Estimating household structure in ancient China by using historical data: a latent class analysis of partially missing patterns

Summary.  Social data often contain missing information. The problem is inevitably severe when analysing historical data. Conventionally, researchers analyse complete records only. Listwise deletion not only reduces the effective sample size but also may result in biased estimation, depending on the missingness mechanism. We analyse household types by using population registers from ancient China (618–907 AD) by comparing a simple classification, a latent class model of the complete data and a latent class model of the complete and partially missing data assuming four types of ignorable and non-ignorable missingness mechanisms. The findings show that either a frequency classification or a latent class analysis using the complete records only yielded biased estimates and incorrect conclusions in the presence of partially missing data of a non-ignorable mechanism. Although simply assuming ignorable or non-ignorable missing data produced consistently similarly higher estimates of the proportion of complex households, a specification of the relationship between the latent variable and the degree of missingness by a row effect uniform association model helped to capture the missingness mechanism better and improved the model fit.     

Household strategies in the face of resource scarcity in coastal Ghana: are they associated with development priorities?

In many developing regions, women and young girls spend several hours daily in the collection of natural resources. Still the link between these household resource strategies and stakeholder perceptions of development priorities remains unexplored. This project examines this association with survey data representative of the adult population from Ghana’s Coastal Region. Although natural resource scarcity and the sustainability of resource use represent key development challenges, there are others (e.g., energy, sanitation, employment, and educational opportunities). As such, even in the face of natural resource scarcity, individuals may place greater importance on other dimensions of development, especially if household resource strategies are perceived as relatively efficient. The analytical focus here is on water and the results suggest that gender roles shape household water collection strategies, while also shaping these strategies’ perceived opportunity costs. Specifically, Ghanian adults more often see drinking water provision as their primary development need when water sources are distant and/or when male household members collect water (particularly male heads). In the end, I argue that social science inquiry benefits by contextualizing social dynamics within environmental context, particularly within cultural settings in which human subsistence is intimately tied to the state of the natural environment.     

Household debt and financial assets: evidence from Germany, Great Britain and the USA

Summary.  We explore the determinants of debt, financial assets and net worth at the household level by using survey data for Germany, Great Britain and the USA. To identify which households are potentially vulnerable to adverse changes in the economic environment, we also explore the determinants of a range of measures of financial pressure: the probability that a household has negative net worth; the debt-to-income ratio; mortgage income gearing; the saving-to-income ratio. Our empirical findings suggest that the poorest and the youngest households are the most vulnerable to adverse changes in their financial circumstances.     

The econometrics of female labor supply and children

This is a survey of applied econometric research on the effects of children on female labor supply. Reasons for interest in the topic, and a basic model and terminology, are reviewed. Concerns are raised about the possible endogeneity of child status variables, and about the instrumental variables approach for dealing with this problem. Alternative ways of conceptualizing and estimating child status effects are considered, together with selected empirical evidence. Relevant developments from the household demand literature are summarized. Basic issues of model choice are also discussed.     

An Assessment of Change in Risk Perception and Optimistic Bias for Hurricanes Among Gulf Coast Residents

This study focuses on levels of concern for hurricanes among individuals living along the Gulf Coast during the quiescent two‐year period following the exceptionally destructive 2005 hurricane season. A small study of risk perception and optimistic bias was conducted immediately following Hurricanes Katrina and Rita. Two years later, a follow‐up was done in which respondents were recontacted. This provided an opportunity to examine changes, and potential causal ordering, in risk perception and optimistic bias. The analysis uses 201 panel respondents who were matched across the two mail surveys. Measures included hurricane risk perception, optimistic bias for hurricane evacuation, past hurricane experience, and a small set of demographic variables (age, sex, income, and education). Paired t‐tests were used to compare scores across time. Hurricane risk perception declined and optimistic bias increased. Cross‐lagged correlations were used to test the potential causal ordering between risk perception and optimistic bias, with a weak effect suggesting the former affects the latter. Additional cross‐lagged analysis using structural equation modeling was used to look more closely at the components of optimistic bias (risk to self vs. risk to others). A significant and stronger potentially causal effect from risk perception to optimistic bias was found. Analysis of the experience and demographic variables’ effects on risk perception and optimistic bias, and their change, provided mixed results. The lessening of risk perception and increase in optimistic bias over the period of quiescence suggest that risk communicators and emergency managers should direct attention toward reversing these trends to increase disaster preparedness.     

The Impact of Personal Finance Education Delivered in High School and College Courses

This study investigates the impact of personal finance education delivered in high school and college. Outcomes of interest were investment knowledge and household savings rates measured years after the financial education was delivered. A web-based survey with questions about participation in financial education, financial experiences, income and inheritances, and demographic characteristics was administered to 1,039 alumni from a large midwestern university. Participation in a college level personal finance course was associated with higher levels of investment knowledge. Experience with financial instruments appeared to explain more of the variance in both investment knowledge and savings rates. No significant relationship between taking a high school course and investment knowledge was found. Financial experiences were found to be positively associated with savings rates.

Welfare analysis of a tax reform for Germany: a comparison of the unitary and collective models of household labour supply

We compare results of a tax reform analysis obtained with the collective and unitary models of household behaviour. We simulate real world micro-data by means of a collective approach, using a compound procedure of estimation and calibration based on the 1998 wave of the German socio-economic panel. We estimate a unitary model on this ‘collective’ data set. Investigating a move from joint to individual taxation on the basis of both models, we obtain important discrepancies between predicted adjustments to labour supply and distortions in the welfare analysis of the reform on the basis of unitary estimates.      

Toward an integrated Bayesian network approach to measurement error detection and correction

In this article, the quality of data produced by national statistical institutes and by governmental institutions is considered. In particular, the problem of measurement error is analyzed and an integrated Bayesian network decision support system based on non-parametric Bayesian networks is proposed for its detection and correction. Non-parametric Bayesian networks are graphical models expressing dependence structure via bivariate copulas associated to the edges of the graph. The network structure and the misreport probability are estimated using a validation sample. The Bayesian network model is proposed to decide: (i) which records have to be corrected; (ii) the kind and amount of correction to be adopted. The proposed correction procedure is applied to the Banca d’Italia Survey on Household Income and Wealth and, specifically, the bond amounts are analyzed. Finally, the sensitivity of the conditional distribution of the true value random variable given the observed one to different evidence configurations is studied.     

Household gambling expenditures and the Irish recession

This article examines the determinants of household gambling expenditures in Ireland and the effects of the recession on these expenditures using a large micro data-set, the Irish Household Budget Survey (HBS). Two gambling expenditures are examined, bookmaker tote betting and spending on the national lottery. Households with an older and a less educated head of household participate in and spend more on both forms of gambling while the presence of children in the households tends to reduce participation and spending in gambling. There is also evidence to suggest that households with an unemployed head of household have a higher likelihood of participation in gambling. The recession has affected the two forms of gambling in different ways. Lottery expenditures appear resilient to the effects of the recession. This is demonstrated in the estimated expenditure elasticities in particular. Bookmaker/tote expenditures have changed from a necessity to a luxury good, while lottery expenditures have increased in their necessity status. This can be explained by the fact that playing the lottery requires less time, knowledge and risk and has potentially greater benefits attached to it in comparison to bookmaker/tote betting. During a recession these factors become much more prevalent.     

户籍类型与城乡居民医疗服务利用 ——基于Andersen模型的经验分析

本文利用中国社会科学院经济研究所2018年城乡居民入户调查数据,从户籍改革角度分析户口类型改变对城乡居民医疗服务利用的影响。研究发现:与户口类型未发生改变的城乡居民相比,户口类型发生过改变(农转非)的城乡居民门急诊服务利用的可能性更高,住院医疗服务支出水平更低。从户籍改革与参保类型交互效应看,相对于户口类型未发生过改变的居民医保参保人群,户口类型发生改变(农转非)会显著提高居民医保参保人群门急诊服务利用,同时降低其住院服务利用。进一步采用PSM方法进行稳健性检验,户籍改革对提高城乡居民门急诊服务利用,降低住院医疗服务利用的结论依然成立。此外,本文还发现,直接结算提高了城乡居民门急诊和住院的就诊概率;健康自评状况越差,门急诊和住院医疗服务利用可能性越高,门急诊医疗支出、住院医疗支出和跨省异地就医支出也越高。本文认为,相对于推行基层分级诊疗制度,以户籍改革推动农村居民自由流入医疗资源更丰富的城镇地区,改革基层卫生院制度,以及改变基层医疗服务提供激励机制,可能更有助于改善农村居民健康状况。