Optimally Combining Censored and Uncensored Datasets

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.

Are Shirking and Leisure Substitutable? An Empirical Test of Efficiency Wages Based on Urban Economic Theory

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.

Human Capital and Interethnic Marriage Decisions

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.

Cross-Nativity Marriages, Gender, and Human Capital Levels of Children

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.

Which School Attributes Matter? The Influence of School District Performance and Demographic Composition on Property Values

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.

Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes

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.

An examination of the relationship between maternal and neighborhood-level characteristics and intrauterine growth retardation in Harris County, Texas, 1999--2001

The persistence of low birth weight and intrauterine growth retardation (IUGR) in the United States has puzzled researchers for decades. Much of the work that has been conducted on adverse birth outcomes has focused on low birth weight in general and not on IUGR. Studies that have examined IUGR specifically thus far have focused primarily on individual-level maternal risk factors. These risk factors have only been able to explain a small portion of the variance in IUGR. Therefore, recent work has begun to focus on community-level risk factors in addition to the individual-level maternal characteristics. This study uses Social Ecology to examine the relationship of individual and community-level risk factors and IUGR. Logistic regression was used to establish an individual-level model based on 155, 856 births recorded in Harris County, TX during 1999-2001. IUGR was characterized using a fetal growth ratio method with race/ethnic and sex specific mean birth weights calculated from national vital records. The spatial distributions of 114,460 birth records spatially located within the City of Houston were examined using choropleth, probability and density maps. Census tracts with higher than expected rates of IUGR and high levels of neighborhood disadvantage were highlighted. Neighborhood disadvantage was constructed using socioeconomic variables from the 2000 U.S. Census. Factor analysis was used to create a unified single measure. Lastly, a random coefficients model was used to examine the relationship between varying levels of community disadvantage, given the set of individual-level risk factors for 152,997 birth records spatially located within Harris County, TX. Neighborhood disadvantage was measured using three different indices adapted from previous work. The findings show that pregnancy-induced hypertension, previous preterm infant, tobacco use and insufficient weight gain have the highest association with IUGR. Neighborhood disadvantage only slightly further increases the risk of IUGR (OR 1.12 to 1.23). Although community level disadvantage only helped to explain a small proportion of the variance of IUGR, it did have a significant impact. This finding suggests that community level risk factors should be included in future work with IUGR and that more work needs to be conducted. ^

A survey of the implementation status of environmental management systems in U.S. colleges and universities, and, An environmental management system implementation model for U.S. colleges and universities

A census of 925 U.S. colleges and universities offering masters and doctorate degrees was conducted in order to study the number of elements of an environmental management system as defined by ISO 14001 possessed by small, medium and large institutions. A 30% response rate was received with 273 responses included in the final data analysis. Overall, the number of ISO 14001 elements implemented among the 273 institutions ranged from 0 to 16, with a median of 12. There was no significant association between the number of elements implemented among institutions and the size of the institution (p = 0.18; Kruskal-Wallis test) or among USEPA regions (p = 0.12; Kruskal-Wallis test). The proportion of U.S. colleges and universities that reported having implemented a structured, comprehensive environmental management system, defined by answering yes to all 16 elements, was 10% (95% C.I. 6.6%–14.1%); however 38% (95% C.I. 32.0%–43.8%) reported that they had implemented a structured, comprehensive environmental management system, while 30.0% (95% C.I. 24.7%–35.9%) are planning to implement a comprehensive environmental management system within the next five years. Stratified analyses were performed by institution size, Carnegie Classification and job title. ^ The Osnabruck model, and another under development by the South Carolina Sustainable Universities Initiative, are the only two environmental management system models that have been proposed specifically for colleges and universities, although several guides are now available. The Environmental Management System Implementation Model for U.S. Colleges and Universities developed is an adaptation of the ISO 14001 standard and USEPA recommendations and has been tailored to U.S. colleges and universities for use in streamlining the implementation process. In using this implementation model created for the U.S. research and academic setting, it is hoped that these highly specialized institutions will be provided with a clearer and more cost-effective path towards the implementation of an EMS and greater compliance with local, state and federal environmental legislation. ^

Bexar County's dental safety net for children: An estimate of our current capacity and need

Introduction. It has been well established that poor uninsured children lack access to dental care and have greater dental needs than their insured counterparts. ^ Objective. To assess the capacity of Bexar County's dental safety net to treat children. To assess the dental needs of Bexar County children ages 0-18 who are uninsured or are Medicaid or SCHIP recipients. ^ Methods. Information was requested from dental safety net clinics that treat children ages 0-18. Data from the census, NHANES and other sources was used to estimate the dental needs. ^ Results. The capacity of the current safety net to treat children is 33,537 patient encounters per year. The dental needs of the community are 227,124 patient encounters per year. ^ Conclusion. The results of the study indicate that Bexar County is not prepared to treat the dental needs of the underserved children in San Antonio.^

The local safety net, health insurance, preventable hospitalizations and costs: Harris County (Houston), Texas

The aim of this study was to examine the association between determinants of access to healthcare and preventable hospitalizations, based on Davidson et al.'s framework for evaluating the effects of individual and community determinants on access to healthcare. The study population consisted of the low income, non-elderly, hospitalized adults residing in Harris County, Texas in 2004. The objectives of this study were to examine the proportion of the variance in preventable hospitalizations at the ZIP-code level, to analyze the association between the proximity to the nearest safety net clinic and preventable hospitalizations, to examine how the safety net capacity relates to preventable hospitalizations, to compare the relative strength of the associations of health insurance and the proximity to the nearest safety net clinic with preventable hospitalizations, and to estimate and compare the costs of preventable hospitalizations in Harris County with the average cost in the literature. The data were collected from Texas Health Care Information Collection (2004), Census 2000, and Project Safety Net (2004). A total of 61,841 eligible individuals were included in the final data analysis. A random-intercept multi-level model was constructed with two different levels of data: the individual level and the ZIP-code level. The results of this study suggest that ZIP-code characteristics explain about two percent of the variance in preventable hospitalizations and safety net capacity was marginally significantly associated with preventable hospitalizations (p= 0.062). Proximity to the nearest safety net clinic was not related to preventable hospitalizations; however, health insurance was significantly associated with a decreased risk of preventable hospitalization. The average direct cost was $6,466 per preventable hospitalization, which is significantly different from reports in the literature. ^

A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

The association of area socioeconomic status and cancer screening: A systematic review and multilevel study

Background. The gap between actual and ideal rates of routine cancer screening in the U.S., particularly for colorectal cancer screening (CRCS) (1;2), is responsible for an unnecessary burden of morbidity and mortality, particularly for disadvantaged groups. Knowledge about the effects of individual and area influences is being advanced by a growing body of research that has examined the association of area socioeconomic status (SES) and cancer screening after controlling for individual SES. The findings from this emerging and heterogeneous research in the cancer screening literature have been mixed. Moreover, multilevel studies in this area have not yet adequately explored the possibility of differential associations by population subgroup, despite some evidence suggesting gender-specific effects. ^ Objectives and methods. This dissertation reports on a systematic review of studies on the association of area SES and cancer screening and a multilevel study of the association between area SES and CRCS. The specific aims of the systematic review are to: (1) describe the study designs, constructs, methods, and measures; (2) describe the association of area SES and cancer screening; and (3) identify neglected areas of research. ^ The empiric study linked a pooled sample of respondents aged ≥50 years without a personal history of colorectal cancer from the 2003 and 2005 California Health Interview Surveys with a comprehensive set of census-tract level area SES measures from the 2000 U.S. Census. Two-level random intercept models were used to test 2 hypotheses: (1) area SES will be associated with adherence to two modalities of CRCS after controlling for individual SES; and (2) gender will moderate the relationship between area socioeconomic status and adherence to both modalities of CRCS. ^ Results. The systematic review identified 19 eligible studies that demonstrated variability in study designs, methods, constructs, and measures. The majority of tested associations were either not statistically significant or significant and in the positive direction, indicating that as area SES increased, the odds of CRCS increased. The multilevel study demonstrated that while multiple aspects of area SES were associated with CRCS after controlling for individual SES, associations differed by screening modality and in the case of endoscopy, they also differed by gender. ^ Conclusions. Conceptual and methodologic heterogeneity and weaknesses in the literature to date limit definitive conclusions about the underlying relationships between area SES and cancer screening. The multilevel study provided partial support for both hypotheses. Future research should continue to explore the role of gender as a moderating influence with the aim of identifying the mechanisms linking area SES and cancer prevention behaviors. ^

Hazardous air pollutants and childhood lymphohematopoietic cancer in Southeast Texas, 1995--2004

Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^

Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

Spatial analysis of water body distance and West Nile Virus human cases in Houston, TX

West Nile Virus (WNV) is an arboviral disease that has affected hundreds of residents in Harris County, Texas since its introduction in 2002. Persistent infection, lingering sequelae and other long-term symptoms of patients reaffirm the need for prevention of this important vector-borne disease. This study aimed to determine if living within 400m of a water body increases one’s odds of infection with WNV. Additionally, we wanted to determine if one’s proximity to a particular water type or water body source increased one’s odds of infection with WNV.^ 145 cases’ addresses were abstracted from the initial interview and consent records from a cohort of patients (Epidemiology of Arboviral Encephalitis in Houston study, HSC-SPH-03-039). After applying inclusion criteria, 140 cases were identified for analysis. 140 controls were selected for analysis using a population proportionate to size model and US Census Bureau data. MapMarker USA v14 was used to geocode the cases’ addresses. Both cases’ and controls’ coordinates were uploaded onto a Harris County water shapefile in MapInfo Professional v9.5.1. Distance in meters to the closest water source, closest water source type, and closest water source name were recorded.^ Analysis of Variance (p=0.329, R2 = 0.0034) indicated no association between water body distance and risk of WNV disease. Living near a creek (x2 = 11.79, p < 0.001), or the combined group of creek and gully (x 2 = 14.02, p < 0.001) were found to be strongly associated with infection of WNV. Living near Cypress Creek and its feeders (x2 = 15.2, p < 0.001) was found to be strongly associated with WNV infection. We found that creek and gully habitats, particularly Cypress Creek, were preferential for the local disease transmitting Culex quinquefasciatus and reservoir avian population.^