From the existing literature, there is no consensus on the effects of financial integration on economic growth. The studies have mostly focused on country samples without taking into account country heterogeneity, or have been limited to a causality study. This paper examines the effects of international financial integration on economic growth in seven West African Economic and Monetary Union’s countries (WAEMU)[i], over the period 1980 - 2019. Methodologically, the study applies heterogeneous panel techniques taking into account inter-individual dependence (MG, CCEMG and AMG). The results show that the stock of external debt and the opening of the capital account negatively affect long-term economic growth in the WAEMU region. The country analysis confirms the panel results for Benin, Burkina Faso and Mali. Sectoral misallocation of external capital could be a plausible explanation. The economies of WAEMU countries are mostly dominated by the service sector, which contributes more to their GDP than the productive sectors, i.e. agriculture and industry. While the agricultural sector, which employs a large part of the active population, is still traditional and does not benefit from capital inflows, the industrial sector is still embryonic. [i] Benin, Burkina Faso, Côte d'Ivoire, Guinea-Bissau, Mali, Niger, Senegal and Togo. In this study, we have removed Guinea-Bissau due to lack of data over a large part of the period.
{"title":"Effects of International Financial Integration on Economic Growth in Developing Countries: Heterogeneous Panel Evidence from Seven West African Countries","authors":"Lamissa Barro, B. Bassolet","doi":"10.47743/saeb-2023-0018","DOIUrl":"https://doi.org/10.47743/saeb-2023-0018","url":null,"abstract":"From the existing literature, there is no consensus on the effects of financial integration on economic growth. The studies have mostly focused on country samples without taking into account country heterogeneity, or have been limited to a causality study. This paper examines the effects of international financial integration on economic growth in seven West African Economic and Monetary Union’s countries (WAEMU)[i], over the period 1980 - 2019. Methodologically, the study applies heterogeneous panel techniques taking into account inter-individual dependence (MG, CCEMG and AMG). The results show that the stock of external debt and the opening of the capital account negatively affect long-term economic growth in the WAEMU region. The country analysis confirms the panel results for Benin, Burkina Faso and Mali. Sectoral misallocation of external capital could be a plausible explanation. The economies of WAEMU countries are mostly dominated by the service sector, which contributes more to their GDP than the productive sectors, i.e. agriculture and industry. While the agricultural sector, which employs a large part of the active population, is still traditional and does not benefit from capital inflows, the industrial sector is still embryonic.\u0000 \u0000[i] Benin, Burkina Faso, Côte d'Ivoire, Guinea-Bissau, Mali, Niger, Senegal and Togo. In this study, we have removed Guinea-Bissau due to lack of data over a large part of the period.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46274511","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}
Bubbles in asset prices have attracted the attention of economists for centuries. Extreme increases in asset prices, followed by their sudden decline, create a turbulent effect on the economy and even invite crises in time. For this reason, some measurement techniques have been employed to investigate the price bubbles that may occur. This study explores the possible speculative price bubbles of Bitcoin, Ethereum, and Binance Coin cryptocurrencies, compares them with the pre-and post-COVID-19 period, and examines asymmetric causality relationships between variables. Therefore, we analyzed the price bubbles of these cryptocurrencies using the closing price for daily data between 16.01.2018 and 31.12.2021 by the Supremum Augmented Dickey-Fuller (SADF) and the Hatemi-J (2012) asymmetric causality test. In this context, 1446 observations, 723 of which were before COVID-19 and 723 after COVID-19, were employed in the study. Looking at the SADF analysis results, we detected 103 price bubbles before COVID-19 for the three cryptocurrencies, while we determined 599 price bubbles after COVID-19. The common finding in the asymmetric causality test results is that there is a causality relationship between the negative shocks faced by one cryptocurrency and the positive shocks faced by the other cryptocurrencies.
{"title":"Testing the Price Bubbles in Cryptocurrencies using Sequential Augmented Dickey-Fuller (SADF) Test Procedures: A Comparison for Before and After COVID-19","authors":"A. Çelik, Çağrı Ulu","doi":"10.47743/saeb-2023-0005","DOIUrl":"https://doi.org/10.47743/saeb-2023-0005","url":null,"abstract":"Bubbles in asset prices have attracted the attention of economists for centuries. Extreme increases in asset prices, followed by their sudden decline, create a turbulent effect on the economy and even invite crises in time. For this reason, some measurement techniques have been employed to investigate the price bubbles that may occur. This study explores the possible speculative price bubbles of Bitcoin, Ethereum, and Binance Coin cryptocurrencies, compares them with the pre-and post-COVID-19 period, and examines asymmetric causality relationships between variables. Therefore, we analyzed the price bubbles of these cryptocurrencies using the closing price for daily data between 16.01.2018 and 31.12.2021 by the Supremum Augmented Dickey-Fuller (SADF) and the Hatemi-J (2012) asymmetric causality test. In this context, 1446 observations, 723 of which were before COVID-19 and 723 after COVID-19, were employed in the study. Looking at the SADF analysis results, we detected 103 price bubbles before COVID-19 for the three cryptocurrencies, while we determined 599 price bubbles after COVID-19. The common finding in the asymmetric causality test results is that there is a causality relationship between the negative shocks faced by one cryptocurrency and the positive shocks faced by the other cryptocurrencies.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42036068","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}
Bosede Ngozi Adeleye, B. U. Achugamonu, T. George, M. Ogbari, Oluyomi Ola-David
Towards achieving the 2030 United Nations Sustainable Development Goals, this study revisits the information and communication technology (ICT) leapfrogging hypothesis of Steinmueller (2001), and Fong (2009) to expand the literature by testing its relevance in the labour force-growth dynamics in Asia. To achieve this, the study addresses four objectives: (i) test the ICT leapfrogging hypothesis; (ii) investigate the growth-enhancing impact of labour; (iii) examine whether ICT enhances or distorts the productivity of labour on economic growth; and (iv) if these effects differ by economic development. The study uses an unbalanced panel data on 81 countries located in East Asia and Pacific (EAP) and Europe and Central Asia (ECA) from 2010 to 2019. Two estimation techniques, namely panel spatial correlation consistent fixed effects (PSCC-FE) and random effects instrumental variables two-stage least squares (RE-IV2SLS), are deployed. To appraise if the impact differs by economic development, the study engages income group analysis. Among other findings: the leapfrogging hypothesis holds; labour is a significant predictor of economic growth; mobile phones usage is a more potent ICT indicator with more leapfrogging potentials relative to fixed telephones subscription; the net effect of labour on growth is mostly positive in the mobile phones’ models.
{"title":"ICT Leapfrogging Amidst Labour Force-Economic Growth Nexus in EAP and ECA Regions","authors":"Bosede Ngozi Adeleye, B. U. Achugamonu, T. George, M. Ogbari, Oluyomi Ola-David","doi":"10.47743/saeb-2023-0004","DOIUrl":"https://doi.org/10.47743/saeb-2023-0004","url":null,"abstract":"Towards achieving the 2030 United Nations Sustainable Development Goals, this study revisits the information and communication technology (ICT) leapfrogging hypothesis of Steinmueller (2001), and Fong (2009) to expand the literature by testing its relevance in the labour force-growth dynamics in Asia. To achieve this, the study addresses four objectives: (i) test the ICT leapfrogging hypothesis; (ii) investigate the growth-enhancing impact of labour; (iii) examine whether ICT enhances or distorts the productivity of labour on economic growth; and (iv) if these effects differ by economic development. The study uses an unbalanced panel data on 81 countries located in East Asia and Pacific (EAP) and Europe and Central Asia (ECA) from 2010 to 2019. Two estimation techniques, namely panel spatial correlation consistent fixed effects (PSCC-FE) and random effects instrumental variables two-stage least squares (RE-IV2SLS), are deployed. To appraise if the impact differs by economic development, the study engages income group analysis. Among other findings: the leapfrogging hypothesis holds; labour is a significant predictor of economic growth; mobile phones usage is a more potent ICT indicator with more leapfrogging potentials relative to fixed telephones subscription; the net effect of labour on growth is mostly positive in the mobile phones’ models.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45191231","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 research population of this study consists of Australia, Azerbaijan, Egypt, Brazil, Chile, Canada, Hungary, Pakistan, India, Ukraine and the United Kingdom. For these countries; T, the relationship between Exchange Rate Index (exc), Real Interest Rate (int) and Consumer Price Index (cpi) variables were examined. Data from 2000Q1 to 2021Q3 were used in the study. The data are taken from the IMF's data bank. Analysis was done in R-Studio. Wo Seasonality Test, Augmented Dickey-Fuller Test, Linear Granger Causality Analysis and Nonlinear Granger Causality Analysis were used to investigate the relationship between variables. The theory claims that there is causality in both directions between exchange rate, interest rate and inflation. In the study, the relationship between these variables was investigated with linear and nonlinear causality tests. It is thought that the empirical results that contradict the theory are caused by the development levels of the countries, their macroeconomic structures, the applied fiscal and monetary policy instruments, the conjuncture and the analysis methods. The study aims to investigate these claims. For this reason, the development levels, sociocultural and socioeconomic structures of the selected countries were requested to be different. In addition, two different test methods, linear and non-linear, were preferred for the causality relationship. It was observed that the selected analysis methods significantly affected the results. Linear causality analysis results are closer to theoretical implications. However, the level of development of the countries does not have a significant effect on the relationship between the variables.
{"title":"Linear and Nonlinear Relationship Between Real Exchange Rate, Real Interest Rate and Consumer Price Index: An Empirical Application for Countries with Different Levels of Development","authors":"Ersın Sünbül","doi":"10.47743/saeb-2023-0008","DOIUrl":"https://doi.org/10.47743/saeb-2023-0008","url":null,"abstract":"The research population of this study consists of Australia, Azerbaijan, Egypt, Brazil, Chile, Canada, Hungary, Pakistan, India, Ukraine and the United Kingdom. For these countries; T, the relationship between Exchange Rate Index (exc), Real Interest Rate (int) and Consumer Price Index (cpi) variables were examined. Data from 2000Q1 to 2021Q3 were used in the study. The data are taken from the IMF's data bank. Analysis was done in R-Studio. Wo Seasonality Test, Augmented Dickey-Fuller Test, Linear Granger Causality Analysis and Nonlinear Granger Causality Analysis were used to investigate the relationship between variables. The theory claims that there is causality in both directions between exchange rate, interest rate and inflation. In the study, the relationship between these variables was investigated with linear and nonlinear causality tests. It is thought that the empirical results that contradict the theory are caused by the development levels of the countries, their macroeconomic structures, the applied fiscal and monetary policy instruments, the conjuncture and the analysis methods. The study aims to investigate these claims. For this reason, the development levels, sociocultural and socioeconomic structures of the selected countries were requested to be different. In addition, two different test methods, linear and non-linear, were preferred for the causality relationship. It was observed that the selected analysis methods significantly affected the results. Linear causality analysis results are closer to theoretical implications. However, the level of development of the countries does not have a significant effect on the relationship between the variables.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43221822","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}
Composite indices have become a popular tool for providing a quantitative, simplified, and visualized representation of complex phenomena. An example of such is the Human Development Index (HDI) which ranks countries by their level of development. The primary limitation of the HDI is its narrow scope, which hinders its effectiveness at explaining why some nations are more developed than others. The discussion as to why some nations are more developed than others goes back as far as the 14th century, where Ibn Khaldun developed a theory which aims to explain why civilizations rise and fall. Some of the hypotheses which seek to answer this question point to the importance of economic freedoms, absence of corruption, high investment in human capital, and the importance of institutions etc. to development. One hypothesis which has not been properly studied regards the culpability of individual and institutional behavior. The purpose of this study is to introduce a composite measure of the development hindering behavior of individuals and institutions, i.e., the Bad Behavior Index (BBI). The methodology of this study is influenced by the Mazziotta & Pareto framework for composite indices. The index weights have been computed by integrating expert opinion with the Fuzzy Analytic Hierarchy Process (FAHP). The findings of this study suggest that African countries engage in the highest level of bad behavior, which subsequently leads to their poor socio-economic development, whereas Northern countries engage in the least level of bad behavior. The study also finds that the most important drivers for socio-economic development are low levels of corruption, high levels of knowledge creation, strict application of the rule of law, high levels of social cohesion, and high levels of political stability.
{"title":"The 'Bad Behavior Index': A Composite Measure of the Development Hindering Behavior of Individuals and Institutions","authors":"Mohammad Tariq Al Fozaie","doi":"10.47743/saeb-2023-0003","DOIUrl":"https://doi.org/10.47743/saeb-2023-0003","url":null,"abstract":"Composite indices have become a popular tool for providing a quantitative, simplified, and visualized representation of complex phenomena. An example of such is the Human Development Index (HDI) which ranks countries by their level of development. The primary limitation of the HDI is its narrow scope, which hinders its effectiveness at explaining why some nations are more developed than others. The discussion as to why some nations are more developed than others goes back as far as the 14th century, where Ibn Khaldun developed a theory which aims to explain why civilizations rise and fall. Some of the hypotheses which seek to answer this question point to the importance of economic freedoms, absence of corruption, high investment in human capital, and the importance of institutions etc. to development. One hypothesis which has not been properly studied regards the culpability of individual and institutional behavior. The purpose of this study is to introduce a composite measure of the development hindering behavior of individuals and institutions, i.e., the Bad Behavior Index (BBI). The methodology of this study is influenced by the Mazziotta & Pareto framework for composite indices. The index weights have been computed by integrating expert opinion with the Fuzzy Analytic Hierarchy Process (FAHP). The findings of this study suggest that African countries engage in the highest level of bad behavior, which subsequently leads to their poor socio-economic development, whereas Northern countries engage in the least level of bad behavior. The study also finds that the most important drivers for socio-economic development are low levels of corruption, high levels of knowledge creation, strict application of the rule of law, high levels of social cohesion, and high levels of political stability.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42086091","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 examined the impact of foreign direct investment on economic growth in BRICS using fixed effects, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). Panel data ranging from 1991 to 2019 was used for the purposes of this study. The same study also explored whether financial sector and human capital development are necessary absorption capacities that enhance economic growth in BRICS. To a larger extent, foreign direct investment had a negative impact on economic growth in BRICS, consistent with the dependency theory. Financial development was also found to be the channel through which economic growth is enhanced by foreign direct investment. Although the influence was observed to be non-significantly negative, human capital development improved the influence of foreign direct investment on economic growth. BRICS authorities are therefore urged to implement human capital and financial development enhancement policies to ensure significant foreign direct investment’s positive influence on economic growth.
{"title":"Foreign Direct Investment-Growth Nexus in BRICS: How Relevant are the Absorption Capacities?","authors":"Kunofiwa Tsaurai","doi":"10.47743/saeb-2023-0006","DOIUrl":"https://doi.org/10.47743/saeb-2023-0006","url":null,"abstract":"This study examined the impact of foreign direct investment on economic growth in BRICS using fixed effects, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). Panel data ranging from 1991 to 2019 was used for the purposes of this study. The same study also explored whether financial sector and human capital development are necessary absorption capacities that enhance economic growth in BRICS. To a larger extent, foreign direct investment had a negative impact on economic growth in BRICS, consistent with the dependency theory. Financial development was also found to be the channel through which economic growth is enhanced by foreign direct investment. Although the influence was observed to be non-significantly negative, human capital development improved the influence of foreign direct investment on economic growth. BRICS authorities are therefore urged to implement human capital and financial development enhancement policies to ensure significant foreign direct investment’s positive influence on economic growth.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46102916","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 article aims to model the relationship between the size of the shadow economy and the most important government expenditures respectively social protection, health, and education, using nonlinear approaches. We applied four different Machine Learning models, namely Support Vector Regression, Neural Networks, Random Forest, and XGBoost on a cross-sectional dataset of 28 EU states between 1995 and 2020. Our goal is to calibrate an algorithm that can explain the variance of shadow economy size better than a linear model. Moreover, the most performant model has been used to predict the shadow economy size for over 30,000 simulated combinations of expenses in order to outline some possible inflection points after which government expenditures become counterproductive. Our findings suggest that ML algorithms outperform linear regression in terms of R-squared and root mean squared error and that social protection spending is the most important determinant of shadow economy size. Further to our analysis for the 28 EU states, between 1995 and 2020, the results suggest that the lowest size of shadow economy occurs when social protection expenses are greater than 20% of GDP, health expenses are greater than 6% of GDP, and education expenses range between 6% and 8% of GDP. To the best of the authors' knowledge, this is the first paper that used ML to model shadow economy and its determinants (i.e., government expenditures). We propose an easy-to-replicate methodology that can be developed in future research.
{"title":"Modelling the Non-Linear Dependencies between Government Expenditures and Shadow Economy Using Data-Driven Approaches","authors":"Codrut-Florin Ivascu, Sorina Emanuela Ștefoni","doi":"10.47743/saeb-2023-0001","DOIUrl":"https://doi.org/10.47743/saeb-2023-0001","url":null,"abstract":"This article aims to model the relationship between the size of the shadow economy and the most important government expenditures respectively social protection, health, and education, using nonlinear approaches. We applied four different Machine Learning models, namely Support Vector Regression, Neural Networks, Random Forest, and XGBoost on a cross-sectional dataset of 28 EU states between 1995 and 2020. Our goal is to calibrate an algorithm that can explain the variance of shadow economy size better than a linear model. Moreover, the most performant model has been used to predict the shadow economy size for over 30,000 simulated combinations of expenses in order to outline some possible inflection points after which government expenditures become counterproductive. Our findings suggest that ML algorithms outperform linear regression in terms of R-squared and root mean squared error and that social protection spending is the most important determinant of shadow economy size. Further to our analysis for the 28 EU states, between 1995 and 2020, the results suggest that the lowest size of shadow economy occurs when social protection expenses are greater than 20% of GDP, health expenses are greater than 6% of GDP, and education expenses range between 6% and 8% of GDP. To the best of the authors' knowledge, this is the first paper that used ML to model shadow economy and its determinants (i.e., government expenditures). We propose an easy-to-replicate methodology that can be developed in future research.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46465630","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 capital structure has been extensively analysed in the empirical literature. Despite of the great contribution of the technological industry to the global economy, little research has been conducted regarding corporate finance of ICT firms. Moreover, the previous literature barely considers the effect of macroeconomic variables on financial decisions, focusing much more on internal determinants, such as cash flow, firm’s size or growth opportunities. The objective of this work is to reduce this gap by disentangling the reasons behind the financial decisions of technological firms. The sample included 1,510 public ICT firms from 23 countries over the period 2004 – 2019 (17,342 observations). The variables used in this study are obtained from S&P Capital IQ, World Development Indicators, Main Science and Technology Indicators from OECD, and FMI dataset. The two-step system generalized method of moments (GMM) was used as methodology. Consistent with the extant literature, more profitable and liquid ICT firms and those with an increased non-debt tax shields are less leveraged. However, the companies which present higher risk, measured as volatility of EBIT, increase their use of debt financing. Contrary to the findings of many other studies, the analysis of a firm’s size and tangible assets shows non-conclusive results. Regarding macroeconomic determinants, only economic growth and foreign direct investment inflows were found to generate a positive effect on financial decisions of ICT firms. The findings of this work can be used to design and develop policies, measures, and facilitate mechanisms for optimal management of the financing decisions of ICT firms.
{"title":"The Empirical Study of the Impact of Firm- and Country-level Factors on Debt Financing Decisions of ICT Firms","authors":"Inna Alexeeva-Alexeev","doi":"10.47743/saeb-2023-0014","DOIUrl":"https://doi.org/10.47743/saeb-2023-0014","url":null,"abstract":"The capital structure has been extensively analysed in the empirical literature. Despite of the great contribution of the technological industry to the global economy, little research has been conducted regarding corporate finance of ICT firms. Moreover, the previous literature barely considers the effect of macroeconomic variables on financial decisions, focusing much more on internal determinants, such as cash flow, firm’s size or growth opportunities. The objective of this work is to reduce this gap by disentangling the reasons behind the financial decisions of technological firms. The sample included 1,510 public ICT firms from 23 countries over the period 2004 – 2019 (17,342 observations). The variables used in this study are obtained from S&P Capital IQ, World Development Indicators, Main Science and Technology Indicators from OECD, and FMI dataset. The two-step system generalized method of moments (GMM) was used as methodology. Consistent with the extant literature, more profitable and liquid ICT firms and those with an increased non-debt tax shields are less leveraged. However, the companies which present higher risk, measured as volatility of EBIT, increase their use of debt financing. Contrary to the findings of many other studies, the analysis of a firm’s size and tangible assets shows non-conclusive results. Regarding macroeconomic determinants, only economic growth and foreign direct investment inflows were found to generate a positive effect on financial decisions of ICT firms. The findings of this work can be used to design and develop policies, measures, and facilitate mechanisms for optimal management of the financing decisions of ICT firms.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43199691","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}
António Portugal Duarte, Fátima Sol Murta, Nuno Baetas da Silva, Beatriz Rodrigues Vieira
This paper analysis and compares the volatility of seven cryptocurrencies – Bitcoin, Dogecoin, Ethereum, BitcoinCash, Ripple, Stellar and Litecoin – to the volatility of seven centralized currencies – Yuan, Yen, Canadian Dollar, Brazilian Real, Swiss Franc, Euro and British Pound. We estimate GARCH models to analyze their volatility. The results point to a considerably high volatility of cryptocurrencies when compared to that of centralized currencies. Therefore, we conclude that cryptocurrencies still fall far short of fulfilling all the requirements to be considered as a currency, specifically regarding the functions of store of value and unit of account.
{"title":"Flip the Coin: Heads, Tails or Cryptocurrencies?","authors":"António Portugal Duarte, Fátima Sol Murta, Nuno Baetas da Silva, Beatriz Rodrigues Vieira","doi":"10.47743/saeb-2023-0013","DOIUrl":"https://doi.org/10.47743/saeb-2023-0013","url":null,"abstract":"This paper analysis and compares the volatility of seven cryptocurrencies – Bitcoin, Dogecoin, Ethereum, BitcoinCash, Ripple, Stellar and Litecoin – to the volatility of seven centralized currencies – Yuan, Yen, Canadian Dollar, Brazilian Real, Swiss Franc, Euro and British Pound. We estimate GARCH models to analyze their volatility. The results point to a considerably high volatility of cryptocurrencies when compared to that of centralized currencies. Therefore, we conclude that cryptocurrencies still fall far short of fulfilling all the requirements to be considered as a currency, specifically regarding the functions of store of value and unit of account.","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48832101","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}
A. Sirbu, Andreea IACOBUȚĂ-MIHĂIȚĂ, Mircea Asandului, M. Brezuleanu
Are people more likely to be satisfied with their lives if they had freedom from regulations, if they had the ability to trade freely internationally? In light of the demographic aging phenomenon we are facing, the present study analyzes the relationship between economic freedom and life satisfaction among European older adults. In order to do so, we are using data from the European Health, Ageing, and Retirement Survey and Economic Freedom of the World. By using the ordered logit regression method, we estimated different models to identify how sub-indicators of economic freedom affect the subjective well-being. According to the findings, the quality of the institutions that define the legal system and establish rules for the protection of private property and sound monetary policy have a positive effect on subjective well-being. On the other hand, openness to international trade has a negative effect and government and regulation doesn’t show any significance.
{"title":"Effects of Economic Freedom on Subjective Well-Being","authors":"A. Sirbu, Andreea IACOBUȚĂ-MIHĂIȚĂ, Mircea Asandului, M. Brezuleanu","doi":"10.47743/saeb-2023-0015","DOIUrl":"https://doi.org/10.47743/saeb-2023-0015","url":null,"abstract":"Are people more likely to be satisfied with their lives if they had freedom from regulations, if they had the ability to trade freely internationally? In light of the demographic aging phenomenon we are facing, the present study analyzes the relationship between economic freedom and life satisfaction among European older adults. In order to do so, we are using data from the European Health, Ageing, and Retirement Survey and Economic Freedom of the World. By using the ordered logit regression method, we estimated different models to identify how sub-indicators of economic freedom affect the subjective well-being. According to the findings, the quality of the institutions that define the legal system and establish rules for the protection of private property and sound monetary policy have a positive effect on subjective well-being. On the other hand, openness to international trade has a negative effect and government and regulation doesn’t show any significance.\u0000 ","PeriodicalId":43189,"journal":{"name":"Scientific Annals of Economics and Business","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43158712","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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