Regional Productivity Growth Research Articles

Modeling Low Income Vehicle Ownership in Cibadak District

The number and growth of vehicles is a separate problem related to the problem of sustainable transportation. In 2019, the number of motorized vehicles in Indonesia was recorded at more than 448 vehicles per 1,000 people. And specifically for motorcycles, it reaches 365 vehicles per 1,000 people. The growth of motor vehicles is significantly influenced by economic growth as measured by Gross Regional Domestic Product. When compared with the growth of motorized vehicles, it can be concluded temporarily that the high growth rate of motorized vehicles at the end of this decade has an impact on traffic problems on the highway. To see the trend between economic growth represented by regional gross domestic product and motorcycle growth, a model is needed to be useful for policymakers who handle the road in making decisions. The results showed that the growth model of motorcycles in Sukabumi can be approached with a linear regression equation. With the sample from the Cibadak sub-district, the area is classified as a low-income area.

The impact of COVID-19 on China’s regional economies and industries

Scientifically assessing the economic impact of major public health emergencies, containing their negative effects, and enhancing the resilience of an economy are important national strategic needs. The new coronavirus disease (COVID-19) has, to date, been effectively contained in China, but the threat of imported cases and local risks still exist. The systematic identification of the virus’s path of influence and intensity is significant for economic recovery. This study is based on a refined multi-regional general equilibrium analysis model, which measures the economic and industrial impacts at different epidemic risk levels in China and simulates development trends and the degree of damage to industries and the economy under changes to supplies of production materials and product demand. The results show that, at the macroeconomic level, China’s GDP will decline about 0.4% to 0.8% compared to normal in 2020, with an average drop of about 2% in short-term consumption, an average drop in employment of about 0.7%, and an average increase in prices of about 0.9%. At the industry level, the epidemic will have the greatest short-term impact on consumer and laborintensive industries. For example, the output value of the service industry will fall 6.3% compared to normal. Looking at the impact of the epidemic on the industrial system, the province most affected by the epidemic is Hubei, which is the only province in China in the level-1 risk category. As the disease spread outward from Hubei, there were clear differences in the main industries that were impacted in different regions. In addition, simulation results of recovery intensity of regional economies under the two epidemic response scenarios of resumption of work and production and active fiscal stimulus policies show that an increase in fiscal stimulus policies produces a 0.3% higher rate of gross regional product growth but it causes commodity prices to rise by about 1.8%. Measures to resume work and production offer a wider scope for industrial recovery.

Impact of particulate matter on the morbidity and mortalityand its assessment of economic costs

Kazakhstan's cities experience high concentrations levels of atmospheric particulate matter (PM), which is well-known for its highly detrimental effect on the human health. A further increase in PM concentrations in the future could lead to a higher air pollution-caused morbidity and mortality, causing an increase in healthcare expenditures by the government. However, to prevent elevated PM concentrations in the future, more stringent standards could be implemented by lowering current maximum allowable PM concentration limit to Organization for Economic Co-operation and Development (OECD)'s limits. Therefore, this study aims to find out what impact this change in environmental policy towards PM has on state economy in the long run. Future PM10 and PM2.5 concentrations were estimated using multiple linear regression based on gross regional product (GRP) and population growth parameters. Dose-response model was based on World Health Organization's approach for the identification of mortality, morbidity and healthcare costs due to air pollution. Analysis of concentrations revealed that only 6 out of 21 cities of Kazakhstan did not exceed the EU limit on PM10 concentration. Changing environmental standards resulted in the 71.7% decrease in mortality and 77% decrease in morbidity cases in all cities compared to the case without changes in environmental policy. Moreover, the cost of morbidity and mortality associated with air pollution decreased by $669 million in 2030 and $2183 million in 2050 in case of implementation of OECD standards. Thus, changing environmental regulations will be beneficial in terms of both of mortality reduction and state budget saving.

The Impact of Clusters on Regional Competitiveness

Cluster development is one of determinants used in the regional competitiveness that are related to the presence of competitive local suppliers and competitive local industries in the regional economy. The correlation analysis permits to conclude that regions, which are more competitive, have more developed clusters and regions with more developed clusters are more competitive. However, the comparison between competitiveness and cluster development of particular regions reveal that the impact of clusters on competitiveness can differ across regions and countries, thus creating challenges for policy makers. The paper focuses on the evaluation of the clusters’ approach in promoting regional productivity, innovation and economic growth leading to increased competitiveness, yet arguing that the targeted cluster development can foster structural change leading to improved economic performance, as well as welfare.

Dynamic simulation for comprehensive water resources policies to improve water-use efficiency in coastal city

Coastal cities play an important role in regional economic development and sustainable development strategies of water resources and their ecological environment. As a typical coastal city in Hebei Province, Qinhuangdao city is facing severe problems, such as water shortages and water environment deterioration, while social and economic development continues. Based on input-output analysis, we established a dynamic optimization model among Qinhuangdao city's socioeconomic development, water resources and water environment. The 2013-2030 simulation after introducing comprehensive water resources policies of regional development, examines the regional socioeconomic development, optimizes the water resources supply structure and improves the water environment under the optimal scenario, and evaluates policy feasibility through cost-benefit analysis (CBA). The simulation results suggest that under the optimal scenario, the water-use efficiency (WE) of Qinhuangdao is improved by 59.14% and the proportion of reclaimed water and desalinated seawater in the water supply structure is increased by 13.70%. In addition, it has achieved an average annual gross regional production (GRP) growth rate of 6.36% and an average annual chemical oxygen demand (COD) emission rate of 17.95%. Moreover, the net present value (NPV) of the projects under the optimal scenario is 1.534 billion Chinese yuan (CNY), which means that the policy is economically feasible. Our research is helpful to improve the WE, optimize the water supply structure and protect the hydrogeological environment in coastal cities with water shortages and can provide a reference for Qinhuangdao city and other similar coastal cities to realize the rational utilization of water resources and regional sustainable development.

Predictive analysis of labor productivity growth factors: regional aspects

The study is aimed at identifying predictors of labor productivity growth in Russian regions. To compile a primary set of predictors and establish the relationship between them, a contextual review of publications on the topic under study was carried out. The factors, that directly and indirectly affect the increase in labor productivity in the regions of Russia, include institutional conditions; investments in fixed assets; orientation of companies to the development of new markets and participation in export activities; research and development costs; technological and organizational innovation; investment in human capital. The theoretical foundations for the formation of effective incentives in the regions for changing the strategic behavior of companies that meet global technological and socio-economic challenges are formulated. The results of predictive analysis are the basis for building a model of system dynamics of relevant factors of growth in labor productivity in the regions.

АНАЛИЗ ВЛИЯНИЯ ПРОИЗВОДИТЕЛЬНОСТИ ТРУДА НА ПОКАЗАТЕЛИ ЭКОНОМИЧЕСКОГО РОСТА НА НАЦИОНАЛЬНОМ, СУБФЕДЕРАЛЬНОМ И РЕГИОНАЛЬНОМ УРОВНЯХ

Labour productivity has a predominant impact on economic growth and the rate of postcrisis economic recovery. The increase in labour productivity, in turn, depends on the employed population’s standard of living. A comparative longitude analysis of these indicators’ dynamics reveals the potential for the economic growth of the territory. The historically determined asymmetry in the economic development of Russian regions requires analysis carried out at the national, sub-federal (federal districts), and regional levels. In the study, the author evaluates the dynamics of the per capita gross regional product (GRP), labour productivity, and real wages in constant prices at purchasing power parity for Russia, the Siberian Federal District, and Krasnoyarsk Krai. The results of this analysis allow comparing economic growth and labour productivity growth in Russia and Russian regions with international trends. The author has found that labour productivity per working hour measured in constant prices in Russia, Siberia, and Krasnoyarsk Krai is several times lower than the corresponding indicators of countries leading in productivity and economic growth. The dynamics of per capita GRP and labour productivity, measured both in current and constant prices, is positive. The statistical relationship between labour productivity growth and cyclical processes in the national economy is noted; in the crisis and post-crisis periods, there is outstripping growth in labour productivity due to the mobilization of the workers’ labour potential. The economy of the Siberian Federal District has been characterized by a steady excess of the growth rate of labour productivity over the growth rate of per capita GRP, while in Krasnoyarsk Krai and Russia this trend has manifested since 2014 with the onset of the crisis. This process indicates a change in the mechanisms of economic growth: with the entry into the crisis phase, human labour, as well as its efficiency, becomes the only significant factor in maintaining the stability of national and regional economies. The obtained results also show the depressive impact of a long-term decline in real wages on labour productivity and economic growth during the economic crisis. The structural analysis demonstrates that labour productivity growth has a strong positive effect on economic growth, while the growth of the employment rate has a moderate positive effect. A decline in the share of the working-age population in the demographic structure has a pronounced negative impact on economic growth in the long-term period. The study results can be used in the development of national and regional policies related to stimulating economic growth.

ДИНАМИКА СОЦИАЛЬНЫХ ПОКАЗАТЕЛЕЙ УСТОЙЧИВОГО РАЗВИТИЯ НЕФТЕДОБЫВАЮЩИХ РЕГИОНОВ РОССИИ

The article presents an assessment of social sustainable development indicators for Russian oil-and-gas regions. Natural energy resources are one of the most important factors in ensuring the competitiveness of regional economy. However, the resource sector development leads to a subnational resource dependence and to a decline in the quality of life indicators. Natural resources could be a motor of economic development. For this purpose, local authorities should enhance the social and market infrastructure, innovation and investment activity, create institutions that support diversification and prevent the overindulgence of resource companies. The natural resources’ impact on the quality of life for Tomsk Oblast, the Komi Republic, the Udmurt Republic, the Republic of Tatarstan, and Samara Oblast was assessed. These regions have small energy resource (oil and gas) reserves, but mining creates 15 to 30% of the regional product. Extractive industries employ 2% of the workforce. World economy trends in 2008-2018 had a significant negative impact on the mining sector of these regions. Dependence on oil prices has led to a reduction in subnational budget revenues, the Gross Regional Product growth rate has declined, the poverty rate has increased, and the quality of life indicators have decreased. Demographic indicators (fertility and mortality rates) have also worsened. The social and economic development indicators in most of the considered oil-and-gas regions became worse than the same indicators in Russia. This fact indicates a high level of resource dependence of subnational economies (resource curse). Only in the Republic of Tatarstan the resource sector became the motor of the regional economic performance, despite the decline in oil prices. As a result, Tatarstan occupies a leading position in the rating of the quality of life indicators. The level of poverty in Tatarstan is lower than in other resource regions and in Russia. Tatarstan also has a high level of population growth, low unemployment, and higher rates of economic growth than Russia. The worst situation is in Tomsk Oblast and in the Komi Republic, in which the share of the extractive sector in the Gross Regional Product is 30%; therefore, the indicators of the socioeconomic development are highly dependent on the oil-and-gas companies’ performance. Low diversification, transport accessibility limitations, poor natural and climatic conditions, as well as a decrease in the income of oil-and-gas companies due to the fall in oil prices leads to an increase in poverty rates in these regions, increases the out-region migration of the working-age population, which reduces regional competitiveness. Thus, the economies of most of the considered oil-and-gas regions cannot be considered sustainable.

Economic growth vs. eco-efficiency of Russian industrial regions

The article focuses on issues of economic growth, and eco-efficiency in Russian industrial regions on the example of the Urals Federal District. The study is based on the concept of existing tensions between economic development, and eco-efficiency. The author claims that within this concept an optimum could be found. The purpose of the study is to determine the most optimal industrial growth rate within the Urals Federal District. Industrial production representing 50% of the sectoral gross value added structure is the key factor of economic growth in the researched regions. This basic hypothesis of the study is confirmed by a relatively strong correlation between industrial growth rate and Gross Regional Product growth rate in Sverdlovsk region, Tyumen region, and Chelyabinsk region. As part of the study the author made use of correlation analysis, which confirmed the basic hypothesis of the research, and paired regression analysis, where industrial production growth rate is used as a regressor to build paired regression models. Economic growth is estimated via Gross Regional Product growth rate. For every sector, where the basic hypothesis is confirmed, there is a graphical model illustrating dependence of economic growth (E1), and eco-efficiency (E2) on industrial growth rate. The study discovers optimal industrial growth rate providing development of eco-efficiency in the researched regions. The results of the study can be applied both by scientists or government structures in strategies of regional development taking into account eco-efficiency.

Regional Economic Integration and Productivity Convergence: Empirical Evidence from East Asia

The study attempts to seek evidence on regional economic integrationin driving labor productivity convergence in low-and middle-income East Asian states towards Japan, the country assumed to be the regional technology leader. The labor productivity convergence of low-and middle-income East Asian countries towards their rich neighbor is modelled against their national levels of innovation, technology spill-oversfrom the regional economic leader and their productivity differential with the frontier country. The hypothesized relationship is empirically verified for seven East Asian states, using a robust econometric approach. The time-series test estimates under Error Correction Representation yield absolute support in favor of valid productivity convergence occurring between Japan and its low-and middle income neighbors. However, panel data estimates generated with better statistical power outperform the time-series test findingsand these results reject the significance of Japan as the regional productivity growth driver for its regionaldevelopingstates.

ANALISIS POTENSI SEKTOR BASIS DAN NON BASIS KOTA SABANG TAHUN 2013-2019

The success of a region in improving its economy can be measured by the growth of Gross Domestic Regional Product (GDRP) from various existing sectors. This Gross Domestic Regional Product (GDRP) growth occurs if the region has a leading sector or a basic sector whose growth rate is relatively fast and has strong competitiveness and a non-basic sector that has the opportunity to become a basic sector if the local government is able to condition the opportunities that exist into an optimal result. This study uses secondary data obtained from the Central Statistics Agency (BPS) of Aceh Province in the form of time series data for 7 years, namely the 2013-2019 period. This research was conducted to identify the basic and non-basic sectors in the economic structure of the City of Sabang for the period 2013 - 2019 using the LQ (location quotient) analysis method, the Dynamic Location Quotient (DLQ) method, Shift Share Analysis, and quadrant analysis. 10 basic sectors with the highest average index value SLQ ≥ 1 and 7 sectors which are non-basic sectors with index numbers <1. In the quadrant analysis from the results of the existing Shift-Share calculations, there are 3 sectors in Quadrant I with fast and strong growth,3 sectors in Quadrant II with slow and strong growth, and 11 sectors in Quadrant III with fast growth but have weak competitiveness

The Strategic Development Prospects of the North Caucasus Federal Okrug

Last year (2019) was the tenth year of the implementation of the Strategy of Socioeconomic Development of the North Caucasus Federal Okrug until 2025, adopted in 2010. The Strategy aims at achieving significant economic growth across the North Caucasus regions, as well as modernizing their social structure and stabilizing their socio-political situation. In order to achieve economic growth in the North Caucasus, the Strategy focuses on the creation of a tourism cluster, accelerated development of the region’s transport system, and the emergence of new centers of economic development. The Strategy’s targets that should serve as the indicators of its successful implementation (under the optimal scenario) are the gross regional product growth of 7.7% per annum in the regions of the North-Caucasian Federal Okrug, and industrial production growth of 10.1% per annum over the period from 2010 through 2025. The Strategy also aims at creating not less than 400,000 new jobs, reducing the official unemployment rate to 5% (from 16.5% in 2010), and decreasing the share of households with incomes below the subsistence level to 9.2% (from the regions average of 15.5% 2010).

De facto power of elites and regional growth

AbstractInstitutions are considered one of the fundamental elements of economic growth. We analyse the impact of the feudal landlordship institution on regional economic growth in nineteenth century Prussia in order to help draw implications for the modern roles of institutions. To measure landlord power, we use three measures of feudal landlordship: landowner concentration, servant population share, and household‐servant population share. These proxies, measured in 1816, are associated with both faster regional population growth and agricultural productivity growth, but no impact on industrialization in the early nineteenth century. However, in the latter nineteenth century, these same proxies are associated with delayed industrialization and no influence on regional population. Thus, stronger feudal landlordship was beneficial to regional growth when agriculture was the dominant industry but became detrimental to growth when manufacturing became dominant.

RECONCILED ESTIMATES AND NOWCASTS OF REGIONAL OUTPUT IN THE UK

There is renewed interest in levelling up the regions of the UK. The combination of social and political discontent, and the sluggishness of key UK macroeconomic indicators like productivity growth, has led to increased interest in understanding the regional economies of the UK. In turn, this has led to more investment in economic statistics. Specifically, the Office for National Statistics (ONS) recently started to produce quarterly regional GDP data for the nine English regions and Wales that date back to 2012Q1. This complements existing real GVA data for the regions available from the ONS on an annual basis back to 1998; with the devolved administrations of Scotland and Northern Ireland producing their own quarterly output measures. In this paper we reconcile these two data sources along with UK quarterly output data that date back to 1970. This enables us to produce both more timely real terms estimates of quarterly economic growth in the regions of the UK and a new reconciled historical time-series of quarterly regional real output data from 1970. We explore a number of features of interest of these new data. This includes producing a new quarterly regional productivity series and commenting on the evolution of regional productivity growth in the UK.

Haze pollution, new-type urbanization and regional total factor productivity growth: based on a panel dataset involving all 31 provinces within the territory of China

Purpose This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth. Design/methodology/approach This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth. Findings The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect. Originality/value This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.

World Productivity: 1996-2014

We account for the sources of world productivity growth, using data for more than 36 industries and 40 major economies from 1996 to 2014, explicitly taking into account changes in the misallocation of resources in labor, capital, and product markets. Productivity growth in advanced economies slowed but emerging markets grew more quickly which kept global productivity growth relatively constant until around 2010. After that, productivity growth in all major regions slowed. Much of the volatility in world productivity growth reflects shifts in the misallocation of labor across countries and industries. Using new data on PPP-based value-added measures by country and industry, we show that about a third of these shifts is due to employment growing in countries, most notably China and India, that benefit from an international cost advantage. Markups are large and rising and impact the imputed misalloction of capital. However, they have little effect on the country-industry technology contribution to global productivity.

Why Is Current Unemployment So Low?

We account for the sources of world productivity growth, using data for more than 36 industries and 40 major economies from 1996 to 2014, explicitly taking into account changes in the misallocation of resources in labor, capital, and product markets. Productivity growth in advanced economies slowed but emerging markets grew more quickly which kept global productivity growth relatively constant until around 2010. After that, productivity growth in all major regions slowed. Much of the volatility in world productivity growth reflects shifts in the misallocation of labor across countries and industries. Using new data on PPP-based value-added measures by country and industry, we show that about a third of these shifts is due to employment growing in countries, most notably China and India, that benefit from an international cost advantage. Markups are large and rising and impact the imputed misallocation of capital. However, they have little effect on the country-industry technology contribution to global productivity.

DETERMINANTS OF DISTRICTS/CITIES EDUCATION ATTAINMENT INEQUALITY IN EAST JAVA PROVINCE DURING 2014-2016

High school enrollment rate can reduce educational inequality. However, East Java Province which has a high school enrollment rate, education inequality is also high. Using data from the National Socioeconomic Survey (Susenas) from 2014 to 2016 and publications from several institutes, this research aims to find out the determinants of districts/cities education inequality in East Java in 2014-2016. The inferential analysis uses panel data regression with the random effect model (REM). The results show that the significant variables increasing the education inequality are the percentage of poor population and percentage of married young women, while the significant variables decreasing the education inequality are Gross Domestic Regional Product (GDRP) growth, the percentage of household head educated minimum secondary level, and teacher-school ratio on the secondary level. There are no significant effects of government spending on education inequality.

DETECTION OF THE SPECIFICITY OF PUBLIC REPRODUCTION OF THE AMUR REGION WITH THE HELP OF THE COBB – DOUGLAS PRODUCTION FUNCTION

Construction of the Cobb – Douglas production function taking into account the factor “innovations and information” (on the example of the economy of the Amur region) has been considered. The adequacy of the obtained production function to the initial data has been checked using Fisher`s criterion. An analysis of the constructed production function using the indicators of average and marginal resource efficiency, elasticity of output, depending on resource consumption has been carried out. It has been revealed, that labor is the most stable factor during the study period. In the Amur Region in 2000-2017 labor-saving (intensive) gross regional product growth is observed. However, this indicator increased more slowly than factors, that is, the average costs calculated per 1 unit of output are growing and there is a diminishing effect on the scale of production.

Determinants of labour productivity growth in Spanish and Portuguese regions: a spatial shift-share approach

This article analyses the structural changes in labour productivity in the regions of Spain and Portugal during the period 2000–2015, by business sector contribution and spatial distribution. A shift-share empirical analysis was applied to identify the components of aggregate productivity growth and to ascertain the role played by the different sectors. Both the intra-sectoral component and the presence of spatial autocorrelation were found to be statistically significant, which led us to identify two clusters: one of high productivity, corresponding to regions in the eastern half of the Iberian peninsula, and the other of low productivity, in the west. For both clusters, various model specifications that have been proposed in spatial econometrics literature were used to estimate spatial spillovers of each sector and determine the contribution made to productivity growth by each sectoral component, and to identify any spatial feedbacks that may be generated in this process. The total effect of intra-sectoral component for all sectors in both clusters is positive. The highest values are obtained by the agriculture, construction, trade and public services sectors. Moreover, the total effects are greater in the high-productivity cluster, except for the industry sector.