Econometric Analysis

Jean-Michel Josselin and Benoît Le Maux
Additional contact information
Jean-Michel Josselin: University of Rennes 1
Benoît Le Maux: University of Rennes 1

Chapter 5 in Statistical Tools for Program Evaluation, 2017, pp 137-187 from Springer

Abstract: Abstract Econometrics encompasses several multivariate tools for testing a theory or hypothesis, quantifying it and providing indications about the evolution of an outcome of interest. This chapter gives the basic knowledge on how those tools work, with examples and the corresponding R-CRAN codes. The first step is dedicated to simple and multiple linear regression models and their estimation by the method of ordinary least squares (Sects. 5.1 and 5.2). The classical assumptions (e.g., linearity, normality of residuals, homoscedasticity, non-autocorrelation) underlying the method are exposed (Sect. 5.3). An important step in conducting an econometric analysis is model specification as it determines the validity of the regression analysis (Sect. 5.4). Another issue is the choice of the functional form that best fits the data, i.e. whether the variables are expressed or not in a non-linear form (Sect. 5.5). Several tests also exist to detect potential misspecifications (Jarque-Bera, Breusch-Pagan, and Durbin-Watson tests) which are fully detailed (Sect. 5.6). Last, the selection of the final model relies on a meticulous examination of regression outputs, e.g., whether the variables sufficiently explain the outcome of interest (Sect. 5.7). Methods are then extended to the case where the latter is binary (Sect. 5.8), the so-called logit and probit models.

Keywords: Regression; Ordinary least squares; Residuals; Misspecification; Logit; Probit (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-52827-4_5

Ordering information: This item can be ordered from
http://www.springer.com/9783319528274

DOI: 10.1007/978-3-319-52827-4_5

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().