Search results

The concept of the “global production network” (GPN) has emerged as a framework for analyzing the intricate connections between a dominant or pivotal firm and its suppliers across various countries. ¹ The expansion of GPNs signifies that trade encompasses not only the final products but also the parts and components (P&C) involved in their production. The reduction of tariff barriers and advancements in transportation and communication technology have facilitated the fragmentation of production processes across different countries. This has led to a significant transformation in the nature and structure of global trade. This chapter aims to synthesize and present this literature. By identifying the key drivers, determinants, and consequences of fragmentation trade through a literature-based approach, this study aids in assessing the opportunities and challenges those lagging countries, like India, encounter in terms of increased participation in GPNs.

The purpose of this study is to analyse the gender wage gap (GWG) in Spain adopting a labour market segmentation approach. Once we obtain the different labour segments (or idiosyncratic labour markets), we are able to decompose the GWG into its observed and unobserved heterogeneity components.

We use the data from the Continuous Sample of Working Lives for the year 2021 (matched employer–employee [EE] data). Contingency tables and clustering techniques are applied to employment data to identify idiosyncratic labour markets where men and/or women of different ages tend to match/associate with different sectors of activity and occupation groups. Once this “heatmap” of labour associations is known, we can analyse its hottest areas (the idiosyncratic labour markets) from the perspective of wage discrimination by gender (Oaxaca-Blinder model).

In Spain, in general, men are paid more than women, and this is not always justified by their respective attributes. Among our results, the fact stands out that women tend to move to those idiosyncratic markets (biclusters) where the GWG (in favour of men) is smaller.

It has not been possible to obtain remuneration data by job-placement, but an annual EE relationship is used. Future research should attempt to analyse the GWG across the wage distribution in the different idiosyncratic markets.

Our combination of methodologies can be adapted to other economies and variables and provides detailed information on the labour-matching process and gender wage discrimination in segmented labour markets.

Our contribution is very important for labour market policies, trying to reduce unfair inequalities.

The study of the GWG from a novel labour segmentation perspective can be interesting for other researchers, institutions and policy makers.

Employees facing challenges in their careers – i.e. female, migrant, elderly and lower-educated employees – might expect job searches to have a low likelihood of success and might therefore more often stay in unsatisfactory positions. The goal of this study is to discover inequalities in job mobility for these employees.

We rely on a large sample of Dutch public sector employees (N = 30,709) and study whether employees with challenges in their careers are hampered in translating job dissatisfaction into job searches. Additionally, we assess whether this is due to their perceptions of labor market alternatives.

Findings show that non-Western migrant, elderly and lower-educated employees are less likely to act on job dissatisfaction than their advantaged counterparts, whereas women are more likely than men to do so. Additionally, we find that although they perceive labor market opportunities as limited, this does not affect their propensity to search for different jobs.

This paper is novel in discovering inequalities in job mobility by analyzing whether employees facing challenges in their careers are less likely to act on job dissatisfaction and therefore more likely to remain in unsatisfactory positions.

Increasing trade liberalization and financial integration with rise in foreign direct investment (FDI) flows have an intense impact on the labor market of both the developed as well as the developing world. The restructuring of economic activity has resulted in destruction of jobs in some parts of the economy and start-ups of new firms in the other part, growing import competition with foreign firms displacing local firms, relocation of jobs from high wage to low wage nations. It is claimed that rapid globalization has also the outcome of “race to the bottom” in terms of wages and the quality of employment. As per the latest International Labor Organization (ILO) Global Employment Trends, 2022, total global number of unemployed youths is estimated to reach 73 million in 2022 but still six million above the prepandemic level of 2019. The latest press release October 2022 points out that trade growth is likely to experience a slowdown in 2023 due to multiple shocks on global economy. High energy prices due to the Russia–Ukraine war is expected to contract household expenditure and raise the cost of manufacturing. The present chapter seeks to analyze the impact of trade flows on the labor market – job creation or job loss, wage inequality, movement toward informal economy, gender inequalities, and other related issues. The data are based on various reports available from the ILO, the World Development Indicators (WDI) and the United Nations Conference on Trade and Development (UNCTAD), and World Trade Oorganization (WTO) Trade Reports. The empirical analysis also confirms that there is a unidirectional causality from trade to employment generation.

The aim of the paper is to explore within-firm vertical pay inequality and its relation to firm size and firm performance.

Using firm-level microdata for Kazakhstan, the authors measure within-firm pay inequality as the wage differential between the top- and the bottom-level job occupations. The authors carry out their analysis based on panel regression models.

The authors find that within-firm pay inequality increases as firms grow. Further, they identify that this trend is mainly driven by top-occupation workers receiving more significant wage increases compared to lower-level workers as firms expand. Once the authors address concerns about endogeneity, they find that pay inequality is negatively associated with firm performance.

Developing strategies and policies that prioritize fairness and transparency in compensation practices is crucial during the expansion process of firms. By actively discouraging rent-seeking behavior, firms can create a work environment that promotes productivity and sustainability, ultimately leading to improved firm performance. The research findings highlight the importance of implementing context-specific interventions, recognizing that different environments may require tailored approaches to address pay inequality effectively.

This study contributes to the study of within-firm pay inequality, firm size and performance in an emerging economy, an area that has been largely overlooked in previous empirical research. The contrasting findings show the importance of the structural and industrial characteristics of emerging markets that contribute to broader and deeper impact of pay inequality compared to developed economies.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

The use of economic sanctions has grown dramatically in recent decades. Nevertheless, many arguments are presented in the public policy space regarding their effects on target populations. The author presents the first systematic analysis of the effects of sanctions on living conditions in target countries.

This paper provides a comprehensive survey and assessment of the literature on the effects of economic sanctions on living standards in target countries. The author identifies 31 studies that apply quantitative econometric or calibration methods to cross-country and national data to assess the impact of economic sanctions on indicators of human and economic development. The author provides in-depth discussions of three sanctions episodes—Iran, Afghanistan and Venezuela—that illustrate the channels through which sanctions affect living conditions in target countries.

Of the 31 studies, 30 find that sanctions have negative effects on outcomes ranging from per capita income to poverty, inequality, mortality and human rights. The author provides new results showing that 54 countries—27% of all countries and 29% of the world economy— are sanctioned today, up from only 4% of countries in the 1960s. In the three cases discussed, sanctions that restricted the access of governments to foreign exchange limited the ability of states to provide essential public goods and services and generated substantial negative spillovers on private sector and nongovernmental actors.

This is the first literature survey that systematically assesses the quantitative evidence on the effect of sanctions on living conditions in target countries.

The authors illustrate that there are significant differences in the wage performance across companies in relation to the digital content of their production and training activities.

Using company-level data from three waves of the Continuing Vocational Training Survey (2005, 2010 and 2015), this paper provides an overview on European firms implementing training and the magnitude of their training effort.

The authors conduct a regression analysis documenting that a wage premium of 9% is associated with companies undertaking training and that an additional 8% is paid by firms arranging training for IT skills-intensive workers. The latter effect is pervasive across sectors and is not strictly related to industry exposure to the digital transformation.

The authors assess the wage effect of training, in relation to the digital content of firm production or job tasks, using a large set of European companies (112,000), from countries with different degree of specialisation and institutional setting. The analysis covers a significant period of time of the last wave of digitalisation (2005, 2010, 2015).