European Journal of Government and Economics 10(1), June 2021, 30-45 European Journal of Government and Economics ISSN: 2254-7088 Natural resource abundance and broad-based financial development nexus in ASEAN countries: accounting for globalization and human capital Solomon Prince Nathaniel a* a Department of Economics, University of Lagos, Akoka, Nigeria * Corresponding author at: nathaniel_solomon21@yahoo.com Abstract. Sustainable resource consumption is important for the development of the financial system. Besides, an advanced financial system eases the transfer of revenues from production activities and export to productive investments. The influence of natural resource (NR) abundance on financial development (FD) is still an ongoing debate with conflicting results. However, this study applies a novel proxy for FD, which measures the efficiency, accessibility, and depth of the financial market and institutions. Therefore, the current study is a maiden attempt to explore the nexus between FD and NR abundance amidst globalization, human capital, and economic growth in ASEAN economies. Reliable panel econometric techniques, including second-generation unit root tests, Westerlund (2007) cointegration tests, and the Augmented Mean Group (AMG) estimator are employed on the data for the period 1990-2017. The preliminary tests affirm the existence of cross-sectional dependence, unit root, and cointegrating relationship among the variables. The findings from the study reveal that NR abundance reduces FD, while globalization, human capital and economic growth add to FD. A feedback causality exists between NR abundance and FD. Thus, this study argues that more investment to the manufacturing sector will ease the attainment of efficiency in financial sector accessibility and benefits from NR abundance. Keywords. natural resource abundance; globalization; financial development; human capital; ASEAN; AMG. JEL Codes. E44; N57; P48; Q32; Q33. DOI. https://doi.org/10.17979/ejge.2021.10.1.7202 1. Introduction Financial development (FD) is one of the strategies used by the World Bank to ensure poverty reduction and sustainable growth in developing countries. Loans and credits are the essential instruments adopted by the World Bank to actualize these objectives (Gokmenoglu and Rustamov, 2019). The World Bank directs these credits/loans to improve the private and financial sector, human and rural development, and public sector governance (World Bank, 2017). There is evidence in the literature that most resource-rich/dependent countries are barely financially developed (Frenkel 2012). More so, studies have revealed an inverse relationship between FD and natural resource (NR) abundance of resource-rich economies, but there is still no consensus, hence necessitating further probe to the nexus (Nathaniel et al. 2020c; Gylfason 2001; Auty 2003). https://doi.org/10.17979/ejge.2021.10.1.7202 Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 31 In recent times, resource-rich regions (like Africa, Asia, and Latin America) have witnessed minimal economic growth in relation to other regions with seemingly fewer NR (Khan et al. 2020). The link between lagging economic performance and NR abundance compared to economies with relatively few resources is termed “resource curse hypothesis” popularized by (Auty, 1993). The resource curse phenomenon has dominated recent policy and development discourse. Also, it remained an influential area of research for practitioners and economists, mostly from developing countries, after the 1980s. The intention was to challenge/refute the conventional idea of considering NR as a blessing (Xu et al. 2016; Apergis and Payne 2014 among others). The Association of Southeast Asian Nations (ASEAN) founded in 1967, headquartered in Jakarta, Malaysia, is a regional grouping of ten (10) countries (the Philippines, Laos DPR, Cambodia, Brunei, Malaysia, Singapore, Myanmar, Thailand, Vietnam, and Indonesia) for security, economic, and political cooperation. The region had an average growth rate of 5.5% in 2018 (IMF, 2019). The 21st century was tagged ‘the Asian Century’ as economic growth was shouldered by Asia countries, and particularly countries in the ASEAN bloc (Nathaniel 2021; Nathaniel & Khan 2020). ASEAN is a resource-rich region. The regions NR include bauxite, iron, petroleum, landmass, copper, energy (natural gas, oil, and coal), fertile land, nickel, tin, freshwater, and timber, among others. ASEAN accounts for about 82% and 56% of the world’s total production of natural rubber and tin, respectively. With a growth rate of 5.2% and a collective GDP of 2.6 trillion USD, ASEAN has assumed the status of an important economic bloc (Nasir et al., 2019). The primary objective of this study is to examine the effect of NR abundance, globalization, and human capital on FD in ASEAN. This study is super useful for ASEAN countries considering the fact that it is a resource-rich region and has witnessed significant growth over the years. Again, the region is opened to trade, which makes it globalized, but little or nothing is known as regards the influence of NR abundance, globalization, and human capital on FD in ASEAN. This was the motivation for this study. Thus, an adequate knowledge of the relationship between NR abundance and FD is required for better policy coordination and economic expansion. Hence, any impact of NR abundance on FD is likely to ease the pace of economic growth in ASEAN. In addition, exploring the relationship between FD and NR abundance will provide new insights for decision-makers in ASEAN to utilize NR more as a blessing other than a curse. A sound financial system is vital for the efficient utilization and sustainable use of NR and the stimulation of economic growth (Nathaniel et al., 2020e). FD is required to attain higher economic growth (Redmond and Nasir 2020; Sun et al. 2020; Nathaniel et al. 2020b; Nawaz et al. 2019). A developed financial sector facilitates the transfer of funds, stimulate savings, create investment opportunities, encourage corporate control, drives innovation, and promotes risk management (Murshed et al. 2020b; Gokmenoglu and Rustamov, 2019). ASEAN is considered an economically dynamic region with laudable policies directed towards economic openness, heralding trade liberalization and globalization. Considerable globalization and natural resource consumption, together with persistent economic growth, necessitated the issue of FD. Globalization is an international phenomenon that economically and socially impacts Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 32 human lives, in terms of poverty reduction, and the financial well-being of the economy (Ahmed et al. 2020a). Evidence pertaining to the influence of globalization on the climate, economic growth, and inequality has been discussed in the literature, but the exact effect of globalization on FD has not been figured out (Murshed et al., 2020a). Globalization is becoming more and more important in ASEAN, which becomes a powerful promoter of its financial sector. Generally speaking, globalization can decrease the taxes and tariffs, and bring openness to trade and FD, which can boost economic growth (Ulucak & Khan, 2020). FD can decline the supporting costs of increasing financing networks, which could trigger enterprises to make more investment in buying new equipment (Umar et al., 2020). This study adds to the literature in the following ways: (i) this is a maiden attempt to examine the impact of NR abundance on FD in ASEAN (ii) unlike previous studies, this study is the first to adopt the recently developed broad-based financial development index of the IMF to examine the FD-NR abundance nexus. This index is superior to those used by earlier studies in that, it considers the complex multidimensional nature of FD. It summarizes how developed financial institutions and financial markets are; in terms of access, depth, and efficiency. In addition, this study considered a more comprehensive human capital indicator which provides adjusted estimated returns to education for each country and covers labour market information. With these, the policy relevance of this study is assured. (iii) panel data have lots of issues (like serial correlation, heteroskedasticity, cross-sectional dependence (CD), heterogeneity, etc.) which could lead to inefficient and biased outcomes if ignored. The core of these issues is CD and heterogeneity (Dogan et al. 2020). This study, unlike previous studies, adequately deal with these issues to obtain robust estimates via advanced econometrics techniques. The Augmented Mean Group (AMG) estimator, Driscoll-Kraay (DK), and the Prais-Winsten regression (otherwise known as panel-corrected standard errors (PCSE) approach), have been applied to deal with these issues. The study is arranged as follows: Section 2 presents the literature review which encompasses the theoretical framework and empirical review. Section 3 addresses the methodology. Results are presented and discussed in Section 4. Finally, Section 5 concludes. 2. Literature Review 2.1. Theoretical Framework Theoretically, the channels through which NR abundance adversely affects FD has been highlighted by Beck (2002) who argued that NR sectors draw investment and skills away from financial sectors, concomitantly declining demand saving rates. In a similar gesture, Rajan and Zingales (2003) postulate the interest group theory of FD, which argued that existing powerful firms are always against FD by using their market power as an instrument to circumvent competition. In the presence of human capital, globalization, and economic growth, this study explores the nexus between FD and NR in ASEAN. FD is determined by NR, human capital, and Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 33 globalization which, in turn, affects economic growth (Yu et al. 2020; Nawaz et al., 2019). A sound financial system distributes NR wealth for lucrative investment projects that can promote growth (Shahbaz et al., 2018). NR could serve as an engine of growth and development, rather than the only driver of growth (Badeeb et al., 2017). Human capital enhances financial growth through the efficient utilization of NR (Tiba and Frikha, 2019). Human capital adds to the effective use of NR as well as the growth and stability of the financial system (Zaidi et al., 2019). An educated investor, as opposed to uneducated and unskilled people, can efficiently utilize financial resources (Hatemi-J and Shamsuddin, 2016). 2.2. Empirical Review According to the Classical resource abundance studies, NR is a blessing for the host countries. However, theories like the “Dutch disease” and “Resource curse,” have provided evidence that these resources (NR) could impede the economic growth of the countries concerned. Available studies affirmed that the blessings associated with NR abundance could transform to a curse amidst rent-seeking dependency, weak institutional management, low literacy rate, Dutch disease, and poor human capital development, among others (Nathaniel et al. 2020a; Ahmed et al. 2020a; Shahbaz et al., 2018a; Dwumfour and Ntow-Gyamfi, 2018). Besides, this “curse” is evidence in resource abundance economies. Khan et al. (2020) explored the impact of NR, technological innovations, and human capital on FD in China from 1987–2017. Their findings confirmed the negative impact of NR on FD in China. Also, trade openness, technological innovations, and human capital exact a positive impact on FD. The authors argued for the development of human capital and technological innovations to ensure the sustainable use of NR to enhance FD. Dwumfour and Ntow-Gyamfi (2018) discovered that NR has an unclear impact on FD in thirty-eight African countries. They attributed this to a weak institutional framework in the region. Institutions, especially political institution, could minimize the NR curse in developing economies by promoting sustainable resource use in resource-rich countries (Bhattacharyya and Hodler 2014; Mehlum et al., 2006; Humphreys et al. 2007). Guan et al. (2020) applied the FMOLS technique to investigate the NR-FD nexus in China while controlling for globalization, economic growth, and human capital. Analogous to the study of Khan et al. (2020), they discovered that NR is inimical to financial sector development, while globalization, economic growth, and human capital promote FD in China. Further findings revealed a one-way causality, in the long run, from NR, economic growth, and human capital to FD. This further corroborates the findings of Asif et al. (2020) for China. Nevertheless, the majority of the recent studies affirmed that NR deteriorates FD in developing countries (Asif et al., 2020). There is also a growing literature on how NR promotes FD in high- income countries (Shahbaz et al., 2018a,b). Gokmenoglu and Rustamov (2019) examined the effect of NR on FD for selected countries, including Turkmenistan, from 1992 to 2017. Their findings confirmed that NR abundance plays a fascinating role in promoting FD in Azerbaijan, Kazakhstan, Turkmenistan, and Russia. Zaidi et al. (2019) investigated the effects of NR, globalization, and human capital on FD in 31 OECD countries from 1990 to 2016. They discovered Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 34 that economic growth, NR, globalization, capital formation, and human capital exact a positive impact on FD. Studies like (Bravo-Ortega and De Gregorio 2005; Behbudi et al. 2010; Marchand and Weber 2015; Sibel et al. 2015; Rickman et al. 2017; Khan et al. 2020) have shown the positive impact of human capital in promoting FD. Recent studies have also linked globalization and human capital to environmental degradation (Ahmed et al. 2021a,b; Ahmed et al. 2019; Ahmed et al. 2020a,b,c; Ahmed and Wang 2019) Now, the reviewed studies point to inconsistent results as regards the nexus between NR and FD. Again, the majority of the studies are for a single country case, and there is/are no single study(s) on the ASEAN economies which should be an attractive case study considering the region’s resource abundance, unprecedented growth, openness to trade, and budding financial sector. Therefore, there is a dire need to examine the NR-FD nexus for the ASEAN economies, including factors like human capital, globalization, and economic growth. 3. Methodology 3.1. Model Construct and Data Source From the above analogy, a framework has been developed to investigate the impact of NR abundance on FD in ASEAN by introducing human capital, economic growth, and globalization. The functional form of the model is given as: 𝐹𝐹𝐹𝐹𝑡𝑡 = 𝑓𝑓(𝑁𝑁𝑁𝑁𝑡𝑡, 𝐻𝐻𝐻𝐻𝑡𝑡 , 𝐺𝐺𝐺𝐺𝑡𝑡 , 𝐺𝐺𝑁𝑁𝑡𝑡) (1) where 𝐹𝐹𝐹𝐹𝑡𝑡, 𝑁𝑁𝑁𝑁𝑡𝑡, 𝐻𝐻𝐻𝐻𝑡𝑡, 𝐺𝐺𝐺𝐺𝑡𝑡, and 𝐺𝐺𝑁𝑁𝑡𝑡 represent financial development, natural resource, human capital, globalization, and economic growth, respectively. We linearized and transformed Eq. (1) by taking the natural logarithm of the variables in line with the recent studies of Khan et al. (2020) and Sun et al. (2020) since log-linear models give reliable empirical results in elasticities (Meo et al., 2020a,b). 𝑙𝑙𝑙𝑙𝑓𝑓𝑙𝑙𝑖𝑖,𝑡𝑡 = 𝜉𝜉0 + 𝜉𝜉1ln (𝑙𝑙𝑛𝑛)𝑖𝑖𝑡𝑡 + 𝜉𝜉2ln (ℎ𝑐𝑐)𝑖𝑖𝑡𝑡 + 𝜉𝜉3ln (𝑔𝑔𝑔𝑔)𝑖𝑖𝑡𝑡 + 𝜉𝜉4ln (𝑔𝑔𝑛𝑛)𝑖𝑖𝑡𝑡 + 𝜇𝜇𝑖𝑖𝑡𝑡 (2) where 𝑖𝑖 = 1,2, 3, …𝑁𝑁 for individual countries. 𝑡𝑡 = 1,2, 3, …𝑇𝑇 for time. Detailed information on the variables are presented in Table 1. The data for the study spans 1990-2017 for eight (8) ASEAN countries, a decision constraint by data availability. Table 1. Description of Variables. S/N Variables Measurement Source Supporting studies 1. Natural resource natural resource rent (% of GDP) WDI (2019) Sun et al. (2020) 2. GDP per capita in constant 2010 USD WDI (2019) Nathaniel et al. (2020a) 3. Globalization Overall KOF index KOF (2017) Guan et al. (2020) 4. Financial development Broad‐based index of financial depth IMF (2016) Kassouri & Altıntaş (2020) access and efficiency 5. Human capital human capital index Penn World Table Khan et al. (2020) Sources: Author’s compilation. Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 35 3.2. Econometric Procedure 3.2.1. Cross-sectional Dependence and Unit Root Tests It is always necessary to examine whether individual units in the panel are independent or not, as this will help to overturn biased estimates (Omojolaibi and Nathaniel 2020; Adedoyin et al. 2020; Adeleye et al. 2020). International treaties, trade agreements, and spillover effect are the possible causes of CD (Chudik et al., 2016); and the ASEAN countries have signed more than three hundred and fifty agreements after its inception, and are also signatories to various international agreements. Therefore, it is possible that the cross-sections are not independent. This study applies the Pesaran (2004) tests to investigate the dependence/independence of the cross- sections. The tests equation is given as: 𝐻𝐻𝐹𝐹 = � 2𝑇𝑇 𝑁𝑁(𝑁𝑁−1) �∑ ∑ 𝜌𝜌𝑖𝑖𝜌𝜌𝑁𝑁−1 𝑗𝑗=𝑖𝑖+1 𝑁𝑁−1 𝑖𝑖=0 � 𝑁𝑁 (0,1), where N and T are the cross-sections and time horizon, respectively. ρij stands for cross-sections correlation of error between i and j. This test is suitable for this study due to the nature of our panel, given that 𝑇𝑇(time dimension) > 𝑁𝑁 (cross-section). In a situation where CD exist, second- generation tests are preferred. As such, the CADF (Cross-sectionally augmented ADF) and CIPS (Cross-sectionally augmented IPS) of Pesaran (2007) are applied in this study. The CADF test equation is given as: ∆𝑦𝑦𝑖𝑖𝑡𝑡 = ∆𝜑𝜑𝑖𝑖𝑡𝑡 + 𝛽𝛽𝑖𝑖𝑥𝑥𝑖𝑖𝑡𝑡−1 + 𝜌𝜌𝑖𝑖𝑇𝑇 + ∑ 𝜃𝜃𝑖𝑖𝑗𝑗𝑛𝑛 𝑗𝑗=1 ∆𝑥𝑥𝑖𝑖,𝑡𝑡−𝑗𝑗 + 𝜀𝜀𝑖𝑖𝑡𝑡 , where 𝜑𝜑𝑖𝑖𝑡𝑡 , 𝑥𝑥𝑖𝑖𝑡𝑡 ,∆, 𝑇𝑇 and 𝜀𝜀𝑖𝑖𝑡𝑡 represent the intercept, study variables, difference operator, time span, and disturbance term respectively. 𝜌𝜌𝑖𝑖 is the proxy of the unobservable common factor, which Pesaran (2007) introduced to eliminate CD emanating from common shocks that might affect all the units. Previous studies have applied these tests (CIPS and CADF) amidst CD in the dataset (Murshed 2020; Saint Akadırı et al. 2020). 3.2.2. Cointegration and Parameter Estimation Tests for long-run relationship are important for non-stationary variables, especially when variables are integrated at the same order, let’s say I(1). The study preferred the Westerlund (2007) cointegration test because it has a greater explanatory power, and also robust even in the presence of CD and nuisance from endogeneity. The test constructs four statistics; the group mean statistics, 𝐺𝐺𝜏𝜏 = 1 𝑁𝑁 ∑ 𝛼𝛼𝚤𝚤� 𝑆𝑆𝑆𝑆(𝛼𝛼𝚤𝚤)� 𝑁𝑁 𝑖𝑖=1 and 𝐺𝐺𝛼𝛼 = 1 𝑁𝑁 ∑ 𝑇𝑇 𝛼𝛼𝚤𝚤� 𝛼𝛼𝚤𝚤�(1) 𝑁𝑁 𝑖𝑖=1 , and the panel mean tests, 𝑃𝑃𝜏𝜏 = 𝛼𝛼𝚤𝚤� 𝑆𝑆𝑆𝑆(𝛼𝛼𝚤𝚤)� and 𝑃𝑃𝛼𝛼 = 𝑇𝑇𝛼𝛼�. The former examines cointegration of the whole panel, while the latter explores the existence of cointegration in at least one of the units. Since cointgration does not suggest long-run impact (Li et al. 2020), the AMG estimator, Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 36 popularized by Bond & Eberhardt (2013), is applied for parameter estimation, while the DK and PCSE were adopted to confirm the consistency of the AMG results. The AMG estimator involves a two-step procedure: AMG - Stage 1: ∆𝑦𝑦𝑖𝑖𝑡𝑡 = 𝛼𝛼𝑖𝑖 + 𝑔𝑔𝑖𝑖∆𝑥𝑥𝑖𝑖𝑡𝑡 + 𝑐𝑐𝑖𝑖𝑓𝑓𝑡𝑡 + ∑ 𝑙𝑙𝑡𝑡𝑇𝑇 𝑡𝑡=2 ∆𝐹𝐹𝑡𝑡 + 𝑒𝑒𝑖𝑖𝑡𝑡 AMG - Stage 2: 𝑔𝑔�𝐴𝐴𝐴𝐴𝐴𝐴 = 𝑁𝑁−1 ∑ 𝑔𝑔�𝑖𝑖𝑁𝑁 𝑖𝑖=1 𝑥𝑥𝑖𝑖𝑡𝑡 and 𝑦𝑦𝑖𝑖𝑡𝑡 are the observables. 𝑓𝑓𝑡𝑡 represents the unobserved common factor. The country- specific estimates of coefficients, the AMG estimator, and the time dummies are respectively 𝑔𝑔𝑡𝑡, 𝑔𝑔�𝐴𝐴𝐴𝐴𝐴𝐴 , and 𝑙𝑙𝑡𝑡. This test was preferred because it suits the nature of our panel (𝑇𝑇 > 𝑁𝑁), it adequately addresses the two core panel data issues (CD and heterogeneity) and shows country-wise results which could inform the alignment of policies to suit countries peculiarities. The AMG is also appropriate for nonstationary data typical of our panel. 4. Results and Discussion This section presents the trend of the variables, descriptive statistic and correlation, CD test, unit root, cointegration, and the parameter estimation tests (AMG, PCSE, and DK). From Figure 1, Malaysia, Thailand and Singapore are the most financially developed countries in ASEAN, while Laos DPR is the least developed. As shown in Figure 2, all the countries are getting increasingly globalized. However, Singapore is the most globalized, while Lao DPR is the least globalized. In Figure 3, NR rent is higher in Brunei compared to the other ASEAN countries. Trend of the Variables Figure 1. FD in ASEAN. Figure 2. Globalization in ASEAN. 0 .2 .4 .6 .8 Fi na nc ia l D ev el op m en t 1990 2000 2010 2020 YEAR Brunei Thailand Indonesia Malaysia Singapore Philippines Vietnam Lao DPR 20 40 60 80 10 0 G lo ba liz at io n 1990 2000 2010 2020 YEAR Brunei Thailand Indonesia Malaysia Singapore Philippines Vietnam Lao DPR Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 37 Figure 3. NR Abundance in ASEAN. Figure 4. Human Capital in ASEAN. Figure 5. Economic Growth in ASEAN. Singapore has witnessed more economic expansion (in terms of GDP growth) and human capital development in relation to the remaining countries in ASEAN as shown in Figure 4 and Figure 5 respectively. Table 2. Descriptive Statistic and Correlation. FD NR GB GR HC Mean 0.390 8.064 59.25 1163 2.384 Max. 0.799 38.37 85.34 5674 3.947 Mini. 0.001 0.000 24.00 433.2 1.512 Std. D 0.190 8.081 14.73 1.547 0.416 Correlation FD 1 NR -0.367 1 GB 0.329 -0.284 1 GR 0.409 0.263 0.422 1 HC 0.170 -0.007 0.384 0.634 1 Source: Author’s computation. Table 2 reports the properties and correlation of the variables. Economic growth has the highest average while FD has the least. These findings reveal that economic growth has been increasing faster than FD in ASEAN countries. FD and NR have a minimum value of 0.001 and 0.000, respectively. All the variables are positively associated with FD, except NR. Economic growth and human capital show a positive correlation with globalization, while globalization is negatively associated with NR. 0 10 20 30 40 N at ur al R es ou rc es A bu nd an ce 1990 2000 2010 2020 YEAR Brunei Thailand Indonesia Malaysia Singapore Philippines Vietnam Lao DPR 1. 5 2 2. 5 3 3. 5 4 H um an C ap ita l 1990 2000 2010 2020 YEAR Brunei Thailand Indonesia Malaysia Singapore Philippines Vietnam Lao DPR 0 20 00 0 40 00 0 60 00 0 Ec on om ic G ro w th 1990 2000 2010 2020 YEAR Brunei Thailand Indonesia Malaysia Singapore Philippines Vietnam Lao DPR Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 38 Table 3. Cross-sectional Dependence Result. Variables Breusch-Pagan LM Pesaran scaled LM Pesaran CD lnEF 621.3251a 21.56473a 15.57385a LnGR 345.3425a 45.67483a 45.67464a LnGR 153.4738a 43.57382a 23.68937a LnHC 214.4636a 98.56785a 44.64445a LnNR 327.3524a 67.78294a 34.76589a Source: Author’s computation. Note: ‘a’ represents significance at 1% level. Table 3 confirms the existence of CD across the three tests. Table 4 revealed that the variables are non-stationary at I(0), but I(1). Therefore, with I(1) variables, cointegration is a possibility. The Westerlund (2007) test affirms cointegration as Ga, Pt, and Pa are significant. Table 5 reports the AMG, DK, and PCSE results. The focus is on the AMG results. The DK and PCSE are applied to check the robustness of the AMG results. From the findings, NR abundance reduces FD. This is consistent with the findings of Sun et al. (2020) and Guan et al. (2020) for seven emerging economies and China, respectively. Table 4. Unit Root and Cointegration Results. Variables Level First Difference CIPS CADF CIPS CADF FD (log) -2.621 10.62 -5.387a 21.21a NR (log) -2.779 11.32 -5.440a 25.12a HC (log) -1.528 11.82 -1.911b 23.56a GB (log) -1.782 10.67 -4.314a 28.12a GR (log) Westerlund (2007) -0.733 Gt -3.016a 11.92 Ga - 8.782 -2.624a Pt -7.474a 20.43a Pa -9.783b Note: a and b represent statistical significance at 1% and 10% levels, respectively. Source: Author’s computation. This suggests a trade-off between both variables. This finding could be attributed to the fact that ASEAN countries are still emerging, with weak institutional quality, and difficulty in efficiently managing the available NR. As such, the resource curse phenomenon, as it relates to FD, still exist. Another plausible reason is the increase in NR exports which decline the number of investments channelled to the manufacturing sector in ASEAN. More so, crowding-out investment from the manufacturing and industrial sector, as well as, inadequate infrastructure could be the other potential reasons for a decrease in FD in ASEAN. Further findings showed that human capital and globalization promote FD, though the influence of the former is not significant. Human capital is vital for FD. It helps in efficient utilization of NR, promotes financial inclusion and financial literacy, which contribute to FD. Besides, education is necessary for FD. An uneducated human capital is unaware of the mechanism of the financial sector, hence it may contribute little or nothing to its development. More human capital triggers productivity and skill-building economies, which is associated with more opportunities in the financial sector. However, the findings confirmed that Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 39 human capital is not yet at a desirable level to efficiently contribute to FD in the ASEAN bloc. Table 5. AMG, DK, and PCSE Results. Variables AMG DRISCOLL/KRAAY PCSE NR (log) -0.010 (-3.91) a -0.001 (-9.11) a -0.019 (-4.20) a HC (log) 1.246 (0.21) 0.080 (1.31) 0.209 (1.56) GB (log) 0.123 (3.45) a 0.538 (10.5) a 1.877 (14.8) a GR (log) 0.327 (2.96)a 0.009 (6.88)a 0.011 (0.49) _cons. -2.219 (-3.35) a -1.786 (-7.60) a -8.389 (-20.8)a Source: Author’s computation. Note: ‘a’ represents significance at 1% level. The z/t-values are in parenthesis. Therefore, human capital development should be top on the agenda of policymakers in ASEAN, especially when enacting policies that relate to financial sector development. On the other hand, globalization opens up an economy. It allows for the importation of advanced technologies which could boost manufacturing, promote gainful trade, enhance productivity, and ensure FD. This is in line with the findings of Zaidi et al. (2019) and Guan et al. (2020). Just like globalization, economic growth adds to FD in ASEAN, consistent with the findings of (Nawaz et al. 2019; Sun et al. 2020). This suggests that economic expansion in ASEAN have created jobs and resulted in increased wage (purchasing power), leading to higher investment and consumption which promotes financial services, and hence increase FD. Table 6. Country-Specific AMG Results. Countries lnNR lnHC lnGB lnGR Brunei -43.1 (-1.96)b 34.1 (4.43)a -1.31 (-0.96) 1.19 (0.49) Thailand -0.11 (-1.31) 0.62 (5.88)a 0.40 (3.09)a -0.80 (-1.56) Indonesia 0.05 (0.90) -3.09 (-3.91)a 0.69 (1.68)c 0.07 (0.27) Malaysia -0.00 (-0.13) -0.34 (-1.13) 0.75 (8.23)a 0.02 (2.07)b Singapore Philippines Vietnam Lao DPR -0.13 (-3.04)a -0.11 (-3.30)a 0.00 (2.08)b 0.10 (1.65)c -0.34 (-1.13) -9.84 (-1.46) 2.85 (0.61) -22.1 (-2.81)a 0.10 (7.23)a 1.11 (1.79)c -0.27 (-4.21)a 0.32 (0.68) 1.21 (3.89)a 0.04 (3.34)a 1.87 (3.34)a 1.84 (1.93)b Source: Author’s computation. Note: ‘a’, ‘b’, and ‘c’ represent significance at 1%, 5%, and 10% levels respectively. The z/t-values are in parenthesis. The DK and PCSE results affirmed the outcome of the AMG estimator. Therefore, similar explanation applies. In Table 6, NR improves FD only in Vietnam, Laos DPR, and Indonesia. The influence of human capital is mixed, but it promotes FD in Brunei, Thailand, and Vietnam. Globalization harms FD in Brunei and Vietnam, while economic growth is not compatible with FD in Thailand. Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 40 Table 7. Dumitrescu & Hurlin (DH) (2012) Results. Null Hypothesis W-stat. Zbar-stat. Probability Decision lnNR → lnFD lnFD → lnNR 10.01 9.376 9.987 7.908 0.000 0.000 Bidirectional causality lnHC → lnFD lnFD → lnHC 7.650 2.988 5.783 1.345 0.003 0.299 Unidirectional causality lnGB → lnFD lnFD → lnGB 8.910 5.382 7.557 4.185 0.000 0.001 Bidirectional causality lnGR → lnFD lnFD → lnGR 5.780 4.799 2.962 2.278 0.003 0.023 Bidirectional causality lnNR → lnGR lnGR → lnNR 6.789 2.560 4.129 1.519 0.000 0.212 Unidirectional causality lnGB → lnGR lnGR → lnGB 1.078 1.346 0.347 0.667 0.565 0.765 No causality Source: Author’s computation. Note: ‘→’ shows the direction of causality. The results in Table 7 suggests a feedback causality between NR and FD, globalization and FD, and between economic growth and FD. This further confirms the link between FD and NR, and why NR and economic growth policies should consider/be connected with policies that relate to financial sector development, vice versa. 5. Conclusion and policy implications This study examined the nexus between FD and NR for eight (8) ASEAN countries from 1990- 2017. The preliminary estimation procedures involve the investigation of possible CD among the cross-sections. The three CD tests exposed the presence of CD which necessitated the adoption of robust second-generation unit root and cointegration tests to ameliorate the possible adverse effects associated with CD. Besides, the existence of a long-run relationship among the variables informed the choice of the AMG estimator. The causal direction between variables is investigated by using the DH panel causality method. The AMG results showed that human capital, globalization, and economic growth promote FD. On the flipside, NR abundance reduces FD, which confirms the resource curse hypothesis for ASEAN economies. The country- wise results are mixed. However, economic growth harms FD only in Thailand. These findings necessitate relevant policy directions. In line with these findings, this study argues that more investment in the industrial and manufacturing sectors will help ASEAN economies attain efficiency in financial sector accessibility, efficiency, depth, and enhance the benefits from their NR abundance. The most serious issue is to manage NR to support FD; NR can be transformed into value-added exports to enhance export revenues and promote FD. Therefore, revisiting NR abundance utilization for a more productive output is recommended. Since human capital and economic growth trigger FD, policies regarding sustainable growth should be maintained and the formation of human capital should be focused. More so, there is a dire need to develop human capital in ASEAN economies. An investment in human capital will enhance the available labour market with skills to direct the benefits from trade to the financial sector. It will also promote financial inclusion, and help in the efficient utilization of NR for FD. The estimates of the causality test indicate a feedback causality Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 41 between economic growth and FD, globalization and FD, and between NR and FD. These further confirm the link between NR, globalization, and FD in the ASEAN bloc. Thus, policies to reduce customs duties, taxes, and trade restrictions, and boosting foreign investment would be the right option in the ASEAN region as globalization increases FD. However, trade and foreign investment in environmentally friendly technology should be encouraged to reap the economic and environmental benefits of globalization. In conclusion, future investigation of the interaction between NR and FD in different countries/regions may lead to more generalizable results, as financial policies and NR abundance vary from country to country/region to region. Future studies may need to incorporate the moderating role of technical innovations and governance with NR to re-examine FD using other advanced measures. References Adedoyin, F. F., Nathaniel, S., Adeleye, N. (2020). An investigation into the anthropogenic nexus among consumption of energy, tourism, and economic growth: do economic policy uncertainties matter? Environmental Science and Pollution Research, 1-13. https://doi.org/10.1007/s11356-020-10638-x Adeleye, B. N., Adedoyin, F., Nathaniel, S. (2020). The criticality of ICT-trade nexus on economic and inclusive growth. Information Technology for Development, 1-21. https://doi.org/10.1080/02681102.2020.1840323 Ahmed, Z., Wang, Z. (2019). Investigating the impact of human capital on the ecological footprint in India: An empirical analysis. Environmental Science and Pollution Research, 26(26), 26782-26796. https://doi.org/10.1007/s11356-019-05911-7 Ahmed, Z., Asghar, M. M., Malik, M. N., Nawaz, K. (2020c). Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China. Resources Policy, 67, 101677. https://doi.org/10.1016/j.resourpol.2020.101677 Ahmed, Z., Cary, M., Le, H. P. (2021a). Accounting asymmetries in the long-run nexus between globalization and environmental sustainability in the United States: An aggregated and disaggregated investigation. Environmental Impact Assessment Review, 86, 106511. https://doi.org/10.1016/j.eiar.2020.106511 Ahmed, Z., Nathaniel, S. P., Shahbaz, M. (2020a). The criticality of information and communication technology and human capital in environmental sustainability: Evidence from Latin American and Caribbean countries. Journal of Cleaner Production, 125529. https://doi.org/10.1016/j.eiar.2020.106511 Ahmed, Z., Wang, Z., Mahmood, F., Hafeez, M., Ali, N. (2019). Does globalization increase the ecological footprint? Empirical evidence from Malaysia. Environmental Science and Pollution Research, 26(18), 18565-18582. https://doi.org/10.1007/s11356-019-05224-9 Ahmed, Z., Zafar, M. W., Ali, S. (2020b). Linking urbanization, human capital, and the ecological footprint in G7 countries: An empirical analysis. Sustain. Cities Soc, 55, 102064. https://doi.org/10.1016/j.scs.2020.102064 Ahmed, Z., Zhang, B., Cary, M. (2021b). Linking economic globalization, economic growth, financial development, and ecological footprint: Evidence from symmetric and asymmetric ARDL. Ecological Indicators, 121, 107060. https://doi.org/10.1016/j.ecolind.2020.107060 Apergis, N., Payne, J. E. (2014). The oil curse, institutional quality, and growth in MENA countries: Evidence from time-varying cointegration. Energy Economics, 46, 1-9. https://doi.org/10.1016/j.eneco.2014.08.026 https://doi.org/10.1007/s11356-020-10638-x https://doi.org/10.1080/02681102.2020.1840323 https://doi.org/10.1007/s11356-019-05911-7 https://doi.org/10.1016/j.resourpol.2020.101677 https://doi.org/10.1016/j.eiar.2020.106511 https://doi.org/10.1016/j.eiar.2020.106511 https://doi.org/10.1007/s11356-019-05224-9 https://doi.org/10.1016/j.scs.2020.102064 https://doi.org/10.1016/j.ecolind.2020.107060 https://doi.org/10.1016/j.eneco.2014.08.026 Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 42 Asif, M., Khan, K. B., Anser, M. K., Nassani, A. A., Abro, M. M. Q., Zaman, K. (2020). Dynamic interaction between financial development and natural resources: Evaluating the ‘Resource curse’hypothesis. Resources Policy, 65, 101566. https://doi.org/10.1016/j.resourpol.2019 .101566 Auty, R., (1993). Sustaining Development in Mineral Economies: The Resource Curse Thesis. Routledge, London. Badeeb, R. A., Lean, H. H., Clark, J. (2017). The evolution of the natural resource curse thesis: A critical literature survey. Resources Policy, 51, 123-134. https://doi.org/10.1016/ j.resourpol.2016.10.015 Beck, T. (2002). Financial development and international trade: Is there a link? Journal of international Economics, 57(1), 107-131. https://doi.org/10.1016/S0022-1996(01)00131-3 Behbudi, D., Mamipour, S., Karami, A. (2010). Natural resource abundance, human capital and economic growth in the petroleum exporting countries. Journal of Economic Development, 35(3), 81. https://doi.org/10.35866/caujed.2010.35.3.004 Bhattacharyya, S., Hodler, R. (2014). Do natural resource revenues hinder financial development? The role of political institutions. World Development, 57, 101-113. https://doi.org/10.1016/j.worlddev.2013.12.003 Bond, S., Eberhardt, M. (2013). Accounting for unobserved heterogeneity in panel time series models. University of Oxford. Bravo-Ortega, C., & De Gregorio, J. (2005). The relative richness of the poor? Natural resources, human capital, and economic growth. The World Bank. https://doi.org/10.1596/1813-9450- 3484 Chudik, A., Mohaddes, K., Pesaran, M. H., Raissi, M. (2016). Long-run effects in large heterogeneous panel data models with cross-sectionally correlated errors. Emerald Group Publishing Limited. https://doi.org/10.1108/S0731-905320160000036013 Dogan, E., Ulucak, R., Kocak, E., Isik, C. (2020). The use of ecological footprint in estimating the Environmental Kuznets Curve hypothesis for BRICST by considering cross-section dependence and heterogeneity. The Science of the Total Environment, 723, 138063. https://doi.org/10.1016/j.scitotenv.2020.138063 Dumitrescu, E. I., Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic modelling, 29(4), 1450-1460. https://doi.org/10.1016/j.econmod.2012.02.014 Dwumfour, R. A., Ntow-Gyamfi, M. (2018). Natural resources, financial development and institutional quality in Africa: Is there a resource curse? Resources Policy, 59, 411-426. https://doi.org/10.1016/j.resourpol.2018.08.012 Gokmenoglu, K. K., Rustamov, B. (2019). Examining the World Bank Group lending and natural resource abundance induced financial development in KART countries. Resources Policy, 63, 101433. https://doi.org/10.1016/j.resourpol.2019.101433 Guan, J., Kirikkaleli, D., Bibi, A., Zhang, W. (2020). Natural resources rents nexus with financial development in the presence of globalization: is the “resource curse” exist or myth? Resources Policy, 66, 101641. https://doi.org/10.1016/j.resourpol.2020.101641 Gylfason, T. (2001). Natural resources, education, and economic development. European economic review, 45(4-6), 847-859. https://doi.org/10.1016/S0014-2921(01)00127-1 Hatemi-J, A., & Shamsuddin, M. (2016). The causal interaction between financial development and human development in Bangladesh. Applied Economics Letters, 23(14), 995-998. https://doi.org/10.1080/13504851.2015.1128066 Humphreys, M., Sachs, J. D., Stiglitz, J. E., Soros, G., Humphreys, M. (2007). Escaping the resource curse. Columbia University Press. International Monetary Fund (IMF) (2019). World Economic Outlook Database, October 2019. Retrieved 11 October 2019. International Monetary Fund (IMF) (2016). Introducing a new broad‐based index of financial development, IMF Working Paper WP/16/5. https://data.imf.org/?sk=388dfa60-1d26-4ade- b505-a05a558d9a42 Kassouri, Y., Altıntaş, H. (2020). Human well-being versus ecological footprint in MENA countries: A trade-off? Journal of Environmental Management, 263, 110405. https://doi.org/10.1016/j.jenvman.2020.110405 https://doi.org/10.1016/j.resourpol.2019.101566 https://doi.org/10.1016/j.resourpol.2019.101566 https://doi.org/10.1016/j.resourpol.2016.10.015 https://doi.org/10.1016/j.resourpol.2016.10.015 https://doi.org/10.1016/S0022-1996(01)00131-3 https://doi.org/10.35866/caujed.2010.35.3.004 https://doi.org/10.1016/j.worlddev.2013.12.003 https://doi.org/10.1596/1813-9450-3484 https://doi.org/10.1596/1813-9450-3484 https://doi.org/10.1108/S0731-905320160000036013 https://doi.org/10.1016/j.scitotenv.2020.138063 https://doi.org/10.1016/j.econmod.2012.02.014 https://doi.org/10.1016/j.resourpol.2018.08.012 https://doi.org/10.1016/j.resourpol.2019.101433 https://doi.org/10.1016/j.resourpol.2020.101641 https://doi.org/10.1016/S0014-2921(01)00127-1 https://doi.org/10.1080/13504851.2015.1128066 https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/index.aspx https://data.imf.org/?sk=388dfa60-1d26-4ade-b505-a05a558d9a42 https://data.imf.org/?sk=388dfa60-1d26-4ade-b505-a05a558d9a42 https://doi.org/10.1016/j.jenvman.2020.110405 Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 43 Khan, Z., Hussain, M., Shahbaz, M., Yang, S., Jiao, Z. (2020). Natural resource abundance, technological innovation, and human capital nexus with financial development: a case study of China. Resources Policy, 65, 101585. https://doi.org/10.1016/j.resourpol.2020.101585 Li, Z. Z., Li, R. Y. M., Malik, M. Y., Murshed, M., Khan, Z., Umar, M. (2020). Determinants of carbon emission in China: how good is green investment? Sustainable Production and Consumption, 27, 392-401. https://doi.org/10.1016/j.spc.2020.11.008 Marchand, J. T., Weber, J. (2015). The labor market and school finance effects of the Texas shale boom on teacher quality and student achievement (No. 2015-15). University of Alberta, Department of Economics. Mehlum, H., Moene, K., Torvik, R. (2006). Cursed by resources or institutions? World Economy, 29(8), 1117-1131. https://doi.org/10.1111/j.1467-9701.2006.00808.x Meo, M. S., Nathaniel, S. P., Khan, M. M., Nisar, Q. A., Fatima, T. (2020b). Does Temperature Contribute to Environment Degradation? Pakistani Experience Based on Nonlinear Bounds Testing Approach. Global Business Review, 0972150920916653. https://doi.org/10.1177 /0972150920916653 Meo, M., Nathaniel, S., Shaikh, G., Kumar, A. (2020a). Energy consumption, institutional quality and tourist arrival in Pakistan: Is the nexus (a) symmetric amidst structural breaks? Journal of Public Affairs, e2213. https://doi.org/10.1002/pa.2213 Murshed, M. (2020). An empirical analysis of the non-linear impacts of ICT-trade openness on renewable energy transition, energy efficiency, clean cooking fuel access and environmental sustainability in South Asia. Environmental Science and Pollution Research, 27(29), 36254- 36281. https://doi.org/10.1007/s11356-020-09497-3 Murshed, M., Abbass, K., Rashid, S. (2020a). Modelling renewable energy adoption across south Asian economies: Empirical evidence from Bangladesh, India, Pakistan and Sri Lanka. International Journal of Finance & Economics. https://doi.org/10.1002/ijfe.2073 Murshed, M., Nurmakhanova, M., Elheddad, M., Ahmed, R. (2020b). Value addition in the services sector and its heterogeneous impacts on CO 2 emissions: revisiting the EKC hypothesis for the OPEC using panel spatial estimation techniques. Environmental Science and Pollution Research, 27(31), 38951-38973. https://doi.org/10.1007/s11356-020-09593-4 Nasir, M. A., Huynh, T. L. D., Tram, H. T. X. (2019). Role of financial development, economic growth & foreign direct investment in driving climate change: A case of emerging ASEAN. Journal of environmental management, 242, 131-141. https://doi.org/10.1016/j.jenvman .2019.03.112 Nathaniel, S. P. (2021). Environmental degradation in ASEAN: assessing the criticality of natural resources abundance, economic growth and human capital. Environmental Science and Pollution Research, 1-13. https://doi.org/10.1007/s11356-020-12034-x Nathaniel, S. P., Nwulu, N., Bekun, F. (2020a). Natural resource, globalization, urbanization, human capital, and environmental degradation in Latin American and Caribbean countries. Environmental Science and Pollution Research, 1-15. Nathaniel, S. P., Omojolaibi, J. A., Ezeh, C. J. (2020b). Does stock market-based financial development promotes economic growth in emerging markets?: New evidence from Nigeria. Serbian Journal of Management, 15(1), 45-54. https://doi.org/10.5937/sjm15-17704 Nathaniel, S. P., Yalçiner, K., Bekun, F. (2020c). Assessing the environmental sustainability corridor: Linking natural resources, renewable energy, human capital, and ecological footprint in BRICS. Resources Policy, 1-13. https://doi.org/10.1016/j.resourpol.2020.101924 Nathaniel, S., Khan, S. A. R. (2020). The Nexus between Urbanization, Renewable Energy, Trade, and Ecological Footprint in ASEAN Countries. Journal of Cleaner Production, 122709. https://doi.org/10.1016/j.jclepro.2020.122709 Nathaniel, S., Aguegboh, E., Iheonu, C., Sharma, G., Shah, M. (2020d). Energy consumption, FDI, and urbanization linkage in coastal Mediterranean countries: re-assessing the pollution haven hypothesis. Environmental Science and Pollution Research, 27(28), 35474-35487. https://doi.org/10.1007/s11356-020-09521-6 Nathaniel, S. P., Omojolaibi, J. A., Ezeh, C. J. (2020e). Does stock market-based financial development promotes economic growth in emerging markets? New evidence from Nigeria. Serbian Journal of Management, 15(1), 45-54. https://doi.org/10.5937/sjm15-17704 https://doi.org/10.1016/j.resourpol.2020.101585 https://doi.org/10.1016/j.spc.2020.11.008 https://doi.org/10.1111/j.1467-9701.2006.00808.x https://doi.org/10.1177/0972150920916653 https://doi.org/10.1177/0972150920916653 https://doi.org/10.1002/pa.2213 https://doi.org/10.1007/s11356-020-09497-3 https://doi.org/10.1002/ijfe.2073 https://doi.org/10.1007/s11356-020-09593-4 https://doi.org/10.1016/j.jenvman.2019.03.112 https://doi.org/10.1016/j.jenvman.2019.03.112 https://doi.org/10.1007/s11356-020-12034-x https://doi.org/10.5937/sjm15-17704 https://doi.org/10.1016/j.resourpol.2020.101924 https://doi.org/10.1016/j.jclepro.2020.122709 https://doi.org/10.1007/s11356-020-09521-6 https://doi.org/10.5937/sjm15-17704 Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 44 Nawaz, K., Lahiani, A., Roubaud, D. (2019). Natural resources as blessings and finance-growth nexus: A bootstrap ARDL approach in an emerging economy. Resources Policy, 60, 277-287. https://doi.org/10.1016/j.resourpol.2019.01.007 Omojolaibi, J., Nathaniel, S., P. (2020). Assessing the potency of environmental regulation in maintaining environmental sustainability in MENA countries: An advanced panel data estimation. Journal of Public Affairs, e2526. https://doi.org/10.1002/pa.2526 Pesaran, M. H. (2004). General diagnostic tests for cross-section dependence in panels. Fac. Econ. https://doi.org/Doi.org/10.17863/CAM.5113 Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. J. Appl. Econom. 22, 265–312. https://doi.org/10.1002/jae.951 Rajan, R. G., Zingales, L. (2003). The great reversals: the politics of financial development in the twentieth century. Journal of financial economics, 69(1), 5-50. https://doi.org/10.1016/S0304- 405X(03)00125-9 Redmond, T., Nasir, M. A. (2020). Role of natural resource abundance, international trade and financial development in the economic development of selected countries. Resources Policy, 66, 101591. https://doi.org/10.1016/j.resourpol.2020.101591 Rickman, D. S., Wang, H., Winters, J. V. (2017). Is shale development drilling holes in the human capital pipeline? Energy Economics, 62, 283-290. https://doi.org/10.1016/j.eneco .2016.12.013 Saint Akadırı, S., Alola, A. A., Usman, O. (2021). Energy mix outlook and the EKC hypothesis in BRICS countries: a perspective of economic freedom vs. economic growth. Environmental Science and Pollution Research, 1-5. https://doi.org/10.1007/s11356-020-11964-w Shahbaz, M., Naeem, M., Ahad, M., Tahir, I. (2018a). Is natural resource abundance a stimulus for financial development in the USA? Resources Policy, 55, 223-232. https://doi.org/10.1016/j.resourpol.2017.12.006 Shahbaz, M., Nasir, M. A., Roubaud, D. (2018b). Environmental degradation in France: the effects of FDI, financial development, and energy innovations. Energy Economics, 74, 843-857. https://doi.org/10.1016/j.eneco.2018.07.020 Sibel, B. E., Kadir, Y. E., Ercan, D. (2015). Local financial development and capital accumulations: Evidence from Turkey. Panoeconomicus, 62(3), 339-360. https://doi.org/10.2298/ PAN1503339E Sun, Y., Ak, A., Serener, B., Xiong, D. (2020). Natural resource abundance and financial development: A case study of emerging seven (E− 7) economies. Resources Policy, 67, 101660. https://doi.org/10.1016/j.resourpol.2020.101660 Tiba, S., Frikha, M. (2019). The controversy of the resource curse and the environment in the SDGs background: The African context. Resources Policy, 62, 437-452. https://doi.org/ 10.1016/j.resourpol.2019.04.010 Ulucak, R., Khan, S. U. D. (2020). Does information and communication technology affect CO2 mitigation under the pathway of sustainable development during the mode of globalization? Sustainable Development. https://doi.org/10.1002/sd.2041 Umar, M., Ji, X., Kirikkaleli, D., Shahbaz, M., Zhou, X. (2020). Environmental cost of natural resources utilization and economic growth: Can China shift some burden through globalization for sustainable development? Sustainable Development, 28(6), 1678-1688. https://doi.org/10.1002/sd.2116 Westerlund, J. (2007). Error correction based panel cointegration tests. Oxford Bulletin of Economics and Statistics, 69, 709-748. https://doi.org/10.1111/j.1468-0084.2007.00477.x World Bank (2017). World Bank Lending: Fiscal 2017. The World Bank Group. Retrieved from the World Bank. Website: http://pubdocs.worldbank.org/. World Development Indicator (WDI) (2019). World Bank Development Indicators database (online) available at https://data.worldbank.org/ Accessed date 24.10.2019. Xu, X., Xu, X., Chen, Q., Che, Y. (2016). The research on generalized regional “resource curse” in China's new normal stage. Resources Policy, 49, 12-19. https://doi.org/10.1016 /j.resourpol.2016.04.002 Yu, A., Jia, Z., Zhang, W., Deng, K., Herrera, F. (2020). A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods. Sustainability, 12(5), 1715. https://doi.org/10.3390/su12051715 https://doi.org/10.1016/j.resourpol.2019.01.007 https://doi.org/10.1002/pa.2526 https://doi.org/Doi.org/10.17863/CAM.5113 https://doi.org/10.1002/jae.951 https://doi.org/10.1016/S0304-405X(03)00125-9 https://doi.org/10.1016/S0304-405X(03)00125-9 https://doi.org/10.1016/j.resourpol.2020.101591 https://doi.org/10.1016/j.eneco.2016.12.013 https://doi.org/10.1016/j.eneco.2016.12.013 https://doi.org/10.1007/s11356-020-11964-w https://doi.org/10.1016/j.resourpol.2017.12.006 https://doi.org/10.1016/j.eneco.2018.07.020 https://doi.org/10.2298/%0bPAN1503339E https://doi.org/10.2298/%0bPAN1503339E https://doi.org/10.1016/j.resourpol.2020.101660 https://doi.org/10.1016/j.resourpol.2019.04.010 https://doi.org/10.1016/j.resourpol.2019.04.010 https://doi.org/10.1002/sd.2041 https://doi.org/10.1002/sd.2116 https://doi.org/10.1111/j.1468-0084.2007.00477.x http://pubdocs.worldbank.org/ https://doi.org/10.1016/j.resourpol.2016.04.002 https://doi.org/10.1016/j.resourpol.2016.04.002 https://doi.org/10.3390/su12051715 Solomon Prince Nathaniel / European Journal of Government and Economics 10(1), June 2021, 30-45 45 Zaidi, S. A. H., Wei, Z., Gedikli, A., Zafar, M. W., Hou, F., Iftikhar, Y. (2019). The impact of globalization, natural resources abundance, and human capital on financial development: Evidence from thirty-one OECD countries. Resources Policy, 64, 101476. https://doi.org/ 10.1016/j.resourpol.2019.101476 https://doi.org/10.1016/j.resourpol.2019.101476 https://doi.org/10.1016/j.resourpol.2019.101476