Good Governance and Economic Growth in South European Countries

Economic growth is a prerequisite for economic development. However, there is no “recipe” for countries to create an environment of prosperity and to achieve high rates of economic growth. Many researchers have examined the drivers of economic growth and find that economic growth depends on many economic and institutional variables. In this context, the main objective of this paper is to examine the role of good governance on economic growth in piicgs countries (Portugal, Ireland, Italy, Cyprus, Greece, and Spain). The database was collected from many sources and the empirical analysis is based on a 2SLS (two-stage least squares) technique. In our empirical results, we find that trade openness, gross capital formation, inflation, political stability, rule of law, debt rule, budget balanced rule, and the combination between debt rule/budget balanced rule with political stability and combination between debt rule/budget balanced rule with rule of law are significant drivers of economic growth in piicgs countries while foreign direct investments, government effectiveness, voice and accountability, regulatory quality, fiscal rule index and expenditure rule are insignificant. However, the results may be different if we use other sample groups and/or different periods.


Introduction
Economic growth is a broad notion and there is no economic development without economic growth. In general, it's beneficial for countries to achieve high rates of economic growth. it offers new jobs; it brings money and it creates an environment of macroeconomic stability and sustainable development. However, there is no "silver bullet" to do. Many researchers have tried to examine the determinants of economic growth (Cheng and Feng, 2000;Barro, 1999;Bayraktar, 2006;Asheghian, 2009;Checherita-Westphal et al., 2012;Chan and Mendy;2012) and how they affect it (positively or negatively). Traditionally, researchers focus on macroeconomics determinants like trade openness, foreign direct investments, government expenditures, inflation, direct saving, direct investment, real exchange rate, human capital, etc (Fischer, 1992;Anyanwu, 2014;Dollar, 1992;Radelet et al.,2001;Fetchi-Vehapi et al.,2015).
Reviewing the existence literature, we find that they are many economic factors that affect economic growth. Trade Openness as measured by the sum of exports plus imports as a percentage of GDP is identified as economic growth determinant. However, the results are mixed. Studies by Dollar and Kray (2004), Das andPaul (2011) andNowbutsing (2014) confirm the positive effect of trade openness on economic growth while Fenira (2015) investigates a not so strong relationship. Similarly, empirical evidence reveals that foreign direct investment has a positive impact on economic growth (Koojaroenprasit, 2012;Shahbaz and Rahman, 2010). However, researches also reveal that foreign direct investment has a negative impact on economic growth (Konings, 2001). Besides, several studies have examined the relationship between gross capital formation and the results are mixed. There are studies that reveal a positive relationship between these variables (Noor Siddiqi, 2010;Bal, Dash and Subhasish, 2016;Khan et al., 2019;Awodumi and Adewuyi, 2020) while Muhammad and Khan (2019) find that gross capital formation has a negative and statistically significant impact on economic growth. Moreover, the size of the government expenditure is also a positive key factor for economic growth (Baldacci et al., 2009;Yasin, 2011;Nwaka and Onifade, 2015). On the other hand, high inflation considered as a factor that destabilizes the economy and as a result it has a generally negative effect on economic growth (Nell, 2000;Mubarik, 2005;Sergi, 2009).
Besides, except economic variables, institutions also play an important role in economic growth (Calderoan and Chong, 2000;Cebula and Fuley, 2011;Ahmad et al., 2012;Drury et al.,2006;Acemoglu et al., 2005;Morita and Zaelke,2007;Alesina et al.,1996). A country with strong institutions can create high rates of economic growth while a country with weak institutions can hamper economic growth. Governance indicators like political stability, rule of law, voice and accountability, government effectiveness, control of corruption, and rule of law -developed by Kaufman et al. (1999)are the key factors for economic growth (Huynch et al, 2009;Rodrik, 2008;Han et al., 2014;Campos and Nugent, 2000;Aisen and Veiga, 2013). The first institution to be examined at this point is the effect of political stability on economic growth (Abosedra, 2014;Younis et al., 2008). For instance, Huynh et al. (2009) find that political stability has a positive and significant effect on economic growth. The same results are reported from Han et al. (2014). On the other hand, Alesina (1992) finds that political instability affects negatively economic growth while Pere (2005) cannot support any of the above results. A strong system of legacy is also an important driver for economic growth (Cebula and Foley, 2011;Morita and Zaelke;2007). In particular, Cebula and Foley (2011) reveal that economic growth is positively connected with regulatory quality while Morita and Zaelke (2007) report that economic growth is not associated with the existence of rules but with the enforcement of them. In addition, Huynh et al. (2009) andHan et al. (2014) find a positive correlation between voice accountability and government effectiveness.
As concerns, the rest of the institutional variables, Acemoglu and Robinson (2010), Emara andJhonsa (2014), andKaufman andKray (2002) give attention to the role of government effectiveness on economic growth. They find that government effectiveness has a positive and statistical significance link with economic growth. However, this link is not universal and researchers of Kurtz et al. (2007) and Quibria (2006) cannot establish a significant impact between government effectiveness and economic growth. Examining the control of corruption with economic growth we find mixed results. More precisely, Mo (2001) reveals that an increase in corruption reduces economic growth while Pere (2015) finds no linkage between these two variables.
Moreover, fiscal rules as a measure of fiscal policy have a prominent role in economic growth. Especially in Europe and after the hit of the crisis of 2008, the European Union strengthened its fiscal policy by adopting 4 national fiscal rules (debt rules, expenditure rules, budget balanced rules, and revenue rules). These rules set quantitative limits on fiscal variables like debt and deficit and European Commission poses penalties to European countries in case of not obey with the rules. Empirical researches have examined fiscal rules (e.g primary balance) and how they impact fiscal outcomes (Alesina and Bayoumi, 1996;Alesina et al., 1999;Debrun et al., 2008;Perotti and Kontopulos, 2002;Badinger & Reuter, 2017;Caselli & Reynard, 2020;Mitsi, 2021). However, the literature lacks on how fiscal rules affect economic growth in piicgs countries and how a combination of fiscal rules and governance indicators impact economic growth.

Data
In our study, we investigate the impact of institutions on economic growth in piicgs countries. We use this country group as these countries were worst hit by the European debt crisis and had many economic problems and especially high rates of economic recession. As a result, the implementation of fiscal rules in these country group was necessary to improve their fiscal aggregates. Our sample has yearly data and all the data was collected from 2002 to 2018. Data are derived from the sources below: 1) World Bank's Worldwide Governance Indicators, 2) World Bank's Worldwide Development Indicators, 3) United Nations Conference on Trade and Development, 3) European Commission Database, and 4) International Monetary Fund (Appendix A).

Model Specification
According to the above the linear equation of the economic growth is given as follows: rgdpca=f (to, fdi, gcf, govcon, inf ,inst, fri) The equation of the model can be written as follows: logrgdpca=α it + β 1 to it + β 2 fdi it + β 3 gcf it + β 4 govcon it + β 5 inf it + γin it + u it + e it , t=1, 2.
where α, β 1, β 2, β 3, β 3, β 4, β 5 , and γ are the unknown coefficient of the explanatory variables. u it is the effect of each country and e ii is the unobserved zero mean white noise-type. Logarithm of gdp per capita (logrgdpca) expresses the dependent variable and trade openness (to), foreign direct investments (fdi), gross capital formation (gcf), general government final consumption expenditure (govcon), inflation (inf) as independent variables. Moreover variable in expresses a set of institutional variables like rule of law (rl), government effectiveness (ge), political stability (ps), regulatory quality (rq), voice and accountability (va), control of corruption (cc), fiscal rule (fri), debt rule (dr), budget balanced rule (bbr) , expenditure rule (er). Finally, i expresses each country and t expresses the period.
Moreover, Globerman et al. (2002) and Buchanan et al. (2012) have reported in their researches that Kaufman et al. (1998) indicators (political stability, rule of law, regulatory quality, government effectiveness, voice and accountability, and control of corruption) have a strong correlation with each other and it's suggested not to include all of the variables in a single regression. In this context, we use the method of Principal Component Analysis (PCA) to construct an overall index (inst) which is comprised of these 6 sub-indices.
A significant concern in our empirical analysis is that some regressors might be endogenous in determining gdp per res.ccsenet.org Vol. 13, No. 2;2021 capita. For instance, gdp per capita may be increased due to a higher rate of trade openness and vice versa (a higher trade openness may be increased by higher gdp per capita. At this point, if we run a regression such as: OLS (Ordinary Least Squares), Fixed Effects or Random Effects (we select the appropriate model according to the Hausman test), the estimations would give biased or inappropriate results as there is correlation among error term and explanatory variables. To deal with the problem of endogeneity we apply the technique of 2SLS by using the statistical program -Stata-to make our estimations and we apply the command xtivreg2. In our model, the endogenous variable is trade openness and use as instrumental variable the first lag of trade openness. (Note 1)

Descriptive Statistics
In Figure 1 we present the average real gdp per capita of Portugal, Ireland, Italy, Cyprus, Greece, and Spain from 2002 to 2018.   Besides, Figure 3 it's illustrated the fiscal rule index (from 2002 to 2018) for each of the six countries. As we can see, after 2008 all the countries have a high fiscal rule index. This can be explained as a consequence of the financial crisis of 2007-2008. More precisely, the burst of the crisis shows the weaknesses of European countries and the huge deficits that have been created all these years. As a result, European Union tried to strengthen its fiscal policy and to make countries more fiscal disciplined in many ways and especially by adopting fiscal institutions like fiscal rules and fiscal councils.  Table 1, we present the descriptive statistics of Portugal such as mean, standard deviation, min, and max of the variables (logrgdpca, to, fdi, gcf, govcon, inf, inst, and fri) for 18 years (from 2002 to 2018).

Presentation of Results
In Tables 2, 3, and 4, we present the estimation results by using the 2SLS technique while in Table 8, we present the correlation matrix of governance indicators.
In Table 2, we show the effects of governance indicators (ps, ge, va, rl, rq, cc) on economic growth. In Table 3, we present the high correlation between governance indicators and the importance to use each variable separately in our estimation and not altogether because of the problem of multicollinearity. In Table 4, we show the effects of fiscal rules (fri, er, dr, bbr) on economic growth.  *Denotes 1% level of significance, ** Denotes 5% level of significance and *** Denotes 10% level of significance. In parentheses are the standard errors.

Discussion
In Table 2 The coefficient of gross capital formation is also positive for the 7 models. This means that a 1% increase in gross capital formation will cause an increase in real gdp per capita equal to 0.01435% in Model (A), 0.01451% in Model (B), 0.01444% in Model (C), 0.01334% in Model (D), 0.01291% in Model (E), 0.01536% in Model (F) and 0.01421% in Model (G). It's noted that the impact of gross capital formation on real gdp per capita (in 7 models) is statistically significant at a 1% level. The coefficient of inflation is positive and statistically significant only in Model (C), Model (D) and Model (E) at a 10% level of significance. In particular, a 1% increase in inflation will cause an increase of 0.0048% in real gdp per capita in Model (C), 0.00515% in Model (E), and 0.00467% in Model (F).
Among institutions of political stability, government effectiveness voice and accountability, rule of law, regulatory quality, and control of corruption, only three have a statistically significant impact on real gdp per capita. These are political stability, rule of law, and control of corruption. Coefficients of political stability and rule of law are positive while the coefficient of control of corruption is negative. This means that a 1% increase in political stability will cause an increase equal to 0.05365% in real gdp per capita. A 1% increase in rule of law index will cause an increase of 0.07946% in real gdp per capita while a 1% increase in control of corruption index will cause a decrease of 0.062% in real gdp per capita.
In Table 3, governance indicators show a high and positive correlation among them. For instance, control of corruption and rule of law have a positive correlation equal to 93.15%. Rule of law and government effectiveness have a positive correlation equal to 88.63% while regulatory quality and voice and accountability have a positive correlation equal to 80.04%. The same results are reported with other governance indicators (see Table 3).
In Table 4, the results in 4 columns present the effects of fiscal rules on economic growth. Models (A), (B), (C) and (D) show positive coefficients for trade openness, gross capital formation, inflation, debt rules, and budget balanced rules. This means that an increase in trade openness, gross capital formation, inflation, debt rules, and budget balanced rules will lead to an increase in real gdp per capita. For instance, a 1% increase in debt rule will increase real gdp per capita by 0.03833%. The same results are reported for budget balanced rules (this happens as countries in our sample have adopted the same number of debt rules and budget and balanced rules at the same year period).
Finally, in Table 5, the results in 6 columns present the interaction effects of governance indicators and fiscal rules on economic growth. Models (A) to (F) show positive coefficients for trade openness, gross capital formation, and inflation. Also, we find a positive effect of political stability and budget balanced rule/debt rule on economic growth equal to 0.05499 and a positive effect of rule law and budget balanced rule/debt rule on economic growth equal to 0.06329.

Conclusion
In this study, we investigate the role of good governance on economic growth in piicgs countries. We use a sample of 6 countries from 2002 to 2018 and we apply the 2SLS technique in our econometric analysis.
From the findings above, we can observe that foreign direct investments, government effectiveness, voice and accountability, regulatory quality, fiscal rule index, and expenditure rule are insignificant explanatory variables by using the technique of 2SLS. However, the findings also show that trade openness, gross capital formation, inflation, political stability, rule of law, debt rule, budget balanced rule, and the combination between debt rule/budget balanced rule with political stability and combination between debt rule/budget balanced rule with rule of law have significant and positive effects on real gdp per capita and should be considered as significant factors of real gdp per capita in piicgs countries. On the other hand, control of corruption shows a negative impact on economic growth.
Also, it's evident that among institutions the most effective governance indicator on economic growth is rule of law with an effect equal to 0.07946. The second position places the combination between rule of law and debt rule/budget balanced rule (0.06329) and the third position is the combination between political stability and debt rule/budget balanced rule (0.05499). In the last position, is political stability (0.05365).
The results, of the empirical analysis, have policy recommendations and suggest that piicgs countries can achieve higher rates of economic growth by adopting fiscal rules and by having an environment of good governance. In particular, policymakers should give more attention to debt rules and budget balanced rules as well to political stability, rule of law, and their combinations (political stability with debt rules/ budget balanced rules and rule of law with debt rules/ budget balanced rules).

trade indicators.
Asian Economic and Financial Review, 5, 468-482. https://doi.org/10.18488/journal.aefr/2015.5.3/102.3.468.482 Notes Note 1. We cannot use the GMM approach to deal with the problems of heterogeneity, autocorrelation and endogeneity as the number of countries are less than the number of periods.

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