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Credit Crunch and Saving Glut in Taiwan: Empirical Evidences

Credit Crunch and Saving Glut in Taiwan: Empirical Evidences. Cheng-Few Lee Distinguished Professor of Finance, Rutgers University, USA Chiung-Min Tsai Central Bank of the Republic of China (Taiwan). Abstract. To indentify the developments for bank credit allocation in Taiwan

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Credit Crunch and Saving Glut in Taiwan: Empirical Evidences

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  1. Credit Crunch and Saving Glut in Taiwan: Empirical Evidences Cheng-Few Lee Distinguished Professor of Finance, Rutgers University, USA Chiung-Min Tsai Central Bank of the Republic of China (Taiwan)

  2. Abstract • To indentify the developments for bank credit allocation in Taiwan • Using a disequilibrium model to evaluate whether • An excess demand, i.e. a credit crunch, or • Excess supply, i.e. a saving glut, during these periods • Major findings • A considerable excess demand, or credit crunch, during Asian financial crisis • On the contrary, there were some periods experiencing an excess supply from 2001 to 2004, or the “saving glut” as mentioned by Bernanke (2005) • Furthermore, the saving glut was still prevailing during the periods of global financial crisis

  3. Outline • I. INTRODUCTION • II. A DISEQUILIBRIUM MODEL OF THE BANK LOAN MARKET A. Development of Disequilibrium Model for Bank Loan Market B. Estimation Methods • III. TESTING THE EXISTENCE OF PRICE ADJUSTMENT PROCESS IN TAIWAN’S COMMERCIAL LOAN MARKET A. Model Specification B. Empirical Results • IV. SUMMARY

  4. I. INTRODUCTION • The concept of credit rationing is first developed by Jaffee (1971) for a commercial loan market • One of the reasons for credit rationing is the existence of bankruptcy costs, as proposed by Miller (1977) • As a result, some firms will not receive the loan regardless of the rate they are willing to pay • Sealey (1979) extends the study and uses a generalized disequilibrium model (DM) to examine whether there is an excess demand in the commercial loan market • The empirical results show that models of commercial loan market being unable to explicitly include the effects of market disequilibrium are likely to yield inconsistent parameter estimate

  5. I. INTRODUCTION • Nehls and Schmidt (2003) examine whether the Germany economy is affected by a credit crunch in the early years of 2000 • The empirical results suggest a supply-side restriction of loans is not in line with market interest rates and profitability of investment projects • A considerable excess demand, i.e., a credit crunch, particularly in the second half of 2002 • Financial liberalization and deregulation reduce the magnitude of disequilibrium; However, the risk of credit crunch can’t be ruled out • The global imbalance and financial crisis tell us that • Sometimes the price adjusts too slow to clear the market, and • Sometimes the government has to step in • The insightful value of DM should be explored widely in practice

  6. Supply Demand P P* Qd, Qs Q* II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET A. Disequilibrium Model • In general, markets are in equilibrium • Supply: • QS = α1 +α2P + α3X + εS (α2 > 0) • Demand: • QD =β1+ β2P + β3Y + εD (β2 < 0) • Equilibrium • QS = QD = Q* • But, sometimes are not

  7. P P* Qd, Qs Supply Demand II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET • All disequilibrium models share the feature that prices do not fully adjust to the market clearing level • The DM consists of the following equations: (1) QDt = α1 Pt + β1’XD,t + μt, (2) QSt = α2 Pt + β2’XS,t + υt, (3) Qt = min (QDt, QSt ), (4) ΔPt = Pt - Pt-1 = γ(QDt - QSt ), γ: price adjustment factor, 0<γ∞

  8. II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET • where the QDt and QSt are the quantities of securities demanded and supplied, respectively • Qt is the actual or observed quantity of securities in the market; Pt is the observed return rate of securities • XD,tand XS,t are vectors of exogenous or predetermined variables including the lagged Pt-1 • α1 and α2 are unknown parameters for Pt; β1and β2are vectors of unknown parameters for exogenous variables • γ is an unknown positive scalar parameter; and • μt and νt are disturbance terms and assumed to be jointly normal and independent over time with distributions N(0, σ2μ) and N(0, σ2υ)

  9. II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET • In the equilibrium model, the existence of supply effect is the core issue • In the DM, the parameter of the most interested is γ in (4) • If γ = 0, then, there is no price adjustment in response to an excess demand, and • If γ is infinity, price adjusts instantaneously • In other words, if one assumes there is price rigidity in response to an excess demand, γ should equal to zero • i.e., the most important test of the disequilibrium model is to examine whether the price adjustment parameter is zero

  10. 1 = a + - D + m + ' Q P β X P g t 1 t 1 D,t t t 1 - = a + - D + u ' Q P β X P t 1 t 2 S,t t t g II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET B. Estimated Methods • One can reformulate the above model by considering periods of rising prices ΔPt > 0 and periods of falling prices ΔPt < 0 • The equations (1) to (4) can be reformulated and summarized as: (5a) (5b) where

  11. II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET 1. 2SLS Estimator • The equations system shown in (5) contains the jointly dependent variables Qt, Pt, ΔPt+ andΔPt- • The parameters in the above modified model can be consistently estimated by the conventional 2SLS method • In the first stage, regress and on all of the exogenous variables, XD, t and XS, tto obtain the estimations of and then, • In the second stage, regress Qt on XD, tand in equation (5a), and regress Qton XS, tand in equation (5b) • The estimators of , , and could be consistent, but are not asymptotically efficient in this model

  12. 1 1 + - = - a - b + D - a - b + D ' ' ' u ( Q P X P , Q P X P ) ,t 1 2 1 D 2 S t t t t t t t t g g II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET 2. Maximum Likelihood Estimator • Quandt (1988) employs an appropriately formulated full-information maximum likelihood technique • He suggests one can use the log likelihood function represented as equation (6) to find the ML estimator (6) where

  13. II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET • Amemiya (1974) suggests the MLE can be obtained by solving the following equations simultaneously

  14. II. DEVELOPMENT OF DISEQUILIBRIUM MODEL FOR BANK LOAN MARKET • That is, the ML estimators of α and β are the same as LS estimators given γ applied to equation (5). • Amemiya suggests the above parameters can be solved by using the following iterative procedures Step 1: Use 2LSL estimates of α, β, σ2μ and σ2υ as the initial estimates Step 2: Substitute , , and into (7e) and solve for the positive root of γ, Step 3: Use in (5) to obtain least squares estimates of α, β, σ2μ and σ2υ Step 4: Repeats step 2 and 3 until the solutions converge

  15. III. TESTING THE EXISTENCE OF PRICE ADJUSTMENT PROCESS IN TAIWAN’S COMMERCIAL LOAN MARKET A. Model Specification • Demand Function where QDt is the demand for commercial loan (in DM, this can’t be observed) rtis the observed commercial loan rate, IPt is the index of industrial production, and Xt is the growth rate of export • The 2nd variable, the index of industrial production, can measure the firm’s expectations about future economics activity, and thus, is used as a typical specification in many studies • In Taiwan, export sector has played a very important role in economic performance. And thus, firms’ demand for commercial loan is affected by the growth rate of export

  16. III. TESTING THE EXISTENCE OF PRICE ADJUSTMENT PROCESS IN TAIWAN’S COMMERCIAL LOAN MARKET • Supply Function where QSt is supply of commercial loan, TDtis the amount of total deposits, and ORt is the interbank overnight interest rates • The TDt is used to capture the capacity of the banking sector to lend, which is the major variable to the supply function • The 3rd variable, ORt, is used for two reasons • This rate can be seemed as an indicator of monetary policy direction, and • It is also related to the banks’ profit margin indirectly as well

  17. III. TESTING THE EXISTENCE OF PRICE ADJUSTMENT PROCESS IN TAIWAN’S COMMERCIAL LOAN MARKET B. Empirical Results • The expected signs of the coefficients should be as follows • The sign of α1and α2 should be negative and positive respectively since a higher price (i.e. loan rate) means a decline in demand but encourages bank to lend more • β11and β12 are expected to be positive since a prosper economic activities boost demand for loan. And finally • β21 and β22 should be positive and negative respectively • For the former, an increase in total deposits gives the banking industry more ability to lend • For the latter, a lower interbank overnight rate will increase one bank’s profit margin and it also means an easing in monetary policy. Both of the reasons will encourage banks to lend more

  18. Table 1. MLE of Commercial Loan Market Table 1 summarizes the MLE of the presented DM. From the table, the signs of the estimated parameters are all in the correct direction and at a significance level of 5% Data used are from 1994Q3 to the end of 2009. This is because though the banking industry was deregulated in 1989, the number of institutions and branches was at peak around 1994. The business of banking industry then becomes more stable and reliable

  19. III. TESTING THE EXISTENCE OF PRICE ADJUSTMENT PROCESS IN TAIWAN’S COMMERCIAL LOAN MARKET B. Empirical Results • The parameter of most interest in the model, the market adjustment parameter γ, is slightly larger than zero and significant • Both extreme values, zero and infinity, are excluded in a confidence interval (even a fifteen times of the standard error) • This reflects the partial adjustment mechanism, the most special character of a disequilibrium model • As we obtain the estimates of the parameters, we can trace back to find out the real or the desired supply and demand for commercial loan • And then, using the difference between the desired demand and supply, divided by supply, we can calculate the excess demand (Figure 1)

  20. Figure 1. Excess Demand for Bank Loans

  21. III. TESTING THE EXISTENCE OF PRICE ADJUSTMENT PROCESS IN TAIWAN’S COMMERCIAL LOAN MARKET B. Empirical Results • According the calculation, there are three periods of time in a situation of credit crunch. They are 1996Q1, 1997Q1 to 1998Q1, and 2007Q2 • The first one can be related to the Taiwan Strait tension in 1996 • The second credit crunch is coincident with the Asian financial crisis • The third one is related to a near-bank-run event and a tension in money market in early 2007 • The figure also shows that there exists excess supply in some periods, especially during the periods from 2001 to 2004 • This may be reflecting the so-called saving glut as Bernanke (2005) mentioned.

  22. IV. SUMMARY • To indentify the developments for bank credit allocation in Taiwan • Using a disequilibrium model to evaluate whether • an excess demand, i.e. a credit crunch, or • excess supply, i.e. a saving glut, since 1994 • Major findings • A considerable excess demand, or credit crunch, during Asian financial crisis • The main cause of this credit crunch can be contributed to the tightening in the money market because of capital outflow • On the contrary, there were some periods experiencing an excess supply from 2001 to 2004, or “saving glut” as mentioned by Bernanke (2005) • Furthermore, the saving glut was still prevailing during the periods of global financial crisis, this is probably due to • The aggressive and pre-empt policy actions taken by the financial and monetary authorities to avoid a possible meltdown in credit market

  23. IV. SUMMARY • Discussions • According to our specification of supply function, the overnight interest and bank deposits are two major exogenous variables • The authorities lowered the interest rate fast enough and adopted the policy of blanket guarantee on deposits in time had supported the banking sector to resist the crisis • Debates • Though existing debates in the model specification • For example, lack of some variables such as the ROE or the profit margin etc. • However, all the coefficients estimated in both functions are at the expected directions and are significant • Beside, the periods of excess demand/supply for bank loan are coincident with those periods of some specific economic events • These evidences have showed the disequilibrium character in Taiwan’s bank loan market successfully and are helpful in policy discussion

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