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. 2009 Feb 17;106(7):2114-7.
doi: 10.1073/pnas.0810016106. Epub 2009 Jan 21.

Market forces affect patterns of polygyny in Uganda

Affiliations

Market forces affect patterns of polygyny in Uganda

Thomas V Pollet et al. Proc Natl Acad Sci U S A. .

Abstract

Polygynous marriage is generally more beneficial for men than it is for women, although women may choose to marry an already-married man if he is the best alternative available. We use the theory of biological markets to predict that the likelihood of a man marrying polygynously will be a function of the level of resources that he has, the local sex ratio, and the resources that other men in the local population have. Using records of more than 1 million men in 56 districts from the 2002 Ugandan census, we show that polygynously married men are more likely to own land than monogamously married men, that polygynous marriages become more common as the district sex ratio becomes more female biased, that owning land is particularly important when men are abundant in the district, and that a man's owning land most increases the odds of polygyny in districts where few other men own land. Results are discussed with reference to models of the evolution of polygyny.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Predicted proportions of men marrying polygynously by individual land ownership and the OSR of the district. The units of the horizontal axis are SDs of the district OSR, thus 0 represents an average district sex ratio, 1 represents an SD more men than average, and −1 an SD fewer men than average. All other variables are set to the mean.
Fig. 2.
Fig. 2.
Predicted ratio of polygynously married landowners to polygynously married landless men, as the proportion of landowners in the district varies. The units of the horizontal axis are SDs of the district proportion of men owning land, thus 0 represents an average district, 1 represents an SD more landowners than average, and −1 an SD fewer landowners than average. All other variables are set to the mean.

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