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Using the most recent dataset from 2013–2014 to 2017–2018, the study examines the efficiency of 75 coal-fired power plants in the Indian thermal power sector. The authors obtained robust estimates of efficiency scores by employing Seiford and Zhu’s (2002) DEA-based classification invariance technique to account for CO₂ emissions as an undesirable output. Meta-frontier analysis and the Tobit regression are used to compute technology heterogeneity across power plants belonging to public and private groups and investigate the factors driving carbon-adjusted efficiency, respectively. The results reveal that, on average, the efficiency of power plants during the study period is 78.26%, showing significant room for reduction in CO₂ emissions alongside augmentation in electricity generation. Private plants are more efficient than public ones, and relative performance inefficiency is the primary source of inefficiency in the thermal power sector. Regression analysis indicates that domestic-equipped plants perform with lesser levels of efficiency, and plants with more units are more inefficient than plants with fewer units. Carbon productivity significantly improves efficiency since fewer fossil fuels with high carbon will generate more electricity.

This chapter reviews the econometric approaches typically used to deal with the spike of zeros when modelling non-negative outcomes such as expenditures, income, or consumption. Relying on the assumptions of selection on observables for evaluating a policy or treatment, this chapter discusses other issues that arise with spikes of zeros in the data, including the analyst's choice between full information versus quasi-likelihood methods, considering whether observed zeros are true or masking more complex behavioural decisions, and dealing with zeros that arise due to self-selection. This chapter ends with discussions of empirical strategies to deal with these behavioural assumptions and a brief review of the literature where such strategies were employed.

Depression imposes substantial individual and societal economic costs, including lower productivity and higher healthcare use. However, while the relationship between employment and mental health has been explored, less is known about the potentially countervailing effects of different types of economic inactivity on depression among older individuals. The authors employ a series of models, including fixed effects panel data models and matching on rich data from the English Longitudinal Study of Ageing (ELSA) to investigate whether different types of inactivity might have heterogenous effects on depression. The authors find that whereas transitions to involuntary inactivity (unemployment) do not appear to have a perceivable effect on depression, transitions to voluntary inactivity (retirement) seem to decrease it.

This study examines the contribution of urban development to Vietnam's economic progress over the period 1986–2020. The study uses an augmented Solow framework, where urbanization is included as a shift variable in addition to capital per worker and accounts for structural breaks. It examines the cointegration and the long-run and short-run effects of urban development from four different cases of cointegration (constant, restricted constant, restricted trend and trend options), with each case accounting for the effect of a significant structural break. Also, the study provides causality nexus to check the presence of urbanization-led growth hypothesis. From the results, we note a long-run positive effect of urbanization on economic growth, but no short-run effects. In all cases, a 1% increase in population results in 0.8–0.9 increase of output, hence supporting a positive and momentous effect of urbanization over the long-term. We note a significant positive effect of a single structural break period (1991), which is a period of major shift towards economic progress. We note bidirectional causality between capital and output and a unidirectional causality from output and capital to urbanization. The former suggests a mutually reinforcing effect of capital accumulation and economic growth, and the latter indicates that urban development necessitates economic growth and capital accumulation. The findings derived from this study provide further impetus for urban development and urban policies and consider urbanization as a critical source of economic growth for Vietnam.

Public health measures implemented early in the COVID-19 pandemic brought the idea of essential work into the public discourse, as the public reflected upon what types of work are essential for society to function, who performs that work, and how the labour of essential workers is rewarded. This chapter focusses on the rewards associated with essential work. The authors develop an intersectional lens on work that was officially deemed essential in 2020 to highlight longstanding patterns of devaluation among essential workers, including those undergirded by systemic racism in employment and labour law. The authors use quantitative data from the CPS-MORG to examine earnings differences between essential and non-essential workers and investigate whether the essential worker wage gap changed from month to month in 2020. The authors find that patterns of valuation among essential workers cannot be explained by human capital or other standard labour market characteristics. Rather, intersectional wage inequalities in 2020 reflect historical patterns that are highly durable and did not abate in the first year of the global pandemic.

This chapter presents a mediation model that aims to disentangle the indirect from the direct effects of retirement on health, considering the mediating role of lifestyles. The model is applied to the risk of depression, and physical inactivity is assumed to potentially mediate the effect of retirement. The results indicate that there is a significant indirect effect via the mediator, albeit relatively small in comparison to the direct effect. The analysis highlights the importance of further exploring the influence of lifestyle factors in the relationship between retirement and health, in order to gain a better understanding of the potential pathways through which retirement impacts health.

This chapter tries to hedge extreme financial risk of entrepreneurs who work with wheat by combining wheat with four stock indices of developed and emerging European markets in a portfolio. Extreme risk of the portfolios is measured by the parametric and historical value-at-risk (VaR) metrics. Portfolios that target maximum return-to-VaR ratio are also constructed because different market participants prefer different goals. Preliminary equicorrelation results indicate that integration between wheat and emerging markets is lower (0.218) vis-á-vis the combination of wheat and developed markets (0.307), which gives preliminary advantage to emerging markets in diversification efforts. The results show that portfolios with emerging stock indices have significantly lower parametric (–0.816) and historical (–0.831) VaR than portfolios with developed indices, –1.080 and –1.295, respectively. As for optimal portfolios, the portfolios with developed indices have a slight upper hand. This chapter shows that parametric VaR is not a good measure of extreme risk, because it neglects the third and fourth moments.

There are multiple threats that cause consumers to be vulnerable in the marketplace, with poverty being a leading cause. Impoverishment often negatively impacts access to multiple categories of goods and services that consumers require to experience a reasonable quality of life. While there is research that explores the underlying factors that lead to resource deficits and marketplace restrictions, as well as their physical and emotional outcomes, an understanding of what is necessary to survive and thrive across societies is more elusive. To this end, our chapter carefully examines the concept of consumption adequacy (CA), which historically captures consumer needs for food and potable water, socially acceptable clothing adapted to weather conditions, safe housing that provides for privacy needs of occupants, preventative and remedial health care, and opportunities to grow and advance through education and training. After briefly summarizing the extant literature, each is described in turn, and ways of empirically investigating them across societies are advanced. This chapter closes with both marketer and public policy implications.

We explore the effect of selective schooling, where students are assigned to different schools by ability, on adult health, well-being and labour market outcomes. We exploit the 1960s transition from a selective to a non-selective secondary schooling system in England and Wales. The introductio3n of mixed-ability schools decreased average school quality and peer ability for high-ability pupils, while it increased them for low-ability pupils. We therefore distinguish between two treatment effects: that of high-quality school attendance for high-ability pupils and that of lower-quality school attendance for low-ability pupils, with mixed-ability schools as the alternative. We address selection bias by balancing individual pre-treatment characteristics via entropy balancing, followed by ordinary least squares (OLS) regression. Selective schooling does not affect long-term health and well-being, while it marginally raises hourly wages, compared to a mixed-ability system, and school aspirations for high-ability pupils. Cognitive and non-cognitive abilities measured prior to secondary school are significantly and positively associated with all adult outcomes.

In this chapter, the authors critically examine the application of unmeasured latent method factors (ULMFs) in human resource and organizational behavior (HROB) research, focusing on addressing common method variance (CMV). The authors explore the development and usage of ULMF to mitigate CMV and highlight key debates concerning measurement error in the HROB literature. The authors also discuss the implications of biased effect sizes and how such bias can lead HR professionals to oversell interventions. The authors provide evidence supporting the effectiveness of ULMF when a specific assumption is held: a single latent method factor contributes to the data. However, the authors dispute this assumption, noting that CMV is likely multidimensional; that is, it is complex and difficult to fix with statistical methods alone. Importantly, the authors highlight the significance of maintaining a multidimensional view of CMV, challenging the simplification of a CMV as a single source. The authors close by offering recommendations for using ULMFs in practice as well as more research into more complex forms of CMV.