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14.32 Econometrics, Spring 2003

Author(s)
Angrist, Joshua David
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Download14-32Spring-2003/OcwWeb/Economics/14-32EconometricsSpring2003/CourseHome/index.htm (12.79Kb)
Alternative title
Econometrics
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Usage Restrictions: This site (c) Massachusetts Institute of Technology 2003. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license"). The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions.
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Abstract
Introduction to econometric models and techniques, emphasizing regression. Advanced topics include instrumental variables, panel data methods, measurement error, and limited dependent variable models. Includes problem sets. May not count toward HASS requirement. From the course home page: Course Description This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects. Topics include statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and the evaluation of government policies and programs.
Date issued
2003-06
URI
http://hdl.handle.net/1721.1/39818
Department
Massachusetts Institute of Technology. Department of Economics
Other identifiers
14.32-Spring2003
local: 14.32
local: IMSCP-MD5-702c8593ad786e98f8e702cb905f1ee9
Keywords
probability, distribution, sampling, confidence intervals, bivariate regression, residuals, fitted values, multivariate regression, heteroscedasticity, linear probability models, serial correlation, measurement error, goodness of fit

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