New Directions in the Development of Population Estimates in the United States?

The advent of a continuously updated Master Area File (MAF) following the 2000 census represents an information resource that can be tapped for purposes of developing timely, cost-effective, and precise population estimates for even the smallest of geographical units (e.g., census blocks). We argue that the MAF can be enhanced (EMAF) for these purposes. In support of our argument we describe a set of activities needed to develop EMAF, each of which is well within the current capabilities of the U.S. Census Bureau and discuss various costs and benefits of each. We also describe how EMAF would provide population estimates containing a wide range of demographic (e.g., age, race, and sex) and socio-economic characteristics (e.g., educational attainment, income, and employment). As such, it could largely negate and eliminate the need for many of the traditional demographic methods of population estimation and possibly reduce the number of sample surveys. We identify important challenges that must be surmounted in order to realize EMAF and make suggestions for doing so. We conclude by noting that the idea of the EMAF could be of interest to other countries with MAF files and strong administrative records systems that, like the United States, are facing the challenge of producing good population information in the face of increasing census costs.     

Has Income Segregation Really Increased? Bias and Bias Correction in Sample-Based Segregation Estimates

Several recent studies have concluded that residential segregation by income in the United States has increased in the decades since 1970, including a significant increase after 2000. Income segregation measures, however, are biased upward when based on sample data. This is a potential concern because the sampling rate of the American Community Survey (ACS)—from which post-2000 income segregation estimates are constructed—was lower than that of the earlier decennial censuses. Thus, the apparent increase in income segregation post-2000 may simply reflect larger upward bias in the estimates from the ACS, and the estimated trend may therefore be inaccurate. In this study, we first derive formulas describing the approximate sampling bias in two measures of segregation. Next, using Monte Carlo simulations, we show that the bias-corrected estimators eliminate virtually all of the bias in segregation estimates in most cases of practical interest, although the correction fails to eliminate bias in some cases when the population is unevenly distributed among geographic units and the average within-unit samples are very small. We then use the bias-corrected estimators to produce unbiased estimates of the trends in income segregation over the last four decades in large U.S. metropolitan areas. Using these corrected estimates, we replicate the central analyses in four prior studies on income segregation. We find that the primary conclusions from these studies remain unchanged, although the true increase in income segregation among families after 2000 was only half as large as that reported in earlier work. Despite this revision, our replications confirm that income segregation has increased sharply in recent decades among families with children and that income inequality is a strong and consistent predictor of income segregation.     

The Astonishing Population Averted by China’s Birth Restrictions: Estimates,Nightmares, and Reprogrammed Ambitions

China launched an unprecedented program to control its population in 1971. Experts have dismissed the official estimate of 400 million births averted by this program as greatly exaggerated yet neglect to provide their own estimates. Counterfactual projections based on fertility declines in other countries suggest that China’s program-averted population numbered 360–520 million as of 2015. The low end of this range is based on Vietnam—China’s best national comparator, with a two-child program of its own—and the high end is based on a 16-country comparator selected, ironically, by critics of the official estimate. The latter comparator further implies that China’s one-child program itself averted a population of 400 million by 2015, three-quarters of the total averted population. All such estimates are projected to double by 2060, due mostly to counterfactual population momentum. These and other findings presented herein affirm the astonishing impact of China’s draconian policy choices and challenge the current consensus that rapid socioeconomic progress drove China’s fertility well below two children per family. International comparisons of fertility and income suggest instead that China’s very low fertility arrived two or three decades too soon. If China had not harshly enforced a norm of 1.5-children during the last quarter century, most mothers would have had two children, one-half birth higher than observed.     

Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities

Household consumption expenditure represents a crucial measure to be used for assessing individuals’ material living conditions and well-being. Indeed, the analysis of household conditions can provide policy makers with a clear picture of the economic and social situation of the area in which they are operating. However, official sample surveys which are generally used for this purpose, such as the Household Budget Survey in Italy carried out by the National Institute of Statistics, do not allow for reliable disaggregated estimates thus hindering appropriate and effective planning and evaluation of political interventions at local level. By referring to the 2012 Italian Household Budget Survey, this paper aims at obtaining reliable provincial estimates of household consumption expenditure in Italy. We use Small Area Estimation methods and we adjust the estimates for spatial differences in price levels by computing and using sub-national Purchasing Power Parities, thus obtaining “real” estimates of consumption expenditure to be used for intra-national comparisons.     

A Comparative Evaluation of Error and Bias in Census Tract-Level Age/Sex-Specific Population Estimates: Component I (Net-Migration) vs Component III (Hamilton–Perry)

While the housing-unit method continues to be the preferred method nationwide for producing small-area population estimates, this procedures lacks a method for making age/sex-specific estimates. This paper reports evaluation research on implementation of component-based methods for estimating census tract populations with age/sex detail. Two alternatives are explored: (1) the Component I method relying upon estimates of births, deaths, and net-migration and (2) the Component III method relying solely upon 1990 and 2000 Census counts. From an April 1, 2000 base, each method is used to make estimates moving forward to an April 1, 2010 estimate that is compared to the results of the 2010 Census. The two methods are compared in terms of accuracy and bias using both absolute and algebraic mean and median percentage errors. Results are reviewed and discussed in light of their implications for applied demographers tasked with making small-area demographic estimates.