdam Econometric Institute basturk@ese.eur.nl http://people.few.eur.nl/basturk/ Introduction Course Introduction Course Organization Motivation Introduction Today Regression Linear Regression Ordinary Least Squares Linear regression model Gauss-Markov conditions and the properties of OLS estimators Example: individual wages Goodness-of-fit 1 / 42 2 / 42
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A brief overview of the classical linear regression model What is a regression model? Regression versus correlation Simple regression Some further terminology Simple linear regression in EViews -- estimation of an optimal hedge ratio The assumptions underlying the classical linear regression model Properties of the OLS estimator Precision and standard errors An introduction to statistical inference 27 27 28 28 37 2.6 2.7 2.8 2.9 v 40 43 44 46 51 vi Contents
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ECONOMETRICS Bruce E. Hansen c 2000‚ 20101 University of Wisconsin www.ssc.wisc.edu/~bhansen This Revision: January 10‚ 2010 Comments Welcome 1 This manuscript may be printed and reproduced for individual or instructional use‚ but may not be printed for commercial purposes. Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 1 Introduction 1.1 What is Econometrics? . . . . . . . . . . . . 1.2 The Probability
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ECO 1 chapter An overview of regression analysis Econometrics – literally ‚‚economic measurement” is the quantitative measurement and analysis of actual economic and business phenomena. Econometrics has three major uses: 1) Describing economic reality 2) Testing hypothesis about economic theory 3) Forecasting future economic activity The simplest use of econometrics is description. For most goods‚ the relationship between consumption and disposable income is expected
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