Financial Development, Financial Fragility, and Growth
Summary (3 min read)
FINANCIAL DEVELOPMENT, FINANCIAL FRAGILITY, AND GROWTH
- This paper analyzes the apparent contradiction between two strands of the literature on the effects of financial intermediation on economic activity.
- Second, the authors attempt to provide an empirical explanation to these contrasting effects.
- In particular, on the one hand the authors relate the positive influence of financial depth on investment and growth to the long-run effect of financial liberalization; and, on the other, they describe a link between the negative impact of financial volatility and crisis and the short-run effect of liberalization.
- For this purpose, the authors estimate an encompassing model of short- and long-run effects using a panel of crosscountry and time-series observations.
- And third, the authors go back to the classic context of growth regressions and consider whether the volatility and crises aspects of financial liberalization are relevant growth determinants, along with the usual measures of financial depth.
II. SHORT- AND LONG-RUN GROWTH EFFECTS OF FINANCIAL INTERMEDIATION
- In this section the authors estimate an empirical model that encompasses the short- and long-run growth effects of financial intermediation.
- The authors use the estimation results to formulate an empirical explanation of the apparently contradictory effects of financial intermediation on economic activity.
- This explanation is based on the distinction 1 Except for a few rather recent papers, some of the reviewed below in the paper.
- The authors method can be summarized as a panel errorcorrection model, where short- and long-run effects are estimated jointly from a general autoregressive distributed-lag (ARDL) model and where short-run effects are allowed to vary across countries.
- First, while averaging clearly induces a loss of information, it is not obvious that averaging over fixed-length intervals effectively eliminates business-cycle fluctuations.
A. Methodology
- The first is the need to separate and estimate short- and long-run effects without the need to decompose directly trend and transitory components of growth, financial intermediation, and the other explanatory variables.
- The authors treat this issue below in the context of single-country estimation.
- The second issue is the likely possibility that the parameters in the relationship between financial intermediation and economic activity be different across countries.
- On the other hand, the authors can expect that long-run relationships would be more homogeneous across countries.
- 2 Similar arguments are made by Attanasio, Scorcu, and Picci (2000) in their cross-country study on the dynamic relationship between saving, investment, and growth.
Single-country estimation
- The challenge the authors face is to estimate long- and short-run relationships without observing the long- and short-run components of the variables involved.
- From this literature, two common misconceptions have been derived.
- Furthermore, these methods avoid the need for pre-testing and order-ofintegration conformability given that they are valid whether the variables of interest are I(0) or I(1).
- It is worth noting that the assumption of a unique long-run relationship underlies implicitly the various single-equation based estimators of long-run relationships commonly found in the cointegration literature.
- Related to growth and its determinants, β are the long-run coefficients, ϕ is the speed of adjustment to the long-run relationship, ε is a time-varying disturbance, and the subscripts i and t represent country and time, respectively.
Multi-country estimation
- The sample the authors use for estimation is a “data field,” in the sense that it is characterized by time-series (T) and cross-section (N) dimensions of roughly similar magnitude.
- The PMG estimator also generates consistent estimates of the mean of short-run coefficients across countries by taking the simple average of individual country coefficients (provided that the cross-sectional dimension is large).
- The choice among these estimators faces a general trade-off between consistency and efficiency.
- The interested reader is referred to Pesaran, Shin and Smith (1999) where the PMG estimator is developed and compared with the MG estimator.
- When the main interest is on the long-run parameters, the lag order of the ARDL can be selected using some consistent information criteria (such as the Schwartz-Bayesian Criterion) on a country-by-country basis.
B. Data and Results
- As outlined in the previous section, the consistency and efficiency of the PMG estimates relies on several specification conditions.
- Most importantly for their purposes, the authors find that economic growth is positively and significantly linked to the measure of financial intermediation in the long run.
- Before the authors do that, however, they need to make sure that their results are robust to the exclusion of outlying and dynamically unstable observations.
- In particular, the authors want to check to what extent the long-run coefficients and especially the average of short-run coefficients are sensitive to the exclusion of countries whose estimated short-run effects are considerably larger (in absolute value) than typical effects in the sample and countries that present errorcorrection coefficients that statistically fall outside the dynamic stable range.
FINANCIAL DEVELOPMENT
- By focusing on the effects of financial intermediation at different time horizons, the analysis conducted in the previous section helps us set the basis for an explanation of the apparently contradictory effects of financial intermediation on economic activity.
- Second, the authors consider this possibility by examining connection between country-specific measures of financial volatility and crisis and the country-specific short-run effects of financial intermediation estimated in the previous section.
- Then, whereas the short run of financial liberalization is marked with financial crisis, volatility, and low output growth, in the long run financial liberalization is bound to improve economic growth.
- When financial liberalization occurs and a large cohort of new firms enters the market, the absence of information capital leads to high interest rates, a risky banks’ loan portfolio, and inevitably credit misallocation.
- Table 4 presents the tests of the difference in short-run coefficient means for the various ways of grouping countries.
Data and Methodology
- The authors work with a pooled (cross-country, time-series) data set consisting of 82 countries and, for each of them, at most 8 non-overlapping five-year periods over 1960- 2000.
- They are the average ratio of private credit to GDP, as measure of financial depth, and the frequency of systemic banking crises and the standard deviation of the growth rate of private credit/GDP, as measures of financial fragility.
- Finally, the regression equation allows for both unobserved time-specific and country-specific effects.
- Since typically the moment conditions over-identify the regression model, they also allow for specification testing through a Sargan-type test.
Results
- Table 5 reports the regression estimation results as well as the Sargan and Serial- correlation specification tests.
- These tests indicate that the hypothesis of correct identification cannot be rejected, thus supporting the estimation results to which the authors turn next.
- The second and third columns include, respectively, financial volatility and the frequency of systemic banking crises as additional explanatory variables.
- The authors can get a broad sense of the economic importance of these effects by using the point estimate of the regression coefficients to calculate the growth impact of a change in their financial measures.
- An increase of one sample standard deviation in financial volatility leads to a decrease of 0.3 percentage points in the annual growth rate of GDP per capita, and an analogous increase in the frequency of systemic banking crises produces a 0.7 percentage point drop in annual growth.
IV. CONCLUSIONS
- Over the long run, financial development supports and promotes economic growth.
- Whether intrinsic to the process of development or induced by policy mistakes, these elements of financial fragility can hurt economic growth and will do so until maturity is reached.
- Recognizing the possibility of a dual effect of financial intermediation on economic growth, this paper estimates an encompassing empirical model of long- and short-run effects using a sample of cross-country and time-series observations.
- For more stable countries, this effect is in average nil.
- Finally, attempting to relate their results to the empirical growth literature, the authors go back to the classic context of growth regressions using panel data.
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References
26,580 citations
"Financial Development, Financial Fr..." refers background or methods in this paper
...This is the generalized method of moments (GMM) for dynamic models of panel data developed by Arellano and Bond (1991) and Arellano and Bover (1995)....
[...]
...As Arellano and Bond (1991) and Arellano and Bover (1995) show, this set of assumptions generates moment conditions that allow estimation of the parameters of interest....
[...]
19,132 citations
16,245 citations
"Financial Development, Financial Fr..." refers background or methods in this paper
...This is the generalized method of moments (GMM) for dynamic models of panel data developed by Arellano and Bond (1991) and Arellano and Bover (1995)....
[...]
...As Arellano and Bond (1991) and Arellano and Bover (1995) show, this set of assumptions generates moment conditions that allow estimation of the parameters of interest....
[...]
9,420 citations
8,204 citations
"Financial Development, Financial Fr..." refers background in this paper
...This is interpreted as the growth enhancing effect of financial development (e.g., King and Levine, 1993; Levine, Loayza, and Beck, 2000)....
[...]
...The growth literature has emphasized the role of financial depth and found a positive and significant effect on growth (see King and Levine 1993 a, b; and Levine, Loayza, and Beck 2000)....
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Frequently Asked Questions (11)
Q2. What are the future works mentioned in the paper "Financial development, financial fragility," ?
Recognizing the possibility of a dual effect of financial intermediation on economic growth, this paper estimates an encompassing empirical model of long- and short-run effects using a sample of cross-country and time-series observations. The authors find that a positive long-run relationship between financial intermediation and output growth can coexist with a negative short-run relationship, which indeed is the case for the average country in the sample. Since the methodology allows us to obtain the short-run effects of financial intermediation on growth country by country, the authors can attempt to link these effects to the aspects of financial liberalization that the literature proposes as harmful to growth. The authors find that financially fragile countries, namely those that experience banking crises or suffer high financial volatility, tend to present significantly negative short-run effects of intermediation on growth.
Q3. What are the main requirements for the validity of this methodology?
The main requirements for the validity of this methodology are that, first, there exist a long-run relationship among the variables of interest and, second, the dynamic specification of the model be sufficiently augmented so that the regressors are strictly exogenous and the resulting residual is serially uncorrelated.
Q4. What is the effect of financial depth on growth?
whereas financial depth leads to higher growth, financial fragility --as captured by financial volatility and banking crises-- has negative growth consequences.
Q5. What are the two conditions that are required to be considered as exogenous?
The first are that the regression residuals be serially uncorrelated and that the explanatory variables can be treated as exogenous.
Q6. What criteria can be used to select the lag order of the ARDL?
When the main interest is on the long-run parameters, the lag order of the ARDL can be selected using some consistent information criteria (such as the Schwartz-Bayesian Criterion) on a country-by-country basis.
Q7. Does the Hausman test reject the homogeneity of individual long-run coefficients?
The Hausman test does not reject the joint homogeneity of all long-run parameters; and it does not reject the homogeneity of individual long-run coefficients except for that on initial income.
Q8. How can the authors get a broad sense of the economic importance of these effects?
The authors can get a broad sense of the economic importance of these effects by using the point estimate of the regression coefficients to calculate the growth impact of a change in their financial measures.
Q9. How is the estimation of the long-run slope coefficients done?
the estimation of the long-run slope coefficients is done jointly across countries through a (concentrated) maximum likelihood procedure.
Q10. How much does an increase in one sample standard deviation of financial depth lead to economic growth?
On the other hand, an increase in one sample standard deviation of financial depth leads to economic growth rising by 0.9 percentage points.
Q11. What is the average short-run impact of financial intermediation on output growth?
Countries that experienced financial crises in the last 40 years exhibit an average shortrun impact of financial intermediation on output growth that is significantly more negative than the average of countries that did not have any crisis.