Short-Run Pain, Long-Run Gain
The Effects of Financial Liberalization
Author:
Mr. Sergio L. Schmukler https://isni.org/isni/0000000404811396 International Monetary Fund

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Graciela Laura Kaminsky https://isni.org/isni/0000000404811396 International Monetary Fund

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Contributor Notes

Author’s E-Mail Address: graciela@gwu.edu
Publication Date:
01 Feb 2003
eISBN:
9781451845280
Language:
English
Keywords:
WP; financial liberalization; liberalization reform; insider trading; liberalization period; liberalization process; liberalization reversal; episode end; liberalization of the capital account
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We examine the short- and long-run effects of financial liberalization on capital markets. To do so, we construct a new comprehensive chronology of financial liberalization in 28 mature and emerging market economies since 1973. We also construct an algorithm to identify booms and busts in stock market prices. Our results indicate that financial liberalization is followed by more pronounced boom-bust cycles in the short run. However, financial liberalization leads to more stable markets in the long run. Finally, we analyze the sequencing of liberalization and institutional reforms to understand the contrasting short- and long-run effects of liberalization.

Abstract

We examine the short- and long-run effects of financial liberalization on capital markets. To do so, we construct a new comprehensive chronology of financial liberalization in 28 mature and emerging market economies since 1973. We also construct an algorithm to identify booms and busts in stock market prices. Our results indicate that financial liberalization is followed by more pronounced boom-bust cycles in the short run. However, financial liberalization leads to more stable markets in the long run. Finally, we analyze the sequencing of liberalization and institutional reforms to understand the contrasting short- and long-run effects of liberalization.

I. Introduction

The financial crises of the 1990s have claimed several victims. Banking systems in many countries collapsed, fast growing economies suddenly faced sharp recessions, and the booming international capital flows of the mid-1990s dwindled to a trickle. This is not all. Another important casualty of these crises has been the support for the liberalization of financial systems. In the aftermath of the Asian crisis, many have argued that globalization has gone too far, leading to erratic capital markets and causing costly crises. This has prompted some to suggest a return to the old order of financial controls. For example, Stiglitz (1999) clamors for developing countries to put some limits on capital inflows to moderate “excessive” boom-bust patterns in financial markets2 Even controls on capital outflows, not long ago dismissed as ineffective, have been recommended again. Krugman (1998), for example, argues that capital controls might help in managing, at least temporarily, an otherwise disorderly retreat of investors. The debate has reached the general public, with Soros (2002) and Stiglitz (2002) broadly criticizing the functioning of the international financial system. With many more economists joining the ranks of those supporting intervention in financial markets, long gone seem to be the days of an indiscriminate advocacy of financial integration.3

Interestingly, in what seems to be a parallel world, many still praise the advantages of liberalization. It is claimed that financial liberalization helps to improve the functioning of financial systems, increasing the availability of funds and allowing cross-country risk diversification. For example, Obstfeld (1998) argues that international capital markets can channel world savings to their most productive uses, irrespective of location. Stulz (1999) and Mishkin (2001) claim that financial liberalization promotes transparency and accountability, reducing adverse selection and moral hazard while alleviating liquidity problems in financial markets. They argue, moreover, that international capital markets help to discipline policymakers, who might be tempted to exploit an otherwise captive domestic capital market. Others even claim that financial liberalization and the financial development it triggers tend to greatly facilitate economic growth.4 As has the group that favors more repression, the group supporting deregulation has also been growing in numbers.5

The empirical research, so far, has not helped to resolve the conflicting views. The findings in the crisis literature suggest that booms and busts in financial markets are at the core of currency crises and that these large cycles are triggered by financial deregulation.6 On the contrary, the findings in the finance literature tend to support the claim that deregulation is beneficial, with liberalization reducing the cost of capital.7 Perhaps, the inability to settle this debate is due to the fact that the various lines of empirical research focus either on the short-run or the long-run effects of deregulation, without studying the possible time-varying effects of financial liberalization. Moreover, the existing empirical literature has not provided a comprehensive analysis of the liberalization process. It has concentrated alternatively on the liberalization of the domestic financial sector, the capital account, or the stock market, even when liberalization reforms have entailed the progressive opening of the three sectors.

The goal of this paper is, first, to provide a better understanding of the liberalization process and, second, to explain both the link between liberalization and crises, as well as the relation between deregulation and more stable financial markets. To do so, we first assemble a new, more comprehensive database on financial liberalization for 28 countries for the period January 1973–June 1999. By itself, this is an important contribution, because this database is an improvement over the existing ones in several respects: (1) the new dataset looks at the experiences of a wide set of countries, both developed and developing; (2) it captures various aspects of liberalization, namely the deregulation of the capital account, the domestic financial sector, and the stock market; (3) the chronology covers an extended period in which several regulatory changes occurred, including deregulations and impositions of new controls; and (4) the new data provide information on the degrees of liberalization.

We also analyze the anatomy of stock-market cycles by applying algorithms designed to identify business cycles. With this technique, we study the duration and magnitude of upturns and downturns. Since financial cycles would be spurious if markets were efficient, we test the null hypothesis of a random walk.8 We then study whether booms and busts change with financial liberalization. We finally analyze the possibility that financial deregulation triggers forces that favor changes in institutions, which can ultimately promote financial stability and growth.

The rest of the paper is organized as follows. Section II describes the new data on financial liberalization and examines the patterns of deregulation. Section III characterizes booms and busts in the different regions. Section IV examines whether domestic financial liberalization and capital controls can explain the changing nature of financial cycles. Section V relates financial liberalization to institutional reform. Section VI concludes.

II. The Evolution of Global Financial Liberalization

One of the most prolific areas of empirical research in international economics and finance has been that of the analysis of the effects of controls and financial liberalization on financial markets, investment, and growth. Surprisingly, in spite of the great interest of several disciplines on the effects of deregulation of financial markets, the information on the evolution of financial regulations is still very fragmented. Below is a brief review of the existing measures.

Information on capital account controls is mostly based on indicators published by the International Monetary Fund (IMF) in its Annual Report on Exchange Arrangements and Exchange Restrictions.9 For the period 1975–95, this publication reports a single indicator classifying only two capital account regimes: a “no controls” regime, which includes episodes with full liberalization of the capital account, and a “controls” regime, which includes both episodes with minor restrictions to the free flow of capital as well as episodes with outright prohibition of all capital account transactions. This indicator does not distinguish between controls on capital inflows and controls on capital outflows. Not until 1996, did the IMF begin to publish a more comprehensive report on capital account controls, which still does not capture the intensity of controls.10

Information on regulations of the domestic financial sector is even more fragmented. There is no institution compiling systematic cross-country information over time and researchers have relied on varied sources. One of them is Williamson and Mahar (1998), which dates liberalization according to five distinct dimensions of financial liberalization: existence of credit controls, controls on interest rates, entry barriers to the banking industry, government regulation of the banking sector, and importance of government-owned banks in the financial system. Most researchers construct their own liberalization chronology. For example, Demirgüç-Kunt and Detragiache (1999) date liberalization for 53 countries since 1980. In that study, liberalization of the domestic financial sector is interpreted as liberalization of domestic interest rates.

Information on the liberalization of domestic stock markets is also still quite partial. The International Financial Corporation (IFC) provides this information just for emerging markets. Again, this index (as the IMF index for the capital account) only captures two regimes: a “liberalization” regime and a “restricted” regime. The liberalization dates are determined based on whether foreigners are allowed to purchase shares of listed companies in the domestic stock exchange and whether there is free repatriation of capital and remittance of dividends and capital gains. Others, such as Bekaert and Harvey (2000), construct their own chronologies of stock market liberalization to date liberalization episodes for emerging markets, using information compiled by the IFC and the establishment of new investment vehicles like country funds and depositary receipts.11

The existing chronologies share some limitations. One limitation is that they do not distinguish between different intensities of liberalization/repression. Since deregulation tends to change slowly, valuable information is lost when the indicators only try to assess whether or not the liberalization has occurred.12 Another limitation is that most chronologies analyze financial liberalization episodes as if they were permanent. Still, many countries have undergone several liberalization reversals, particularly following currency crises.13 Naturally, these limitations call for a more comprehensive analysis of the various aspects of financial controls.

A. New Measures of Financial Liberalization

The new measures of financial liberalization introduced in this paper try to overcome part of the shortcomings of previous chronologies discussed above. Thus, our database captures to some degree the intensity of financial liberalization episodes as well as episodes of liberalization reversals. Our chronology also tries to address some of the limitations of the empirical research on the effects of financial liberalization. First, most of the empirical research focuses on emerging markets, perhaps because most concerns are associated with liberalization episodes in developing countries, with even the most averse critics of capital account liberalization still supporting the financial deregulation of mature markets. A comprehensive picture of the effects of financial liberalization requires the analysis of deregulation episodes in both developed and developing countries, which the new database covers. Second, most of the previous studies focus on the elimination of controls on just one particular financial sector, be it the capital account, the domestic financial sector, and the stock market. This focus on the opening of just one financial market may result in a biased picture, since controls in one sector can also affect the behavior of other parts of the financial system, which may or may not be directly under any type of restrictions.14 The new chronology deals with the regulations in three sectors.

The new database includes 28 countries for the period 1973–1999.15 We classify the sample into four (mostly regional) country groupings: the G-7 countries, which are comprised of Canada, France, Germany, Italy, Japan, United Kingdom, and the United States; the Asian region, which includes Hong Kong SAR, Indonesia, Malaysia, the Philippines, the Republic of Korea, Taiwan (Province of China), and Thailand; the European group, which excludes those countries that are part of the G-7 and includes Denmark, Finland, Ireland, Norway, Portugal, Spain, and Sweden; and the Latin American sample, which consists of the largest economies in the region, Argentina, Brazil, Chile, Colombia, Mexico, Peru, and Venezuela.

To capture the liberalization of the capital account, we evaluate the regulations on offshore borrowing by domestic financial institutions, offshore borrowing by nonfinancial corporations, multiple exchange rate markets, and controls on capital outflows. The first two indicators reflect restrictions on capital inflows. Restrictions on capital inflows can take various forms, with the most extreme restriction being an outright prohibition to borrow overseas. Milder controls include restrictions of minimum maturity on capital inflows and non-interest reserve requirements on foreign borrowing.

To measure the liberalization of the domestic financial system, we analyze the regulations on deposit interest rates, lending interest rates, allocation of credit, and foreign-currency deposits. As additional information, we also collect data on reserve requirements. To set the liberalization dates, we focus mainly on the first two variables, the price indicators. However, we complement that information with the regulations on the last three variables, those on quantities, to have a better picture of the degree of repression of the domestic financial sector. Finally, to track the liberalization of stock markets, we study the evolution of regulations on the acquisition of shares in the domestic stock market by foreigners, repatriation of capital, and repatriation of interest and dividends.

For each sector, the chronology identifies three regimes: “fully liberalized,” “partially liberalized,” and “repressed.” The criteria used to determine whether the capital account, the domestic financial sector, and the stock market are fully or partially liberalized, or repressed, are described in detail in Appendix Table 1. We established these criteria after collecting all the regulations and carefully studying the range of restrictions adopted throughout countries and years. We believe that these criteria characterize well the degrees of financial liberalization. The chronology of restrictions compiled for each country and sector along with the complete list of references used to construct it are described in Appendix Tables A2 and A3 16

Table 1 reports the dates of partial and full financial liberalization for all the countries in the sample. The first three columns of dates display the liberalization of the capital account, the domestic financial sector, and the stock market. The last two columns report dates of partial and full liberalization taking into account the three sectors analyzed. A country is considered to be fully liberalized when at least two sectors are fully liberalized and the third one is partially liberalized. A country is classified as partially liberalized when at least two sectors are partially liberalized.

Table 1.

Liberalization Dates

article image
This table reports the dates of partial and full liberalization of financial markets. The first three columns provide information by sector: capital account, domestic financial sector, and the stock market. The last two columns provide information on an integral measure of financial liberalization. The dates are based on the criteria displayed in Appendix Table 1. A country is considered to be fully liberalized when at least two sectors are fully liberalized and the third one is partially liberalized. A country is considered to be partially liberalized if at least two sectors are partially liberalized. Otherwise, the country is considered to be financially repressed. If there is no information about the month of liberalization, we use January (December) if the corresponding report indicates that liberalization is implemented at the beginning (end) of the year. “-” followed by a blank means that it covers the period until June 1999. Pre 73 (Pre 73p) means that the sector is already fully (partially) liberalized at that time, with no significant measures taken at that date.

B. Pace and Dynamics of Liberalization

Figures 1–3 and Table 2 summarize the information in Table 1 by displaying the time-series and cross-sectional variation of liberalization. Figure 1 plots the index of financial liberalization in emerging and mature markets. This index jointly evaluates the liberalization of the capital account, the domestic financial sector, and the stock market. It can take values between one and three, with one indicating fully liberalized and three indicating fully repressed financial systems. As expected, mature financial markets are on average less regulated. The index for mature markets averages 1.7 over the sample, while for emerging markets, it averages 2.3. Interestingly, across all regions there is a gradual lifting of restrictions, with the index of liberalization declining from an initial value of 2.5 for mature markets and 2.9 for emerging economies to one and 1.2, respectively, toward the end of the sample. Still, there is also a regional pattern in the dynamics of financial liberalization, with emerging markets suffering liberalization reversals in the early 1980s, following the debt crisis. In contrast, the pace of liberalization in mature markets, while also gradual, is uninterrupted.

Figure 1.
Figure 1.

Index of Financial Liberalization

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

The index of financial liberalization jointly evaluates the liberalization of the capital account, the domestic financial sector, and 1he stock market. The index is a cross country average. The value three means repression, two means partial liberalization, and one means full liberalization. Mature markets include: Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, Norway, Portugal, Spain, Sweden, United Kingdom, and United States. Emerging markets include: Argentina, Brazil, Chile, Colombia, Hong Kong SAR, Indonesia, Korea, Malaysia, Mexico, Peru, Philippines, Taiwan (Province of China), Thailand, and Venezuela.
Figure 2.
Figure 2.

Indexes of Financial Liberalization by Sector

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

The three indexes evaluate separately the liberalization of the capital account, the domestic financial sector, and the stock market. The indexes are a cross-country average. The value three means repression, two means partial liberalization, and one means full liberalization. Mature markets include: Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, Norway, Portugal, Spain, Sweden, United Kingdom, and United States. Emerging markets include: Argentina, Brazil, Chile, Colombia, Hong Kong SAR, Indonesia, Korea, Malaysia, Mexico, Peru, Philippines, Taiwan (Province of China), Thailand, and Venezuela.
Figure 3.
Figure 3.

The Sequencing of Financial Liberalization

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

The panels show the proportion of countries with (at least partially) liberalized capital account, domestic financial sector, and stock market. Mature markets include: Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, Norway, Portugal, Spain, Sweden, United Kingdom. and United States. Emerging markets include: Argentina, Brazil, Chile, Colombia, Hong Kong SAR, Indonesia, Korea, Malaysia, Mexico, Peru, Philippines, Taiwan (Province of China), Thailand, and Venezuela.
Table 2.

Sequencing of Liberalization

article image
The bottom panel reports the duration of the liberalization reform measured as the number of months between the partial opening of the first sector and the partial opening of the third sector.

Figures 2 and 3 examine separately the sequencing of liberalization of the capital account, the domestic financial sector, and the stock market. Figure 2 shows the index of liberalization for each sector for both emerging and mature markets. Stock markets in developed countries are liberalized earlier, with the index for this sector oscillating around 1.5 in the early 1970s. In contrast, both the domestic financial sector and the capital account tend to be severely repressed until the early 1980s. In the early 1970s, the indexes for both sectors are on average above 2.5. Financial markets across the board are heavily repressed in developing countries in the early 1970s. But in the mid and late 1970s, many emerging economies liberalize the domestic sector and the capital account. The liberalization reform is short-lived. Controls are re-imposed in the aftermath of the 1982 debt crisis. Overall, restrictions in stock markets remain in place until the late 1980s when a liberalization wave occurs in Asia and Latin America.

While Figure 2 provides information on the average level of restrictions in the various financial markets in the two regions, it may still mask individual country experiences. For example, a medium value of the index in one region may reflect that all the countries in that region are partially liberalized, or that some countries are fully liberalized while the rest of the countries are completely repressed. Figure 3 presents another perspective of the sequencing of liberalization across countries. This figure reports the proportion of countries with (at least) partial liberalization of the capital account, the domestic financial sector, and the stock market, again examined separately for emerging markets and mature markets. By the early 1970s, about 80 percent of stock markets in mature markets are already liberalized. In mature markets, the liberalization of the domestic financial sector also predates the opening of the capital account, with about all countries liberalizing, at least partially, the domestic financial sector by the mid 1980s. It is only in the late 1980s and the beginning of the 1990s, in part driven by the movement toward the formation of the European Monetary Union, that capital account liberalization reaches all mature markets.

Liberalization follows a different path in emerging markets. Only a small proportion of countries implement reforms before the early 1970s. This proportion increases in the late 1970s and then again in the mid and late 1980s. By early 1990s, all the sectors of the financial system are finally liberalized. There are two episodes of financial liberalization. The first one is in the late 1970s. In this episode, all the action centers in the domestic sector and the capital account, with the stock market continuing to be out of the reach for foreign investors. This liberalization episode ends following the debt crisis in 1982. The second wave of liberalization starts in the late 1980s. This time around, basically both the domestic sector and the stock market are jointly deregulated, predating capital account liberalization that only starts in the early 1990s.

Table 2 examines even further the sequencing of liberalization by analyzing the strategies and duration of liberalizations in Asia, Europe, G-7 countries, and Latin America. The top two panels show the proportion of episodes in which the capital account, the domestic financial sector, or the stock market is liberalized first. The top panel focuses on partial liberalization episodes, the panel below examines full liberalization episodes. The bottom two panels display the duration of liberalization episodes; they report the number of months from the time the first market is deregulated until liberalization is implemented in all markets. The top two panels reveal that the paths toward financial reform differ across regions. Basically all the G-7 countries deregulate the stock market first. European countries implement a somewhat mixed strategy toward deregulation, with 25 percent of the countries liberalizing the domestic financial sector first and basically all the rest deregulating the stock market first. On the other hand, Latin American countries overwhelmingly adopt liberalization of the domestic financial sector first, while Asian countries follow a mixed strategy, with some countries opting for deregulating the domestic sector first and some others focusing on the stock market first. Capital account liberalization in all Asian countries is mostly introduced at a latter stage.

The bottom panels reveal that liberalization reforms take a long time to be completed. On average, 66 months elapse from the time the first market is liberalized until all markets are deregulated. Interestingly, the time to completion of the liberalization reform is far longer in Asia than in Latin America. Finally, liberalization episodes that are first implemented in the stock market are the ones that become completed the fastest. The variety of experiences in financial reforms indicates that it is important to examine not just the responses to liberalization in one particular financial market, but that it is important to examine the effects of the sequencing of the deregulation reform.

III. Financial Cycles

As discussed above, to understand better the conflicting stylized evidence on the effects of financial liberalization, it is useful to study the short-and long-run response of financial markets to deregulation. This section sets the groundwork to reconcile the evidence by constructing an anatomy of booms and busts (crashes) in stock markets.

A. Methodology for Identifying Financial Cycles

There is a long tradition in macroeconomics in analyzing economic fluctuations in terms of business-cycle phases. Economists have examined the behavior of output in expansions and recessions, with particular attention to asymmetries in the two phases and to the possible changing nature of those fluctuations. For the United States, there is also an “official” classification of the cycle in expansions and contractions. No similar interest has flourished in characterizing boom-bust cycles in financial markets. Most studies in financial markets are focused on examining the relation between dividends, interest rates, and stock prices to evaluate whether markets are efficient. Other papers analyze the time-varying volatility in financial markets using ARCH-GARCH models. A third line of research looks at the domestic and global factors that influence prices.17 In contrast, there seem to be no studies on the behavior of stock prices over financial cycles. This lack of evidence on the amplitude and duration of booms and busts seems particularly notable in light of the evidence that links booms and busts in credit and asset prices with financial crises.

Perhaps, the lack of interest in booms and busts in stock prices steams from the idea that in efficient markets prices should follow random walk processes. In this case, cycles are meaningless. However, as Cecchetti, Lam, and Mark (1990) show, even in efficient markets stock prices can follow mean-reverting processes, with cycles in the stock market replicating cycles in output. Moreover, cycles could be magnified by the increasing presence of institutional investors, which tend to follow momentum-based fads (buying stocks that are past winners and selling past losers), and by the presence of asymmetric information that leads to herding.18

This paper concentrates on the fluctuations of stock prices without trying to quantify the possible imperfections in financial markets. The latter would not be an easy task due to the lack of agreement about the empirical counterpart to any definition of equilibrium stock prices. However, while we do not isolate the effects of fundamentals and fads on financial cycles, the characterization of stock market cycles will allow us to start understanding the behavior of financial markets. In particular, we will be able to have a reading on whether financial liberalization has magnified the boom-bust cycles in financial markets.

The question now is how to identify historical cycles in stock prices. There is no general agreement on the techniques to isolate fluctuations of variables at business cycles frequencies. The first approach was that pioneered by researchers at the National Bureau of Economic Research (NBER).19 The business cycle turning points were identified retrospectively and on an ongoing basis by the NBER. Although initially these turning points were determined judgmentally, the process can be well approximated by a computer algorithm developed by Bry and Boschan (1971). The NBER continues to use this methodology to identify what has become to be known as the official business cycles dating in the United States.20

In this paper, we follow the approach used by the NBER to construct an algorithm that identifies turning points. We examine stock market fluctuations at intermediate frequencies, since financial crises tend to follow boom-bust cycles in financial markets of an intermediate duration, between two and three years. According to Bry and Boschan (1971), the first step in the determination of cycles is the identification of cyclical turning points. This technique and the algorithms that we apply look for clearly defined swings in stock market prices in each country. We work with the same order of duration as business cycles, that is swings that are longer than two years. This is the only identifying restriction. We are not imposing any other restrictions such as minimum amplitude of cycles. Essentially, the algorithm isolates local minima and maxima in a time series, subject to the constraint that the duration of upturns and downturns cannot be less than 12 months.21

The cycles we identify would be spurious if stock prices followed random walk processes. To show that the random walk does not capture the basic properties of the data on stock prices, we estimate random walks with drift using parameters calculated from the actual data. For each country, we simulate a specific model 1,000 times. Since some of the series on stock prices do not span the whole sample, the number of months for each country simulation is the same as the number of months in the actual data. We then filter the simulated data with the algorithm and compare the cycles generated by random walk processes and those generated by the actual data.

B. Empirical Regularities

Figure 4 reports monthly log stock price indexes for the 28 countries in the sample. Stock prices are measured in 1993 U.S. dollars22 (Appendix Table 4 reports the indexes used as well as their sources.) Figure 4 also identifies the booms and crashes obtained using the algorithm described above. The algorithm identifies 146 cycles. The shaded areas denote expansions. The series show well-defined swings with an average duration of about 44 months.

Figure 4.
Figure 4.

Stock Markets Indexes

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

Stock market indexes are in constant U.S. dollars (in logs). Base 1993 = 100. The sample covers from January 1975 to June 1999. Peaks are calculated using +/- 12 months windows. The shaded areas mark the identified expansion episodes.

Table 3 examines the characteristics of stock cycles in the 28 countries in the sample and compares them to the behavior of the random walk simulations. This table provides mean values and tests of whether the differences between the actual and simulated samples are statistically significant. Columns 2–3 and 5–6 report the mean amplitude and duration of cycles using the actual and simulated data. Columns 4 and 7 report the significance level of tests of the null hypothesis that mean cycles from the actual and simulated data are equal. The depth of the contraction (height of the expansion) is measured as the change between the peak (trough) and the following trough (peak), as a percent of the mid value of the peak and trough. This measure puts the amplitude of expansions and contractions on an equal foot. Finally, the duration of a contraction (expansion) is defined as the number of periods between a peak (trough) and the following trough (peak).

Table 3.

Characteristics of Stock Market Cycles

article image
The table shows the average amplitude and duration of booms and crashes in stock prices for the actual data and for the simulated data, under null hypothesis that stock prices follow a random-walk process. The stock market indexes start in January 1975 and end in June 1999. The filter used identifies 146 stock market cycles. To estimate the average amplitude of booms and crashes under the null hypothesis of a random walk, we first estimate a random walk with drift model for each country. We simulate those models 1,000 times. Since the stock market series for several countries do not span the whole sample, the length of the simulated random walk series for each country is the same as the length of the actual series. Amplitude is expressed in percent, calculated as a deviation from the mid point between the peak and the trough. Duration is expressed in months. Standard errors are in parentheses.

According to Table 3, booms across all regions oscillate around 74 percent. The typical contraction in stock markets is about 61 percent. The data reveal that contractions tend to be short-lived relative to expansions. The mean duration of contractions is around 18 months, while the mean duration of expansions is around 26 months and statistically different from the duration of contractions at all conventional significance levels. From the table, it is clear that there are significant differences between the amplitude of booms and crashes in the actual data relative to the one that is observed under the null hypothesis of a random walk. The amplitude of booms for the actual data is about 15 percent larger than the average amplitude for the simulated data. Similarly, the average duration of booms for the actual data is about 20 percent longer than the average duration for the simulated data. Analogous comparisons can be made for contraction episodes. Again, contractions obtained from the actual data are significantly more protracted than those obtained from random walk processes.

To provide another picture of the differences between the actual and simulated data, Figure 5 reports the frequency distribution of the amplitude and duration of booms and crashes. The horizontal axis in each figure shows the size or duration of booms and crashes, the vertical axis shows the frequencies in percent. If stock prices followed a random walk process, the frequency distribution of the amplitude and duration of each phase of the cycle for the actual and the simulated data would be equal. From this figure, it is clear that there are significant differences in the amplitude and duration of booms and crashes relative to what one would expect if stock prices followed random walks. Booms and crashes are more pronounced and protracted than those generated under the null hypothesis of a random walk. Kolmogorov-Smirnov test are used to evaluate the null hypothesis of equal frequency distributions of the size and duration of booms and crashes in the actual and random walk data. As shown by the p-value at the bottom of each panel, we reject the null hypothesis that stock prices follow random walk processes.

Figure 5.
Figure 5.

Frequency Distribution of the Amplitude and Duration of Stock Market Booms and Crashes

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

The figures report the frequency distribution of the amplitude and duration of booms and crashes for the actual and simulated data, assuming random walk processes with drift. The horizontal axis in each figure shows the size or the duration of booms and crashes, the vertical axis shows the frequencies in percent. The Kolmogorov-Smirnov test is used to evaluate the null hypothesis of equality of the frequency distribution of the amplitude and duration of booms and crashes in the actual and generated data.

Figure 6 examines the characteristics of the typical cycle in the four regions. The top panel reports the mean amplitude and duration of booms and crashes in Asia, Europe, the G-7 countries, and Latin America. The bottom panel plots the typical cycle in each region. The horizontal axis in the figure records the number of months before and after the peak of the cycle. The horizontal axis contains 26 months for expansions and 18 months for contractions. These are the durations of the two phases for the typical cycle in our sample. The vertical axis reports the value of the stock index. To obtain the typical cycle, the value of the stock index in each cycle is normalized to 100 at the peak. Each line in this panel represents the average value of the stock index during the 44 months around the peaks of the four regions.

Figure 6.
Figure 6.

Characteristics of Regional Cycles

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

Notes: The table and figure show the average cycle per region. The sample starts in January 1975 and ends in June 1999. The total number of cycles per region is as follows: 28 for Asia; 35 for Europe; 44 for G-7; and 39 for Latin America. In the top panel, duration is expressed in months while amplitude is expressed in percent; it is calculated as a deviation from the mid point between the peak and the trough.

Figure 6 shows that cycles are more pronounced in Latin America. On average, the amplitude of cycles in this region is about twice as large as the amplitude of cycles in the G-7 countries. As expected, the most developed countries, the G-7, have milder stock market cycles, with the Asian and the other European stock market cycles being of intermediate magnitudes. The Asian cycles are larger than the European ones. In contrast to the disparities concerning the amplitude of cycles, the duration of booms and busts is similar across regions, though the ones from developed countries tend to be longer, making the larger amplitudes for emerging markets even more striking.

IV. Stock Market Cycles and Financial Liberalization

To examine the claim that financial liberalization triggers more protracted and deeper booms and busts in asset markets, we examine the characteristics of financial cycles during episodes of financial repression and liberalization. Our first approach is in the event study tradition, analyzing the behavior of stock markets in the aftermath of liberalization relative to their functioning in repression times, those years before deregulation occurs. To examine the conflicting views that liberalization triggers financial excesses but also contributes to less volatile financial markets, we compare the characteristics of financial cycles in the short run and long run following liberalization. We then report regression results that control for other factors and study the sequencing of the openings. Those results examine whether liberalization creates larger cycles when the first market opens or whether each consecutive opening triggers substantial increases in booms and crashes. The regressions also test whether financial turbulences are just the product of liberalization episodes that start with opening first the capital account, the domestic sector, or the stock market.

A. Event Studies

Figure 7 examines the characteristics of financial cycles around the time of the overall partial liberalization of financial markets, that is, when at least two sectors are partially liberalized. We classify financial cycles in three categories, those that occur during repression times, those that occur in the short run after liberalization, and those that occur in the long run following liberalization. The short run is defined as the four years after liberalization. The long run includes the fifth year after liberalization and the years thereafter, conditional on the deregulation not being reversed.23 The top panel in Figure 7 shows the average amplitude of booms and crashes for all countries in our sample during repression times (the striped bars), the short-run effects of liberalization (the white bars), and the long-run effects of liberalization (the gray bars). It also reports the characteristics of cycles separately for emerging and mature markets since the evidence from these two groups of countries might differ. The bottom panel examines whether the differences of amplitudes across regimes are statistically significant.

Figure 7.
Figure 7.

Average Amplitude of Booms and Crashes

(in percent)

Citation: IMF Working Papers 2003, 034; 10.5089/9781451845280.001.A001

The figure shows the average amplitude of booms and crashes in the different periods and markets (mature and emerging). The table shows hypothesis tests of equality of booms and crashes during repression times and after liberalization. The repression period occurs when less than two sectors are partially liberalized. The short-run liberalization period is defined as the immediate aftermath of partial financial liberalization (four-year window), and zero otherwise. The long-run liberalization period occurs after four years have elapsed from the time of the partial financial liberalization.

The evidence for the 28 countries in the sample indicates that the amplitude of booms substantially increases in the immediate aftermath of liberalization (about 20 percent higher than during repression times). But equity markets stabilize in the long run if liberalization persists, with the amplitude of booms about 25 percent smaller than in repression times. Similarly, the amplitude of crashes increases in the immediate aftermath of liberalization (about 15 percent higher than during repression times), but declines to about 60 percent of its size during repression times if liberalization persists in the long run. As shown in the bottom panel, these differences are statistically significant at conventional levels.

The evidence for the 28 countries, however, obscures important differences across emerging and mature markets. When examined separately, we note that the short-run effects of liberalization in emerging markets are more striking, with booms and crashes in the immediate aftermath of liberalization increasing by about 35 percent over their size during repression. Still, if liberalization persists, financial cycles become less pronounced, with booms about 30 percent smaller than during repression times, and crashes about 90 percent of their size during repression times. On the other hand, the evidence from mature markets indicates that if liberalization triggers more volatile stock markets in the short run, booms and busts do not increase as much as in the case of emerging markets. Moreover, on average, crashes do not increase relative to their value during repression times. Still, liberalization seems to generate more stable financial markets in the long run, with crashes averaging only about 60 percent of their size in repression times.

B. Accounting for Domestic and External Shocks

While the evidence in Figure 7 suggests that financial liberalization influences the size of expansions and contractions in financial markets, stock price fluctuations also reflect changes in other market fundamentals. For example, stock prices respond to expansions and recessions in the domestic economy. They also react to world economic conditions.24 The omission of these variables may bias our results, especially since the timing of liberalization may not be fortuitous. In fact, we have described in Section I that Latin American countries reintroduce controls on domestic interest rates and credit and re-impose controls on capital flows following the hikes in interest rates in industrial countries in the early 1980s. Also, many emerging markets liberalize their financial markets when international capital flows resume in the late 1980s. Insofar as countries react to “bad times” by adopting capital controls and to “good times” by relaxing them, there is the danger that we may ascribe the increase in the size of booms to liberalization and the amplification of crashes to capital controls, when in fact it is the world market condition the one fueling changes in stock prices.

To account for these factors, the event study analysis is complemented with regressions that control for domestic and world economic conditions. In particular, we examine the role of growth in domestic and world economic activity and changes in world real interest rates. We estimate the following equation by least squares with heteroskedastic-consistent standard errors,

amplitude i = α ′ X i + ρ 1 d i r + β 1 d i s r + λ 1 d i l r + ε i , ( 1 )

where amplitudei is the amplitude of expansion (contraction) i. Xi is a matrix of control variables that includes the change in world real interest rate, the world output growth, and the domestic output growth during each expansion (contraction). dir is a dummy variable equal to one if the cycle occurs during “repression” times, and zero otherwise. disr is a “short-run” dummy variable equal to one if the cycle occurs in the immediate aftermath of financial liberalization (four-year window), and zero otherwise. dilr is a “long-run” dummy variable equal to one if the cycle occurs after four years have elapsed from the time of financial liberalization, and zero otherwise. The world real interest rate is proxied with the U.S. federal funds real interest rate, world output is the average of the industrial production indexes of the G-3 countries, and domestic output is captured by the index of industrial production in the domestic economy. All data come from the IMF’s International Financial Statistics.

The results from this estimation are shown in Table 4. As in Figure 7, this table examines the effects of overall partial financial liberalization (when at least two sectors have been partially liberalized). As expected, fluctuations in the world interest rate affect stock market cycles as does output growth, with a one percentage point increase in the world real interest rate leading to a five percentage point contraction in the amplitude of stock market expansions. Similarly, booms and crashes in stock markets are also explained by upturns and recessions in the domestic economy. Even after accounting for these other determinants of fluctuations in stock prices, financial liberalization still matters. Financial liberalization triggers larger cycles in the short run and stabilizes financial markets in the long run. Interestingly, once we control for the state of the economy (domestic and foreign) and for interest rate fluctuations, the short-run effects of financial liberalization become even more pronounced. For example, in the immediate aftermath of liberalization, booms increase by about 40 percent in emerging markets and by 55 percent in mature markets relative to repression times. Similarly, crashes in emerging markets increase by 30 percent in the immediate aftermath of liberalization vis-à-vis repression times.

Table 4.

Determinants of Booms and Crashes: The Effects of Partial Liberalization

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The top panel shows regressions of the amplitude of booms (crashes) in stock markets on changes in the world real interest rate, world output growth, domestic output growth, a dummy for “repression” effects, a dummy for “short-run liberalization” effects, and a dummy for “long-run liberalization” effects. The bottom panel reports hypothesis tests on the regression coefficients. A country is considered to be partially liberalized if at least two sectors are partially liberalized. Otherwise, the country is considered to be financially repressed. The change in world real interest rate, the change in world output, and the change in domestic output are growth rates from the beginning to the end of the corresponding boom or crash. “Repression” is a dummy variable equal to one if the particular phase of the cycle occurs during repression times, and zero otherwise. “Short-run liberalization” is a dummy variable that equals one if the particular phase of the cycle occurs in the immediate aftermath of partial financial liberalization (four-year window), and zero otherwise. “Long-run liberalization” is a dummy variable equal to one if the particular phase of the cycle occurs after four years have elapsed from the time of the partial financial liberalization, and zero otherwise. Standard errors are in brackets. *, **, *** mean significance at 10, 5, and 1 percent, respectively.

Note that the results in Figure 7 and Table 4 suggest two tales about the aftermath of liberalization reforms. While larger booms follow liberalization in both emerging and mature markets, it is only in emerging markets that crashes are more severe following liberalization. The average short-run experience in emerging markets seems to support the evidence from the crisis literature that concludes that liberalization leads to excessive financial booms and crashes. Liberalization episodes do not seem to bring (on average) this short-run pain to mature markets; larger booms are not followed by larger crashes, suggesting that larger booms may just reflect the reduction in the cost of capital once deregulation takes place, as the finance literature argues.25 Still, financial liberalization brings more stable financial markets in both emerging and mature market economies in the long run. In section IV, we examine possible explanations for the varied short-run effects of liberalization as well as for the long-run gains across countries.

C. Sequencing of Liberalization

So far we have studied the liberalization across all markets. Now we turn to examine whether the short-run increase in boom-bust amplitudes occurs every time a new sector is deregulated and whether the sequencing of the openings matters. Table 5 examines whether the short-run increase in booms and busts occurs every time a new sector is deregulated. We limit our search to the deregulation of the first two sectors. We define repression times as those episodes in which all sectors are closed. The short-run liberalization periods are the four years after the opening of the first sector and the four years after the opening of the second sector. The long-run liberalization episode includes the fifth year after the opening of the second sector and the following years if the liberalization reform is not reversed.

Table 5.

Determinants of Booms and Crashes: The Effects of Sequencing I

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This table analizes whether the sucessive liberalizations of the three sectors trigger more unstable financial markets (larger booms and crashes) in the short run. The top panel shows regressions of the amplitude of booms (crashes) in stock markets on the change in the world real interest rate, world output growth, domestic output growth, a dummy for “repression” effects, two dummies for “short-run liberalization” effects, and a dummy for “long-run liberalization” effects. The change in world real interest rate, the change in world output, and the change in domestic output are growth rates from the beginning to the end of the corresponding boom or crash. “Repression” is a dummy variable equal to one if the particular phase of the cycle occurs during repression times, and zero otherwise. “Short-run liberalization sector one and two” is a dummy variable that equals one if the particular phase of the cycle occurs in the immediate aftermath of financial liberalization of the first or second sectors (four-year window), and zero otherwise. “Short-run liberalization sector two” is a dummy variable that equals one if the particular phase of the cycle occurs in the immediate aftermath of financial liberalization of the second sector (four-year window), and zero otherwise, “Long-run liberalization” is a dummy variable that equals one if the particular phase of the cycle occurs after four years have elapsed from the time of financial liberalization of the second sector, and zero otherwise. The bottom panel reports hypothesis tests on the regression coefficients. “Short-run liberalization first (second) sector” corresponds to the test of the null hypothesis that the opening of the first (second) sector does not trigger larger booms and crashes relative to repression times or long-run liberalization, alternatively. If the stock market is liberalized before 1973, only the capital account and the domestic financial sector are being considered in the analysis. Standard errors are in brackets. *, **, *** mean significance at 10, 5, and 1 percent, respectively.

We estimate the following regression,

amplitude i = α ′ X i + ρ 1 d i r + β 1 d i s r , 1 , 2 + β 2 d i s r , 2 + λ 1 d i l r , 2 + ε i . ( 2 )

The new variable disr,1,2 is a dummy variable equal to one if the cycle occurs in the immediate aftermath of financial liberalization (four-year window after the first sector is deregulated and four-year window after the second sector is deregulated), and zero otherwise. disr,2 is a dummy variable equal to one if the cycle occurs in the four years after the deregulation of the second sector, and zero otherwise. dilr,2 is a dummy variable equal to one if the cycle occurs after four years have elapsed from the time of the liberalization of the second sector, and zero otherwise. Thus, the average amplitude of booms (crashes) in the aftermath of the first opening is captured by β1, while that of the second market opening is captured by β1+β2.

While the evidence on short-and long-run effects of financial liberalization is not reversed, the focus on the first and second openings reveals some important differences. Interestingly, the increase in the amplitude of booms is similar following the first and second opening, but crashes in the immediate aftermath of the first opening are smaller than those observed during repression times. The amplitude of crashes in emerging markets only increases following the opening of the second sector. Again, this evidence is consistent with the results from the crisis literature, which finds that booms of credit persist for several years following the deregulation of financial markets with these booms in turn fueling protracted bull markets.

Table 6 examines the effects on financial markets of various types of sequencing of the deregulation process. We estimate the following regression,

amplitude i = α ′ X i + ρ 1 d i r + β 1 d i s r , 1 , 2 + β 2 d i s r , 2 + β 3 d i C A + β 4 d i + λ 1 d i l r , 2 + ε i . ( 3 )
Table 6.

Determinants of Booms and Crashes: The Effects of Sequencing II

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This table shows whether the short-run effects of liberalization depend on which sector is deregulated first. The top panel shows regressions of the amplitude of booms (crashes) in stock markets on changes in the world real interest rate, world output growth, domestic output growth, a dummy for “repression” effects, two dummies for “short-run liberalization” effects, a dummy for the capital account opening if this is the first sector to open, a dummy for the stock market opening if this is the first sector to open, and a dummy for “long-run liberalization” effects. The change in world real interest rate, the change in world output, and the change in domestic output are growth rates from the beginning to the end of the corresponding boom or crash. “Repression” is a dummy variable equal to one if the particular phase of a cycle occurs during repression times, and zero otherwise. “Short-run liberalization sector one and two” is a dummy variable that equals one if the particular phase of a cycle occurs in the immediate aftermath of financial liberalization of the first and second sectors (four-year window), and zero otherwise. “Short-run liberalization sector two” is a dummy variable that equals one if the particular phase of the cycle occurs in the immediate aftermath of financial liberalization of the second sector (four-year window), and zero otherwise. “Long-run liberalization” is a dummy variable that equals one if the particular phase of the cycle occurs after four years have elapsed from the time of financial liberalization of the second sector, and zero otherwise. “First sector to open: capital account (stock market)” is a dummy variable equal to one if the first sector to open is the capital account (stock market), and zero otherwise. The bottom panel reports hypothesis tests on the regression coefficients, “Short-run liberalization domestic financial sector (capital account/stock market)” corresponds to the test of the null hypothesis that opening first the domestic financial sector (capital account/stock market) does not trigger larger booms and crashes relative to repression times or long-run liberalization, alternatively. If the stock market is liberalized before 1973, only the capital account and the domestic financial sector are being considered in the analysis. Standard errors are in brackets. *, **, *** mean significance at 10, 5, and 1 percent, respectively.

The variables diCA and diSM help to capture the possible differential effect on booms and crashes of opening respectively the capital account and the stock market first. These dummy variables are equal to one if the cycle occurs during the four years after that particular sector is liberalized, and zero otherwise. The average amplitude of booms (crashes) in the aftermath of the first opening, when the liberalization reform is initiated with the deregulation of the domestic financial sector, is captured by β1. If the liberalization reform starts with the opening of the capital account (stock market), the amplitude of booms or crashes in the four years after the first opening is captured by β1+ β3 (β1 + β4).

Our results indicate that the ordering of liberalization does not matter in general. Opening the capital account or the stock market first does not have a different effect than opening the domestic financial sector first. But one exception exists; crashes seem to be larger in emerging markets if the capital account opens up first. This might provide some mild support to the usual claim that the capital account should be opened last.

In sum, our results suggest that we gain from examining the effects of deregulation of different sectors. In particular, we find that crashes become more pronounced not at the onset of the liberalization reform but after some years have elapsed. Interestingly, the sequencing of financial liberalization does not seem to matter when evaluating the effects on financial cycles. Finally, as also shown in the previous section, the experiences of mature and emerging markets look different in the aftermath of financial liberalization. We analyze these differences next.

V. Financial Liberalization and Institutional Reform

Our findings necessarily provoke several questions. What is the essential ingredient for more stable financial markets in the long run? Is it just financial liberalization? Or, does liberalization trigger some other changes that in turn deliver more stable financial markets in the long run? Can we explain the differences in the aftermath of financial liberalization in mature and emerging markets? And, is it possible to avoid the short-run pain following liberalization?

These questions have generated an intense debate on the sequencing of liberalization and institutional reform. 26 Many have argued that it is very risky to open up financial systems. During financial repression, banks tend to have poor balance sheets.27 Protected from outside competition, badly regulated, and badly supervised banks do not have the pressure to run efficiently. Liberalization in this scenario unveils a new problem, as protected domestic banks suddenly get access to new sources of funding, triggering protracted financial booms. Moreover, financial liberalization brings competition and lowers bank profits, eroding banks’ franchise values and lowering their incentive for making good loans. Naturally, this worsens problems of moral hazard.28 Based on these views, a standard recommendation on sequencing is to first clean up domestic financial institutions and change government institutions, then deregulate the industry and open up the capital account.

This discussion about sequencing may be irrelevant if the timing is such that reforms never predate liberalization, with institutional changes happening mostly as a result of financial deregulation. To shed new light on this sequencing debate, we collect data on the quality of institutions as well as data on the laws governing the proper functioning of financial systems. Then, we compare the timing of financial liberalization and institutional reforms. The data on the quality of institutions is captured by the index of law and order.29 To better assess the functioning of the financial system, we use information on the existence and enforcement of insider trading laws, constructed by Bhattacharya and Daouk (2002). Appendix Table 5 reports the time of improvement in the law and order index, the time when the insider trading law is passed, and the time when insider trading starts to be prosecuted.

We characterize as an improvement in the quality of government institutions when the index of law and order increases by one unit and this change is maintained for at least two years.

The top panel in Table 7 examines the sequencing of liberalization and reform in our sample of 28 countries. It shows the probabilities that financial liberalization occurs conditional on reforms having already been implemented. In particular, we look at whether reforms to institutions occur prior to the partial or full liberalization of the financial sector. If governments clean up financial institutions and improve the quality of institutions prior to deregulating the financial sector, one would expect this probability to be close to one.

Table 7.

Financial Liberalization and Institutional Reforms

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Panel A shows the probability of financial liberalization conditional on the existence and enforcement of insider trading laws and on the dummy for law and order. Panel Β reports the regression reported in Table 4 with the inclusion of the institutional variables: law and order, existence of insider trading laws, and enforcement of insider trading laws. “Law and order” is a dummy variable that equals one in periods in which there is a “permanent” improvement in the International Country Risk Guide’s index of law and order or the index is at its highest level. The improvement periods in this index are characterized by at least one point increase in the index from its two-year period average, and the maintainance of the index above this average for at least another two years. “Insider trading laws” are dummy variables that equal one after the existence or enforcement of those laws. The data come from Bhattacharya and Daouk (2000). See Appendix Table 3. Standard errors are in brackets. *, **, *** mean significance at 10, 5, and 1 percent, respectively.

The evidence for emerging and mature markets displayed in Table 7 suggests that reforms to institutions occur mostly after liberalization is implemented. For example, in the case of emerging markets, in only 18 percent of the cases, law and order improves prior to the partial liberalization of financial markets. Also, while in 62 percent of the cases, the laws prosecuting insider trading exist prior to partial financial liberalization, insider trading starts to be prosecuted in only 11 percent of the cases before the partial deregulation of the financial sector. Interestingly, law and order improves substantially following partial liberalization. By the time the financial sector becomes fully liberalized, the quality of institutions, as measured by the law and order index, has improved in 64 percent of the cases. Also, insider trading prosecution is enforced in 44 percent of the cases before the full liberalization of the financial sector.

This evidence casts doubts on the notion that governments tend to implement institutional reforms before they start deregulating the financial sector. On the contrary, the evidence suggests that partial liberalization fuels institutional reforms. The evidence for mature markets is less compelling. Still, insider trading prosecution is only enforced in 17 percent of the cases prior to the partial liberalization of the financial sector, but in this case, in 44 percent of the cases, institutions improve prior to the full liberalization of the financial sector. Again, both indicators show that reforms continue following partial liberalization.

There are several reasons that can explain why financial liberalization might prompt institutional reforms. First, as discussed in Rajan and Zingales (2001), well-established firms may oppose reforms that promote financial development because it breeds competition. These firms can even be hurt by financial development as financial development implies better disclosure rules and enforcement (reducing the importance of these firms’ collateral and reputation) and permits newcomers to enter and compete away profits. We can add that incumbents may oppose the removal of capital controls as capital can flow away to more attractive destinations, limiting their sources of funds. However, opposition may be weaker in the presence of worldwide abundance of trade and cross-border flows. In these times, free access to international capital markets will allow the largest and best-known domestic firms to tap foreign markets for funds, with the support for financial liberalization becoming stronger. But financial liberalization sows the seeds of destruction of the old protected and inefficient financial sector, as foreign and domestic investors (now with access to international capital markets) require better enforcement rules.

Second, as mentioned before, the liberalization and the gradual integration of emerging markets with international financial markets by itself may help to fortify the domestic financial sector. Foreign investors have overall better skills and information and can thus monitor management in ways local investors cannot. Liberalization, moreover, allows firms to access mature capital markets. Firms listing on foreign stock markets are also in the jurisdiction of a superior legal system and have higher disclosure standards.

Third, the integration with world markets and institutions tends to speed up the reform process to achieve a resilient financial system. Capital markets can help supervise domestic financial institutions, imposing stricter market discipline, increasing transparency and the diffusion of information, and even pushing governments into guaranteeing that its financial system is well supervised and regulated.30

To have a sense of the effects of changes in institutions on financial booms and busts, we estimate the following regression,

amplitude i = α ′ X i + ρ 1 d i r + β 1 d i s r + λ 1 d i l r + τ 1 d i L & O + τ 2 d i I T A + τ 2 d i I T E + ε i . ( 4 )

This regression is the same as regression (1) but also evaluates the possible effects of changes in government institutions. diL&O is a dummy variable equal to one if the boom (crash) occurs when the law and order index has improved or it is at its highest level, and zero otherwise. diITA is a dummy variable equal to one if the boom (crash) occurs following the approval of the law prosecuting insider trading, and zero otherwise. diITE is a dummy variable equal to one if the boom (crash) occurs when insider trading prosecution is enforced and zero otherwise.

The results are also reported in Table 7. Note that improvements in the law and order index trigger more stable financial markets, with the amplitude of booms and crashes declining about 18 and 9 percentage points, respectively. This evidence provides one possible explanation of why mature markets, with better government institutions, do not experience the larger crashes observed in emerging markets in the aftermath of liberalization31

VI. Conclusions

This paper presented a new approach to understand the effects of financial liberalization by introducing a novel database on liberalization and by focusing on booms and busts in stock market prices. Our main results can be summarized as follows.

First, our chronology of financial liberalization indicates that domestic and international financial liberalization is a process in which different types of restrictions are removed over time. Moreover, while liberalization has been an uninterrupted process in most mature markets, it has been characterized by reversals in emerging markets, in which capital controls and restrictions are at times reintroduced. We also found that the pattern of liberalization varies across regions, with developed countries liberalizing their stock markets first and developing economies opening their domestic financial sector first.

Second, with regard to the possible changing nature of financial cycles, our analysis shows that stock market booms and busts have not intensified in the long run after financial liberalization. In fact, despite the claim that financial integration leads to volatile capital markets around the world, stock market cycles become less pronounced after liberalization. Still, in the short run, we found that financial liberalization does tend to trigger larger cycles. Interestingly, the short-run effects of liberalization vary across mature and emerging markets. The evidence from emerging markets, with larger booms and crashes in the immediate aftermath of liberalization, provides some support to the findings of the crisis literature of excessive financial cycles following liberalization. In contrast, the evidence from mature markets, with larger bull markets but less pronounced bear markets in the aftermath of deregulation, supports the view that liberalization is beneficial even in the short run.

Third, to explain the contrasting short- and long-run effects of financial liberalization, we explored the dynamics of liberalization and institutional reform. We collected information on the quality of institutions as well as data on the laws governing the functioning of the financial system. The evidence suggests that institutional reforms do not predate liberalization. Most of the time, government reforms are implemented within a few years after the partial opening of financial markets. As the quality of institutions improves, financial cycles become less pronounced. Perhaps due to lack of correct incentives, countries do not tend to improve their financial systems before liberalization, disregarding the typical policy prescriptions.

To conclude, this paper opened several avenues for future research. First, the new dataset will allow researchers to understand better the links between financial liberalization and financial development, investment, and growth. Second, the richness of the data will allow researchers to better comprehend the channels through which financial deregulation impacts economies. Third, more research on whether financial liberalization can be a first step toward achieving institutional reforms would be welcome. Last but not least, the relation between financial liberalization and reforms leaves unanswered the question of whether countries can deregulate financial systems without becoming vulnerable to crises.

APPENDIX I

Table A1.

Criteria to Define Liberalization Periods

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This table describes the criteria used to determine whether the capital account, the domestic financial sector, and the stock market are fully or partially liberalized.
Table A2.

Chronology of Financial Liberalization

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Table A3.

References Used to Construct the Chronology of Financial Liberalization

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Table A4.

Stock Market Indexes and Their Sources

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The table shows which stock market index is used for each country, its beginning and ending date, its base period, and its data source.
Table A5.

Institutional Reforms

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Column (1) reports the dates in which there is a “permanent” improvement in the International Country Risk Guide’s index of law and order. In this index, law and order are assessed separately, with each sub-component comprising zero to three points. The law sub-component is an assessment of the strength and impartiality of the legal system, while the order sub-component is an assessment of popular observance of the law. The improvement periods in mis index are characterized by at least one point increase in the index from its two-year period average, and the maintainance of the index above this average for at least another two years. This column also shows those countries for which the index of law and order was at its highest level during all the sample. “No change” corresponds to no permanent changes in the index. Columns (2) and (3) come from Bhattacharya and Daouk (2000). The columns report, respectively, the dates when insider trading laws are aproved and when the first prosecution under these laws occurs. The authors surveyed stock market participants and national regulators to obtain the answers, “n/a” means not available. “No” means that there is no enforcement of insider trading laws.

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1

Graciela Kaminsky is Professor of Economics and International Affairs at George Washington University, and Sergio Schmukler is a Senior Economist at the World Bank. Part of the paper was done while she was a visiting scholar at the Research department of the International Monetary Fund. We have received insightful comments from Tom Glaessner, Raghu Rajan, and Linda Tesar, as well as participants at presentations held at the American Economics Association 2002 Annual Meeting, the Federal Reserve Bank of New York, the Deutsche Bundesbank, the conference Financial Globalization: A Blessing or a Curse? (World Bank), and the Society for Economic Dynamics 2002 Meeting (New York University). We are grateful to Tatiana Didier, Federico Guerrero, Cicilia Harun, José Pineda, Arun Sharma, Akiko Terada, Francisco Vazquez, Chris van Klaveren, and Kevin Wang, who helped us by providing excellent research assistance at different stages of the project. This paper has been previously circulated under the title “On Booms and Crashes: Financial Liberalization and Stock Market Cycles.” The Research Committee and the Latin American Regional Studies Program of the World Bank kindly provided financial support.

2

These overreactions in capital markets are often explained by information asymmetries. With imperfect and costly information, investors may act as a herd and overreact to shocks, withdrawing from countries at the smallest signs of problems, even when fundamentals do not warrant it. See, for example, Calvo and Mendoza (2000).

3

See, for example, Eichengreen and Wyplosz (1993) and Rodrik (1998).

4

The evidence on the benefits of financial deregulation seems to be quite strong with, for example, output growth rates estimated to have increased about one percentage point following liberalization (as shown in Bekaert, Harvey, and Lundblad 2001).

6

See, for example, Corsetti, Roubini, and Pesenti (1998), Kaminsky and Reinhart (1999), and McKinnon and Pill (1997).

7

See, for example, Henry (2000).

8

Some empirical evidence in the last two decades has undermined the belief in efficient markets. Now many economists believe that imperfections in asset markets trigger bubbles and protracted and predictable bull and bear markets. See for example, De Long, Shleifer, Summers, and Waldmann (1990), Allen and Gorton (1993), and Allen, Morris, and Postlewaite (1993).

9

See Quinn and Inclan (1997) for an alternative measure.

10

The new indicators evaluate restrictions on 11 types of capital account transactions: (1) capital market securities, (2) money market instruments, (3) collective investment securities, (4) derivatives and other instruments, (5) commercial credits, (6) financial credits, (7) guarantees, sureties, and financial backup facilities, (8) direct investment, (9) liquidation of direct investment, (10) real estate transactions, and (11) personal capital movements.

11

There is a very large related literature that studies the extent of financial and economic integration from observable economic variables, not from government regulations.

12

For example, Chile introduced restrictions on capital inflows at the beginning of the 1990s. Controls were reinforced in the mid-1990s in the midst of the capital inflow episode. In 1998, under the threat of a contagious speculative attack against the Chilean peso, controls were eliminated. Similarly, domestic financial deregulation may take several years to be complete. For example, the deregulation of the domestic banking sector in Colombia was initiated in August 1974. Only in the 1980s were credit controls finally eliminated.

13

For example, Argentina implemented a broad liberalization of financial markets in 1977, which was later reversed in 1982. Again, in the late 1980s, a new wave of financial liberalization affected the domestic financial sector, the capital account, and the stock market. This time around the liberalization attempt was longer lasting. Still, again in 2001, in the midst of Argentina’s crisis, the government reintroduced controls on interest rates and restrictions on capital account transactions.

14

This problem may be particularly important because the complete deregulation of financial systems is not accomplished in just one round, and the time span between the deregulation of one market and the elimination of controls across the board takes, in most cases, several years. For example, the data show that, in the 1970s, domestic financial repression is widespread not only in emerging markets, but also in several mature financial markets. Governments start lifting the various restrictions gradually. In many cases, the liberalization reform starts in the banking sector with the deregulation of domestic interest rates. The elimination of interest rate controls not only affects the market for bank loans and deposits, but also attracts international capital flows (when these flows are not strictly prohibited). Also, the stock market flourishes as the extent of credit rationing diminished.

15

As used in this paper, the term “country” does not in all cases refer to a territorial entity that is a state as understood by international law and practice.

16

The sources of information include the IMF publications Annual Report on Exchange Arrangements and Exchange Restrictions and Country Reports, the IFC publication Emerging Markets Database, and the Organization for Economic Cooperation and Development (OECD) publication Economic Surveys. We also use various reports by the Economist’s Intelligence Unit, the World Bank, annual reports of central banks, as well as research papers with chronologies on financial market restrictions.

17

For a review see, for example, Karolyi and Stulz (2002).

20

Other researchers of the business cycle have used linear filters to distinguish between the trend and cyclical components of time series. However, there has not been any agreement on whether variables are trend stationary or difference stationary or what is the best filter to isolate the fluctuations at different frequencies. As examined in Stock and Watson (1998), these considerations have led econometricians to find methods that better isolate the cyclical component of economic time series with some researches proposing using the Hodrik-Prescott (1997) filter and others arguing in favor of the Baxter and King’s (1999) band-pass filter.

21

The algorithm dates contractions and expansions using each country’s stock price series, rather than the de-trended series. Therefore, busts correspond to sequences of absolute declines in stock prices rather than periods of slow growth relative to the trend.

22

As it is common in the international finance and finance literature, we look at stock returns from the point of view of investors with portfolios comprising assets in various countries. This is why, we study returns in one international currency. Alternatively, we could have focused on prices in domestic currency deflated by the domestic price index. Our results do not change substantially when using prices in domestic currency from those discussed in the text.

23

Since the choice of the short-run window is ad-hoc, we also examined the robustness of the results to different definitions of window size. The results for three-and six-year windows are quite similar.

24

For example, Calvo, Leiderman, and Reinhart (1993) argue that decreases in U.S. interest rates trigger large capital flows to emerging markets, which in turn fuel increases in asset prices.

25

As always averages may hide exceptions, Denmark, Finland, Norway, and Sweden suffer financial collapses and banking crises in the early 1990s following liberalization.

26

Note that the sequencing mentioned here discusses the optimal order between financial liberalization and other financial sector reforms. While the sequencing mentioned in the previous section deals with the order of liberalization of the stock market, the domestic financial sector, and the capital account.

27

This is shown, for example, in Rojas-Suarez and Weisbrod (1994).

29

This index is published in the International Country Risk Guide (ICRG). The law sub-index assesses the strength and impartiality of the legal system, while the order sub-index assesses the popular observance of the law. Each index can take values from one to three, with lower scores for less tradition for law and order.

30

See Gourinchas and Jeanne (2002) for a model on the link between financial liberalization and social infrastructure.

31

For more discussion on this issue, see Martin and Rey (2002).

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Cover IMF Working Papers
Short-Run Pain, Long-Run Gain: The Effects of Financial Liberalization
Author:
Mr. Sergio L. Schmukler
and
Graciela Laura Kaminsky
Volume/Issue:
Volume 2003: Issue 034
Publisher:
International Monetary Fund
ISBN:
9781451845280
ISSN:
1018-5941
Pages:
60
DOI:
https://doi.org/10.5089/9781451845280.001
Figure 1.

Index of Financial Liberalization
Figure 2.

Indexes of Financial Liberalization by Sector
Figure 3.

The Sequencing of Financial Liberalization
Figure 4.

Stock Markets Indexes
Figure 5.

Frequency Distribution of the Amplitude and Duration of Stock Market Booms and Crashes
Figure 6.

Characteristics of Regional Cycles
Figure 7.

Average Amplitude of Booms and Crashes

(in percent)