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This chapter revisits the Hausman (1978) test for panel data. It emphasizes that it is a general specification test and that rejection of the null signals misspecification and is not an endorsement of the fixed effects estimator as is done in practice. Non-rejection of the null provides support for the random effects estimator which is efficient under the null. The chapter offers practical tips on what to do in case the null is rejected including checking for endogeneity of the regressors, misspecified dynamics, and applying a nonparametric Hausman test, see Amini, Delgado, Henderson, and Parmeter (2012, chapter 16). Alternatively, for the fixed effects die hard, the chapter suggests testing the fixed effects restrictions before adopting this estimator. The chapter also recommends a pretest estimator that is based on an additional Hausman test based on the difference between the Hausman and Taylor estimator and the fixed effects estimator.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

In recent decades, the use of capital punishment has declined, but in its place, a ‘new death penalty’ has arisen: life without parole (LWOP), which is being used far more frequently and for more crimes than capital punishment ever was. Yet, LWOP has received far less scholarly attention than the death penalty. Because of its greater scale, assessing the effects of LWOP on crime has important policy implications and is a better test of extreme penalties. Existing studies of LWOP focus on humanitarian issues and ignore its potentially reciprocal relationship with crime. Therefore, we use available LWOP data to fill these gaps in the literature, using models specifically designed to control for potential reciprocal effects. The results indicate there is no reciprocal causation between LWOP and violent crime and, at best, LWOP’s impact on crime is small, temporary, and, most importantly, no greater than the impact of life with parole.

Corporate social responsibility (CSR) promotes society, reduces risk, and encourages ethical business practices. Due to its relevance, we study how CSR influences firms' sustainable development. We analyze data from 427 New York Stock Exchange (NYSE)-listed firms from 2008 to 2022. The Refinitiv environmental and social score is used to measure CSR, whereas for firms' sustainable development we rely on corporate sustainable growth rate (SGR) and market-based metrics. The analysis employs various econometric techniques, including ordinary least square, fixed effect regression, two-stage least square, generalized method of moment, and simultaneous quantile regression. The results indicate that CSR has a positive and significant effect on firms' sustainable development across all models. This relationship supports the notion that socially responsible business can contribute to long-term financial sustainability in line with “stakeholder theory”, indicating that companies should accommodate the concerns of various stakeholders, including society and the environment, to achieve sustainable development. We evaluate how the conditional distributions of SGR and firms’ value are affected by CSR, categorizing them into high, moderate, and low regimes. The quantile regression estimates indicate that the effect of CSR is more pronounced at upper quantiles, followed by moderate and low regimes. These findings underscore the importance of considering CSR in assessing the SGR and enterprises market value. We also confirm that our results are robust under range of different econometrics' methods. Finally, we enlighten current literature, and our research has useful policy implications for management and investors.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.

Relationships have changed dramatically in the last 50 years. Fewer couples are marrying, more are cohabiting. Reasons for this shift include more attractive labor market opportunities for women and changing social norms, but the shift may have consequences of its own. A number of models predict that those cohabiting will specialize less than those marrying. Panel data on time use – particularly housework time – as well as on the degree of specialization in more narrowly defined household tasks from the 2001–2019 waves of the Household, Income and Labour Dynamics in Australia survey are used to test this prediction.

The time use data for men provides only limited supporting evidence for specialization. The results for women are much stronger. Women who marry without first cohabiting increase their reported housework time more than those who enter cohabitations (by 3.7 hours versus 1.2 hours). The latter generally make up a third of the difference if they do marry. Expanding the analysis to other uses of time yields some further evidence of specialization.

Survey responses on the degree of specialization are more informative. The raw data show substantial intrahousehold specialization and further analysis reveals that on average married couples specialize more than cohabiting couples. Adding couple-specific fixed effects reveals that specialization increases when cohabiting couples marry. Interestingly, there does not appear to be a substantial tradeoff between tasks; partners who report specializing more on one task are more likely to report specializing on other tasks as well. Given the important roles couples have in family formation and the labor market, it is important to understand this intrahousehold behavior.

Research has shown that young adults face strong economic burdens when it comes to establishing their intimate relationships in times of labor market deregulation and economic recession. However, little is known about possible protective effects of the transition to cohabitation on subjective worries. Based on economic and gender-specific assumptions, the present paper uses data from the German Socio-economic Panel (GSOEP) from 1991 to 2020. Longitudinal analyses show that the transition into cohabitation reduces the economic worries of German women, especially in times of macroeconomic crisis. For men, cohabitation is only protective against economic worries if they or their partner have high economic resources. The latter may indicate that young men in precarious living situations perceive the male breadwinner model as a subjective burden in the context of cohabitation.

In the new economy, governed by technological progress and informational abundance, e-government service represents one of the drivers of the digital economy and society. The government and its institutions have the role of stimulating, leading, and controlling the process of transition to the digital society, which is a key component for the future prosperity and resilience of the European Union (EU). With focus on a better functioning of society by improving the citizens' access and use of e-government services, in this work we aim to identify the factors that influence the online interaction of individuals with public authorities in the EU member states. We used panel data for the EU member states in the period 2013–2021 to investigate the determinants of individuals' interaction with public authorities through institutional websites, using clustering regression with fixed effects, which allows both the clustering of the states and obtaining different slope parameters for each cluster. The results indicated the grouping of the EU states in an optimal number of two clusters, and the fixed effects regression clustering pointed out different coefficients for the two clusters, indicating distinct patterns. The main factors that influence the online interaction of citizens with public authorities are related to internet use, education, and government effectiveness, but the impact is different for the two clusters, depending on the specifics of the component countries.

The aim of our study is to explore the nexus between the gender composition of board and firm financial performance. We use the data of 114 listed banks from 10 Asian emerging economies. Data were extracted from the DataStream for the year 2012–2021. We apply fixed effect model to analyze the data. In addition, we use generalized method of moments (GMM) to verify our main findings. We find that both proxies of board gender composition which are the proportion of female board members and the percentage of female executives on the board have a significant impact on banks' financial performance. Findings suggest that female representation on board provides more insights of monitoring and optimal advisory capabilities and, therefore, gender-diversified board enhances firm performance. Females are more active in business matters and take more interests to fulfill their responsibilities. The results of our study provide useful signals for corporate and regulatory policymakers. Board gender disparities between enterprises should be better understood by all stakeholders to have the optimal combination of board members that ultimately lead to better performance of the firm.