Historical Methods最新文献

This paper presents a probabilistic method of record linkage, developed using the U.S. full count censuses of 1900 and 1910 but applicable to many sources of digitized historical records. The method links records using a two-step approach, first establishing high confidence matches among men by exploiting a comprehensive set of individual and contextual characteristics. The method then proceeds to link both men and women by leveraging links between households established in the first step. While only the first stage links can be directly comparable to other popular methods in research on the U.S., our method yields both considerably higher linkage rates and greater accuracy while only performing negligibly worse than other algorithms in resembling the target population.

This paper describes a method to reconstruct complete birth histories for women in the 1900 and 1910 U. S. census IPUMS samples. The method is an extension of an earlier method developed by Luther and Cho (1988). The basic method relies on the number of children ever born, number of children surviving, number of children coresident in the household and age-specific fertility rates for the population to probabilistically assign an "age" to deceased and unmatched children. Modifications include the addition of an iterative Poisson regression model to fine-tune age-specific fertility inputs. The potential of complete birth histories for the study of the U.S. fertility transition is illustrated with a few examples.

New large-scale linked data are revolutionizing quantitative history and demography. This paper proposes two complementary strategies for improving inference with linked historical data: the use of validation variables to identify higher quality links and a simple, regression-based weighting procedure to increase the representativeness of custom research samples. We demonstrate the potential value of these strategies using the 1850-1930 Integrated Public Use Microdata Series Linked Representative Samples (IPUMS-LRS)-a high quality, publicly available linked historical dataset. We show that, while incorrect linking rates appear low in the IPUMS-LRS, researchers can reduce error rates further using validation variables. We also show how researchers can reweight linked samples to balance observed characteristics in the linked sample with those in a reference population using a simple regression-based procedure.

The U.S. Census Bureau has created a set of linkable census, survey, and administrative records that provides longitudinal data on the American population across the past eight decades. While these files include modern decennial censuses, Census Bureau surveys, and administrative records files from other federal agencies, the long time span is only possible with the addition of the complete count 1940 Census microdata. In this paper, we discuss the development of this linked data infrastructure and provide an overview of the record linkage techniques used. We primarily focus on the techniques used to produce a beta version of a linkable 1940 Census microdata file and discuss the potential to further document and extend the infrastructure.

Despite there being several estimates for famine-related deaths in the west of The Netherlands during the last stage of World War II, no such information exists for war-related excess mortality among the civilian population from other areas of the country. Previously unavailable data files from Statistics Netherlands allow researchers to estimate the number of war-related excess deaths during the last stage of the war in the whole country. This study uses a seasonal-adjusted mortality model combined with a difference-in-difference approach to estimate the number of excess deaths in the period between January 1944 and July 1945 at a total of close to 91,000 (75%) excess deaths. Almost half of all war-related excess mortality during the last year of the war occurred outside the west.

This paper overviews the research opportunities made possible by a NIA-funded program project, Early Indicators, Intergenerational Processes, and Aging. Data collection began almost three decades ago on 40,000 soldiers from the Union Army in the US Civil War. The sample contains extensive demographic, economic, and medical data from childhood to death. In recent years, a large sample of African-American soldiers and an oversampling of soldiers from major US cities have been added. Hundreds of historical maps containing public health data have been geocoded to place soldiers and their family members in a geospatial context. With newly granted funding, thousands of veterans will be linked to the demographic information available from the census and vital records of their children.

Most quantitative research on segregation and neighborhood change in American cities prior to 1940 has utilized data published by the Census Bureau at the ward level. The transcription of census manuscripts has made it possible to aggregate individual records to a finer level, the enumeration district (ED). Advances in Geographic Information Systems (GIS) have facilitated mapping these data, opening new possibilities for historical GIS research. We report here the creation of a mapped public use data set for EDs in ten northern cities for each decade from 1900 to 1930. We illustrate a range of research topics that can now be pursued: recruitment into ethnic neighborhoods, the effects of comprehensive zoning on neighborhood change, and white flight from black neighbors.

The U.S. National Health Interview Survey (NHIS) is the world's longest survey time series of health data and a rich source of information on health conditions, behaviors, and care from the 1960s to the present. NHIS public-use files are difficult to use for long-term analysis, due to complex file structure, changes in questionnaire content, and evolving variable names and coding schemes. Researchers at the Minnesota Population Center have created the Integrated Health Interview Series (IHIS) to overcome these problems. IHIS provides access to thousands of consistently coded and well-documented NHIS variables on the Internet and makes it easy to analyze health trends and differentials. IHIS multiplies the value of NHIS data by allowing researchers to make consistent comparisons over half a century and thus to study U.S. health status as a dynamic process. This article describes the main features of IHIS and suggests fruitful avenues for historical research using these invaluable health data.

The Urban Transition Historical GIS Project is a new data resource for United States counties and cities that takes advantage of NAPP's 100% digital transcription of records from the 1880 Census. It has developed several additional resources to make possible analysis of social patterns at the level of individuals and households while also taking into account information about their communities. One key contribution is the creation of historically accurate GIS maps showing the boundaries of enumeration districts in 39 major cities. These materials are now publicly available through a web-based mapping system. Addresses of all households in these cities are also being geocoded, a step that will enable spatial analyses of residential patterns at any geographic scale. Preliminary analyses demonstrate the utility of multiple scales and the ability to combine information about individuals with data about their neighborhoods.

The Minnesota Population Center (MPC) provides aggregate data and microdata that have been integrated and harmonized to maximize crosstemporal and cross-spatial comparability. All MPC data products are distributed free of charge through an interactive Web interface that enables users to limit the data and metadata being analyzed to samples and variables of interest to their research. In this article, the authors describe the integrated databases available from the MPC, report on recent additions and enhancements to these data sets, and summarize new online tools and resources that help users to analyze the data over time. They conclude with a description of the MPC's newest and largest infrastructure project to date: a global population and environment data network.