The Nexus of Monetary Policy and Shadow Banking in China 1

Transcription

1 The Nexus of Monetary Policy and Shadow Banking in China 1 Kaiji Chen a, Jue Ren b, and Tao Zha c a Emory University b Texas Christian University c FRB Atlanta, Emory University, and NBER MFM Conference 25 January Copyright c by Chen, Ren, and Zha. The views expressed herein are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Atlanta or the Federal Reserve System or the National Bureau of Economic Research. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

2 Monetary policy and the banking system Growth rate (%) M2 Bank loans Growth rate (%) M2 Deposits Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

3 Monetary policy and shadow banking 35 Annual growth rate 10.5 Shadow-banking loans outstanding 30 M2 Bank loans 10 Percent Log Share of shadow-banking loans Share of entrusted loans outstanding Percent 16 Percent Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

4 Off-balance-sheet shadow banking in China Shadow banking have three components: Trust loans Bank acceptances Entrusted loans Entrusted loans cover financing activities between nonfinancial companies. A role of the banking system: banks or nonbank financial intermediaries act as trustees or middlemen to facilitate the financing activities. The share of outstanding entrusted lending in total outstanding shadow banking lending was always high with 47% in 2009 and 49% in A unique feature of China s shadow banking and thus is a focus of our analysis. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

5 Entrusted lending by law Lenders (Firm A) Trustees Borrowers (firm B) Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

6 The balance sheet for the banking system Shadow banking products showed up on banks balance sheets in the form of ARI: Assets Cash Bank loans Account-receivable investment (ARI) ARIX is ARI excluding central bank bills. Liabilities Deposits Equity Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

7 This paper: assessing effects of China s contractionary monetary policy on its shadow banking activities Identify monetary policy rule and monetary policy shocks; Construct two bank-level micro datasets (off-balance-sheet and balance-sheet); Estimate the impacts of contractionary monetary policy on banks shadow banking activities off balance sheet as well as on the balance sheet. Quantify the effects of monetary policy on bank loans and ARIX in the banking system. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

8 Main findings In response to monetary policy tightening, nonstate banks increased shadow banking activities and brought shadow bankings products onto their balance sheets, while state banks did not. Contractionary monetary policy in China, although exerting an expected effect on bank loans, stimulated shadow loan during As a result, the effectiveness of monetary policy on the total credit in the banking system was severely hampered. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

9 Nexus between monetary policy, the banking system, and shadow banking Safe-loan regulation Bank loans Regulation on the LDR Lenders (firm A) OffBS Banks OffBS Risky borrowers (firm B) ARIX (OnBS) Deposits Regulation on capital Investors MPSs Central bank Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

10 Monetary policy rule for China g m,t = γ 0 + γ m g m,t 1 + γ π (π t 1 π ) + γ x,t ( gx,t 1 g x,t 1) + σm,t ε m,t, where ε m,t is a serially independent random shock that has a standard normal distribution, { γ x,a if g x,t 1 gx,t 1 γ x,t = 0 γ x,b if g x,t 1 gx,t 1 < 0, and σ m,t = { σ m,a σ m,b if g x,t 1 gx,t 1 0 if g x,t 1 gx,t 1 < 0. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

11 Endogenous and exogenous components of monetary policy GDP growth less target (%) CPI inflation (%) Year over year change (%) 30 Data 25 Endogenous Year over year change (%) 5 Exogenous Estimation Results Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

12 Impact of monetary policy on shadow banking activities We run the unbalanced regression log L bt = α + α g g t 1 + β ns g t 1 I (NSB b ) + β sb g t 1 I (SB b ) + Control bt + u bt. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

13 Table: Estimated results for the panel regression on total entrusted lending (1) (2) (3) Trustee Bank Bank Dependent Variable: Log of total entrusted lending Sample Sample Sample gt 1 : αg 13.12* *** (7.51) (10.14) (85.76) gt 1I (NSBb) : βnsb *** *** *** (7.70) (9.838) (13.49) gt 1I (SBb) : βsb (10.72) gt 1 Liquidity ratio 0.51 (0.90) gt 1 Return on assets 90.47*** (30.22) gt 1 Log of total assets *** (6.35) gt 1 Capital (2.59) gt 1 NPL 9.62 (14.77) gt 1 LDR (0.590) Impact of money growth on nonstate bank *** *** (4.39) (5.73) Impact of money growth on state bank 17.42* (9.29) (10.14) Observations Bank Characteristics single term controls NO NO Yes GDP, CPI controls Yes Yes Yes

14 Table: Estimated results for the unbalanced panel regression on ARIX (1) (2) (3) (4) Bank Bank Bank Bank Dependent Variable: Log of ARIX Sample Sample Sample Sample gt 1 : αg 26.56** 23.57* (12.55) (13.01) (189.8) (215.3) gt 1I (NSBb) : βnsb *** *** *** *** (15.45) (15.48) (32.83) (32.59) gt 1 Liquidity ratio (1.15) (1.35) gt 1 Return on assets 196.2** 190.7** (93.56) (87.09) gt 1 Log of total assets (16.60) (18.40) gt 1 Capital (12.47) (12.89) gt 1 NPL (24.62) (21.09) gt 1 LDR (1.37) (1.29) Impact of money growth on nonstate bank *** *** (9.85) (8.89) Impact of money growth on state bank 26.56** 23.57* (12.55) (13.01) Observations Bank Characteristics single term controls No No Yes Yes GDP, CPI controls Yes Yes Yes Yes

15 Takeaway Nonstate banks are not only passive facilitator in shadow banking activities, but also active participants in bringing these shadow banking products onto their balance sheets. Further Evidence Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

16 Intuition for nonstate banks to conduct regulatory arbitrage The fundamental asset-pricing equation: Return on ARIX Default risk premium = Return on bank loans Expected regulation costs. Monetary policy tightening increases the risk of deposit withdrawal and thus Expected regulation costs under the LDR regulation. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

17 ARIX share in state and non-state banks State Nonstate ARIX share 20 Percent Micro data. ARIX share is the ratio of ARIX holdings to the sum of ARIX holdings and bank loans on the balance sheets of the 16 publicly listed commercial banks. Based on the bank asset data from these individual banks, the data are further grouped into those from state banks and from nonstate banks. Data sources: PBC and WIND. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

18 Effectiveness of monetary policy: panel SVAR Extend the Romer and Romer (2004) methodology to a dynamic panel model. The dynamic quarterly panel model is of simultaneous-equation form as A b 0 [ Bbt A bt ] = c b + l k=1 A b k [ Bbt k A bt k ] + [ l k=0 cb k ε m,t k 0 ] + η bt, where the subscript b represents an individual bank, B bt represents bank loans made by bank b at time t, and A bt represents ARIX accumulated by bank b at time t. For k = 0,..., l c b, c b k, A b k = { c ns, ck ns, Ans k, if bank b is a nonstate bank c sb, c sb k, Asb k, if bank b is a state bank. The asset pricing equilibrium condition in our theory indicates that indicates that B bt and A bt must be simultaneously determined. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

19 Impulse responses panel SVAR 3 ARIX Percent Bank loans -0.5 Percent Total credit 1 Percent Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

20 Conclusion The interaction between China s monetary policy and regulatory policies made its monetary policies ineffective in reducing total credit in the banking system. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

21 Impact of monetary policy: on-balance-sheet activities The quarterly panel regression on ARIX: log A bt = α + α g g t 1 + β ns g t 1 I (NSB b ) + Control bt + ε bt. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

22 Understanding China monetary policy Mechanically applying the standard Taylor interest rate rule. R t = α 0 + α R R t 1 + α π (π t π ) + α x (x t x t ) + ε R,t, Estimated results with the HP filtered output x t : 1-day Repo 7-day Repo Coefficient Estimate SE p-value Estimate SE p-value α R α π α x day Chibor 7-day Chibor Coefficient Estimate SE p-value Estimate SE p-value α R α π α x Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

23 Estimated monetary policy Coefficient Estimate SE p-value γ m γ π γ x,a γ x,b σ m,a σ m,b Back Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

24 State versus nonstate banks: usual suspects (%) Description Capital adequacy ratio Excess reserve ratio LDR State banks Nonstate banks Overall Std. Err P-value Note. Each reported ratio is weighted by bank assets for The calculation is based on the balance-sheet information of all commercial banks reported by Bankscope and WIND. Capital adequacy ratios and loan-to-deposit ratios (LDRs) are downloaded directly from Bankscope and excess reserve ratios are manually collected from banks annual reports, which are downloaded from WIND. The standard error (Str. Err.) for the difference between the ratio for state banks and the ratio for nonstate banks, along with the corresponding p-value (P-value), is reported in the last two rows of the table. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

25 Data Cleaning Duplications in reporting transactions. Outstanding vs. newly originated loans. Reporting how the transaction of an entrusted loan was conducted (planned vs executed). Delays in announcing transactions. Announcement date vs. transaction date. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

26 Data verification Number of raw announcements we collect versus number published by the PBC s Financial Stability Reports. Data source: WIND Our data PBC 350 Number of raw announcements Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

27 Number of announcements ( ) By lenders and borrowers: Description NLA NBA NLABA Total Number of observations By types of trustees and types of loans: Description NBTs State banks Nonstate banks Total Non-affiliated loans Affiliated loans Total Proportions (%) by types of trustees, frequency, and volume. Description NBTs State banks Nonstate banks Total Number of transactions Loan volume Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

28 Bank attributes Descriptive statistics of individual bank characteristics from 2009 to 2015 Attribute/variable Obs Mean Std. Dev. Min Median Max LDR Size Capital Liquidity ROA NPL Note. All variables except Size (log value of total assets) are expressed in percent. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

29 Further evidence Correlation between new entrusted loans (L) channeled by banks and changes in ARIX or the share of ARIX in Description State banks p-value Nonstate banks p-value Corr ( ( ARIX, L) ) Corr ARIX ARIX+B, L Note. The symbol B stands for bank loans. Back Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

30 Effectiveness of monetary policy: theoretical framework The economy is populated by a continuum of banks whose identity is indexed by j [0, 1]. All banks are infinitely-lived and are subject to idiosyncratic withdrawal shocks to deposits with a fraction ω t of deposits withdrawn in the economy. Denote the deposits of bank j at the beginning of period t by D t (j). The deposits of bank j after the realization of an idiosyncratic withdrawal shock to deposits, therefore, is D t (j) (1 ω t ). We follow Bianchi and Bigio (2014) in modeling the shock process of ω t. The idiosyncratic shock ω t is uniformly distributed with the support of [µ (ε m,t ), 1]. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

31 Monetary policy shocks and deposit withdrawal Denote exogenous money growth by ε m,t = log Mt exog, where Mt exog represents exogenous money supply. Changes in ε m,t affect bank deposits directly through open market operations. Direct effect on deposits: ε m,t = log µ(ε m,t) (1 + µ (ε m,t ))/2, D t (j) (1 ω t ) f(ω t ) dω t dj log 1 0 D t (j) dj which leads to µ (ε m,t ) (2ε m,t + 1). Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

32 Open Market Sales Stage 0 The central bank performs open market sales by selling central bank bills (CBB 0 ) to the primary dealer, while debiting primary dealer an amount equal to CBB 0. The bank observes the open market operations initiated by the central bank and anticipates a higher risk of deposit withdrawal from the primary dealer. The bank then decides on dividend payout (DIV0 ) and a portfolio allocation among three assets: bank loans (B 0 ), risky assets (Ir 0 ), and cash (C 0 ). Stage 1 Primary dealers withdraw deposit from their banks to payoff its loan to the central bank. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

33 T-account analysis Stage 0 (before ω t is realized) central bank DPD 0 CBB 0 C 0 Bank Primary Dealer CBB 0 DPD 0 D 0 B 0 D 0 I0 r C 0 (E DIV 0 ) Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

34 T-account analysis (cont.) central bank DPD 1 = 0 CBB 1 = CBB 0 C 1 Stage 1 (after ω t is realized) Bank B 1 = B 0 D 1 I1 r = I 0 r C 1 E - DIV 0 Primary Dealers CBB 1 = CBB 0 DPD 1 = 0 D 1 Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

35 Policy Implications counterfactual panel SVAR -0.4 Bank loans Percent Bank loans equal total credit in this case Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

36 Impulse responses theory 2 Risky assets 1.5 Percent Bank loans -0.6 Percent Total credit Percent Dynamic responses to a one-standard-deviation fall of exogenous money growth in the theoretical model. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35

37 Linkage to Recent Regulatory Policy Reforms A recent series of regulatory policy changes in China bear the same spirit as our counterfactual experiments. Since the beginning of 2016, the PBC has established the so-called macro prudential assessment (MPA) system to coordinate its conduct of monetary policy. A salient feature of MPA is the requirement that the broad credit growth rate should not deviate from the targeted growth rate of M2 by more than 22%. In October 2016, the PBC further incorporated those assets financed by wealth management products into the measure of broad credit. Also, the growth rate of entrusted loan should not deviate from the targeted growth rate of M2 by more than 22%. Presentation of K. Chen Monetary Policy and Shadow Banking 25 January / 35