INTRODUCTION
Problem statements
In recent years, globalization has become a significant concern, particularly regarding international economic integration and financial globalization across nations Researchers have extensively analyzed this phenomenon, highlighting its implications Mckinnon (1973) and Shaw (1973) emphasize the crucial role of finance in fostering technological innovation and driving economic development.
Research consistently supports the notion that financial liberalization plays a significant role in economic growth However, opinions on its impact vary, with some arguing that increased openness in local financial markets is essential for global economic integration This ongoing debate centers around whether financial liberalization has a positive or negative effect on economic growth, highlighting the need for adjustments in financial regulations.
According to Sachs and Warner (1995) and Rodrik (2000), advancements in technology and economic institutions have led to a reduction in the distance between countries, fostering increased international trade and investment This trend not only lowers costs for consumers and producers but also accelerates international economic integration A prime example of this integration is the World Trade Organization (WTO), formed by over 120 economies, alongside the nearly universally inclusive International Monetary Fund (IMF), which mandates currency convertibility among its members Notably, China's currency, the renminbi (RMB), met the criteria for inclusion in the IMF's Special Drawing Rights (SDR) basket as of November 2015, officially becoming a convertible currency on October 1, 2016 The SDR basket now comprises the U.S dollar (41.73%), Euro (30.93%), Chinese renminbi (10.92%), Japanese yen (8.33%), and Pound sterling (8.09%) One significant benefit of a freely convertible RMB is its low transaction costs, which can reduce the spread costs associated with buying and selling.
Economic integration varies among countries, with notable examples including the European Union (EU) and the Organization for Economic Co-operation and Development (OECD) in Europe, as well as the Asia-Pacific Economic Cooperation (APEC) and the Association of Southeast Asian Nations (ASEAN) in Asia Established in December 2015, the ASEAN Economic Community (AEC) aims to create a unified market among its member countries, including Vietnam, by promoting a single market and production base, competitive economic development, equitable growth, and integration into the global economy The AEC emphasizes the free flow of goods, services, investment, capital, and skilled labor, facilitating trade by reducing tariffs to 0% for several member countries Additionally, the AEC fosters a favorable investment environment, ensuring liberalization and protection for cross-border investments, and aims to enhance ASEAN capital markets through collaborative stock exchange initiatives This strategic positioning within the global supply chain presents new business opportunities and strengthens ASEAN's economic landscape.
The integration process necessitates that Vietnam and other countries open their local and domestic financial markets Current government policies aimed at market control face criticism for potentially hindering the efficient functioning and development of financial institutions Professor McKinnon's writings highlight that imperfect capital markets significantly obstruct the growth of developing nations due to economic fragmentation in institutions and policies, which in turn discourages effective resource mobilization Despite ASEAN, including Vietnam, having abundant natural resources and advantages in the global supply chain, the region has not developed as anticipated, prompting a need to examine the effects of financial liberalization on economic growth Recently, financial liberalization has garnered attention from scholars and policymakers, with numerous studies, such as those by Quinn (1997) and Klein & Olivei (1999), demonstrating a positive correlation between financial liberalization and economic growth However, other research, including works by Rodrik (1998) and Stiglitz (2000), challenges the notion that liberalization necessarily spurs growth.
This study aims to analyze the relationship between financial liberalization and economic growth in ASEAN countries, utilizing the Bekaert et al (2005) model with some modifications The KAOPEN index serves as the proxy for financial liberalization, and the research covers new data from 1990 to 2013, specifically focusing on ASEAN nations Vietnam, as a member of the ASEAN Economic Community (AEC), is particularly relevant as AEC developments will impact its economy While many studies on financial liberalization examine broader regions, few concentrate on ASEAN, despite scholarly consensus that financial liberalization can drive local financial market reforms and strengthen financial systems As Vietnam implements changes in financial policy due to AEC, there is heightened concern regarding the benefits and potential drawbacks of financial liberalization on economic growth This study seeks to determine if financial liberalization fosters economic growth in ASEAN from 1990 to 2013, with the expectation of finding positive evidence to support the integration process.
Research objectives
-To assess the impact of financial liberalization on economic growth in ASEAN countries
-To give some policy recommendation for ASEAN countries related to financial liberalization and economic growth.
Research questions
This study explores the effects of financial liberalization on economic growth in Southeast Asian countries through quantitative research using panel data It specifically seeks to answer two key questions related to this impact.
- Does financial liberalization prompt economic growth in ASEAN countries in the period 1990 – 2013?
- How does financial liberalization affect economic growth of cross countries?
1.4 The scope of the study
This research examines the financial liberalization process within the ASEAN Economic Community (AEC), focusing on member countries, including Vietnam As one of the five core principles of the ASEAN single market, the demand for an open financial market underscores the importance of this study, particularly given the limited existing research on financial liberalization in ASEAN nations By analyzing the correlation between financial liberalization and economic growth among AEC member countries, this study aims to fill a critical gap in understanding the economic dynamics within the region.
1.5 The structure of the study
This paper is structured into five main chapters The introduction is followed by a critical literature review in Chapter 2, which explores the relationship between economic growth, financial development, and the impact of financial liberalization on economic growth Chapter 3 details the regression model and research methodology used to empirically assess the effects of financial liberalization Chapter 4 provides an overview of economic growth and financial liberalization in ASEAN countries, along with descriptive statistics and an analysis of the study's results Finally, Chapter 5 summarizes the key findings, discusses limitations, and suggests areas for further research.
LTERATURE REVIEW
Economic Growth and Growth Theory
Economic growth refers to the positive change in a country's production of goods and services over time, typically measured by Gross Domestic Product (GDP) and Gross National Product (GNP) Nominal GDP includes inflation, while real GDP adjusts for it, providing a clearer picture of economic performance To compare economic growth across countries, GDP or GNP per capita is utilized, accounting for population differences This growth not only reflects an increase in productive capacity but also signifies an enhancement in the quality of life for the population Theories such as neoclassical, exogenous growth, and endogenous growth have been developed to better understand the dynamics of economic growth.
Neoclassical growth theory, as discussed by Barro (1991) and Howitt (1999), emphasizes the significant link between economic growth and technological advancements The Solow-Swan growth model illustrates the interplay between output, capital, labor, and technology, indicating that economic growth occurs with an increase in capital relative to labor until the economy reaches a steady state At this steady state, further increases in capital and labor do not lead to economic growth; instead, technological change becomes crucial for the economy to progress beyond this stagnation.
Endogenous growth theory, building on neoclassical foundations, explains long-term economic growth as a result of activities that generate new technological knowledge This theory aligns with the "Schumpeterian" vision of innovation, suggesting that growth rates are determined by internal factors within the economic system rather than external influences Key elements, such as the AK model, illustrate that growth can stem from a constant returns to scale production function This initial version of endogenous growth theory emphasizes the importance of opportunities and incentives for creating technological advancements.
The AK model highlights the significance of production technology, represented by A, and establishes a new production function, Y = AK, where H = K/L denotes human capital By dividing the equation by L, we derive y = Ak, demonstrating that the marginal productivity of capital A remains constant despite an increase in capital stock While the model assumes constant returns to scale, it does not explicitly address diminishing returns The AK theory emphasizes that capital is a crucial factor in production, which also enhances human capital, resulting in a linear increase in output corresponding to capital stock Furthermore, it asserts that an economy's long-term growth rate is influenced by its saving rate, indicating that a higher saving rate leads to greater economic growth, whereas higher population growth rates can result in lower income per capita.
Aghion and Howitt (1998) highlight key distinctions between the neoclassical model and endogenous growth theory, noting that in the latter, per capita growth can persist independently of external technological changes, and income convergence is not guaranteed, meaning poorer countries may not necessarily grow faster than wealthier ones Nonetheless, akin to the Solow model, endogenous growth theory also underscores the importance of factor accumulation and productivity enhancements in driving economic growth.
This study utilizes both neoclassical theory and the AK model to analyze the relationship between variables in a regression model that influences economic growth Specifically, neoclassical theory helps to interpret income convergence, while the AK model accounts for increases in total factor productivity.
Financial Development
Financial development is defined as an improvement in the quality, quantity and the efficiency of financial system This process involves the combination of many activities and institutions
Beck et al (2000) align with the Schumpeterian perspective that enhanced financial development drives economic growth by increasing total factor productivity Levine (2005) elaborates that financial development occurs when financial instruments, markets, and intermediaries are improved, leading to reductions in information, enforcement, and transaction costs.
Financial development drives economic growth through a well-functioning financial system, primarily via two key channels: increased financial deepening that boosts investment and improved resource allocation that enhances productivity growth.
Financial deepening refers to the rise in the ratio of financial assets to GDP, which enhances the availability of financial services across all societal levels This process fosters increased savings and capital accumulation, enabling investors to access diverse funding sources for their projects, ultimately leading to improved investment opportunities.
Financial development significantly enhances productivity growth by increasing saving rates, allowing savers to invest in the financial system and earn profits As capital flows into financial markets, intermediaries actively screen, select, and monitor potential capital users This process ensures that viable projects receive financing while unproductive ventures are left unfunded, highlighting the crucial role of financial markets and intermediaries in the efficient allocation of resources.
At the end of this process, productivity is increasing in the whole economy
According to Beck et al (2000) financial development could be measured by the size, the activity, and the efficiency of the financial sector
The size of the financial sector is measured using the "liquid liabilities ratio," which is calculated by dividing the sum of currency, demand, and interest-bearing liabilities of financial intermediaries and non-bank financial intermediaries by GDP This ratio serves as a proxy for financial deepening, encompassing various financial institutions Additionally, the activity of the financial sector can be assessed by comparing the roles of commercial banks to central banks, exemplified by the "Commercial-Central Bank Assets" indicator, which is derived from the ratio of deposit money banks' assets to the total assets of both deposit money banks and central banks.
The "ratio of credit to the private sector" serves as a key indicator of financial sector activity and resource allocation efficiency This measure is more effective than traditional monetary aggregates as it provides a clearer picture of the actual funds directed towards the private sector A higher ratio of domestic credit as a percentage of GDP signifies increased domestic investment and a more developed financial system Additionally, domestic credit to the private sector can be utilized as a proxy for private credit, highlighting its significance in economic analysis (De Gregorio & Guidotti, 1995).
Financial deepening refers to the enhancement of financial services accessibility across all societal levels, characterized by a rising ratio of financial assets to GDP This phenomenon is quantified using a specific formula that captures the relationship between financial assets and economic output.
Where M2 is measure of the money supply which including cash, checking, and saving account
It may also be calculated by the ratio as below
Financial deepening refers to the rising ratio of money supply to GDP, indicating an increase in liquid money This increase in liquidity typically fosters greater investment and creates more opportunities, ultimately driving economic growth Furthermore, as financial services become more accessible to individuals and households, essential services like health and education become easier to obtain, significantly contributing to poverty reduction.
Financial deepening, as identified by King and Levine (1993), is a key indicator of a country's financial development Their research, along with numerous other studies, demonstrates that financial deepening has a significant positive impact on economic growth.
Government policies aimed at regulating financial activities necessitate the implementation of various restrictions According to the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER), these restrictions are categorized into four distinct types.
Since the early 1970s, scholars have raised concerns about government policies aimed at controlling financial markets, arguing that such interventions hinder the efficient functioning and development of financial institutions while distorting domestic markets Mckinnon (1973) and Shaw (1973) critiqued these restrictive policies, highlighting the negative implications for economic growth Despite this, many governments believe intervention is necessary to mobilize resources and support activities that foster domestic economic development Reasons for these restrictive measures include fears of reliance on foreign capital, the desire to assist state-owned enterprises, and the need to prevent domestic savers from seeking higher returns in international markets.
Quinn and Toyoda (2007) argue that during the 1980s, many developing countries rejected the financial openness model proposed by developed nations due to concerns over dependency and the potential for economic colonialism By allowing foreign capital influx, these countries risked deepening their economic vulnerabilities Consequently, some nations chose to restrict international capital to protect their economies from exploitation, which has historically contributed to the wealth of developed countries and the poverty of developing ones From a developmental perspective, it is suggested that these nations should pursue import substitution industrialization, focusing on replacing foreign imports with domestic production to enhance their trade conditions, necessitating a degree of financial closure.
Financial liberalization encompasses the reduction of government regulations and restrictions in financial markets, often resulting in deregulation and the removal of controls According to Kunt and Levine (1996), this process typically involves deregulating interest rates and easing entry policies to encourage greater participation from private entities, which can lead to significant financial development, particularly in developing countries that have experienced substantial government repression in economic management Despite the enthusiasm for financial liberalization in some nations, challenges such as underperforming lending institutions necessitate further reforms Over the past two decades, many developing countries have undertaken reforms in their domestic financial markets in response to both domestic and international pressures In essence, financial liberalization refers to the "opening up" of economies to foreign capital and investments, allowing for the free movement of money in and out of countries.
Financial liberalization is shown to enhance the efficiency of financial markets, facilitating the transformation of savings into investments (Bumann et al., 2013) It improves resource allocation, provides easier access to risk diversification for firms and investors, and accelerates financial development, ultimately contributing to economic growth (Edison et al., 2004).
To evaluate a country's financial liberalization, researchers such as Bumann et al (2013), Quinn et al (2011), and Cline (2010) have developed various indicators that measure capital account openness globally These indicators are categorized into three groups: de jure, de facto, and hybrid indicators, with hybrid indicators combining elements of both de jure and de facto measures Most of these indicators are based on data from the International Monetary Fund's Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) Notable indicators for assessing financial liberalization include the "Share" derived directly from AREAER, "CAPITAL" by Quinn (1997), "KAOPEN" by Chinn & Ito (2007), and "KA" by Schindler (2009).
Empirical Studies
As above mentioned, the direct relationship between financial liberalization and economic growth is ambiguous
Numerous empirical studies highlight the theoretical perspectives supporting financial liberalization, with Quinn (1997) being one of the pioneers in examining its impact on economic growth Klein and Olivei (1999) analyzed capital account liberalization using the “Share” indicator, assessing financial depth changes from 1986 to 1995 across 82 countries, both developed and developing Their findings indicate a significant relationship between capital account openness and financial depth changes Furthermore, when they used financial depth as a dependent variable in a growth model, the results demonstrated that financial development positively influences per capita growth While capital account liberalization positively affects economic growth in developed countries, the same cannot be said for nonindustrial countries, where no evidence supports its contribution to economic growth.
Bailliu (2000) found that capital account openness promotes economic growth by fostering financial development, specifically in developing countries His study, which analyzed panel data from 40 developing nations between 1975 and 1995, examined the impact of foreign direct investment (FDI) and various capital flows on economic growth He emphasized the crucial role of domestic financial sectors in linking capital flows to growth The findings indicated that a well-developed banking system is essential for capital openness to positively influence economic growth; otherwise, in countries with underdeveloped banking sectors, capital inflows may lead to negative outcomes by diverting funds from productive investments to speculative activities.
Edwards (2001) found that the impact of financial liberalization on economic growth varies according to a country's development level He concluded that capital account openness negatively affects economic growth in low-income countries, while positively influencing growth in industrialized nations and wealthier emerging markets Utilizing both Quinn variables and share proxies for financial liberalization in his regression analysis of 60 countries from the 1980s, Edwards demonstrated that Quinn variables significantly correlate with increases in per capita income, although the share variable produced less consistent results.
In his 2008 study, Bonfiglioli introduced a novel method to assess the effects of financial liberalization on economic performance, emphasizing the importance of understanding the mechanisms through which financial openness influences economic growth By analyzing data from 70 countries over a 25-year period (1975-1999), he evaluated the impact of financial liberalization on total factor productivity The findings revealed an overall positive effect of financial liberalization on productivity growth, while its impact on investment was found to be negligible.
Bonfiglioli posits that financial openness enhances market integration in financial services, yielding gains similar to those from trading ordinary goods In countries with imperfect financial markets, services like screening, monitoring, and debt structuring become crucial for firms seeking external capital Variations in quality and specialization of financial products across countries create demand for trade, suggesting that financial liberalization can generate typical trade gains Additionally, the specialization of financial services enables firms globally to acquire these services at optimal prices This access allows firms to identify the most suitable financial instruments, contributing to increased allocative efficiency and explaining growth in total factor productivity (TFP), as noted by Galindo et al (2007) Furthermore, financial liberalization enhances international risk diversification, facilitating financing for riskier yet more productive projects, thereby significantly boosting aggregate TFP.
Several studies show that there is no relationship between financial liberalization and economic growth
One of the first studies that use the cross section countries data set to verify the financial openness and economic growth nexus, is the study of Grilli & Ferretti,
In a 1995 study analyzing financial liberalization's impact on economic growth, researchers found no evidence supporting the notion that such liberalization stimulates growth The study utilized a sample of 61 countries over the period from 1966 to 1999, conducting two sets of regressions with 181 and 238 observations, respectively The authors focused on the average growth of per capita income as the dependent variable across five non-overlapping five-year periods In their regression analysis, the "share" variable served as a proxy for capital account liberalization, while additional comparable variables, including current account controls and a system of multiple exchange rates, were sourced from the IMF.
Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER)
The study examines the impact of various factors, including political variables, initial GDP, and education levels, on economic growth and finds no support for the notion that capital account liberalization directly enhances growth Interestingly, some variables, such as "Share," "CurrAcct," and "MultEx," yield unexpected results However, the research does provide evidence that financial liberalization is linked to external discipline, which can help countries maintain lower inflation rates; specifically, countries with greater financial openness tend to experience less inflation than their more closed counterparts Additionally, the analysis of IFM indicators reveals that smaller public sectors and independent central banks positively influence economic growth and help control inflation, suggesting that capital account liberalization may have a beneficial impact on these factors.
Rodrik (1998) conducted a study involving 100 countries from both developed and developing regions, analyzing data from 1975 to 1989, and found no significant impact of capital account liberalization on economic growth His regression model, which measured real income per capita, indicated no relationship between financial openness and growth or inflation He expressed skepticism regarding the benefits of financial liberalization, noting that while macroeconomic policies can mitigate risks, they cannot eliminate them entirely With advancements in technology and communication facilitating global capital flows, the integration of domestic financial markets into the international arena raises questions about the advantages of accelerating financial liberalization for individual countries.
Kraay (1998) found no support for the hypothesis that financial liberalization promotes economic growth In his regression model, he utilized various proxies for financial liberalization, including the "Share" and Quinn’s capital account openness "CAPITAL" indicators, along with measures based on actual net capital flows The analysis, covering the period from 1985 to 1997, used output growth as the dependent variable and applied cross-sectional data with one observation per country Both ordinary least squares (OLS) regression and an alternative method using lagged capital account liberalization variables as instruments were employed The results indicated that neither the "Share" nor "CAPITAL" indicators had a significant impact on growth Kraay concluded that the lack of strong empirical evidence supporting the benefits of financial liberalization may be attributed to the increased volatility associated with it He further noted that countries could reap the benefits of financial liberalization only when supported by appropriate policies and a conducive institutional environment.
Hellmann et al (2000) highlight the negative impact of financial liberalization on economic growth, particularly within the banking sector They argue that increased competition resulting from financial liberalization reduces banks' profits, prompting them to engage in risky behaviors, referred to as "gambling." This phenomenon occurs when banks opt for riskier asset portfolios in pursuit of higher profits or bonuses, which can lead to significant losses if their gambles fail, ultimately jeopardizing depositors and insurers The study notes that recent trends in financial liberalization, such as deregulated interest rates and fewer restrictions on asset choices, facilitate banks' access to risky investments Consequently, this heightened competition diminishes franchise values, reducing banks' incentives to lend to sound projects and exacerbating moral hazard issues The authors assert that the process of relaxing restrictions on banking operations, including derivative trades and real estate lending, increases the likelihood of gambling activities within the sector They conclude that financial liberalization fosters intense competition among banks while granting them greater freedom in asset allocation and interest rate decisions, thereby elevating the risk of gambling in the banking industry.
Chapter Remarks
Financial liberalization significantly enhances economic growth by strengthening local financial markets, leading to more efficient resource allocation, increased foreign investment, higher savings rates, and improved risk diversification opportunities It also contributes to the development of financial systems, boosts trade and service volumes, and raises total factor productivity (TFP), thereby enhancing the competitive abilities of countries However, it is essential to address potential negative effects that may arise during the liberalization process, as there is a trade-off between benefits and unexpected consequences Despite the risks associated with financial transactions, engaging in globalization remains a crucial trend, necessitating the acceptance of these risks This study utilizes regression estimation techniques to analyze the impact of financial liberalization on economic growth in ASEAN countries, employing the KAOPEN index as a proxy for financial liberalization Unlike previous research, this study focuses on the dynamic ASEAN region, encompassing a sample of ten countries from 1990 onward.
Table 2.1: The role of financial Liberalization in economic growth
(B onfi gl io li, 2008), ( G al in do et al , 200 7), (H enry, 2007), (K os e et a l., 200 6), (K os e et al , 2 009 ) hy pothe sis
-More efficient international allocation of capital
Encourage investment in higher growth technologies
New technology and management techniques that help raising the efficiency of firms and give economy wide knowledge spillovers
( Mc Kin no n, 197 3 ), (Le vin e, 1996), (Qu in n, 9 7), (C la es sen s & G la es sner, 1998) hy pot hes is
Financial liberalization plays a crucial role in driving economic growth by strengthening local financial markets, which leads to more efficient resource allocation, increased foreign investment, and higher savings rates This process also fosters opportunities for risk diversification and the development of robust financial systems Additionally, financial liberalization boosts trade volumes and enhances total factor productivity (TFP), ultimately improving the competitive capabilities of a country Numerous scholars, including McKinnon, Levine, and Quinn, have supported this hypothesis, while recent studies by Bonfiglioli and others highlight the collateral benefits of financial liberalization, such as institutional strengthening and knowledge spillovers from foreign direct investment (FDI), which enable firms to invest in higher-growth technologies.
RESEARCH METHODOLOGY
Model Specification
Numerous studies, including those by Cline (2010), Edison et al (2004), and Quinn et al (2011), highlight the ongoing exploration of the positive effects of financial liberalization on economic growth and development over the long term These investigations empirically assess the relationship between financial liberalization and economic growth, utilizing growth models that incorporate variables such as investment levels, population growth, education, and initial GDP Authors like Beck et al (2000), Bekaert et al (2005), and Quinn and Toyoda (2008) have employed similar models in their research However, the results across these studies vary significantly, indicating the presence of diverse methodologies and contexts in the analysis of financial liberalization's impact.
Cline (2010) confirmed this model is the synthesis approach for calculation the impact of financial liberalization on economic growth The general form is: g = α + βX + ∑γZ
The annual growth rate (g), which can represent either total or per capita growth depending on the model, is influenced by financial openness (X) and various control variables (Z) Since population growth is exogenous to financial openness, the coefficient on openness remains applicable in analyses, regardless of whether total or per capita growth is used as the dependent variable in a specific study.
In the research that apply the model in which openness interacts with another variable such as domestic banking dept or education level, the form turns to g = α + βX + δ(XV) + ∑γZ
Where V is variable which can be domestic banking dept or education level
In some cases, to reach the synthesis of country estimates on the model parameters from a number of different studies, both the constant α and the control variables (
In the model, the variable ∑γZ can be excluded as it is considered exogenous to the effects of financial liberalization Consequently, the model simplifies to g = βX + δ(XV), retaining only the essential components βX and δ(XV).
Various models in the literature aim to quantify the impact of financial liberalization on economic growth The proxy variable for financial liberalization, denoted as X, varies among these models Over different time periods, the indicators of openness reflect changes in the level of economic openness, providing a consistent direction across various measures for specific countries.
Numerous empirical studies have explored the potential benefits of financial liberalization on long-term economic growth and development, as noted by Edison et al (2004) These studies establish a direct relationship between financial liberalization and economic growth based on growth models, yet they exhibit significant differences For instance, the choice of countries included in the sample varies, with some researchers focusing on industrial nations, while others examine developing countries or a combination of both Additionally, the time periods analyzed differ across studies, which is particularly relevant for developing countries experiencing recent financial liberalizations Methodological approaches also vary, with some studies utilizing cross-sectional, time series, or panel data, each facing limitations such as omitted variable bias and unobserved country-specific effects To address these issues, many researchers advocate for the use of dynamic panel data methods over traditional cross-sectional analyses.
Bekaert et al (2005) Presents the growth model in simple form as below
-Y is dependent variable which can be either, growth, Capital growth, Production, or Saving
-Q0 represents the logarithm of per capita real GDP in the beginning year and serves as an initial GDP proxy
-Xit represents the vector variables which control for different levels of long-run per capita GDP across countries
- Libi;t is main addition to the literature is to verify the effect of adding an liberalization variable, Libi;t; to the growth regression
Bekaert et al (2005) indicate that initial GDP can serve as a proxy for a stable state level of GDP, typically showing a negative correlation with conditional convergence, suggesting that lower GDP levels are associated with higher growth rates Additionally, life expectancy is positively correlated with economic growth, as longer life spans often align with increased economic activity While population growth can enhance the labor force, excessive growth may hinder per capita growth rates In some models, population growth shows a significant negative impact, whereas in others, particularly those using OLS standard errors, its effect is insignificant Quinn et al (2011) provide growth models for this study, starting with the base model from Quinn & Toyoda (2008), represented by the equation ΔGDP i,t = β0 + β1(ΔFinancial Globalization Variablei,t-1(2)).
+ β2(Income i,t-1) + β3(ΔTrade Openness i,t-1) + β4(ΔInvestment i,t-1) + β5(ΔPopulation Growth i,t-1) + unit effects + period dummies + εi,t
For i = 1,2,…,187, Where [Financial Globalization Variable] = “CAPITAL” indicator This proxy for financial liberalization and calculated by Quinn himself
The base model form Bekaert et al (2005) ΔGDP i,t= β0 + β1(ΔFinancial Globalization Variablei,t-1(2))
+ β2(Income i,t-1) + β3(LifeExpectancy i,t-1) + β4(ΔEducational Attainment i,t-1) + β5(ΔPopulation Growth i,t-1) + β6(Government Expenditure i,t-1) + period dummies
[Official Liberalization indicator]: Dating equity market liberalization Based on the assessment that foreign Investors officially have the opportunity to invest in
The Official Liberalization Indicator, developed by Bekaert et al (2005), assesses the openness of a country's capital account regarding domestic equity securities This indicator assigns a value of 1 to countries that are fully liberalized and a value of 0 to those that are not.
[IMF Capital account openness] is the measurement of capital account openness by employing the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER)
In this study, the Bekaert et al (2005) model is utilized to analyze financial liberalization in ASEAN countries, as it offers a simpler framework compared to Quinn's model While both models use the same control variables, Quinn's indicator is limited to data only up to 2004 Consequently, the study replaces Quinn's indicator with Chinn's indicator, which provides updated data available until 2013 and serves as a reliable proxy for financial liberalization.
Measuring Financial liberalization
Bumann et al (2013) identify three primary methods for measuring financial liberalization: capital account liberalization, equity market liberalization, and banking sector liberalization These categories reflect different aspects of financial freedom, with some studies, such as those by Quinn et al (2011) and Cline (2010), indicating a preference for capital account measures as proxies for financial liberalization Consequently, measures related to equity markets and banking sectors are less frequently utilized in research.
The efficiency of financial liberalization on economic growth is significantly influenced by the varying empirical measures used to assess a country's removal of restrictions on cross-border financial capital Scholars often develop their own methodologies for scoring and creating indicators that measure financial openness among nations Notable research in this area includes the works of Bumann et al (2013) and Quinn et al., highlighting the importance of consistent measurement in understanding the impact of financial liberalization.
According to Cline (2010) and further supported by research in 2011, capital account restrictions can be categorized into three main types: de jure, de facto, and hybrid indicators De jure indicators refer to formal regulations, while de facto indicators reflect the actual implementation of those regulations Hybrid indicators combine elements of both de jure and de facto measures, providing a comprehensive view of capital account restrictions across various countries.
De jure indicators of financial openness assess legal restrictions on international capital transactions, primarily derived from the International Monetary Fund's (IMF) Annual Report on Exchange Arrangement and Exchange Restrictions (AREAER).
The Annual Report on Exchange Arrangement and Exchange Restrictions (AREAER), published annually by the International Monetary Fund (IMF) since 1950, serves as a key indicator of a nation's adherence to international financial law and practices This report is essential for assessing financial openness, making it a vital resource for understanding global economic dynamics.
The AREAER is a comprehensive research report by the IMF that analyzes the evolving economies of over 180 countries worldwide Utilizing data from official staff visits and consultations with national authorities, it synthesizes information on regulations governing capital flows and the distinctions between resident and non-resident transaction agents Since its inception in 1950, AREAER has been published in book format, detailing the laws and regulations countries enforce to manage cross-border financial transactions and the resulting proceeds between residents and non-residents.
From 1967 to 1996, AREAER introduced a new edition featuring a summary table titled “Summary Features of Exchange and Trade Systems in Member Countries.” This table illustrated the existence of restrictions on residents' payments across different types of current and capital accounts According to Edison et al (2004), the specific row in this table provides critical insights into these restrictions.
Restrictions on payments for capital transactions play a crucial role in a country's capital control regulations, serving as a foundation for assessing financial liberalization Chinn and Ito (2007) categorized these controls into four main groups: the use of multiple exchange rates, enforcement of restrictions on current account transactions, limitations on capital account transactions, and mandatory surrender of export proceeds They noted that capital account restrictions, often combined with current account restrictions, are frequently utilized to create a dummy variable indicating the presence of such restrictions Similarly, Quinn et al (2011) highlighted that these table indicators can be easily transformed into level measures, typically in binary form (0/1), for use in regression analysis This methodology has been employed by various researchers, including Grilli and Ferretti, in their studies.
Since 1997, the AREAER has adopted a new tabular format that enhances the presentation of information regarding capital account transactions This updated structure features 13 distinct categories, highlighting the diversity of restrictions imposed by different countries As a result, it offers a more comprehensive view of capital account restrictions, including various investor types and asset categories.
As demand for a more exactly indicator is generated, Quinn (1997) developed a new coding rules to capture the enforcement of controls on both the capital account and the current account
He carefully read the text and analysis the summary table of AREAER
In his study, he distinguished the enforcement of control between “receipts” and
Capital account transactions are categorized into two dimensions: "inward" and "outward" transactions, allowing for a clearer analysis of payment flows To assess the level of control over these capital account transactions, a specific variable was developed.
The "CAPITAL" metric is evaluated on a 0-4 scale across two dimensions, with scores ranging from (0) to (2) A score of (0) indicates that payments are prohibited, while (0.5) applies to laws imposing quantitative or regulatory restrictions, such as licensing requirements A score of (1) signifies that transactions require authority approval or are subject to significant taxation, whereas (1.5) reflects a scenario with lighter tax burdens Finally, a score of (2) denotes a situation where transactions are free from any constraints or taxes.
Current account transactions are analyzed using a consistent method divided into four dimensions: two for goods and two for services These transactions are then scored on a scale from 0 to 8, and this scoring is designated as CURRENT.
The seventh dimension, known as AGREE, measures the intensity of domestic laws by reflecting the influence of international legal agreements that limit a nation's ability to restrict exchange and capital flows Countries participating in international economic organizations typically commit to liberalizing their financial markets, making AGREE a gauge of a government's dedication to maintaining open financial markets Scored on a 0-2 scale, AGREE assesses the extent of restrictions, contributing to a comprehensive OPENNESS measure that ranges from 0 to 14 Additionally, the CURRENT indicator from Quinn & Toyoda (2008) has been rebranded as FINANCIAL CURRENT (FIN_CURRENT), with each measure transformed into a 0-100 scale using the formula 100*(CAPITAL/4).
100*(FIN_CURRENT) The data collected from 1949 to 2004 which contains information for 94 countries
According to Chinn and Ito (2007), the IMF's AREAER may inadequately assess the intensity of capital controls, as it primarily emphasizes the extent and nature of restrictions across various countries Consequently, the variables used by the IMF are overly broad and fail to capture the diverse forms of actual capital controls effectively.
Capital control policies can often be implemented without clear objectives, leading to instances where the private sector circumvents these restrictions, rendering them ineffective Researchers can analyze financial integration across countries to identify de facto restrictions on capital transactions, although distinguishing between de jure and de facto controls remains challenging To address this, Chinn and Ito (2007) introduced the capital account openness index, known as KAOPEN, which combines the extent and intensity of capital controls KAOPEN is calculated using four variables: varying exchange rates, barriers in current account transactions, barriers in capital account transactions, and requirements for surrendering export proceeds The index scores financial liberalization on a scale from -1.888895 (completely closed economy) to 2.3896685 (full openness) The strength of the KAOPEN index lies in its focus on the intensity of capital controls, allowing it to reflect nuanced restrictions, such as a country being open to capital account transactions while imposing limits on current account transactions or employing multiple exchange rates Thus, KAOPEN measures openness in both capital and current accounts, alongside multi-exchange rate policies and export proceeds requirements.
Endogenous Problem from the relationship between Financial Liberalization and
Bumann et al (2013) highlight criticisms regarding endogeneity issues in their study, which are challenging to address convincingly within the existing literature Similarly, Bekaert et al (2005) acknowledge significant endogeneity concerns in the relationship between financial liberalization and economic growth The difficulty lies in determining whether liberalization is an exogenous political decision or a response to anticipated growth opportunities, as finding a relevant instrument for liberalization is nearly impossible While attempting to control for growth opportunities directly is a potential solution, it poses challenges since any locally correlated variable might suggest an increase in growth opportunities due to planned financial market liberalization Consequently, incorporating growth opportunity variables into the regression analysis may not yield informative results An alternative approach is to utilize exogenous growth opportunity variables as part of the solution.
The variable "growth opportunities" (GO) is defined by the perspective that each country's economy consists of industries with fluctuating growth potential It is assumed that the price-to-earnings (PE) ratios of global industry portfolios indicate these growth prospects By integrating the PE ratios with the three-digit Standard Industrial Classification (SIC) and the United Nations Industrial Development Organization (UNIDO) classifications, an implied measure of growth opportunities for each country is established.
Bekaert et al (2005) demonstrate that incorporating the growth opportunities (GO) variable into a growth regression yields significant results, indicating that GO is a reliable measure of growth prospects When comparing the growth effects of liberalization with and without the GO variable, the coefficients remain largely consistent, at 0.92% and 0.97% respectively, along with their statistical significance Although this analysis may not fully address the endogeneity problem, it enhances confidence that the findings are not primarily influenced by such issues.
According to Beck et al (2000) and La Porta et al (1998), the legal origin of countries serves as an effective instrumental variable (IV) for financial development, helping to address potential simultaneity bias Legal systems can be categorized into four main types: English common law, French civil law, German civil law, and legal systems based on communism or Islamic law The influence of European legal origins has been widespread due to historical factors such as colonization and occupation For example, the English legal system was adopted in numerous Asian and African nations, as well as in Australia, New Zealand, and North America Similarly, French civil codes were disseminated throughout Indochina, Africa, and the Caribbean via colonization The German civil code notably impacted countries like China and Taiwan, influenced Japan's legal framework, and subsequently spread to Korea.
The legal origin plays a crucial role in shaping the overall legal environment, particularly regarding investor protection Enhancing investor protection can significantly contribute to financial development and stimulate economic growth When foreign investors actively participate in local economies, it fosters financial reforms, reduces financial constraints, and lowers the external finance cost of capital.
Financial reform that strengthens the legal framework and protects investors is a key driver of economic growth A robust legal environment fosters stability, contributing to a consistent GDP growth trajectory.
The English legal system is different from other civil law countries, since the
The English legal system, based on common law, emphasizes resolving specific circumstances and offers robust institutions, an attractive investment climate for foreign investors, and strong investor protection In contrast, countries with a French legal origin tend to have weaker rights for shareholders and creditors This is reflected in their accounting standards, as these countries typically produce less comprehensive financial statements for companies.
Measurement of Variables
The regression model for this study is suggested as follow:
Y = β0 +β1kaopen1+ β2lgdp90+ β3gconsum+β4second+ β5Pop
-Y is logarithmic growth in real GDP per capita
- kaopen1 Proxy for financial liberalization
- lgdp90 is logarithm of Initial GDP, that is the log real per capital GDP level in beginning year of data set
- gconsum is Government consumption where is the ratio of government consumption to GDP (Government consumption / GDP)
- second is defined as Secondary school enrollment ratio
- Pop is Population growth rate that is the growth rate of total population
- llife is Logarithm life expectancy of total population
- dlegal is dummy variables to separate countries to the legal origin dlegal = 1 if English common law origin countries dlegal = 0 if French civil law origin countries
In numerous empirical studies, the dependent variable Y represents the economic growth rate, specifically measured as the rate of real per capita GDP growth derived from national accounts data Additionally, economic growth can be assessed through productivity growth, which is based on the neoclassical production function incorporating capital (K), labor (L), and total factor productivity (A), with the capital share denoted as (α) Consequently, the aggregate output can be expressed through this framework.
Due to the challenges in calculating the capital share (α), many studies utilize the growth rate of GDP per capita as a key dependent variable Gross Domestic Product (GDP) serves as a widely recognized indicator of a country's total economic production GDP per capita, which represents the average economic output per person, is a crucial metric that reflects social and economic changes By dividing GDP by the population of a specific country or region, this measure provides an initial insight into economic well-being Since total output equates to total income, income per capita can sometimes substitute for output per worker or labor productivity Consequently, economists and various social scientists often prioritize GDP per capita as a fundamental measure of economic growth.
In this study, following Bekaert et al (2005), the dependent variable is defined by the logarithmic growth in real GDP per capita for country i and year t
Y i,t = ln((GDP i,t /POP i,t )/(GDP i,t-1 /POP i,t-1 ))
Chinn & Ito (2007) introduced the KAOPEN index, a new measure of capital account openness derived from AREAER tabulation, which assesses both the extent and intensity of capital controls This study utilizes the KAOPEN indicator as a proxy for financial openness, as it spans the years 1970 to 2013 and is readily available, unlike Quinn’s CAPITAL data, which only extends to 2004 Although Quinn’s CAPITAL indicator often yields more significant results in regression estimations, KAOPEN provides a more comprehensive view of financial openness over a longer period.
In this study, the KAOPEN measure is utilized as a proxy for financial liberalization due to its availability and continuous updates, unlike Quinn's CAPITAL index, which ceased updates after 2004 Additionally, Schindler's (2009) KA index was not selected because it lacks data for Cambodia, Myanmar, and Lao PDR, and it only begins from the year 1995.
Initial GDP Logarithm of real per capita gross domestic product in the year of beginning of data set (1990)
The simple conditioning information set incorporates the logarithm of initial real per capita GDP to account for convergence, highlighting that countries with lower GDP levels tend to experience higher growth rates (Bekaert et al., 2005).
Government consumption as a percentage of gross domestic product (GDP) is a key indicator that reflects total government expenditures on goods and services, including employee compensation Economic theory suggests that government spending can significantly influence economic performance, with many economists agreeing that lower levels of government spending may enhance economic growth in certain contexts, while higher spending can also yield positive effects in others When government spending is non-existent, economic growth tends to stagnate, as essential functions such as enforcing contracts, protecting property rights, and developing infrastructure become challenging without government intervention.
Bekaert et al (2005), Beck et al (2000) agree that the ratio of government expenditure to GDP as indicators of macroeconomic stability
The secondary school enrollment ratio, which measures total enrollment regardless of age against the population of the corresponding age group, serves as a key indicator of educational quantity at the secondary level Other relevant metrics include average years of schooling, adult literacy rates, and education spending Numerous studies suggest a positive correlation between educational quantity and economic growth, while the quality of the labor force, as indicated by international mathematics and science scores, also significantly impacts economic development Consequently, enhancing both the quantity and quality of education is essential for fostering economic growth.
Beck et al (2000) show that the average years of schooling as an indicator of the human capital stock in the economy
The growth rate of the total population encompasses all residents, regardless of their legal status or citizenship According to the Solow neo-classical growth model, the economy can be categorized into two scenarios: steady state and transitional effects In the steady state, increased population growth tends to reduce income per capita, while having no impact on the growth of per capita income Consequently, this suggests that population growth can enhance overall economic growth However, during the transition to the steady state, higher population growth negatively affects per capita economic growth.
Bekaert et al (2005) highlight in their empirical studies that while certain models indicate a significant negative relationship between population growth, other models using OLS standard errors reveal that population growth is statistically insignificant.
Life expectancy at birth reflects the average number of years an individual is expected to live based on current mortality rates and is influenced by factors such as occupation, nutrition, heredity, and physical health The relationship between life expectancy and economic growth is significant, particularly through the lens of demographic transition theory, which suggests that an initial increase in population precedes improvements in life expectancy As life expectancy rises, population growth tends to slow, fostering the accumulation of human capital and ultimately leading to sustained income growth A high life expectancy is thus a critical driver for transitioning toward long-term economic development.
Bekaert et al (2005) demonstrate that life expectancy plays a crucial role in economic growth, as evidenced by its significant positive coefficient in their regression model Their findings indicate a strong correlation between longer life expectancy and increased economic development.
Di is dummy variables to separate countries to the legal origin dlegal = 1 if English common law origin countries dlegal = 0 if French civil law origin countries
According to Beck et al (2000) and La Porta et al (1998), the legal origin of countries serves as an effective instrumental variable (IV) in growth models to address potential simultaneity bias This is because the legal origin is not only exogenous to economic growth but also has a correlation with financial development.
Table 3.1 The expected sign of variables in model
CONCEPT VARIABLES UNIT EXPECTED SIGN
Logarithm of Growth rate of real GDP per capita Y
Liberalization KAOPEN indicator kaopen1 Positive
Control Variables Logarithm of Initial GDP in year 1990 lgdp90 Negative
Second school enrollment Second % Positive
Population Growth rate Pop % Positive/Negative
Logarithm of Life expectancy at birth Llife Positive
Dummy Variable legal origin Dlegal binary number Positive
Data collection
This study utilizes eight variables to estimate a regression model, focusing on the growth rate of real GDP per capita The control variables used in this research are primarily sourced from the World Development database, encompassing a comprehensive list of available countries.
The World Bank's database from 1990 to 2013 reveals gaps in data availability across various countries, particularly concerning secondary school enrollment ratios and government consumption This inconsistency results in scattered missing data for several indicators throughout the years.
Financial liberalization indicator is KAOPEN1 collected from the website of Chinn
Retrieved on March 20, 2015 from: http://web.pdx.edu/~ito/Chinn-Ito_website.htm
The legal origin variable is gathered in the appendix of Bekaert et al (2005)
The collected sample contains 10 member countries of ASEAN in 24 year, from
Model Specification
This section focuses on econometric methods and estimation techniques to address research inquiries, utilizing the framework established by Bekaert et al (2005) The proposed regression model for this analysis is outlined as follows:
Y = β0 +β1kaopen1+ β2lgdp90+ β3gconsum+β4second+ β5Pop
Generally, The Pooled OLS, Fixed effects method (FEM) and Random effects model (REM) are three common methods estimating models for panel data
Due to the challenges in identifying a suitable proxy for financial liberalization, this study utilizes a single indicator, KAOPEN1, to represent financial liberalization Consequently, only one model is employed for analysis The estimation techniques applied include Pooled OLS, Fixed Effects Method (FEM), and Random Effects Model (REM).
Chapter Remarks
This chapter focuses on identifying an appropriate empirical model, selecting relevant variables, and determining data collection methods to explore the relationship between financial liberalization and economic growth The selected model aligns with the framework established by Bekaert et al (2005), with KAOPEN1, developed by Chinn & Ito (2007), serving as the proxy for financial liberalization The analysis employs estimation methods including pooled OLS, random effects model (REM), and fixed effects model (FEM) The anticipated outcome is a significant positive coefficient for KAOPEN1, indicating that financial liberalization promotes economic growth.