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This chapter applies the five drivers of productivity framework to regional microdata for Egypt and extends it by introducing an index of industrial clusters as an explanatory factor of the productivity performance of local private sector firms. Applying structural equation models, the geographic concentration of sectoral economic activity is found to have a positive and statistically significant effect on labor productivity. The transmission mechanism is conjectured to be the positive spillovers that are created, which local firms can tap into. In contrast, a higher concentration of skilled workers in an industrial sector in a region is associated with lower levels of labor productivity – a finding that suggests there may be structural deficiencies in the allocation of skilled workers. Regional policy should focus on net investments in gross capital formation throughout the country, for which the national and regional governments should improve how public investments are managed and the institutional framework – including the rule of law, bureaucracy and red tape, conflict of interest, transparency, and governance – so that private investment (both local and foreign) may substantially increase.

The objective of this study is threefold–first, to develop a Regional Competitiveness Index (RCI) for measuring competitiveness of sub-national regions for India; second, to test this index for its ability to explain regional growth, which validates usage and applicability of this index; and third, to further investigate if the competitiveness of states is in turn caused by economic growth, i.e. it is tested if there is a bidirectional causality between competitiveness and regional growth.

The data of indicators used in the index are from sources available freely in public domain. The competitiveness index is constructed using equal weightage supported by principal component analysis (PCA) technique. The causal relationship analysis is done using panel data of 10 years from 2008 to 2017 for 32 Indian states/union territories. The generalized method of moments (GMMs) is used for this dynamic regression estimation.

Based on RCI score, states have been ranked and through rank analysis, the authors observe the performance status of these sub-national regions and are able to categorize them as improving, no change or deteriorating in regional competitiveness. Using the GMM estimation, the association between RCI and economic growth is found to be significant at 10% level. This shows that regional competitiveness as captured through the RCI score is able to explain regional economic growth and economic disparity among the sub-national units. Further, that RCI score is found to Granger-cause growth, while growth does not lead to better RCI scores. This establishes the usefulness of RCI as an important policy variable to compare states and provide direction for sectoral reforms.

The limitations of the study include (1) broad assumption that these sub-national regions belong to a uniform macro-economic and technology environment, and (2) data constraints as it is a longitudinal study. The study implies that the composite index could capture differences in regional competitiveness explaining regional economic disparity and that competitiveness causes higher economic growth and not vice versa.

The RCI score can prove to be a useful indicator of economic performance of different states and can be used by national and state policymakers to compare and assess regional disparity among different states. The pillar-wise scores will be useful for in-depth study of weakness and strength of the sub-national territories.

Construction of an RCI for sub-national territories and analysis of panel data for longitudinal study of ten years is unique in the regional competitiveness literature.

This paper aims to research the relationship between income gap (IG) and green economic growth based on the perspective of economic inequality.

Based on the panel data of 283 prefecture-level cities in China from 2011 to 2020, this paper uses the super slack based model (Super-SBM) to measure the efficiency of regional green economic growth, and constructs a regression model of the IG and regional green economic growth.

Firstly, the IG has an inhibitory effect on the growth of regional green economy (GE). Secondly, the relationship between the IG and regional green economic growth will be affected by the threshold value of income level. Thirdly, environmental regulation and government competition will increase the inhibitory effect of the IG.

According to the characteristics of China's regional economy, the researchers construct an empirical model of the IG and green economic growth to study their relationship, the threshold effect of income level and the moderating effect of environmental regulation and local government competition. The research content, methods and conclusions of this paper provide new evidence for the sustainable growth of China's regional GE.

In today's complex and rapidly changing business environment, cross-boundary growth is increasingly critical to the survival or even success of organizations. The purpose of this study is to examine the forming mechanism of firm’s cross-boundary growth by integrating the two important antecedent factors of performance pressure and managerial discretion into a united framework and theoretically analyze the direct role of performance pressure on firm’s cross-boundary growth as well as reveal the moderating role of managerial discretion. Also, the authors select listed manufacturing companies in China as samples to empirically test the research hypotheses.

The authors design a multiple regression model to perform empirical analysis by using a panel of 4,002 year-observations in 1,334 listed manufacturing companies between 2013 and 2016. The sample data sources mainly come from the Wind Database, which is mainland China's leading financial database and software services provider. The hypotheses proposed are tested by adopting a panel data set of the listed manufacturing companies of China.

Empirical results show that performance pressure has a positive effect on the cross-industry growth and cross-domestic regional growth but a negative effect on the cross-international regional growth, and managerial discretion has a different moderating effect. Specifically, capital intensity strengthens the positive effect of performance pressure on cross-industry growth but weakens the negative effect of performance pressure on cross-international regional growth. State ownership enhances the positive effect of performance pressure on cross-domestic regional growth but decreases the negative effect of performance pressure on cross-international regional growth. CEO duality increases the negative impact of performance pressure on cross-international regional growth.

This study provides several implications for top executives, including how to dialectically consider the double-edged effect of performance pressure on cross-boundary growth of firms, create an appropriate environments of managerial discretion and design the types of cross-boundary growth strategies that top executives can follow in the volatility, uncertainty, complexity and ambiguity era.

Although the relevant literature highlights the importance of performance pressure, it has not been related to the cross-boundary growth of firms. This paper makes an incremental contribution to the literature on the forming mechanisms of firm’s cross-boundary growth by providing an important perspective of performance pressure to firm growth determinants and taking into account the moderating role of managerial discretion.

This paper aims to explore the impact of digital inclusive finance (DIF) on regional economic growth and innovation-driven development.

Based on the panel data of 31 provinces (autonomous regions and municipalities directly under the central government) in China from 2011 to 2018, this paper explores the impact of DIF on economic growth and innovative development.

(1) DIF has a direct positive effect on economic growth and innovative development; (2) there is significant regional heterogeneity in the impact of DIF on economic growth and innovative development. (3) DIF can indirectly affect economic growth and innovative development by increasing residents’ personal disposable income, increasing fiscal expenditure and improving educational level.

Exploring the relationship between them and digital inclusive financial development can provide a reference for national productivity construction and development.

Economic growth and innovation-driven development have been one of the main concerns of China’s policymakers. Exploring the relationship between them, digital inclusive financial development can provide a reference for national productivity construction and development.

Institute for Economics and Peace (IEP) every year produces peace setting scores of many countries over the globe. The peace index score (PIS) and its ranking are fabricated by involvement of numerous recognised variables. The internal and external violence factors and their intensity regulate the strength of such scores. The present study deliberates such peace scores and rank of the countries in terms of regional variation and income class specifications. The study uses alteration of rank over three consecutive years and the growth of the PIS to elucidate the disparities over the region and income classification. The study recognised that income classification of countries smoothly elucidates the rank differences in terms of peace scores, but regional variation wise enlightenment remains misnomer. Further, this study contemplates four violence indicators and their growth over three years to describe the non-conformities of peace score between the countries. Studies acknowledged that inter-correlation between the peace growth scores and also between the growth of violence indicators is the significant factor to comprehend the peace score behaviour. Over the years, studies confirm that high-income countries are able to improve their PIS though there has large levels of inconsistency among countries. Among the regional specification, studies perceive that countries around the globe improved their peace score during 2018–2019, rather than 2019–2020.

This paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties.

Among other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate.

Statistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth.

The findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development.

The existence of the regional Kuznets curve, i.e. an inverted U-shaped relationship between regional disparity and economic development is widely debated and discussed. The bell-shaped curve of the spatial growth process where during the initial phase inequality increases and then reduces is theoretically supported by Myrdal (1957), Hirschman (1958), and Williamson (1965). It becomes important to understand regional Kuznets curve globally. Understanding the relationship between regional disparity and economic development becomes essential for public policy for balanced regional growth.

Regional Kuznets Curve which is an inverted U-shaped relationship between regional disparity and economic development is not a new phenomenon. Theoretical framework by Myrdal (1957), Hirschman (1958), and Williamson (1965) support the an inverted U-shaped relationship. To understand the relationship between regional disparity and economic development, the authors investigate the regional Kuznets curve by using data for 184 countries and 1765 subnational regions. Using parametric, semi-parametric, and non-parametric, it is found that there exists an inverted U-shaped relationship between regional disparity and economic development. The presence of the regional Kuznets curve is observed. As the theoretical framework suggests, regional inequality increases with income initially and decreases after attaining a certain level of income. This study identifies two stages of divergence-convergence where in the first stage, divergence across regions in a country happens with increasing income and in the later stage, convergence across regions in a country occurs with increasing income.

Using the parametric approach (panel data analysis), semi-parametric and non-parametric approaches, it is found that there exists a regional Kuznets curve. It is found that there exists an inverted-U relationship between regional inequality and per capita GNI. This suggests that the divergence-convergence passes through two stages. In the first stage, divergence across regions in a country happens with increasing income while in the later stage convergence occurs.

This research work has done three important things which fill the research gap that exists in the literature: (1) constructing the Gini coefficient to measure the regional inequality for 184 countries using 1765 subnational regional data; (2) using a parametric approach (panel data analysis) to understand the regional Kuznets phenomenon and (3) using a semi-parametric approach and non-parametric approach to understand the regional Kuznets phenomenon.

The Association of Southeast Asian Nations (ASEAN) has evolved into ASEAN Economic Community (AEC), which aims to pursue a single market and production base to transform ASEAN into a dynamic, competitive and global region. ASEAN is inherently heterogeneous that potentially could promote further economic integration, fundamentally, through the interactions between intra-regional outward foreign direct investment (OFDI), export trade and economic growth. Hence, this paper attempts to explore the causal relationship between intra-ASEAN OFDI, intra-ASEAN exports and economic growth of ASEAN-10 countries.

This paper attempts to explore the causal relationship between intra-ASEAN OFDI, intra-ASEAN exports and economic growth of ASEAN-10 countries, using regional panel data based on Dumitrescu and Hurlin (2012) non-causality analysis, which allows us to take into account of the heterogeneity in terms of causal relationships.

The empirical study shows bidirectional causality between intra-ASEAN export and intra-ASEAN OFDI, a bidirectional causality between intra-ASEAN export trade and intra-ASEAN economic growth and a unidirectional causality running from the real GDP of ASEAN-10 countries to intra-ASEAN OFDI.

The findings have implications for the extent of intra-ASEAN production fragmentation, policy formulations for furthering intra-regional OFDI, and trade to achieve the ASEAN integration agenda.

The main contribution of the current study is to use the panel causality analysis for an emerging dynamic region, specifically, the AEC. As far as we know, this is the first study ascertaining whether there is a causality relationship between intra-ASEAN OFDI, intra-ASEAN export trade and economic growth of ASEAN-10, which is a longstanding objective of ASEAN integration agenda.

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.