2019
DOI: 10.1007/s00181-019-01716-2
|View full text |Cite
|
Sign up to set email alerts
|

Identification and decompositions in probit and logit models

Abstract: Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Founda… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
1
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
4

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 11 publications
0
1
0
Order By: Relevance
“…Previous studies using the Findex dataset supported the appropriate distribution of the data to be estimated with probit regressions (Zins & Weill, 2016). While a complete decomposition of the differences across groups based on sample proportions offers a more precise approach (Choe, Jung, & Oaxaca, 2020), the model and variables used do not impose restrictions to use a probit model. The dependent variable (x i ) takes values of one or zero for the different models (e.g., access to finance, perception of barriers, source of finance, among the four others).…”
Section: Methodsmentioning
confidence: 99%
“…Previous studies using the Findex dataset supported the appropriate distribution of the data to be estimated with probit regressions (Zins & Weill, 2016). While a complete decomposition of the differences across groups based on sample proportions offers a more precise approach (Choe, Jung, & Oaxaca, 2020), the model and variables used do not impose restrictions to use a probit model. The dependent variable (x i ) takes values of one or zero for the different models (e.g., access to finance, perception of barriers, source of finance, among the four others).…”
Section: Methodsmentioning
confidence: 99%
“…8 The parameters of the utility functions are identified up to the usual scale normalization (Choe et al (2020)).…”
Section: Multivariate Binary Field Choicementioning
confidence: 99%