Loan-to-Value Caps, Bank Lending, and Spill-over to General-Purpose - - PowerPoint PPT Presentation

Loan-to-Value Caps, Bank Lending, and Spill-over to General-Purpose Loans

Selva Bahar Baziki & Tanju C ¸apacıo˘ glu

Central Bank of the Republic of Turkey Macro Financial Analysis Division Housing, Household Debt and Policy Reserve Bank of New Zealand December 12, 2017 Wellington, New Zealand

The views and opinions expressed are those of the author and do not necessarily reflect those of the Central Bank of the Republic of Turkey or its employees.

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A rise in General-Purpose Loan Usage for Residential Borrowers

After the LTV cap increases from 75% to 80% at the end of September 2016, we

• bserve a rise in the median and total GP borrowing for new home owners.

Figure 1: Median general-purpose loans (thousand TL) by residential borrowers.

What explains this increase after the policy easing?

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 2 / 52

Questions

What is the impact of the introduction of restrictive LTV caps on bank lending behavior? ◮ Introducing a cap of 75% (2011) should affect banks’ lending and risk

• ptimization.

◮ ”Unmet lending appetite” redistributed among other retail? Commercial? ◮ ”Unmet risk appetite” triggers riskier lending behavior? What is the impact of an easing change in LTV caps on non-residential borrowing by constrained home owners? ◮ Increasing the cap from 75% to 80% (2016) should affect borrowers’ optimization ◮ Lower the additional borrowing?

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Timeframe

LTV cap introduced in 2011 at 75%, and increased to 80% in 2016m9.

2011m1 2016m9 75% 80% E xpo se d Une xpo se d Co nstra ine d Bo rro we rs Unc o nstra ine d Bo rro we rs Co nstra ine d Bo r. Unc o nstra ine d Bo r.

Figure 2: Timeframe of the analysis

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Contributions

◮ Use credit register data and appraisal reports

◮ Universal coverage on housing loans at the individual-loan level ◮ In a large emerging economy

◮ Policy changes were exogenous shocks ◮ Bank Assets and Risk Preferences: Contrast exposed and non-exposed banks in terms of retail, commercial lending and risk preferences. ◮ Residential Borrowers’ Additional Loan Use: Contrast non-residential borrowing of LTV cap constrained borrowers before and after the policy change ◮ Isolating demand and supply side effects

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Analysis on Exposed/Unexposed Banks

How has the balance sheet changed?

2011m1 2016m9 75% 80%

• Sa me L
• c a tio n : Re ta il L

e nding

• Sa me F

irm : Co mme rc ia l L e nding E xpo se d Une xpo se d

Figure 3: Retail and Commercial Lending

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 6 / 52

Analysis on Exposed/Unexposed Banks

How has other lending to residential borrowers changed?

2011m1 2016m9 75% 80% Co nstra ine d Bo rro we rs Unc o nstra ine d Bo rro we rs E xpo se d Une xpo se d

Figure 4: General Purpose Loan Issuance

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Preview of Results - Lending and Risk Taking

Introduction : High exposure banks ◮ Reduce residential loan amounts, ◮ Increase GPloans... ◮ ...and they do so for new residential borrowers ”unmet lending/risk appetite” ◮ Increase commercial loans... ◮ ...esp for riskier firms ”unmet risk appetite” Expansion : Banks with average LTV closer to 75% ◮ Increase residential and GPloans esp for residential borrowers ”credit spill-over” ◮ They have lower commercial loan outcomes than banks farther away from the limit but the effect is for a short period

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 8 / 52

Analysis on Constrained/Unconstrained Residential Borrowers

How has the additional demand of residential borrowers changed?

2011m1 2016m9 75% 80% Co nstra ine d Bo rro we rs Unc o nstra ine d Bo rro we rs Co nstra ine d Bo r. Unc o nstra ine d Bo rro we rs

Figure 5: Additional leverage???

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Preview of Results - Easing

Higher LTV cap increases access to residential borrowing - should lower the need for additional funds But we see that average and total GP borrowing has increased after the easing policy LTV cap constrained buyers are taking out more non-residential loans than unconstrained : ”credit spillover”. LTV cap constrained buyers after the change are taking out more non-residential loans than before : ”flight to quality”?

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Mechanism

Demand Side Factors Introduction of a cap makes some buyers credit constrained. Some buyers are discouraged from entering the housing market altogether. Others will enter purchase contracts: ◮ Will need additional funds to cover expenses associated with a new home.

◮ These purchases usually occur after the home purchase.

◮ May still need additional funds to cover the cost of the required downpayment.

◮ These additional funds will be needed leading up to the home purchase.

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Mechanism

Supply Side Factors Introduction of a cap frees up funds Banks may chose to reallocate these funds within their loan portfolio ◮ Either by extending residential credit to constrained applicants the bank would

• therwise not be in business with,

◮ Or by extending a non-residential loan to residential loan applicants which would result in a higher leverage ratio per the value of the house, ◮ Or switching sides completely and increase commercial lending. Either path, the bank engages in riskier lending behavior.

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Previous Literature : Macroprudential Policies

Cross-country studies: Kuttner and Shim (2016), Cerruti et al. (2015), and Lim et al. (2011) Micro-level data: Jim´ enez et al. (2012) and Igan and Kang (2012) ◮ Most macroprudential policies are linked to lower credit growth ◮ Focus on macroprudential policies and house prices or financial cycles Claessens et al. (2014) find policies targeting consumers help bank balance sheets through lower leverage. ◮ But lower leverage in housing loans does not necessarily mean lower risk or leverage on the consumer side ◮ Riksbanken (2012) announced an increase in unsecured loans after the introduction of LTV cap ◮ Furthermore, riskier lending on the commercial side would exacerbate the situation.

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Previous Literature : LTV and Income Related Caps

Hallissey et al. (2014) LTV and LTI together lower credit risk on new lending ◮ Loan-level data from 3 banks ◮ Sharp increases in losses on defaulted loans for LTV > 85%. Jung and Lee (2017) find DTI better at stabilizing HP than LTV. ◮ District-level data on transactions ◮ LTV alone is subject to higher LGD Lee (2012) stable NPL on housing despite lower HP due to LTV and DSTI. J´ acome and Mitra (2015) LTV and DTI together lower credit growth (but not always HP). IMF Staff Guidelines (2014) imply that DSTI increase the effectiveness of LTV as they limit the use of unsecured loans to meet the downpayment limit.

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Data Credit Registry Data ◮ Bank-individual matched data covering 2,984,655 new housing loans that allow for identification of 88% of all housing loans.

Housing GP AverageDebt

◮ Interest rate, capital borrowed and remaining, maturity, collateral, location. LTV Data ◮ Available from 2010m1 on all housing loans with appraisal values of all purchases from

• ne dataset.

◮ Another dataset from 2011m1 with further details which we use in the easing analysis. Bank Data ◮ Monthly balance sheet and income statements for 30 banks. ◮ Private, state-owned, foreign-owned and participation banks. ◮ Real assets, loan-to-asset and deposit-to-asset ratios, capital-to-assets ratio, liquid assets to total assets, NPL ratios, ROA. Macro-level Data ◮ Monthly macroeconomic aggregates such as interest rates, IPI, CPI, REER.

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 15 / 52

Changes in Residential Loans

◮ Residential loans (county-month controls): Loanb,i,l,t =β0 + β1Aftert + β2LTVb + β3After ∗ LTVb + ζBankObsb,t−1 + γMacroObst−1 + αb + ηl + θt + εb,i,l,t. (1) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 16 / 52

Changes in Residential Loans

◮ Residential loans (county-month controls): Loanb,i,l,t =β0 + β1Aftert + β2LTVb + β3After ∗ LTVb + ζBankObsb,t−1 + γMacroObst−1 + αb + ηl + θt + εb,i,l,t. (1) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 16 / 52

Changes in Residential Loans

◮ Residential loans (county-month controls): Loanb,i,l,t =β0 + β1Aftert + β2LTVb + β3After ∗ LTVb + ζBankObsb,t−1 + γMacroObst−1 + αb + ηl + θt + εb,i,l,t. (1) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 16 / 52

Residential Loans

Residential Loans declined after the introduction, and increased after the expansion of the cap.

Table 1: Effects of LTV Regulations on the Amount of Housing Loans Window: 1-Month 2-Months 4-months 6-Months Tightening 2011m1 After*LTV

• 0.832***
• 0.813***
• 0.426***
• 0.262***

(0.188) (0.130) (0.093) (0.074) Obs 35,516 80,316 177,573 264,962 R-sq 0.240 0.236 0.232 0.232 Loosening 2016m10 After*LTV 1.187*** 0.470** 0.352*** 0.218** (0.320) (0.203) (0.133) (0.102) Obs 74,896 147,838 268,475 400,175 R-sq 0.242 0.238 0.240 0.245 Bank Obs Yes Yes Yes Yes Bank FE Yes Yes Yes Yes County*Month Yes Yes Yes Yes

Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 17 / 52

GP Loans

GP Loans are larger, especially for residential loan customers, and in particular following the increase in the cap.

Table 2: Effects of LTV Regulations on the Amount of GP Loans Policy Tightening Loosening After*LTV 1.875*** 10.739*** (0.356) (0.158) R-sq 0.372 0.997 GPL of NonResidential Borrowers After*LTV 1.884*** 8.473*** (0.373) (0.156) R-sq 0.367 0.997 GPL of Residential Borrowers After*LTV 1.833*** 11.404*** (0.100) (0.158) Obs 80,316 154,803 R-sq 0.246 0.987 Bank Observables Yes Yes Bank FE Yes Yes City*Month FE Yes Yes

Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 18 / 52

Changes in Commercial Loans

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3After ∗ LTVb + ζBankObsb,t−1 + γMacroObst−1 + αb + ηf ,t + εb,f ,t. (2) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante.

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Changes in Commercial Loans

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3After ∗ LTVb + ζBankObsb,t−1 + γMacroObst−1 + αb + ηf ,t + εb,f ,t. (2) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 19 / 52

Changes in Commercial Loans

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3After ∗ LTVb + ζBankObsb,t−1 + γMacroObst−1 + αb + ηf ,t + εb,f ,t. (2) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 19 / 52

Commercial Loans

Commercial loan growth responds more in the introduction phase, the effect in loosening dies out very fast.

Table 3: Effects of LTV Regulations on the Amount of Commercial Loans Policy Tightening Loosening Location Control After*LTV 4.448***

• 0.280*

(0.283) (0.145) Obs 76,755 154,803 R-sq 0.873 0.967 City*Month FE Yes Yes Firm Control After*LTV 0.150***

• 0.049***

(0.049) (0.010) Obs 206,935 397,820 R-sq 0.679 0.739 Bank Observables Yes Yes Bank FE Yes Yes Firm*Month FE Yes Yes

Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 20 / 52

Changes in Commercial Loan Riskiness

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3Ratingb,f ,t + β4After ∗ LTVb + β5After ∗ Ratingb,f ,t + β6LTV ∗ Ratingb,f ,t + β7After ∗ LTV ∗ Ratingb,f ,t + ζBankObsb,t−1 + γMacroObst−1 + αb,t + ηf + εb,f ,t. (3) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante. ◮ Rating shows riskiness for firms ranked 1-4, and non-riskyness for banks ranked 5,6 by banks.

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Changes in Commercial Loan Riskiness

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3Ratingb,f ,t + β4After ∗ LTVb + β5After ∗ Ratingb,f ,t + β6LTV ∗ Ratingb,f ,t + β7After ∗ LTV ∗ Ratingb,f ,t + ζBankObsb,t−1 + γMacroObst−1 + αb,t + ηf + εb,f ,t. (3) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante. ◮ Rating shows riskiness for firms ranked 1-4, and non-riskyness for banks ranked 5,6 by banks.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 21 / 52

Changes in Commercial Loan Riskiness

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3Ratingb,f ,t + β4After ∗ LTVb + β5After ∗ Ratingb,f ,t + β6LTV ∗ Ratingb,f ,t + β7After ∗ LTV ∗ Ratingb,f ,t + ζBankObsb,t−1 + γMacroObst−1 + αb,t + ηf + εb,f ,t. (3) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante. ◮ Rating shows riskiness for firms ranked 1-4, and non-riskyness for banks ranked 5,6 by banks.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 21 / 52

Changes in Commercial Loan Riskiness

◮ Newly issued commercial loans (same firm borrowing from two banks): Loanb,f ,t =β0 + β1Aftert + β2LTVb + β3Ratingb,f ,t + β4After ∗ LTVb + β5After ∗ Ratingb,f ,t + β6LTV ∗ Ratingb,f ,t + β7After ∗ LTV ∗ Ratingb,f ,t + ζBankObsb,t−1 + γMacroObst−1 + αb,t + ηf + εb,f ,t. (3) ◮ BankObs are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets taken ex-ante. ◮ MacroObs are macroeconomic observables: interest rates, IPI, CPI, REER taken ex-ante. ◮ Rating shows riskiness for firms ranked 1-4, and non-riskyness for banks ranked 5,6 by banks.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 21 / 52

Risky Commercial Loans

Commercial loan growth in the initial phase is mostly in riskier firms.

Table 4: Effects of LTV Regulations on the Riskiness of Commercial Loans

Policy Tightening Loosening Rating

• 0.033***

0.015 (0.004) (0.010) Rate*LTV 0.139***

• 0.076***

(0.013) (0.010) After*LTV*Rate

• 0.053***

0.003 (0.009) (0.002) Obs 360,504 445,578 R-sq 0.670 0.746 Firm FE Yes Yes Bank*Month FE Yes Yes

Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 22 / 52

Recall: Analysis on Constrained/Unconstrained Residential Borrowers

How has the additional demand of residential borrowers changed

2011m1 2016m9 75% 80% Co nstra ine d Bo rro we rs Unc o nstra ine d Bo rro we rs Co nstra ine d Bo r. Unc o nstra ine d Bo rro we rs

Figure 6: Additional leverage???

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 23 / 52

LTV Ratio

◮ From the appraisal reports, we calculate the LTV ratio for each residential loan at time t for each borrower i using the formula: LTVit = OriginalHousingLoanit ExpertEvaluationit . (4) ◮ Where the appraisal report is done by a certified agency by the BRSA or the Capital Markets Board of Turkey.

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LTV ratios before and after

LTV cap increase from 75% to 80% shifts LTV ratios in favor of higher leverage.

Figure 7: LTV histograms by loan amount.

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Pseudo LTV Ratio

◮ Purchasing a home is a long term investment, and requires some planning. Take the GP borrowing in the months leading up to the house purchase to be residential-related. ◮ Define a new LTV ratio called Pseudo LTV, to calculate the effective leverage of the housing loan: PseudoLTVit = OriginalHousingLoanit + GPloansit + GPloansit−1 ExpertEvaluationit . (5)

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 26 / 52

LTV to Pseudo LTV

The month of the initial LTV introduction shows a fuzzy implementation and many above the official cutoff. Still, possible to see more people at or around the cutoff have higher Pseudo LTV.

20 40 60 80 100 Gross Loan-to-Value Ratio 20 40 60 80 100 Loan-to-Value Ratio

Figure 8: Mapping of individual LTV to Pseudo LTV - January 2011

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 27 / 52

LTV to Pseudo LTV around the regime change

A sharper implementation and a larger concentration of high Pseudo LTV around the cutoffs.

20 40 60 80 100 Gross Loan-to-Value Ratio 20 40 60 80 100 Loan-to-Value Ratio

Figure 9: Mapping of individual LTV to Pseudo LTV - September and October 2016

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 28 / 52

LTV to Pseudo LTV last data

A sharper implementation and a larger concentration of high Pseudo LTV with longer practice.

Figure 10: Mapping of individual LTV to Pseudo LTV - April 2017

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 29 / 52

Methodology - Diff in Diff Strategy

◮ For bank b, individual-credit i over the policy change: GeneralPurposeloansibt =αi + ωAftert + θLTVconstit + βLTVconstit ∗ Aftert + ζPersonObsit + γBankObsbt + ηMacroObst + εibt. (6)

◮ ζPersonObsit are person observables : in-house credit rating, number of credit cards, and other outstanding debt. ◮ γBankObsbt are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets. ◮ ηMacroObst are macroeconomic observables: interest rates, IPI, CPI, REER.

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 30 / 52

Methodology - Diff in Diff Strategy

◮ For bank b, individual-credit i over the policy change: GeneralPurposeloansibt =αi + ωAftert + θLTVconstit + βLTVconstit ∗ Aftert + ζPersonObsit + γBankObsbt + ηMacroObst + εibt. (6)

◮ ζPersonObsit are person observables : in-house credit rating, number of credit cards, and other outstanding debt. ◮ γBankObsbt are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets. ◮ ηMacroObst are macroeconomic observables: interest rates, IPI, CPI, REER.

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 30 / 52

Methodology - Diff in Diff Strategy

◮ For bank b, individual-credit i over the policy change: GeneralPurposeloansibt =αi + ωAftert + θLTVconstit + βLTVconstit ∗ Aftert + ζPersonObsit + γBankObsbt + ηMacroObst + εibt. (6)

◮ ζPersonObsit are person observables : in-house credit rating, number of credit cards, and other outstanding debt. ◮ γBankObsbt are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets. ◮ ηMacroObst are macroeconomic observables: interest rates, IPI, CPI, REER.

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 30 / 52

Methodology - Diff in Diff Strategy

◮ For bank b, individual-credit i over the policy change: GeneralPurposeloansibt =αi + ωAftert + θLTVconstit + βLTVconstit ∗ Aftert + ζPersonObsit + γBankObsbt + ηMacroObst + εibt. (6)

◮ ζPersonObsit are person observables : in-house credit rating, number of credit cards, and other outstanding debt. ◮ γBankObsbt are bank observables : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets. ◮ ηMacroObst are macroeconomic observables: interest rates, IPI, CPI, REER.

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 30 / 52

Results - DID Table 5: Differences in Differences Estimates

70 vs 75 71 vs 76 72 vs 77 73 vs 78 74 vs 79 75 vs 80 Baseline After 0.318 1.143** 1.150** 1.147** 1.077** 1.028** (0.528) (0.500) (0.497) (0.493) (0.489) (0.479) LTVconstr 5.225*** 5.645*** 6.051*** 6.617*** 7.355*** 11.657*** (0.564) (0.588) (0.615) (0.657) (0.721) (1.090) LTVconstr*After 2.280** 4.886*** 5.224*** 5.346*** 6.021*** 3.325** (0.974) (1.057) (1.103) (1.148) (1.246) (1.547) Larger Sample After 0.293 0.836 0.865 0.894 0.857 0.891 (0.648) (0.599) (0.592) (0.584) (0.575) (0.554) LTVconstr 3.894*** 4.193*** 4.571*** 5.094*** 5.742*** 9.493*** (0.532) (0.539) (0.549) (0.571) (0.606) (0.849) LTVconstr*After 1.501* 3.784*** 4.030*** 4.067*** 4.605*** 2.186* (0.895) (0.886) (0.909) (0.928) (0.983) (1.175)

Alternate IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 31 / 52

Results - DID Table 5: Differences in Differences Estimates

70 vs 75 71 vs 76 72 vs 77 73 vs 78 74 vs 79 75 vs 80 Baseline After 0.318 1.143** 1.150** 1.147** 1.077** 1.028** (0.528) (0.500) (0.497) (0.493) (0.489) (0.479) LTVconstr 5.225*** 5.645*** 6.051*** 6.617*** 7.355*** 11.657*** (0.564) (0.588) (0.615) (0.657) (0.721) (1.090) LTVconstr*After 2.280** 4.886*** 5.224*** 5.346*** 6.021*** 3.325** (0.974) (1.057) (1.103) (1.148) (1.246) (1.547) Larger Sample After 0.293 0.836 0.865 0.894 0.857 0.891 (0.648) (0.599) (0.592) (0.584) (0.575) (0.554) LTVconstr 3.894*** 4.193*** 4.571*** 5.094*** 5.742*** 9.493*** (0.532) (0.539) (0.549) (0.571) (0.606) (0.849) LTVconstr*After 1.501* 3.784*** 4.030*** 4.067*** 4.605*** 2.186* (0.895) (0.886) (0.909) (0.928) (0.983) (1.175)

Alternate IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 31 / 52

Results - DID Different time brackets Table 6: Differences in Differences Estimates for various time brackets and LTV cutoffs

70 vs 75 71 vs 76 72 vs 77 73 vs 78 74 vs 79 75 vs 80 4 months: August 2016 to November 2016 After 0.226 1.136** 1.135** 1.127** 1.059** 0.922* (0.523) (0.517) (0.516) (0.514) (0.512) (0.506) LTVconstr 4.973*** 5.325*** 5.674*** 6.188*** 6.876*** 10.508***

• 0.343
• 0.358
• 0.378
• 0.405
• 0.447
• 0.67

LTVconstr*After 2.399*** 3.967*** 4.221*** 4.315*** 4.913*** 2.845***

• 0.592
• 0.643
• 0.673
• 0.706
• 0.767
• 0.953

Obs 92632 92632 92632 92632 92632 92632 6 months: July 2016 to December 2016 After 0.208 1.263** 1.261** 1.250** 1.190** 1.057*

• 0.566
• 0.564
• 0.564
• 0.563
• 0.561
• 0.556

LTVconstr 5.435*** 5.822*** 6.210*** 6.766*** 7.538*** 11.559***

• 0.55
• 0.584
• 0.623
• 0.676
• 0.751
• 1.149

LTVconstr*After 2.601*** 3.774*** 4.041*** 4.126*** 4.640*** 2.217*

• 0.653
• 0.702
• 0.745
• 0.798
• 0.881
• 1.251

Obs 133130 133130 133130 133130 133130 133130 8 months: June 2016 to January 2017 After

• 0.123

0.577 0.595 0.606 0.619 0.6

• 0.681
• 0.664
• 0.663
• 0.662
• 0.66
• 0.657

LTVconstr 5.069*** 5.438*** 5.814*** 6.345*** 7.080*** 10.967***

• 0.398
• 0.422
• 0.45
• 0.488
• 0.541
• 0.833

LTVconstr*After 3.674*** 4.753*** 5.118*** 5.321*** 5.914*** 3.744***

• 0.566
• 0.624
• 0.665
• 0.712
• 0.789
• 1.049

Obs 177793 177793 177793 177793 177793 177793

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 32 / 52

Results - DID Different time brackets Table 6: Differences in Differences Estimates for various time brackets and LTV cutoffs

70 vs 75 71 vs 76 72 vs 77 73 vs 78 74 vs 79 75 vs 80 4 months: August 2016 to November 2016 After 0.226 1.136** 1.135** 1.127** 1.059** 0.922* (0.523) (0.517) (0.516) (0.514) (0.512) (0.506) LTVconstr 4.973*** 5.325*** 5.674*** 6.188*** 6.876*** 10.508***

• 0.343
• 0.358
• 0.378
• 0.405
• 0.447
• 0.67

LTVconstr*After 2.399*** 3.967*** 4.221*** 4.315*** 4.913*** 2.845***

• 0.592
• 0.643
• 0.673
• 0.706
• 0.767
• 0.953

Obs 92632 92632 92632 92632 92632 92632 6 months: July 2016 to December 2016 After 0.208 1.263** 1.261** 1.250** 1.190** 1.057*

• 0.566
• 0.564
• 0.564
• 0.563
• 0.561
• 0.556

LTVconstr 5.435*** 5.822*** 6.210*** 6.766*** 7.538*** 11.559***

• 0.55
• 0.584
• 0.623
• 0.676
• 0.751
• 1.149

LTVconstr*After 2.601*** 3.774*** 4.041*** 4.126*** 4.640*** 2.217*

• 0.653
• 0.702
• 0.745
• 0.798
• 0.881
• 1.251

Obs 133130 133130 133130 133130 133130 133130 8 months: June 2016 to January 2017 After

• 0.123

0.577 0.595 0.606 0.619 0.6

• 0.681
• 0.664
• 0.663
• 0.662
• 0.66
• 0.657

LTVconstr 5.069*** 5.438*** 5.814*** 6.345*** 7.080*** 10.967***

• 0.398
• 0.422
• 0.45
• 0.488
• 0.541
• 0.833

LTVconstr*After 3.674*** 4.753*** 5.118*** 5.321*** 5.914*** 3.744***

• 0.566
• 0.624
• 0.665
• 0.712
• 0.789
• 1.049

Obs 177793 177793 177793 177793 177793 177793

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 32 / 52

Results - DID Different time brackets Table 6: Differences in Differences Estimates for various time brackets and LTV cutoffs

70 vs 75 71 vs 76 72 vs 77 73 vs 78 74 vs 79 75 vs 80 4 months: August 2016 to November 2016 After 0.226 1.136** 1.135** 1.127** 1.059** 0.922* (0.523) (0.517) (0.516) (0.514) (0.512) (0.506) LTVconstr 4.973*** 5.325*** 5.674*** 6.188*** 6.876*** 10.508***

• 0.343
• 0.358
• 0.378
• 0.405
• 0.447
• 0.67

LTVconstr*After 2.399*** 3.967*** 4.221*** 4.315*** 4.913*** 2.845***

• 0.592
• 0.643
• 0.673
• 0.706
• 0.767
• 0.953

Obs 92632 92632 92632 92632 92632 92632 6 months: July 2016 to December 2016 After 0.208 1.263** 1.261** 1.250** 1.190** 1.057*

• 0.566
• 0.564
• 0.564
• 0.563
• 0.561
• 0.556

LTVconstr 5.435*** 5.822*** 6.210*** 6.766*** 7.538*** 11.559***

• 0.55
• 0.584
• 0.623
• 0.676
• 0.751
• 1.149

LTVconstr*After 2.601*** 3.774*** 4.041*** 4.126*** 4.640*** 2.217*

• 0.653
• 0.702
• 0.745
• 0.798
• 0.881
• 1.251

Obs 133130 133130 133130 133130 133130 133130 8 months: June 2016 to January 2017 After

• 0.123

0.577 0.595 0.606 0.619 0.6

• 0.681
• 0.664
• 0.663
• 0.662
• 0.66
• 0.657

LTVconstr 5.069*** 5.438*** 5.814*** 6.345*** 7.080*** 10.967***

• 0.398
• 0.422
• 0.45
• 0.488
• 0.541
• 0.833

LTVconstr*After 3.674*** 4.753*** 5.118*** 5.321*** 5.914*** 3.744***

• 0.566
• 0.624
• 0.665
• 0.712
• 0.789
• 1.049

Obs 177793 177793 177793 177793 177793 177793

IntRates Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 32 / 52

GP Demand 2011

Constrained borrowers demand more GP

Table 7: LTV introduction and the effect on GP demand of the constrained Window: 1-Month 2-Months 4-months 6-Months 73 vs 78 LTVconst 0.496*** 0.491** 1.463** 1.157*** (0.181) (0.198) (0.656) (0.432) Obs 7,211 15,309 35,199 54,307 74 vs 79 LTVconst 0.747*** 0.709*** 1.734** 1.364*** (0.189) (0.202) (0.734) (0.484) Obs 7,211 15,309 35,199 54,307 75 vs 80 LTVconst 0.785*** 0.744*** 1.870* 1.464** (0.237) (0.226) (1.085) (0.712) Obs 7,211 15,309 35,199 54,307 Individual Observables Yes Yes Yes Yes Bank Observables Yes Yes Yes Yes Bank*Month FE Yes Yes Yes Yes

Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 33 / 52

GP Demand - 2016

Constrained borrowers demand more GP after the loosening.

Table 8: LTV cap increase and the effect on GP demand of the constrained Window: 1-Month 2-Months 4-months 6-Months 73 vs 78 LTVconst 5.458*** 5.593*** 6.006*** 5.886*** (0.634) (0.401) (0.499) (0.355) After*LTVconst 4.739*** 4.135*** 5.360*** 5.126*** (1.471) (0.849) (0.805) (0.607) 74 vs 79 LTVconst 5.953*** 6.202*** 6.718*** 6.597*** (0.697) (0.445) (0.558) (0.396) After*LTVconst 5.646*** 4.828*** 6.009*** 5.743*** (1.559) (0.911) (0.891) (0.673) 75 vs 80 LTVconst 9.089*** 9.476*** 10.529*** 10.269*** (1.039) (0.679) (0.875) (0.619) After*LTVconst 4.111** 3.140*** 3.964*** 3.782*** (1.756) (1.089) (1.171) (0.871) Obs 41,292 88,448 173,609 262,691 Individual Observables Yes Yes Yes Yes Bank*Month FE Yes Yes Yes Yes

Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 34 / 52

Summary of Results - Introduction

Introduction of the LTV cap ◮ Reduces residential loans in favor of higher uncollateralized lending to new residential borowers, ◮ And higher riskier lending on the commercial side. ”unmet lending/risk appetite” ◮ Results confirm that there is ”spillover” from housing to non-residential loans, increasingly so for the exposed banks.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 35 / 52

Summary of Results - Easing

◮ Being constrained by the LTV ratio cap increases GP loans by 5 to 6 thousand TL. ◮ The added premium of being constrained by the LTV ratio cap after the regime change is an additional 4 to 6 thousand TL.

◮ per-capita GP loans are at 12 thousand TL. ◮ Surprising result since a larger LTV ratio cap should reduce the need for additional loans.

◮ Results confirm that there is ”spillover” from housing to non-residential loans, increasingly so for the credit constrained. ◮ And that as the cap is increased, borrowers are switching to more expensive homes, increasing demand for credit.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 36 / 52

Robustness

Results are robust to different definitions of LTV, constraint cutoffs, and brackets. LTV here can take on one of three values:

GPlong

◮ Share of weighted LTV over total lending

LTVb,i,t∗Amountb,i,t TotalAmountb,i,t

◮ Share of lending above cutoff over total lending

ExposureAmountb,i,t TotalAmountb,i,t

◮ Quantile Approach : compare top/bottom 5pctl Where the appraisal report is done by a certified agency by the BRSA or the Capital Markets Board of Turkey. General Purpose Use by Home Owners:

GPLlong

Commercial Credit Use:

CommercialLong

Commercial Credit Demand 2011:

GPdemandL11

Commercial Credit Demand 2016:

GPdemandL16

Pooled OLS of entire period :

OLS Method Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 37 / 52

Conclusion

◮ With LTV, credit constrained individuals have a higher likelihood to top off their residential loans with other means of borrowing. ◮ LTV may also result in riskier bank balance sheets through increased riskier commercial lending (2011) or uncollateralized loans (2016). ◮ LTV caps alone do not provide sufficient deterrence from residential leverage for households. ◮ Implications for credit availability, transmission, asset decomposition, and optimal risk weight design. ◮ Best practice may have to introduce income related limits.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 38 / 52

Appendix

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 39 / 52

Data - Average Debt Table 9: Average Current Debt by Loan Type of Housing Loan Customers 2011m1-2017m4

Average Amount of Debt (Thousand TL) Total Debt General Purpose Housing Vehicle Credit No of Total Debt w/o Housing Loans Loans Loans Cards Banks 04.16 21.27 17.20 22.12 125.35 37.69 8.10 1.49 05.16 21.62 17.27 22.14 127.84 37.81 8.36 1.49 06.16 22.45 17.53 22.40 130.66 38.25 8.36 1.51 07.16 20.43 17.45 22.29 124.66 38.17 8.41 1.50 08.16 21.12 17.44 22.15 120.89 38.27 8.59 1.49 09.16 24.37 19.59 22.58 128.23 38.42 8.78 1.46 10.16 25.60 19.94 23.14 134.96 38.65 8.77 1.46 11.16 26.84 20.36 23.71 141.79 39.52 8.82 1.47 12.16 26.92 20.76 24.25 144.56 40.08 9.01 1.49 01.17 25.64 20.65 24.17 142.68 40.30 8.85 1.51 02.17 25.82 20.70 24.26 148.70 40.43 8.76 1.47 03.17 28.14 20.89 24.58 167.17 40.84 8.93 1.47

Data Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 40 / 52

Results - DID with Cluster Table 10: Differences in Differences Estimates

(1) (2) (3) (4) (5) (6) 70 vs 75 71 vs 76 72 vs 77 73 vs 78 74 vs 79 75 vs 80 Baseline Clustered After 0.318 1.143* 1.150** 1.147** 1.077** 1.028* (0.466) (0.559) (0.546) (0.527) (0.504) (0.490) LTVconstr 5.225** 5.645** 6.051** 6.617** 7.355** 11.657** (2.208) (2.356) (2.497) (2.676) (2.925) (4.479) LTVconstr*After 2.280* 4.886* 5.224* 5.346* 6.021* 3.325 (1.144) (2.470) (2.586) (2.684) (2.921) (2.109) Larger Sample Clustered After 0.293 0.836 0.865 0.894* 0.857* 0.891* (0.440) (0.510) (0.509) (0.495) (0.476) (0.489) LTVconstr 3.894* 4.193* 4.571* 5.094** 5.742** 9.493** (1.914) (2.059) (2.190) (2.350) (2.561) (3.988) LTVconstr*After 1.501 3.784* 4.030* 4.067* 4.605* 2.186 (1.455) (1.900) (2.022) (2.095) (2.306) (2.142)

Back Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 41 / 52

Interest Rates and Spread 2 4 6 8 10 12 14 16 18 20 2 4 6 8 10 12 14 16 18 20 01.10 05.10 09.10 01.11 05.11 09.11 01.12 05.12 09.12 01.13 05.13 09.13 01.14 05.14 09.14 01.15 05.15 09.15 01.16 05.16 09.16 01.17 05.17 Spread btw General P. And Housing Loans General‐Purpose Vehicle Housing Figure 11: Interest Rates and Spread Between Housing and GP Loans.

Data LTVg DID DIDresults DIDtime Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 42 / 52

Data - Housing Loans Table 11: Summary Statistics on New Housing Loans

Date Total Loans Average Loans # of Credit # of People 04.16 3,838,708 114.61 33,495 33,230 05.16 4,350,762 115.79 37,576 37,216 06.16 4,390,482 118.07 37,184 36,844 07.16 2,838,803 115.67 24,542 24,307 08.16 4,238,492 113.40 37,378 37,061 09.16 5,167,644 118.30 43,682 43,360 10.16 6,132,442 122.43 50,089 49,671 11.16 6,386,490 125.34 50,953 50,491 12.16 6,328,205 126.49 50,029 49,524 01.17 5,073,685 129.89 39,061 38,712 02.17 5,339,186 131.04 40,745 40,304 03.17 7,074,793 134.90 52,443 52,010

Data Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 43 / 52

Data - Housing Loans Table 12: Summary Statistics on General Purpose Loans of Housing Borrowers

General Purpose Loans (Thousand TL) Same Month 1 Month Before 1 Month After 2 & 3 Months Before 2 & 3 Months After Date Amount Number Amount Number Amount Number Amount Number Amount Number 04.16 44,304 1,272 7,272 165 4,962 437 8,161 381 18,081 1,753 05.16 65,253 1,760 4,867 190 11,955 785 10,846 445 17,171 1,934 06.16 68,044 1,832 5,616 186 5,698 567 13,334 453 17,280 2,010 07.16 55,473 1,055 4,688 171 5,653 432 5,786 266 13,595 1,185 08.16 48,830 1,291 3,106 153 6,109 457 10,438 436 21,270 1,530 09.16 65,801 1,385 5,251 209 9,264 562 12,001 569 24,761 1,564 10.16 88,281 1,852 6,013 251 13,227 657 11,294 535 23,416 1,677 11.16 99,374 2,232 10,036 336 17,251 830 14,235 666 27,050 1,821 12.16 101,734 2,335 10,949 344 10,078 660 15,138 651 27,901 1,938 01.17 98,759 1,807 9,934 293 9,749 621 16,710 679 22,666 1,881 02.17 74,834 1,882 6,846 251 9,546 599 15,813 535 8,154 533 03.17 106,362 2,475 8,412 323 10,822 791 18,848 672 Data Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 44 / 52

Residential Loans

Residential Loans declined after the introduction, and increased after the expansion of the cap.

Table 13: Effects of LTV Regulations on the Amount of Housing Loans

Policy Tightening (2011m1) Loosening (2016m10) Window 1-Month 2-Months 4-Months 6-Months 1-Month 2-Months 4-Months 6-Months After*LTV

• 0.832***
• 0.813***
• 0.426***
• 0.262***

1.187*** 0.470** 0.352*** 0.218** (0.188) (0.130) (0.093) (0.074) (0.320) (0.203) (0.133) (0.102) Obs 35,516 80,316 177,573 264,962 74,896 147,838 268,475 400,175 R-sq 0.240 0.236 0.232 0.232 0.242 0.238 0.240 0.245 After*Exposure

• 0.144***
• 0.101***
• 0.049***
• 0.027*

0.236*** 0.106** 0.144*** 0.150*** (0.040) (0.026) (0.018) (0.015) (0.078) (0.053) (0.045) (0.038) Obs 35,508 80,308 177,559 264,949 74,896 147,771 268,337 399,978 R-sq 0.239 0.236 0.232 0.232 0.242 0.237 0.240 0.244 After*Quantile

• 0.056**
• 0.059***
• 0.045***
• 0.032***

0.039*** 0.049*** 0.064*** 0.070*** (0.024) (0.015) (0.011) (0.009) (0.009) (0.006) (0.005) (0.004) Obs 16,795 36,336 54,869 85,663 68,787 135,133 248,843 371,641 R-sq 0.274 0.268 0.249 0.245 0.247 0.242 0.244 0.247 Bank Obs Yes Yes Yes Yes Yes Yes Yes Yes Bank FE Yes Yes Yes Yes Yes Yes Yes Yes County*Month Yes Yes Yes Yes Yes Yes Yes Yes GPshort Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 45 / 52

GP Loans

GP Loans are larger, especially for residential loan customers, and in particular following the increase in the cap.

Table 14: Effects of LTV Regulations on the Amount of GP Loans

Policy Tightening (2011m1) Loosening (2016m10) Window 1-Month 2-Months 4-Months 6-Months 1-Month 2-Months 4-Months 6-Months After*LTV 1.685*** 1.875*** 1.659*** 0.940*** 6.872*** 10.739*** 5.396*** 9.554*** (0.471) (0.356) (0.257) (0.205) (0.139) (0.158) (0.206) (0.157) R-sq 0.399 0.372 0.319 0.316 0.999 0.997 0.980 0.978 GPL of NonResidential Borrowers After*LTV 1.728*** 1.884*** 0.589** 0.188 3.633*** 8.473*** 4.694*** 8.403*** (0.605) (0.373) (0.261) (0.209) (0.123) (0.156) (0.216) (0.167) R-sq 0.406 0.367 0.322 0.316 0.999 0.997 0.978 0.975 GPL of Residential Borrowers After*LTV 4.182*** 1.833*** 1.968*** 1.854*** 10.879*** 11.404*** 11.459*** 11.595*** (0.208) (0.100) (0.087) (0.071) (0.236) (0.158) (0.137) (0.117) R-sq 0.298 0.246 0.240 0.257 0.992 0.987 0.964 0.959 Obs 35,516 80,316 177,573 264,962 78,617 154,803 281,779 419,925 Bank Obs Yes Yes Yes Yes Yes Yes Yes Yes Bank FE Yes Yes Yes Yes Yes Yes Yes Yes City*Month Yes Yes Yes Yes Yes Yes Yes Yes GPLshort Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 46 / 52

Commercial Loans

Commercial loan growth responds more in the introduction phase, the effect in loosening dies out very fast.

Table 15: Effects of LTV Regulations on the Amount of Commercial Loans

Policy Tightening (2011m1) Loosening (2016m10) Window 1-Month 2-Months 4-Months 6-Months 1-Month 2-Months 4-Months 6-Months After*LTV 8.796*** 4.448*** 0.659*** 1.922***

• 4.560***
• 0.280*

0.125 1.383*** (0.479) (0.283) (0.180) (0.148) (0.104) (0.145) (0.116) (0.115) Obs 33,742 76,755 169,285 251,782 78,617 154,803 281,486 375,597 R-sq 0.899 0.873 0.863 0.859 0.977 0.967 0.967 0.965 Bank Observables Yes Yes Yes Yes Yes Yes Yes Yes Bank FE Yes Yes Yes Yes Yes Yes Yes Yes City*Month Yes Yes Yes Yes Yes Yes Yes Yes Credit Registry Data After*LTV 0.140** 0.150*** 0.135*** 0.058*

• 0.041***
• 0.049***

0.016 0.029*** (0.060) (0.049) (0.038) (0.030) (0.016) (0.010) (0.011) (0.009) Obs 115,759 206,935 389,945 635,786 161,186 397,820 655,631 893,937 R-sq 0.682 0.679 0.682 0.676 0.742 0.739 0.744 0.740 Bank Observables Yes Yes Yes Yes Yes Yes Yes Yes Bank FE Yes Yes Yes Yes Yes Yes Yes Yes Firm*Month Yes Yes Yes Yes Yes Yes Yes Yes CommercialLong Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 47 / 52

Risky Commercial Loans

Commercial loan growth in the initial phase is mostly in riskier firms.

Table 16: Effects of LTV Regulations on the Amount of Risky Commercial Lending

Policy Tightening (2011m1) Loosening (2016m10) Window 1-Month 2-Months 4-Months 6-Months 1-Month 2-Months 4-Months 6-Months Rating

• 0.023***
• 0.033***
• 0.039***
• 0.038***

0.007 0.015 0.003

• 0.002

(0.006) (0.004) (0.003) (0.002) (0.016) (0.010) (0.006) (0.004) Rate*LTV 0.104*** 0.139*** 0.162*** 0.155***

• 0.057***
• 0.076***
• 0.066***
• 0.064***

(0.019) (0.013) (0.010) (0.007) (0.017) (0.010) (0.006) (0.004) After*LTV*Rate

• 0.042***
• 0.053***
• 0.055***
• 0.054***

0.007* 0.003

• 0.003*
• 0.005***

(0.013) (0.009) (0.006) (0.005) (0.004) (0.002) (0.002) (0.001) Obs 159,592 360,504 783,051 1,298,736 136,032 445,578 1,234,823 1,555,586 R-sq 0.699 0.670 0.645 0.627 0.795 0.746 0.711 0.737 Firm FE Yes Yes Yes Yes Yes Yes Yes Yes Bank*Month Yes Yes Yes Yes Yes Yes Yes Yes RiskyShort Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 48 / 52

GP Demand

Constrained borrowers demand more GP

Table 17: LTV introduction and the effect on GP demand of the constrained

(1) (2) (3) (4) (6) (8) (10) Window: 1-Months 2-Months 4-Months 6-Months 70 vs 75 LTVconst 0.596*** 0.533*** 0.458** 0.215 0.157 0.923* 0.711** (0.190) (0.182) (0.222) (0.177) (0.193) (0.534) (0.355) 71 vs 76 LTVconst 0.698*** 0.632*** 0.573** 0.322* 0.273 1.088* 0.857** (0.193) (0.186) (0.225) (0.176) (0.196) (0.563) (0.373) 72 vs 77 LTVconst 0.759*** 0.693*** 0.658*** 0.393** 0.341* 1.224** 0.962** (0.198) (0.190) (0.231) (0.177) (0.201) (0.602) (0.399) 73 vs 78 LTVconst 0.868*** 0.802*** 0.770*** 0.496*** 0.491** 1.463** 1.157*** (0.207) (0.198) (0.237) (0.181) (0.198) (0.656) (0.432) 74 vs 79 LTVconst 1.094*** 1.026*** 1.044*** 0.747*** 0.709*** 1.734** 1.364*** (0.223) (0.213) (0.256) (0.189) (0.202) (0.734) (0.484) 75 vs 80 LTVconst 1.184*** 1.122*** 1.208*** 0.785*** 0.744*** 1.870* 1.464** (0.291) (0.277) (0.339) (0.237) (0.226) (1.085) (0.712) Obs 8,481 8,480 7,213 7,211 15,309 35,199 54,307 Individual Obs

• Yes

Yes Yes Yes Yes Yes Bank Obs

• Yes

Yes Yes Yes Yes Macro Obs

• Yes

n/p n/p n/p n/p Bank FE Yes Yes Yes

• Time (Year) FE

Yes Yes Yes

• Bank*Month
• Yes

Yes Yes Yes GPdemandS Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 49 / 52

GP Demand - 2016

Constrained borrowers demand more GP after the loosening.

Window: 1-Month 2-Months 4-Months 6-Months 70 vs 75 LTVconst 4.460*** 4.460*** 4.262*** 4.522*** 4.699*** 4.756*** 4.577*** 4.734*** (0.530) (0.530) (0.312) (0.332) (0.430) (0.399) (0.301) (0.286) After*LTVconst 1.895 1.895 1.949*** 2.222*** 3.031*** 3.631*** 3.129*** 3.494*** (1.350) (1.350) (0.707) (0.762) (0.650) (0.658) (0.483) (0.492) 71 vs 76 LTVconst 4.483*** 4.753*** 4.561*** 4.825*** 5.069*** 5.121*** 4.932*** 5.088*** (0.521) (0.558) (0.330) (0.350) (0.457) (0.427) (0.320) (0.305) After*LTVconst 3.526** 3.957*** 3.253*** 3.672*** 3.993*** 4.719*** 4.024*** 4.479*** (1.388) (1.500) (0.765) (0.824) (0.705) (0.717) (0.527) (0.539) 72 vs 77 LTVconst 4.788*** 5.056*** 4.886*** 5.146*** 5.447*** 5.489*** 5.282*** 5.432*** (0.551) (0.589) (0.351) (0.372) (0.488) (0.458) (0.341) (0.327) After*LTVconst 3.949*** 4.408*** 3.497*** 3.946*** 4.342*** 5.110*** 4.365*** 4.849*** (1.407) (1.513) (0.788) (0.844) (0.748) (0.760) (0.559) (0.572) 73 vs 78 LTVconst 5.184*** 5.458*** 5.323*** 5.593*** 5.678*** 6.006*** 5.552*** 5.886*** (0.596) (0.634) (0.379) (0.401) (0.476) (0.499) (0.337) (0.355) After*LTVconst 4.241*** 4.739*** 3.668*** 4.135*** 4.850*** 5.360*** 4.804*** 5.126*** (1.371) (1.471) (0.795) (0.849) (0.754) (0.805) (0.572) (0.607) 74 vs 79 LTVconst 5.698*** 5.953*** 5.938*** 6.202*** 6.382*** 6.718*** 6.253*** 6.597*** (0.658) (0.697) (0.422) (0.445) (0.534) (0.558) (0.377) (0.396) After*LTVconst 5.082*** 5.646*** 4.334*** 4.828*** 5.478*** 6.009*** 5.410*** 5.743*** (1.463) (1.559) (0.856) (0.911) (0.839) (0.891) (0.637) (0.673) 75 vs 80 LTVconst 8.752*** 9.089*** 9.096*** 9.476*** 10.056*** 10.529*** 9.773*** 10.269*** (0.984) (1.039) (0.648) (0.679) (0.837) (0.875) (0.589) (0.619) After*LTVconst 3.521** 4.111** 2.689*** 3.140*** 3.487*** 3.964*** 3.543*** 3.782*** (1.657) (1.756) (1.029) (1.089) (1.109) (1.171) (0.828) (0.871) Obs 45,286 41,292 96,417 88,448 189,119 173,609 283,896 262,691 Individual Obs

• Yes
• Yes
• Yes
• Yes

Bank*Month Yes Yes Yes Yes Yes Yes Yes Yes GPdemandS16 Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 50 / 52

Methodology - OLS Regressions

◮ Finally, we investigate if additional GP lending is motivated by housing LTV ratios from January 2011-April 2017 with the following specification for individual-credit i, for bank b, and time t: GPloans HousePrice ibt =αi + βLTVit + ζPersonObsit + ωAftert + θLTVit ∗ Aftert + ρPersonObsit ∗ Aftert + γBankObsbt + ηMacroObst + εibt. (7)

◮ PersonObsit : in-house credit rating, number of credit cards, and other outstanding debt. ◮ BankObsbt : capital, liquidity, NPL, ROA, loan-to-asset ratios, and log real assets. ◮ MacroObst : interest rates, IPI, CPI, REER. ◮ LTVit ∗ Aftert accounts for the way LTV levels affect the dependent variable differently after the policy change. ◮ PersonObsit ∗ Aftert allows for different returns to personal observables.

Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 51 / 52

Results - OLS Table 18: OLS Estimates Jan 2011 - April 2017

(1) (2) (3) (4) (5) (6) LTV 0.012*** 0.012*** 0.025*** 0.033*** 0.028*** 0.029*** (0.003) (0.003) (0.004) (0.004) (0.005) (0.005) N of CC 0.026*** 0.053*** 0.057*** 0.057*** 0.062*** (0.006) (0.008) (0.008) (0.008) (0.008) Other Debt

• 0.014***
• 0.005***
• 0.005***
• 0.006***

(0.002) (0.001) (0.001) (0.001) Rating =2 4.642*** 4.730*** 4.782*** (0.958) (0.959) (0.954) =3 5.131*** 5.124*** 5.213*** (1.221) (1.221) (1.216) =4 2.042 2.095 2.254 (2.854) (2.845) (2.848) =5 2.000 1.854 1.919 (1.271) (1.271) (1.266) =6 3.886*** 3.862*** 3.926*** (0.788) (0.787) (0.782) After

• 0.269
• 0.708

(0.732) (0.747) After*LTV 0.026** 0.024** (0.010) (0.010) After*Other Debt 0.004*** (0.001) After*N of CC

• 0.036**

(0.018) Obs 102,799 102,799 90,005 70,745 70,745 70,745 R-sq 0.189 0.189 0.182 0.153 0.153 0.154 Robustness Baziki & C ¸apacıo˘ glu (CBRT) LTV Caps and Additional Loans 52 / 52