The present study builds upon Rudmin's 1992a publication by using a second data base to replicate and evaluate analyses on the cross-cultural correlates of private property ownership. Rudmin seeks to assess the reliability of Swanson's (1966) data base of 39 variables coded on 50 cultures. To do so, Swanson's data was evaluated against matching societies and variables from Murdock's (1967) Ethnographic Atlas. Swanson's reliable variables are tested against three measures of property ownership, one from Swanson and two from Murdock. Rudmin discusses results and speculates why certain clusters of societal variables correlate with private property ownership.

The present study aims to assess the reliability of Simmons' (1937) database of 109 variables coded for 71 societies. Simmons' data was evaluated against matching societies and variables from Murdock's (1967) Ethnographic Atlas. The ultimate purpose of Rudmin's analysis is to identify the features of societies that are correlated with the private ownership of property. To do so, Simmons' reliable variables are tested against four measures of property ownership, two from Simmons and two from Murdock. Rudmin discusses results and speculates why certain clusters of societal variables correlate with private property ownership.

The present study aims to evaluate correlations of private property from two of Murdock's datasets, one of 147 societies (1981) and the other of 312 societies (1967). Altogether the author tested 146 variables coded by Murdock against variables regarding the ownership of land and of movables drawn from Murdock (1967), Simmons (1937), and Swanson (1960). In total, there were 51 statistically significant correlations between private property ownership and other variables. Additionally, the author summarizes the results from this article and the two that preceded it stating that throughout all of the correlations he ran, the practice of agriculture, the use of cereal grains, and the presence of castes and classes were the only variables that predicted private property in all of the datasets that were utilized.

The present study builds upon Rudmin's 1992a publication by using a second data base to replicate and evaluate analyses on the cross-cultural correlates of private property ownership. Rudmin seeks to assess the reliability of Swanson's (1966) data base of 39 variables coded on 50 cultures. To do so, Swanson's data was evaluated against matching societies and variables from Murdock's (1967) Ethnographic Atlas. Swanson's reliable variables are tested against three measures of property ownership, one from Swanson and two from Murdock. Rudmin discusses results and speculates why certain clusters of societal variables correlate with private property ownership.

The present study aims to evaluate correlations of private property from two of Murdock's datasets, one of 147 societies (1981) and the other of 312 societies (1967). Altogether the author tested 146 variables coded by Murdock against variables regarding the ownership of land and of movables drawn from Murdock (1967), Simmons (1937), and Swanson (1960). In total, there were 51 statistically significant correlations between private property ownership and other variables. Additionally, the author summarizes the results from this article and the two that preceded it stating that throughout all of the correlations he ran, the practice of agriculture, the use of cereal grains, and the presence of castes and classes were the only variables that predicted private property in all of the datasets that were utilized.

In this article, the author seeks to correlate interpersonal values with attitudes toward private property. After giving a brief intellectual history on the philosophy of private property, the author draws data from the Multinational Student Survey (MSS) in order to discern attitudes towards private property and preferences for one of six psychological constructs (Support, Conformity, Recognition, Independence, Benevolence, Leadership) which were outlined in the Survey of Interpersonal Values which was itself incorporated in the aforementioned MSS. These measures were then edited in order to be correlated and the reliability of each was verified. The strongest correlations that resulted were for dominance and nonconformity. The author concludes without a theory of how to reckon with these seemingly paradoxical results.

Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.