They also stated that the benefit of deposit insurance is to ensure banking system stability from systemic risks. Another study also found that deposit insurance schemes are motivated to protect small and uninformed depositors (Dewatripont and Tirole, 1994). Similarly, Cull et al. 2005) stated that the strength of public regulations affects the deposit insurance system.
Surprisingly, Calomiris (1990) used the US banking system and found that banks are more likely to fail with a deposit insurance fund. Using land banks as a sample, Alston et al. 1994) found that agricultural distress affects more banks to fail in a state with deposit insurance systems. According to the FSB (2016), “safety nets” are “the functions of the resolution authority, the lender of last resort and the authorities responsible for prudential regulation and supervision and for financial sector policy and relevant insurance schemes and arrangements for the protection of depositors and other protected customers”.
The deposit insurance scheme is known as one of the three pillars of the net financial system1. 1 The three pillars of the safety net: a deposit guarantee scheme, a lender of last resort, a framework for bank resolution.
MORAL HAZARD PROBLEM: CAPITAL ADEQUACY AND BANK RISK
BANK RESOLUTION IN INDONESIA
Through this scheme, assets and liabilities with the strongest legal status of the bank should be excluded from the failed bank. Second, if the asset is abandoned by the buyer due to poor financial market conditions, then the assets and liabilities of the failed bank will be temporarily accommodated by the bridge bank managed by IDIC. In choosing solution options, IDIC has one main principle, the principle of the lowest cost solution.
The choice of bank resolution method should take into account the costs and benefits as a whole (not only the financial aspects), but also the socio-economic aspects. The new alternative to settlement arrangement in Indonesia: (1) Purchase and Assumption (P&A): According to IADI, P&A is a settlement method in which a healthy bank or thrift purchases assets and assumes liabilities from an unhealthy bank or thrift. In this bankwide transaction scheme, all of the bank's assets and liabilities are transferred to the acquiring bank (FDIC, 2017).
Governments now require the investors and depositors of a bank to take a loss before taxpayers because bailouts would simply create moral hazard. To complete a least-cost comparison, the cost to liquidate should be compared with the cost of each type of resolution scheme (purchase and assumption, bridging bank, temporary capital investment and liquidation). Input/classification, asset valuation, asset recovery calculation, expected income and expenses, and least cost test results.
The importance of calculating the shadow price of equity capital of rural banks in Indonesia is to find out how this shadow price can affect the recovery rate of failed banks. As far as we are concerned, there is no study on the impact of shadow pricing on bank recovery rates. High shadow prices of bank equity imply that banks have a high cost of capital and also indicate excessive risk-taking behavior, which can result in lower recovery rates.
By the same token, high shadow prices of bank deposits imply that banks have high costs of borrowed funds and also have indicators of excessive risk-taking behavior that may result in lower recovery rates.
DATA AND METHODOLOGY
- DATA AND SAMPLE
- SHADOW PRICES CALCULATION
- METHODOLOGY AND EMPIRICAL SPECIFICATIONS: RECOVERY RATES AND SHADOW PRICES
- METHODOLOGY AND EMPIRICAL SPECIFICATIONS: MORAL HAZARD EFFECT
As for the macroeconomic variables, we use quarterly data from the Indonesian Central Statistics Office's SME Producer Price Index. Second, to test whether a moral hazard effect exists, we use bank risk (NPL ratio) as the dependent variable. We use the capital adequacy ratio, the IDIC interest rate limit and other control variables as independent variables.
To calculate the shadow price, we use stochastic frontier analysis (SFA), which is a parametric method. In this study, we use current loan and other income as a proxy for good outputs y1 and y2 and non-performing loan as the bad output b. As a set of inputs x we use the price of labor (P1) calculated as the ratio of personal and administration expenses relative to total assets, the price of physical capital (P2) calculated as the ratio of total depreciation expenses to fixed, the price of funds (P3) calculated as the interest expenses on total deposits, which includes the deposits of other banks.
As can be seen from Panel A in table 4.1, the average recovery rate of the sample of 52 failed rural banks is 42 percent of which the liquidation processes have been completed. The average of IDIC interest rate is 9 percent for rural banks (2.5% higher than commercial banks). One of the characteristics of rural banks in Indonesia is a high loan to deposit ratio, because they mostly earn profit or margin from the loan market (borrowing) as the.
We use the quarterly index of micro and small industrial production (SME production index) to proxy the provincial macroeconomic variable. In Panel B, we use all the variables (input, output, net and total cost) to be included in the SFA analysis to obtain the shadow prices of equity and the shadow prices of deposits. This number is high, while compared to the KJPs of rural banks at the national level, about 6 percent.
In terms of capital requirement ratio, the average CAR is 12.7 percent, but more than 50 percent of these failed rural banks have a CAR of less than 10 percent (low capital).
MAIN EMPIRICAL RESULTS AND ANALYSIS
SHADOW PRICES OF BANK EQUITY-CAPITAL AND BANK DEPOSITS
The shadow price is the unit change in the optimal objective value per unit change in the right-hand side (RHS) of the equation. The negative shadow price of equity capital means an increase in RHS coefficient leads to a decrease in optimal objective value. The average shadow price of deposits is 0.19, which means that an increase in RHS coefficient leads to an increase in optimal objective value.
We also calculate the bank's cost efficiency using the SFA methodology, the BC95 model (parametric techniques).
THE EFFECT OF SHADOW PRICES OF BANK EQUITY-CAPITAL AND BANK DEPOSITS ON BANK RECOVERY RATE
We explain this as the results of a negative shadow price of equity in failed rural banks, as banks face high deleveraging, so that in the short term (temporarily) shadow prices of equity could become negative. On the other hand, the effect of the shadow price of deposits on the bank recovery rate is -0.07. Although we cannot reject the hypothesis as this result is not significant, the sign of shadow prices is consistent with our expectation with an R-squared of 31.60 percent.
The main function of traditional banking, especially rural banks, is to accept deposits and grant loans. When banks fail, they must return deposits and this will reduce the disbursement results of the assets collected by the IDIC. The variable days or time for liquidation of failed banks shows a positive effect on the recovery rate.
Although we expect the liquidation period to have a negative effect on the recovery rate of banks, we can explain it as IDIC can achieve more asset disbursements from failed banks. Larger banks tend to generate higher recovery rates than smaller banks since the deposit insurer can achieve more asset sales at banks with higher assets. Most rural banks earn profits from the loan market, and this probably increases the value of the banks.
The IDIC interest rate cap has a positive effect on the banks' recovery rate, which increases depositors' confidence in putting their money in the banks, as the guaranteed interest rate is higher. The bank stability index shows a negative sign of recovery rate, it could be interpreted as in a more normal state, if the bank failed, the recovery rate fell. More banks give loans to SMEs, create more unpaid loans and then reduce the disbursement of assets.
MORAL HAZARD IN RURAL BANKING MARKET
The results are consistent with our OLS estimation, with a negative effect of CAR on banks' NPL ratio, supporting the moral hazard hypothesis.
LIMITATIONS AND IMPLICATIONS
CONCLUSION
The results show that banks with high capital costs (shadow price of equity) have high recovery rates. However, this finding is against our hypothesis, which claims that the shadow price of equity has a negative effect on the recovery rate. We explain it as the results of negative shadow price of equity, which is found in bankrupt rural banks, as the banks experience high deleveraging, so that the shadow price of equity in the short term (temporarily) can become negative.
On the other hand, the effect of shadow price of deposits on bank recovery rate is negative, consistent with our expectation that banks with high cost of funds tend to lower the recovery rate. In terms of moral hazard effect, we conclude that moral hazard exists in rural banking market. Also, when the maximum interest rate given by IDIC is higher, the bank can take an advantage to give more interest to the deposits as well as increase their loan interest.
It causes more loans and also the non-performing loans as the default risk of the borrower increased. Deposit insurance could lead to moral hazard, because banks have incentives to take more risk (Demirgüç-Kunt and Kane, 2002). Panel B: Variables used in the analysis of shadow prices Total costs TC Total interest costs.
Panel C: Variables used in the analysis of moral hazard effect NPL ratio NPL Non-performing loan to total. This table presents the value of shadow prices of equity capital, shadow price of deposits and bank cost efficiency based on the translog cost functions using SFA method BC95. This table presents the regression of shadow prices of equity capital, shadow price of deposits and cost efficiency on recovery rate, controlling for days of liquidation, bank stability index, IDIC interest rate, SMEs production growth, bank size and liquidity using OLS estimation.
This table presents the regression of capital adequacy ratio on NPL ratio, controlling for IDIC interest rate, bank stability index and SME output growth using fixed effect OLS estimation and Dynamic Panel Model GMM.
