Lecture

House Price Regressions: Exploring OLS Assumptions

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In course

FIN-403: Econometrics

The course covers basic econometric models and methods that are routinely applied to obtain inference results in economic and financial applications. ...

Description

This lecture delves into the practical aspects of using Ordinary Least Squares (OLS) regressions for house price analysis. Topics covered include interpreting linear models, handling outliers, assessing influential observations, model specification, and model selection strategies. The instructor demonstrates these concepts through a case study on house price regressions using Stata commands. Diagnostic tests such as RESET, VIF, DFBETA, and avplots are applied to evaluate model assumptions and performance. Additionally, the lecture discusses the importance of presenting regression results effectively, including regression tables and diagnostic plots.

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Instructor

Andreas Fuster

Andreas Fuster is an Associate Professor of Finance at Swiss Finance Institute @ EPFL and a Research Fellow at the CEPR. Previously, he worked at the Federal Reserve Bank of New York and the Swiss National Bank. Andreas's main research interests are in empirical finance, macroeconomics, and behavioral economics. His recent work has focused in particular on the effects of technological advances on household credit markets. Andreas’s research has been published in academic journals such as the Quarterly Journal of Economics, the Review of Economic Studies, the Journal of Finance, and the Review of Financial Studies. Andreas obtained his Ph.D. from Harvard University and also holds an M.Phil. from Oxford University and a B.A. from the University of Lausanne (Switzerland), all in economics.

Official source

Ontological neighbourhood

Statistics

Data analysis: Regression analysis

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Nonlinear regression

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