Governance Quality And Economic Growth In The Caribbean In Times Of Covid-19

ABSTRACT:The Caribbean region faces a daunting challenge as it confronts the COVID-19 pandemic. This study aims to shed light on the intricate relationship between governance quality and the economic performance of Caribbean nations, especially in the context of a global health crisis. Our research method involves a panel-random effects model, which captures the effects of governance quality and the COVID-19 pandemic on economic growth. We utilize data from various Caribbean countries, considering six dimensions of governance quality, trade openness, inflation, investment, and human capital. This comprehensive approach ensures a nuanced understanding of the region’s economic landscape during these turbulent times. Our findings expose a significant negative association between the various dimensions of governance and the ongoing pandemic crisis. Specifically, governance indicators such as voice and accountability, rule of law, political stability, and absence of violence, along with government effectiveness, emerge as positive catalysts for economic growth. On the contrary, the control of corruption and regulatory quality demonstrate a notable negative impact on growth. Furthermore, our research unveils that investment and human capital significantly contribute to boosting output growth in the Caribbean. Conversely, the impact of the COVID-19 pandemic, inflation, and trade openness is observed to be detrimental to economic growth. These findings corroborate existing empirical evidence on the governance-growth nexus, underscoring the complex interplay between governance and economic development. These results emphasize the urgency of long-term strategies to enhance governance quality in Caribbean countries. It is imperative to bolster the capacity of governments to address future epidemic episodes, recognizing the persistent threat of pandemics. Policymakers should prioritize measures that promote voice and accountability, rule of law, political stability, and government effectiveness while addressing corruption and regulatory quality issues. This research holds profound significance for both academics and policymakers, offering a pathway to stable and sustainable long-term economic growth and calling for proactive preparedness in the face of future global health challenges. It also invites further research in this critical area.


INTRODUCTION
The novel COVID-19 coronavirus pandemic has had a major impact on the economies in the Caribbean and elsewhere.This is reflected in the number of COVID-19 cases and deaths, and the severe contraction of Gross Domestic Product (GDP) in many countries.In efforts to isolate cases and limit the transmission rate of the virus, while mitigating the pandemic, countries have implemented stringent measures such as mandatory national lockdown and border closure that have caused huge disruptions to work, life, and the economy.Restrictions have caused GDP drops and increased unemployment to levels worse than that of the Great Depression (Gopinath 2020).
While advanced economies are rebounding from the pandemic-induced recession, many of the world's poorest countries and vulnerable individuals are still struggling, thus adding to the already existing social gaps in these countries.These are serious problems, and simply designing and implementing government policies to expand vaccine production or distribution or providing fiscal stimulus packages to protect firms, households, and vulnerable populations is not an appropriate strategy to achieve post-COVID economic recovery and foster inclusive and sustainable economic growth and human development unless combined with functionally effective governing system.
For decades, international organizations such as the International Monetary Fund (IMF), the United Nations, and the World Bank have consistently stated that good governance is imperative for long-run economic growth and human development.Numerous empirical studies have used different methodologies and data sets to demonstrate the existence of a strong positive relation between good governance and economic growth and development.However there is a lack of research on how external shocks like pandemics, health, and economic crises affect this relationship, especially in developing countries.This study aims to fill this gap and contribute to the frontiers of knowledge by investigating the impact of COVID-19 pandemic crisis and governance indicators on economic growth in a panel of Caribbean countries.This is particularly relevant because the pandemic crisis has become an unprecedented test of any government's ability to rise to the occasion and draw upon its institutions' innate strength and capacity to manage, exit, and recover from the crisis.
According to Davidoff and Zaring (2008), government in general tends to focus more on stimulating economic growth than on enhancing governance quality during an economic crisis.During such times, the government's response is to enact emergency-style rules and practices that may potentially have adverse consequences for long-term economic recovery (Reinhart and Rogoff 2009).The COVID-19 pandemic crisis serves as an opportunity to comprehensively evaluate the hypothesis about how the quality of governance influences a country's economic growth and social outcomes.
This study contributes to the literature related to governance, economic growth, and pandemic outbreak across several dimensions.To the best of authors' knowledge, the present study is the pioneer to investigate the possible influence of disease outbreaks such as the current coronavirus pandemic on governance-economic growth nexus in the Caribbean where the COVID-19 pandemic has exposed and further amplified the chronic problems of governance and low quality of governance existing in these countries (Kaufmann 2020;Merke 2021).We are unaware of any such studies that have examined these groups of countries from this perspective.This is particularly significant because the Caribbean is the most dependent region in the world on tourism, which has been the global sector most affected by the COVID-19 pandemic (UNWTO 2021).This issue is also important because tourism in the Caribbean accounts for a larger share of employment and capital investment, which are vital ingredients to economic growth than other regions of the world (World Travel and Tourism Council [WTTC] 2021).Understanding the impact of the pandemic crisis on governance quality and economic growth is integral for developing appropriate strategies and policies to improve the quality of governance, mitigate the impacts of virulent disease outbreaks in the foreseeable future, assist tourism in its recovery process, and enhance economic and social development outcomes in the region.
Second, most of the previous studies of the relationship between governance and economic growth utilize dynamic generalized method of moments techniques; however, this can lead to biased results due to the small number of cross-sections (Bruno, 2005).Unlike past studies that may yield biased results due to limited data, we use advanced panel data techniques, the pooled ordinary least squares (OLS), Fixed Effects Model (FEM), and Random Effects Model (REM) estimators to analyze the connection between governance and economic growth in Caribbean countries.
The pooled OLS assumes that all countries share a common relationship between governance and growth, while the FEM regression considers unobserved country-specific effects, suitable when certain factors unique to each country affect economic growth consistently over time.Additionally, the REM estimator accounts for both constant and changing unobserved factors, making it appropriate when unobserved factors change over time but are not specific to individual Caribbean countries.By comparing these models, we gain a clearer understanding of how governance quality influences economic growth.This approach ensures a robust analysis while considering various factors.Using OLS, FEM, and REM estimators ensures reliable estimates for policy insights in the Caribbean countries under study.
Third, the level of influence of the COVID-19 pandemic and governance quality on economic growth is expected to vary from one dimension of governance quality to another.Accordingly, rather than using one aggregate index of governance we break down governance into six dimensions1 focusing on different aspects of governance in order to facilitate better understanding of the nexus between the individual dimensions of governance and economic growth during turbulent times of crisis and provide more room for policy implications.
The results reveal a significant negative relationship between all dimensions of governance and the pandemic crisis.In contrast, the COVID-19 pandemic is positively and significantly correlated with investment and inflation.Additionally, we find that several governance indicators, investment, and human capital significantly contribute to increasing output growth in the Caribbean economy.Conversely, the impact of the COVID-19 pandemic, inflation, and trade openness is found to be negative.Among the dimensions of governance, voice and accountability, rule of law, political stability and absence of violence, and government effectiveness foster economic growth.In contrast, control of corruption and regulatory quality have a significant negative impact on growth.
The paper is organized as follows.The next section consists of a review of relevant studies on the role of good governance in economic growth and public health outcomes.Afterward, we describe the model specification, and then followed by the methodology as well as the data sets utilized in the estimation of the model and the empirical strategy.Then, we report and discuss the econometric results.The last section summarizes and concludes the paper with important issues on policy implications.

Governance-Economic Growth Nexus
The emergence of new endogenous growth theories in the late 1980s led scholars to look at alternative sources of economic growth and observed differences among countries' economic development levels (Romer 1990;Barro 1991).While the importance of good governance for economic growth and development is often postulated, the theoretical and empirical debate remained inconclusive (Holmberg et al. 2009).One reason might be that there seems to be no generally accepted definition of governance [e.g., United Nations Development Program (UNDP 1997)].2Governance has different meanings for different things, people, and institutions based on the purpose and context (Mellor and Jabes 2004), but there is significant consensus across the board that governance relates to political and institutional processes and outcomes that are deemed necessary to achieve and sustain economic growth and human development.
The most frequently used definition of governance is the World Bank's notion of governance which it defines as "the traditions and institutions by which authority in a country is exercised.This includes the process by which governments are selected, monitored, and replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens and the state for the institutions that govern economic and social interactions among them" (Kaufmann et al. 1999, pp. 1).In line with this definition, the World Bank developed a series of composite indicators, the Worldwide Governance Indicators (WGI, 2020), by analyzing factors including (i) Political Governance which comprises voice and accountability and political instability and violence; (ii) Economic Governance which comprises government effectiveness and regulatory quality; and (iii) Institutional Dimensions or Social Governance which comprises the rule of law and control of corruption.
The World Bank is not the only international organization that examines the issue of good governance.The major ratings agencies (Moody's, Standard & Poor's, and Fitch) also consider issues such as political stability, corruption, and various social indicators.
The Berlin-based NGO Transparency International also ranks countries from the least corrupt governments to the most corrupt in its Corruption Perceptions Index.According to Arndt and Oman (2006), the World Governance Indicators (WGI) cover the most important aspects of the governing process; therefore, these indicators have been extensively used by policymakers and scholars to measure and compare governance quality.For instance, Kaufmann et al. (1999) studied more than 150 countries, and provides empirical evidence that governance quality, as proxied by the six WGI, is crucial for positive economic outcomes.Kaufmann and Kraay (2002) conducted another study of 175 countries for the period 1996 to 2002 and found a positive relationship between per capita income and quality of governance.
The positive association between good governance and economic growth is also seen in the studies of Fayissa and Nsiah (2013), Adzima and Baita (2019), and Adedokun (2017), all on a large panel of sub-Saharan African countries, which found that individual measures of governance as proxied by the WGI showed positive effect on growth rate of real GDP per capita.However, the conclusion is that the effect of institutional variables and good governance on economic growth varied depending on the income level of countries.In the same vein, Yerrabati and Hawkes (2015) examined the impact of governance, as measured by WGI, on economic growth in South and East Asia and Pacific countries.They found that while corruption is significantly and negatively correlated with growth, government effectiveness and regulatory quality are positively and significantly correlated.Political stability and the rule of law have no important effect on economic growth.Mehanna, et al. (2010) investigated the relationship between governance and economic development for Middle Eastern and North African (MENA) countries.The results showed that voice and accountability, government effectiveness, and control of corruption were the most important factors affecting economic development.In another study focusing on MENA countries, Emara and Jhonsa (2014) found that good governance positively and significantly affects economic growth.Specifically, an increase in the composite governance index by one unit resulted in a 2 percent increase in per capita GDP.
Huynh and Jacho-Chavez ( 2009) employed a nonparametric method to analyze the relationship between good governance and economic growth.The results showed that three of the six governance indicators: voice and accountability, political stability, and rule of law are significantly correlated with economic growth while regulatory quality, control of corruption, and government effectiveness are insignificant.In contrast, Bayar (2016) utilized panel data to examine the relationship between governance and economic growth in the transnational economies of the European Union.The results revealed that all governance indicators except regulatory quality had a statistically positive impact on growth, and control of corruption and rule of law had the largest impact, while political stability had the least impact.
Han et al. (2014) argued that the role of good governance in economic growth need to be studied further and thus examined whether countries with above-average governance grow faster than countries with below-average governance.They found that developing Asian countries with a surplus in government effectiveness, regulatory quality, and corruption control grow faster than those with a deficit in these indicators-up to 2 percentage points annually, while Middle East and North African countries with a surplus in political stability, government effectiveness, and control of corruption grow faster than those with a deficit in these indicators by as much as 2.5 percentage points annually.
In contrast to the above studies, some scholars have found negative correlation between governance quality and economic growth.For instance, Pritchett's (2003) comparative analysis of Vietnam and the Philippines economic growth experiences showed that though the Philippines ranks higher than Vietnam in terms of the conventional indicators of good governance, the former has virtually economically stagnated, and the latter is fast "booming out of a poverty trap."In the same vein, Quibria ( 2006) investigated the governance-economic growth nexus for 29 Asian countries and found that the GDP growth rate of countries with higher governance quality was lower than that of countries with lower governance quality.Qian (2002) notes that China's economic growth rate was higher than the world average, while its governance quality was lower than the world average.

Governance and Public Health Outcomes
Aside from linking governance with economic growth, other studies have sought to explain the role good governance has played in public health outcomes in the last century.For example, Besley and Kudamatsu (2006) examined democracy to analyze the link between governance and health in a cross section of countries.They found that health policy interventions are superior in democracies and that in countries that have been democratic from 1956 onward, life expectancy is about five years higher than in countries that have been autocratic in the same period.The results also showed that democratic countries also have roughly 17 fewer infants dying before the age of one per 1000 births in comparison with countries that have been continuously autocratic since 1956.The authors ascribe this to democracies having greater representation and accountability, so that health issues are promoted, and to the ability of voters in democratic countries to elect competent leaders.
Nabin et al. (2021) used a panel of 185 countries and found that countries with better governance are more capable of adopting and implementing appropriate policies in controlling a pandemic like COVID-19 and that such governments are considered more trustworthy by their people.They concluded that the existence of a persistently significant inverse relationship between all measures of good governance and COVID-19 positive rates and COVID-19 growth rates confirms that the quality of governance is a key factor in a country's success in pandemic management.In contrast, Toshkov et al. (2020) found that European countries with more centralized forms of government that scored relatively poorly on measures of government effectiveness, trust, and freedom tended to respond more quickly and decisively in controlling the spread of the pandemic than decentralized countries with better scores on those measures.
Tartar et al. (2021) investigated the role of governance and government effectiveness indicators in the acquisition and administration of COVID-19 vaccines in a panel of 172 countries.The results showed that countries with the highest COVID-19 vaccination rates also have higher effective governance indicators.Regulatory quality was the most important indicator in predicting COVID-19 vaccination status in a country, followed by voice and accountability, and government effectiveness.In an earlier study, Menon-Johansson (2005) investigated the role of good governance in controlling the spread of human immunodeficiency virus (HIV).The author found that HIV prevalence falls as governance improves and, the three most influential dimensions of governance are government effectiveness, the rule of law, and control of corruption.
The study by Liang et al. (2020) explored factors responsible for the pronounced variability in Covid-19 pandemic mortality in a cross-section of 169 countries.COVID-19 mortality rate was calculated as number of deaths per 100 COVID-19 cases and government effectiveness (the capacity of government to effectively formulate and implement sound policies) was measured by WGI government effectiveness scores.They found that higher COVID-19 mortality is associated with lower test number, lower government effectiveness, aging population, fewer beds, and better transportation infrastructure.The authors concluded that increasing COVID-19 test number and improving government effectiveness have the potential to reduce COVID-19 related mortality.Similarly, Brauner et al. (2020) used data from 41 countries to investigate the effectiveness of governments in controlling the COVID-19 pandemic by implementing nonpharmaceutical interventions (NPI).They found that limiting gatherings to fewer than 10 people, closing high-exposure businesses, and closing schools and universities were each more effective than stay-at-home orders, which were of modest effect in slowing transmission.
As summarized above, the majority of the previous studies have found a positive relationship between good governance and economic growth and between government effectiveness and public health outcomes but there is a dearth of research on how pandemic outbreak and turbulent crisis impact on this relationship, particularly in developing countries.Here, we attempt to show the possible impact of COVID-19 pandemic on the governance-economic growth nexus.

Panel Model Specification
Our empirical investigation is based on a simple augmented Solow growth model where economic growth is a function of indicators of governance quality, COVID-19 pandemic crisis, and a variety of contemporary economic growth inputs.The panel growth model takes the form: where log denotes logarithm; Yit is real GDP per capita adjusted for purchasing power parity, which is taken as a dependent variable in i country and t time period.E e E e   .

Data Description and Sources
For the measure of economic growth, we use GDP per capita at purchasing power parity, expressed in natural logarithmic terms, which is commonly used in growth literature.A total of six conditioning variables are considered in the analysis.We use the six governance indicators (VA, PV, GE, RQ, RL, and CC)as defined earlierto measure governance.The scores of each governance indicator vary between -2.5 (weak) and 2.5 (strong) governance performance (World Bank, 2021).
Our second control variable is COVID-19 pandemic crisis.Various measures, including COVID-19 case numbers, death numbers, vaccination rates, crude mortality rate, and excess mortality rate have often been used as indicators of the comparative scale of the COVID-19 pandemic in different countries and regions.Any quantification of countries' virulent disease outcomes however is subject to limitations given the ongoing nature of the pandemic and differences in countries capacities to prevent, detect, respond, and maintain vital statistics on disease outbreaks.Consequently, to avoid erroneous inferences and policy prescriptions, we use a dummy variable to estimate the possible influence of the pandemic crisis on indicators of governance and economic growth.The dummy variable (COV) takes the value of unity in time period of the year 2020 and zero otherwise.
The next four conditioning variables are quality of human capital (HC) proxied by secondary school enrolment; investment (CF) proxied by gross fixed capital formation as a percent of GDP; trade openness (OP) proxied by the sum of exports and imports as percent of GDP; and inflation rate (IN) proxied by changes in the GDP deflator.
The data on governance indicators are obtained from World Governance Indicators (www.govindicators.org).All of the other variables are retrieved from the World Bank's World Development Indicators (WDI).Details of data sources and definitions are found in Table 1.

Variables
Variable GE WGI capturing perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies Rule of law RL WGI capturing perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence Control of corruption index CC WGI capturing perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests COVID-19 pandemic crisis 0,1 dummy COV Author

Estimation Method
This study utilized a panel of 12 Caribbean countries for the period 2002-2020 to test the economic growth model, specified in equation ( 1).The sample countries are Antigua and Barbuda, The Bahamas, Barbados, Cuba, Dominica, Dominican Republic, Guyana, Haiti, Jamaica, St. Kitts and Nevis, St. Lucia, and Trinidad and Tobago.The choice of sample countries and data period were determined by the availability of data in respect of the variables utilized in the study.
The main advantage of using panel data is that it affords greater flexibility in modelling differences in behavior across the Caribbean countries sampled.In comparison to countryspecific time-series econometric methods, the panel data provides more information, more variability, less collinearity among the variables, higher degrees of freedom and relatively more efficient estimates (Baltagi 2005).Moreover, panel data are better suited to accommodating possible omitted variable biases in the dataset (Hsiao 2007).This study's panel growth model offers three estimation techniques: pooled OLS, fixed effect model (FEM), and random effects model (REM).The pooled OLS treats the data as cross-sectional, ignoring time and individual dimensions.In contrast, the FEM and REM address time-invariant omitted variables, mitigating endogeneity bias.These estimation techniques are as outlined by Baltagi (2005).In addition, the REM assumes these variables are uncorrelated with time-varying covariates, while FEM allows for correlations (Wooldridge, 2010).
Since our cross-sectional units cover less than 20 countries, it is appropriate to use the FEM to estimate the parameters (Seddigi and Lawler, 2000).Our data cover the Caribbean sovereign states that share several common characteristics (location, a low degree of export diversification, proneness to natural disasters, extreme openness of their economies, and a high level of dependence on tourism), but differ greatly in their economic, social, political, cultural, and ethnic character, and resilience to shocks.This suggests that the relationship between governance, economic growth, and pandemic crises in the Caribbean may be country-specific and, if this heterogeneity is not considered, it will inevitably bias the results; therefore, choosing the correct estimator is important.Before moving toward pooled OLS, FEM or REM estimation, we conduct a series of tests to determine the characteristics of the data and select the best fitted model among three models of pooled OLS, FEM and REM.
Since the panel data regression results can be analyzed only after finalizing the model, we apply the following steps.First, we examined the correlation between the variables used in the growth regression model to check whether the regression results are distorted by perfect multicollinearity in regression or not.Second, we performed pooled regression (OLS) to estimate common intercept term and the common slope coefficient.Third, we tested the validity of random effects model (REM).Fourth, we checked which model, the REM, or pooled OLS is appropriate.To check the appropriateness, we applied Breusch and Pagan (1980) Lagrange multiplier (LM) test.The null hypothesis of this test is that variances across countries are zero, which means there is no significant difference across countries (i.e.no panel effect), and that the pooled OLS regression model is appropriate against the alternative hypothesis, thus implying the appropriateness of REM.
In the next step, we tested the validity of fixed effects model (FEM), and finally, we applied the Hausman (1978) test to determine the appropriate model -FEM or REMto use (Wooldridge 2010).Essentially, the Hausman test looks to see if there is a correlation between the error terms and the independent variables in the model.The null hypothesis is that there is no correlation between the two.The null hypothesis of this test is that REM is the appropriate model.If the result of Hausman's test is statistically significant at p-value less than 0.05, then this means that there is a serial correlation between the independent variables and the error term, and we may conclude that the appropriate model is FEM, otherwise REM is appropriate (Gujarati and Porter, 2009).

Pre-estimation Diagnostics: Descriptive Statistics and Correlation Analysis
Tables 2 and 3 present the descriptive statistics of variables and the correlation matrix among variables.Tables 4 and 5 present the results of the pooled OLS, FEM, and REM regressions and tests for the model selection, respectively.The descriptive statistics reported in The correlation matrix in Table 3 show no evidence of perfect multicollinearity between explanatory variables except for a high correlation (0.912), albeit not perfect, between two governance indicators: VA and RQ.From the correlation matrix, we observe that the six variables measuring governance quality are positively and significantly correlated with per capita income, supporting the idea that good governance enhance economic growth and development.Additionally, per capita income is positively associated with human capital, investment, and trade openness, but it is negatively associated with macroeconomic instability, as proxied by inflation and the pandemic crisis (COV).Also from our correlation outputs, we find that COVID-19 pandemic is negatively correlated with per capita income, human capital, trade openness, and the six government indicators but it is positively and significantly correlated with investment and inflation 3 .The negative correlations between COVID-19 and the governance indicators are consistent with the idea that good governance can reduce the spread and impact of the pandemic on society and the economy.
3 The positive correlation between COVID-19 pandemic and inflation could be explained by the fiscal, monetary, and financial policies deployed in response to COVID-19.Specifically, many of the governments adopted economic support measures aimed at easing the financial burden of the pandemic on businesses and the most vulnerable households (OECD 2020).This may increase the quantity of money in circulation in the economy and cause excess demand, and therefore stimulate inflation (Blanchard 2020).Another plausible explanation for the result could be that uncertainties about the pandemic and the speed of the spread of the coronavirus generate panic buying, price gouging, and hoarding of various high-demand goods including toilet paper, household cleaning supplies, face masks, soaps, sanitizers, and pain relief medications.At the same time, disruption in the global value chain and increases in number of COVID-19 confirmed cases reduced labor supply and therefore reduced the supply of goods and services.The combination of these factors may have created the positive correlation between COVID-19 and inflation (Ebrahimy et al. 2020).

Pooled OLS, REM, and FEM results
Table 4 shows results of the multivariate statistical analysis.Columns 1, 2, and 3 show the pooled OLS estimate, REM regression, and FEM regression, respectively.Results corresponding to pooled OLS reveal that this model explains 93% of the variations in real per capita income.In the regression HC, CF, GE, PV, and RL have statistically significant positive influence on economic growth at p < 0.10, whereas the impact of COV, IN, OP, CC, VA, and RQ on economic growth is negative and highly significant.Pool ability test was performed to test the null hypothesis of a common intercept and slope coefficient versus the alternative of running individual regressions for each cross-section.The calculated probability value of the regression suggests rejection of the null hypothesis as it is less than 5 percent level of significance; therefore, the conclusion that the data should not be pooled for regression purpose.
As noted previously, estimation of the growth model through pooled OLS leads to biased estimates as cross-sectional heterogeneity is not being accounted for in this approach.When we add random effect in the growth regression framework, the results presented in Column 2 of Table 4 indicate that the REM explains 72 percent of the variations in per capita income.Further, the calculated probability of F-statistics indicates rejection of null hypothesis at less than 5 percent level of significance.This means that the REM fits well, and the coefficients are not all equal to zero.In the regression, HC, CF, and the governance indicators still exert statistically significant positive influence on economic growth.The exception is RQ whose coefficient is still negative and insignificant.Further, the estimated coefficients for COV, IN, OP, and CC still remained negative and statistically significant at the 10 percent level and better.
The regression results using the FEM procedure are qualitatively similar to the REM, albeit with a higher explanatory power (97 percent).Observe that the PV variable retains its positive sign but is now insignificant.Also, the estimated coefficient of RQ retains its negative sign, however, it is now statistically significant.

Tests of the Model Selection
Based on the Breusch-Pagan Lagrange Multiplier (LM) test used to identify the appropriate method between pooled OLS and REM, the result in Table 5 shows that the null hypothesis that variances across entities is zero (HO: Var (u) = 0) can be rejected because probability value of Chi-squared (χ 2 ) is greater than the critical value at the 5 percent level of significance.As a result, the pooled OLS estimation could create biased coefficients and therefore cannot be applied in this paper to estimate the growth model.Next, we compare the FEM and REM by using the Hausman test, where the null hypothesis is that the preferred model is REM versus the alternative FEM.The result in Table 5 implies that we cannot reject the null hypothesis (HO: difference in coefficients not systematic) because the probability value of χ 2 with p-value of 0.169 is greater than 5 percent level of significance.This means that the REM is more appropriate than FEM; therefore, we choose the REM.Fail to reject HO Based on the REM, it is apparent that gains in quality of governance, human capital, and investment have significantly contributed to economic growth in the Caribbean countries over the period of analysis while COVID-19 pandemic and inflation negatively impacted the economic growth, as was expected.This finding is consistent with the literature, and it signifies the importance of a stable macroeconomic environment for economic growth.
Regarding the impact of governance quality on economic growth, the analysis shows a positive and significant impact of political stability, government effectiveness, voice and accountability, and rule of law on economic growth.This is consistent with the majority of previous studies of the governance-economic growth nexus (Han et al. 2014;Yerrabati and Hawkes 2015;Acemoglu and Robinson 2012).This evidence suggests that an institutional environment free of political tensions and social unrest, bureaucratic delays, waste in government expenditures but, characterized by strong and sound legal system, business transparency, voice and accountability, a perfect protection of property rights and contractual rights, a high level of societal trust in government and a free and independent press, is likely to stimulate long-term economic growth in the Caribbean countries.
The control of corruption (that is, a high level of corruption that is associated to a low value of the control of corruption index) has significant negative impact on economic growth, and this is consistent with the majority of previous studies which found that high corruption "sands the wheels" of the economy.In other words, high corruption discourages local and foreign investment, reduces productivity, and thus lowers economic growth (Acemoglu & Verdier, 2001;Truong 2020;Grundler & Potrafke 2019;d'Agostino et al. 2016;Mauro1995).This result however contradicts the empirical studies that support the so-called "grease the wheels" hypothesis (Houston 2007; Meon & Weill 2010) which sees corruption as an economically and socially "positive" and "redistributive" force.
In simple terms, proponents of the "grease the wheels" hypothesis argue that in some highly regulated countries that do not have effective government institutions and governance systems, corruption may be economically justified as it could potentially promote economic growth by removing bureaucratic barriers to entry and lowering companies' transaction costs when trying to comply with excessive regulation.That is, corruption can compensate for red tape and institutional weaknesses and "grease the wheels" of the economy.However, empirical evidence abounds that higher corruption is likely to adversely affect long-term economic growth (in the Caribbean) because it might undermine the regulatory environment and the efficiency of state institutions, lead to increases in the cost of production, misallocation of resources by redirecting them from public interests to private ones and distort incentives and decision-making processes (Aidt 2009;Mauro 1995).In terms of policy, it is important that the Caribbean governments work on formulating strategies and policies that may curb corruption and foster long-term economic growth because corruption has many deleterious effects on the economy and society.
The estimated coefficient for regulatory quality is negative.This is in contrast to previous studies that found a positive relationship between the volume of legislation and economic growth (Fukumoto 2008;Kirchner 2012;Di Vita 2017), but is consistent with the argument of public choice theory that although a certain level of government intervention and regulation is needed for the economy to grow as it reduces uncertainty (Graetz, 2007), poor and complex regulations can hinder economic growth by disincentivizing firms to invest, create new technologies, enter a market and invest in skill formation (Niskanen 1971;Botero et al. 2004;Di Vita 2017).
The coefficient for trade openness is also negative and significant.This is surprising given the high openness to trade of Caribbean economies.The factors that can explain this aberrant observation include the structure and composition of Caribbean bilateral trade in goods and services, which is not diversified, low value addition and little share of manufacturing exports, low customs performance, and limited market access (Ding & Hadzi-Vaskov 2017;Ossio et al. 2013).This suggests that the structure and pattern of Caribbean trade need diversification along with improvements in customs efficiency in order to capitalize on the opportunities provided by the significant and fast-growing North American, European Union, and Latin American market economies.Our result contrast with earlier findings of a positive and statistically significant effect of trade openness on economic growth (Onafowora & Owoye, 1998;Frankel & Romer, 1999;Irwin & Tervio, 2002), but is consistent with Kim (2011) and Musila and Yiheyis (2015) who found a negative effect of trade openness on economic growth for developing countries.

CONCLUSIONS AND POLICY IMPLICATIONS
The global nature and the magnitude of the health, social, political, and economic impacts of the COVID-19 pandemic has highlighted the need to understand the relationship between governance and economic growth during periods of disease outbreaks.Statistics show Latin America and the Caribbean to be the region of the world hardest hit in economic and social terms by the pandemic.We use panel-random effects model in conjunction with correlation matrix to econometrically investigate the relationship between COVID-19 pandemic, governance quality, and economic growth in the Caribbean.
The correlation matrix shows that all the six dimensions of governance quality are positively and significantly correlated with per capita income but are negatively correlated with COVID-19 pandemic.The panel-regression results show that several dimensions of governance, investment, and human capital have significant positive impacts on economic growth while COVID-19 pandemic, inflation, and trade openness exert significant negative impacts on growth.Among the governance indicators, voice and accountability, political stability, government effectiveness, and rule of law have positive effects on growth.In contrast, regulatory quality and control of corruption have negative impacts on economic growth although the impact of regulatory quality is insignificant.
These findings have policy implications for the importance of high-quality governance, human capital, and investment in influencing economic growth in the Caribbean where the pandemic is still pervasive.Given the challenges of governance and low quality of governance in the region, promoting strong rule of law and judicial enforcement, political stability, property rights, greater transparency and better accountability, and control of corruption might be some of the first-priority issues for Caribbean governments to focus on.Improving the quality of governance on a continuous and long-term basis will create an essential set of institutions that can increase the productivity of human capital and investment, improve the economic and social conditions, and ultimately promote economic growth.
While the COVID-19 pandemic has been the main global concern since March 2020, Latin America and the Caribbean have a history of coping with infectious and noncommunicable diseases (NCDs) that harm society and the economy.For instance, Zika and Chikungunya outbreaks in 2015-2016and 2014, respectively, H1N1 Influenza Pandemic in 2009, and the 2010 cholera outbreak in Haiti have severely impacted governance and economic growth in affected areas (UNDP 2017;CDC 2010;Higgs et al. 2018;UNDP 2020;Santos et al. 2023;Qureshi 2018;Bardosh 2019).These epidemics, along with high NCD rates like heart disease, cancer, stroke, diabetes, hypertension, and obesity, have exposed weaknesses in public health systems, strained government resources, and disrupted economies, leading to significant socio-economic consequences (UNDP 2017;Fischer & Staples 2014;Wilder-Smith & Osman 2020).Diverting resources from development projects to manage these outbreaks has strained public budgets, reducing funding for crucial social services and impacting governance quality.This weakened governance has hindered crisis management as overwhelmed healthcare systems struggle to provide adequate care, eroding trust in government institutions.
Our findings allow us to conclude that an environment of responsible institutions can promote the expansion of international trade and moderate the negative impacts of future disease outbreaks on the Caribbean economy.However, we do recognize that COVID-19 might be different from other exogenous shocks (epidemics and natural disasters) and given its global nature and the magnitude of the health, economic, social, and political impacts that it has had and is still having, further research is needed.Given that the COVID-19 pandemic hit most countries since March 2020 and many countries have just started reopening their economies and borders, the analysis of the pandemic disease outbreak-governance quality-economic growth nexus will continue to evolve as more data become available.
The independent variables VAit, PVit, GEit, ROit, RLit, and CCit represent six governance indicators: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption, respectively.COVit is the COVID-19 pandemic crisis proxy variable with a value of unity during the era of the pandemic, and zero otherwise.The coefficients to be estimated are 17 ,..., and Table 2 show that the series of Y, IN, HC, CF, OP, and COV indicate a high concentration with low standard deviations around the mean value while the series of VA, PV, GE, RQ, RL and CC give a low concentration with high standard deviations around the mean values.