America: Growth,
Development and Crises
Juan Sebastin Bernal
s1633201
Supervisor: Dr. Natascha A.J. van der Zwan
Second Reader: Dr. Marike Knoef
1 i n t r o d u c t i o n 6
2 t h e o r y 12
2.1 Introduction . . . 12
2.1.1 Financialization as a regime of accumulation 12 2.1.2 Financialization and shareholder value . . 13
2.1.3 Financialization of the everyday . . . 13
2.2 Financialization and Economic Stability . . . 14
2.2.1 Increased role of the financial markets . . . 14
2.2.2 Increased role of the financial motive . . . 17
2.3 The development of financialization and its con-sequences . . . 20 2.3.1 Phase 1: 1980-1990 . . . 20 2.3.2 Phase 2: 1990-2000 . . . 22 2.3.3 Consequences . . . 22 2.3.4 Hypotheses . . . 24 3 r e s e a r c h d e s i g n 26 3.1 Methodology . . . 26
3.2 Variables and Operationalization . . . 27
3.3 Limitations . . . 35 4 r e s u lt s 36 4.1 Descriptive Statistics . . . 36 4.1.1 Univariate Analysis . . . 36 4.1.2 Bivariate Analysis . . . 44 4.2 Inferential Analysis . . . 45
4.2.1 Financialization and economic crises . . . . 45
4.2.2 Financialization and economic growth . . . 47
5 c o n c l u s i o n s 50
Figure 1 GDP growth . . . 7
Figure 2 Unemployment . . . 8
Figure 3 Unemployment youth . . . 8
Figure 4 Principal Agent Relation . . . 18
Figure 5 Interest Rates France, Germany, Japan, United Kingdom And USA . . . 22
Figure 6 LAC regions . . . 33
Figure 7 GDP Per Capita . . . 38
Figure 8 Lending Interest Rate Brazil . . . 39
Figure 9 Lending Interest Rate Peru . . . 39
Figure 10 Lending Interest Rate Uruguay . . . 40
Figure 11 Box Plot Trade . . . 42
Figure 12 Evolution FIRE . . . 43
Figure 13 Correlation Matrix . . . 43
Figure 14 Summary Table . . . 50
Figure 15 Financialization cycle . . . 53
Table 1 Variables . . . 34
Table 2 Summary statistics . . . 37
Table 3 Summary statistics 2 . . . 40
Table 4 Logit Models . . . 46
Table 5 Marginal Effects . . . 47
Table 6 Panel Data Fixed Effects . . . 49
GDP Gross Domestic Product
NFC Non Financial Corporation
LAC Latin America and the Caribbean
CEPAL Comisin Econmica para America Latina y el Caribe
IMF International Monetary Fund
CEO Chief Executive Officer
1
I N T R O D U C T I O N
”The interconnectedness of peoples, countries, and economies around the globe is a development that can be used as effectively to promote prosperity as to spread greed and misery. The same is true for the market economy: the power of markets is enormous, but they have no inherent moral character. We have to decide how to manage them. Joseph E. Stiglitz, The Price of Inequality (preface) Financialization along with globalization and neoliberalism is one of the most important processes that shape the new world economics (Epstein, 2005), politics, and society. Despite its im-portance, scholars have recently started to understand what are its causes and consequences. Moreover, there is no agreement among academics about its definition. In essence, it is a ”pat-tern of accumulation in which profits accrue primarily through financial channels rather than through trade and commodity production” (Krippner, 2005, p. 174). Financialization then is the process by which finance gains importance over tradi-tional ways of production and even replaces them. This trivial change in the modes of production has brought with it some unintended consequences that range from everyday life to eco-nomic growth and even power redistribution that I will explain in the next chapters.
Perhaps the best way to understand financialization and its consequences is by looking at the outcomes of the last finan-cial crisis, the subprime mortgage crisis of 2008-2009. The ex-cess of debt in the American households, the predatory lend-ing practices of the financial markets, and soft financial regu-lation (all symptoms of financialization) caused this crisis. Al-most eight years after the crisis we can still feel its effects on economic growth, inequality, and unemployment. Economic growth measured as Gross Domestic Product (GDP) per capita had a tremendous contraction not only for industrialized coun-tries but also in developing ones. Figure 1 shows how the crisis decreased the rate of growth of the world’s GDP per capita
Figure 1: GDP growth
from 2.67% in 2007 to -3.24% in 2009 it is a reduction of almost 600 basis points. This crisis then had consequences for the eco-nomic stability of countries but above all, it affected citizens worldwide. First, industries that were not in the financial sec-tor reduced their income rising unemployment. Pension funds suffered massive losses affecting the financial stability of pen-sioners. And finally, the turmoil of the financial crisis had a vast redistribution impact affecting most of all the vulnerable population (the 99%) not the ones at the top (the 1%). As a consequence, these problems caused movements all around the world like ”Los Indignados” in Spain or ”Occupy Wall Street” in the United States of America, which shows the outrage and suffering created by the financial crisis (Stiglitz, 2012).
Financialization literature has focused on large political economies (Krippner, 2005; Crotty, 2005; Dumnil & Lvy, 2001), leaving aside the effects that this process could have in developing countries. This process could even have worst repercussions in emerging nations (as most of the LAC region). To show these figures 1, 2 and 3 illustrates descriptive statistics that could be an indication of how the crisis affected the LAC re-gion differently than the world. It is evident then that LAC suffered almost the same effects as the world: contraction in GDP, increased unemployment, and greater inequality. What is interesting then is the rate of recovery after the crisis. In the aftermath of the crisis, LAC had a faster recovery than the
Figure 2: Unemployment
world in the initial years, but then the crisis had a ”stickiness” force (the effect prevailed more) in LAC that curtailed economic growth. Compared to the global economy LAC is lagging while the world is finally emerging out of the crisis. In other words, it is evident from figures 1, 2 and 3 that LAC’s economic growth had a change of trend before and after the crisis. The same goes for unemployment (especially for the youth unemployment -15 to 24 years old), and inequality. Before the crisis, there is a steady decrease in these variables (less inequality and unem-ployment) until the crisis where both increase (more inequality and unemployment) but the ”stickiness” of the crisis persists in LAC contrary to the global trend.
Scholars have studied this process from different disciplines, two, in particular, have opposed points of view about this sub-ject. On one hand, we have the neoclassical economic litera-ture in which financialization plays a critical role in economic growth. According to them, finance is not the responsible for most of the economic crisis but instead it alleviated a situation that could have been worst. Even one of the most recognized economist against neo-classical economics, Joseph Stiglitz, has acknowledged its importance but not without warning us about its possible consequences (see the quote at the beginning of this chapter). On the contrary, critical scholars of financialization have shown how it has led to a fictitious economy, stagnating wages, increasing inequality, moving rents from the real sector to the financial sector, and in general to a more unstable econ-omy. Hence, it is not clear what are the consequences of finan-cialization for the economic growth and stability of a country. What I intend to do throughout this thesis is to understand what is the influence of financialization for the economic stabil-ity of LAC countries? This dissertation would then address to some questions that remain unclear from the literature: what role does financialization play in an economic crisis? And what are the consequences of financialization on economic growth? It is evident then that financialization is an important process studied by different disciplines and points of view. But as I mentioned before, there is a gap in the literature, the develop-ing countries have been left out of the discussion even though the effects of financialization could be worst in an already un-stable environment. I plan to answer these questions using a cross-national quantitative study of 18 countries from LAC; the
period of study is from 1990 to 2014. So the contribution of this article would be the study of this phenomenon in LAC. But why is it important to study this process in LAC? LAC is an interesting case study for financialization especially in the last decade of the 20th century and the first decade of the 21st century. LAC countries suffered a structural change promoted by the World Bank and The IMF encouraging macroeconomic policies that supported the financialization process.
During the 1980s, most LAC governments experienced an eco-nomic crisis caused by high indebtedness and increased inter-est rates (Pastor, 1987). To solve the liquidity problem and bal-ance payment they used the IMF and World Bank short-term financial assistance. Most Latin American countries were re-luctant to use their help as they saw them as a lender of last resort (Moffit, 1983, p. 124) because of the conditions attached to the loan that included reduced government spending and tight macroeconomic policies. According to Diaz (1981) and Lichtensztejn (1983) some of the conditions established by the IMF included: the devaluation of the local currency to have a competitive advantage over the exports, limiting the access to credit and public borrowing, removal of subsidies, policies that encourage international trade (like open markets, reduced tariffs and less imports control), encouragement of foreign in-vestment, and, finally wage stagnation. The IMF and World Bank assistance, according to Crotty, slowed the world total ag-gregate demand (GDP) by ”eroding the necessary institutional foundation for high growth in developing countries” (2005, p. 89). He goes so far as to blame these institutions for working not only for the stabilization of the monetary system, but to im-prove the economic conditions and increase the rents perceived by financial institutions: ”Saturated with neoliberal ideology and virtually run by the US Treasury Department on behalf of Wall Street, these institutions forced the implementation of slow-growth macro policy on client states in order, they said, to restore foreign investor confidence” (2005, p 89). Almost 20 years after the IMF and World Bank intervention we have the opportunity to study their market-oriented reform that en-hanced financialization throughout LAC and study on how this process affected LAC as a whole. This thesis then aims to eval-uate the financialization of LAC and give the analytical tools to design future strategies that could, if necessary, correct market forces so that they work to the benefit of most citizens.” (Stiglitz,
2012, preface).
To sum things up for this chapter I have shown what is the importance of financialization by highlighting the possible in-fluence it had over the last financial crisis. I also have explained some of the gaps that exist in the literature and addressed the relevance of studying this phenomenon in LAC. Thus, my re-search question is what is the influence of financialization for the economic stability of LAC countries? Supported by two subquestions (1) what role does financialization play in an eco-nomic crisis? And (2) what are the consequences of financial-ization on economic growth? The rest of the chapters are orga-nized as followed. In the second chapter, theory, I will lay out what the conflict between critics and the neoclassical economist about financialization explaining the different points of view. In Chapter 3, Research design, I will explain the research tools and quantitative methodology used for analysis of the informa-tion as well as the definiinforma-tion of all the variables. Chapter 4, Results, will focus on the results obtained from the descriptive statistics and the regressions. And finally in the last chapter, Conclusions, I will analyze the results and give the findings of this thesis.
2
T H E O R Y
2.1 i n t r o d u c t i o n
In this section, I will use previous studies on financialization and economic development from different disciplines to under-stand financialization. This task will be complex because there are contradicting theories on financialization and its relation-ship with economic stability. Thus, the possible consequences of financialization remain unclear. There is no agreement about the definition of financialization and what processes it encom-passes. However, scholars have used different definitions to analyze it from various points of view, but all of these defini-tions show different sides of the same phenomenon. In this sense, van der Zwan (2014) identified three distinct approaches to financialization.
2.1.1 Financialization as a regime of accumulation
The first approach is financialization as a regime of accumu-lation. One of the most representative scholars in this area is Gretta Krippner throughout her article, The financialization of the American economy (2005), she defines financialization during the last decades of the 20th century from two different perspectives ”activity-centered” and ”accumulation-centered”. The first process, ”activity-centered”, refers to the increased role of financial products in the economy. She shows how the American gross domestic product (GDP) has become more de-pendent on the financial industry. This process is due to the financial sector being more profitable than the rest of the econ-omy. While the first process focused on what the economy produces (financial products and non-financial products) the second approach, ”accumulation-centered, analyzes where the companies generate their profits. Here she makes a distinction between the financial corporation (commercial banks, invest-ment banks, pension funds, insurance companies, etc.) and the
nonfinancial corporations (NFC). In her article, Krippner stud-ies how the financial revenues (interests and dividends) have gained more importance over operating income in the total cor-porate cash flow of NFC. To describe this process in her own words ”accumulation is now occurring increasingly through fi-nancial channels” (Kripner, 2005, p 199).
2.1.2 Financialization and shareholder value
The second approach is financialization described as the pro-cess by which shareholder value has steered corporate gover-nance to one objective; the maximization of the price of the stock (Crotty, 2005, p 91-95). Some of the consequences of max-imizing the price of the stock are the sacrifice of long-term by short-term growth. For example, investment in research and development could be reduced because it is a long-term invest-ment. This ”savings” would be seen as a cost reduction, and total income would rise at the expense of future revenue. Other strategies to maximize the price of the stock include wage stag-nation and reduced benefits for the workers, manipulation of financial reports to increase apparent profits, and an active en-rollment in financial operations including speculation. So, max-imizing the price of the stock creates tensions among the share-holders of the firm, but these tensions will be discussed later on in this chapter.
2.1.3 Financialization of the everyday
The final approach is financialization of the everyday. Van der Zwan (2014) summarizes it as the ”rise of the citizen as in-vestor” (2014, p. 111). Scholars of the everyday life claim that finance has not only changed the ways of production but ulti-mately it has altered the citizens view of the market. In this line Martin (2007) explains this shift in perspective ”When personal finance becomes the way in which ordinary people are invited to participate in that larger abstraction called the economy, a new set of signals are introduced as how life is to be lived and what it is for” (Martin, 2007, p 17). Additionally, other authors support this idea and even state that the society is now more aware of the performance of the financial market. Such is the importance of capital markets that it has become a barometer by which citizens measure the performance of the economy even more important than unemployment or wage levels. Not only
the perception of economic growth is linked to financial mar-kets indicators, but citizens are also exposed to a variety of fi-nancial instruments like pension plans, consumer credit, home mortgages, saving accounts among others that have become a necessity for modern life.
2.2 f i na n c i a l i z at i o n a n d e c o n o m i c s ta b i l i t y
In my view the definition that best summarizes financializa-tion is the definifinancializa-tion of Epstein as it takes into account each of the aspects mentioned previously this is why I am going to use his definition when I refer to financialization. Epstein defined financialization as the ”increasing role of financial mo-tive, financial markets, financial actors and financial institutions in the operation of the domestic and international economics” (Epstein, 2005, p. 3). There are three processes involved in fi-nancialization, so to understand it I will focus the next section to describe each of the processes. In particular, how these con-cepts have been linked throughout the neoclassical economic literature as key factors for economic development. In the first section, I will explain the role of the financial markets and how some economists have associated it with economic growth. In the second section, I will focus on the increasing role of the fi-nancial motive and finally in the last section I will discuss how certain financial actors and institutions have gained increased power over the domestic and international economies.
2.2.1 Increased role of the financial markets
One of the processes used by Epstein (2005) to define financial-ization is the increasing role of the financial markets. In gen-eral, financial markets have gained importance in the macroe-conomic policies of governments and even everyday life. As a consequence, many scholars have focused on financial mar-kets to explain economic growth and in this way justify the implementation of pro-market policies and market-based eco-nomic growth. Some economists (Gregorio & Guidotti, 1995; Khan, 2001; Caldern & Liu, 2003; Patrick, 1966) have concluded that the financial market is a critical factor that leads to eco-nomic growth. In other words, financial markets and ecoeco-nomic growth are highly and positively correlated. That is to say that an increase of the financial market performance would lead to a rise of the total output (measured as GDP) and thus contribute
to economic growth. On the other hand, different studies have shown that although there is a correlation between these two variables, there is no direct causality (Demetriades & Hussein, 1996). So it is not clear if financial markets growth would lead to an increase in economic growth or the other way around. Setting this argument aside, other authors (Patrick, 1966; Levine & Zervos, 1998) have argued that certain services provided by financial markets are an essential factor in economic growth. Despite financial markets offer a variety of services, in this sec-tion I will describe three that have had a significant impact on the study of financialization and increased the role of the fi-nancial markets. According to these economists, fifi-nancial mar-kets had: enabled entrepreneurship investment, reduced trans-actional costs and provided increased liquidity.
First, financial markets have created an environment that al-lows investment by allowing entrepreneurs to ”think big” (Patrick, 1966, p 176) and, therefore, opening the economy to new oppor-tunities and sources of growth (Levine & Zervos, 1998). They not only promote new opportunities but they also select finan-cially viable projects. Traditional macroeconomic models have pointed this mechanism as a key factor for economic growth that is associated with the Total Factor Productivity (TFP or Solow Residual). These models of economic growth were devel-oped by Solow-Swan (1957), according to it, economic growth comes from three factors: capital, labor, and TFP. If the first two variables are stable as in most economies one of the fac-tors that can lead to an increase in economic growth is the TFP. Solow (1957) defined the TFP as a catch-all term that could be used to explain any change (increase or decrease) of the eco-nomic growth. In this sense, models usually use the TFP to show improvements in education and labor force. In this case, scholars would use it to capture increased entrepreneurship op-portunities. In other words, the role of the financial market is to sponsor and select productive investment that generates eco-nomic growth.
Second, financial markets reduce transactional costs (Levine & Zervos, 1998; Arestis, Demetriades & Luintel, 2001; Fama, 1980). This reduction allows investors to reallocate their investment without additional costs, so investors can manage their invest-ment without retaliation or heavy transactional costs. Fama
(1980) argues that financial markets with low transactional cost allow investors to diversify their portfolio and optimize their gains. Hence, investors can use the market to hedge against risk and select only productive investment that generates value. Finally, Cihak (2012) argued that reduced transactional costs help to mobilize savings easier facilitating investment opportu-nities.
Financial markets reduce not only transactional costs related to moving investment from one place to another but also agency costs (Jensen, 1980) related to the principal-agent problem. There are three types of agency costs: the monitoring expenditures by the principal, the bonding expenditures by the agent and the residual costs. The principal incurs in monitoring costs to restrain the decisions taken by the agent like auditing, formal control systems, budget restrictions, and the establishment of income compensation systems (performance bonds and stock options). Second, bonding expenditures are costs taken by the agent when their actions harm the principal; it works as an insurance if the decisions of the agent harm in some way the principal then they have to compensate them. Third, residual costs refer to the expenses of the principal caused by the loss of welfare (theory assumes that they are rational agents seeking to maximize their utility function) due to any divergence in the preferences of each actor. In conclusion, agency costs can hin-der innovation and economic growth. Financial markets then serve as a mechanism to align the interest of both the agent and the principal and in this way reduce transactional costs. One of the mechanisms used by financial markets is competition between firms in the same market because it forces the corpo-ration to develop efficient monitoring systems while providing a performance indicator in the form of the stock value of the company.
Finally, the third reason used by scholars (Arestis 2001; Levine 1991; Bencivcnga, Smith, and Starr, 1996) is that financial mar-kets enhance liquidity. In a market without liquidity, most of the investors would decide to invest in short-term projects be-cause of the volatility implied in long-term projects. Scholars then argue that if investors are allowed to change their portfolio composition instantly which requires a liquid market it is pos-sible for them to hedge against these uncertainties and avoid unnecessary risks. Thus, the liquidity provided by the financial
market allows investing in long-term projects. But investors are not the only ones that benefit from the market liquidity; com-panies also enjoy easy access to capital in liquid markets. So liquidity provided by financial markets allows investors and businesses to improve the allocation of capital and in this way contribute to economic growth.
In conclusion, the neoclassical economic literature has praised the financial markets for its multiple benefits that contribute to economic growth. There are three types of services provided by financial markets: enable entrepreneurship investment, reduce transactional costs and increased liquidity. All of which create an ideal environment for the firms and investors that partici-pate in the financial markets. At the beginning of this chapter I mentioned that most of this services have had unintended con-sequences that are not always in line with the goals of economic growth, but I will discuss them later in this chapter.
2.2.2 Increased role of the financial motive
The growing role of the financial motive has various dimen-sions. In this section, I will explain how shareholder value, in particular, the value maximization proposition, has been used as a model of corporate governance. To understand the role of the financial motive I will first describe the agency problem. In Economics, it is a theory used to show the problem caused by the separation of ownership and administration of an insti-tution. According to Jensen, an agency relationship is: ”a con-tract under which one or more persons (the principal(s)) engage another person (the agent) to perform some service on their be-half which involves delegating some decision-making authority to the agent” (Jensen, 1980, p 308). The problem arises when both the principal and the agent have different interests. So to keep the interest of both the agent and the principal in line they incur in agency costs (monitoring, bonding and residual costs as explained earlier).
Figure 4: Principal Agent Relation
As depicted in Figure 4 many actors can assume the position of principal and agent: stockholders, bondholders, managers, and workers. Stockholders are the owners of the capital or eq-uity. Bondholders are the owners of the debt or bonds of a firm. While they want the firm to perform well, each of the actors has different views on how to achieve it and maximize their utility function. For example, stockholders and bondholders represent two distinct sides of a firm; the stockholder is more exposed to risk but can capitalize more while the bondholder has less risk, but the amount of debt determines its earnings. This rela-tionship is in constant tension, as the stockholders will always push for higher risk whereas the bondholder is risk averse and would do the opposite. It is clear how the stockholders would approve a risky project that would increase the value of a com-pany beyond the present value of the stock. Any increase be-yond this price would be an increase in the value of the stock; thus, this project would be valuable for the stockholders. On the other hand, the bondholders have nothing to win if the mar-ket value of the stock goes beyond it’s present value, as they already know that they will just gain the present value of the debt even if the value of the company is higher. Another exam-ple of this tension between the agent and the principal (Jensen, 1980 p 313) is when there are costs involved for the manager to develop a new project like learning a new technology or tak-ing too much time and effort to manage the project. Therefore, agency cost and the principal-agent theory represent a problem
for the firm when the manager or agent has multiple principals, and each of them has different views on the company. In par-ticular, three questions sum up this problem, what is the role of a manager? Should the manager maximize the utility function of only one shareholder? And what is the objective of a firm? There is a theory in finance and economics that answers these questions and is responsible for the increased role of the fi-nancial motive of firms. This approach is called the value maximization proposition, and its primary objective is to align the interests of all the stakeholders (stockholders, bondhold-ers, managbondhold-ers, and workers). The value maximization hypoth-esis states that ”managers should make all decisions so as to increase the total long-run market value of the firm” (Jensen, 2001, p 236), in other words, the objective of the corporate governance is to maximize the long-run market value of the firm. Only by achieving this goal the company can survive in the long run. But this is a complex task because maximiz-ing the value of the firm is a function of different endogenous (employee motivation, innovation, values, the perception of the public among others) and exogenous (the economy, business cycles, the rate of savings, welfare of the population, etc.) vari-ables. In summary, the maximization proposition is a rule of thumb for the corporate governance: spend an additional dol-lar on any constituency to the extent that the long-term value added to the firm from such expenditure is a dollar or more (Jensen, 2001, p 242). This condition is met, in the economic literature, when the marginal costs are equal to the marginal benefits. This is how the financial motive has permeated corpo-rate governance, and now the stock market value is the pri-mary measure to determine the firm performance. Further-more, Warner, Watts, and Wruck, (1988) studied the associa-tion between stock market returns and top management (agent) changes. They studied the behavior of 269 firms listed on NYSE or AMEX from 1963 to 1978 and concluded that there is an in-verse relationship between the stock market performance and top management change. If the value of the stock underper-forms, there is a high probability that the top management would change. This article provides evidence that supports shareholder value as the central principle of the firm.
In conclusion, throughout this section, I have defined finan-cialization as a process that includes the ”increasing role of
fi-nancial motive, fifi-nancial markets, fifi-nancial actors and fifi-nancial institutions in the operation of the domestic and international economics” (Epstein, 2005, p 3). I have shown what other au-thors have to say from different disciplines. In particular, how financial markets have provided services that, according to neo-classical economist, promote economic growth by improving entrepreneurship investment, reducing transactional costs and increasing liquidity. On the other hand, I have shown how the financial motive; through the value maximization proposition has changed the incentive dynamics in the corporate manage-ment leading to power redistribution among the stakeholders of the firm. In the next section, I will focus in the resurgence of financialization, giving particular attention to the development of this process in Latin America.
2.3 t h e d e v e l o p m e n t o f f i na n c i a l i z at i o n a n d i t s c o n s e q u e n c e s
Financialization has been appraised in the economic literature for its multiple benefits. But all actions have consequences, and sometimes the costs are greater than the benefits. In this sense, scholars have shown how financialization has triggered a series of events that have had negative consequences for the welfare of the society and economic stability. Dumnil and Lvy (2001) explain the rise of financialization in two phases for four de-veloped countries USA, Germany, France and the UK. Albeit this processes took place in advanced political economies most of the effects described in their article, particularly the rise of the interest rates, was a global event that affected all countries equally.
2.3.1 Phase 1: 1980-1990
The first stage takes place at the beginning of the 1980s and is characterized by a turn in the objectives of the central bank-ing and low-profit rates in the economy. In this way, central banks changed the monetary policy objectives from full em-ployment to price stability. Their first policy change was to raise interest rates to control the inflation. As they explain this shift in goals triggered a series of events: Deregulation of fi-nancial markets, less power of the union movement, policies that incentivized mergers and the rise of the new corporate governance that held shareholder value above everything else.
So, financialization changed the firms objective using the value maximization proposition as the primary goal of the modern company. Moreover CEOs have used it as a way to promote other changes that promote short-term growth at the expense of long term growth of the firm like wage stagnation and reduced benefits for the workers, manipulation of financial reports to increase apparent profits (e.g. Long Term Capital Management -Lowenstein (2000) and Barings Bank), and an active enrolment in financial operations including speculation (e.g. Enron). In fact, it has changed the power redistribution among the share-holders of the modern corporation giving an excess of author-ity to the CEO. Excess of power has given the managers the ability to determine their salary and compensation system ”In modern corporations, the CEO has enormous power including the power to set his own compensation, subject, of course, to his board but in many corporations, he even has considerable power to appoint the board, and with a stacked board, there is little check. Shareholders have minimal say” (Stiglitz, 2012, p. 31).
On the other hand this process, the rising of interest rates and deregulation of the financial markets, help to increase the in-comes and power of the rentier class (Epstein & Jayadev, 2005). The rentier class as defined by Keynes are those ”functionless investor(s)” (1973, ch. 24) who ”generate(s) income via his own-ership of capital” (Epstein & Jayadev, 2005, p 48). Epstein & Jayadev define in their article the rentier income as the prof-its generated from the financial sector like banks, stockbrokers, and insurance companies. This rentier income directly depends on interest rates, if the interest rate raises the portion of the economy that goes to the rentier class increases. This process becomes evident from figure 5, which shows the interest rates from 1965 to 2015, with a peak during the 80s.
Figure 5: Interest Rates France, Germany, Japan, United King-dom And USA
2.3.2 Phase 2: 1990-2000
The second stage takes place in the late 1980s. The recovery of the profit rates and the decrease in the interest rates portrayed this period. Financial markets gained importance as the chan-nel for transferring income to the shareholder. In this way, the transfer channels changed from debt to dividends. This process continued during the 1990s, but its consequences would be felt in the crisis of the late 1990s. They finally conclude their arti-cle by stating that ”the sudden rise of interest rates prolonged the effects of the crisis, as the benefits of the firm’s profitability were transferred to the lenders” Dumnil and Lvy (2001, p 29). 2.3.3 Consequences
Epstein (2005) explains that financialization has had an adverse effect on all the society except for the rentier class. He then explores how financialization has exploited NFC. In particular, he shows how financial markets have demanded more income and growth from NFC as the shareholder value became the only objective of the corporate government. The author states that NFC competing at the beginning of the 1980s were faced with the challenge to grow at higher rates that were unsustain-able while competing in a stagnant economy characterized by low growth rates and increased competition from other firms.
As a response NFC had to adapt to these requirements, some of the consequences were to cut on wages and benefits for the workers, fraud, and deception to increase their profits and a movement from their core business to a more profitable busi-ness like the financial markets. The problem of these firms is that they were not looking to hedge their risk in the market but rather to speculate on it. But these efforts to become more profitable could only be achieved by an excess of power of the CEOs. Consequently one of the most important outcomes of financialization was the power redistribution among the share-holders of the firm. This had critical effects on stability and income inequality.
Changes induced by financialization, power redistribution among shareholders, are critical to understand its consequences on economic stability. First, CEOs used their power to increase their income at the expense of the workers. Although it might seem inconsequential, according to the High Pay Commission this changes matter, ”Fair pay within companies matters; it af-fects productivity, employee engagement and trust in our busi-nesses.” (2011, p. 24). Moreover, Mishel and Bivens (2011, p. 7) provide overwhelming empirical evidence from the US that supports this theory; the salary of the managers has risen ex-ponentially while the rest of workers pay has stagnated. In 1965, the ratio of average annual CEO compensation to aver-age worker compensation was 24-to-1 while in 2010 the ratio is 243-to-1. This means that the average CEO gains the same as 243 average workers. It’s hard to imagine that the marginal productivity of the CEO has increased ten times more than the average worker. So there is no economic explanation, at least from a marginal productivity point of view, for why salaries of the CEO’s have increased so much compared to the average worker.
Stiglitz (2012, p. 77) proposes some possible explanations: tech-nology skill biased technological change, social factors like the weakening of unions and the breakdown of social norms, glob-alization and finally the increasing role of finance (financializa-tion). It is not the particular effect of those mentioned above but rather the interaction with each other. Moreover financial-ization promotes income inequality, those at the top (the 1%) have increased their income at an exponential growth while the average worker has not increased its revenues and relied on
debt and financial institutions to pay for its expenses. Income inequality could play a significant role in the development and prevention of crisis (economic stability). Berg and Ostry (2011, p 22) show how income inequality, is the most important factor in determining the longevity of a period of economic growth. They concluded then that a 10% decrease in inequality would increase the length of the duration of an economic growth spell by 50%. So if we compare two countries with the exact initial conditions except for the level of inequality, we should expect that the country with less income inequality would be more prosperous and more resilient to crises.
2.3.4 Hypotheses
Up until now I have shown financialization from two opposed points of view. In my opinion is not a matter of black and white. That is to say that, financialization is not as good as some economist think neither it is the worst thing that could happen to an economy. To have a healthy and prosperous econ-omy, we need finance, banks, and insurance companies. Even Stiglitz acknowledges it ”markets have played a central role in the stunning increases in productivity and standards of living in the past two hundred years - increases that far exceeded those of the previous two millennia.” (2012). The problem is that this sector lacks a moral character (Stiglitz, 2012) and as such it will do everything to increase the profits in the short term even at the expense of long-term growth. So we must keep it in line with regulation in to prevent an economic disas-ter such as the ones described above. In this sense, I have two hypothesis concerning economic stability and financialization.
• First, financialization has grown in LAC much faster than the economy can adapt. As a result, LAC has become vulnerable to economic crisis. This process could be the cause of the cri-sis during the 1990s in LAC. In this case, we should expect that countries that have gone through a quick financialization process would be more susceptible to an economic crisis. So fi-nancialization increases the probability of a financial crisis in LAC.
• Second, an excess of financialization has harmed the economy and society as a whole. It has abused consumers with predatory
lending practices, producers by establishing short-term over long-term growth and labor by reducing the benefits and stagnating wages. Therefore, financialization has reduced economic perfor-mance of LAC. These three facts, more crises, more inequality, and less economic growth are what I define in this dissertation as economic stability.
3
R E S E A R C H D E S I G N
In this chapter, I will describe the quantitative methodology that I used to prove my hypotheses. This will be useful to understand the limitations and strengths of this dissertation. In the First section of this chapter, I will briefly discuss why I chose an econometric approach over other methodologies. In the second part of the chapter, I will describe the variables and its operationalization over the model. And finally, I will discuss the limitations of this dissertation.
3.1 m e t h o d o l o g y
For the methodology, I will follow the same approach used by previous investigations on economic growth. Traditionally economic literature has analyzed growth from two different perspectives, empirical (econometric models) and theoretical (macroeconomic models). In this sense, Macroeconomic els have had a long trajectory and evolved from simple mod-els to complex mathematical abstractions. The most influential macroeconomic models of economic growth are the ones de-veloped by Solow (1956), Swan (1956), Ramsey (1928), Romer (1986), Lucas (1988) Rebelo (1991), and Barro (1991). While macroeconomic models have proven to be useful for the de-velopment of policies and to understand complex interactions among variables their mathematical difficulty and in some cases, their assumptions have reduced their empirical usefulness. On the contrary, econometric models have been used to analyze different phases of economic growth. Although they are less sophisticated than macroeconomic models, their practical util-ity makes them highly valuable. For this research, I would use an econometric approach.
To test my hypotheses and correctly measure the effects of fi-nancialization on economic growth it is necessary to use a panel
data. In which I am going to observe different variables from 18 countries in Latin America and the Caribbean during 20 years. What I propose is to build a panel data containing financial, eco-nomic, and social data. Hsiao (2014) explains the advantages of panel data sets over traditional data sets like cross-sectional data or time series. The author explains that panel data will contain more information and degrees of freedom Individuals and Time than the other data sets. In this regard, it will help the model to improve the efficiency of the estimators by reduc-ing the collinearity (the problem when two or more variables are highly correlated in a way that one variable can predict the others) among the explanatory variables. Finally, he states that using a panel data will allow the researcher to analyze infor-mation that with only cross-sectional data or time series would not be possible. On the other hand, to understand the effects of financialization in crises, I will use a logit model. Accord-ingly, the first hypothesis regarding the effects of financializa-tion on economic growth and inequality will be analyzed using panel data regressions while the effects of financialization on economic crises will be analyzed using a logit model.
3.2 va r i a b l e s a n d o p e r at i o na l i z at i o n
I will use publicly available data from various sources like the World Bank and the Economic Commission for Latin America and the Caribbean (CEPAL, for its initials in Spanish). The World Bank repository is one of the most complete and com-monly used sources of information for this type of research. It groups more than 52 databases ranging from World Devel-opment Indicators to Global Financial DevelDevel-opment from 214 countries. Additionally, I will use other sources of information like the CEPAL database. In this section, I will define the vari-ables and explain how they are measured.
Perhaps the most used indicator to measure economic develop-ment and growth in econometric models is the Gross Domestic Product (GDP). It is defined as the total output of a countrys economy measured as the total value added in the economy plus taxes minus any subsidies. The World Bank defines it as ”the sum of value added, measured at constant prices, by households, government, and industries operating in the econ-omy. GDP accounts for all domestic production, regardless of whether the income accrues to domestic or foreign institutions”
(2014). The World Bank estimates the value added by measur-ing the production of all goods and services in the economy produced during a year subtracting the costs of intermediate products, both measured at constant prices of 2005.
But GDP measured this way only indicates the size of the econ-omy, in other words, bigger economies do not imply develop-ment (Martin, 1994). For example, if we compare a big econ-omy like India with a small one like Luxemburg we could not conclude about the degree of development of each country as, for 2013 Luxemburg had a GDP of only 60 billion USD com-pared to Indias 1,877 Billion USD. To control for the size of the economy GDP per capita is used as an indicator of economic development. Behind this logic is the idea that a country is de-veloped not because it has a significant outcome but because its average citizen produces more. Going back to the example we can see the difference between using the GDP per capita in-stead of the total GDP: Luxemburgs GDP per capita for 2013 is 110,967 USD compared to Indias 1,498 USD. It then comes naturally that a measurement of economic growth will come from the change the GDP per capita from one year to another. The variation of the GDP per capita will be used to measure economic growth in my econometric models. It does not have units of measurement, as it is a ratio of growth.
Nevertheless, scholars have criticized the use of this indicator to account for development and economic growth. Stiglitz (2012) for example explains that GDP does not work in a highly un-equal society ”If Bill Gates and Warren Buffetts income go up, the average earnings for America goes up”(2012, p 22). In this case, an increase in the revenue of the top 1% would increase the GDP per capita, but it will not reflect the situation of the average citizen. Another critique to this indicator is that it does not account for the environmental cost of extracting natural resources. Thus, an important element such as sustainability is not included in the GDP. Additionally, there are different methodologies to measure GDP (This is why the GDP can have different values) and depends on the quality of national ac-counts. As we can see GDP is far from ideal but still it is the most common used indicator.
Another important variable for our econometric analysis is in-equality. Throughout this work, I will measure income
inequal-ity using the GINI index. This variable is a measurement of how income is distributed among the population. If the in-come is equally distributed among all the individuals, then the index takes a value of zero. In contrast, if the income is not evenly distributed for example in the most extreme case all the income would be received by just one individual the variable would take a value greater than zero but less than one. Conse-quently, the index is a measurement of income inequality that ranges between zero and one, taking the value of zero to show no inequality and the value of one to indicate total inequality. The technical definition of the GINI used by the World Bank is ”A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The GINI index measures the area between the Lorenz curve and a hy-pothetical line of absolute equality, expressed as a percentage of the maximum area under the line” (2014). Because it is a percentage it does not have any units of measurement.
One of the probable causes of financialization is the increase in the real interest rate; to understand the effect of this vari-able I used the lending interest rate in the short and medium term. According to the World Bank (2014), different types of interest rates vary according to particular conditions like the maturity (short-term or long-term) of the debt and the credit-worthiness of borrowers. This variable does not have a unit of measurement. It is a critical variable, as Dumnil and Lvy (2001, p29) explain, a rise in this variable would prolong the effects of financial crises by transferring the profits of the firms to the lenders. Causing serious consequences on the economy in general, by decreasing economic growth resulting from the reduced investment power of companies and thus triggering high unemployment.
One of the most common variables used to control for govern-ment burden on private entrepreneurship is the consumption of government as a percentage of the GDP (Loayza, Fajnzylber, & Caldern, 2004, p 22). Loayza, Fajnzylber, and Caldern acknowl-edge that the government spending is used for productive ac-tivities that promote economic growth like education, health, police and infrastructure. But explain that another significant portion of these expenditures does not contribute to the total outcome of the economy and most of its budget is devoted to
cover the bureaucracys wage bill. Additionally, they argue that this variable can be used as a proxy of the government ”bur-den” on the private activity in the way of taxes and market distortions. We should expect that financialization would af-fect countries by reducing government expenditure because of the ”race to the bottom,” countries try to be more appealing to foreign investment and thus reduce their taxes and labor pro-tection. This variable is calculated as a percentage, so it does not have units of measurement.
Some economies, particularly in Latin America, follow different economic growth dynamics because of their dependence on nat-ural resources. For example, a fall in the prices of the oil would affect an economy differently like Venezuela (natural resources represent nearly 25% of the GDP) compared to Colombia (nat-ural resources represent only 10% of the GDP). To control for this effect of natural resources on economic growth, I am going to use the ratio of total natural resources rents to GDP. Total nat-ural resources as calculated by the World Bank (2014) include rents from oil, natural gas, coal (hard and soft), minerals, and forest rents. It is measured as a percentage of the GDP, so this variable does not have units of measurement.
Another measure of economic performance is the rate of un-employment from the working age population. According to the World Bank (2014), Unemployment is an indicator of the total economic activity. The International Labour Organization (ILO) defines it as all persons above a specified age who dur-ing the reference period (yearly) were: without work, currently available for work, and seeking a job (2014). This indicator is measured as a percentage of the total working population, so it does not have units of measurement.
Total urban population is a control variable for the degree of industrialization (Wheaton Shishido, 1981). In this aspect, we should expect that countries with high level of industrializa-tion could generate more income per capita and thus more eco-nomic growth. The World Bank then measures Urban popula-tion as the ”people living in urban areas as defined by napopula-tional statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Ur-banization Prospects” (2014). In the econometric analysis, I will use this variable to control for the degree of industrialization of
a country. This variable is measured as a ratio between the ur-ban population and the total population, so it does not have units of measurement.
The variable crisis is a binary variable that takes the value of one if a country had an economic crisis and 0 otherwise during each period. Although authors use different conditions to de-termine the existence of an economic crisis. Laeven and Valen-cia (2008) for example, include three types of crisis: Systematic banking crisis, Currency Crisis and Debt Crisis. According to them, two conditions define a systematic banking crisis. The first indication would be systematical losses and liquidations of banks. Followed by banking policy intervention measures. Is defined as ”a nominal depreciation of the currency vis--vis the U.S. dollar of at least 30 percent that is also, at least, ten per-centage points higher than the rate of depreciation in the year before” (Laeven and Valencia, 2008, p 11). All of their databases are updated until 2007 and are publically available in the IMF. In spite of their efforts, their data is not compatible with the type of study that I plan to do because they don’t show how long a crisis last. The alternative I propose to use is to create my definition of a financial crisis. In the literature is of com-mon knowledge to define an economic crisis as three consecu-tive quarters of negaconsecu-tive GDP growth. Because the information provided is yearly, I propose to use a year to year measure-ment; if the GDP per capita growth is below 0, I will mark it as a crisis. This measurement has several disadvantages; the first one is that it won’t show a crisis that started after the annual measurement and before the next year’s remeasurement. The second problem is the assumption that GDP per capita growth captures the effect of other relevant measures that are consid-ered to determine a crisis like unemployment, interest rates, and inflation. Finally, this measurement could incur in a type 2 error: A change in the GDP that is not an economic crisis. For example, if the population grows (like in the case of immi-gration) the GDP per capita diminishes and this is not a direct consequence of an economic crisis.
For the market indicator, I use two variables that measure differ-ent aspects of financialization. The first variable is the turnover ratio and it is calculated as the value of total shares traded over the market capitalization. This variable measures the efficiency of the market. In other words, market turnover is an indication
of how efficient is a market. The second variable is the volatil-ity of the stock market; this is a straightforward variable that measures the volatility of the stock market.
The next set of variables that I am going to explain is a col-lection of regional dummies. These dummies will capture the differences between the regions by grouping countries with similar social, geographical, and cultural backgrounds. There is a total of 5 regions: Andean Region, South Region, Brazil, Central America, and Mexico. The Andean region includes Bo-livia, Colombia, Ecuador, Peru, and Venezuela. The South Re-gion covers Argentina, Chile, Paraguay, and Uruguay. Central America is constituted by Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Nicaragua, and Panama. The other two regions are self-explanatory. These dummies are dis-played mapped in figure 6.
Figure 6: LAC regions
The last variable is the participation of the financial industry in the economy. It is a measurement of the participation of financial incomes like insurances, real interest rate, and finance commonly denoted as FIRE. This measurement has been used in the literature as an indication of financialization (Krippner, 2005, p 179). Consequently, it will be the primary variable that I will use to measure the degree of financialization of a country. The source of information for this variable is the CEPAL, and it is measured as a ratio between financial value added over the total outcome of the economy.
Table 1: Variables
Variable Measures Definition Source Natural
Re-sources
Control Rents from oil, natural gas, coal (hard and soft), miner-als, and forest rents
World Bank Unemployment Control Unemployment/Total
Working Population
World Bank Urban
Popula-tion
Control Urban Population/Total Population
World Bank Median Wage
Variation
Control The variation of the me-dian wage calculated at constant prices of 2011
CEPAL Government
Consumption
Control Government expenditure/ GDP World Bank GDP percapit growth Economic Growth
Variation of the GDP per capita from one year to an-other
World Bank Lending
Inter-est Rate
Financialization Lending interest rate in the short and medium term
World Bank Trade Financialization Imports+Exports/GDP World
Bank FIRE Financialization Financial Intermediation,
real state, and renting
World Bank Crisis Financialization
- Consequence
1if crisis 0 other wise IMF Stock Market
Turnover
Financialization-Efficiency
Value of stocks traded/ Market capitalization World Bank Stock Price Volatility Financialization-Stability of markets
Stock Price Volatility World Bank GINI Inequality Measures how income
is distributed among the population
World Bank
3.3 l i m i tat i o n s
The limited amount of resources, time and budget, makes it dif-ficult to obtain information that would be useful to understand the financialization process altogether. For example, one of the missing variables in this study is the profit rates of financial and nonfinancial corporations, to gather this information from the accounting system of the 18 countries would be a challenging task. As such the only alternative is to use publicly available information, which limits the quality of the information and leaves out other variables, this could have repercussions in my conclusions and their validity. Additionally, I used 20 years of information (1990-2010) leaving out any relevant information and phenomena that could have occurred during the 1980s, this was because the public database for these years was incomplete which is usually a challenge for developing countries.
As usual, there are other limitations of quantitative research, the findings cannot be generalized to the global process of fi-nancialization. They only apply to LAC during the time of the study. Another important limitation is that financialization is not an isolated phenomenon other events could trigger the con-sequences attributed to financialization in spite of the control variables events like national elections, internal conflict, and natural disasters.
4
R E S U LT S
In this chapter, I will analyze the results obtained from the econometric models to test the two hypotheses established be-fore. In the first section, I will examine descriptive statistics that can help to understand the individual behavior of the variables, and the interaction among them. Then in the second section, I will use two econometric models to understand the effect of financialization on the economic stability of LAC. The first re-gression is a logit model. I will use it to comprehend the role of different financialization variables in an economic crisis. In particular this model estimates the relationship between finan-cialization variables and the probability of a crisis. The second regression is a panel data. This model will capture the conse-quences of financialization on economic growth. In particular I will take into account five different aspects of financialization for this regression. . In both of cases, I will use control variables to isolate the effect of financialization
4.1 d e s c r i p t i v e s tat i s t i c s 4.1.1 Univariate Analysis
Table 2 shows the descriptive statistics of each of the variables used in the modeling process. In this table, I show five ba-sic descriptive statistics: the number of observations, the mean, the standard deviation the minimum and the maximum. I do this to give a general idea of how these variables behave and to check the quality of the input variables in the model by identify-ing and filteridentify-ing outstandidentify-ing values. It is important to validate the data in the early stages this process because this would de-termine its quality and performance. As expected almost all of the variables behave according to what was described in the previous section.
The Gini has a minimum value of 40% (or .4) and a maxi-mum value of 60% (or .6) measured as percentage points, this is within 0 and 100 (or 1) the boundary established for this vari-able. It presents a small standard deviation, which could be an indication that almost all of the Latin American countries chosen for this study behave in the same way. However this variable is not complete, from the 432 possible number of ob-servation the Gini is only available for 234, so we are missing 32% of the Data.
Table 2: Summary statistics
Variable Mean Std. Dev. Min. Max. N
GDP percapita growth 2.26 3.507 -11.877 16.233 432 GINI 51.284 4.775 40.2 63 293 Government Consumption 11.933 3.789 2.976 43.479 430 Lending Interest Rate 39.641 241.903 4.248 4774.525 397 Natural Resources 7.047 7.923 0.113 44.097 432 Trade 64.253 33.424 13.753 198.767 430 Unemployment 8.319 4.103 1.3 20.7 391 FIRE 15.082 6.094 3.647 37.602 418 Stock Price Volatility 27.45 17.719 3.909 134.182 177 Stock Market Turnover 16.499 24.104 0.043 228.621 270
The next variable is the GDP per capita growth; this vari-able ranges from -11% in the deepest of the crises to 16% at best. The mean for this variable is unusually low at 2.26% per year. This could be explained by the multiple crises suffered in these countries during the 1990s and the low economic growth caused by the mortgage crisis in the United States during 2008. This variable is complete, which means that the growth of the GDP per capita is available for all of the countries every year. Additionally, the GDP per capita presented in Figure 7 shows the evolution of this variable during the period of study; it is interesting to notice that the global crisis has had repercussions in the economy of LAC. The crisis at the beginning of the 21st century is portrayed in the figure as well as the sub-mortgage crisis of 2008.
Figure 7: GDP Per Capita
The lending interest rate is an interesting variable because of its exceptionally high maximum value, which could be an indi-cation of outlier observations that could affect the estimators in the model. After a careful analysis of the information from the World Bank, I discovered unusual observations coming from Peru, Brazil, and Uruguay at the beginning of the 1990s caused by the interest rate crisis in Latin America. Figures 8, 9, and 10show the lending interest rate for Brazil, Peru and Uruguay respectively. I decided to remove all variables greater than 60 because they will induce the models to biased results. I chose 60 since it corresponds to the 95th percentile so it will include all relevant information but it will leave out undesired outliers. The following table shows the descriptive statistics for the lend-ing interest rate after removlend-ing outliers.
Natural Resources weight on average of 7% of the GDP. This means that on out of every 100$ produced 7$ come from nat-ural resources in Latin American. The standard deviation for this variable is 7.92 and the variable ranges from the least de-pendent country producing only 0.11% of their total GDP to the most dependent country relying 44% on their natural resources as a source of economic growth.
per-Figure 8: Lending Interest Rate Brazil
Figure 10: Lending Interest Rate Uruguay
Table 3: Summary statistics 2
Variable Mean Std. Dev. Min. Max. N
GDP percapita growth 2.26 3.507 -11.877 16.233 432 GINI 51.284 4.775 40.2 63 293 Government Consumption 11.933 3.789 2.976 43.479 430 Lending Interest Rate 22.606 12.699 4.248 59.902 378 Natural Resources 7.047 7.923 0.113 44.097 432 Trade 64.253 33.424 13.753 198.767 430 Unemployment 8.319 4.103 1.3 20.7 391 Urban Population 68.278 14.594 40.46 94.983 432 FIRE 15.082 6.094 3.647 37.602 418 Stock Price Volatility 27.45 17.719 3.909 134.182 177 Stock Market Turnover 16.499 24.104 0.043 228.621 270
formance of financial markets, stock market turnover and stock price volatility, the problem of these variables is that out of the 18developing countries analysed only 9 have information of the stock price volatility: Argentina, Brazil, Chile, Peru, Ecuador, Mexico, Colombia, Panama, and Venezuela. making it an in-complete variable, missing almost 60% of the observations. The stock market turnover varied from 0 to 228. An interpretation of this index for the maximum amount is that in one year the stock market rotated on average 228 times. On the other hand, the volatility of the financial markets has a mean of 27 with a minimum value of almost 4 and a maximum of 134.
One of the control variables is unemployment used in the mod-els to control for other effects that cannot be accounted in the model like macroeconomic policies. In Latin America, this vari-able seems stvari-able with a mean of 8.32, a standard deviation of 4.10. The minimum value of unemployment from the countries analyzed was 1.3% while the maximum from the same period is 20.70%.
The openness of the economy represented by the variable Trade varies in great measure from country to country. This can be inferred from the high standard deviation. A useful graph to understand the differences between countries is a box plot pre-sented in figure 11. The chart displays the percentile 25 (base of the rectangle), 50(middle line of the box) and 75 (top side of the rectangle), so we can compare it to other countries. In essence, a box plot is a graphical representation of the distribution of the variable that can be valuable for comparing the degree of trade among countries. In figure 7 I Identified three groups of countries, those who have their 50th percentile under 55%, those who are located between 55% and 80%, and lastly those who are above 80% of trade. The first group represents coun-tries with economies that do not rely much on trade this group is constituted by Argentina, Brazil, Bolivia, Colombia, Ecuador, El Salvador, Guatemala, Mexico, Peru, Uruguay, and Venezuela. The second group shows countries with medium level of trade; these countries include Chile, Costa Rica, Dominican Republic, and Nicaragua. Finally, the last group is characterized by re-lying on trade for their economic growth: Honduras, Panama, and Paraguay.
Figure 11: Box Plot Trade
Another control variable, used as a proxy for the degree of industrialization is the percentage of the population that lives in urban areas. This variable has a mean of 68% and has a standard deviation of 14.59% with a maximum of 95% from Uruguay and a minimum of 40% in Costa Rica.We can see from the data that all countries in Latin America have a growing ten-dency of the urban population. But interestingly, near the year 2000, some states changed their patterns of growth (slope), ei-ther it increased as is the case of Costa Rica and the Dominican Republic, or it grew at a slower rate like Panama, Paraguay, and Venezuela.
The other control variable shows that the government consump-tion ranges from 3% to 37% of the total GDP. In the previ-ous chapter I explained this difference as a result of the dif-ferent types of government and in particular to the ”burden” of the government on investment. The countries that present the highest government consumption is Brazil, Colombia and Honduras. Here it is important to clarify that most of the gov-ernment expending in Colombia comes from the internal con-flict that this country has suffered for more than 50 years. Its military expenditure over GDP is 3.5% almost 3 times the aver-age of the Latin American Countries.
models is the amount of income generated from financial ac-tivities (FIRE). This variable has a mean of 15%, a small stan-dard deviation of just 6%. It ranges from 3.65% to 43% of the total Gross Domestic Product of a country. Some of the coun-tries that rely more on financial activities are Chile, Colombia, Mexico, Panama, and Uruguay. On the other hand the coun-tries that are less dependent on financial markets are Peru, Ar-gentina, Paraguay, Costa Rica, Dominican Republic, Guatemala, Nicaragua and Venezuela.
Figure 12: Evolution FIRE
4.1.2 Bivariate Analysis
The correlation Matrix shown in Figure 13 displays the rela-tionship between each set of variables. From this table, we can determine how these variables are related and in this way pro-vide more statistical epro-vidence to support my hypotheses. First, there is a weak correlation between the degree of financializa-tion, measured as the amount of income generated by the fi-nancial markets, and economic growth. But I will analyse in detail this interaction in the next section. On the other hand, this variable is strongly and positively correlated with the ur-ban population, the government consumption, and the stock market turnover ratio. The correlation between urban popula-tion and FIRE is not easy to explain. The urban populapopula-tion is a proxy for the degree of industrialization of a country. Indus-trialization is the process of moving from the primary sector (direct use of natural resources) to the secondary sector (pro-duction of goods from natural resources), it then comes clear that the secondary sector needs more the services provided by the financial industry than the primary sector because it is more capital intensive. This would also explain the negative correla-tion between FIRE and the natural resources of a country. Figure 13 shows some relationships were not expected. One of these correlations is the income inequality variable GINI with urban population if the urban population increases in-come inequality will decrease. Although this result might seem counter-intuitive, it is easier to understand if we use a different interpretation. What this is saying is that if there is more indus-trialization (resulting in a middle class), economic differences between socio-economic groups will decrease.
There are some of the results from the correlation matrix that provide statistical evidence for my hypothesis regarding finan-cialization, economic growth, and crises. Inequality would then be the link among these variables, and as we can see in the correlation matrix, it has adverse consequences on economic growth the correlation of the GINI and economic growth is -0.17. Up to this point, I have focused on providing an empirical and theoretical base to support the econometric models in the next section I will describe the results of such models as well as their interpretation.
4.2 i n f e r e n t i a l a na ly s i s
4.2.1 Financialization and economic crises
In this section, I will show the results obtained from both econo-metric models. The first model is designed to test if financializa-tion makes LAC more susceptible to an economic crisis while the second model will provide insights to how financialization has affected the economic performance of LAC. The objective of this model is to determine how the independent variables affect the probability of occurrence of the dependent variable. The independent variable is ”crisis” this variable has a value of 1 if there was an economic crisis and 0 otherwise. The inde-pendent variables for these models are the Gini coefficient, the lending interest rate, the variable trade, unemployment, FIRE, Stock Price Volatility, Stock Market Turnover and a set of Dum-mies representing the region of the country. The model is dis-played in Table 4.
In Table 4 there are two Logit regressions, the first one (1) has all the variables including market turnover, market volatility, and unemployment. The issue with the first two variables is that financial markets are not developed in most of the LAC economies; only 9 out of the 18 countries have capital markets. Then, the problem of working with these two variables is that we are leaving out information, almost 60% of the data, which limits the results of the model. Additionally, the first regression also runs the variable unemployment that is most probably cor-related with the dependent variable crisis, in other words, un-employment is the result of a financial crisis which does not add much to the model. Nonetheless, it is interesting to notice that there are four significant variables unemployment, stock price volatility, the South Zone region, and the Andean region. Continuing with the results, in the second regression of Table (4), I corrected for these variables by leaving them out of the model. In this case, we can see that this change had a major effect on the variance of the estimators, so the only significant variable for the model is the Interest Rate, which is consistent with the interest rate crisis of LAC in the 1990’s. Furthermore the marginal effect for this model is in Table 5, which shows that an increace of 1% in the interest rate would increace the probability of an economic crisis in 3%. The rest of the vari-ables for the regions did not impact in the probability of an
