The methods used to estimate the Jewish population at the national, state, and sub-state levels continue to develop as new data are added to the data synthesis. The addition of data increases the power to estimate smaller geographic areas. As the power to estimate smaller geographic areas is improved, so too is the ability to explore factors that can affect estimation of these areas.
Previous work included the clustering of respondents within surveys, as well as within geographic areas, such as states or counties (See Publications). Also included in past population models are demographic characteristics related to the representativeness of survey samples and to the distribution of the Jewish population. These demographics include sex, age, educational attainment, and race/ethnicity.
Hierarchical Bayesian models, using R and Stan, are used to fit the data. A set of simulations from the models are stored to generate estimates of the proportion of adults who are Jewish for each demographic group within each geographic region. These estimates are post-stratified to county and metropolitan area population counts based on data from the US Census Current Population Estimates Program (PEP). The PEP produces yearly estimates of the population for the United States, its states and counties by age, sex, race, and Hispanic origin. Data from the American Community Survey (ACS) are used for distributions by educational attainment.
See Also Publications