What is happening to the impact of financial deepening on economic growth?I. INTRODUCTION
Among the strongest elements of the modern economists' canon is that financial sector development has a significant impact on economic growth. A generation ago, economists like Goldsmith (1969) (1) and McKinnon (1973) began to draw attention to the benefits of financial structure development and financial liberalization lib·er·al·ize
v. lib·er·al·ized, lib·er·al·iz·ing, lib·er·al·iz·es
To make liberal or more liberal: "Our standards of private conduct have been greatly liberalized . . . . By the early 1990s, McKinnon (1991, 12) could write with confidence that:
"Now, however, there is widespread agreement that flows of saving and investment should be voluntary and significantly decentralized de·cen·tral·ize
v. de·cen·tral·ized, de·cen·tral·iz·ing, de·cen·tral·iz·es
1. To distribute the administrative functions or powers of (a central authority) among several local authorities. in an open capital market at close to equilibrium interest rates."
Since the 1990s, a burgeoning empirical literature has illustrated the importance of financial sector development for economic growth. Despite the growing consensus, however, we find that the link between finance and growth in cross-country panel data has weakened considerably over time. At the very time that financial sector liberalization spread around the world, the influence of financial sector development on economic growth has diminished di·min·ish
v. di·min·ished, di·min·ish·ing, di·min·ish·es
a. To make smaller or less or to cause to appear so.
The seminal seminal /sem·i·nal/ (sem´i-n'l) pertaining to semen or to a seed.
Of, relating to, containing, or conveying semen or seed. empirical work that established the growth-finance link is King and Levine (1993), which extended the cross-country framework introduced in Barro (1991) by adding financial variables such as the ratios of liquid liabilities or claims on the private sector to gross domestic product (GDP GDP (guanosine diphosphate): see guanine. ) to the standard growth regression. They found a robust, positive, and statistically significant relationship between initial financial conditions and subsequent growth in real per capita [Latin, By the heads or polls.] A term used in the Descent and Distribution of the estate of one who dies without a will. It means to share and share alike according to the number of individuals. incomes for a cross-section of about 80 countries. In the subsequent decade numerous empirical studies Empirical studies in social sciences are when the research ends are based on evidence and not just theory. This is done to comply with the scientific method that asserts the objective discovery of knowledge based on verifiable facts of evidence. expanded upon this, using both cross-country and panel data sets for the post-1960 period. (2)
In this paper we reexamine re·ex·am·ine also re-ex·am·ine
tr.v. re·ex·am·ined, re·ex·am·in·ing, re·ex·am·ines
1. To examine again or anew; review.
2. Law To question (a witness) again after cross-examination. the core cross-country panel result and find that the impact of financial deepening Financial deepening is a term used often by economic development experts. It refers to the increased provision of financial services with a wider choice of services geared to all levels of society. on growth is not as strong with more recent data as it appeared in the original panel studies with data for the period from 1960 to 1989. We consider various explanations for this clear shift. First, we suggest that financial deepening has a positive effect on growth if not done to excess. Rapid and excessive deepening deep·en
tr. & intr.v. deep·ened, deep·en·ing, deep·ens
To make or become deep or deeper.
Noun 1. deepening - a process of becoming deeper and more profound , as manifested in a credit boom, can be problematic even in the most developed markets because it can both weaken the banking system and bring inflationary pressures. We test this hypothesis by looking at the finance-growth nexus among countries that have or have not experienced financial sector crises. We find that once crisis episodes are removed, the finance-growth relationship remains intact. Its weakening over time thus seems to be a result of an increased incidence of crises in later years.
Our second and related hypothesis is that the widespread liberalization of financial markets that occurred in the late 1980s and early 1990s made financial deepening less effective. This is reminiscent of Robert Lucas's (1975) critique of econometric e·con·o·met·rics
n. (used with a sing. verb)
Application of mathematical and statistical techniques to economics in the study of problems, the analysis of data, and the development and testing of theories and models. policy evaluation advanced three decades ago. Policies that have promoted and/or forced increases in financial depth over the past two decades may have altered the basic structural relationship between finance and growth. This could occur if the observed benefits of financial deepening led many countries to liberalize lib·er·al·ize
v. lib·er·al·ized, lib·er·al·iz·ing, lib·er·al·iz·es
To make liberal or more liberal: "Our standards of private conduct have been greatly liberalized . . . before the associated legal and regulatory institutions were sufficiently well developed. As a consequence, the impact of financial deepening on growth would become smaller. Our evidence does not indicate that recent liberalizations are responsible for the breakdown of the finance-growth link. However, there may be an indirect link as premature financial development can lead to financial crises that have real effects.
Third, we examine the role of global equity markets that have grown in importance and prominence prominence /prom·i·nence/ (prom´i-nins) a protrusion or projection.
frontonasal prominence in the years over which the finance-growth relationship disappeared. However, we do not find any evidence to suggest that equity market growth has substituted for the role of credit markets and banks in particular.
We also examine some sample composition effects. For example, we distinguish between developed and developing countries. Although the finance-growth relationship is somewhat stronger among developed countries, the decline in the impact of finance on growth in recent years is found in both groups.
Further, we look at several estimation estimation
In mathematics, use of a function or formula to derive a solution or make a prediction. Unlike approximation, it has precise connotations. In statistics, for example, it connotes the careful selection and testing of a function called an estimator. techniques in order to be confident of the robustness of our major finding, the virtual disappearance of the finance-growth relationship in recent data. The finance-growth literature uses various estimation approaches because of the difficulty in adequately controlling for endogeneity. We examine pure cross-section estimates, panels of 5-year average growth rates Growth Rates
The compounded annualized rate of growth of a company's revenues, earnings, dividends, or other figures.
Remember, historically high growth rates don't always mean a high rate of growth looking into the future. , and dynamic panels in order to show that our basic result is robust to the choice of estimation technique.
Although the finance-growth nexus has become firmly entrenched en·trench also in·trench
v. en·trenched, en·trench·ing, en·trench·es
1. To provide with a trench, especially for the purpose of fortifying or defending.
2. , this is not the first study to question its importance. Economists as disparate as Joan Robinson Joan Violet Robinson (October 31, 1903 in Surrey - August 5, 1983 in Cambridge) was a Marxist Keynesian economist who was well known for her knowledge of monetary economics and wide-ranging contributions to economic theory. and Robert Lucas
For the English cricketer, see .
Robert Lucas (April 1, 1781–February 7, 1853) was the 12th governor of the U.S. state of Ohio, serving from 1832 to 1836. have expressed doubts about the link. (3) In addition, some authors have been less than enthusiastic about the strength of the recently established empirical consensus and there are indications that the relationship varies and lacks robustness. (4)
A few earlier papers, including those by Demetriades and Hussein (1996), Rousseau and Wachtel (1998), and Arestis, Demetriades, and Luintel (2001), have noted that the relationship between financial deepening and growth varies considerably across countries. Rousseau and Wachtel (2002) show that the relationship varies with the inflation rate; financial deepening does not affect growth when annual inflation is above a threshold of about 13%. Rioja and Valev (2004) also show that the relationship varies with the level of economic development. Specifically, deepening has a larger impact on growth with a moderate level of financial sector development. However, none of the earlier studies has provided an explanation for the weakening of the relationship over time.
A recent paper by Loayza and Ranciere (2006) addresses the dual role of financial deepening discussed above. They distinguish between the short-run impact of credit expansions on growth and the long-run positive impact of financial deepening on growth. The short-run effect is sometimes negative, particularly during episodes of financial crisis. Our approach to this dual role of finance is somewhat different. First, we investigate how banking crises and liberalizations affect the impact of financial deepening on growth. Second, we relate these phenomena to the secular decline in the impact of financial deepening observed in the classical cross-country panel regression framework.
The next section describes the data and the by-now-standard approach to panel estimates of growth equations. In Section III we present baseline estimates and show that the finance-growth nexus has weakened over time. In Section IV we examine the hypotheses suggested above regarding the possible causes of decline in the effect of financial deepening on growth. Section V presents some additional evidence on the relationship between the strength of the finance-growth link and the levels of economic development and financial depth in a country. Our conclusions are in Section VI.
II. DATA AND METHODOLOGY
Our study includes cross-sectional and panel data on financial and macroeconomic mac·ro·ec·o·nom·ics
n. (used with a sing. verb)
The study of the overall aspects and workings of a national economy, such as income, output, and the interrelationship among diverse economic sectors. indicators for 84 countries over the period from 1960 to 2004. (5) Data are from the 2007 edition of the World Bank's Worm Development Indicators database. The selection of countries is based on data availability Refers to the degree to which data can be instantly accessed. The term is mostly associated with service levels that are set up either by the internal IT organization or that may be guaranteed by a third party datacenter or storage provider. from this source. To ensure comparability with King and Levine's original study and others, we use three familiar measures of financial development, namely, the ratios to GDP of liquid liabilities (M3), liquid liabilities less narrow money (M3 less M1), and credit allocated to the private sector. M3 as a percentage of GDP has become a standard measure of financial depth and an indicator of the overall size of financial intermediary Financial Intermediary
An institution that acts as the middleman between investors and firms raising funds. Often referred to as financial institutions.
This can include chartered banks, insurance companies, investment dealers, mutual funds, and pension funds. activity in cross-country studies. M3 less M1 removes the pure transactions asset and the credit measure isolates intermediation to the private sector from the credit allocated to government or state enterprises.
King and Levine's version of the Barro growth regression, and the starting point Noun 1. starting point - earliest limiting point
terminus a quo
commencement, get-go, offset, outset, showtime, starting time, beginning, start, kickoff, first - the time at which something is supposed to begin; "they got an early start"; "she knew from the for our analysis, has the form
(1) [Y.sub.it] = [[alpha].sub.0] + [alpha][F.sub.it] + [beta][X.sub.it] + [u.sub.it],
where [Y.sub.it] is the growth rate of real per capita GDP, [F.sub.it] is a measure of financial sector development, and [X.sub.it] is a set of baseline explanatory ex·plan·a·to·ry
Serving or intended to explain: an explanatory paragraph.
ex·plan variables that have been shown empirically to be robust determinants of growth. The X variables include the log of initial real per capita GDP, which should capture the tendency for growth rates to converge con·verge
v. con·verged, con·verg·ing, con·verg·es
a. To tend toward or approach an intersecting point: lines that converge.
b. across countries and over time, and the log of the initial secondary school enrollment rate, which should reflect the extent of investment in human capital. We include the ratio of trade (i.e., imports plus exports) to GDP and the ratio of government final consumption to GDP as additional explanatory variables.
Following King and Levine, we start with cross-sectional estimates where the dependent variable is the average annual growth rate over our entire data period (i.e., 1960-2004). To reduce any simultaneity bias that might result from the influence of economic growth on the development of the financial sector, we use initial values from the start of the cross-section for all explanatory variables in the regression. Following the subsequent literature, we also exploit the time series variation in the data by estimating Equation (1) with a panel of 5-year averages.
In these regressions we use instrumental variables to reduce any simultaneity bias. Specifically, we attempt to extract the predetermined pre·de·ter·mine
v. pre·de·ter·mined, pre·de·ter·min·ing, pre·de·ter·mines
1. To determine, decide, or establish in advance: component of the financial variable by using its initial value (in each 5-year period) along with the initial values of government expenditure and trade as percentages of GDP as instruments in each regression equation Regression equation
An equation that describes the average relationship between a dependent variable and a set of explanatory variables. . All panel estimates include time period fixed effects. Finally, we will also present estimates with the system GMM GMM Generalized Method of Moments (economics)
GMM Gaussian Mixture Model
GMM General Membership Meeting
GMM Good Mobile Messaging
GMM GPRS Mobility Management
GMM Global Marijuana March
GMM Genetically Modified Microorganisms dynamic panel estimation techniques that have become common in the literature. (6) Our fundamental result that the finance-growth relationship weakened dramatically is robust to the choice of estimation approach.
III. THE DECLINE IN THE FINANCE-GROWTH RELATIONSHIP
Table 1 contains results from the baseline cross-section growth equations for each of the three measures of financial depth for the full data period, 1960-2004, and two subperiods. The first subperiod, 1960-1989, coincides with the time period analyzed an·a·lyze
tr.v. an·a·lyzed, an·a·lyz·ing, an·a·lyz·es
1. To examine methodically by separating into parts and studying their interrelations.
2. Chemistry To make a chemical analysis of.
3. by King and Levine and others that established the consensus results that have become so important. The results for 1960-1989 and for the full period are largely consistent with this consensus. (7) For the 1960-1989 subperiod, the coefficients on the financial variables are all positive and significant at the 5% level; the same is true for the full period except for the ratio of private credit to GDP. The contrast with the second subperiod is dramatic; none of the finance variables is significant in the cross section for 1990-2004. The coefficients on the log of initial real GDP is negative and statistically significant for the 1960-1989 and 1960-2004 periods, which is consistent with the notion of beta convergence, but they are not significant for 1990-2004. The positive and significant coefficients on the log of the initial secondary school enrollment rate in all specifications suggest that human capital investment matters for growth. The other control variables--government expenditure and trade as percentages of GDP--are not always significant in these cross-section results but robustness tests (not shown) indicate that their presence or absence does not have much effect on the finance coefficients.
The dramatic difference between the initial and recent time periods found in the cross-section estimates of Table 1 is repeated when we look at panels with 5-year averages estimated with both standard two-stage least squares and with dynamic system GMM. Tables 2 and 3 present these same equations estimated with the alternative techniques. With all three estimation approaches, the effect of financial depth on growth, which is always significant in the first 30-year period, disappears in the next 15. Whereas all of the finance coefficients are significant at the 5% level in the early time period, none are significant in the more recent data and the coefficients fall to near zero.
To examine further the differences over time in the effect of financial depth on growth, we estimated the baseline equation separately with the cross section of data from each 5-year period. That is, from 1960 to 2004 there are nine cross sections. Instrumental variable regressions with each of the three measures of financial depth are summarized in Table 4, which shows only the finance coefficients from each cross-section regression. (8)
The coefficient coefficient /co·ef·fi·cient/ (ko?ah-fish´int)
1. an expression of the change or effect produced by variation in certain factors, or of the ratio between two different quantities.
2. on M3 as a percent of GDP is positive and statistically significant for five successive time periods running from 1965 to 1989 but insignificant in the earlier and subsequent periods. The same is true for the coefficients on M3 less M1 with the exception of one time period in the 1980s when the coefficient is not quite significant. In contrast, the coefficient on the private credit ratio is only significantly different from zero in two time periods. But the coefficient on private sector credit is clearly positive (averaging .025) from the late 1960s until 1989 and then falls to zero or below. The coefficient on the M3 ratio falls to zero from 1990 on, as does the coefficient on M3 less M1. Chow tests for the regressions in each table reject the hypothesis of coefficient stability across the nine time periods at the 1% level.
These tables provide a clear story. The effect of finance on growth is a disappearing phenomenon. In the next section we examine several hypotheses that might explain the result.
IV. UNDERSTANDING THE CHANGES IN THE FINANCE-GROWTH RELATIONSHIP
In this section we relate changes in the finance-growth relationship to the hypotheses stated in the Introduction (Section I). We start by relating the finance effect to the incidence of financial crises. The disappearance of the finance effect on growth over time may be related to the incidence of financial crises since such episodes are often associated with too-rapid a financial deepening. There is a thin line between financial deepening that comes from the expansion of financial intermediary activity and financial deepening that is the consequence of a credit boom. In the first instance increased intermediation is likely to be growth enhancing, while in the second instance credit standards Credit Standards
The guidelines a company follows to determine whether a credit applicant is creditworthy. deteriorate de·te·ri·o·rate
1. To grow worse in function or condition.
2. To weaken or disintegrate. , nonperforming loans proliferate pro·lif·er·ate
To grow or multiply by rapidly producing new tissue, parts, cells, or offspring. and a banking crisis ensues. The effect of financial deepening on growth disappears in a financial crisis and the incidence of financial crises increased in the late 1980s. Thus, the reduced effect of finance on growth may be due to the increased incidence of financial crises.
We investigate this hypothesis by isolating episodes of financial crisis and examining the impact of financial deepening on growth in non-crisis episodes. We use the identification and dating prepared by Caprio and Klingebiel (2003) for systemic systemic /sys·tem·ic/ (sis-tem´ik) pertaining to or affecting the body as a whole.
1. Of or relating to a system.
2. banking and financial crises around the world. Of the 84 countries in our sample, 45 have experienced at least one major crisis. We characterize a 5-year country observation as a crisis period if the country was in crisis at any time during the period. Table 5 shows the number of countries in crisis at any time during each 5-year period.
Instrumental variable estimates of the baseline growth equations that allow the finance coefficient to vary when there is either a major or minor financial crisis are shown in Table 6. Each equation shows the finance variable for all observations and then the finance variable interacted with dummies for crisis episodes. The size of the coefficient on the finance variable indicates the impact of finance on growth in non-crisis observations. These effects are all positive, statistically significant, and larger than the corresponding coefficients in Table 2, which do not account for crisis episodes. The interaction with the major crisis dummy Sham; make-believe; pretended; imitation. Person who serves in place of another, or who serves until the proper person is named or available to take his place (e.g., dummy corporate directors; dummy owners of real estate). indicates the difference in the finance effect when a country is in crisis. In every case, the finance effect is significantly smaller at the 5% level when there is a financial crisis. In fact, the impact of financial deepening in these crisis periods is often near zero. The minor crisis episodes also have a negative impact on the finance coefficients but the changes are small and not statistically significant.
Since excessive credit creation can lead to instability and crisis, and financial liberalization is usually associated with the rapid development of financial institutions, capital flows, and increases in liquid liabilities, the disappearance of the finance effect on growth over time could also be related to the rapid liberalization of financial markets in many countries in the latter period. In particular, policy makers have busily touted the benefits of liberalization of financial markets and the growth of financial institutions throughout the 1980s and 1990s. However, the increases in financial depth in many countries took place without the requisite development of lending expertise, mechanisms for monitoring, and supervisory and regulatory skills. So the relationships observed in the early data may have disappeared as efforts to liberalize financial markets became widespread.
In order to explore the impact of liberalizations we use the dating of equity market liberalizations in Bekaert, Harvey, and Lundblad (2005). They use a variety of sources to date an important element of financial-sector liberalization-the liberalization of access by foreigners to the domestic equity market. This classification scheme can be applied to virtually all of the countries in our sample, and it turns out that a large number of countries experienced liberalization, although most of it occurred within a rather short period of time in the late 1980s and the early 1990s. Thus, we can associate our 5-year average growth observations with the liberalization status of the country. We separate our observations into four groups indicating whether a country was always liberalized, never liberalized, the preliberalization periods of countries that liberalized, and the corresponding postliberalization observations.
Instrumental variable estimates of the base line growth equations that allow the finance coefficient to vary with the country's liberalization status are shown in Table 7. Each equation shows the finance variable for all observations and then the finance variable interacted with dummies for three of the liberalization groups (the always liberalized group is omitted). Thus, the coefficients on the interaction variables are differences in the finance effect from the effect for always liberalized countries. The signs of the interaction coefficients offer some indication that the finance effect is larger in neverliberalized countries and smaller in countries prior to liberalization, but they are never significantly different from zero. Of course, it might be difficult to identify the effect of liberalizations on the finance-growth relationship because the liberalization itself often promotes growth. Indeed, Bekaert, Harvey, and Lundblad find that equity market liberalizations increase growth rates by a full percentage point. Further, it might be hard to distinguish a liberalization effect from the effect of time since all the postliberalization observations occur later in our sample and time period fixed effects are included in all of the equations. (9)
Next, equity markets have grown in size and importance around the world in just the years in which the effect of financial deepening on growth seems to have disappeared. It therefore is reasonable to suggest that equity market financing has acted as a substitute for credit market financing so that the impact of financial deepening has been mitigated mit·i·gate
v. mit·i·gat·ed, mit·i·gat·ing, mit·i·gates
To moderate (a quality or condition) in force or intensity; alleviate. See Synonyms at relieve.
To become milder. in recent years by the increasing role of equity markets. The positive impact of equity markets on growth has been demonstrated with panel data sets like ours by Levine and Zervos (1998) and Rousseau and Wachtel (2000). In order to investigate this hypothesis we define a broad financing measure which is the sum of M3 and the market capitalization Market Capitalization
A measure of a public company's size. Market capitalization is the total dollar value of all outstanding shares. It's calculated by multiplying the number of shares times the current market price. This term is often referred to as market cap. of the stock market as a ratio to GDP. (10) The stock market data is not widely available until the 1980s and even then is not available for every country. Nevertheless, we estimated the baseline equation for the countries that were available for each cross section after 1980 with the broad financing measure. Table 8 shows the coefficients on the broad financing measure from each cross section with its standard error in parentheses and the number of countries. The finance effect is present though not quite statistically significant in the 1980s but disappears afterward af·ter·ward also af·ter·wards
At a later time; subsequently.
Adv. 1. afterward - happening at a time subsequent to a reference time; "he apologized subsequently"; "he's going to the store but he'll be back here even when the equity and credit markets are considered together.
The conclusion to be drawn from these tests is clear. The decline in the finance coefficients over time is not an inexplicable in·ex·pli·ca·ble
Difficult or impossible to explain or account for.
in·expli·ca·bil or transitory time effect. The coefficients are smaller in recent years because of the increased incidence of financial and banking crises. Financial deepening promotes growth as long as it is not excessive. Once excessive growth of money and credit leads to a crisis in the banking system, the benefits of financial deepening disappear until the crisis is cleaned up. The change in the finance effect is not due to liberalization as measured by financial sector openness and it is not due to the increasingly important role of equity markets.
V. ADDITIONAL EVIDENCE
In this section we examine sample composition effects that might affect the relationship between finance and growth. To begin, we distinguish between developed and developing countries using the World Bank's classification and estimate the baseline growth equation for each group. Table 9 shows the panel estimates for both country groups for the initial sample period (1960-1989) and the subsequent period (1990-2004) with M3 as a percentage of GDP as the finance variable. The finance effect is significant for both in the earlier period though it is larger for the developed countries. In the later period it is much smaller for the developed countries and disappears for the less developed ones.
The effect of both time and level of development on the finance coefficient can be related to changes in the per capita income Noun 1. per capita income - the total national income divided by the number of people in the nation
income - the financial gain (earned or unearned) accruing over a given period of time of the countries in the sample. In order to examine this, we used a rolling regression technique to investigate the relationship between per capita income and the finance effect more closely. (11) In results not shown here, we find that for very low-income countries (income below US $3,000 in the year 2000), the effect of financial deepening is positive but not significant. The effect is imprecisely im·pre·cise
impre·cisely adv. estimated because in many of these countries increased financial depth might be due to directed finance and poor lending standards. However, in the middle-income range (from $3,000 to $12,000), there seems to be clear evidence of a finance-growth relationship. The relationship disappears among very high-income countries. These results indicate that the finance-growth nexus appears to be stronger in certain economic environments. Countries with moderately developed financial sectors or countries with middle levels of per capita income have a stronger and significant impact of financial deepening on economic growth.
We also use the roiling regression technique to investigate the relationship between the level of financial development and the impact of finance with IV panel regressions for the baseline equation with the M3 ratio as the finance variable. (12) Figure 1 shows the evolution of the finance coefficient for 20-country rolling windows; the solid line gives the estimated coefficients and 5% confidence intervals are given by the dotted lines. The countries are ordered by the average level of financial depth (after adjusting for global time effects) and rolled in as the ratio of M3 to GDP increases.
The initial regression includes the 20 countries with the lowest levels of financial depth and rolls in additional countries and rolls out the initial countries one by one so that each coefficient is estimated with a 20-country window. Thus, the coefficients depicted de·pict
tr.v. de·pict·ed, de·pict·ing, de·picts
1. To represent in a picture or sculpture.
2. To represent in words; describe. See Synonyms at represent. in Figure 1 reflect the effects of finance on growth among countries with relatively similar levels of financial sector development. The horizontal axis measures the average ratio of M3 to GDP among the 20 countries corresponding to each particular point estimate.
The results are striking; financial deepening matters when the M3 to GDP ratio is around the middle of the observed range (about 40%). The 20-country window that corresponds with this peak positive effect includes M3 to GDP ratios that range from 32% to nearly 60%. Among the financially less developed countries the coefficient is usually negative, is quite variable, and is imprecisely measured. Among the financially most developed countries the coefficient is about zero but rising slowly with the level of financial depth; although finance differs considerably among these countries it has little relationship to growth.
[FIGURE 1 OMITTED]
We examined the robustness of some now-classic findings on the cross-country relationship between financial development and economic growth and found that the finance-growth relationship that was estimated with data from the 1960s to the 1980s simply disappeared over the subsequent 15 years. One might conclude that the underlying relationship that is so widely used is simply unstable and that with additional data it might well reappear reappear
to come back into view
Verb 1. reappear - appear again; "The sores reappeared on her body"; "Her husband reappeared after having left her years ago" . Alternatively, we investigate some simple hypotheses that might explain the time effects.
First, we test whether the incidence of domestic banking and financial crises affects the impact of deepening. Here the evidence is very strong. Financial deepening has a strong impact on growth throughout the sample period as long as a country can avoid a financial crisis. In crisis episodes, which are more often than not due to excessive deepening, the benefits of financial deepening, not surprisingly, disappear.
Second, we test to see whether an affect analogous analogous /anal·o·gous/ (ah-nal´ah-gus) resembling or similar in some respects, as in function or appearance, but not in origin or development.
adj. to the Lucas critique The Lucas Critique, named for Robert Lucas's work on macroeconomic policymaking, says that it's naive to try to predict the effect of a policy experiment based purely on correlations in historical data, especially high-level aggregated historical data. is at work. In the context of our problem, it would imply that financial deepening causes growth as long as the relationship is not exploited. We use international equity market opening as an indicator of liberalization and the effort to develop financial markets. We find that the effect of financial deepening does not weaken when liberalizations occur.
Third, we test to see whether the disappearance of the finance effect is due to the omission omission n. 1) failure to perform an act agreed to, where there is a duty to an individual or the public to act (including omitting to take care) or is required by law. Such an omission may give rise to a lawsuit in the same way as a negligent or improper act. of the role of equity markets on growth. This is of particular concern because of the increasing role of equity markets in many countries in the recent years. We do not find any indication that our result is due to the absence of equity markets in the baseline model. Although market capitalization is not available for all of the countries in our sample, when it is included the effect of finance, broadly defined, still declines after the 1980s.
All of this does not detract from detract from
verb 1. lessen, reduce, diminish, lower, take away from, derogate, devaluate << OPPOSITE enhance
verb 2. the basic point that at one time countries with higher levels of financial development tended to have higher growth rates than those with lower levels of financial development. The question of how these countries acquired large financial sectors and how they may have served as engines of growth, however, remains imperfectly im·per·fect
1. Not perfect.
2. Grammar Of or being the tense of a verb that shows, usually in the past, an action or a condition as incomplete, continuous, or coincident with another action.
3. understood. Did finance emerge due to the presence of deeper institutional fundamentals that had a direct impact on growth as Acemoglu, Johnson, and Robinson (2001) suggest? Or is Joan Robinson correct that growth is the prime mover prime mover: see energy, sources of.
The component of a power plant that transforms energy from the thermal or the pressure form to the mechanical form. behind financial development? Our study, while by no means arguing that financial factors are no longer important for economic development, serves simply as a reminder that the link between finance and growth is more complex than the simple relationships suggest. It would appear that deepening needs to be accompanied by appropriate policies for financial sector reform and regulation. Thus, the systematic study of the financial development experiences of individual countries becomes all the more critical as the next step in furthering our understanding of the nexus.
Acemoglu, D., S. Johnson, and J. A. Robinson. "The Colonial Origins of Economic Development: An Empirical Investigation." American Economic Review, 91, 2001, 1369-1401.
Arestis, P., P. O. Demetriades, and K. B. Luintel. "Financial Development and Economic Growth: The Role of Stock Markets." Journal of Money, Credit, and Banking, 33, 2001, 16-41.
Barro, R. J. "Economic Growth in a Cross Section of Countries." Quarterly Journal of Economics The Quarterly Journal of Economics, or QJE, is an economics journal published by the Massachusetts Institute of Technology and edited at Harvard University's Department of Economics. Its current editors are Robert J. Barro, Edward L. Glaeser and Lawrence F. Katz. , 106, 1991, 407-43.
Bekaert, G., C. R. Harvey, and C. Lundblad. "Does Financial Liberalization Spur Growth?" Journal of Financial Economics, 77, 2005, 3-55.
Caprio, G., and D. Klingebiel. "Episodes of Systemic and Borderline borderline /bor·der·line/ (-lin) of a phenomenon, straddling the dividing line between two categories.
borderline Financial Crises." Mimeo, World Bank, 2003.
Demetriades, P. O., and K. A. Hussein. "Does Financial Development Cause Economic Growth? Time Series Evidence from Sixteen Countries." Journal of Development Economics, 51, 1996, 387-411.
Goldsmith, R.W. Financial Structure and Development New Haven New Haven, city (1990 pop. 130,474), New Haven co., S Conn., a port of entry where the Quinnipiac and other small rivers enter Long Island Sound; inc. 1784. Firearms and ammunition, clocks and watches, tools, rubber and paper products, and textiles are among the many , CT: Yale University Yale University, at New Haven, Conn.; coeducational. Chartered as a collegiate school for men in 1701 largely as a result of the efforts of James Pierpont, it opened at Killingworth (now Clinton) in 1702, moved (1707) to Saybrook (now Old Saybrook), and in 1716 was Press, 1969.
King, R. G., and R. Levine, "Finance and Growth: Schumpeter Might Be Right." Quarterly Journal of Economics, 108, 1993, 717-37.
Levine, R. "Financial Development and Economic Growth: Views and Agenda." Journal of Economic Literature, 35, 1997, 688-726.
Levine, R. "Finance and Growth: Theory and Evidence," in Handbook of Economic Growth, Vol. 1A, edited by P. Aghion and S. N. Durlauf. Amsterdam: North-Holland, 2005, 865-934.
Levine, R., N. Loayza, and T. Beck. "Financial Intermediation and Growth: Causality causality, in philosophy, the relationship between cause and effect. A distinction is often made between a cause that produces something new (e.g., a moth from a caterpillar) and one that produces a change in an existing substance (e.g. and Causes." Journal of Monetary Economics, 46, 2000, 31-77.
Levine, R., and S. Zervos. "Stock Markets, Banks, and Economic Growth." American Economic Review, 88, 1998, 537-58.
Loayza, N. V., and R. Ranciere. "Financial Development, Financial Fragility, and Growth." Journal of Money, Credit, and Banking, 38, 2006, 1051-76.
Lucas, R. E., Jr. "Econometric Policy Evaluation: A Critique." Carnegie-Rochester Series on Public Policy, 1, 1975, 19-46.
Lucas, R. E., Jr. "On the Mechanics of Economic Development." Journal of Monetary Economics, 22, 1988, 3-42.
Manning, M. J. "Finance Causes Growth: Can We Be So Sure?" Contributions to Macroeconomics macroeconomics
Study of the entire economy in terms of the total amount of goods and services produced, total income earned, level of employment of productive resources, and general behaviour of prices. , 3, 2003, http://www.bepress.com/bejm/contributions/vol3/iss1/ art12.
McKinnon, R. I. Money and Capital in Economic Development. Washington, DC: Brookings Institution Brookings Institution, at Washington, D.C.; chartered 1927 as a consolidation of the Institute for Government Research (est. 1916), the Institute of Economics (est. 1922), and the Robert S. Brookings Graduate School of Economics and Government (est. 1924). , 1973.
McKinnon, R. I. The Order of Economic Liberalization Economic liberalization is a broad term that usually refers to less government regulations and restrictions in the economy in exchange for greater participation of private entities; the doctrine is associated with neoliberalism. . Baltimore: Johns Hopkins University Johns Hopkins University, mainly at Baltimore, Md. Johns Hopkins in 1867 had a group of his associates incorporated as the trustees of a university and a hospital, endowing each with $3.5 million. Daniel C. Press, 1991.
Rioja, F., and N. Valev. "Does One Size Fit All? A Reexamination re·ex·am·ine also re-ex·am·ine
tr.v. re·ex·am·ined, re·ex·am·in·ing, re·ex·am·ines
1. To examine again or anew; review.
2. Law To question (a witness) again after cross-examination. of the Finance and Growth Relationship." Journal of Development Economics, 74, 2004, 429-47.
Robinson, J. "The Generalization gen·er·al·i·za·tion
1. The act or an instance of generalizing.
2. A principle, a statement, or an idea having general application. of the General Theory," in The Rate of Interest and Other Essays. London: Macmillan, 1952.
Rousseau, P. L., and P. Wachtel. "Financial Intermediation and Economic Performance: Historical Evidence from Five Industrialized in·dus·tri·al·ize
v. in·dus·tri·al·ized, in·dus·tri·al·iz·ing, in·dus·tri·al·iz·es
1. To develop industry in (a country or society, for example).
2. Economies." Journal of Money, Credit and Banking, 30, 1998, 657-78.
Rousseau, P. L., and P. Wachtel. "Equity Markets and Growth: Cross-Country Evidence on Timing and Outcomes, 1980-1995." Journal of Banking and Finance, 24, 2000, 1933-57.
Rousseau, P.L., and P. Wachtel. "Inflation Thresholds and the Finance-Growth Nexus." Journal of International Money and Finance, 21, 2002, 277-93.
Temple, J. "The New Growth Evidence." Journal of Economic Literature, 37, 1999, 112 56.
Wachtel, P. "How Much Do We Really Know about Growth and Finance?" Federal Reserve Bank of Atlanta The Federal Reserve Bank of Atlanta is responsible for the 6th District of the Federal Reserve, which covers Alabama, Florida, Georgia, and parts of Louisiana, Mississippi, and Tennessee. Economic Review, 88, 2003, 33-47.
Windmeijer, F. "A Finite finite - compact Sample Correction for the Variance of Linear Efficient Two-Step GMM Estimators." Journal of Econometrics econometrics, technique of economic analysis that expresses economic theory in terms of mathematical relationships and then tests it empirically through statistical research. , 126, 2005, 25-51.
PETER L. ROUSSEAU and PAUL WACHTEL *
* This article is an extension of a paper prepared for the UNU/WIDER conference on Financial Sector Development for Growth and Poverty Reduction, July 1-2, 2005, Helsinki, Finland. See Economic Growth and Financial Depth: Is the Relationship Extinct Already? WIDER Discussion paper DP2005/10. We are also grateful for comments and suggestions from three anonymous referees and seminar participants at the London School of Economics The School is a member of the Russell Group, the European University Association, Association of Commonwealth Universities, the Community of European Management Schools and International Companies, The Association of Professional Schools of International Affairs as well as the Golden , the Bank of Finland The Bank of Finland (Finnish: Suomen Pankki, Swedish: Finlands Bank) is the central bank of Finland. It is the fourth oldest central bank in the world. , and the European Money and Finance Forum.
Rousseau: Professor, Department of Economics, Vanderbilt University Vanderbilt University, at Nashville, Tenn.; coeducational; chartered 1872 as Central Univ. of Methodist Episcopal Church, founded and renamed 1873, opened 1875 through a gift from Cornelius Vanderbilt. Until 1914 it operated under the auspices of the Methodist Church. , Box 1819 Sta. B, Nashville, TN 37235, and Research Associate, National Bureau of Economic Research. Phone 1-615-343-2466, Fax 1-615-343-8495, E-mail peter.L.email@example.com
Wachteh: Professor, Department of Economics, Stem School of Business, New York University New York University, mainly in New York City; coeducational; chartered 1831, opened 1832 as the Univ. of the City of New York, renamed 1896. It comprises 13 schools and colleges, maintaining 4 main centers (including the Medical Center) in the city, as well as the , 44 West 4th Street, New York New York, state, United States
New York, Middle Atlantic state of the United States. It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the Canadian province of , NY 10012. Phone 1-212-998-4030, Fax 1-212-995-4218, E-mail firstname.lastname@example.org
(1.) Goldsmith, for example, found a positive relationship between economic growth and financial development using a comparative approach with data for 35 countries over the period from 1860 to 1963.
(2.) Levine (1997) surveys the literature through the mid-1990s, and Levine (2005) offers a comprehensive treatment of the many contributions that have followed. See also Temple (1999).
(3.) Lucas (1988) suggests that the role of finance is "overstressed" and Robinson (1952, p. 80) asserts that "where enterprise leads, finance follows."
(4.) The titles of some recent papers express the growing skepticism skepticism (skĕp`tĭsĭzəm) [Gr.,=to reflect], philosophic position holding that the possibility of knowledge is limited either because of the limitations of the mind or because of the inaccessibility of its object. , for example, "How much do we really know about growth and finance?" Wachtel (2003) and "Finance causes growth: Can we be so sure?" Manning (2003).
(5.) The 84 countries are Algeria, Argentina, Australia, Austria, Bangladesh, Barbados, Belgium, Bolivia, Brazil, Cameroon, Canada, Central African Republic Central African Republic, republic (2005 est. pop. 3,800,000), 240,534 sq mi (622,983 sq km), central Africa. The landlocked nation is bordered by Chad (N), Sudan (E), Congo (Kinshasa) and Congo (Brazzaville) (S), and Cameroon (W). , Chile, Colombia, Costa Rica, Cote d'Ivoire, Denmark, Dominican Republic Dominican Republic (dəmĭn`ĭkən), republic (2005 est. pop. 8,950,000), 18,700 sq mi (48,442 sq km), West Indies, on the eastern two thirds of the island of Hispaniola. The capital and largest city is Santo Domingo. , Ecuador, Egypt, E1 Salvador, Fiji, Finland, France, Gambia, Ghana, Greece, Guatemala, Guyana. Haiti, Honduras, Iceland, India, Indonesia, Iran, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kenya, Republic of Korea, Lesotho, Luxembourg, Malawi, Malaysia, Malta, Mauritius, Mexico, Morocco Morocco, country, Africa
Morocco (mərŏk`ō), officially Kingdom of Morocco, kingdom (2005 est. pop. 32,726,000), 171,834 sq mi (445,050 sq km), NW Africa. , Nepal, Netherlands, New Zealand New Zealand (zē`lənd), island country (2005 est. pop. 4,035,000), 104,454 sq mi (270,534 sq km), in the S Pacific Ocean, over 1,000 mi (1,600 km) SE of Australia. The capital is Wellington; the largest city and leading port is Auckland. , Nicaragua, Niger, Nigeria, Norway, Pakistan, Panama, Papua New Guinea Papua New Guinea (păp`ə, –y , Paraguay, Peru, Philippines, Portugal, Rwanda, Senegal, Sierra Leone Sierra Leone (sēĕr`ə lēō`nē, lēōn`; sēr`ə lēōn), officially Republic of Sierra Leone, republic (2005 est. pop. 6,018,000), 27,699 sq mi (71,740 sq km), W Africa. , South Africa South Africa, Afrikaans Suid-Afrika, officially Republic of South Africa, republic (2005 est. pop. 44,344,000), 471,442 sq mi (1,221,037 sq km), S Africa. , Spain, Sri Lanka Sri Lanka (srē läng`kə) [Sinhalese,=resplendent land], formerly Ceylon, ancient Taprobane, officially Democratic Socialist Republic of Sri Lanka, island republic (2005 est. pop. , Sudan, Sweden, Switzerland, Syrian Arab Republic, Thailand, Trinidad and Tobago Trinidad and Tobago (trĭn`ĭdăd, təbā`gō), officially Republic of Trinidad and Tobago, republic (2005 est. pop. 1,088,000), 1,980 sq mi (5,129 sq km), West Indies. The capital is Port of Spain. , Togo, Turkey, United Kingdom, United States United States, officially United States of America, republic (2005 est. pop. 295,734,000), 3,539,227 sq mi (9,166,598 sq km), North America. The United States is the world's third largest country in population and the fourth largest country in area. , Uruguay, Venezuela, and Zimbabwe.
(6.) Our use of the "System GMM" estimator parallels that introduced to the finance-growth literature by Levine, Loayza, and Beck (2000). We complement this with a small sample correction of the standard errors as described in Windmeijer (2005).
(7.) The slight differences in these results from earlier published work with the same data definitions arise because later editions of the World Bank's Worm Development Indicators, such as the one that we use from 2007, provide some observations for earlier years that were missing from previous editions.
(8.) The equations estimated include all the control variables used in Tables 1-3.
(9.) For example, an additional explanation might be that there are distinct characteristics of the two decades, the 1970s and 1980s, that made the financial ratios seem to cause growth at that time but not otherwise. Those decades are dominated by the oil shocks and periods of high inflation in many countries. It could well be that greater financial depth is associated with growth because these countries were better able to withstand the large nominal shocks that characterized char·ac·ter·ize
tr.v. character·ized, character·iz·ing, character·iz·es
1. To describe the qualities or peculiarities of: characterized the warden as ruthless.
2. the period. This would in fact be a benefit of deeper financial institutions but would not imply that increases in financial depth cause growth.
(10.) The data on stock market capitalization are from the World Development bulicators database and worksheets underlying Rousseau and Wachtel (2000).
(11.) Rolling regression techniques were first applied to study of the finance-growth nexus by Rousseau and Wachtel (2002). In that paper we showed that the cross-sectional relationship between finance and growth vanished in high-inflation environments.
(12.) The overall estimate for the entire sample is given in Table 1.
TABLE 1 OLS Growth Regressions with Pure Cross Section Data Dependent Variable: % Growth of Per Capita Real GDP 1960-2004 Log of initial real -0.583 ** -0.641 ** -0.611 ** per capita GDP (0.178) (0.178) (0.186) (2,000 US$) Log of initial 1.311 ** 1.346 ** 1.570 ** secondary (0.389) (0.411) (0.347) school enrollment rate Initial liquid 0.026 ** liabilities (M3) (0.009) (% of GDP) Initial M3 less 0.032 ** M1 (% of (0.016) GDP) Initial private 0.013 sector credit (% (0.011) of GDP) Initial government 0.042 0.075 0.051 expenditure (% (0.053) (0.053) (0.046) of GDP) Initial trade -0.008 -0.008 -0.002 (% of GDP) (0.006) (0.006) (0.004) [R.sup.2] 0.42 0.44 0.44 (number of (77) (70) (83) observations) 1960-1989 Log of initial real -0.552 ** -0.645 ** -0.565 ** per capita GDP (0.181) (0.199) (0.216) (2,000 US$) Log of initial 0.987 ** 1.067 ** 1.370 ** secondary (0.342) (0.359) (0.327) school enrollment rate Initial liquid 0.042 ** liabilities (M3) (0.010) (% of GDP) Initial M3 less 0.058 ** M1 (% of (0.017) GDP) Initial private 0.027 ** sector credit (% (0.013) of GDP) Initial government 0.077 0.113 ** 0.075 * expenditure (% (0.048) (0.051) (0.044) of GDP) Initial trade -0.020 ** -0.019 ** -0.005 (% of GDP) (0.009) (0.010) (0.006) [R.sup.2] 0.38 0.35 0.39 (number of (75) (68) (80) observations) 1990-2004 Log of initial real -0.041 -0.159 -0.077 per capita GDP (0.226) (0.226) (0.231) (2,000 US$) Log of initial 1.430 ** 1.374 ** 1.444 ** secondary (0.462) (0.464) (0.417) school enrollment rate Initial liquid -0.003 liabilities (M3) (0.006) (% of GDP) Initial M3 less 0.007 M1 (% of (0.010) GDP) Initial private -0.001 sector credit (% (0.006) of GDP) Initial government -0.123 ** -0.120 ** -0.120 ** expenditure (% (0.051) (0.055) (0.045) of GDP) Initial trade 0.012 * 0.009 * 0.010 ** (% of GDP) (0.005) (0.005) (0.004) [R.sup.2] 0.36 0.35 0.37 (number of (74) (70) (83) observations) Notes: Coefficient estimates are from OLS regressions with standard errors in parentheses. Growth rates are averaged across each data period and all explanatory variables are measured at the start of the period. The symbols ** and * indicate statistical significance at the 5% and 10% levels. TABLE 2 Instrumental Variables Growth Regressions with 5-Year Panel Data Dependent Variable: % Growth of Per Capita Real GDP 1960-2004 Log of initial real -0.059 -0.096 -0.026 per capita GDP (0.106) (0.110) (0.115) (2,000 US$) Log of initial 0.852 ** 0.851 ** 0.936 ** secondary (0.175) (0.179) (0.172) school enrollment rate Liquid liabilities 0.014 ** (M3) (% of (0.004) GDP) M3 less M1 (% 0.025 ** of GDP) (0.007) Private sector 0.005 credit (% of (0.004) GDP) Government -0.082 ** -0.074 ** -0.077 ** expenditure (% (0.022) (0.023) (0.022) of GDP) Trade (% of 0.008 ** 0.007 ** 0.010 ** GDP) (0.003) (0.003) (0.003) [R.sup.2] 0.26 0.26 0.25 (number of (637) (632) (657) observations) 1960-1989 Log of initial real -0.053 -0.157 -0.155 per capita GDP (.128) (0.137) (0.145) (2,000 US$) Log of initial 0.626 ** 0.667 ** 0.782 ** secondary (.197) (0.200) (0.194) school enrollment rate Liquid liabilities (M3) (% of GDP) M3 less M1 (% 0.028 ** 0.046 ** of GDP) (.006) (0.010) Private sector 0.024 ** credit (% of (0.007) GDP) Government -0.075 ** -0.060 ** -0.062 ** expenditure (% (.028) (0.028) (0.028) of GDP) Trade (% of 0.004 0.002 0.009 ** GDP) (.005) (0.005) (0.005) [R.sup.2] 0.30 0.30 0.29 (number of (423) (423) (427) observations) 1990-2004 Log of initial real -0.164 -0.156 -0.069 per capita GDP (0.207) (0.206) (0.206) (2,000 US$) Log of initial 1.632 ** 1.577 ** 1.650 ** secondary (0.440) (0.455) (0.418) school enrollment rate Liquid liabilities -0.001 (M3) (% of (0.006) GDP) M3 less M1 (% 0.002 of GDP) (0.009) Private sector -0.005 credit (% of (0.005) GDP) Government -0.105 ** -0.110 ** -0.107 ** expenditure (% (0.039) (0.041) (0.037) of GDP) Trade (% of 0.011 ** 0.012 ** 0.012 ** GDP) (0.004) (0.005) (0.004) [R.sup.2] 0.18 0.19 0.19 (number of (214) (209) (230) observations) Notes: Coefficient estimates are from two-stage least squares regressions using 5-year averages of the data with standard errors in parentheses. Instruments include initial values of all right-hand side variables, with initial values taken as the first observation of each 5-year period. The regressions include a dummy variable for each time period. The symbols ** and * indicate statistical significance at the 5% and 10% levels. TABLE 3 System GMM Growth Regressions with 5-Year Panel Data Dependent Variable: % Growth of Per Capita Real GDP 1965-2004 Log of initial real -0.128 -0.121 -0.031 per capita GDP (.150) (.154) (.164) (2,000 US$) Log of secondary 0.687 ** 0.682 ** 0.720 ** school (.238) (.240) (.259) enrollment rate Liquid liabilities 0.008 ** (M3) (% of (.004) GDP) M3 less M1 (% 0.013 ** of GDP) (.007) Private sector -0.001 credit (% of (.005) GDP) Government -0.055 * -0.052 -0.045 expenditure (% (.033) (.032) (.031) of GDP) Trade (% of 0.008 ** 0.008 ** 0.008 ** GDP) (.004) (.004) (.004) Hansen J-Test 0.57 0.70 0.50 (p-value) (number of (576) (571) (595) observations) 1965-1989 Log of initial real -0.143 -0.240 -0.103 per capita GDP (.156) (.169) (.153) (2,000 US$) Log of secondary 0.437 0.421 0.526 * school (.276) (.287) (.279) enrollment rate Liquid liabilities 0.028 ** (M3) (% of (.007) GDP) M3 less M1 (% 0.044 ** of GDP) (.011) Private sector 0.017 ** credit (% of (.007) GDP) Government -0.091 ** -0.076** -0.080 ** expenditure (% (.037) (.035) (.033) of GDP) Trade (% of 0.011 * 0.011 0.014 ** GDP) (.006) (.007) (.006) Hansen J-Test 0.91 0.87 0.95 (p-value) (number of (363) (363) (366) observations) 1990-2004 Log of initial real -0.243 -0.157 -0.040 per capita GDP (.265) (.246) (.290) (2,000 US$) Log of secondary 1.708 ** 1.523 ** 1.651 ** school (.589) (.603) (.565) enrollment rate Liquid liabilities 0.001 (M3) (% of (.005) GDP) M3 less M1 (% 0.004 of GDP) (.008) Private sector -0.010 * credit (% of (.006) GDP) Government -0.078 ** -0.098 -0.092 expenditure (% (.073) (.072) (.064) of GDP) Trade (% of 0.007 * 0.009 ** 0.010 ** GDP) (004) (.005) (.004) Hansen J-Test 0.18 0.38 0.12 (p-value) (number of (213) (208) (229) observations) Notes: Coefficient estimates are from "system" GMM regressions using 5-year averages of the data with standard errors in parentheses. The regressions include a dummy variable for each time period. The symbols ** and * indicate statistical significance at the 5% and 10% levels. TABLE 4 Summary of Instrumental Variables Growth Regressions with Individual 5-Year Cross Sections Dependent Variable: % Growth of Per Capita Real GDP 1960-64 1965-69 1970-74 1975-79 Liquid liabilities -0.005 0.044 ** 0.029 * 0.040 ** (M3) (.019) (.013) (.013) (.016) (% of GDP) M3 less M1 -0.002 0.062 ** 0.041 * 0.043 * (% of GDP) (.030) (.020) (.022) (.025) Private sector credit 0.009 0.034 * 0.024 0.022 (% of GDP) (.024) (.019) (.018) (.020) Dependent Variable: % Growth of Per Capita Real GDP 1980-84 1985-89 1990-94 1995-99 2000-04 Liquid liabilities 0.029 * 0.020 * -0.000 -0.001 0.002 (M3) (.015) (.012) (.012) (.008) (.008) (% of GDP) M3 less M1 0.046 0.062 ** 0.012 -0.001 0.003 (% of GDP) (.031) (.020) (.021) (.015) (.011) Private sector credit 0.011 0.036 ** -0.003 -0.005 0.001 (% of GDP) (.017) (.013) (.011) (.007) (.007) Notes: Coefficient estimates are for the financial variables listed in the left column of the table from separate two-stage least squares regressions using 5-year averages of the data with standard errors in parentheses. The growth regression summarized in each cell includes initial income, secondary education, government expenditure, and trade as controls along with the single financial variable listed. Instruments include initial values of all right-hand side variables, with initial values taken as the first observation of each 5-year period. The regressions include a dummy variable for each time period. The symbols ** and * indicate statistical significance at the 5% and 10% levels. TABLE 5 Number of Sample Countries in Financial Crises during 5-Year Periods, 1960-2004 1960-64 1965-69 1970-74 1975-79 1980-84 Major crisis 0 0 1 4 16 Minor crisis 0 0 1 3 5 1985-89 1990-94 1995-99 2000-04 Major crisis 25 23 24 15 Minor crisis 15 22 15 8 TABLE 6 Instrumental Variables Growth Regressions with 5-Year Panel Data by Crisis Status, 1960-2004 Dependent Variable: % Growth of Per Capita Real GDP Financial Variable: M3 (% GDP) M3-M1 (% GDP) Credit (% GDP) Log of initial real per -0.073 -0.103 -0.091 capita GDP (2,000 US$) (.105) (.110) (.116) Log of secondary school 0.817 ** 0.845 ** 0.940 ** enrollment rate (.175) (.179) (.171) Finance 0.020 ** 0.029 ** 0.012 ** (.004) (.007) (.004) Finance x major -0.017 ** -0.020 ** -0.015 ** financial crisis (.005) (.009) (.005) Finance x minor -0.006 -0.007 -0.008 financial crisis (.006) (.010) (.006) Government expenditure -0.085 ** -0.078 ** -0.079 ** (% of GDP) (.022) (.023) (.022) Trade (%n of GDP) 0.006 * 0.006 * 0.009 ** (.003) (.004) (.003) [R.sup.2] 0.27 0.26 0.26 (number of observations) (637) (632) (657) Notes: Coefficient estimates are from two-stage least squares regressions using 5-year averages of the data with standard errors in parentheses. Instruments include initial values of all right-hand side variables, with initial values taken as the first observation of each 5-year period. The regressions include a dummy variable for each time period. The symbols ** and * indicate statistical significance at the 5% and 10% levels. TABLE 7 Instrumental Variables Growth Regressions with 5-Year Panel Data by Liberalization Status, 1960-2004 Dependent Variable: % Growth of Per Capita Real GDP Financial Variable: M3 (% GDP) M3-M1 (% GDP) Credit (% GDP) Log of initial real per -0.036 -0.076 0.007 capita GDP (2,000 US$) (.107) (.112) (.117) Log of secondary school 0.816 ** 0.837 ** 0.935 ** enrollment rate (.178) (.180) (.174) Finance 0.014 ** 0.023 ** 0.005 (.004) (.007) (.004) Finance x never 0.005 0.009 -0.001 liberalized (.005) (.007) (.004) Finance x 0.001 -0.005 -0.005 preliberalization (.006) (.009) (.007) Finance x 0.003 0.006 0.003 postliberalization (.006) (.008) (.006) Government expenditure -0.090 ** -0.081 ** -0.080 ** (% of GDP) (.022) (.023) (.022) Trade (% of GDP) 0.008 ** 0.006 * 0.010 ** (.003) (.004) (.003) Exclude liberalization 0.79 0.45 0.79 variables (p-value) R2 0.26 0.27 0.25 (number of observations) (630) (619) (646) Notes: Coefficient estimates are from two-stage least squares regressions using 5-year averages of the data with standard errors in parentheses. Instruments include initial values of all right-hand side variables, with initial values taken as the first observation of each 5-year period. The regressions include a dummy variable for each time period. The symbols ** and * indicate statistical significance at the 5% and 10% levels. TABLE 8 Coefficients on Broad Finance Measure from Baseline Equation 1980-1984 1985-1989 1990-1994 Broad finance 0.018 0.010 -0.003 (standard error) (.013) (.009) (.006) Number of countries 39 44 51 1995-1999 2000-2004 Broad finance -0.002 0.002 (standard error) (.004) (.005) Number of countries 61 45 TABLE 9 Instrumental Variables Growth Regressions with 5-Year Panel Data for Developed and Less Developed Countries Dependent Variable: % Growth of Per Capita Real GDP Developed 1960-2004 1960-1989 1990-2004 Log of initial real per capita -0.426 ** -0.418 * -0.650 GDP (2,000 US$) (.209) (.254) (.411) Log of secondary school 0.569 ** 0.407 1.435 ** enrollment rate (.236) (.267) (.625) Liquid liabilities 0.035 ** 0.045 ** 0.019 (M3) (%n of GDP) (.010) (.017) (.014) Government expenditure (% of -0.112 ** -0.103 ** -0.127 * GDP) (.036) (.047) (.070) Trade (% of GDP) -0.001 -0.006 0.004 (.006) (.008) (.008) R2 (number of observations) 0.21 0.24 0.17 (360) (238) (122) Dependent Variable: % Growth of Per Capita Real GDP Less Developed 1960-2004 1960-1989 1990-2004 Log of initial real per capita -0.585 ** -0.552 ** -0.354 GDP (2,000 US$) (.210) (.256) (.392) Log of secondary school 1.624 ** 1.447 ** 2.371 ** enrollment rate (.333) (.371) (1.075) Liquid liabilities 0.008 ** 0.019 ** -0.006 (M3) (%n of GDP) (.004) (.005) (.005) Government expenditure (% of -0.068 ** -0.067 * -0.122 ** GDP) (.030) (.040) (.048) Trade (% of GDP) 0.013 ** 0.013 ** 0.016 ** (.004) (.006) (.005) R2 (number of observations) 0.32 0.36 0.22 (277) (185) (92) Notes: Coefficient estimates are from two-stage least squares regressions using 5-year averages of the data with standard errors in parentheses. Instruments include initial values of all right-hand side variables, with initial values taken as the first observation of each 5-year period. The regressions include a dummy variable for each time period. The symbols ** and * indicate statistical significance at the 5%n and 10% levels.