Extracting More Knowledge from Time Diaries?

Time-use diary data convey information about the activities an individual was engaged in, when and for how long, and the order of these activities throughout the day. The data are usually analyzed by summarizing the time used per activity category. The aggregates are then used to determine the mean time use of a mean individual on an average day. However, this approach discards information about the duration of activities, the order in which they are undertaken, and the time of day each activity is carried out. This paper outlines an alternative approach grounded in the time-geographic theoretical framework, which takes the duration, order, and timing of activities into consideration and thus yields new knowledge. The two approaches to analyzing diary data are compared using a simple empirical example of gender differences in time use for paid work. The focus is on the effects of methodological differences rather than on the empirical outcomes. The argument is made that using an approach that takes the sequence of activities into account deepens our understanding of how people organize their daily activities in the context of a whole day at an aggregate level.     

Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index

This study uses data from the Framingham Heart Study to examine the relevance of the gene-environment interaction paradigm for genome-wide association studies (GWAS). We use completed college education as our environmental measure and estimate the interactive effect of genotype and education on body mass index (BMI) using 260,402 single-nucleotide polymorphisms (SNPs). Our results highlight the sensitivity of parameter estimates obtained from GWAS models and the difficulty of framing genome-wide results using the existing gene-environment interaction typology. We argue that SNP-environment interactions across the human genome are not likely to provide consistent evidence regarding genetic influences on health that differ by environment. Nevertheless, genome-wide data contain rich information about individual respondents, and we demonstrate the utility of this type of data. We highlight the fact that GWAS is just one use of genome-wide data, and we encourage demographers to develop methods that incorporate this vast amount of information from respondents into their analyses.     

Sampling Weights for Analyses of Couple Data: Example of the Demographic and Health Surveys

In some surveys, women and men are interviewed separately in selected households, allowing matching of partner information and analyses of couples. Although individual sampling weights exist for men and women, sampling weights specific for couples are rarely derived. We present a method of estimating appropriate weights for couples that extends methods currently used in the Demographic and Health Surveys (DHS) for individual weights. To see how results vary, we analyze 1912 estimates (means; proportions; linear regression; and simple and multinomial logistic regression coefficients, and their standard errors) with couple data in each of 11 DHS surveys in which the couple weight could be derived. We used two measures of bias: absolute percentage difference from the value estimated with the couple weight and ratio of the absolute difference to the standard error using the couple weight. The latter shows greater bias for means and proportions, whereas the former and a combination of both measures show greater bias for regression coefficients. Comparing results using couple weights with published results using women’s weights for a logistic regression of couple contraceptive use in Turkey, we found that 6 of 27 coefficients had a bias above 5 %. On the other hand, a simulation of varying response rates (27 simulations) showed that median percentage bias in a logistic regression was less than 3 % for 17 of 18 coefficients. Two proxy couple weights that can be calculated in all DHS surveys perform considerably better than either male or female weights. We recommend that a couple weight be calculated and made available with couple data from such surveys.     

Behaviour and the life cycle: a consideration of the role of longitudinal time use studies

This paper discusses the application of time use data for the study of behavioural change over the life cycle. The longitudinal design reduces the need for complex statistical controls and sample matching procedures and simplifies the problem of distinguishing period effects from cohort and development effects.The data are based upon 24 hour time diaries of a panel of 453 persons in Halifax, Canada who were interviewed on the same day of the week in the Fall of both 1971 and 1981. Data for each gender are presented illustrative of the kinds of changes in time use which might be associated with aging or with changes in occupational, financial, educational, or familial status. Cross-sectional time use data from different periods can be used in conjunction with the longitudinal time use data to differentiate between behavioural change based upon maturation or other individual changes and that deriving from a broader base of cultural change.     

Cumulative Disadvantage and Connections Between Welfare Problems

In this paper, we perform a latent class factor analysis of a panel that involves two waves of data from an annual survey of living conditions in Sweden that were gathered in the years 1994–1995 and 2002–2003. We follow the same 3,149 individuals over both waves, describing them by sex, age group, family type, nationality background, education level and socio-economic class. Further, since the welfare disadvantages included in the analysis are chronic unemployment, economic problems, health problems, experiences of threat or violence, crowded housing, lack of a close friend and sleeping problems, we also have data on exactly which welfare problems each individual in the data set suffers from. In the empirical analysis, latent class factor analysis provides us not only with information on which individual characteristics that are important in the accumulation of welfare problems, but also gives us information on which disadvantages in fact are accumulated. First, we find that welfare problems do cluster. Second, the welfare problems that most often appear at a factor level with several disadvantages are experiences of threat or violence and sleeping problems. Finally, being an immigrant and being single are individual characteristics that turn up most often in factor levels with problem accumulation, whereas there is no distinctive difference between the sexes. However, women seem to be more prone to suffer from experiences of threat or violence and sleeping problems, while men are more likely to suffer from lack of a close friend.     

Methods for combining ancillary data in stochastic compartment models of cancer mortality: Generalization of heterogeneity models∗

In analyzing mortality data there may be available information from survey and other sources that describe the marginal distribution of risk factors. We present a mortality model where nationally representative survey data on risk factor distributions are combined with data on cohort mortality rates to increase information, i.e., a fixed marginal risk factor distribution is combined with a cohort model representing unobserved individual risk heterogeneity. The model is applied to lung cancer mortality in nine U.S. white male cohorts aged 30 to 70 in 1950 and followed 38 years. Estimates of the cohort specific proportions of smokers were made from the National Health Interview Survey. Comparisons are made for models with different patterns of changes with age of individual heterogeneity.     

The importance of education-occupation matching in migration decisions

In this article, we present and test a model that incorporates education-occupation matching into the migration decision. The literature on education-occupation matching shows that earnings are affected by how individuals' education matches that required by their occupation. Accordingly, individuals with more schooling than required by their occupation have an additional incentive to migrate: the increase in earnings that occurs with a more beneficial education-occupation match. Using data from Mexico, we found statistical support for the importance of education-occupation matching in migration decisions. Education-occupation matching provides a plausible explanation for the mixed findings in the literature on the relationship between educational attainment and migration.     

Household structure and child nutrition: A reinterpretation of income and mother's education

Two frequently used predictors of child malnutrition are family income and mother's education. Despite their common sense rationale, they pose difficult and perhaps intractable problems of measurement and conceptualization. This paper proposes to substitute the concepts of family and maternal differentiation for these traditionally used indicators. Differentiation is defined as the capacity of the individual or group to process a diversity of information categories. Using data from a recent survey of households in Panama, indicators of this concept were constructed at the family and at the maternal levels using principal component analysis. These are shown to predict a range of indicators of childrens' nutritional status when appropriate control variables are included in the regression analysis. The same analysis was then repeated with income and mother's education replacing the differentiation measures. The results support our claim that the differentiation indicators are superior, and we argue that an even more important reason for using them is that they open the door to a long-term research program that is theoretically consistent and potentially cumulative.     

Report on matching procedures of a dual record system in the southern Philippines

There are generally three stages to the development of rules for matching vital events data from two sources covering the same population: (a) establishing a set of “true” matches and nonmatches; (b) determining the best tolerance limits for each single characteristic which might be used in matching; and (c) experimenting to determine the set or sets of characteristics and the weights to be used in classifying a pair of records as matched or nonmatched. Specific examples, based on early matching experiments with data from the dual record system of the Mindanao Center for Population Studies (MCPS), are presented. Successive application of different sets of characteristics (differential valence rule) to the remaining unmatched events produced an acceptable rule for matching in this study.     

Social Capital and Subjective Wellbeing in Europe: A New Approach on Social Capital

This paper aims to analyze the relationship between the various dimensions of social capital and subjective wellbeing. Data used in this study come from the fourth wave of the European Social Survey and different measures of wellbeing are used to take account of both the cognitive and affective processes of individual wellbeing (i.e. life satisfaction, happiness, and subjective wellbeing). A factor analysis is performed to summarize information coming from a large set of variables into different components corresponding to each dimension of social capital (i.e. networks, norms, and trust). Among the results, we find that the impact of social capital on subjective wellbeing differ depending on the component of social capital which is under analysis. In particular, social networks, social trust and institutional trust are the components that show a higher correlation with subjective wellbeing. Furthermore, in addition to the positive effects of the individual variables, our results suggest that social capital at the aggregate level positively correlates with individual wellbeing, thus pointing to an external or environmental effect of social capital.     

高等教育质量收益的估计:基于倾向指数匹配法的研究

文章基于2005年中国城镇居民调查数据,估计接受高质量高等教育对劳动者工资的影响。研究以211大学作为高质量大学的标准,并使用倾向指数匹配法克服传统的OLS估计方法的缺陷。研究发现,个体能力、家庭背景、高中教育质量及大学入学机会都是影响个体能否进入高质量大学的因素。同时,匹配法的估计结果表明,在中国高等教育质量具有较高的收益,对毕业于211大学的劳动者而言,上211大学的平均收益可能使其年工资增长了37.5%。     

Social inequality of reading literacy: A longitudinal analysis with cross-sectional data of PIRLS 2001 and PISA 2000 utilizing the pair wise matching procedure

In accordance to Boudon's structural-individualistic action model, it is the aim of this paper to investigate the casual effects of individual abilities, resources of the parental home, socially selective educational transitions as well as teaching and learning conditions in schools on the development of reading literacy and its dispersion in respect of social origin. It is assumed that the socially selective transition into the secondary school tracks contributes to the general deterioration of the mean reading literacy when controlling for social origin and individual achievement. The socially selective transition from primary to secondary school contributes to the increase of social inequality of reading literacy existing already since the start of the pupils’ schooling. Since it is not possible to isolate these causes with comparative-static cross-sectional data like PIRLS or PISA empirically, we use a design of generating quasi-longitudinal data with three time references, namely reading literacy at the point of enrolment into elementary school, at the age of 9–10 years, and at the age of 15 years by the pair wise matching of “synthetic twins” with identical status criteria. The empirical analysis of the German data of PISA 2000 and PIRLS 2001 confirm the effects of the individual abilities depending on social origin, the social selectivity of transition into the secondary schools, the sorting and selection performances of the school system, the allocation of children into different learning contexts, and the schooling of both the individual development of reading competences and the social inequality of reading literacy.     

Forgone labor participation and earning due to childbearing among Norwegian women

Individual-level retrospective data from the Family and Occupation Survey of 1988 are used to assess the time diverted from gainful employment because of the presence of children in two Norwegian birth cohorts. We find that a two-child mother born in 1950, whose births occurred in her early twenties, lost 6.6 women-years up to age 37, compared to a childless woman. By matching information on registered income with the survey data, we estimate that her lost income amounts to $151,000 at 1990 prices. After taxation the loss is $98,000. Women with fewer than 12 years of schooling seem to forgo more labor market activity by reason of childbearing than do their better-educated counterparts. The pattern is less clear with respect to the loss of income.     

Quantifying the costs of drought: new evidence from life satisfaction data

We estimate the cost of droughts by matching rainfall data with individual life satisfaction. Our context is Australia over the period 2001 to 2004, which included a particularly severe drought. Using fixed-effect models, we find that a drought in spring has a detrimental effect on life satisfaction equivalent to an annual reduction in income of A$18,000. This effect, however, is only found for individuals living in rural areas. Using our estimates, we calculate that the predicted doubling of the frequency of spring droughts will lead to the equivalent loss in life satisfaction of just over 1% of GDP annually.

Space,Context, and Human Capital: A Micro–Macro Perspective on the Social Environment and Financial Literacy in Later Life

Despite a large body of literature documenting the association between individual characteristics and financial literacy, our understanding of the impact of macro-environmental conditions on individual financial literacy remains limited, particularly in later life. Drawing from a micro–macro perspective on the social environment and individual processes, we examined the extent to which three state-level contextual characteristics were associated with individual financial literacy: tertiary educational attainment, poverty prevalence, and Internet penetration. We utilized data from the Understanding America Study for adults aged 50 years or older to assess financial literacy and data from the American Community Survey to evaluate contextual conditions. Cross-sectional multilevel regression models were used to examine the hypothesized effects. We found that state-level poverty prevalence was negatively associated with individual financial literacy, while state-level Internet penetration was positively associated with individual financial literacy, over and above individual characteristics known to impact financial literacy. No association was found between state-level educational attainment and individual financial literacy after controlling for respondents’ own education. Findings suggest that the social environment may condition older adults’ financial literacy through exposure to opportunities that promote knowledge acquisition. Interventions to enhance older adults’ financial literacy may benefit from targeted approaches that take into account the environmental characteristics of their locations of residence.

     

The Missing Link: Deficits of Country-Level Studies. A Review of 22 Articles Explaining Life Satisfaction

To explain country differences in an analytical or structural dependent variable, the application of a macro–micro-model containing contextual hypotheses is necessary. Our methodological study examines whether empirical studies apply such a model. We propose that a theoretical base for country differences is well described in multilevel studies, but aggregate and individual data analyses fail to specify contextual hypotheses ex ante (in the theory section of an article) and instead elaborate on macro–micro explanations ex post (in the discussion section). To test our assumptions, we analyzed 22 studies published in journals cited in the Social Science Citation Index between 2007 and 2010, which compare countries with respect to life satisfaction. Results are in accordance with our expectations. We conclude that cross-country comparisons should apply a macro–micro-model theoretically and empirically, if possible, and include the meso level, if appropriate. In case of insufficient data (i. e. only individual level or aggregate level data), applying a macro–micro-model theoretically may prevent premature conclusions.     

Your House,Your Car,Your Education: The Socioeconomic Situation of the Neighborhood and its Impact on Life Satisfaction in Germany

This study deals with the impact of socioeconomic conditions and social integration into a local neighborhood on individual life satisfaction in Germany. While the majority of ecological studies to date are based on very broad neighborhood concepts, using large research units for defining neighborhood the present study contains micro-geographic information on a representative sample of private households in Germany, including features of their respective residential environments. The data was derived from the German Socio-Economic Panel (SOEP) study and enriched with data from the Micromarketing-Systeme and Consult GmbH (microm) for the years 2000–2006. Our analyses reveal neighborhood effects on various facets of life satisfaction. Controlling for several covariates at the household and individual level, life satisfaction increases when a person lives in a neighborhood with a higher socioeconomic status. In addition, the individual gap between a person’s economic status and the status of the neighborhood also affects individual well-being. However, when comparing with other neighborhood aspects, the strongest effects on individual life satisfaction have social networks.     

Individual and couple utility of children

Models specifying the utility of another child as either a couple or an individual experience and incorporating variations in the measurement properties of responses about child utility and expectations are estimated with data from the U.S. Value of Children survey. Full information, maximum likelihood analyses indicate that child utility is an individual experience of wives and husbands rather than a shared couple experience. That is, differences in the measurement properties of wives’ and husbands’ responses do not account entirely for the less than perfect correlations between their responses. These findings demonstrate the importance of estimating errors in measurement in the analysis of wives’ and husbands’ responses about the utility of children, and they challenge the assumption that marital partners share the utility of children.     

The demographic assessment of family planning programs: a bibliographic essay

Over the past 15-20 years a substantial literature has accumulated in the area of determining the effect of family planning programs upon fertility, and a selected bibliography is provided. The development of modern contraceptive techniques coincided with the development of large national programs designed to reduce the fertility of the general population, and literature is presented on each of the several evaluation methods that have been used to examine program-induced changes in 1 or more fertility measures. 2 methods deal with data on individuals - births averted among acceptors and individual matching; the latter compares the fertility experience of acceptors and matched non-acceptors. A different class of methods is aggregated methods. Either areas and areal variables are the focus of the analysis proceeds with measures on general subgroups identified by such factors as residence, age, or marital status. The aggregate methods are multiple regression, program experiemnts, matching of areas, correspondence between program activity and fertility change, decomposition, and simulation. The disparity in methods has conspired with large differences in programs, data sets, and investigator interests to produce serious problems of non-comparability in results.     

Methods for combining ancillary data in stochastic compartment models of cancer mortality: generalization of heterogeneity models

"We present a mortality model where nationally representative survey data on risk factor distributions are combined with data on cohort mortality rates to increase information, i.e., a fixed marginal risk factor distribution is combined with a cohort model representing unobserved individual risk heterogeneity. The model is applied to lung cancer mortality in nine U.S. white male cohorts aged 30 to 70 in 1950 and followed 38 years. Estimates of the cohort specific proportions of smokers were made from the National Health Interview Survey. Comparisons are made for models with different patterns of changes with age of individual heterogeneity." (SUMMARY IN FRE)