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.

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.

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.

The second and third parts of this book classify the economic systems of foraging and agricultural societies in the SCCS based on correlations between their institutions of property an distribution. These economic types are then examined for relationships with other social, political, demographic, and environmental factors in order to draw tentative conclusions regarding the origins of the Agricultural and Industrial Revolutions. The fourth part of the book uses cross-national data to examine similar associations in industrial/service economies, and is not included here.