Necessary conditions for establishing an international financial center in Asia

Thang Cong Nguyen; Nhan Thien Nguyen; Duc Hong Vo Article Necessary conditions for establishing an international financial center in Asia Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Thang Cong Nguyen; Nhan Thien Nguyen; Duc Hong Vo (2020) : Necessary conditions for establishing an international financial center in Asia, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 7, Iss. 1, pp. 1-19, https://doi.org/10.1080/23311975.2020.1823597 This Version is available at: https://hdl.handle.net/10419/244961 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Published online: 24 Sep 2020. Submit your article to this journal Article views: 1415 View related articles View Crossmark data Citing articles: 1 View citing articles MANAGEMENT | RESEARCH ARTICLE Necessary conditions for establishing an international financial center in Asia Thang Cong Nguyen 1 , Nhan Thien Nguyen 2 and Duc Hong Vo * 1 Abstract: Establishing an international financial center appears to be an important goal of many governments in emerging markets in Asia to support national economic growth. The establishment of such a center requires a multifaceted approach in which theoretical and practical aspects are important to consider. This study is conducted to examine and identify the necessary conditions leading to the establishment of a center in the Asian region. We identify 14 determinants in the current literature. We then construct 16,384 models to consider the relevance and importance of each of these 14 determinants in the context of the Asian region. The Bayesian averaging of classical estimates (BACE) is used with a sample of 35 Asian countries in this paper. Findings from our paper indicate that emerging and developing countries in the Asian region should focus on the following fundamental determinants: freedom to trade internationally, market size, higher education and training, and the size of the government. Policy implications are offered based on our findings. Subjects: Development Policy; Economics and Development; Business, Management and Accounting ABOUT THE AUTHORS Thang Cong Nguyen is a researcher Ho Chi Minh City Open University, Vietnam. His research interests include issues on energy and financial economics. He has published in various international journals including North American Journal of Economics and Finance, Emerging Markets Finance and Trade, Annals of Financial Economics; and others. Nhan Thien Nguyen is currently completing the master degree at Vietnam-the Netherlands Economics Program in Vietnam. His research interests include financial development and energy economics. He has published in SSCI- indexed journals including Emerging Markets Finance and Trade and Borsa Istanbul Review. Duc Hong Vo is Professor, and practitioner, of applied economics and finance. He has been working for the Australian public sector at the executive role. More than 80 papers from his research have been published internationally. His current research interest covers energy, environment and climate change; and applied corporate finance. PUBLIC INTEREST STATEMENT Emerging cities such as Ho Chi Minh City (Vietnam), Putrajaya (Malaysia) and many other metropolises in the region have put great efforts to attract finance and service industries. These cities have also emerged as competitors to other Asian cities such as Hong Kong, Singapore, and Shanghai in becoming the international financial centers (IFC). However, studies with a focus on identifying necessary conditions for a city to become an IFC are limited, in particular for the Asian region. The establishment of such a center requires a multifaceted approach in which theoretical and practical aspects are important to consider. Findings from our paper indicate that emerging and developing countries in the Asian region should focus on the following determinants as the necessary conditions for the establishment of an IFC: (i) freedom to trade internationally; (ii) market size; (iii) higher education and training; and (iv) the size of the government. Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 1 of 19 Received: 24 June 2020 Accepted: 01 September 2020 *Corresponding author: Duc Hong Vo, Business and Economics Research Group, Ho Chi Minh City Open University Vietnam, Ho Chi Minh City, Vietnam E-mail: [email protected] Reviewing editor: Len Tiu Wright, De Montfort University Faculty of Business and Law, UK Additional information is available at the end of the article © 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Keywords: freedom to trade; market size; higher education and training; government size; Bayesian averaging of classical estimates; Asian region 1. Introduction In 1966, in his book World Cities, Peter Hall not only provided a clear concept of international financial centers but also classified cities based on their economic indicators. This analysis explained the term “international financial center” (IFC), or “global financial center” (GFC), which are used interchangeably in this paper, by providing assessments on many aspects, such as the ease of entering the market, trade liberalization, trade volume, higher education and training, living standards, social security, and the business environment. Since it was first introduced in the 1970s and 1980s, the concept of a world city has gradually extended to one of a global financial center. Sassen (1994) theorized global cities as transnational specialized sites for global finance and third-party services. Thrift (1994) attributed the durability and persistence of global financial centers to their locational characteristics, viewing the establishment of GFCs as for generating, capturing, and transferring the immense amounts of monetary information interlocked in it every day. Similarly, Leyshon (1997) argued that political economic stability and geographical factors mostly explain clustering in a modern monetary and financial system. The author also emphasized the importance of socioeconomic factors in the formation and success of financial networks. Top-notch financial cities such as London, New York, and Tokyo are more likely to become control centers or leading locations for global capital flows and other financial services. Accompanied by the emergence of many IFCs and globalization, promoting cities’ attractiveness for inward investment is considered a vital advantage in achieving desirable outcomes for a host country, such as creating more jobs and improving standards of living. Additionally, countries with IFCs become interlocked with international financial currents and attractive to more high technologies in terms of foreign direct investment. As a consequence, competition between cities is not a new concept, and it has become more intensive and widespread than ever. In Europe, London has been demonstrated to be an irreplaceable city in comparison to Paris and Frankfurt since its first emergence as a significant city in the sixteenth century. In Asia, competition has also been intense between Singapore, Hong Kong, and Tokyo. Ho Chi Minh City in Vietnam, Putrajaya in Malaysia, and many other metropolises in the region have attracted financial and service industries, such as telecommunication. These cities have made a significant contribution to the gross national product. These cities have also emerged as competitors to other Asian cities, such as Hong Kong, Singapore, and Shanghai in becoming regional financial centers. However, studies with a focus on identifying necessary conditions for a city to become a GFC are limited, in particular on the Asian region. The lack of empirical studies and analyses makes it difficult for emerging cities to develop sensible policies to achieve their ambition of becoming a GFC. As such, this study is conducted to examine the key determinants of a GFC so that emerging metropolises in the Asian region can target policies formulated and implemented to achieve their ambition. The paper is structured as follows. Following this Introduction, relevant literature and related empirical studies are discussed in Section 2. Section 3 discusses the method and data used in this study. Empirical findings are presented and discussed in Section 4, followed by conclusions and policy implications in Section 5. 2. Literature review No consensus has yet been reached on the critical determinants for becoming an international or GFC. The rapid advancement of telecommunication enables the globalization process to eliminate geographic distance in international financial transactions. As such, the second strand of research on the role of IFCs is its ability to advance the entire financial system and hence the economy of the country where it is located through competition over IFC. Studies in this strand concentrate on Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 2 of 19 the emergence of competition between cities in promoting themselves as a lucrative place for inward investment. The literature also mentions many competitive advantages associated with financial agglomeration. Davis (1990) discussed competition between countries promoting their IFC as an inevitable outcome of the globalization process. He implied that the increasing return to scale of financial market services is emblematic of IFCs. O’Brien (1992) agreed on the necessity of an IFC in the financial concentration process. He argued that the impact of the telecommunication revolution on global centralization created a paradox between the durability and persistence of IFCs. On the one hand, information networks shrink the world in the dimension of space and time, which hurts local monopolies and improves financial market integration. On the other hand, because financial markets are more integrated, electronic linkages render moot the requirement for traditional concentration on firms and practitioners. He concluded that wholesale and retail markets arise concurrently and result in a more integrated and extensive financial market. From a different perspective, the competitive advantages of attracting foreign capital inflows to an IFC are well elucidated in many earlier studies. Consistent with this idea, Falzon (2001) emphasized the role of IFC in enhancing the financial infrastructure and capabilities of the country where it occurs. Additionally, countries with major financial centers have competitive advantages over those without them. The financial concentration benefits host countries by granting them global in terms of economic efficiency. As articulated by Shin and Timberlake (2000), these IFCs are important nodes meant to complete the conduit through which international flows of money are concentrated. We revisit previous studies on classifying financial centers and the determinants of a GFC. Khoury (1989) put more emphasis on political and geographical factors in boosting international trade and investment inflow, saying that the size of the host country is also crucial in enlarging the trade volume of international business and securing importance of the geopolitics. Some studies were conducted to identify what enabled London to become a GFC. Neal and Quinn (2001) attributed London’s status to an effective monitoring and enforcement mechanism, which was developed by London-based merchants in the seventeenth century. Additionally, the network between counterparties is maintained by British bankers. Neal (1990) pointed to the liquidity of the British government open market operation following the Glorious Revolution in 1688. Furthermore, Carlos and Neal (2011) attributed the irresistible position of London for foreign and domestic investment to the early establishment of the Bank of England in 1694. Historical records found that London was the first industrial city engaging in large volumes of foreign trade, which gives rise to trade credit for foreign and domestic merchants. Focusing on more recent studies, Clark (2002) attributed the success of London as a leading center to the development of an ecosystem, third-party services, legal consultants, and auditing. Faulconbridge (2004) believed that the revolution in telecommunication, an effective tax system, trading history, the number of head offices and international banks, financial services, and institutional link led to the current position of London. Cassis (2006) mentioned that efficient regulation in the United States induces the growth of the eurodollar in the currency market in London in the 1950s. Budd (1995) and Clark (2001) indicated the decrease in restrictive regulations in the financial market as a lubricant in the emergence of mutual fund and pension fund activities. Moreover, the UK Financial Securities Act of 1986 (“the Big Bang”) marked the development of private transactions in the UK. Several studies attempted to identify the determinants that make a city attractive enough to become an IFC. Wojcik (2009) paid attention to the importance of financial interrelations and concentration over the convenience of transferable information in financial centers. Martin (1999) strengthened the role of physical distance in conditioning a cluster of financial activities, emphasizing financial information as crucial in ensuring international business functionality. Zhao et al. (2004) empirically explained that the clustering of international third-party services is the key factor contributing to the formation of a global city. The geographic agglomeration of a major city is the effective way to address the information problem raised by a booming financial telecommunication network. Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 3 of 19 Few empirical studies consider the formation and the determinants of a GFC. Tey (2004) took into consideration many indices that might explain being a GFC, dividing a city’s traits into five categories: (51) business environment (e.g., macroeconomic conditions, tax system), (2) financial sector development (availability of financial instruments, stock market and currency market trade volume, the degree of financial liberalization), (3) infrastructure (means of transportation, building, transport system), (4) human capital (higher education training, human development and social security), and (5) reputation (attractiveness). Similarly, Yildirim and Mullineux (2015) employed a data set on 200 senior managers about weighting the competitiveness of Istanbul on a Likert scale from 1 to 5. Using factor analysis, they used 19 indices collected from a questionnaire and divided them into two criteria, competitiveness and infrastructure. The respondents are confident about Istanbul’s foresight in being an IFC based on current economic condition and business location factors. Kayral and Karan (2012) used a quantile regression to filter out indices on 10 variables that affect an international center ranking reported by the Z/Yen corporation. None of their variables of interest is significant. Moosa et al. (2016) performed extensive work on IFCs using all potential variables in conjunction with the extreme bound analysis method. Their work identified only two variables that statistically support their assumptions, including a global competitiveness index by the World Economic Forum and a high cost of occupancy. Eichengreen and Shah (2020) considered the latest studies and the most comprehensive work so far on the issue. Employing mostly a set of variables used by Kayral and Karan (2012) and Moosa et al. (2016), they found that, in addition to size, protection of property rights, transparency in financial market mechanisms, and trade openness, the advancement in technology is also an essential element in the process of economic growth and development of the rest of the others industrialized countries. 3. Methodology and data 3.1. Estimation technique Because our main interest is the factors that affect the formation of IFCs, our dependent variable GFCit takes binary values that denote whether country i has an IFC in year t. The equation is as follows: GFCit ¼αiþ∑ T l¼0 xi;tδi;tþPit where i21;. . . ;Nð Þ and t21;. . . ;Tð Þ, xit is the k�1 dimension vector that can explain the establishment of an IFC of country i in period t. Pit is the error term. αi is the individual fixed effects corresponding to country i. We also control for the financial crash event in 2008 using a dummy variable, denoted as Crisis. We compiled a dataset on 14 determinants widely used in the literature on GFCs, such as Kayral and Karan (2012), Moosa et al. (2016), and Eichengreen and Shah (2020), though only a subset is included in the final model. Among the 14 available determinants taken into consideration, there are 2 14 models, or 16,384 different models, indicated by statistical theory. One of these 16,384 models might be the best model. Our first step is to set out selected criteria for model selection. The second step is examining all the models and determining the typical pattern. Based on our criteria and statistical inferences, the remaining step is to select the best model. We have four criteria, proposed in Ca’Zorzi et al. (2012), for model selection. Criterion 1 We accept all models that yield the correct sign of their coefficients as expected or significantly statistical regressors (determinants). Sequentially, among these selected models, we choose the model(s) which have the largest numbers of regressors (determinants). Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 4 of 19 Criterion 2: We accept all models that yield the correct sign of their coefficients as expected and significantly statistical regressors. The model with the largest number of determinants is then selected among these models. Criterion 3 We accept the model with the lowest Schwarz information criterion (SIC) or Bayesian information criterion (BIC), which measures the goodness of fit. Criterion 4 We accept the model with the lowest Akaike information criterion (AIC), which measures the goodness of fit. The first criterion ensures the minimum potential exposure to omitted variables hazards based on parsimony. The other three criteria are associated with statistical inferences. Also, our analysis is extended using the Bayesian averaging of classical estimates (BACE), which is discussed in detail below. 3.2. The Bayesian averaging of classical estimates model The establishment of a GFC requires advancements in many aspects that are not comprehensively developed and grounded in theory. As such, previous empirical studies provide a limited number of determinants. Previous studies appear to use an arbitrary combination of determinants. In response to this limited number of determinants, Moosa et al. (2016) introduced extreme bounds analysis to identify “robust” empirical linkage between country specifics and the establishment of a GFC. Briefly, the extreme bound analysis conditions are too difficult to satisfy when the number of potential variables (determinants) becomes significant. More specifically, if one regression yields an insignificant or opposite sign of the estimated coefficient βz, then the element is considered “unreliable.” This problem was addressed by Granger and Uhlig (1990). Many methods have been developed and widely applied in addressing model uncertainty. The advantages of using BACE are clearly outlined in Sala-i-Martin et al. (2004). The criteria, as mentioned above, allow us to filter out the subset of predetermined models. We cannot guarantee that one of the preferred models is the best model. To be more accurate, BACE involves the prior probabilities of the model and averages them based on the posterior probabilities deduced. The process allows us to address the model uncertainty and predictors formally and explicitly (Ca’Zorzi et al., 2012). The posterior probabilities of model Mj, therefore, can be calculated as follows: P Mjjy  �¼lyMj  �:P Mj  � ∑2K i¼1lyMi ð ÞP Mi ð Þ where lyMj  �denotes the likelihood of model j as the best model given the data y with several potential candidate predictors K. We are left only with the determination of the prior beliefs of the model, P Mj  �. The BACE method requires us to define one prior hyper-parameter: the model size expectation k. Sala-i-Martin et al. (2004) suggested using a prior mean of the model size, k, for each predictor, and the probability of being included in the best model is represented as k K. The posterior probability is the function of the goodness of fit, which is deflated by the number of variables included in the model—in sum, using one best model whose highest posterior probability seems to yield less reliable predictive ability than model averaging. On that basis, we recommend using PðMjjyÞas the weight. 3.3. Data The dependent variable (the establishment of a GFC) is a binary variable, in which 1 is used when a country has a financial center in the current year, and 0 otherwise. Recognition as if GFC is defined by a global financial center index (GFCI) published by the Z/Yen Group. The GFCI report first appeared in March 2007 and is published in a half-year frequency. The GFCI is constructed using two sources of data: instrumental variables collected from many reliable sources and survey data collected from an online questionnaire since 2007. To be included on the list of GFCs, a city must Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 5 of 19 have at least five responses to the question “Are there any financial center that might become significantly more important over the next two years.” The respondents must be reputable people. The dataset consists of 35 Asian countries. Data on independent variables are computed from many sources, including the World Bank, the Fraser Institute, and the World Economic Forum. The value of explanatory variables ranges from 1 (lowest quality) to 10 (highest quality). Data on explanatory variables are available only at the country level. We compile our dataset with filtering based on 14 potential determinants of GFC status most commonly used in previous literature. These determinants are developed based on combinations of many sub-indicators on a scale from 1 to 10. For example, sound money has four distinct dimensions, including: money growth, inflation, inflation in the most recent year, and freedom to own a foreign bank account. We consider it appropriate to use these multidimensional indicators for the following reasons. First, the paper uses the BACE method. The disadvantage of the BACE method is its computational burden (Magnus et al., 2010). If we have 50 independent variables, which are presumably determinants of the formation of a GFC, then calculations will be very time consuming. Second, the indicators used in the paper are multidimensional indices, which have a high degree of representativeness. There are trade-offs between hazards omitted and the robustness of predictions. The list of variables, sources of data, expected signs and definitions are summarized in Table 1. All signs of regressors (determinants) should positively correlate to the dependent variables. Descriptive statistics on 14 variables are presented in Table 2. 4. Global financial centers in Asia: Characteristics and empirical findings 4.1. Characteristics of selected Asian Global Financial Centers Table 3 lists the top 10 global financial centers in the Asian region. China has three GFCs in this list whereas Australia and Japan have two each. Hong Kong and Singapore are the two premier Asian cities, which surpassed the top-ranked Tokyo since 2018, thanks to their reputation for efficiency and transparency in handling financial services. Hong Kong gained superior expertise in international financial services and its strategic position in the first few decades after the conclusion of World War II. The success of laissez faire economic policy, often described as “free interventionism,” is considered fundamental to Hong Kong’s outstanding growth. Based on a deep understanding of trade liberalization, the British colonial government optimally restricted exchange controls and lowered trading barriers to international capital flows. Therefore, it has no central bank or monetary policy. Three colonial banks minted currency against deposits of British pounds, which created soundness for multinational corporations as well as domestic manufacturers. Moreover, the trusted local institutions comprehensively based on the English legal framework are also advantageous for financial operations. The exclusion of larger authorized and foreign bank branches created a prominent link between the local and foreign banking sectors. Singapore’s largely analogous conditions also extensively focus on transparency in doing business and trade liberalization. After it ceased to be a British colony, Singapore rapidly became a significant entrepôt in trading and naval operations because of its strategic position. These historical trade flows laid a firm foundation for further enhancement of financial services and trading activities, such as money exchange and shipping insurance (Cassis, 2006). 4.2. Empirical findings Our literature review indicates that 14 determinants are essential for the establishment of an IFC. With various combinations among these 14 determinants, statistical theory states that 2 14 models, which are 16,384 models, could be created. Figure 1 presents the distribution/histogram of all estimated coefficients obtained from 16,384 models using the 14 determinants. The estimated coefficients for some of these models might not be statistically significant. However, the most critical aspect of the histograms is to provide readers with the first glance of the contributions of estimated coefficients from 14 determinants in the establishment of a GFC when we run 16,384 Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 6 of 19 Table 1. Definition of variables, data sources, and expected signs Variable Definition Source Expected sign Global Financial Center Dependent variable take a binary value, with 1 denoting countries with a financial center. Z/Yen Corporation None Size of government The average of government consumption, transfers and subsidies, and government investment. This variable is measured on a scale of 0 to 10. Fraser Institute Positive (+) The legal system and property rights The average of judicial independence, impartial courts, protection of property rights, military subordination to the rule of law and politics, the integrity of the legal system, legal enforcement of a contract, regulatory restrictions on sales and property, reliability of the police, and the business cost of crime. This variable is measured on a scale of 0 to 10. Fraser Institute Positive (+) Sound money The average of money growth standard deviation of inflation, inflation in the most recent year, and freedom to own foreign currency bank accounts. This variable is measured on a scale of 0 to 10. Fraser Institute Positive (+) Freedom to trade internationally The average of tariffs, regulatory trade barriers, black market exchange rate, and controls on the movement of capital and people. This variable is measured on a scale of 0 to 10. Fraser Institute Positive (+) Business sophistication This variable takes into account the local supplier quality and quantity, state of cluster development, nature of competitive advancement, the sophistication of the production process, and value chain breadth. This variable is measured on a scale of 0 to 10. World Economic Forum Positive (+) Financial market development This variable takes into account the efficiency of the financial market and trustworthiness and confidence. This variable is measured on a scale of 0 to 10. World Economic Forum Positive (+) (Continued) Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 7 of 19 Table 4. (Continued) Variable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Model 11 Model 12 Model 13 Market size (8.72) (7.88) (8.26) (7.90) (8.92) (8.20) (8.80) (8.58) (8.28) (8.24) (8.61) (8.01) (8.81) Techno logical readiness 0.207 - 0.191 - - 0.0774 0.408* 0.390 0.348 0.181 0.493* - - (1.15) (0.85) (0.35) (2.07) (1.95) (1.69) (0.82) (2.48) Crisis −0.932* −1.034* −0.828 −0.929* −1.057* −0.948* −0.970* −0.964* −0.960* −0.822 −0.845 −1.013* −1.114* (−2.06) (−2.54) (−1.91) (−2.18) (−2.37) (−2.06) (−2.09) (−2.12) (−2.09) (−1.78) (−1.85) (−2.21) (−2.41) _cons −16.61*** −15.47*** −17.81*** −15.91*** −18.33*** −20.45*** −18.70*** −19.13*** −20.07*** −18.59*** −17.98*** −17.89*** −19.31*** (−7.81) (−6.79) (−6.76) (−7.30) (−7.23) (−7.18) (−7.68) (−6.99) (−7.44) (−7.17) (−6.80) (−7.23) (−7.30) N346 346 346 346 346 346 346 346 346 346 346 346 346 Notes:Mixed-effects probit model on 14 determinants. t-statistics are reported in parentheses. *, ** , and *** coefficient is significant at 5 percent, 1 percent, and 0.1 percent. Two determinants (Financial market development and Population density) are not reported because they do not have correct signs as expected or statistical significance in any models. Crisis is a dummy variable in the model. Criterion 1 accepts all models with the correct sign as expected or statistically significant regressors (determinants). Then, among these accepted models, we select the models with the largest number of determinants. In this analysis, the largest number of determinants is 6, and 13 models with different combinations of 14 determinants satisfy Criterion 1. Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 14 of 19 Table 5. Determinants and their estimated coefficients using Criteria 2, 3, and 4 and the Bayesian model of estimation (BACE) Model 14 (Criterion 2) Model 15 (Criterion 3 using BIC or SIC) Model 16 (Criterion 4 using AIC) BACE Dependent var. IFC IFC IFC IFC Size of government 0.483** 0.717** 0.0455** (2.61) (3.12) (2.90) Legal property rights −0.00771 (−0.42) Sound money 0.310* 0.00262 (2.06) (0.26) Freedom to trade internationally 0.372 1.356*** 1.370*** 0.128*** (1.68) (4.66) (4.39) (4.20) Business sophistication −0.00281 (−0.19) Financial market development −1.182*** −0.702* −0.00496 (−4.50) (−2.39) (−0.32) Goods market efficiency −0.00849 (−0.30) Higher education and training 1.381*** 1.435*** 0.130*** (4.84) (3.74) (4.47) Infrastructure 0.349 0.861** 0.00310 (1.86) (3.24) (0.24) Institutions −0.660 −0.0000256 (−1.76) (−0.00) Labor market efficiency −0.704* −0.00162 (−2.12) (−0.16) Market size 1.130*** 1.763*** 1.757*** 0.196*** (8.08) (7.35) (7.26) (14.94) Technological readiness −0.00282 (−0.22) Population density −0.438** −0.0394*** (−3.15) (−3.54) Crisis −0.970* −0.596 −0.743 −0.0315 (−2.13) (−1.31) (−1.52) (−0.53) _cons −20.82*** −22.13*** −25.15*** −2.441*** (−7.23) (−7.65) (−6.72) (−12.38) N346 346 346 Notes:Mixed effect probit model estimation on 14 determinants. Robust t statistics are in parentheses. For Model 14, all the variables are significant at 10 percent. Crisis is a control variable. Criterion 2 accepts all models with the correct sign as expected and statistically significant regressors (determinants). Only Model 14 satisfies these combined requirements. Criterion 3 selects the model with the lowest value of the Schwarz information criterion (SIC), Model 15. Criterion 4 selects the model with the lowest value of the Akaike information criterion (AIC), Model 16. BACE uses the Bayesian averaging of classical estimates. Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 15 of 19 context of Vietnam, policymakers should identify the sectors that critical to financial growth and enact proper policies for the enhancement of these sectors. We suggest that Ho Chi Minh City, currently the largest economic and financial center in Vietnam, should be considered for promotion as a GFC. Relevant policies should be formed and implemented. An institutional framework is required. We believe that the establishment of a dedicated institution responsible for the establishment of a GFC is essential. Second, Ho Chi Minh City needs to attract foreign investors by promoting it as a safe and reliable environment for development. Trade liberalization should be highly promoted and considered primary in the development of the financial market. The business environment should be considered important for doing business in the financial center, as seen in Hong Kong. The government of Hong Kong optimally opts not to interfere in business activities. What is more, newly enacted policies fundamentally favor trade liberalization, which is critical to the prosperity of Hong Kong. Along with the geographical and cultural characteristics, Vietnam is a cosmopolitan country and is accustomed to a variety of religions and cultures over decades. Under French colonial rule, Ho Chi Minh City was a center for financial services and naval operations. This early emerging trade link and strategic position were based on financial services such as insurance. On that basis, policymakers should take advantage of this experience as a solid foundation for future planning. Third, banking and finance are the lifeblood of the economy and even international trading, though they are not growth sectors. However, banking shapes and contributes to economic activities, building or even developing financial infrastructure and technologies. The government should commence with an understanding of financial services as a means of growth in other industries. For example, in the latest McKinsey report (2017), Ho Chi Minh City is ranked at the bottom among countries in the Asia-Pacific region in terms of the financial development which is measured by three distinct dimensions including investment opportunities, funding at scale and pricing efficiency. The financial market in Vietnam has insufficient diversity based on the following criteria: pricing efficiency, funding at scale, and investment opportunity. Despite the establishment of numerous new small and medium-sized enterprises, the capitalization of Vietnam’s stock market in 2019 captured only about 57 percent of the gross domestic product (World Development Indicators, 2019), which is the lowest among all the countries in the Asia-Pacific region. Despite having many deficiencies, Ho Chi Minh City also has offices of many international financial institutions, including leading global banks and insurance companies. Fourth, Asian financial centers significantly focus on asset management services, which supposedly strengthen individual net worth. Although they have had many setbacks requiring appropriate regulatory reform, such as tax policies and legalization of property rights, those international cities are still apparently lucrative and trustworthy for inward investments as well as mediating global private capital. In Vietnam, asset management services are uncommon at domestic and foreign institutions. More importantly, offering a variety of financial services is vital for asset management services. Fifth, the size of the capital market, including bonds, stocks, over-the-counter derivatives, and diverse financial instruments, demonstrates the importance and significance of the financial centers, meaning there are sufficient financial instruments and opportunities for foreign investors. In addition to bonds and stocks, the currency market is also important for any GFC. Having a comprehensive and liquid currency market offers numerous investment opportunities for domestic and foreign investors and institutions. The currency market lays a sound foundation for the development of third-party services, such as the notary and insurance. The financial center also facilitates the development of other emerging financial services such as mutual funds and exchanged traded funds. Moreover, the existence of a deep currency and capital market provides a benchmark and resilience for various financial derivatives. Nguyen et al., Cogent Business & Management (2020), 7: 1823597 https://doi.org/10.1080/23311975.2020.1823597 Page 16 of 19 Sixth, we consider that Vietnam has now been integrating closely with the globalization process. As such, the advancement of fintech (financial technology) for the nation is a fundamental and important development for sustainable economic growth and development in the future. The emergence of technology is strongly associated with the long-run target of the Vietnamese government to pursue the target of being a Smart Nation and national digitization, which aim to strengthen financial regulations and reduce bureaucracy. Accordingly, the role of fintech is a crucial element of establishing a financial center. Lastly, our theoretical and empirical evidence highlights the role of a skilled workforce in supporting the success and the maintenance of the financial center. Human capital enhancement is significant in the advancement of the economy. The technical demands undoubtedly require a large highly skilled workforce and professionals. Ho Chi Minh City has the advantage of being a top-notch city with an agglomeration of major universities and an advanced education system. According to the General Statistics Office, Ho Chi Minh City has an average of 50 college students out of every 1,000 residents, 80 percent of whom come from other provinces. Over the period 2011–2017 and thanks to universal education, the share of unskilled workers decreased from 38.5 percent to 21.9 percent, and the share of the more highly educated workforce grew from 18.9 percent to 25 percent. Though it has made many improvements, the education system in Vietnam is still considered outdated and in need of comprehensive reforms. University curriculums and programs are outdated, unfocused, relatively impractical. As a result, Vietnamese post-graduate students are not equipped with practical skill sets which are ready for employment. Our study has some limitations. First, we did not capture the physical location and global trading hours in the establishment of a GFC. Second, our analysis largely ignores transnational competition among financial centers, due to the lack of empirical analyses and data on the subject. These shortcomings offer a good starting point for future research on this important and interesting area of research. Funding The study was supported by the Youth Incubator for Science and Technology Program, managed by Youth Development Science and Technology Center, Ho Chi Minh Communist Youth Union, and Department of Science and Technology of Ho Chi Minh City, under contract no. 13/2019/HĐ-KHCN-VƯ. Author details Thang Cong Nguyen 1 E-mail: [email protected] Nhan Thien Nguyen 2 E-mail: [email protected] Duc Hong Vo E-mail: [email protected] 1 Business and Economics Research Group, Ho Chi Minh City Open University Vietnam, 97 Vo Van Tan Street, District 3, Ho Chi Minh City, Vietnam. 2 Vietnam-the Netherlands Economics Program, University of Economics Ho Chi Minh City, 1Bis Hoang Dieu Street, Phu Nhuan District, Ho Chi Minh City, Vietnam. 1 Citation information Cite this article as: Necessary conditions for establishing an international financial center in Asia, Thang Cong Nguyen, Nhan Thien Nguyen & Duc Hong Vo, Cogent Business & Management (2020), 7: 1823597. References Budd, L. (1995). 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