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Parental job loss has been shown to have a negative impact on a large number of children's outcomes, in particular for low-income children. Given the amount of time freed up by loss of employment and the fact that active time with one's children appears to be a productive input in their human capital production function, increases in the time parents spend with their children have the potential to positively impact a child or to counteract other negative consequences of parental job loss. This chapter studies how low- and higher-income parents change their time investment in their children when faced with job loss. Using national time-diary data from the American Time Use Survey (ATUS) linked to longitudinal labor market data from the Current Population Survey (CPS), I find that parents spend almost 15% of the time freed up by job loss – roughly 3.5 additional hours per week – actively with their children. Low-income parents invest their freed-up time no differently from higher-income parents. While mothers who lose their job respond by spending more time actively with their children, this adjustment is much smaller for fathers. This suggests that differential adjustments in time investment may play a role in the impact maternal versus paternal job loss has on children's outcomes.

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 liberalization initiative commenced in India from 1991 onwards, replacing the four-decade long import substitution policy. The primary objective was to enhance the role of foreign and private investment, in line with the newly embraced outward-oriented growth model. The government had undertaken several policy initiatives since then, especially to strengthen the manufacturing sector which plays an important role in the economic development of any country. The current study evaluates the effects of the liberalization policy in India on industrial outcomes. Recent studies have found that when firm heterogeneity is present in trade models, reforms will lead to a decrease in the number of firms and a rise in their average size (Melitz, 2003). A dataset of 24 manufacturing industries had been used in the current study. We test empirically whether liberalization had led to a rise in the average size of establishments as stated in the literature. We also attempt to analyze the magnitude of trade costs in terms of the impact of reforms on wages and prices. The empirical analysis based on the difference-in-difference (DID) estimation method shows that on average, trade reforms do not lead to an increase in the real wages and average size of establishments. In addition, prices appear to increase in the long run due to liberalization, with potential ramifications.

Innovation ecosystems consist of independent and yet interdependent enterprises and actors. This constitutes a challenge for innovation leadership to set the direction to pursue UN SDGs. Enhanced insights and understandings of how collaborative innovation leadership can be conducted in practice are revealed in two cases conducted using a participatory action research approach. Hereby theory and practice are linked by the ecosystem participant actions to reach competitiveness of the offshore wind energy ecosystem compared to traditional/other renewable energy sources pursuing UN SDG number 7 of ‘affordable and clean energy’. The two cases are situated in ports in offshore wind energy innovation ecosystems, respectively in the Baltic Sea and in the North Sea. The first case contains complementary ecosystem participants with both leadership and expert positions. The second case contains both complementary and competitive ecosystem participants with leadership positions. The findings note that both cases can use collaborative innovation leadership through the point of origin in the guiding star of the value proposition at ecosystem level to go beyond their own enterprise self-interest. Next, collaborative innovation leadership is based in heterogeneities of both knowledge domains and individual and organisational behaviours for the innovative imagination of future needed initiatives for collaborative design-based sensemaking. A short-term challenge is present from reduced revenue in own enterprise from future needed initiatives. This short-term impact needs to be addressed for enhanced long-term robustness. The findings are summarised in a model for dissemination of collaborative innovation leadership in ecosystems to pursue UN SDGs in practice.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

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.

The attention of scholars and policy makers towards the topic of innovation has consistently increased, especially in recent years. This is justified by the fact that innovation undoubtedly plays, today, a crucial role in driving a country’s economic growth, improving productivity and, more generally, enhancing overall societal well-being.

When the discourse around innovation focuses on its economic dimension, the strong intertwinement with entrepreneurship emerges. In line with this, focusing on research on innovation in organisations and, especially, innovation in relation to the figure of the entrepreneur is considered, plenty of studies have been carried on, over time, in many disciplines, analysing the role of the entrepreneur in relation to innovation from various different angles. However, especially when management studies are considered, we can notice a poor consideration of the role played by the gender of the entrepreneur. In line with this consideration, by means of a systematic literature review, this chapter aims to fill this literature gap focusing on the intertwinement that can be envisaged, in management studies, among the issues of entrepreneurship and innovation in the case of women-owned firms.

In this chapter, Mousumi De presents the principles and implications of CRT in the context of Asian and Asian American experiences including the perspective, features, strategies, and new directions on how to facilitate the preparation of teacher candidates and work with all teachers to understand the complexity of the Asian and Asian American identity, their racialized experiences, and their sociohistorical, transnational contexts that continue to influence their lived experiences. This chapter highlights the important issues and challenges facing Asians and Asian Americans that have been camouflaged by their stereotypical treatment as model minorities. It also shares the work of many scholars on approaches for promoting diversity and inclusion, such as implementing anti-racist, anti-oppressive, and inclusive history curricula, cultural citizenship education, teaching for social justice, and culturally responsive and culturally sustaining teaching for addressing the marginalization of Asians and Asian Americans.

The COVID-19 pandemic spurred major, and possibly enduring, changes in paid work. In this chapter, we explore the continuity and change in several work day dimensions, including where it is performed, the amount of time spent working, the length of the work day, and who people are with when they work, as well as variation across population subgroups. We use nationally representative data from the American Time Use Survey (ATUS) to analyze change across the 2019 to 2021 period. While the shift to working primarily at home in 2020 is dramatic and continuing into 2021, working primarily at the workplace remains the modal experience for Americans. We find differences by gender, education, parental status, and age in which workers perform their jobs at home, and we find much more continuity in how much people work and when they work.