Papers by Regional Statistics
Regional Statistics, 2024
This paper investigates the role of natural resource rent and other forms of rent on the economic... more This paper investigates the role of natural resource rent and other forms of rent on the economic growth of Middle Eastern and North African (MENA) countries within the framework of the rent curse theory. Rent curse theory suggests that while certain types of rent, such as geopolitical, regulatory, and labour rent, can hinder growth, others may act as incentives. Employing the partial least squares structural equation model (PLS-SEM), this study examines the impact of rent and financial development on economic growth in the region. The empirical findings reveal that forms of rent derived from natural resources and regulatory rent have a negative effect on financial development and economic growth, but labour rent and geopolitical rent do not have any contribution to economic growth, so the rent curse theory cannot be confirmed by these two sources of rent. Furthermore. The result indicates that financial development is a crucial factor for economic progress. Moreover, the study suggests that globalization can enhance financial development in MENA countries and stimulate growth.
Regional Statistics, 2024
The Czech and Hungarian labour markets have undergone significant changes: European Union (EU) ac... more The Czech and Hungarian labour markets have undergone significant changes: European Union (EU) accession and various employment and job creation programmes that have all left their mark on employment. The authors analysed the two major economic crises-the 2008 global economic crisis and Covid-19 pandemic-and their impact on the labour markets of the examined countries from a regional perspective. The phases of change in the examined unemployment rates and the reasons for this change have shown that the crises have affected the employment situation in the regions of the countries in different ways, degrees and lengths of time.
Regional Statistics, 2024
The study employs an empirical Bayesian estimation approach to examine how the crash risk of the ... more The study employs an empirical Bayesian estimation approach to examine how the crash risk of the G-7 (United States [US], United Kingdom [UK], Japan, Germany, Canada, and France excluding Italy) and Chinese equity markets affects the crash risk of the top 11 cryptocurrencies. Two crash risk measures were adopted to determine the monthly crash risk of the two types of markets, which are the most appropriate for skewed returns. Four separate models were estimated using the empirical Bayes estimation method because it considers heterogeneity, is more efficient than least squares, and facilitates more accurate coefficient estimation. The results reveal that the German stock market's crash risks are significantly and contemporaneously associ-ated with the crash risk of all 11 crypto-currencies, indicating that the German equity market is not a reliable diversifier for crypto-currencies. The crash risks of the US, UK, and Japanese (German and Canadian) equity markets have a positive (negative) impact on the crash risk of cryptocurrency markets with a one-month lag. Generally, lagged crash risks have a more substantial influence on crypto-currency crash risk, suggesting that historical crashes in equity markets are better predictors of cryptocurrency crashes. The one-month significant delay effect may present arbitrage opportunities because the risk of crashes in stock markets may signal potential crashes in cryptocurrencies one month in advance. A series of robustness checks confirmed the results of the analysis and the validity of our conclusions. These findings suggest that crypto investors and policy-makers should pay attention to historical events in equity markets. Investors and portfolio managers in the cryptocurrency market should monitor unex-pected fluctuations in the stock market, particularly significant declines that could result in significant losses in the future.
Regional Statistics, 2024
This study aims to assess the impact of green investment on the quality of green economic develop... more This study aims to assess the impact of green investment on the quality of green economic development in 85 constituent entities of Russia during the period 2010–2021. The research findings indicate that the development of green economic practices in these entities is not random but has interrelationships with neighbouring entities. Green investment is an important factor in promoting the quality of green economic development, not only within a single entity but also spilling over to neighbouring entities. Furthermore, the authors also discovered that green investment not only directly affects the quality of green economic development but also indirectly enhances it by reducing environmental pollution. In terms of policy implications, the spillover effects in green investment, CO2 emissions, and green economic development in the constituent entities of Russia highlight the importance of cooperation among entities in jointly advancing green economic development. Careful consideration should also be given to environmental impacts in the formulation of development policies, as they can affect neighbouring entities. Given the limited participation of entities and financial resources for green investment, the Russian government needs to design a clear roadmap for transitioning to a green economy, particularly through policy tools such as taxes and subsidies for green companies and projects, while also encouraging financial institutions to participate in the provision of green financial instruments.
Regional Statistics, 2024
This paper investigates the role of European firms´ location in their access to capital from 2014... more This paper investigates the role of European firms´ location in their access to capital from 2014 to 2018. Spatial variation in a firm´s access to finance triggers differences between the development of rural and urban areas. The study draw on the geography of finance, which explores the phenomenon of the spatial distribution of financial markets, and aim to answer the question of to what extent the location of a firm affects its access to capital. The authors focus on both credit and equity markets and pursue an econometric approach. The paper explore the drivers of the capital structures of European firms with the main control variables connected to the spatial distribution of economic actors. The authors adds to the regional finance literature by examining hard data on the real capital structure patterns of firms. The findings lead to different conclusions: While for the credit market, the location of a firm still matters, financial center bias regarding the primary equity market is fading due to the growing computerization of communication.
Highlights:
• Companies from financial centers have better access to bank credit.
• The concentration of the banking system increases the disparities between the core and periphery.
• There is financial center bias in the equity markets in most European countries.
• Financial center bias is negatively linked to the computerization of financial markets.
Regional Statistics, 2024
The research proposes an alternative inequality index, an extension of the Amato index, which we ... more The research proposes an alternative inequality index, an extension of the Amato index, which we term the extended Amato index. The original Amato index, which represents the length of the Lorenz curve and forms part of the inequality zone's perimeter, serves as the foundation for this extension. The authors derive this index by computing the ratio of the inequality zone's perimeter to the inequality triangle's perimeter, both of which emerge from the egalitarian line and the Lorenz curve. The study apply the extended Amato index to empirical and Lorenz function formulations, using data on income employment per household from The Ghana Living Standards Survey IV. The results suggest that the extended Amato index fulfils all properties of the inequality measure, except egalitarian zero. However, the authors rectify this by performing minimum-maximum scaling adjustments on the extended Amato index, yielding the adjusted extended Amato index, which satisfies all properties of the inequality measure, including egalitarian zero. The empirical findings reveal high levels of income inequality in Ghana in 1998, as indicated by the value of the extended Amato index. Furthermore, when the value of the extended Amato index is calculated using the Lorenz function formulation, the accurate specification of the Lorenz function is validated due to its strong alignment with the empirical Lorenz curve. Ultimately, these findings can guide policies aimed at reducing inequality through wealth redistribution
Regional Statistics, 2024
A large part of market theory literature focuses on the cost pass-through behaviour of firms, as ... more A large part of market theory literature focuses on the cost pass-through behaviour of firms, as it is an essential instrument in the analytical toolkit of competition authorities when carrying out market structure-related examinations. Although spatial relations are well documented in many markets, cost pass-through analysis frameworks do not seem to incorporate these issues. Applying an error correction-based estimation strategy extended by a spatial econometric frame-
work, the present paper provides evidence that spatial dependence appears significantly in the cost pass-through behaviour of firms. This suggests that, on the one hand, the detected symmetric cost pass-through may cover the properties of the competition. On the other hand, competition authorities should consider spatial dependencies when preparing court-case decisions to avoid verdicts arising from presumably spurious analysis results.
Regional Statistics, 2024
This study investigates the impact of a fiscal policy spending shock on the economy of the Visegr... more This study investigates the impact of a fiscal policy spending shock on the economy of the Visegrad 4 countries. The impact is estimated with an SVAR model, and the calculations are based on 84 quarterly observations (1999Q1-2019Q4). The results suggest that fiscal expansion has a larger than usual impact in the V4 countries (except for Slovakia): the estimated long-term (5-year) cumulative spending multipliers are 0.81 for Czechia, 1.14 for Hungary, and 1.76 for Poland (the Slovakian multiplier has a value of-0.18, but it is not significant). The discussion section also connects higher spending multipliers with a higher share of value added tax (VAT) revenues, a higher debt ratio, higher foreign debt, and lower openness.
Regional Statistics, 2024
Szekely Land is a historical and ethnographic area of 12,500 km² located in the southeastern part... more Szekely Land is a historical and ethnographic area of 12,500 km² located in the southeastern part of Transylvania, in the geographical center of Romania. Medieval documents refer to it as Terra Siculorum, Székelyföld in Hungarian, Szeklerland in German, Ţinutul Secuiesc, Secuimea in Romanian, Szekely Land or Szeklerland in English. Based on the data of the 2011 and 2022 Romanian censuses, 70-75% of the currently estimated population of 700,000 people ([1], [2]) are of Hungarian nationality. This represents the largest ethnic Hungarian bloc living outside the territory of Hungary. The settlement of Szekelys/Szeklers in present-day Szekely Land began in the middle of the 12th century and was completed by the end of the century. The border guard population settled in the eastern border region of the Kingdom of Hungary was integrated into the country's ecclesiastical and secular administrative system. Their settlements were organized according to the "ten" system, which is the basis of military service. In the papal tithe register from the 1330s, 152 tax-paying parishes in Szekely Land were identified. Several villages belonged to a tax-paying parish, so the number of existing settlements could have been much larger (Elekes 2016). In the 13th century, the special administrative units, the Hungarian "székek", 'seats' were already delimited territorial units of the "land of the Szekelys" (Terra Siculorum). The earliest surviving documents mention the land of the Sepsi Szekely in 1224 and then Sepsi Seat in 1252. After that, the names of Kézdi-and Orbai-, Udvarhely-, Maros-, Csík-, and then the Aranyos Seats founded between 1260-1272 were recorded in the certificates (Egyed 2014).
Regional Statistics, 2024
Energy poverty is a complex, multidimen-sional problem that affects people’s quality of life. Its... more Energy poverty is a complex, multidimen-sional problem that affects people’s quality of life. Its study has become an important pillar of the public policy agenda and the literature in Latin America. Using the 10% indicator, this paper aimed to model the energy consumption of households in Argentina to estimate the energy expenditure of each and thus determine which households are in a situation of energy poverty. For the empirical analysis The authors used the 2017–2018 National Household Expenditure Survey of Argentina, and urban households in the interior of the province of Buenos Aires were selected as a case study. After characterizing the main energy consumption habits of the sample, energy poverty was assessed. The analysis shows that for the study period (2017–2018), a significant number of house-holds suffered from energy poverty; that is, they spent more than 10% of their income on energy expenditures. The findings indicate that the Demand Model is consistent, as the degree of adjustment is 0.1% in the demand for electricity and natural gas and 0.3% in the demand for liquefied petroleum gas. In addition, 462,143 households (28.3% of the sample analyzed) in the interior of the province of Buenos Aires experienced energy deprivation when considering the 10% indicator. On the other hand, by means of the 2M indicator, the results show that 518,686 households were in energy poverty (31.8% of the sample analyzed).
Regional Statistics, 2024
This study examines the development of stock market indices in the open and small economies of Ce... more This study examines the development of stock market indices in the open and small economies of Central-Eastern European (CEE) countries between 2008 Q1 and 2022 Q1. A panel vector autoregression model (PVAR) was estimated on a set of macrodata and time-variant closeness centralities to understand the role of network effects. The time variance of closeness was achieved through quarterly re-estimation of a minimum spanning tree graph, representing the entire set of European stock markets (market-network). The sample covers the major events of the Global Financial Crisis and Eurozone sovereign debt crisis of 2008 and 2012 and the Covid-19 pandemic after 2020. In this study, the authors estimated the development of stock market indices in relation to macro variables related to funding, foreign exchange, and profitability, which can affect the expectations about the discounted cash flows of publicly listed companies. However, stock market indices decrease if the European market network has a higher degree of synchronization, leading to the temporary emergence of financial contagions. The findings indicate that stock market indices primarily react to traditional macro variables in the short and medium term, but changes in the network’s shape can alter this process in the short term. These results underline the occurrence of cheaper-than-fundamental entry points for value-based investors in these markets due to such contagion-driven excessive decreases in share prices.
Regional Statistics, 2024
The automotive industry, being one of the largest industries worldwide, is a dominant and increas... more The automotive industry, being one of the largest industries worldwide, is a dominant and increasingly important sector across Europe. Due to the large foreign direct investment inflow from multinational automotive companies, it has special importance in the Central and Eastern European region. Owing to their sheer size, large-scale greenfield investment projects by multinational carmakers considerably affect macroeconomic output as well as regional social and economic development, including the housing market. This study explores whether a large-scale investment project can cause regional housing prices to deviate from national trends. Using a multivariate synthetic control method estimator, the authors identify the extent to which local house prices were influenced by the Mercedes-Benz car factory investment in Kecskemét, Hungary. The study compare the evolution of house prices in Kecskemét to a synthetic control of other county seats. The results suggest that following the completion of the Mercedes factory, local house prices increased by 39 percentage points more between 2010 and 2017 compared to the counterfactual case. The estimated effect is significant and large in magnitude compared to the pseudo-effects based on spatial placebo tests. Several robustness analyses confirm this conclusion.
Regional Statistics, 2024
The outbreak of the Covid-19 pandemic primarily and directly affected health care and its backgro... more The outbreak of the Covid-19 pandemic primarily and directly affected health care and its background sector, the health care industry, whose development has become a national economic priority since the 2010s. The epidemic also necessitated quick and effective adaptation and immediate reactions in Hungary. One of these was the introduction of the Healthcare Industry Support Program (HISP) in 2020 with the aim of promoting effective protection against epidemics. The main aim of this study is to reveal the major differences in the characteristics of the enterprises supported in the different periods of the HISP with particular regard to their Industry 4.0 technologies and spatial pattern in connection with the Hungarian industry. Based on different data sources and empirical research (questionnaire survey), the authors found that there are significant differences between the subsidized enterprises in the two main support periods. Although technologybased developments came to the fore in the age of the pandemic, this has not resulted in the widespread spread of Industry 4.0 technologies in the Hungarian health care industry, whose spatial pattern was closely connected to the Hungarian industry.
Regional Statistics, 2024
This study explores the spatial and economic shifts in Slovakia over the past three decades in th... more This study explores the spatial and economic shifts in Slovakia over the past three decades in the spatial organization of industrial economic activities. The economic industrial complexity approach is employed to examine the impact of market forces and historical legacies on the crash of the centrally controlled spatial equity organization of jobs and industries and the shift to a more uneven economic landscape. A long time series of data spanning more than 30 years in Slovakia revealed how the artificial territorial organization of job creation policies in each district, enabled by central state planning, has gradually disintegrated. The results display significant spatial divergence and inequality between the capital city and the rest of the country, as well as between urban and rural areas. Two contrasting cases of Bratislava and Košice, the two largest cities in the country, show different spatial relationships with their surrounding regions, explainable using backwash and spread effects. Since spatial and sectoral dynamics are interconnected, spatial shifts and industrial change occurred together. The emergence of creative and knowledge-based economic activities took place against the backdrop of old industrial policies. Košice, the second largest city in Slovakia, faces growing intraregional disparities, so it is worth examining at a micro level how its sectoral trajectory has shifted away from heavy industry thanks to investment in information and communi-cation technology (ICT) and the successful European Capital of Culture project. The microscale of the city reveals patterns of the gradual occupation of territory by the creative sector, particularly by culture and arts, ICT firms and research and development (R&D) entities, exhibiting different locational behaviors.
Regional Statistics, 2024
Economic openness undoubtedly has income-increasing effects across all economies, but it has led ... more Economic openness undoubtedly has income-increasing effects across all economies, but it has led to increasing inequality within and across countries. India and its states are no exceptions in this regard. There have been many endogenous factors that justify the increasing growth trends in gross and per capita incomes in the postopenness phase. Human capital formation through spending on health and education heads has been one such endogenous factor. The present study aims to investigate the role of education and health expenditure on income in India’s sixteen major states/union territories (UTs) for the 1998–2019 period. By Johansen cointegra-tion analysis, it is found that there is a long-run association among education expen-diture, health expenditure and income in fourteen states: Andhra Pradesh, Assam, Bihar, Gujarat, Haryana, Karnataka, Kerala, Madhya Pradesh, Maharashtra, National Capital Territory (NCT) Delhi, Punjab, Rajasthan, Tamil Nadu and Uttar Pradesh. From vector error correction mechanism (VECM) estimation, the long-run causal relation jointly from education and health expenditure to income has been found in Assam, Bihar, Haryana, Maharashtra, NCT Delhi, and Rajasthan. Employing the Granger causality test in a vector auto-regressive (VAR) setup, mixed results were found for both unidirectional and bidirec-tional causality.
Regional Statistics, 2024
The European Green Capital Award (EGCA) has been given to cities that can serve as role models fo... more The European Green Capital Award (EGCA) has been given to cities that can serve as role models for other cities in responding to environmental challenges with innovative solutions and contributing to the development of more sustainable and healthier cities. This study examines 100 of the 110 cities that applied for the award by the round of 2024 based on quantitative data that could measure the environmental awareness of those cities. The variables were selected in line with the topics of the EGCA call for proposals. Exploratory data analysis (EDA) was used to reveal the differences between the two groups, finalists and applicants who were nonshortlisted. Based on Mann‒Whitney U tests and chi-square tests, the values of the finalists were convincingly more favorable for only 10 variables. To identify the variables with the strongest relationship with the outcome of the application, a logistic regression was performed after a dimension reduction carried out with multiple factor analysis (MFA). The model can be applied with high accuracy mainly in the category of nonshortlisted candidates (there are several erroneous estimates for the winners), which suggests that other, nonmeasurable criteria are also influencing factors. The model, with some limitations, can also be used by cities that also want to compete in the future to assess their chances before submitting their application.
Regional Statistics, 2024
The effects of urbanisation in developing countries like India call for measuring regional dispar... more The effects of urbanisation in developing countries like India call for measuring regional disparities in Quality of Life (QOL). Though there exists, several internationally recognized indexes to assess QOL, a regional QOL assessment is yet not studied in India. The study attempts to develop such an assessment framework for measuring objective QOL at the regional level using a composite index, taking the case of Kozhikode, Kerala, India, as a case example. Firstly, a set of 19 variables under five domains of QOL was arrived at through several steps of screening processes, refinement from a master list, and a final expert opinion survey. Secondly, a Composite Quality of Life Index (CQOLI) was formulated by conducting a series of statistical analyses on the data set, including Principal Component Analysis (PCA). Thirdly, a spatial analysis of QOL of the study area was conducted by mapping the CQOLI scores to understand the pattern and analyse inequities. Accordingly, the spatial study units were grouped into High, Medium, and Low QOL. Out of the total settlements, it was found that 20% fell in high QOL, 46.25% in medium QOL, and 33.75% in low QOL. The pattern was spatially analysed based on the topographical divisions, namely lowlands, midlands, and highlands, and it was found that the QOL decreased from lowlands towards highlands. Finally, solutions and strategies which may be used as policy directives were proposed for each QOL group. The insights from the study are helpful for planners and decision-makers while implementing interventions in the study region. The methodology adopted here can be replicated in other regions of similar scale by altering the variables suited to the context.
Regional Statistics, 2024
Implicit weighting in the normalization of aggregate variables generates distorted composite indi... more Implicit weighting in the normalization of aggregate variables generates distorted composite indices (CI). This distortion is associated with the uneven range of each distribution, the fact that the maximum and minimum values differ from one variable to another, and the asymmetry of each variable. Controlling implicit weighting is a pending issue. All normalization procedures reviewed in this research counteract the influence of implicit weighting only partially. The balanced standardization proposed in this study achieves the triple purpose of simultaneously matching the ranges between variables, matching the maximum and minimum between them, and controlling the asymmetry in each distribution. This new procedure neutralizes implicit weighting in the cross-sectional or longitudinal aggregation of variables. The variables of educational backwardness in Mexico illustrate this procedure. The methodological proposal of this research is applicable to any subject where space-time normalization is necessary.
Regional Statistics, 2024
The recent health crisis and Russia-Ukraine conflict have had an impact on countries around the w... more The recent health crisis and Russia-Ukraine conflict have had an impact on countries around the world. Foreign exchange rate markets have been considerably influenced. The author examine the dynamic interaction over crises between geopolitical risk (GPR) and major exchange rate markets. The asymmetric impact of geopolitical risk and major exchange rates was discovered utilizing a novel time-varying Granger causality approach. The sample includes noteworthy occurrences such as Covid-19 and the ongoing conflict between Russia and Ukraine. The empirical findings uncover bidirectional causality, with geopolitical risks significantly influencing exchange rate markets during Covid-19 and the beginning of the Russia-Ukraine war. However, this phenomenon became weaker as the Russia-Ukraine war continued, which could show that GPR and exchange rate markets were not linked during the Russia-Ukraine war. This research has important implications that may be advantageous to forex investors, helping them make a variety of investment decisions in such turbulent times. Certain policy choices may be advantageous to banks, global organizations, institutional investors, and policy-makers.
Regional Statistics, 2024
This paper investigates the impact of internal migration on the well-being of migrants and their ... more This paper investigates the impact of internal migration on the well-being of migrants and their children in destination areas in Vietnam using the 2015 National Internal Migration Survey. Vietnam is a transition economy with rapid industrialization, which has booted the flow of migration from rural to urban areas. To rule out time-invariant factors, which may affect the estimation results, the model regressions control for district-level fixed effects, industry-level fixed effects, and age fixed effects. The authors show that migrants work longer and are less likely to have an employment contract and health insurance than nonmigrants. Although migrants are more likely to drink alcohol, they do not seem to be heavy drinkers. Meanwhile, migrant children aged 5–18 are 6.5% more likely to drop out of school than nonmigrant children. Long-term migrants have better working conditions, such as shorter working hours, verbal employment contracts, and social and health insurance. Female migrants are less likely to find a job than male migrants, and educated migrants find it easier to get a job and earn better income than uneducated migrants. The findings suggest that governments should design specific policies for internal migrants, such as integration and social protection measures, to help them overcome the difficulties they encounter.
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Papers by Regional Statistics
Highlights:
• Companies from financial centers have better access to bank credit.
• The concentration of the banking system increases the disparities between the core and periphery.
• There is financial center bias in the equity markets in most European countries.
• Financial center bias is negatively linked to the computerization of financial markets.
work, the present paper provides evidence that spatial dependence appears significantly in the cost pass-through behaviour of firms. This suggests that, on the one hand, the detected symmetric cost pass-through may cover the properties of the competition. On the other hand, competition authorities should consider spatial dependencies when preparing court-case decisions to avoid verdicts arising from presumably spurious analysis results.