The Intermediate Data Structure (IDS) is a standardised database structure for longitudinal historical databases. Such a common structure facilitates data sharing and comparative research. In this study, we propose an extended version of IDS, named IDS-Geo, that also includes geographic data. The geographic data that will be stored in IDS-Geo are primarily buildings and/or property units, and the purpose of these geographic data is mainly to link individuals to places in space. When we want to assign such detailed spatial locations to individuals (in times before there were any detailed house addresses available), we often have to create tailored geographic datasets. In those cases, there are benefits of storing geographic data in the same structure as the demographic data. Moreover, we propose the export of data from IDS-Geo using an eXtensible Markup Language (XML) Schema. IDS-Geo is implemented in a case study using historical property units, for the period 1804 to 1913, stored in a geographically extended version of the Scanian Economic Demographic Database (SEDD). To fit into the IDS-Geo data structure, we included an object lifeline representation of all of the property units (based on the snapshot time representation of single historical maps and poll-tax registers). The case study verifies that the IDS-Geo model is capable of handling geographic data that can be linked to demographic data.

In multivariate categorical data, models based on conditional independence assumptions, such as latent class models, offer efficient estimation of complex dependencies. However, Bayesian versions of latent structure models for categorical data typically do not appropriately handle impossible combinations of variables, also known as structural zeros. Allowing nonzero probability for impossible combinations results in inaccurate estimates of joint and conditional probabilities, even for feasible combinations. We present an approach for estimating posterior distributions in Bayesian latent structure models with potentially many structural zeros. The basic idea is to treat the observed data as a truncated sample from an augmented dataset, thereby allowing us to exploit the conditional independence assumptions for computational expediency. As part of the approach, we develop an algorithm for collapsing a large set of structural zero combinations into a much smaller set of disjoint marginal conditions, which speeds up computation. We apply the approach to sample from a semiparametric version of the latent class model with structural zeros in the context of a key issue faced by national statistical agencies seeking to disseminate confidential data to the public: estimating the number of records in a sample that are unique in the population on a set of publicly available categorical variables. The latent class model offers remarkably accurate estimates of population uniqueness, even in the presence of a large number of structural zeros.

We use the cross-state, cross-time variation in bank deregulation across the U.S. states to assess how improvements in banking systems affected the labor market opportunities of black workers. Bank deregulation from the 1970s through the 1990s improved bank efficiency, lowered entry barriers facing nonfinancial firms, and intensified competition for labor throughout the economy. Consistent with Becker's (1957) theory of racial discrimination, we find that in economies where employers have sufficiently strong racial biases, deregulation-induced improvements in the banking system boosted black workers' relative wages by facilitating the entry of new firms and reducing the manifestation . . .

In direct contrast to conventional wisdom and most economic models of marital age gaps, we present robust evidence that men and women who are married to differently-aged spouses are negatively selected. Empirical results show lower cognitive ability, lower educational attainment, lower occupational wages, lower earnings, and less attractive appearance among those married to a differently-aged spouse. These results, obtained using samples of first marriages and controlling for age of marriage, are consistent with a model in which individuals with more schooling and more upwardly-mobile occupations interact more heavily with similarly-aged peers and are ultimately more likely to marry similarly-aged spouses.

The difference between the ways of presentation of the dynamics in databases and ways of visualization of dynamics on the screen is formulated; three groups of the ways of representation of the dynamics of the administrative division are excreted and described, recom‑ mendations for their use are stated, the choice of method the dynamics representation of history of the administrative division of the South Eastern Ukraine for GIS are substantiated

The goal of this paper is to assess the existing state of knowledge about whether SNAP improves health and nutrition outcomes, and if so, which ones and by how much. In an era of fiscal crisis, knowing whether SNAP has any signifi cant causal eff ect on health and nutrition is crucial for informing policy decisions and policy makers. In this review, I pay particular attention to the challenges researchers face in overcoming selection bias and identifying causal eff ects of the program, and I will assess the literature through that lens. The fundamental challenge in program evaluation in general and in assessing the impact of SNAP in particular is that participants are not selected at random from the population. Thus, comparisons of those who use SNAP and those who do not-even conditional on observable characteristics-may not be apples to apples comparisons. To the extent that those who choose to participate in SNAP are negatively selected-as one might expect-SNAP recipients are likely to be less healthy, and thus possible positive estimates of the eff ects of SNAP could be biased downward.

I show that cotton price shocks predict lynchings of African Americans in the US South from 1882 to 1930. Specifically, a standard deviation decrease in the cotton price leads to a 0.095 to 0.16 standard deviation increase in lynchings, within a cotton-producing county. Lynchings also predict more black out-migration from 1920 to 1930. Using a simple model, I show that this is consistent with lynchings having labour market effects that benefitted whites: lynchings cause blacks to migrate away, lowering labour supply and increasing wages for white labourers. I run complier tests to show the mediating effects of railroads, the black-white farm worker ratio, and slavery. I then turn to the long-term effects of lynchings. I show that Mississippi counties with more violence during a 1964 Civil Rights campaign also had more lynchings during the earlier period. Finally, present-day outcomes show that lynchings predict higher black-white worker, family, and household income gaps; a standard deviation rise in past lynchings predicts a 0.08 to 0.15 standard deviation increase in black-white income gaps. These present-day results are robust to historical controls, to the use of California lynchings as a falsification, to the use of white-on-white lynchings as a placebo, and to the use of 1879 cotton acreage as an instrument; they also survive tests using Altonji, Elder, and Taber (2005) statistics.

People with disabilities are generally more vulnerable during disasters and public emergencies than the general population. Physical, sensory and cognitive impairments may result in greater difficulty in receiving and understanding emergency alert information, and greater difficulty in taking appropriate action. The use of social media in the United States has grown considerably in recent years. This has generated increasing interest on the part of national, state and local jurisdictions in leveraging these channels to communicate public health and safety information. How and to what extent people with disabilities use social and other communications media during public emergencies can help public safety organizations understand the communication needs of the citizens in their jurisdictions, and plan their social media and other communications strategies accordingly.

Climate variability is an inherent characteristic of the Earth's climate, including but not limited to climate change. It affects and impacts human society in different ways, depending on the underlying socioeconomic vulnerability of specific places, social groups, households and individuals. This differential vulnerability presents spatial and temporal variations, and is rooted in historical patterns of development and relations between human and ecological systems. This study aims to assess the impact of climate variability on livelihoods and well-being, as well as their changes over time and across space, and for rural and urban populations. The geographic focus is Southern Brazil-the states of Parana, Santa Catarina and Rio Grande do Sul-- and the objectives include (a) to identify and map critical areas or hotspots of exposure to climate variability (temperature and precipitation), and (b) to identify internal variation or differential vulnerability within these areas and its evolution over time (1980-2010), using newly available integrated data from the Terra Populus project. These data include geo-referenced climate and agricultural data, and data describing demographic and socioeconomic characteristics of individuals, households and places.

In this paper, we employ a partially linear nonparametric additive regression estimator, with recent U.S. Current Population Survey data, to analyze returns to schooling. Similar to previous research, we find that blacks and Hispanics have higher rates of return on average. However, for married males, while non-Hispanic whites have lower returns on average, they typically possess the highest returns in the sample. For females, we are able to show that Hispanics have uniformly higher returns over non-Hispanic whites for the full sample. When we restrict our analysis to females whose highest level of education is a high-school diploma, we find average, but no longer uniformly higher returns. However, these uniformly higher returns resurface for college graduates.

Zoning has been cited as a discriminatory policy tool by critics, who argue that ordinances are used to locate manufacturing activity in minority neighborhood(environmental racism) and deter the entry of minority residents into good neighborhoods using density restrictions (exclusionary zoning). However, empirically documenting such discriminatory behavior is complicated by the fact that zoning and land use have been co-evolving for nearly a century in most American cities, rendering discrimination and sorting observationally equivalent. We employ a novel approach to overcome this challenge, studying the introduction of comprehensive zoning in Chicago. Using fine-scale spatial data on the location of African Americans and immigrants across the city along with maps of pre-existing land use, we find strong evidence of environmental racism. Both southern black and immigrant neighborhoods appear to have been targeted for increased levels of industrial use zoning. We also find evidence ofa pre-cursor to modern day exclusionary zoning.

Theories concerning the relationship between economic diversification and growth generate contrasting implications, while empirical studies have been unable to pro- vide conclusive evidence. This paper examines the role of agricultural diversification in the process of development. Evidence from U.S. counties shows that patterns of agricultural production at early stages of development affected structural change and long-run economic performance. Using a novel instrumental variable strategy, which relies on exogenous variation in agricultural diversification generated by natural en- dowments, I show that a one-standard-deviation increase in agricultural diversifica- tion in the mid-19th century led to gains of around 5% in income per capita levels in recent decades. Moreover, the positive effects of diversification can be traced back to the relative size and productivity of the manufacturing sector in the early 20th century, which shows that agricultural diversification affected the industrialization process over the Second Industrial Revolution (1860-1920). An assessment of mech- anisms suggests that the long-term effects of agricultural diversification operated through industrial diversification and human capital formation.

Mapping Segregation in Washington DC is a public history project documenting the historic segregation of DC's housing, schools, playgrounds, and other public spaces. To date the project has focused on racially restrictive housing covenants and how the city's racial geography has been shaped by segregation.

The number of elderly Hispanics, most of whom are immigrants, is growing faster than any other minority group. Even though Hispanics are expected to live longer than non-Hispanic whites, they spend more years living with a disability. Elderly Hispanics are a socially vulnerable group that faces particular financial needs as they tend to have low educational attainment, high levels of poverty, and are more likely to lack health insurance. Understanding the socioeconomic factors associated with physical disability among Hispanics is critical in order to inform public policy to address the needs of this population. I use pooled data from the American Community Survey (ACS) 2008-2012 to examine differences in self-reported physical disability among Hispanic immigrants. First, I determine whether the burden of physical disability is evenly distributed among Hispanic immigrant subgroups, after accounting for demographic and socioeconomic factors. Secondly, I examine whether the relationship between duration of residence in the country and physical disability varies by Hispanic immigrant subgroup. Finally, I explore whether any association between duration of residence and physical limitations can be explained by demographic and socioeconomic differences among Hispanics. Multivariate logistic regressions indicated that there are significant differences among Hispanic immigrant subgroups with Cubans, Central Americans, Mexicans, and Dominicans being more disadvantaged than South Americans. The results indicate that there are little or no significant differences in physical disability among recent arrivals. However, among immigrants with longer residence in the country, Mexicans have higher odds of reporting physical disability than any other immigrant group. While socioeconomic factors, educational attainment, income-to-poverty ratio, occupation, race, and English ability differences reduce the association between length of residence and physical disability, these factors did not explain the observed associations. This study demonstrated that there are important differences among Hispanic immigrant subgroups in physical disability and in their health trajectories.

This essay investigates economic connections between Virginia frontier settlements and Pennsylvania during the period 1746–55. We explore how frontier debtors in remote Augusta County, Virginia, acquired Pennsylvania monetary obligations, what happened when debts involving Pennsylvania money were litigated in Augusta County, and what exchange rate was used in judgments for debts denominated in Pennsylvania money. We find that fluctuations in Augusta County exchange rates correlated to the overall regional market for monetary exchanges involving pounds sterling and Pennsylvania or Virginia money. A statistical tool called the two-tailed student t-test indicates the correlation was not the result of random chance. We therefore conclude that ordinary settlers in the Virginia backcountry were thoroughly acquainted with Pennsylvania market conditions at an earlier period than previously has been recognized.

The United States faces a serious retirement challenge. Many of today's workers will lack the resources to retire at traditional ages and maintain their pre-retirement standard of living. It can be difficult for workers to make informed decisions about their retirements now based on the abundance of confusing and sometimes misleading information put forth by the media and other individuals. For this reason, Charles D. Ellis, Alicia H. Munnell, and Andrew D. Eschtruth have written this highly-accessible guide for individuals wondering what to expect when they reach retirement age and what they can be doing now to best prepare for their future. Falling Short is grounded in academic research yet written in an accessible style for anyone concerned about their future retirement. The authors provide both a vivid picture of the retirement risks facing all Americans and a short list of practical solutions that build on our existing retirement system. The book offers the necessary context for understanding the nature and size of the retirement income shortfall, which is caused by both increasing income needs---due to longer lifespans and rising health costs---and decreasing support from Social Security and employer-sponsored pension plans. The authors give specific advice for what Americans must do now to avoid crisis in retirement; namely, people must work longer and save more. Individuals should plan to stay in the labor force until age 70 and keep their skills up-to-date, and the government should emphasize that retiring at 70 provides the largest monthly Social Security check. Social Security's long-term finances must be shored up so that it remains the foundation of the retirement system. All employers with a 401(k) plan should be required to automatically enroll their workers, increase worker contribution rates over time, and use low-cost index funds as a default investment option. A separate solution is needed for the half of the workforce that lacks even 401(k) coverage; all uncovered workers need an easy and automatic retirement saving option. Finally, individuals should not ignore what is often their largest asset---their house---as a potential source of support for retirement; home equity can be tapped through downsizing or a reverse mortgage. Acting on these solutions now will greatly improve the prospects of a secure retirement for today's workers.

This paper estimates labor supply elasticities of married men and women allowing for heterogeneity among couples (by educational attainments of husbands and wives) and modeling explicitly how household members interact and make their labor supply decisions. We find that the labor supply decisions of husbands and wives depend on each other, unless both spouses are highly educated (college or above). For high-educated couples, the labor supply decisions of husband and wife are jointly determined only if they have pre-school children. We also find that labor supply elasticities differ greatly amoung households. The participation own wage elasticity is largest (0.77) for low-educated women married to low educated men, and smallest (0.03) for high-educated women married to high-educated men and for high educated-women married to high-educated men are similar and fall between these two extremes (about 0.30). For all types of couples, participation elasticity of non-labor family income is small. We also find that cross wage elasticities for married women are relatively small (less than -0.05) if they are married to low educated men and larger (-0.37) if they are married to high-educated men. Allowing for heterogeneity across couples yields an overall participation wage elasticity of 0.56, a cross wage elasticity of -0.13 and an income elasticity of -0.006 for married women. The analysis in this paper provides a natural framework to study how changes in educational attainments and household structure affect aggregate labor supply elasticities.

Indiana’s Common Construction Wage (CCW) is a “prevailing wage law.” Prevailing wage laws (PWLs) establish local standards in labor markets such that the wage rates paid on public construction projects ensure that economic development is broadly shared. PWLs allow workers to support a family in the community where the project is built. Because states and localities typically have statutes which require them to accept the lowest bid on a project letting, contractors must structure their bids to minimize costs and meet minimum engineering and quality standards. Unfortunately, unscrupulous contractors have incentives to cut corners and game the system, with adverse impacts on project quality. The result is often longer-term issues which translate into increased maintenance and reconstruction costs. Since public construction accounts for about one-fourth of the construction market nationwide, the lowbid model used by public bodies puts considerable downward pressure on wages, benefits, and working conditions. Wages are also pushed downward by the inherently seasonal and temporary nature of construction work. Construction workers are always working themselves out of a job, failing to win a bid can swiftly result in a contractor going out of business, and those waiting for another project are vulnerable to accepting reduced wages. Simultaneously, however, the . . .

Attendees at the 2014 Research Data Access and Preservation Summit (RDAP14) heard an update on the DataNet project, funded by the National Science Foundation (NSF) and designed to bring together data research infrastructure organizations to support digital preservation, access, integration and analysis. Five project partners have received funding, each convening collaborating institutions and pursuing group goals. DataONE focuses on data preservation and metadata, distributed storage, usability and assessment, educational outreach, data discovery and interoperability. SEAD (Sustainable Environment Actionable Data) seeks to build a cyberinfrastructure for sustainability science, providing a repository, researcher network and virtual archive. Tools developed by Terra Populus will enable users to extract data from different sources to create custom combinations. The goal of the DataNet Federation Consortium is to support collaborative research and federated collections by putting together a national data infrastructure with client‐friendly metadata templates and bulk uploading to support long‐term management. The DataNet partners continue separate lines of research to build an effective cyberinfrastructure that will support sharing and preserving diverse scientific studies.