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Roberto Steiner and Natalia Salazar are research economists at Fedesarrollo, Bogotá, Colombia. We would like to thank Olver Bernal, Miguel Bonangelino, Eduardo Borensztein, Leonardo Cardemil, Giovanni Dell’ Ariccia, Enrica Detragiache, Pietro Garibaldi, Alfredo Leone, Eduardo Levy-Yeyati, Gian Maria Milesi-Ferreti, Alberto Musalem, Kevin Ross, Ratna Sahay, and Marco Terrones for valuable comments and discussions on earlier drafts of the paper. We would also like to thank the Inter-American Development Bank for support for this project and for comments on earlier versions, and to participants of seminars in the IMF Research Department, the IDB, Fedesarrollo, and the Banco de la República.
See Shaffer (1989) and (1993) for applications to the U.S. and Canada, respectively, Hannan & Liang (1993) for an application local deposit markets in the U.S., Suominen (1994) for an application to Finnish banking, Gruben & McComb (1996) as applied to Mexico, and Gruben & Koo (1997) as applied to Argentina.
It has been suggested that certain non-managerial factors external to the banking firm (such as high security and/or transportation costs) may contribute to the high observed overhead expenses in Colombia. While the study by Suescún & Misas (1996) showed evidence of significant managerial x-inefficiency in banks, there is certainly scope for additional work to investigate to how important the non-managerial factors may be.
This also can be viewed as an issue of bank franchise value, which has been shown to be a key factor limiting moral hazard and excessive risk-taking (Caprio & Summers, 1993; Hellman, Murdock, and Stiglitz, 1998). To the extent that high spreads arising from market power reflect a high franchise value, the likelihood of a bank crisis may be smaller than in the case of a competitive system with lower spreads.
The average lending rate is an “ex post” rate, calculated as interest received/performing loans. To the extent that many nonperforming loans may have been contracted at higher “ex ante” rates, this measure will tend to understate the contracted or ex ante lending rate, and therefore the spread. Also, to the extent that banks have participated in directed credit programs at subsidized interest rates, we adjusted the average lending rate by the share of directed credit in total credit and by its average interest rate, so as to obtain a “market” lending rate”. This adjustment was relevant primarily for the pre-liberalization period, when directed credit represented between up to 16 percent of total bank credit and its lending rate was close to zero in real terms.
For the post-liberalization period we calculated m using a weighted average of 30 banks comprising virtually the entire banking system. For both periods we annualized the respective monthly or quarterly flows, and took the stocks of loans and deposits at their monthly or quarterly level.
For a series yt the procedure consists of finding a trend component µt and a seasonal component (yt - µt) which minimize the following sum of squares:
where β is a predetermined constant which represents the “cost” of introducing fluctuations into the trend component. If β approaches zero, then the sum of squares is minimized with yt equal to µt. If β approaches infinity, then the sum of squares is minimized with a linear trend. Hodrick and Prescott suggest alternative values for β depending on whether monthly, quarterly, or annual data are being used. See Enders (1995) for a detailed description of this methodology.
Part of the observed peak in 1992 is due to a statistical quirk; a large state bank with a particularly high nonperforming loan ratio entered the sample in May, 1992. Our aggregate regressions therefore are run on the 1992:05 - 1996:08 sample.
Separate analysis not reported here shows that lending and deposit rates both exhibit a unit root and are cointegrated for the banking system as a whole, for state-owned banks, and for private banks. Therefore, bivariate regressions between the two are free of spurious correlation problems arising in non-cointegrated I(1) variables. These results are available upon request.
Exogeneity of loan quality with respect to the spread was further supported by regression analysis of NPL. In equations with NPL as the dependent variable and which included as regressors the monthly index of industrial production, a survey index of business climate, and the one-period lagged value of NPL, the lending rate was not a significant explanatory variable.
This type of model was used earlier by Barajas (1996) to analyze the aggregate banking system during the 1974-1988 period. An individual bank-level framework for Colombia was used by Montes & Carrasquilla (1986) and later updated by Carvajal & Zarate (1996), but was based on accounting identities rather than on a behavioral model.
Two comments must be made. First, although the required reserve ratio is a policy variable which is imposed equally on all banks, the average reserve ratio, ε, varies from bank to bank since the required reserve ratio varies by type of deposit and each bank has a different composition of deposits. Second, in the pre-liberalization period R and ε also contain forced investments which frequently amounted to over 10 percent of bank deposits.
One significant difference between this formulation and that of Shaffer is that the latter includes interest costs within the aggregate cost function C, while we include only nonfinancial costs and opt to separate financial costs from the cost function. Since there is no clear consensus on whether financial costs should be included or not (see for example Dick (1996) and Suescún & Misas (1996)), excluding them proved more convenient in order to obtain a clear expression for the interest spread. Furthermore, separating interest costs from the operational cost function could potentially allow one to test whether market power exists on the deposit side as well.
This assumption was also maintained in applications of the Shaffer analysis to Mexico and Argentina by Gruben & McComb(1996) and Gruben & Koo (1997), respectively. This assumption seemed reasonable in the Colombian case, as banks face natural competition from other financial intermediaries that offer similar types of deposits, but may have a certain amount of market power on the lending side where they do not face as clear a challenge. As Shaffer points out, if the deposit market is not perfectly competitive, then a finding of market power is still valid, but may be misattributed to the loan market.
Suominen models the banking firm as a producer of two outputs, deposits and loans, but provides no balance sheet link between the two. Barajas (1996) uses a two-product formulation that incorporates the balance sheet link but does not rely on joint estimation with the demand function(s).
For 21 banks, information was available from 1991:03 but for the aggregate system estimations we opted for the shorter time period since the additional bank (for which information was available only from 1992:05 onward) was particularly large.
The lack of success in estimating a reliable demand function for loans in the pre-liberalization period limited our ability to apply the system approach for comparative purposes between the two periods. The difficulties arose in obtaining satisfactory indicators for a price of substitutes of bank loans, which hindered the identification of λ.
We were only able to construct a wage variable in the post-liberalization sample, since no banking sector employment data was available prior to 1990.
Shaffer (1993) used a similar variable for the U.S., a 3-month treasury bill, and Gruben & McComb (1996) used a 28-day treasury bill in the case of Mexico. We also ran the regressions using a money market or interbank interest rate as the price of a substitute, but it did not perform as well as the central bank bill rate, possibly as a result of its high volatility.
Berger & De Young (1997) find evidence of a positive relationship between banks’ operational costs in the U.S. and the percentage of nonperforming loans, which appear to reflect two hypotheses: (1) a “bad luck” hypothesis whereby exogenous increases (decreases) in bad loans lead to increases (decreases) in costs as banks must intensify their monitoring, and undertake additional expenses for working out or selling off these loans, (2) a “bad management” hypothesis whereby a deterioration in managerial efficiency-shown by an increase in operational costs-causes an increase in bad loans, as the ability to screen loans and manage credit risk also deteriorates.
The probability of the Wald test for perfect competition is equal to zero at four digits. This is also true for a test comparing this parameter to the value estimated in the earlier subperiod, 1.29.
This result contrasts with one presented in a previous version of this paper (Steiner, et. al., 1997), where the hypothesis of market power in the 1992-1996 period was not rejected for the banking system as a whole. Regressions were run using a linearized version of the spread equation (5b), and with a preliminary data set. Once several improvements were made to the data (adjusting for certain excessive volatility in estimates of individual bank interest rates) and regressions were run using the exact functional form of the spread equation, the finding of significant market power remained only for the private banks.
It could be argued that since the lending rate reflects the cost in terms of foregone earnings of nonperforming loans, the effect of loan quality on the spread should tend to increase if the lending rate increases. However, given that the lending rate remained essentially constant on average between the two periods (at 35 percent) the increase in the estimated parameter does not seem to be due to an increase in the foregone earnings cost of nonperforming loans.
While it is likely that the pre-crisis years were marked by the perception of an implicit deposit insurance--a situation conducive to moral hazard--the handling of the Colombian crisis has been considered largely successful in providing adequate signals to bank managers. Stockholders of failing institutions were forced to assume significant losses, one bank was closed, and parties responsible for reckless management were prosecuted (Clavijo, 1992; Rojas-Suárez & Weisbrod, 1996).
In other words, total loans of an individual bank are much smaller than those of the aggregate system. For example, a banking industry coefficient of -0.1 (as in the FIML result) is equivalent-in terms of its effect on the interest spread--to a coefficient of -2.0 for a bank with a 5 percent market share.
Since one essential difference between the aggregate estimation and the panel data regression is that the former procedure implicitly assigns weights to individual banks according to size, the contrasting results on market power indicate that the aggregate results may be driven by several larger private banks that possess market power, while on average most smaller banks behave competitively, consistent with a von Stackelberg type of market structure. Spiller & Favaro (1984) use this type of framework to study the impact of changes in banking regulations in Uruguay in 1977-1980 period.
Given that our results for these two regressions indicated that there was no market power, we re-estimated these equations imposing competitive behavior (dl=1).
Loan quality did not even appear to worsen in 1996, when economic growth decelerated from an average of 5.2 percent in 1992-1995 to 2.1 percent.
For the banking system as a whole, Table 9 shows that the capital-to-asset ratio was 13.7 percent at the of 1996, while the legal requirement was 9 percent. For three of the largest banks, this ratio was above 15 percent.
Yu (1995) found a similar positive relationship between bank intermediation spreads in Canada and the capital-to-asset ratio. The approach there was different, however, in that the capital ratio was treated as an exogenous and policy-determined variable, and therefore entered the equations as a determinant of the spread. In our case, given that observed capital ratios greatly exceeded the legal minimum, it seemed more reasonable to consider this variable as an endogenous decision variable by the banking firm, and to treat it as a use of the profits engendered by the banking activity.
Claessens, et. al (1997) analyze a sample of 80 countries to show how significant gains in efficiency and in spread reduction are derived from foreign entry into banking.
It is interesting to note that this measure--an increase in required reserves on private foreign borrowing--was applauded by the bankers themselves, thus suggesting that their effective market power had been enhanced (see El Espectador, pg 6B, May 22, 1997).