Scientific Annals of Economics and Business

Testing the Price Bubbles in Cryptocurrencies using Sequential Augmented Dickey-Fuller (SADF) Test Procedures: A Comparison for Before and After COVID-19

2022-08-04T10:45:05+00:00

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.

ICT Leapfrogging Amidst Labour Force-Economic Growth Nexus in EAP and ECA Regions

2022-09-26T09:12:26+00:00

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.

Foreign Direct Investment-Growth Nexus in BRICS: How Relevant are the Absorption Capacities?

2022-07-21T08:40:01+00:00

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.

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

2023-02-28T19:26:26+00:00

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.

How to Analyze the Association between Two Categorical Variables Based on Census Data with a High Level of Nonresponse

2023-03-02T06:34:05+00:00

Statistical surveys are often used in shaping managerial policy and practice. In this paper we study, how to analyze the association between two categorical variables based on census data with a high level of nonresponse. The purpose is to discuss the suggested approach to the investigation. We used the census data from the survey executed at one Slovak University for testing the new process. The proposed process offers the methods of analysis of the association between two categorical variables based on pseudo-population estimated from the census data with a high level of nonresponse. We recommend using the process in the surveys in which the costs of survey execution by the census are practically not different from sample survey costs, and the connections to all units of the population are available.

Effects of International Financial Integration on Economic Growth in Developing Countries: Heterogeneous Panel Evidence from Seven West African Countries

2023-02-04T11:25:12+00:00

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.

Modelling the Non-Linear Dependencies between Government Expenditures and Shadow Economy Using Data-Driven Approaches

2022-08-04T09:55:20+00:00

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.

The 'Bad Behavior Index': A Composite Measure of the Development Hindering Behavior of Individuals and Institutions

2023-01-17T21:06:25+00:00

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.