Accounting undergraduate Honors theses: Essays on international trade and finance

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The dissertation consists of three papers exploring the macroeconomic implications of heterogeneity of countries in financial development, economic interconnectedness via trade and financial linkages.

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University of Arkansas, Fayetteville ScholarWorks@UARK Theses and Dissertations 5-2012 Essays on International Trade and Finance Amat Adarov University of Arkansas, Fayetteville Follow this and additional works at: http://scholarworks.uark.edu/etd Part of the Finance Commons, International Economics Commons, and the Macroeconomics Commons Recommended Citation Adarov, Amat, "Essays on International Trade and Finance" (2012). Theses and Dissertations. 307. http://scholarworks.uark.edu/etd/307 This Dissertation is brought to you for free and open access by ScholarWorks@UARK. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of ScholarWorks@UARK. For more information, please contact scholar@uark.edu, ccmiddle@uark.edu.
ESSAYS ON INTERNATIONAL TRADE AND FINANCE
ESSAYS ON INTERNATIONAL TRADE AND FINANCE A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Economics By Amat B. Adarov Altai State Technical University Bachelor of Arts in Economics, 2003 University of Arkansas Master of Arts in Economics, 2007 May 2012 University of Arkansas
ABSTRACT The dissertation consists of three papers exploring the macroeconomic implications of heterogeneity of countries in financial development, economic interconnectedness via trade and financial linkages. Chapter 1 examines whether countries which are more centrally located in the global trade network have more synchronized stock markets. Global trade data is used to construct a novel measure of random walk betweenness centrality (RWBC), measuring the extent to which a country lies on random pathways in-between other countries and is therefore likely to be a conduit in the transmission of a shock across global markets. Based on a panel dataset of 58 countries over the period 1990–2000, the study finds that higher centrality of a country in the world trade network is indeed associated with greater stock market synchronicity, ceteris paribus. Chapter 2 uses aggregate macroeconomic experiences of 118 countries over the period 1994–2008 to establish benchmark relationships between macroeconomic fundamentals and levels of financial development of the banking sector, equity markets, and private bond markets. The analysis quantifies the extent to which de-facto financial development of emerging market economies (EMEs) deviates from the levels predicted by their macroeconomic stance. While financial markets in Latin American EMEs are found to be well aligned with their macroeconomic fundamentals, Asian EMEs exceed their reference levels, and European EMEs are found to be systematically financially underdeveloped. No support is found for the argument that these misalignments are caused by heterogeneity in institutional development. Finally, chapter 3 studies the properties and evolution of the product space—a network of relatedness between products. We use bilateral trade data for 187 countries to construct the product space and export specialization of individual countries over the period 1965—2000. The
study shows that the product space changed significantly during the 20th century and represents a highly uneven core-periphery structure. The highly interconnected core consists of three industries—chemicals, industrial machinery, and crude materials, each forming around 20% of all linkages. Product synergies that these “commanding heights” industries yield are strategically important for industrialization policies. Regression analysis confirms that specialization in these industries is associated with higher real income levels.
This dissertation is approved for recommendation to the Graduate Council Dissertation Directors: _______________________________________ Dr. Raja Kali _______________________________________ Dr. Javier A. Reyes Dissertation Committee: _______________________________________ Dr. Gary D. Ferrier
DISSERTATION DUPLICATION RELEASE I hereby authorize the University of Arkansas Libraries to duplicate this dissertation when needed for research and/or scholarship. Agreed __________________________________________ Amat B. Adarov Refused __________________________________________ Amat B. Adarov
ACKNOWLEDGEMENTS I am grateful to my dissertation co-chairs Javier Reyes and Raja Kali for their invaluable guidance and support. Special thanks are due to Gary Ferrier for insightful comments that helped improve the quality of the dissertation. I am in debt to all my friends and colleagues at the Department of Economics for making the years in the doctorate program so pleasant. My gratitude goes to all my friends around the world whose support was crucial to me. Finally, and most importantly, I am extremely grateful to my parents, Boris and Aleksandra, and my sister, Aradyana, for their continuous love and encouragement.
DEDICATION To my parents, Adarov Boris and Adarova Aleksandra.
TABLE OF CONTENTS Introduction ……………………………..………………………………………………………. 1 Chapter 1: Stock Market Synchronicity and the Global Trade Network: a Random-Walk Approach …………………………………………………….……….. 4 Chapter 2: Macroeconomic and Institutional Determinants of Financial Development: Implications for Emerging Markets …………………………………..... 43 Chapter 3: International Trade and Export Specialization Dynamics: a Network Perspective ………………………………………………………………..... 83 Conclusion …………………………………..…………………………………….……..…… 127
INTRODUCTION The dissertation consists of three papers exploring the macroeconomic implications of heterogeneity of countries in financial development, economic interconnectedness via trade and financial linkages. In Chapter 1, recent advancements in network theory are used along with conventional panel data techniques to analyze cross-border financial synchronicity and propagation of financial shocks. The central question is whether countries that are better integrated into the world economy and more centrally located in the global trade network have more synchronous financial markets. The paper uses a novel measure of random walk betweenness centrality (RWBC) to gauge the extent to which a country lies on random pathways in-between other countries in the global trade network and is therefore likely to be a conduit in the cross-border transmission of a shock resulting in higher stock market synchronicity. Based on a panel dataset of 58 countries over the period 1990-2000 the analysis demonstrates that higher centrality of a country in the world economy is indeed associated with higher synchronicity, ceteris paribus. The analysis also reveals that the global trade network has a well-defined core-periphery structure, where the highly interconnected core, comprising China, France, Germany, Italy, Japan, and the UK, is characterized by significantly lower synchronicity. The study has important policy implications as it demonstrates the importance of network centrality in the world economy for understanding financial synchronicity and global shock propagation. This contrasts sharply with conventional measures of economic integration, e.g. trade openness, which do not reflect the risks associated with economic partners. Therefore, the network-based approach may serve as an important tool for monitoring systemic risks and resilience of the world economy, as well as risk exposures of individual countries to financial shocks. 1
Chapter 2 examines an often-sounded claim that financial markets of emerging market economies (EMEs) are weak, and this is primarily the result of institutional impediments. Based on aggregate experience of 118 countries excluding EMEs over the period of 1994-2008 I find that financial development measured by financial market size can be consistently related to a country's general stage of economic development (proxied by real per capita income), economic openness, inflation, and inflation volatility. Then, I use a full sample of countries and original specification augmented by fixed effects for major EME groups to test if there is any residual effect pertinent to EMEs that is unexplained by macroeconomic fundamentals. Notably, while financial markets in Latin American EMEs are found to be well-aligned with their macroeconomic parameters, European EMEs are underperforming and Asian EMEs are overperforming relative to their expected levels. However, the quality of institutions does not contribute much to explaining these misalignments. Finally, in Chapter 3, bilateral trade data on 1006 product categories (SITC4 classification) for 187 countries over the period 1965-2000 is used to construct the product space—a network of relatedness between nodes-products, where the weight of a link between individual products is proportional to the probability that they are produced and exported together. Along these lines, export specialization of a country is a subnetwork of the product space formed by products in which it enjoys revealed comparative advantage (RCA). Network properties and evolution of the product space and export specialization patterns of individual countries are then examined in order to understand their implications for economic development. The paper demonstrates that the product space changed significantly during the twentieth century and evolved into a highly uneven core-periphery structure. Specifically, the highly interconnected core consists of only three industries—chemicals, industrial machinery, and crude 2
materials—each forming around 20 percent of all product linkages. Product synergies that these commanding heights industries yield are strategically important for industrialization policies. Regression analysis confirms that specialization in the commanding heights industries is associated with higher real income levels, controlling for other relevant factors. 3
CHAPTER 1 STOCK MARKET SYNCHRONICITY AND THE GLOBAL TRADE NETWORK: A RANDOM-WALK APPROACH The chapter is based on the paper “Stock Market Synchronicity and the Global Trade Network: a Random-Walk Approach” by Amat Adarov, Raja Kali, and Javier A. Reyes. 1.1. Introduction During the past decade, one of the most prominent themes sounded by policymakers, observers, and analysts of international economic development has been “globalization.” The world economy has become tightly knit via economic and financial interdependence among nations. Recently however, as the housing sector in the United States slowed sharply and turmoil erupted in many financial markets, a different theme has come to the foreground: “decoupling.” This refers to the apparent divergence in economic performance among different regions of the world economy. In the context of these opposing discussions it seems reasonable to ask, to what extent does integration into the global economy influence synchronized movements in markets around the world? Are there meaningful differences between groups of countries in this relationship? In this paper, we aim to cast some light on these issues by focusing on a narrow version of the questions above. Specifically, how does integration into the global economy affect synchronicity in financial markets? Our approach involves two methodological novelties. First, we construct a network of economic connectedness among nations by using the NBER–United Nations World Trade Database associated with Feenstra et al. (2005). We view individual 4
countries in the world trade network as nodes connected by bilateral trade linkages that are weighted by trade volume. Our assumption here is that the global trade network is a meaningful proxy for economic connectedness among nations, and that alternative proxies of the global economic network are likely to be closely related to the trade network, e.g. a network of bilateral capital flows is linked to trade flows via the balance of payments. As trade linkages are relatively stable over time, highly correlated with other cross-country linkages1, and we are primarily interested in stock market synchronicity over a relatively long time horizon (1990–2000), this seems particularly suitable. Second, we use a novel approach to computing country-level connectedness that is agnostic about the way in which each country receives and transmits shocks. Specifically, based on the notion of random walk betweenness centrality introduced in Newman (2005), for each country in our sample we compute its random walk betweenness centrality in the world trade network (RWBC). In brief, random walk betweenness centrality of node i is equal to the number of times that a random walk starting at s and ending at t passes through i along the way, averaged over all possible combinations of s and t in the network. In computing RWBC, we assume that the probability that a financial shock follows a particular link along its propagation path in the trade network is proportional to the intensity of bilateral trade flow the link represents. Hence, in the context of the world trade network, RWBC summarizes the connectedness of a country in the world economy and its ultimate exposure to a financial shock that can originate anywhere in the system and spread through the network in a manner that is not 1 There is increasing evidence that financial flows depend on the information afforded by trade in goods and are predicted by the same gravity model that captures trade in goods (Kalemli-Ozcan et al., 2001, 2003). Also, theoretically, a balance of payments view suggests integration in the goods and assets markets may go hand in hand (Rajan and Zingales, 1998; Fisman and Love, 2004). 5
necessarily optimal. An attraction of this measure is that it is agnostic about which path a shock actually takes between any particular “epicenter” country and a “target” country with regard to the transmission of shocks. Since the propagation mechanism of international economic shocks is not well understood, with different hypotheses vying for attention in the literature, this approach seems especially useful as it does not favor one transmission mechanism over another. We then examine whether a position of a country in the world trade network contributes to explaining financial synchronicity. Financial synchronicity is measured as comovement intensity between stock market indices of individual countries and the index of a benchmark economy (in our case, the USA and the Dow Jones Industrial Average) that is inspired by the work of Morck, Yeung and Yu (2000). If stock prices are based mainly on the capitalization of country-specific information we expect a low degree of synchronicity, while greater degree of interdependence will be reflected in higher synchronicity, ceteris paribus. Our basic hypothesis is then formulated as follows. Other things equal, a country that has a high measure of random walk betweenness centrality lies on more random pathways in- between countries and is therefore more likely to be affected by an external shock, regardless of the exact transmission mechanism, than a country with lower RWBC. This will be reflected in a higher level of stock market synchronicity of a high-RWBC country than a low-RWBC country. Our empirical analysis supports this hypothesis. Greater connectedness of an economy in the global trade network as measured by RWBC is associated with higher stock market synchronicity, after controlling for other relevant characteristics. However, we find that a group of nations that are highly central in the global trade network (we refer to them as the “core” of the network) are characterized by uniformly lower financial synchronicity than others. The high- RWBC core is comprised of the UK, Germany, France, Italy, China, and Japan. 6
In terms of the literature, only a few studies have attempted to take into consideration multilateral linkages in the global economy to explain stock market correlations. Forbes and Rigobon (2002) find that trade linkages are important factors for stock market dynamics and therefore a country’s susceptibility to financial crisis. Reinhart and Kaminsky (2008) analyze the three emerging markets that experienced financial crises in the late 1990s: Brazil, Russia, and Thailand, and suggest that financial turbulence in these countries spreads globally only when the shock reaches world financial centers and remains local otherwise. A recent paper by Kali and Reyes (2010) explicitly uses a network approach to international economic integration to study financial crisis episodes and associated contagion. A separate strand of the literature, pioneered by Imbs (2004, 2006), focuses on business cycle synchronization and uses simultaneous equations systems to disentangle the complex interactions between trade, finance, specialization, and business cycle synchronization. The overall effect of trade on business cycle synchronization is confirmed to be strong and a sizable portion is found to work through intra-industry trade. Our approach here is differentiated from the prior literature along several dimensions. Most importantly, we apply a network approach to understand stock market synchronicity. Using the network of global trade linkages enables us to use a completely multilateral approach to the propagation of financial shocks. Our measure of network position, RWBC, is novel to the literature and well-suited to the application. Second, unlike most studies we address stock market synchronicity over the long run rather than focusing on financial turmoil periods alone. This is an important distinction because financial crisis years are likely to be characterized by downward financial trends in stock markets resulting in a bias towards higher synchronicity values. Our empirical analysis is based on a panel dataset spanning the 1990–2000 period that includes both 7
tranquil periods and periods of economic crises. Third, we assess stock market synchronicity of a wide range of countries from diverse regions of the world and different in terms of economic development to ensure results are not driven by individual country properties2. The rest of the paper is organized as follows. Section 2 discusses our empirical strategy and data. Regression results are discussed in Section 3. Section 4 presents concluding remarks. 1.2. Research framework and data The question the paper focuses on is whether more interconnected economies have more synchronous stock market dynamics. In order to test this hypothesis, in this section we first develop a measure of stock market synchronicity and a measure of interconnectedness among individual economies – RWBC. We also recognize that other macroeconomic factors can potentially affect the degree of financial synchronicity and consider control variables deemed to be relevant in the related literature. Then, the benchmark econometric specification is described. 1.2.1. Stock market synchronicity Computation of a stock market synchronicity measure that is comparable across countries requires selection of a common benchmark country and associated stock market index to which all other countries are compared. We use the United States of America as the benchmark country and the Dow Jones Industrial Average (the DJIA) as the benchmark index3. Based on our 2 We would be remiss not to mention a rich strand of work in finance that uses cointegration methods to demonstrate international stock market interdependence. However, this literature does not concern itself with the channels of transmission and is therefore orthogonal to our focus. Noteworthy papers are Awokuse, Bessler and Chopra (2009) and Arshanapalli and Doukas (1993). 3 We use the DJIA index as it is the most widely recognized of the stock market indices. We realize it is often criticized, e.g. for being a price-weighted measure, which affects its accuracy as 8
methodology, the US is the most integrated country in the world economy as identified by centrality in the global trade network, and, in general, it is hard to find a better representative financial center by any standard. Stock market index data are obtained from the Bloomberg stock market database, where each data point represents a daily stock market index closing value. Our dataset comprises 58 countries between the 1990–2000 period. For each country in the sample we identify a representative stock market index and employ several techniques to compute its synchronicity with respect to the benchmark index, the DJIA. Our main analysis is based on two synchronicity measures, denoted further as Synch(FREQ) and Synch(R-SQ), that are inspired by the synchronicity measures of Morck, Yeung and Yu (2000). We also use a third viable measure denoted as Synch(CORR) as a robustness check4. Here we provide a detailed description of how the two baseline synchronicity variables are developed. Calculation of Synch(FREQ) involves two steps. First, we compute the frequency of stock market index comovements in year t for country i as a simple fraction: Comovementsi ,t Frequency i ,t  (1) Daysi ,t an index representing the entire stock market. However, the DJIA daily dynamics closely follow other widely recognized indices, e.g. the correlation coefficient between the DJIA and the S&P500 daily values over the period 01/01/1990 – 01/01/2000 is 0.996. Therefore, choosing one index as a benchmark over others should yield identical results. 4 The calculation methodology and empirical results for Synch(CORR) are discussed in Section 3.3 “Robustness checks”. 9
where Comovementsi,t is the number of days in year t in which stock market index of country i moves in the same direction as the DJIA, and Daysi,t is the total number of days for which both stock markets were operating in year t. Equation (1) provides an intuitive assessment of stock market comovements with the benchmark US equity market at daily frequency for a given year. For instance, in the case of Brazil and its representative stock market index, the Bovespa Index, comprised of the most liquid stocks traded on the Sao Paulo Stock Exchange, the frequency value in year 2000 is 0.6929, implying the Bovespa Index moved in the same direction as the DJIA 69.29% of days. Figure 1 lists the frequency of stock market comovements for all countries assessed in our study. [Insert Figure 1 here] However, the computed frequency variable is confined in the interval of [0,1] and therefore cannot be used in our regression analysis directly. In order to map frequency values to the real number set we apply the standard statistical technique of logistic transformation as follows:  Frequency i ,t  Synchi(,tFREQ )  Ln   (2)  1  Frequency i ,t  Hence, our first stock market synchronicity measure, Synch(FREQ), is merely a logistic transformation of stock market comovements frequency. Although it is a simple measure, we believe it is adequate for our purposes and is robust to most issues associated with alternative 10