The perils of father-reported fertility data for household labour supply models

Many panel data-sets contain father-reported fertility data. Yet, since men tend to underreport past fertility--especially daughters or children from previous marriages--using such data can lead to significantly biased results when estimating household labour supply models. For example, when analysing fertility data from the Panel Study of Income Dynamics, which has a significant retrospective component, fathers' labour supply appears more responsive to the births of sons than to daughters (Lundberg and Rose, Review of Economics and Statistics 84(2): 251-268, 2002). However, no evidence for this differential can be found in a much larger sample of Current Population Survey data from the same population. It is important for researchers to consider the provenance of data on fertility variables and to undertake robustness checks with data reported by women whenever possible.     

Retrospective information on health status and its application for population health measures

Healthy life expectancies are almost always calculated by using health data from cross-sectional surveys. This type of calculation is done partly because data from longitudinal surveys are not always available, and when they are available, they are collected at intervals that are longer than one year. In such cases, collecting health information retrospectively for the years skipped by the survey is useful. The main purpose of this paper is to show how retrospective health information can be used to estimate life expectancies in different health states. Healthy life expectancies are estimated with and without using data on retrospective health information, and the corresponding estimates are compared. The two sets of estimates are similar. We conclude that retrospectively assessed health information based on a one-year recall period can be used to estimate years of life in various health states and that estimates based on such information will closely approximate estimates based on concurrent health information.     

Providing Spatial Data for Secondary Analysis: Issues and Current Practices Relating to Confidentiality

Spatially explicit data pose a series of opportunities and challenges for all the actors involved in providing data for long-term preservation and secondary analysis—the data producer, the data archive, and the data user. We report on opportunities and challenges for each of the three players, and then turn to a summary of current thinking about how best to prepare, archive, disseminate, and make use of social science data that have spatially explicit identification. The core issue that runs through the paper is the risk of the disclosure of the identity of respondents. If we know where they live, where they work, or where they own property, it is possible to find out who they are. Those involved in collecting, archiving, and using data need to be aware of the risks of disclosure and become familiar with best practices to avoid disclosures that will be harmful to respondents.

Person, Perception, and Place: What Matters to Health and Quality of Life

Interest in understanding how characteristics associated with where people live, in addition to the characteristics of the people themselves, affect health outcomes has risen sharply in recent years. While much of the research examining this question focus on teasing apart effects of place and individual on outcomes, less attention has been paid to examining how individuals’ perceptions of where they live may provide some clues to better understanding the influence of place on outcomes. We present findings from analysis undertaken that incorporate the subjective responses of individuals, residing in three socially contrasting neighbourhoods, to their local environment. Our first question addressed whether perceptions related to neighbourhood and city of residence matter to self rated health and quality of life independent of individual characteristics, while the second question examined whether the perceptions and individual characteristics are modified by the neighbourhood socio-economic context. Our results show that perceived neighbourhood characteristics, in addition to individual sociodemographic factors, are significant correlates of self rated health and quality of life. Moreover, we show that the type of perceived neighbourhood characteristics and the magnitude of their influence on self rated health and quality of life vary depending on whether they live in high- versus low-socioeconomic status neighbourhoods.

历史分析与比较政治

本文讨论了比较政治学中历史研究的主要分析方法.第一类是因果分析法,包括横截面分析法和样本内分析法.第二类是时序分析法,包括对路径依赖和发展顺序的分析.本文认为,历史分析与众不同的分析方法使它成为比较政治研究中有力的分析工具.     

Quantifying Intrinsic and Extrinsic Contributions to Human Longevity: Application of a Two-Process Vitality Model to the Human Mortality Database

The rise in human life expectancy has involved declines in intrinsic and extrinsic mortality processes associated, respectively, with senescence and environmental challenges. To better understand the factors driving this rise, we apply a two-process vitality model to data from the Human Mortality Database. Model parameters yield intrinsic and extrinsic cumulative survival curves from which we derive intrinsic and extrinsic expected life spans (ELS). Intrinsic ELS, a measure of longevity acted on by intrinsic, physiological factors, changed slowly over two centuries and then entered a second phase of increasing longevity ostensibly brought on by improvements in old-age death reduction technologies and cumulative health behaviors throughout life. The model partitions the majority of the increase in life expectancy before 1950 to increasing extrinsic ELS driven by reductions in environmental, event-based health challenges in both childhood and adulthood. In the post-1950 era, the extrinsic ELS of females appears to be converging to the intrinsic ELS, whereas the extrinsic ELS of males is approximately 20 years lower than the intrinsic ELS.     

A Bayesian Approach for Analyzing Results of Vehicle Collision Tests

Certain motor vehicle safety standards stipulate a collision test speed and a set of performance criteria that vehicles must satisfy during or after the collision test. For example, Federal Motor Vehicle Safety Standard 301 requires a 30 mile per hour (mph) barrier collision and specifies a certain maximum allowable limit on the total spillage of fuel. Vehicle designs are required to meet this standard; however, when collision tests are conducted at speeds higher than the standard, vehicles do not always satisfy the performance criteria. This paper develops a mathematical model for estimating the probability of meeting the standard by using a Bayesian framework to incorporate engineering judgment with collision test results. The model is based on the idea that there are random features to a vehicle's ability to meet performance standards in a collision, especially at such elevated speeds. Example calculations are included to illustrate the estimation of the probability of meeting the standard and to compare it with a maximum likelihood approach.