Regional Productivity Growth Research Articles

Sectoral specialization and productivity in European metropolitan regions: empirical insights and policy implications

This article presents new empirical insights into European metropolitan regions, addressing a gap in the existing literature by examining the sectoral specialization and its impact on the productivity growth of metropolitan regions. The lack of evidence for European metropolitan regions contrasts with the empirical evidence for U.S. metropolitan regions, highlighting a significant research gap. By employing panel-regression analysis and leveraging unique regional data encompassing European metropolitan regions from 2000 to 2020, the authors unveil a multitude of significant findings. Key findings are that higher income countries (EU-15) tend to experience greater benefits from sectoral specialization in metropolitan regions compared to Eastern European regions (EU-NMS), suggesting that generalizing conclusions for EU-27 may be misleading. The study reveals a productivity gap resulting from sectoral specialization between metropolitan and non-metropolitan regions: Results suggest a higher concentration of specialized sectors in metropolitan regions. Policy implications are highlighted within the discussion on the framework of smart specialization in the context of metropolitan regions.

Granular origins of the Chinese business cycle

ABSTRACT Recent events in China, like Foxconn’s factory downsizing and Evergrande’s bankruptcy, have significantly impacted regional economies, highlighting how idiosyncratic shocks from large firms can generate aggregate effects. Using the ‘granular hypothesis’, which posits a significant impact of large firms’ actions on the macroeconomy, this study investigates how idiosyncratic shocks from large Chinese firms affect regional productivity growth and markups. Our findings demonstrate that idiosyncratic shocks to the 100 largest firms per province significantly impact regional labour productivity and total factor productivity growth but not gross regional domestic product growth. Subsequently, we examine how idiosyncratic shocks impact product market distortions, revealing that idiosyncratic shocks to large firms increase markups in regional markets, suggesting amplified market power.

Investigating the impact of tourism on gross regional domestic product growth in Batu City

Investigating the impact of tourism on gross regional domestic product growth in Batu City

Estimation of historical daily PM2.5 concentrations for three Chinese megacities: Insight into the socioeconomic factors affecting PM2.5

Studying historical changes in the 2.5 μm particulate matter concentration (PM2.5) can clarify the relationship between air pollution and socioeconomic development. Daily PM2.5 levels and meteorological data (2012–2022) for three large cities (Beijing, Shanghai, and Xi'an) at different development stages in different regions of China were used to construct a random forest (RF) model for estimating historical PM2.5 data for the period 1973–2011, a time period in which few measurements were made. The eigenvalue for visibility was the largest in the RF model; visibility explained 0.76–0.87 of the variance in PM2.5 for the three cities. The daily estimated PM2.5 was validated, with an R2 of 0.654–0.780 and average absolute error of 11.52–31.73 μg m−3 in the model. PM2.5 concentrations predicted by the RF model for 2004–2011 were highly correlated with gravimetric measurements (R = 0.585, p < 0.01). We extensively validated the results of RF using manual weighing PM2.5 data, online monitoring concentration of PM10, and aerosol optical depth (AOD), demonstrating the accuracy of the model. Over the study period, the PM2.5 level first increased and then decreased in the three cities; however, the year at which the trend changed differed. We further explored the effects of urbanization and economic growth on PM2.5 levels by investigating the correlations between socioeconomic indicators and PM2.5. The magnitude of the permanent population of Beijing and gross regional production growth in Shanghai were both significantly positively correlated with the PM2.5 level. Increasing the size of urban green areas can reduce PM2.5; this effect was strongest for the southern city of Shanghai, may due to their different climates and green tree species. Energy consumption and emissions from primary industries were strongly positively correlated with the urban PM2.5 level. An in-depth understanding of the factors affecting PM2.5 concentrations could help policymakers improve air quality management strategies, especially for densely populated megacities.

Regional economic resilience, productivity growth and sectoral interconnectedness

This paper develops a theoretical model for the conceptualization and empirical analysis of regional economic resilience. Our production function framework is applied to empirically assess the effect of pre-crisis conditions on regional resilience accounting for exogenous changes in technology and changes in production factors. Spatial regression analysis indicates that intersectoral linkages are important factors for explaining the resilience of regions to negative exogenous shocks. A key finding of the study is the positive effect of the interconnectedness of agriculture, construction, and electrical, optical and transport equipment sectors on the ability of European Union regions to absorb the adverse effects of the 2008 economic crisis.

Investment climate assessment standards’ impact on the gross regional product growth of the Russian Federation subjects

The study purpose is to identify the relationship between the provisions’ implementation of the regional investment standard and the growth of the gross regional product (GRP) in the Russian Federation subjects. The average values’ statistically significant deviation of the GRP dynamics in 11 pilot regions of the Russian Federation and other subjects of the Russian Federation as an introduction result of regional investment standards developed by the Agency for Strategic Initiatives for the Promotion of New Projects (ANO “ASI”) together with the Ministry of Economic Development of the Russian Federation has been summarized. It is established that there is a statistically significant difference in the dynamics of the average GRP of the pilot and other regions of the Russian Federation, due to the implementing process of the provisions of the ANO “ASI” Standard. The provisions’ introduction of the ANO “ASI” Standard since 2012 has caused a statistically significant difference in the dynamics of the average GRP of the pilot and other regions of the Russian Federation. In fact, a significant outstripping dynamic of macroeconomic indicators for the development of pilot regions has not been achieved. The revealed situation testifies to the uneven movement of financial flows in the Russian Federation: about 45.8%of the profit of organizations falls on Moscow and St. Petersburg (2021). Despite the lack of outstripping dynamics of GRP and investments in fixed assets in comparison with the average value in the Russian Federation, the pilot regions managed to ensure a more stable dynamics of GRP in 2020. Despite the presence of partially lagging macroeconomic indicators’ dynamics of the pilot Russian Federation regions in comparison with the average values for the Russian Federation, the introduction of regional investment standards is an important condition for effective interaction between territorial authorities and a wide range of investors.

Strategic goal: Enhancing economic growth and labor force in the arctic zone

The authors in their study examined the forms of state support implemented in the Russian Federation to increase labor force and enhance the budgetary independence of the Russian Arctic regions. They investigated the impact of state support on business development and its effects on demographic indicators and gross regional product growth in the Russian regions encompassed by the Arctic zone. The preferential regime of the Arctic zone of the Russian Federation represents the latest regulatory mechanism aimed at counteracting negative socio-economic trends in the macro-region. The purpose of this study is to analyze the transformational changes in the relationship between employment and investment due to the implementation of the preferential regime in the regions fully or partially included in the Russian Arctic.

The dynamic economic landscape of Bengkulu: A comprehensive analysis and its implications for sustainable growth across sectors

This research presents a comprehensive examination of the economic climate of Bengkulu, a province on the southwest coast of Sumatra, Indonesia. Utilizing a mixed-methods approach, this study combined qualitative and quantitative data collected from a purposive sample of 135 participants, including local business owners, government officials, economic analysts, and residents. This study investigates various economic indicators such as income levels, employment statistics, and sectoral contributions to the regional economy. Employing a hypothetical regression analysis, this study explores the connections between sectoral contributions, employment rates, growth rates, and consumer spending in key sectors such as agriculture, services, mining, and retail and their impact on regional Gross Domestic Product (GDP) growth. The findings reveal a dynamic economic landscape with significant growth observed in certain sectors while also highlighting challenges such as economic inequality and the need for diversified economic strategies. This study not only offers insights into the current economic status and trends in Bengkulu, but also provides critical information for policy-making and strategic planning aimed at promoting sustainable and inclusive economic growth in the region.

Pemodelan Regresi Data Panel Pada Indeks Pembangunan Manusia di Pulau Sumatera

The island of Sumatra has 10 provinces with a Human Development Index level that is not much different from the national Human Development Index, several provinces on the island of Sumatra have a Human Development Index below the national Human Development Index. The aim of this research is to analyze the Human Development Index and the factors that influence it in Sumatra for the 2018-2022 period. This research is quantitative research. The variables used in this research are the Human Development Index, Gross regional domestic product, Economic Growth, Poverty, and the Gini Index. The panel data method is used for analysis in the form of cross section data from 10 provinces on the island of Sumatra and time series data for 2018-2022. The results of this research show that Gross regional Domestic Product and Economic Growth have a negative and insignificant effect on the Human Development Index, Poverty and the Gini Index have a negative and significant effect on the Human Development Index in Sumatra for the 2018-2022 period.

Studying green financing, factor allocation efficiency, and regional productivity growth in renewable energy industries

This study aims to test the role of green financing in factor allocation efficiency and regional productivity growth in China's renewable energy industries. Chinese provincial data were acquired from 2008 to 2019, and the GMM technique was applied for empirical estimation. The results showed that renewable energy factor allocation efficiency in China enhances the rate of regional productivity growth by approximately 32.7%, with the role of green financing standing at16.5% in China-based renewable energy industry efficiency. At the same time, the factor allocation efficiency in China has adopted green financing measures to go green and support green process innovation in technological innovation in renewable energy contact. The findings suggest that regional productivity growth is essential, as is the capacity to advance multifactor technological productivity, use of green bonds, and disclosure of sustainable energy development. Fundamentally, this study presents policy implications for key stakeholders.

Technological Catch-Up, Innovation, and Productivity Analysis of National Innovation Systems in Developing Countries in Africa 2010–2018

This study investigates the levels and determinants of regional innovation catch-up, frontier shift, and productivity growth of African national innovation systems from 2010 to 2018. The study relied on the World Development Indicators data for 28 African countries. Non-radial non-oriented Data Envelopment Analysis (DEA) and bootstrapped truncated regression were the central estimation methodologies. The results revealed that 18% of Africa’s national innovation systems had experienced progress in the catch-up and frontier shift indexes. Further results showed that 21% had experienced total factor productivity growth. Nigeria and South Africa were on the region’s efficient frontier and had achieved the most technological advancement. In addition, Ghana and Senegal had the most productive national innovation systems. The results suggested that national innovation systems in Africa had experienced marginal progress. Further results indicate that the population growth rate and GDP per capita are the critical determinants of African national innovation systems, efficiency, technical efficiency, and productivity performance. Consequently, the implications of the results to policy are twofold. First, African countries should use benchmarking practices with the region’s best-performing national innovation systems. Lastly, African countries have the potential to grow their economies through regional collaborative Science, Technology, and Innovation practices.

Aging and regional productivity growth in Germany

We investigate the effects of aging on regional productivity growth, the mechanisms and the strength of which are not well-understood. We focus on two different manifestations of population aging—workforce aging and an increasing share of retirees—and investigate channels through which aging may impact on regional productivity growth for a panel of German counties 2000–2019. We find that workforce aging is more negatively associated with productivity growth in urban than in nonurban regions. A likely reason is that aging is detrimental to innovative and knowledge-intensive activities, which are heavily concentrated in cities. We also find a negative association between the share of the retired population and productivity growth in regions with a small household services sector. A likely reason is that older people’s disproportionate demand for local household services (including health care, recreation) requires a re-allocation of resources from more productive manufacturing or business services to less productive household services. Regions specialized more in highly productive industries have more to lose in this process.

Research and development intensive clusters and regional competitiveness

AbstractModern cluster theory provides reasons for positive external effects that accrue from the interaction of spatially proximate firms operating in common and related fields of economic activity. In this paper, we examine the impact of R&amp;D‐intensive clusters as a key factor of regional competitiveness on productivity growth. In relying on a hybrid approach of cluster identification, we examine effects of cluster specialization and diversity for a panel of German NUTS‐3 regions in 2003–2019. After controlling for regional characteristics and unobserved heterogeneity, a robust cluster strength effect (i.e., specialization) on productivity growth is found within the context of conditional convergence across German regions. With regard to the underlying mechanisms, we find that the presence of multiple R&amp;D‐intensive clusters in specific technological fields is most strongly linked to higher levels of regional productivity growth. We also find that advantages from cluster specialization are strongest in key industrial sector such as automobile production, machinery, chemical and pharmaceutical products. Overall, our estimates particularly highlight the working of Marshallian externalities in productivity dynamics, while Jacobs‐type spillovers tend to be partially realized. These findings indicate that some but not all cluster‐based regional development strategies are promising policy tools to foster regional growth processes.

The intersectoral linkages and manufacturing productivity growth in Italian regions using the I-O approach

The intersectoral linkages in the production structures have been analysed under several angles in recent years, but these were mainly developed at the national level neglecting the regional aspects. In this paper, we aim to fill this gap by analysing the intersectoral linkages from a regional perspective by studying the case of Italian regions. We use the input-output approach to investigate the process of integration between manufacturing and market services, clarifying the role of market services in strengthening the productivity of the regional manufacturing systems. The results show that an increasing share of market services in regional manufacturing is evident across the Italian regions. The empirical estimations clearly show a strong connection between the growth of market services integrated in manufacturing and the growth of manufacturing productivity. The findings are robust when we control for the intersectoral linkages along the value chain, by adopting the vertically integrated sector (or subsystem).

Simulasi Penggunaan Listrik Tarif Sosial Menggunakan Algoritma ERNN

The use of electricity under the social tariff category has increased significantly each year, both purely social and commercial social use. The use of social tariff electricity is intended for public interest activities for both the lower and upper middle social strata which are oriented towards fulfilling growth and development facilities for the public interest, so that a simulation of social electricity usage is needed to map a picture of the condition of the amount of social electricity usage in the future. The research was conducted to determine the estimation of how much electricity is used by using the Elman Recurrent Neural Network (ERNN) algorithm by reducing the input dimensions. The ERNN algorithm is used to simulate network parameters formed from complex input-output relationships, so that data patterns can be found. The factors of the input dimensions of this study are demographic data, electricity usage, social customers, population, gross regional domestic product (GRDP) and industrial growth. The results showed that the ERNN algorithm is capable of simulating formed network parameters that can be used for training and validation so that the value of the network Mean Square Error (MSE) can be determined, with prediction accuracy using the Mean Absolute Percentage Error (MAPE) for forecast in sample in the forecast period of 5 years obtained an average of 0.77%, and able to know the dominant factors that influence the use of social tariff electricity.

Causal analysis of the interinfluence of workforce productivity and rail freight intensity in the regions of the Ural Federal District

Relevance. The development of the railway industry has a significant positive impact on socio-economic dynamics at both the state and regional levels, which has been confirmed by numerous domestic and foreign studies. However, the issue of mutual influence of such categories as regional labour productivity and rail freight intensity has been little studied. At the same time, the most important task today is to find effective icentives for the growth of regional labour productivity. Research Objective. This study aims to econometric analysis of the relationship between rail freight intensity and workforce productivity in the Ural Federal District (UFD). Data and Methods. The study uses official statistical data on Russian regions provided by the Federal State Statistics Service. The methods of Vector Error Correction Models (VECM) and pooled mean group estimates (PMG method) formed the methodological basis of the study. Results. The study has shown that there is a relationship between workforce productivity and rail freight intensity. At that point, in a short-term period growth of rail freight intensity leads to an increase in workforce productivity, which in a long-term period itself becomes an incentive to increase the shipped commodity mass and rail freight intensity. Conclusions. The findings can be of interest to public authorities at the national and regional levels, for heads of industrial structures and functional institutions, representatives of business and scientific communities interested in the development and modernization of transport infrastructure, being a basic condition for the increased intensity of cargo transportation in the region.

Retracted: A Study on the Impact of Digital Finance on Regional Productivity Growth Based on Artificial Neural Networks.

[This retracts the article DOI: 10.1155/2022/7665954.].

Multidimensional impacts from international agricultural research: Implications for research priorities

Investors in international agricultural research seek sustainable agri-food technologies that can potentially serve multiple objectives, including economic growth, food security, and sustainable use of natural resources. We employ quantitative economic models to examine the potential multi-dimensional impacts of agricultural productivity gains in the Global South. These models take into account behavior responses to agricultural technological change, i.e., how productivity changes may affect decisions on what to produce, trade, and consume. We compare potential impacts of productivity growth in different commodities and regions and assess implications along several impact dimensions, including economic and income growth, the population at risk of hunger, adequacy of protein and micronutrients in human diets, land and water use, and greenhouse gas emissions. Potential impacts vary widely by commodity group and by region. These results reveal strengths and potential tradeoffs of different R&amp;amp;D spending allocations, and can help inform decision-making about an optimal R&amp;amp;D portfolio that takes into account the multiple objectives of agricultural investments.

Energy structure dividend, factor allocation efficiency and regional productivity growth-- An empirical examination of energy restructuring in China

This paper introduces the energy structure variables into the generalized cost function from the dual perspective of energy "structural dividend" and factor allocation distortion. It quantitatively estimates the factor allocative efficiency, cost elasticity and marginal cost of the energy decarbonization practice in China from 2004 to 2019. Estimation results show that: (i) there is a "structural dividend" effect of energy restructuring in China. On average, a 1% increase in the level of decarbonization of the energy structure reduces the total cost by 0.57% and the marginal cost by 5.846 billion yuan. Specifically, a 1% reduction in the share of coal consumption reduces the marginal cost by 4.590 billion yuan. (ii)Energy restructuring has accelerated factor allocation distortions in recent years. In terms of the impact of energy decarbonization on productivity growth, the inhibition of factor allocation distortion on productivity growth mainly comes from scale effect. (iii)Energy restructuring has a heterogeneous impact on productivity growth across provinces. Productivity growth in energy-consuming regions is lower than that in energy-supplying regions, while the regions where factor allocation distortions have a greater impact on productivity growth are mostly found in the central and western parts of the country where factor markets are less developed.

The modern Solow paradox. In search for explanations

More than 30 years ago, Robert Solow provided the first evidence of the paradoxical low return of technological progress to productivity. Today, in an era of radical technological changes, characterized by disruptive socio-economic transformations in businesses and society, the puzzle is far from being solved. This paper offers additional reflections on this issue. Stemming from the recognition that in European regions a productivity paradox still persists, this study systematically defines and empirically tests some of the sources that could explain the weak association between the adoption of new technologies and the growth of regional labour productivity. Our findings indicate that, in general, new technologies do have a positive impact on the productivity of the sectors of adoption. The propagation of this effect to the whole regional economy, however, is mitigated by sectoral employment reallocation effects towards less productive sectors.