Convergence or Continuity? The Gender Gap in Household Labor After Retirement

This research examined 2 hypotheses about the effect of retirement on couples' division of household labor. The continuity hypothesis posits that the gender gap in household labor remains unaffected by retirement, whereas the convergence hypothesis expects it to close. The authors tested these hypotheses using longitudinal data from the German Socio‐Economic Panel Study (N = 1,302 couples). Fixed effects models revealed that male breadwinners doubled up on total hours of household labor across their transition to retirement. This rise was accompanied by a concurrent, albeit less pronounced, decline in wives' hours. As a result, the gender gap in household labor was cut in half. This convergence involved a moderate trade‐off in female‐typed tasks of routine housework and an increase in husbands' hours spent on male‐typed tasks of repairs and gardening. The study concludes that gendered patterns of time use change substantially after retirement, rendering couples' division of household labor more equitable in later life.     

What Does Really Drive Consumer Confidence?

We construct a novel index of households’ macroeconomic environment (HOME) based on the data from 22 high-income European countries between 2002 Q1 and 2018 Q4. The resulting index is in line with the broad features of the countries’ business and financial cycles and captures well households’ perception of their underlying economic situation. We discuss joint properties of the HOME index and the widely employed survey-based consumer confidence indicator. We show that households’ expectations are tightly linked to current macroeconomic conditions. This finding echoes the literature linking consumer attitudes and actual economic developments. The HOME index also reflects the importance of asset prices and lending conditions for households’ behavior. In a single-country case study, we provide empirical evidence that links the proposed index to new credit extended to households. The evidence suggests that households need a longer period of good macroeconomic conditions to decide to take on a mortgage than they do in the case of a consumer loan.

     

A bivariate first-order signed integer-valued autoregressive process

Bivariate integer-valued time series occur in many areas, such as finance, epidemiology, business etc. In this article, we present bivariate autoregressive integer-valued time-series models, based on the signed thinning operator. Compared to classical bivariate INAR models, the new processes have the advantage to allow for negative values for both the time series and the autocorrelation functions. Strict stationarity and ergodicity of the processes are established. The moments and the autocovariance functions are determined. The conditional least squares estimator of the model parameters is considered and the asymptotic properties of the obtained estimators are derived. An analysis of a real dataset from finance and a simulation study are carried out to assess the performance of the model.     

Weighted-Average Least Squares Prediction

Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty from the selection procedure. This article proposes a weighted-average least squares (WALS) prediction procedure that is not conditional on the selected model. Taking both model and error uncertainty into account, we also propose an appropriate estimate of the variance of the WALS predictor. Correlations among the random errors are explicitly allowed. Compared to other prediction averaging methods, the WALS predictor has important advantages both theoretically and computationally. Simulation studies show that the WALS predictor generally produces lower mean squared prediction errors than its competitors, and that the proposed estimator for the prediction variance performs particularly well when model uncertainty increases.     

Brokering Interests: The Use of Market-Based Policies by Interest Groups

Objective. This article begins the process of broadly evaluating the role of nongovernmental actors in regulatory markets by specifically examining environmental groups’ use of the sulfur dioxide (SO2) market established by Title IV of the Clean Air Act Amendments of 1990. This research posits that the use of nonexclusionary markets in environmental quality regulation allows interest groups a nonpareil opportunity to seek to directly affect policy outcomes. Methods. This article uses two forms of analysis. The first part of the article provides a qualitative analysis of the motives of interest groups that use incentive‐based policies in an attempt to achieve their desired policy outcomes. The last section of the article uses empirical data from the Environmental Protection Agency's Allowance Tracking System to evaluate interest groups’ use of market‐based policies. Results. The use of market‐based mechanisms in public policies offers interest groups a new form of participation in the policy process, yet it seems that only “new” groups are willing to enter the market. Further, I find that though the participating groups may not be able to affect the relative price of allowances (as they claim they will), they nonetheless are able to reduce the absolute number of allowances available. Finally, using market‐based policies to achieve their preferred outcomes may be a “rational” decision for groups in that the “return” on their investment may indeed be quite high. Conclusions. One aspect of pollution markets is clear—they do create an interesting new mechanism of public activism for groups that wish to protect the environment but do not want to “lobby or litigate.” By purchasing pollution allowances groups attempt to directly affect environmental policy outputs without entering the policy cycle as it has been previously understood. As market‐based policies are employed more broadly, opportunities accorded to environmental groups for active involvement in seeking to limit ambient pollutants, as well as the groups’ potential impact, may only expand.     

Finding education: Stories of how young former refugees constituted strategic identities in order to access school

Educators in resettlement countries are grappling with ways to adequately engage and meet the needs of newly arrived refugee students. In this article we argue that to fully meet the needs of refugee students a deeper understanding of their educational experience as ‘a refugee’ prior to resettlement is vital. In particular we foreground the stories of three young former refugees and explore the ways in which they actively constructed new identities in order to access school in their host countries, prior to resettlement. This article discusses how the negative discursive positioning of ‘the refugee’ in the world today has limited the resources and access to education for young refugees. It concludes by arguing that as these students move into education in Australia there is a danger to quickly relabel young former refugees with deficit terms rather than opening up a discourse to include the intricate complexities of each refugee experience.     

SiZer analysis for the comparison of time series

SiZer (SIgnificant ZERo crossing of the derivatives) is a scale-space visualization tool for statistical inferences. In this paper we introduce a graphical device, which is based on SiZer, for the test of the equality of the mean of two time series. The estimation of the quantile in a confidence interval is theoretically justified by advanced distribution theory. The extension of the proposed method to the comparison of more than two time series is also done using residual analysis. A broad numerical study is conducted to demonstrate the sample performance of the proposed tool. In addition, asymptotic properties of SiZer for the comparison of two time series are investigated.