Population projection is essential to governments, businesses, and research communities for many purposes. Although projection performance is often evaluated, we know very little about what factors affect projection accuracy. It is important to understand these factors in order to utilize the projections knowledgeably. This study fills this gap in the literature by comprehensively investigating the possible factors associated with population projection accuracy in 2010 for the continental US counties. The results indicate that the counties whose populations are more predictable tend to be desirable places-places with abundant employment opportunities, reliable public transportation infrastructure, easy access to work, and/or high land development potential; their neighboring counties tend to have a well-educated population and a higher income level. Also, projection accuracy is highly spatially associated. The findings provide important insights for population projection users to understand the characteristics of counties and their neighboring counties associated with their projection accuracy.
Research on youth and adolescents increasingly suggests that youths' aspirations are complex, multidimensional constructs. This is especially the case for rural youth, who may face conflicting goals when considering their educational, occupational, and residential aspirations. However, few studies have explored rural youths' aspirations from a MultiDimensional perspective. Using data from the younger cohort of the Rural Youth Education study, this research applies latent class analysis to examine the heterogeneity of rural youths' educational, occupational, and residential aspirations. Five distinct subgroups of youth are identified (1) ambitious stayers (27 percent), (2) ambitious yet uncertain youth (28 percent), (3) typical achievers (13 percent), (4) unambitious movers (8 percent), and (5) typical stayers (24 percent). These five subgroups of youth differ in their aspirations, the certainty of those aspirations, and perceived relationships among aspirations. Subsequent multinomial analysis shows strong associations of family, school, and community characteristics with youths' aspirational profiles. Youth with better family economic resources and good parent–child relationships are more likely to fall into the “typical achiever” category, relative to the other four categories. Understanding the interrelationship of rural youth's aspirations can help policymakers and community members develop strategies to assist rural youth in achieving an array of future goals.
Millions of people are surveyed every year regarding their attitudes toward various topics. Together these surveys have produced a large corps of data that document how people think collectively toward various aspects of contemporary social life.The wealth of the attitude surveys has promoted scholars to move beyond the single-survey analysis. However, the use of survey data for studying trends in attitudes is handicapped by a measurement difficulty: different surveys have used different survey instruments to measure the same attitude and thus have generated data that strictly non-comparable. We propose the Latent Attitude Method (LAM) to address this issue. Our method borrows strength from two research traditions: (1) the latent variable method in attitude research and (2) the comparable distribution condition in survey design and evaluation. The core of this method is that, when two or more surveys overlap in a given year, we assume that the same latent attitude is measured as if two measurement scales are randomly given to two independent samples drawn from the same population. Thus, we can assume the same statistical properties for the latent attitude. In so doing, we are able to reduce the number of unknowns to be less than the number of established equations and estimate the best-fit parameters with maximum likelihood method. We demonstrate the utility of the method with simulated data, and apply the method to an empirical example of estimating America’s attitude toward China from 1974 to 2019.
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