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Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

An adverse health event can affect women’s work capacity as they need time to recover. The institutional framework in the Netherlands provides employment protection during the first two years after the diagnosis. In this study, we have assessed the extent to which women’s employment is affected in the short- and long term by an adverse health event. We have used administrative Dutch data which follow women aged 25 to 55 years for four years after a medical diagnosis. We found that diagnosed women start leaving employment during the protection period and four years later they were about one percentage point less likely to be employed. Women in permanent employment did not reduce their employment during the protection period and reduced their employment with less than 0.5 percentage points thereafter. Furthermore, we found minor adjustments in the working hours in the short term and no adjustments in the long term. Lastly, we found that for wages, and not for employment and hours, adjustments could be related to the severity of the health condition: women diagnosed with temporary health conditions experienced a short-term wage penalty of about 0.5–1.7 percent and those diagnosed with chronic and incapacitating conditions experienced a long-term wage penalty of about 0.5 percent, while women diagnosed with some chronic and nonincapacitating conditions, such as respiratory conditions, experienced no wage changes in the short or long term.

In this chapter, we are among the first to investigate the actual course of affairs in AGMs with respect to shareholder forum rights. In the first part of the chapter, we provide descriptive statistics on the use of the right to ask questions and speak in AGMs in the Netherlands. We find that in an average meeting there are around 42 questions and remarks made by around 8 shareholders. Most of these questions and remarks seem to be relevant; with a categorization framework of 14 topics, we could already identify over 50% of these questions and remarks. However, we also find that the average number of shareholders that physically ask questions is only 8. Next, we consider the determinants of the use of these forum rights. In several panel data analyses with a Poisson distribution and a negative binomial distribution, we, inter alia, found that the ‘importance of the meeting’ generally contributes to the amount of questions and remarks and the number of shareholders that actively engage in discussions. We have also found that the number of speakers – and the number of private investors – that actively attend the AGM depends on previous attendance numbers. This may imply that there is a small base of very active (private) investors in the Netherlands. We conclude that the forum function of AGMs is definitely relevant, but given the low number of shareholders that make use of these rights, amendments may be considered.

Panel data-based demand forecasting models have been widely adopted in various industrial settings over the past few decades. Despite being a highly versatile and intuitive method, in the literature, there is a lack of comprehensive review examining the strengths, the weaknesses, and the industrial applications of panel data-based demand forecasting models. The purpose of this paper is to fill this gap by reviewing and exploring the features of various main stream panel data-based demand forecasting models. A novel process, in the form of a flowchart, which helps practitioners to select the right panel data models for real world industrial applications, is developed. Future research directions are proposed and discussed.

It is a review paper. A systematically searched and carefully selected number of panel data-based forecasting models are examined analytically. Their features are also explored and revealed.

This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. A novel model selection process is developed to assist decision makers to select the right panel data models for their specific demand forecasting tasks. The strengths, weaknesses, and industrial applications of different panel data-based demand forecasting models are found. Future research agenda is proposed.

This review covers most commonly used and important panel data-based models for demand forecasting. However, some hybrid models, which combine the panel data-based models with other models, are not covered.

The reviewed panel data-based demand forecasting models are applicable in the real world. The proposed model selection flowchart is implementable in practice and it helps practitioners to select the right panel data-based models for the respective industrial applications.

This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. It is original.

Renewable energy (RE) is an important component to the complex portfolio of technologies that have the potential to reduce CO₂ emissions and to enhance the security of energy supplies. Despite RE's potential to reduce CO₂ emissions, the expenditure on renewable energy research, development, and demonstration (RERD&D) as a percentage of total government energy research, development, and demonstration (ERD&D) investment remains low in developed countries. The declining ERD&D expenditure prompted this research to explore the relationship between CO₂ emissions per capita and RERD&D as opposed to ERD&D.

An econometric analysis of annual CO₂ emissions per capita during the period 1990‐2004 for the 15 pre‐2004 European Union (EU15) countries was carried out. It was hypothesized that the impact of RERD&D expenditure on the reduction of CO₂ emissions would be higher than that of ERD&D expenditure, primarily due to several RE technologies being close to carbon neutral. Country‐level gross domestic product per capita and an index of the ratio between industry consumption and industrial production were introduced in the analysis as proxies to control for activities that generate CO₂ emissions. A number of panel data econometric models that are able to take into account both country‐ and time‐specific unobserved effects were explored.

It was found that random effect models were more appropriate to examine the study hypothesis. The results suggest that expenditure on RERD&D is statistically significant and negatively associated with CO₂ emissions per capita in all models, whereas expenditure on ERD&D is statistically insignificant (ceteris paribus).

The findings of this paper provide useful insight into the effectiveness of RERD&D investment in reducing CO₂ emissions and are of value in the development of policies for targeted research, development, and demonstration investment to mitigate the impacts of climate change.

We investigate the question of whether investing in a child’s development by having a parent stay at home when the child is young is correlated with the child’s adult outcomes. Specifically, do children with stay-at-home mothers have higher adult earnings than children raised in households with a working mother? The major contribution of our study is that, unlike previous studies, we have access to rich longitudinal data that allows us to measure both the parental earnings when the child is very young and the adult earnings of the child. Our findings are consistent with previous studies that show insignificant differences between children raised by stay-at-home mothers during their early years and children with mothers working in the market. We find no impact of maternal employment during the first five years of a child’s life on earnings, employment, or mobility measures of either sons or daughters. We do find, however, that maternal employment during children’s high school years is correlated with a higher probability of employment as adults for daughters and a higher correlation between parent and daughter earnings ranks.

The objective of the study is to analyse the impact of research and development investment on the firm performance of “small” scale firms vis-a-vis “medium”-scale firms.

The dataset comprised of a balanced panel of 486 research and development conducting Indian manufacturing small and medium enterprises, constructed for the period of 2006–2017. Fixed Effects, Random Effects Model and Hausmann test were used to analyse the determinants of firm performance in manufacturing small and medium enterprises in India.

It was found that from firms’ research and development (R&D) investments in terms of performance could be attained if simultaneously internationalisation and higher capital intensity could be achieved.

Managers could pay specific attention to the antecedents of firm performance and calibrate their R&D investment, internationalisation efforts and capital intensity simultaneously to achieve higher growth and productivity. For policymakers, the results provide an insight into how the firms in both categories could be differently incentivised, such that resources are better utilised.

The study analysed the determinants of firm performance in small and medium-sized firms at a disaggregate level as well as at a sectoral level using fixed effects, random effects and lagged effects to arrive at novel results, which have important implications for their competitiveness.

The purpose of this study is to examine whether there is a unidirectional or a bidirectional relationship between women and the environment, and to further study the effect of women on environmental quality.

To achieve this purpose, a Granger causality test and a random effects panel data model are used to study women–environment relationship in developing countries. Error correction model (ECM) is the chosen estimation technique. A Granger causality test is used because of its frequent use in examining the existence of a unidirectional or a bidirectional relationship between two or more variables. A random effects panel data model is used as it has proven to be more efficient than the fixed-effects panel data model.

Women Granger-cause environmental quality while the opposite is not true in developing countries in the long run. This indicates the existence of a unidirectional relationship between women and the environment when the long-run relationship is considered. However, when considering the long- and short-run relationship together, the results indicate the presence of a bidirectional relationship. The empirical results of the random effects panel data model through ECM estimation indicate the positive effect of women on improving environmental quality as illustrated by the coefficient of the current change of women. This shows that women are concerned about environmental degradation. In addition, the empirical results highlight the persistence of CO₂ emissions. Results also confirm that foreign direct investment inflows lead to further environmental degradation. However, education and trade openness coefficients are found insignificant at the current period.

The research results have great implications on women empowerment, the reduction of gender bias and the increase in government expenditure on women’s education and health because of women’s positive effect in improving environmental quality.

To the best of the author’s knowledge, this is the first paper that examines the two-way relationship between women and the environment and, hence, it fills the gap present in the literature.

This chapter investigates which factors contribute to (small) shareholder attendance using a hand-collected panel data set with information about turnout rates, voting behaviour and ownership structures of companies that are listed in seven Member States. We document how ownership concentration positively affects total shareholder turnout, but has a negative effect on small shareholder turnout. Voting power also affects small shareholder turnout rates; the greater small shareholder voting power, the greater their eagerness to vote. In addition, total and small shareholder turnout is higher the more important the meeting agenda. And, small shareholders tend to free-ride on large institutional shareholders and corporate insiders, but the magnitude of the free-rider effect is larger for the latter category of blockholders. Our results provide some important insights for the debate on shareholder rights and the role of the AGM in corporate governance. The results show that, despite the criticism, the AGM still plays an important role in small shareholder monitoring. Some topics seem to clearly motivate small shareholders to attend, while others are less relevant. Policy makers can stimulate shareholder monitoring by focusing on the factors that are determined in this study, but it is important to consider possible endogeneity issues as well.