Estimating Dynamic Probit Models with Higher-order Time- and Network-lag Structure and Correlated Random Effects
Peter H. Egger () and
Michaela Kesina ()
Additional contact information
Peter H. Egger: ETH Zurich
Michaela Kesina: University of Groningen
A chapter in Seven Decades of Econometrics and Beyond, 2025, pp 233-260 from Springer
Abstract:
Abstract Many strategic choices in the social sciences involve sluggish adjustment with an ex-ante unknown lag structure as well as patterns of interdependency among the cross-sectional units, which call for a flexible parameterization based on multiple networks. This chapter proposes straightforward panel-probit estimation approaches based on control functions for such problems. The paper outlines the estimation approaches and illustrates their suitability by simulation examples.
Date: 2025
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:adschp:978-3-031-92699-0_8
Ordering information: This item can be ordered from
http://www.springer.com/9783031926990
DOI: 10.1007/978-3-031-92699-0_8
Access Statistics for this chapter
More chapters in Advanced Studies in Theoretical and Applied Econometrics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().