Political Stability Index Research Articles

Tourism and uncertainty: a machine learning approach

ABSTRACT In this paper, we attempt to create a unique forecasting model to forecast out-of-sample the tourism demand in 24 European Union countries. The initial dataset included 34 relevant variables of annual frequency that span the period from 2010 to 2020 for 40 countries. A data prefiltering process resulted in a final set of 17 relevant variables for 24 countries. Additionally, in the effort to investigate the impact of uncertainty on international tourism, apart from the traditional factors that affect tourism, we also include variables that measure various forms of uncertainty: we use the World Pandemic Uncertainty (WPU) Index, the Global CBOE Volatility Index, the Political Globalisation Index, the Economic Globalisation Index, and the Political Stability Index. In the empirical part of our research, we employ and compare in terms of their forecasting accuracy a set of six state-of-the-art machine learning algorithms, the Support Vector Regression with both a linear and an RBF kernel, the Random Forests, the Decision Trees, the KNN, and gradient-boosting trees. The results show that the Gradient-Boosting Trees algorithm outperforms the other five models providing the most accurate forecasts with a MAPE of 0.10% and 1.36% in the training and the out-of-sample tests, respectively.

Does Political Stability Matter to the Profitability of Banks?

This study examines the impact of net interest margin, non-interest income, non-performing loans, and Political Stability Index on the banks’ profitability regarding return on assets in developing Asian countries, focusing on how political stability affects the bank’s profitability. The secondary data from 14 developing countries used in this study are collected from the World Bank and World Financial Studies Report. The dataset includes 154 data points spanning from 2012 to 2022, focusing on 14 underdeveloped countries of Asia. Exploratory and analytical research designs are utilized. Data are analyzed by using EViews 12. Econometric tools such as descriptive statistics, correlation analysis, panel unit root testing, Fisher-Johnsen combined co-integration test, panel vector error correction model, and Wald test investigate the relationship between response and predictor variables. The net interest margin, non-interest income, non-performing loan, and Political Stability Index are jointly integrated to determine the bank’s profit of developing countries of the Asia continent. Interest margin, non-interest revenue, non-performing loans, and the Political Stability Index all show a 38.6 percent variance in bank profit. It has been discovered that for every unit that rises in net interest margin and Political Stability Index, the bank profitability of developing Asian countries increases by 0.4867 and 0.2221 percent, respectively. Non-interest income has little bearing on the profitability of banks. Meanwhile, non-interest income exhibits minimal influence, suggesting a need for a strategic focus on interest margin enhancement and fostering political stability to optimize banking sector profitability in the region.

The influence of personal and economic oppression on a country's corruption levels worldwide

This empirical research study endeavors to analyze the indirect association between oppression and corruption in 147 nations around the globe to answer one question: "Why does oppression drive corruption in many nations?" The author used secondary data from two different resources. The first source is the Corruption Perception Index (CPI), created by Transparency International (TI) in 2020, and the Human Freedom Index (HFI), co-published by the Cato Institute. In addition, the second source is the Political Stability Index in 2020 to test the three research hypotheses using the R-square, and Anova shows that the model is personal and economic oppression explains 53.5 percent of the variance. In addition, the Weighted Least Squares Regression Analyses imply that there is a positive and meaningful connection between personal oppression (β = 3.028, p < 0.000) and corruption and economic oppression and corruption (5.203, p < 0.000). This study's findings confirmed the theoretical and conceptual relationship between oppression and bribery and identified personal and economic oppression factors as the leading causes of corruption in many countries. The study findings also contribute to the literature and the industry as well. Theoretically, the study results help researchers to understand why oppression causes corruption at the country level. Practically, the study results help policymakers, educators, and international business planners to consider roots when making successful strategic decisions in the era of the globalized world. The author also discussed the research limitations and practical and theoretical implications.

Effect of Ukraine’s public debt management on its macroeconomic development: VAR modeling

One of the tools of economic policy of any country is efficient public debt management, which influences and determines the dynamics of key macroeconomic indicators. The study aims to assess how public debt management affects Ukraine’s macroeconomic development. The analyzed period includes data of 2015–2021. Econometric modeling is used to establish the existence of causal relationships between the dynamics of public debt and changes in key macroeconomic indicators using the Granger causality test and VAR (Vector Autoregression) model. The obtained results demonstrate that during the study period, the strongest links existed between the public debt and GDP, debt servicing and Ukraine’s total state budget expenditures, public debt and consumer price index, real effective exchange rate index of the hryvnia to the US dollar, and political stability index. At the same time, the calculations proved that public debt does not have a significant impact on foreign direct investment and the level of imports of goods and services. The proposed model allows for forecasts for future periods and can be used in developing public debt management policy.

Quality of Government as an Attracting Factor of FDI - Evidence from Chosen Southeastern Europe Countries

This paper aims to examine the indicators of the quality of government of selected countries in South-Eastern Europe, which significantly influence the attractiveness of foreign direct investment. With the aim of quantifying the influence of certain factors on FDI, Montenegro, Serbia, Bosnia and Herzegovina, Romania, Bulgaria, Croatia, Albania and Northern Macedonia are included as the selected countries of the region, with the period of analysis limited to the period from 2007 to 2021. The results of the empirical analysis of the influence of the factors have shown that the factors referred to as the Rule of Law Index, Government Efficiency Index, Public Administration Efficiency Index and Political Stability Index have a significant and positive influence on the attractiveness of the country for foreign investors, while some other factors such as the cost of starting a new business have a negative influence on the country's attractiveness.

Interconnections assessment of banking capitalization with macroeconomic stability, including corruption and shadow economy

The research focuses on bank capitalization and macroeconomic stability, including corruption and the shadow economy. A well-capitalized banking system and a low corruption level are important for maintaining macroeconomic stability and reducing the size of the shadow economy. The paper is aimed at assessing the relationship between bank capitalization and macroeconomic stability, which includes corruption and shadow economy through canonical analysis. The research is conducted on the basis of financial and economic reporting of 35 countries with different levels of socio-economic development during 2010–2021 based on data from the World Bank and the European Central Bank. The main input blocks macroeconomic stability – corruption – shadow economy are characterized. During the research, the following tools were used: – methods of grouping, analysis and comparison in determining the characteristics of the elements of the chain «level of capitalization of the banking system – macroeconomic stability – corruption – shadow economy»; – factor analysis by applying the method of principal components in the selection of statistically significant indicators of the bank capitalization level and macroeconomic stability. The quantitative assessment of the bank capitalization level revealed the following dependencies: there is a strong correlation between return on assets and the level of non-performing loans, return on assets and return on equity. Using the principal components method, the following statistically significant indicators of macroeconomic stability were identified: GDP, Gini index, corruption perception index, corruption control index, and political stability index. Research, based on the canonical analysis, determined that 71.1% of changes in macroeconomic stability indicators are explained by fluctuations in the level of bank capitalization. The level of non-performing loans has a negative impact on macroeconomic stability, while the volatility of return on assets and return on equity has a greater positive impact on the development of the country's economy. The obtained results can be used by banks in the development of their resource and management policies, in the analysis of the volatility of capitalization level, by state bodies in the development of national policies of the country's economic development.

An Analysis of Correlations between Institutional Governance and Economic Development in Zimbabwe

Abstract The main focus of this study was to analyse the correlations between institutional governance and economic development using annual time series data covering the period 1996 to 2019. Since there has not been much attention given to the role of institutional governance in facilitating the economic recovery in Zimbabwe, the economy has failed to register sustainable economic growth post-2000. To give an insight into the major variable excluded in the formulation of national policies, an econometric Pearson correlation model for correlations between institutional governance and economic development was applied. Economic development was measured using GDP per capita growth while institutional governance was measured by four variables, namely, the rule of law index, voice and accountability index, regulatory quality index, and political stability index. The empirical outcome reveals a strong positive correlation between institutional governance variables and GDP per capita growth. Hence, this study recommends that Parliament should exercise its powers to hold public institutions and all other state organs accountable for respecting the rule of law and maintaining political stability; macro-stabilisation institutions should implement sound economic policies; and there should be an immediate response by institutions to curb illicit economic operations to minimise economic leakages. These reforms need institutional political independence to be implemented and can facilitate economic development. Therefore, instead of targeting only macroeconomic indicators as a way out to resolve the economic crisis, this study provides policy makers in Zimbabwe with insight into recommendations for institutional reforms to improve the effectiveness of institutional governance to promote sustainable economic development. Keywords: Correlation, Governance, Institution, Economic development, Zimbabwe

DETERMINANTS OF TRADE INTENSIFICATION WITH FILLS GAP OF GENDER-SPECIFIC INDICATORS IN ECOWAS COUNTRIES

The purpose of this paper is to study the determinants of trade openness in ECOWAS countries and fills the gap of gender-specific indicators. The sample is composed of the 15 ECOWAS countries and covers the period from 2004 to 2018. For this purpose, we used three panel data estimation techniques, such as pooled regression, fixed effects model and Generalized Moment Method (GMM). The results of this study reveal that among the significant variables for all three techniques used, FDI represent the variable that positively influences trade openness of ECOWAS countries while variables such as population growth rate and GDP per capita negatively influence the degree of trade openness. Variables such as GDP per capita, population growth rate, labor force participation rate, political stability index, cost of starting a business, and population density were used as determinants for determinants of trade openness estimation. Result discovered that identification of policies to promote FDI and the implementation of measures to increase production is essential to cover the consumption needs of the population of ECOWAS countries. In addition, it would be beneficial for these countries to put in place an export policy for manufactured products other than primary materials in order to promote the expansion of intra-ECOWAS trade.

Exploring Social Media Knowledge as a Means for Fighting Corruption in CEE Countries

It is evidently seen that social networks are assessed widely in recent times as a means of sharing knowledge, and more importantly, resist control from influential entities compared to the regular media. Social media fight corruption by making information readily available in the form of analysis, endorsements, and through campaigns and collaboration. For this reason, some researchers are increasingly interested in how knowledge of social networks impacts our society leading to corruption reduction. In this paper, we explore the contribution of the knowledge of social media networks in reducing corruption within CEE countries. Regression analysis is employed to analyze an eighteen-year panel data (from 2002 to 2020), using secondary data from the World Bank, the World Press Freedom Index, and Transparency International of the selected CEE countries. We analyze social media variables such as social media usage, cultural tightness looseness (CTL) as independent variables and used press freedom, political stability index, and GDP per capita as control variables. Also, with corruption as a dependent variable, we used control of corruption index (CCI) and corruption perception index (CPI) to ascertain the social media network effect on corruption reduction. This article contributes to the existing knowledge by discovering the unique role that social media knowledge plays in reducing corruption in CEE countries. The result has shown that both social media usage and CTL significantly affect corruption and its reduction. In addition, it allows us to propose some practical implications for policymakers.

Analyzing The Determinants of Agricultural Value Added in EU15 Countries and Turkey by Panel Data

Countries have to deal with the sustainability of food supply and demand due to factors such as rapid increase in demand for agricultural food products on a global scale and climate change. Therefore, productivity and agricultural value added products have become strategically important to ensure food security. Developed countries provide a significant amount of value added in the agricultural sector. The aim of the study was to determine primary factors affecting the agricultural value added production in Turkey and EU15 countries and to determine how Turkey differs from these countries as a developing country. In this context, the long-term impact of government effectiveness, political stability and gross domestic product on agricultural value added has been investigated for the EU15 countries and Turkey for the period of 2002-2019. Results indicated that Turkey had a lower agricultural value added amount than the EU15 countries. While a statistically significant and positive relationship between agricultural value added and agricultural GDP and Political Stability Index, a statistically significant and negative relationship between agricultural value added and Government Effectiveness Index were observed. Keyword: agricultural value added, government efficiency index, political stability index, panel data analysis JEL Classification: C23, , H50, O13, Q18

The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America

This study aims to help managers develop a proper strategy and policy for their company’s future. After the global COVID-19 pandemic, developed countries decided to change their production and relocate and re-industrialize. The U.S.’s big electronics and automobile companies are not an exception to this rule. The lithium batteries are the main instrument of mobile phone and electric vehicles. The leading lithium battery supplier for the U.S mobile phone companies is China. Argentina, Bolivia, and Chile (in South America) have some of the largest lithium mines in the world; these countries are known as the lithium triangle. Among the 86 million tonnes of lithium resources worldwide, 49.9 million tonnes exist in this area. The researchers in this study surveyed the best country for constructing a battery for companies in the U.S. Because of the growth of electric vehicles and their use of the lithium battery, the world is facing astronomical prices for lithium. To emphasize this issue and help managers create good policy, this study combined multiple methods. The improved suitability-feasibility-acceptability (SFA) strategy is integrated with the Bayesian best-worst method (BBWM) and measurement of alternatives and rankings according to compromise solution (MARCOS) multicriteria methods to determine the best destination. For comparison, based on the SFA strategy, seven criteria are introduced: commercially viable reserves, national minimum wage, corporate income tax, accessibility to mining companies, accessibility to the waterway, population, and political stability index. The Bayesian BWM analysis reveals that the foremost factor is corporate income tax, whereas MARCOS’s findings indicate that Chile is the best country to construct the lithium battery industry. To verify the proposed approach, a comparison analysis also is performed.

The Dynamics of the Global Arms Trade Network: States’ Stability and Instability

ABSTRACT This study identifies security-related factors affecting the formation of the global arms trade network. This empirical analysis using a quantitative approach includes data from multiple sources (the Global Peace Index, Political Stability Index, Democracy Index, Global Terrorism Index, Fragile State Index, and military expenditure as a percentage of GDP) and multiple states analyzed using the ERGM. Arms trade data related to six attributes of states representing their (in)stability is collected and analyzed for 2012-2018. Our findings are as follows: (1) states with greater internal stability import more arms, which affects the formation of the global arms trade network; (2) states with greater external instability import more arms, which also affects the formation of the global arms trade network. This study makes two academic contributions, as follows. First, we analyze factors that form the global arms trade network from a holistic or systemic perspective. Second, we analyze those factors empirically and statistically from a security perspective.

AGOA: Economic and Political Effects on FDI Flows Into Sub-Saharan Africa

Foreign Direct Investment (FDI) is widely considered as an important stimulus to the economic growth in the form of employment, technology transfer; and regional economic integration among others. This paper seeks to determine the effects of the Africa Growth and Opportunity Act (AGOA) on FDI flows into Sub￾Saharan Africa. Using a modified gravity model, results suggests that per capita GDP and AGOA participation status positively influences FDI inflow into Sub-Saharan Africa while being a member of other RTAs (Other Regional Trade Agreements) hinder FDI net flow. Also, countries with generally better political stability index score have higher average FDI net flow.

COVID-19 in conflict region: the arab levant response

BackgroundCOVID-19 has hit the world in an unprecedented way causing serious repercussions on several aspects of our life. Multiple determinants have affected various nations’ level of success in their responses towards the pandemic. The Arab Levant region in the Middle East, notoriously known for repeated wars and conflicts, has been affected, similarly to other regions, by this pandemic. The combination of war, conflict, and a pandemic brings too much of a burden for any nation to handle.MethodsA descriptive analysis of data obtained from the health departments of various Arab Levant Countries (ALC) was performed. ALC include Lebanon, Syria, Jordan, Iraq and Palestine. The data collected involves incidence, recovery rate, case fatality rate and number of tests performed per million population, Global Health Security index, government stringency index, and political stability index. The information obtained was compared and analyzed among the ALC and compared to global figures. An extensive electronic literature search to review all relevant articles and reports published from the region was conducted. The 2019 Global Health Security (GHS) index was obtained from the “GHS index” website which was made by John Hopkins University’s center for health security, the Nuclear threat Initiative (NTI) and the Economist Intelligence Unit (EIU). Government stringency index and political stability index were obtained from the University of Oxford and the website of “The Global Economy”, respectively. Other world governance indicators such as government effectiveness were obtained from the World Bank website.ResultsIn terms of incidence of COVID-19, Iraq has the highest with 9665 per one million population, Syria the lowest at 256 per million. Deaths per million population was highest in Iraq at 237, and the lowest in Syria at 12. As for number of tests per million population, Lebanon ranked first at 136,033 with Iraq fourth at 59,795. There is no data available for the tests administered in Syria and subsequently no value for tests per million population. In terms of recoveries from COVID-19 per million population, Iraq had the highest number at 7903 per million, and Syria the lowest at 68 per million. When compared as percent recovery per million, Palestine ranked first (84%) and Syria last (27%). The government response stringency index shows that Jordan had the highest index (100) early in the pandemic among the other countries. Palestine’s index remained stable between 80 and 96. The other countries’ indices ranged from 50 to 85, with Lebanon seeing a drop to 24 in mid-August. Even with improved stringency index, Iraq reported an increased number of deaths.ConclusionIn countries devastated by war and conflict, a pandemic such as COVID-19 can easily spread. The Arab Levant countries represent a breeding ground for pandemics given their unstable political and economic climate that has undoubtedly affected their healthcare systems. In the era of COVID-19, looking at healthcare systems as well as political determinants is needed to assess a country’s readiness towards the pandemic. The unrest in Lebanon, the uprising in Iraq, the restrictions placed on Syria, and the economic difficulties in Palestine are all examples of determinants affecting pandemic management. Jordan, on the contrary, is a good example of a stable state, able to implement proper measures. Political stability index should be used as a predictor for pandemic management capacity, and individual measures should be tailored towards countries depending on their index.

The Role of Knowledge of the International Marketing Environment In Choosing the FDI Strategy for Entering Foreign Markets: An Econometrics Study of the Markets of A Sample of Arab Countries During the Period (2002-2019)Using Panel Data

The study aims to determine the impact of marketing environment variables on the decision of international companies to choose an FDI strategy from foreign market access strategies,by using cross-sectional data models (panel data) for the period (2002-2019) for a sample of Arab markets.&#x0D; Based on the results of estimating the model, the study concluded that there is a positive correlation between independent variables GNI and the political stability index and the dependent variable FDI flows, and negatively between the population size variable, which means that increasing the population does not necessarily mean attracting foreign direct investment, as for the economic freedom variable It has no effect on foreign direct investment flows to the Arab countries under study.&#x0D;

Impact of Political Instability on Economic Growth in CEE Countries

сPolitical instability is often considered to have a negative influence on economic growth. Hence, the study aims to examine whether instability of the political environment (measured by the political stability in- dex and duration of the chief executive in the office) significantly influences economic growth in Central and Eastern European (CEE) countries. The methodology used is a fixed effects model for panel data analysis where the dependent variable is the real growth of gross domestic product (GDP) per capita. The data covers the period from 2006 to 2016 for 13 CEE countries. Additionally, the study considered other macroeconomic variables, such as investment, inflation, human capital, trade openness, etc. The research findings indicate that the political stability index has a positive effect on economic growth, as expected and predicted in the literature. However, the indicator of the years the chief executive has been in the office has shown a negative effect. This effect appears to be weakly significant only for the second variable. These findings allowed us to conclude that the political stability index positively influences economic growth, while the years the chief executive stays in the office has a negative effect. Frequent changes in the cabinet can actually have a positive impact in transition countries characterised by corruption, meaning that the long stay of a chief executive in the office can lead to power abuse.

Food Security Index For Economic Community of West-African States (ECOWAS)

Purpose: In this article attempt is made to develop a composite food security index for some selected countries of the Economic Community of West-African States (ECOWAS), e.g. Nigeria, Niger, Benin, and Ghana. The study also aims to study the stability property of the indicators of composite food security index. Approach/ Methodology/ Design: For constructing a composite food security index for ECOWAS, one can use the basic methodology already developed by IFAD but in a modified form. This study is also based on IFAD methodology but with one more additional variable that is political stability index and assigned weight on the basis of Principal Component Analysis (PCA). Findings: This composite index is an improvement over all the other food security index developed by others eminent economists and institutions from time to time. This index consists of six indicators such as food availability, food production, self-sufficiency of food, inverse relative price index, child survival index, and political stability to construct the composite food security index of ECOWAS. Political stability is an additional indicator in the index of ECOWAS. With the help of this index, the trends, stability and situation of food security index in region are discussed and analyzed from 2001 to 2018.After careful analysis of composite food security index of ECOWAS, one can find out that It has quite impressive and improving gradually. Practical Implication: This study provides strong suggestion about how these five indicators of composite food security index provide an overview for the selected countries to secure their level of food security in their respective country. Originality/Value: After the careful analysis of the collected data, it can be concluded that the composite food security index plays an important role to understand whether food security index is improving in respective countries or not.

Determinants of Banking Stability: Evidence from Haiti’s Banking System

This paper investigates the factors of the banking stability in Haiti, over the period of 1996 to 2017, using macroeconomic, government and institutions, banking system, and economic freedom factors measured respectively by GDP growth and exchange rate, political stability index and regulatory quality index, bank lending-deposit interest rate spread, property rights index and investment freedom index. To carry out the analysis, the yearly data have been transformed into quarterly data, giving a sample of 88 observations. By means of OLS regressions, six statistical models have been specified. Banking stability which is the response variable is measured by the z-score. The results suggest that macroeconomic and economic freedom factors have positive effects on the banking stability, while the banking system factor impacts negatively the banking stability in Haiti. Conversely, government and institutions factor has no significant impact on the Haitian banking stability. When it comes to assess the impact of each explanatory variable (GDP growth, exchange rate, political stability index, regulatory quality index, bank lending- deposit interest rate spread, property rights index and investment freedom index) on banking stability, the results show that they all have significant effects on the Haitian banking stability. However, when all of the independent variables are analyzed in one multiple regression together, the political stability index is not statistically significant. The findings of this study have important implications for decision makers. Governments and the Central Bank should intensity their efforts in creating a promising macroeconomic environment, adopting effective monetary policy, reducing restrictions in investment and reinforcing laws to protect property rights, in order to maintain or improve banking stability in Haiti.

Macroeconomic determinants of MIR interest rate margin in the euro area

Abstract This study aims to examine the determinants of the MIR interest rate in the Euro area for the period 2003Q1-2015Q3. By employing Fixed and Random Effects as econometric methodologies, I examine whether the MIR rate is affected by the following macroeconomic factors: unemployment rate, inflation rate, GDP growth, political stability index, and wages as percentage of GDP. All these factors have been found to be significant drivers of the MIR rate and thus, they have to be taken into consideration when designing macro-prudential policies. The findings in this paper provide alternative explanations for the empirical evidence concerning interest rate spreads behaviour.

Associations between socioeconomic and public health indicators and the case-fatality rate of COVID-19 in sub-Saharan Africa

Aim: To investigate the influence of socioeconomic and public health indicators on the COVID-19 case-fatality rate (CFR) in sub-Saharan African countries. Methods: Ecological study using publicly available, aggregated COVID-19 data, between February 2020 to May 2021, from 46 sub-Saharan African countries. As the outcome of interest, country-specific CFRs were calculated for five 13-week periods. Spatial and temporal distributions of the variables were analysed, and negative binomial regressions with rate ratios (RR) were conducted to estimate the association between socioeconomic and public health indicators with CFR of COVID-19. Results: There were 1.7 million confirmed COVID-19 cases and 29,685 deaths in the 46 sub-Saharan African countries during the investigated time period. The median CFR was between 1% and 2%. A higher human development index (RR = 0.80; 95%CI: 0.63-1.02), higher political stability index (RR = 0.94; 95%CI: 0.90-1.00), higher number of hospital beds (RR = 0.84; 95%CI: 0.73-0.97), and higher population density (RR = 0.85; 95%CI: 0.71-1.01) resulted in a lower CFR. Elevated prevalence of diabetes mellitus (RR = 1.56; 95%CI: 0.99-2.45) and cardiovascular disease mortality (RR = 1.51; 95%CI: 1.04-2.20) were associated with higher CFR. Chronic respiratory disease and handwashing facilities presented little to no effects on COVID-19 CFR. Conclusion: The results draw attention to the vulnerabilities of the sub-Saharan African region which must be considered in the interpretation of our study. Nevertheless, the potential benefits of a lower proportion of pre-existing medical conditions and the young age structure seem to be contrasted by challenges due to socioeconomic and public health factors, which may present possible drivers of CFR on a population level.