In August 2007 the Colorodoan reported dramatic poverty increases in Fort Collins between 1999 and 2006. Using Census Bureau data, the paper reported that 19.8 percent of the citys population lived below the poverty line in 2006. By comparison, the citys 1999 poverty rate was 14 percent. Children were similarly impacted, with nearly 1-in-5 living below the poverty line in 2006, up from 8.9 percent in 1999. While poverty trends in the rest of Larimer County are not as startling, it is undeniable that many households across the region are struggling. Despite increased attention, many dont fully understand the communitys poverty dynamics. Some of this is due to a spotty grasp of the depth and breadth of the poverty problem. And some is due simply to denial. The issue is further complicated in that little is known about the causes underlying increased poverty. As a result, local policymakers, non-profits, churches and human service organizations typically rely on anecdotal evidence in designing poverty alleviation programs. While anecdotes certainly help, they may not capture povertys true dynamics, as anecdotes are typically formed by what people see and experience in their own daily workings. Our goal in this project is to examine poverty from a variety of detached angles to improve our understanding of the regions poverty workings. This report is part of the comprehensive Pathways Past Poverty effort designed to educate and empower citizens, public institutions and human service agencies about the nature, extent, causes and solutions of poverty in Fort Collins and Larimer County. Our study shows the relative importance of a variety of factors that drive both household poverty and changes in regional poverty. Due to the complex nature of poverty, there is no single solution that will eradicate, or even dramatically reduce it in Larimer County and Fort Collins. Further complicating the issue is the fact that the dynamics of child poverty differ from those of adult poverty--these are two unique problems that require unique solutions. This report summarizes a two step process. First we provide a comprehensive picture of local poverty trends, emphasizing the nature and extent of poverty on various socioeconomic groups (e.g., age, gender, education). We then take a multi-faceted approach to better understand the root causes of increasing poverty, using statistical models and focus group methods to examine how social and economic forces influence individual and household poverty.

Many papers in the literature have attempted to document whether accountability programs have played a role in producing higher test scores. Yet, evaluating changes to test scores does not necessarily indicate how the adoption of programs has affected the individual students long-runoutcomes. This paper extends the existing literature by evaluating whether accountability programs led to higher levels of educational attainment and more successful labor market outcomes. I find evidence of heterogeneous treatment effects across race, ethnicity and gender. While accountability programs led to large improvements in schooling and earnings for Hispanics, the effect for whites and blacks are mixed. Additional specifications that control forthe individuals length of exposure to treatment and the frequency with which states administer standardized exams are also conducted to determine whether treatment variation had any impact on individual outcomes. Both of these additional specifications indicate that accountability programs led to mixed success in improving outcomes for black and white individuals. Due to the mixed results from specific states program characteristics, the conclusions of this studyhighlight the fact that the success of accountability programs is strongly tied to the students response to the programs structure and design.JEL classification: I21, J24, J31Keywords: Accountability programs; socioeconomic status; Education outcomes; Labor market outcomes; Heterogeneous treatment effects.

We construct a quarterly time series of the rent‐price ratio for the aggregate stock of owner‐occupied housing in the United States, starting in 1960, by merging micro data from the last five Decennial Censuses of Housing surveys with price indexes for house prices and rents. We show that the rent‐price ratio ranged between 5 and 5.5 percent between 1960 and 1995, but rapidly declined after 1995. By year‐end 2006, the rent‐price ratio reached a historic low of 3.5 percent. For the rent‐price ratio to return to its historical average over, say, the next five years, house prices likely would have to fall considerably.

This article discusses the history of participation of the three largest racial-ethnic groups in the military: whites, blacks, and Latinos. It empirically examines the likelihood of ever having served in the military across a variety of criteria including race-ethnicity, immigrant generation, and socioeconomic status, concluding that significant disparities exist only by socioeconomic status. Finally, the article offers an in-depth look at Latinos in the military, a group whose levels of participation in the armed services have not been thoroughly investigated heretofore. The findings reveal that, among Latinos, those who identify as "Other Hispanic" are more likely to have served in the military than Mexicans, while Puerto Ricans are not significantly different from Mexicans in their service. An important finding of this study is that a large percentage of Latinos who have served in the armed forces are children of immigrants. Thus, even among Latinos, immigrants are not significantly less likely to have served in the military than those with two U.S.-born parents.

Using the confidential long-form records of the 2000 population census, we study the choices of metropolitan destinations made by the Mexican-born and Indian-born immigrants who arrived in the United States in 1995-2000. Based on the application of a multinomial logit model to the data of each of these two ethnic groups, our main findings are as follows. The destination choice behaviors of both ethnic groups were in general consistent with the major theories of immigration. Both groups were subject to (1) the attraction of co-ethnic communities and (2) the positive effects of wage level and total employment growth. With respect to the job increases in different wage deciles, both ethnic groups share the pattern that the less educated were subject to the pull of increase in low-wage jobs, whereas the better educated were subject to the pull of increase in high-wage jobs. With respect to the possibility of competitions against other foreign-born ethnics, both ethnic groups were found to be more prone to selecting destinations where their co-ethnics represented a relatively high proportion of the foreign-born population. The main differences in destination choice behaviors between the two ethnic groups resulted partly from the fact that the relative explanatory powers of our chosen explanatory factors differed substantially between the two ethnic groups. The Mexican-born were more subject to the attractions of (1) larger co-ethnic communities, (2) greater overall employment growth, (3) more job increases in low wage deciles, and (4) greater share of the foreign-born population by co-ethnics. In contrast, the Indian-born were more attracted by (1) higher wage level, and (2) more job increases in high wage deciles.

Background: Differences in the epidemiology of lung cancer between Asians and non-Hispanic whites have brought to light the relative influences of genetic and environmental factors on lung cancer risk. We set out to describe the epidemiology of non-small Cell cancer (NSCLC) among Asians living in California, and to explore the effects of acculturation on lung cancer risk by comparing lung cancer rates between U.S.-born and foreign-born Asians. Methods: Age-adjusted incidence rates of NSCLC were calculated for Chinese. Filipino. Japanese, Korean. Vietnamese, and South Asians in California between 1988 and 2003 using data from the California Cancer Registry. Incidence rates were calculated and stratified by sex and nativity. We analyzed population-based tobacco smoking prevalence data to determine whether differences in rates were associated with prevalence of tobacco smoking. Results: Asians have overall lower incidence rates of NSCLC compared with whites (29.8 and 57.7 per 100,000, respectively). South Asians have markedly low rates of NSCLC (12.0 per 100,000). Foreign-born Asian men and women have an approximately 35% higher rate of NSCLC than U.S.-born Asian men and women. The incidence pattern by nativity is consistent with the population prevalence of smoking among Asian men; however, among women, the prevalence of smoking is higher among U.S.born. which is Counter to their incidence patterns. Conclusions: Foreign-born Asians have a higher rate of NSCLC than U.S.-born Asians, which may be due to environmental tobacco smoke or nontobacco exposures among women. South Asians have a remarkably low rate of NSCLC that approaches white levels among the U.S.-born. More Studies with individual-level survey data are needed to identify file specific environmental factors associated with differential lung cancer risk Occurring with acculturation among Asians.

We use panel data from El Salvador and investigate the intra-household allocation of labor as a risk-coping strategy. Adverse agricultural productivity shocks both increased male migration to the US and male agricultural labor supply. This is not a contradiction if there were nonmonotonic effects on shadow wages within the survey period. In contrast, damage sustained from the 2001 earthquakes exclusively stunted female migration. This is consistent with the earthquakes increasing the demand for home production.

Revised federal policies require that multiple-race responses be allowed in all federal data collection efforts, but many researchers find the multitude of race categories and variables very difficult to use. Important comparability issues also interfere with using multiple-race data in analyses of multiple data sets and/or several points in time. These difficulties have, in effect, discouraged the use of the new data on race. We present a practical method for incorporating multiple-race respondents into analyses that use public-use microdata. Our method is a modification of the regression method developed by the National Center for Health Statistics (NCHS), which uses multiple-race respondentsspecific combination of races, as well as other individual-level and contextual characteristics, to predict the respondents preferred single race. In this paper we (1) apply the NCHS-generated regression coefficients to public-use microdata with limited geographic information; and (2) provide a downloadable computer program with which researchers can apply this practical and preferable method for including multiple-race respondents in a wide variety of analyses.

In this paper we used the weighted kappa through disagreement scaling proposed by Cohen (1968) to measure the exogamous marriage. It is the interest of sociologist to investigate the trend of exogamous or mixed marriage between different ethnic groups, as the upward trend of mixed marriage can be view as degree of assimilation of particular ethnic groups. We are able to measure the strength of exogamous marriage directly. We found that the upward trend of mixed marriage among Americans of different ethnicity tend to increase from 1980 to 2000. We also used the estimated large sample variance of weighted kappa given by Fleiss et al. (1969) to build the Wald confidence interval and hence testing the null hypothesis of nonexistence of exogamous marriage.

Frequent pattern mining often produces a vast set of results. To overcome this problem, two fundamental approaches are commonly employed: condensed representations, such as closed itemsets, and relevance assessment. In recent years, the change of itemsets over time is gaining increasing attention as a promising basis for developing novel, more comprehensible relevance assessment methods. One of the unsolved problems is that typically many of the observed changes are the side-effect of other changes. Existing condensed representation approaches fail in removing such redundancies because they have not been developed with the temporal dimension in mind. This paper proposes a novel approach for a condensed representation of itemsets which is based on utilizing temporal redundancies. In particular we prove that our approach yields a temporally non-redundant subset of closed itemsets which we therefore call temporally closed itemsets. Our experiments with real-life data sets show that the set of temporally closed itemsets is significantly smaller than the set of closed itemsets.

This study builds on the internal migration literature, and especially on the rapidly growing number of studies about the waves of migrants settling in new destinations throughout the United States (Durand et al. 2005; Kritz and Nogle 1994; Kritz and Gurak 2001; Suro and Singer 2002). Most of the prior studies of Latino internal migration have focused on the larger, macro-structural factors pushing or pulling people to migrate. In this study, we instead focus on individual migration motivations and how they enhance explanations solely based on socioeconomic outcomes, as well as our understanding of the challenges to and opportunities for immigrant integration. Our goal is to compare how self-reported migration motivations relate to or diverge from the comparative socioeconomic outcomes for Latinos(as), based on twenty semi-structured . . .

How do we understand the racial and ethnic re-composition of New Orleanss diminished population in the year following Hurricane Katrina? Optimists viewing the influx of Latino migrants see in it a revival of the multicultural past of New Orleans, while skeptics suspect that delays in government assistance for residents to return to the city are an attempt to keep out low-income blacks and make the city whiter and wealthier. The shifts in the population of New Orleans are familiar to sociologists and economists who study labor-market demand for low-skill, inexpensive, and flexible workers. The low-prestige jobs they do are reserved for those at the bottom of the social hierarchy, most often immigrants or members of stigmatized minorities.1 The sociodemographic characteristics of workers building and rebuilding the city shift only when social and market forces combine to make one group less expensive and more flexible than the other. I use this sociological insight to analyze New Orleanss population history and the way race has been socially constructed and reconstructed there.

We use panel data from El Salvador to investigate migration and the intra-household allocation of labor as a strategy for coping with uninsured risk. Adverse agricultural productivity shocks increased both male migration to the US and the supply of male agricultural labor in El Salvador. This is not a contradiction if there were non-monotonic effects on shadow wages within the survey period. In contrast, after damage sustained from the 2001 earthquakes, female migration from El Salvador declined. This is consistent with the earthquakes increasing the demand for home production. We conclude that migration, household labor supply, and gender roles can have complicated interactions.

The authors describe the development of a data source that facilitates the inclusion of individual victims and their characteristics in the study of lynching in the southern United States. Using an inventory of 2,800 lynch victims from 10 states between 1882 and 1930, they develop a methodological approach that allows them to locate victims in the census immediately preceding the lynching. The database will include census information on the victim and all household members. The final product will include census manuscripts, research notes, and supporting documentation used to identify each victim. The authors outline (1) steps taken to identify victims, (2) challenges encountered and solutions developed, (3) plans for publicly disseminating the database, and (4) discussion of investigations that the new database will support.

Context: The robust relationship between socioeconomic factors and health suggests that social and economic policies might substantially affect health, while other evidence suggests that medical care, the main focus of current health policy, may not be the primary determinant of population health. Income support policies are one promising avenue to improve population health. This study examines whether the federal cash transfer program to poor elderly, the Supplemental Security Income (SSI) program, affects old-age disability.Methods: This study uses the 1990 and 2000 censuses, employing state and year fixed-effect models, to test whether within-state changes in maximum SSI benefits over time lead to changes in disability among people aged sixty-five and older.Findings: Higher benefits are linked to lower disability rates. Among all single elderly individuals, 30 percent have mobility limitations, and an increase of $100 per month in the maximum SSI benefit caused the rate of mobility limitations to fall by 0.46 percentage points. The findings were robust to sensitivity analyses. First, analyses limited to those most likely to receive SSI produced larger effects, but analyses limited to those least likely to receive SSI produced no measurable effect. Second, varying the disability measure did not meaningfully alter the findings. Third, excluding the institutionalized, immigrants, individuals living in states with exceptionally large benefit changes, and individuals living in states with no SSI supplements did not change the substantive conclusions. Fourth, Medicaid did not confound the effects. Finally, these results were robust for married individuals.Conclusions: Income support policy may be a significant new lever for improving population health, especially that of lower-income persons. Even though the findings are robust, further analyses are needed to confirm their reliability. Future research should examine a variety of different income support policies, as well as whether a broader range of social and economic policies affect health.

Welcome to the LINC Artist Data User Guide to the Census data on artists, created for Leveraging Investments in Creativity (LINC). This manual is for use with the data sets we have provided you on your state and metropolitan region. We have constructed the tables to make your use of them as easy and transparent as possible. We are very happy to talk with you about them and help you understand any issues you have with the data and its meaning. Please feel free to contact us. You may wonder whether 2000 Census data is good enough for what you most want to know. This data is the only evidence we have that captures artists adequately by artistic discipline, industry, income, employment status, recent migration patterns, and a large number of socioeconomic characteristics (including age, race, gender, immigrant status, education, and homeowner status), at metro and large city as well as state geographical levels. These data were first made available in the fall of 2003—the next decennial Census data will not be available until 2013. The American Community Survey now offers two years (2005 and 2006) of comparable data from a 1% sample, but this is generally too small to use reliably for studying artists at the state and local level, even when pooled across years. Although the numbers and features of artists may have changed from 2000, these data allow you to compare metro and state artists in your region with those in other places, a comparison that is not apt to have changed dramatically over the past seven years.

Comparative proteomics can augment understanding of protein function, the relationship between organisms, and certain evolutionary processes, through comparison of the proteomes of different organisms. When protein sequences are ordered according to the underlying encoding chromosomal DNA, functional correspondence can be inferred for regions of correspondence between two or more proteomes. The ability to align proteomes gene product by gene product is thus a crucial tool in comparative proteomics. Currently, proteome alignments are mainly performed manually using information from an ensemble of tools. However, as more and more genomic data becomes available it is desirable that such comparisons are performed robustly, rapidly and automatically.