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This article intends to analyse the explanatory power of the Travel and Tourism Competitiveness Index (TTCI) and some of its constituent factors on national success metrics in managing the initial surge of the COVID-19 pandemic.

The authors study the outbreak control effectiveness of 132 countries during the first semester of 2020. The authors apply generalized linear regression models and weighted least squares models using 6 COVID-19-related dependent variables, 9 TTCI-related independent variables and 12 control variables.

The results suggest that countries with superior TTCI values and selected constituent factors have the highest daily averages of coronavirus infections and fatalities per million and the highest speed rates of COVID-19 spread. The authors also find that these countries have the shortest government response time, the lowest daily average of the social restrictions index and the shortest time from the first case reported in China to the first case reported nationally.

To the best of the authors' awareness, no previous study exists analysing the statistical relationship between the TTCIB and some of its constituent factors with the selected metrics of national success at managing the initial surge of the COVID-19 pandemic. This fact represents the primary evidence of this article's unique contribution.

本文擬分析旅行及觀光競爭力指數、以及其部份構成因素，如何影響有關國家在新型冠狀病毒肺炎大爆發初期控制病毒傳播方面的成功指標。

我們就132個國家於2020年上半年控制肺炎爆發方面的表現進行研究。我們以廣義線性回歸模型和加權最小平方法進行分析研究，當中使用了六個與新型冠狀病毒肺炎有關的因變數、九個與旅行及觀光競爭力指數有關的自變數、和12個控制變量。

研究結果暗示、在擁有優越的旅行及觀光競爭力指數值和選定的構成因素的國家，以百萬人來計算，每日冠狀病毒感染及死亡的平均數字是最高的; 而且，新型冠狀病毒肺炎的傳播速度也是最高的。研究結果亦顯示、在這些國家，政府反應所需的時間是最短的，社會限制指數的日均值是最低的，以及首宗在中國被報導的個案與首宗在有關的國家被全國性地報導的個案之間的時間距是最短的。

盡作者們所知，從前似沒有相關的研究、以國家在新型冠狀病毒肺炎大爆發初期成功控制病毒傳播的選定指數、來分析旅行及觀光競爭力指數與其部分構成因素之間的統計關係; 這正是本文所作獨特貢獻的基本證據。

This paper aims to study the explanatory power of demographics, financial behaviors and financial literacy on instances of consumer financial fraud (CFF) among Emirati households.

This study is based on a survey applied to the United Arab Emirates’ (UAE’s) largest federal higher education institution. The authors analyzed the data using generalized linear models, specifically generalized regressions based on both the logit and the probit models. Independent sample tests were also applied to compare the different subgroups considered in this study.

The authors found that the CFF victims seem to be older with more years of post-secondary education and high monthly credit card balances. When analyzing the probability of Emirati students becoming CFF victims, the authors found that only age, instances of lack of monthly income to cover living costs, and average monthly credit card balance, all have significant and positive explanatory power on the probability of becoming a CFF victim. However, when analyzing the aggregate subsample of all Emirati respondents, only the credit card balance has a positive and significant relationship with such a probability.

The authors used a non-probability sampling method that produced some biases, including a gender bias and an age-related bias. These biases preclude us from making valid inferences and generalizations about the Emirati population.

To the best of authors’ knowledge, no previous research article has studied CFF in the UAE, which constitutes this study’s original contribution.

The purpose of this paper is to examine monetary policies and bank lending in the emerging economies of Sub-Sahara Africa.

The dynamic system-generalized method of moments (GMM) that overcomes issues of unobserved period and country-specific effects, as well as potential endogeneity of explanatory variables, is applied in the estimation exercise. The study uses the data for 80 banks across 20 Sub-Saharan African countries from 2010 to 2019.

The findings show that expansionary monetary policy such as an increase in money supply stimulates bank lending, while contractionary monetary policies like increase in the monetary policy rates by the central banks lead to credit contraction, albeit a weak effect due to possible underdevelopment of financial markets, institutional constraints, bank concentration and other rigidities in the system characteristic of developing countries that undermine the effectiveness of monetary policy transmission. Capital adequacy ratio and size of economic activities are other variables that significantly influence bank lending channels.

Sub-Sahara Africa countries can enhance the effectiveness of monetary policy transmission on bank lending through the effective use of the transmission mechanism of changes in money supply and monetary policy rate.

While greater empirical attention has been devoted to the nexus between monetary policies and macroeconomic variables in country-specific studies, the connection between monetary policies and bank lending at an extensive regional or cross-country level is still scanty. For Sub-Saharan Africa, there is a palpable lack of empirical evidence on this. This study, therefore, seeks to fill this gap in a region where the impact of monetary policies on credit intermediation is crucial to the economic diversification efforts of the governments of Sub-Sahara Africa.

This research aims to study some national government success factors at controlling the first wave of COVID-19. The author placed special attention on democracy-related factors.

A sample of 156 countries were studied during the first half of 2020 and their government effectiveness was analyzed regarding six dependent variables, namely, the government’s daily average of stringency index, the outbreak response time, the daily average of cases and deaths per million, the daily average of tests per thousand and the mortality rate.

The study finds that countries with the highest democracy indexes applied the softest social constraints measured by the daily average stringency index. These countries suffered a more severe pandemic impact confirmed by the highest daily averages of cases and deaths per million and the highest mortality rate. Similarly, these countries exhibited the shortest outbreak response time and the most extensive daily average tests per thousand.

The limitations of this study include lack of universal consensus for the dependent variables’ definitions, inconsistencies in how countries record COVID-19 deaths, differences in testing efforts, variances on health services, unreliable data from less democratic countries and so on.

To the best of the author’s knowledge, no previous research paper has studied the explanatory power of the author selected government success factors at controlling the first wave of COVID-19, which constitutes this study’s original contribution.