Considering the growing significance of Eurasian economic ties because of South Korea s New Northern Policy and Russia s New Eastern Policy, this study investigates the motivations and locational factors of South Korean foreign direct investment (FDI) in three countries in the Commonwealth of Independent States (CIS: Kazakhstan, Russia, and Uzbekistan) by employing panel analysis (pooled ordinary least squares (OLS), fixed effects, random effects) using data from 1993 to 2017. The results show the positive and significant coefficients of GDP, resource endowments, and inflation. Unlike conventional South Korean outward FDI, labour-seeking is not defined as a primary purpose. Exchange rates, political rights, and civil liberties are identified as insignificant. The authors conclude that South Korean FDI in Kazakhstan, Russia, and Uzbekistan is associated with market-seeking (particularly in Kazakhstan and Russia) and natural resource-seeking, especially the former. From a policy perspective, our empirical evidence suggests that these countries host governments could implement mechanisms to facilitate the movement of goods across regions and countries to increase the attractiveness of small local markets. The South Korean government could develop financial support and risk sharing programmes to enhance natural resource-seeking investments and mutual exchange programmes to overcome the red syndrome complex in South Korean society.
{"title":"Motivations and locational factors of FDI in CIS countries: Empirical evidence from South Korean FDI in Kazakhstan, Russia, and Uzbekistan","authors":"Han-Sol Lee, S. U. Chernikov, S. Nagy","doi":"10.15196/RS110404","DOIUrl":"https://doi.org/10.15196/RS110404","url":null,"abstract":"Considering the growing significance of Eurasian economic ties because of South Korea s New Northern Policy and Russia s New Eastern Policy, this study investigates the motivations and locational factors of South Korean foreign direct investment (FDI) in three countries in the Commonwealth of Independent States (CIS: Kazakhstan, Russia, and Uzbekistan) by employing panel analysis (pooled ordinary least squares (OLS), fixed effects, random effects) using data from 1993 to 2017. The results show the positive and significant coefficients of GDP, resource endowments, and inflation. Unlike conventional South Korean outward FDI, labour-seeking is not defined as a primary purpose. Exchange rates, political rights, and civil liberties are identified as insignificant. The authors conclude that South Korean FDI in Kazakhstan, Russia, and Uzbekistan is associated with market-seeking (particularly in Kazakhstan and Russia) and natural resource-seeking, especially the former. From a policy perspective, our empirical evidence suggests that these countries host governments could implement mechanisms to facilitate the movement of goods across regions and countries to increase the attractiveness of small local markets. The South Korean government could develop financial support and risk sharing programmes to enhance natural resource-seeking investments and mutual exchange programmes to overcome the red syndrome complex in South Korean society.","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46353220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The information age is also an era of escalating social problems. The digital transformation of society and the economy is already underway in all countries, although the progress in this transformation can vary widely. There are more social innovation projects addressing global and local social problems in some countries than in others. This suggests that different levels of digital transformation might influence the social innovation potential. Using the International Digital Economy and Society Index (I-DESI) and the Social Innovation Index (SII), this study investigates how digital transformation of the economy and society affects the capacity for social innovation. A dataset of 29 countries was analysed using both simple and multiple linear regressions and Pearson's correlation. Based on the research findings, it can be concluded that the digital transformation of the economy and society has a significant positive impact on the capacity for social innovation. It was also found that the integration of digital technology plays a critical role in digital transformation. Therefore, a country's progress in digital transformation is beneficial to its social innovation capacity. In line with the research findings, this study outlines the implications and possible directions for policy.
{"title":"The relationship between social innovation and digital economy and society","authors":"S. Nagy, M. V. Somosi","doi":"10.15196/RS120202","DOIUrl":"https://doi.org/10.15196/RS120202","url":null,"abstract":"The information age is also an era of escalating social problems. The digital transformation of society and the economy is already underway in all countries, although the progress in this transformation can vary widely. There are more social innovation projects addressing global and local social problems in some countries than in others. This suggests that different levels of digital transformation might influence the social innovation potential. Using the International Digital Economy and Society Index (I-DESI) and the Social Innovation Index (SII), this study investigates how digital transformation of the economy and society affects the capacity for social innovation. A dataset of 29 countries was analysed using both simple and multiple linear regressions and Pearson's correlation. Based on the research findings, it can be concluded that the digital transformation of the economy and society has a significant positive impact on the capacity for social innovation. It was also found that the integration of digital technology plays a critical role in digital transformation. Therefore, a country's progress in digital transformation is beneficial to its social innovation capacity. In line with the research findings, this study outlines the implications and possible directions for policy.","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48291879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
One of the main contributors to air pollution is particulate matter (PMxy), which causes several Covid-19 related diseases such as respiratory problems and cardiovascular disorders. Therefore, the spatial and temporal trend analysis of particulate matter and the mass concentration of all aerosol particles <= 2.5 mu m in diameter (PM2.5) have become critical to control the risk factors of co-morbidity of a patient. Lockdown plays a significant role in reducing Covid-19 cases as well as air pollution, including particulate matter concentration. This study aims to analyse the effect of the lockdown on controlling air pollution in metropolitan cities in India through various statistical modelling approaches. Most research articles in the literature assume a linear relationship between responses and covariates and take independent and identically distributed error terms in the model, which may not be appropriate for analysing such air pollution data. In this study, a pattern analysis of PM2.5 daily emissions in different main activity zones during 2019 and 2020 was performed. The seasonal effect was also taken into account when measuring the lockdown effect. The PM2.5 values at the unobserved location were predicted using three popular spatial interpolation techniques: (i) inverse distance weight (IDW), (ii) ordinary kriging (OK), and (iii) random forest regression kriging (RFK), and their root mean square error (RMSE) was compared. Subsequently, the spatio-temporal intervention of lock down on air pollution was estimated using the difference-in-difference (DID) estimator. In winter, the transport zones, namely Anand Vihar and ITO airport, were the most affected regions. The northwestern part of Delhi is the most sensitive zone in terms of air pollution. Due to the lockdown, the weekly PM2.5 emission decreased by 62.15%, the mass concentration of all aerosol particles <= 10 mu m in diameter (PM10) decreased by 53.14%, and the air quality index (AQI) improved by 22.40%. A proposal is made to adopt corrective measures to maintain the air pollution index, taking into account the spatial and temporal variability in the responses.
{"title":"Statistical assessment of spatio-temporal impact of Covid-19 lockdown on air pollution using different modelling approaches in India, 2019-2020","authors":"Debjoy Thakur, Dr. Ishapathik Das","doi":"10.15196/RS120303","DOIUrl":"https://doi.org/10.15196/RS120303","url":null,"abstract":"One of the main contributors to air pollution is particulate matter (PMxy), which causes several Covid-19 related diseases such as respiratory problems and cardiovascular disorders. Therefore, the spatial and temporal trend analysis of particulate matter and the mass concentration of all aerosol particles <= 2.5 mu m in diameter (PM2.5) have become critical to control the risk factors of co-morbidity of a patient. Lockdown plays a significant role in reducing Covid-19 cases as well as air pollution, including particulate matter concentration. This study aims to analyse the effect of the lockdown on controlling air pollution in metropolitan cities in India through various statistical modelling approaches. Most research articles in the literature assume a linear relationship between responses and covariates and take independent and identically distributed error terms in the model, which may not be appropriate for analysing such air pollution data. In this study, a pattern analysis of PM2.5 daily emissions in different main activity zones during 2019 and 2020 was performed. The seasonal effect was also taken into account when measuring the lockdown effect. The PM2.5 values at the unobserved location were predicted using three popular spatial interpolation techniques: (i) inverse distance weight (IDW), (ii) ordinary kriging (OK), and (iii) random forest regression kriging (RFK), and their root mean square error (RMSE) was compared. Subsequently, the spatio-temporal intervention of lock down on air pollution was estimated using the difference-in-difference (DID) estimator. In winter, the transport zones, namely Anand Vihar and ITO airport, were the most affected regions. The northwestern part of Delhi is the most sensitive zone in terms of air pollution. Due to the lockdown, the weekly PM2.5 emission decreased by 62.15%, the mass concentration of all aerosol particles <= 10 mu m in diameter (PM10) decreased by 53.14%, and the air quality index (AQI) improved by 22.40%. A proposal is made to adopt corrective measures to maintain the air pollution index, taking into account the spatial and temporal variability in the responses.","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41593420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of selected economic factor impacts on CO2 emissions intensity: A case study from Jordan, 1990-2015","authors":"Mohammad M. Jaber","doi":"10.15196/rs120101","DOIUrl":"https://doi.org/10.15196/rs120101","url":null,"abstract":"","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Halo effect of diversification and polarization, and the role of relative deprivation based on the 2018 Swedish parliamentary elections results","authors":"Dávid Sümeghy","doi":"10.15196/rs120106","DOIUrl":"https://doi.org/10.15196/rs120106","url":null,"abstract":"","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study raises the question of whether the COVID-19 pandemic will have a long-lasting impact on the dynamics of the unemployment rate. More specifically, this problem implies an analysis of whether any sign of a structural break is detectable in the time series of the unemployment rate. To obtain some "firsthand" estimates on whether it is likely that a structural break will occur in the labour market, this study performs several one-step-ahead forecasts based on the best ARIMA model on the time series of the unemployment rate, which takes advantage of the availability of the unemployment rate data for five quarters following the pandemic outbreak. Interestingly, the results document practically no difference in the impact of the pandemic on the labour market in countries with different labour market flexibility. Neither North America (United States of America and Canada) with a flexible labour market nor continental Europe (Germany and Austria) with a regulated labour market experienced any regime change in the unemployment rate time series.
{"title":"Has COVID-19 caused a change in the dynamics of the unemployment rate? The case of North America and continental Europe","authors":"Judit Kapás","doi":"10.15196/rs120107","DOIUrl":"https://doi.org/10.15196/rs120107","url":null,"abstract":"This study raises the question of whether the COVID-19 pandemic will have a long-lasting impact on the dynamics of the unemployment rate. More specifically, this problem implies an analysis of whether any sign of a structural break is detectable in the time series of the unemployment rate. To obtain some \"firsthand\" estimates on whether it is likely that a structural break will occur in the labour market, this study performs several one-step-ahead forecasts based on the best ARIMA model on the time series of the unemployment rate, which takes advantage of the availability of the unemployment rate data for five quarters following the pandemic outbreak. Interestingly, the results document practically no difference in the impact of the pandemic on the labour market in countries with different labour market flexibility. Neither North America (United States of America and Canada) with a flexible labour market nor continental Europe (Germany and Austria) with a regulated labour market experienced any regime change in the unemployment rate time series.","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring shadow banking in Central and Eastern European countries: A new dataset, 2004-2019","authors":"A. Bethlendi, Katalin Mérő","doi":"10.15196/rs120405","DOIUrl":"https://doi.org/10.15196/rs120405","url":null,"abstract":"","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Return equicorrelation and dynamic spillovers between Central and Eastern European, and World stock markets, 2010-2019","authors":"N. Hung","doi":"10.15196/rs120108","DOIUrl":"https://doi.org/10.15196/rs120108","url":null,"abstract":"","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Employment data of participants in supported adult training for jobseekers and their territorial pattern in Hungary, 2010-2020","authors":"Dávid Hajdú, G. Koncz","doi":"10.15196/rs120205","DOIUrl":"https://doi.org/10.15196/rs120205","url":null,"abstract":"","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modelling the customer potential of retail food stores: A case study from the Turiec region in Slovakia, 2020","authors":"Pavol Ďurček, Gabriela Nováková, Ingrid Buceková","doi":"10.15196/rs120208","DOIUrl":"https://doi.org/10.15196/rs120208","url":null,"abstract":"","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66867457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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