8 resultados para Census and revisitas

em University of Connecticut - USA


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This research examines the site and situation characteristics of community trails as landscapes promoting physical activity. Trail segment and neighborhood characteristics for six trails in urban, suburban, and exurban towns in northeastern Massachusetts were assessed from primary Global Positioning System (GPS) data and from secondary Census and land use data integrated in a geographic information system (GIS). Correlations between neighborhood street and housing density, land use mix, and sociodemographic characteristics and trail segment characteristics and amenities measure the degree to which trail segment attributes are associated with the surrounding neighborhood characteristics.

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Researchers have long recognized that the non-random sorting of individuals into groups generates correlation between individual and group attributes that is likely to bias naive estimates of both individual and group effects. This paper proposes a non-parametric strategy for identifying these effects in a model that allows for both individual and group unobservables, applying this strategy to the estimation of neighborhood effects on labor market outcomes. The first part of this strategy is guided by a robust feature of the equilibrium in the canonical vertical sorting model of Epple and Platt (1998), that there is a monotonic relationship between neighborhood housing prices and neighborhood quality. This implies that under certain conditions a non- parametric function of neighborhood housing prices serves as a suitable control function for the neighborhood unobservable in the labor market outcome regression. The second part of the proposed strategy uses aggregation to develop suitable instruments for both exogenous and endogenous group attributes. Instrumenting for each individual's observed neighborhood attributes with the average neighborhood attributes of a set of observationally identical individuals eliminates the portion of the variation in neighborhood attributes due to sorting on unobserved individual attributes. The neighborhood effects application is based on confidential microdata from the 1990 Decennial Census for the Boston MSA. The results imply that the direct effects of geographic proximity to jobs, neighborhood poverty rates, and average neighborhood education are substantially larger than the conditional correlations identified using OLS, although the net effect of neighborhood quality on labor market outcomes remains small. These findings are robust across a wide variety of specifications and robustness checks.

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Economists and other social scientists often face situations where they have access to two datasets that they can use but one set of data suffers from censoring or truncation. If the censored sample is much bigger than the uncensored sample, it is common for researchers to use the censored sample alone and attempt to deal with the problem of partial observation in some manner. Alternatively, they simply use only the uncensored sample and ignore the censored one so as to avoid biases. It is rarely the case that researchers use both datasets together, mainly because they lack guidance about how to combine them. In this paper, we develop a tractable semiparametric framework for combining the censored and uncensored datasets so that the resulting estimators are consistent, asymptotically normal, and use all information optimally. When the censored sample, which we refer to as the master sample, is much bigger than the uncensored sample (which we call the refreshment sample), the latter can be thought of as providing identification where it is otherwise absent. In contrast, when the refreshment sample is large and could typically be used alone, our methodology can be interpreted as using information from the censored sample to increase effciency. To illustrate our results in an empirical setting, we show how to estimate the effect of changes in compulsory schooling laws on age at first marriage, a variable that is censored for younger individuals. We also demonstrate how refreshment samples for this application can be created by matching cohort information across census datasets.

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Recent theoretical work has examined the spatial distribution of unemployment using the efficiency wage model as the mechanism by which unemployment arises in the urban economy. This paper extends the standard efficiency wage model in order to allow for behavioral substitution between leisure time at home and effort at work. In equilibrium, residing at a location with a long commute affects the time available for leisure at home and therefore affects the trade-off between effort at work and risk of unemployment. This model implies an empirical relationship between expected commutes and labor market outcomes, which is tested using the Public Use Microdata sample of the 2000 U.S. Decennial Census. The empirical results suggest that efficiency wages operate primarily for blue collar workers, i.e. workers who tend to be in occupations that face higher levels of supervision. For this subset of workers, longer commutes imply higher levels of unemployment and higher wages, which are both consistent with shirking and leisure being substitutable.

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Despite a longstanding belief that education importantly affects the process of immigrant assimilation, little is known about the relative importance of different mechanisms linking these two processes. This paper explores this issue through an examination of the effects of human capital on one dimension of assimilation, immigrant intermarriage. I argue that there are three primary mechanisms through which human capital affects the probability of intermarriage. First, human capital may make immigrants better able to adapt to the native culture thereby making it easier to share a household with a native. Second, it may raise the likelihood that immigrants leave ethnic enclaves, thereby decreasing the opportunity to meet potential spouses of the same ethnicity. Finally, assortative matching on education in the marriage market suggests that immigrants may be willing to trade similarities in ethnicity for similarities in education when evaluating potential spouses. Using a simple spouse-search model, I first derive an identification strategy for differentiating the cultural adaptability effect from the assortative matching effect, and then I obtain empirical estimates of their relative importance while controlling for the enclave effect. Using U.S. Census data, I find that assortative matching on education is the most important avenue through which human capital affects the probability of intermarriage. Further support for the model is provided by deriving and testing some of its additional implications.

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Because the demographic composition of todays immigrants to the US differs so much from those of natives, immigrants may be less likely to socially integrate into U.S. society, and specically less likely to marry natives. This paper explores the relationship between immigrants' marriage patterns and the academic outcomes of their children. Using 2000 Census data, it is found that while marital decisions of foreign born females do not affect their children's academic success, foreign born males that marry foreign born females are less likely to have children that are high school dropouts. These relationships remain after using various methods to control for the endogeneity of the intermarriage decision. Although we cannot disentangle whether the benefits of same-nativity marriages for foreign born males arise from a more efficient technology in human capital production within the household or from increased participation in ethnic networks, it does appear that immigrant males have better educated children when they marry immigrant females.

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Increasing levels of segregation in American schools raises the question: do home buyers pay for test scores or demographic composition? This paper uses Connecticut panel data spanning eleven years from 1994 to 2004 to ascertain the relationship between property values and explanatory variables that include school district performance and demographic attributes, such as racial and ethnic composition of the student body. Town and census tract fixed effects are included to control for neighborhood unobservables. The effect of changes in school district attributes is also examined over a decade long time frame in order to focus on the effect of long run changes, which are more likely to be capitalized into prices. The study finds strong evidence that increases in percent Hispanic has a negative effect on housing prices in Connecticut, but mixed evidence concerning the impact of test scores on property values. Evidence is also found to suggest that student test scores have increased in importance for explaining housing prices in recent years while the importance of percent Hispanic has declined. Finally, the study finds that estimates of property tax capitalization increase substantially when the analysis focuses on long run changes.

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We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than individuals in nearby but not identical blocks. We find significant evidence of social interactions operating at the block level: residing on the same versus nearby blocks increases the probability of working together by over 33 percent. The results also indicate that this referral effect is stronger when individuals are similar in sociodemographic characteristics (e.g., both have children of similar ages) and when at least one individual is well attached to the labor market. These findings are robust across various specifications intended to address concerns related to sorting and reverse causation. Further, having determined the characteristics of a pair of individuals that lead to an especially strong referral effect, we provide evidence that the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes including employment and wages.