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Cited by 374

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Domestic Violence: A Nonrandom Affair

Tauchen, Helen V., Witte, Ann Dryden, Long, Sharon K.·1991·International Economic Review
DOI 10.2307/2526888
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Abstract

In this paper, we develop and estimate a model of violence between romantically linked men and women.Physical violence is viewed as both a source of direct gratification and as an instrument for controlling the victim's behavior.Our model is a Stackleberg type model in which the assailant maximizes expected utility subject to the stochastic reaction function of the victim.Our model is estimated by a bounded-influence regression technique because the process generating violence appears to lead to a heavy-tailed error distribution.Our empirical results suggest that increases in the assailants (i.e. the male's) income serve to increase violence, while increases in the proportion of the year that he is employed serve to decrease violence.Further, the employment effect is larger than the income effect.y way of contrast, our results suggest that the effect of a change in the female's employment or income depends heavily on her economic status relative to the male's.Finally,we find that improvements in the female's opportunites outside the relationship significantly reduce the level of violence.

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Metadata

Authors
Tauchen, H. V., Witte, A. D., & Long, S. K.
Venue
International Economic Review
Publisher
JSTOR
Published
1991-05
Volume
32
Issue
2
Pages
491
ISSN
0020-6598 (ISSN-L)
DOI
10.2307/2526888
OpenAlex
W2090683361
Cited by
374
References
15
FWCI
4.53
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Domestic Violence: A Nonrandom Affair. https://app.cochat.ai/papers/10.2307/2526888
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Tauchen, H. V., Witte, A. D., & Long, S. K. (1991). Domestic Violence: A Nonrandom Affair. International Economic Review. https://doi.org/10.2307/2526888

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.