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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.

A banking system is essential for financial stability, especially economic growth and development. The authors investigate the dynamic linkage of key banking system stability measures, namely, liquidity, capital, profitability, and credit risk. To this end, the authors employ Panel Vector Autoregressive (VAR) to a panel data set of country-level banking system indicators from seven developing countries; from March 2010 to December 2020 (308 country quarter observations). A nation is selected on the basis of similar characteristics large and bank-based economy with the considerably same stage of economic development. The authors find a remarkable resilient feature of the banking system in which both liquidity risk and credit risk appears significant only in the short run (within three quarters). Shocks from both risk sources dissipate quickly, suggesting an internal mechanism is at work. This study provides evidence of how a good performance of financial safety net should be.

This chapter is devoted to sustainable human resource management that leads to sustainable competitiveness. It features the ways human resources can be managed to carry out sustainable goals and the impact of sustainability on employees' attitudes and behaviours. The aim of this study is to explore the complex objectives of sustainability and human resource management and empirically investigate the dynamic relationship between human resources in science and technology and sustainable competitiveness in the case of 35 European countries. Our contribution emphasizes this interrelationship and its causality. For this research, we applied a vector auto-regression (VAR) model, and the Granger causality method to examine the relationship between human resources in science and technology and sustainable competitiveness. A panel data included 314 observations between 2012 and 2021. The panel VAR for analysing the impulse response function was enriched with the 5% and 95%, using Monte Carlo simulations. The research results revealed bidirectional causality in the European countries between human resources in science and technology and sustainable competitiveness. Human resources in science and technology trigger sustainable competitiveness and vice versa. As an element of originality, our study demonstrates that human resources in science and technology contribute to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to the development of human resources in science and technology. Thus, the chapter outlines the role of human resources in science and technology with regard to sustainable human resource management (HRM), and how to navigate these objectives so that they can positively influence sustainable competitiveness.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

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.

We study the potential effects of pension underfunding on corporate investment, financial constraints and improved employee bonding using 10 Pacific-Basin countries (including the United States, Australia, and eight Asian countries) at heterogeneous economic development stages and different regulatory environments. We document that corporate pensions are significantly underfunded in most countries of our sample in the period of 2001–2017, when interest rates were ultralow in most countries. In addition, firms from countries with stronger employee protection and more generous retirement benefits tend to show higher levels of underfunding in their defined benefit (DB) pension plans. To the extent of pension underfunding imposing constraints on corporate investment, we find that firms in these countries can face more constraints on investment when their pension is underfunded.

The protective aspects of relationships for health have been extensively studied. Here, we assess whether different dimensions of partnership status at the time of a child’s birth are associated with better self-assessed health later in mid-life. Data are from three countries with different social welfare policies relating to union status and parenting: the US, the UK, and Norway. Results indicate that women who were partnered at first birth had better health at midlife in all three countries than women who were unpartnered. The analysis indicates no differences in the mid-life health of Norwegian women who were married or cohabiting at birth, whereas for US and UK women, being married at the birth of a first child is more beneficial for mid-life health than bearing the child in a cohabiting union. In the US, women who are least likely to marry do not demonstrate better mid-life health if they had wed relative to cohabiting. In the UK, in contrast, the women least likely to be married at the birth experience better returns if they marry. These findings highlight the importance of paying closer attention to heterogeneous treatment effects as they relate to childbearing, relationship status, and mid-life health.