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Colombia: Rule of Law, Creditor Rights and the Crisis of Housing Finance

Colombia: Rule of Law, Creditor Rights and the Crisis of Housing Finance. Mauricio Cárdenas Alejandro Badel. Outline. Macroeconomic relevance Overview of the mortgage sector Perils of indexation Other causes (and consequences) of the crisis Creditor rights Econometric analysis

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Colombia: Rule of Law, Creditor Rights and the Crisis of Housing Finance

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  1. Colombia: Rule of Law, Creditor Rights and the Crisis of Housing Finance Mauricio Cárdenas Alejandro Badel

  2. Outline • Macroeconomic relevance • Overview of the mortgage sector • Perils of indexation • Other causes (and consequences) of the crisis • Creditor rights • Econometric analysis • Fiscal costs

  3. Macro relevance

  4. Cyclical Components of Mortgage Disbursements, Construction GDP and Total GDP 100% 30% Disbursements of Mortgage Loan 75% 20% 50% 10% 25% 0% 0% -10% -25% -20% -50% -30% -75% Construction GDP -100% -40% 100% 5% Disbursements of Mortgage Loan 4% 75% 3% 50% 2% 25% 1% 0% 0% -1% -25% -2% -50% -3% -75% -4% Total GDP -100% -5% 2001:1 1977:1 1979:1 1981:1 1983:1 1985:1 1987:1 1989:1 1991:1 1993:1 1995:1 1997:1 1999:1

  5. Granger Causality between GDP and mortgage origination Causality Lags Sample Statistic F Probability 3,583 0,032 2 1977:1 2002:2 GDP Cycle Causes Construction GDP Cycle 0,976 0,381 Construction GDP Cycle Causes GDP Cycle 0,859 0,427 2 1977:1 - 2002:2 GDP Cycle Causes Disbursements of Mortgage Loans Cycle 2,474 0,090 Disbursements of Mortgage Loans Cycle Causes GDP Cycle 3,701 0,028 2 1977:1 - 2002:2 GDP Construction Cycle Causes Disbursements of Mortgage Loans Cycle 3,654 0,030 Disbursements of Mortgage Loans Cycle Causes GDP Construction Cycle 0,050 0,824 1 1990:1 - 2002:2 GDP Cycle Causes GDP Construction Cycle 4,418 0,041 GDP Construction Cycle Causes GDP Cycle 0,008 0,992 2 1990:1 - 2002:2 GDP Cycle Causes Disbursements of Mortgage Loans Cycle 3,222 0,049 Disbursements of Mortgage Loans Cycle Causes GDP Cycle 3,405 0,042 2 1990:1 - 2002:2 GDP Construction Cycle Causes Disbursements of Mortgage Loans Cycle 16,979 0,000 Disbursements of Mortgage Loans Cycle Causes GDP Construction Cycle

  6. Granger Causality between Cyclical Components (1977-2002) Disbursements of Mortgage Loans Total GDP Disbursements of Mortgage Loans Construction GDP (all but the 90s) Total GDP Construction GDP (Only the 90s)

  7. Rolling Correlation 80% 70% 60% Construction GDP Cycle 50% 40% Correlation coefficient* 30% Total GDP Cycle 20% 10% 0% -10% -20% 100% 80% 60% 40% 20% Correlation coefficient* 0% -20% -40% -60% 2000:4 2001:4 1986:4 1987:4 1988:4 1989:4 1990:4 1991:4 1992:4 1993:4 1994:4 1995:4 1996:4 1997:4 1998:4 1999:4 Correlation with the Disbursements of Mortgage Loans Cycle Correlation between Total GDP and Construction GDP Cycles *"Rolling Correlation" using a 10 year window of data

  8. OVERVIEW OF THE MORTGAGE SECTOR

  9. Mortgage Banks in 2002 900 Mortgage Loans % Total assets 800 59% 57% 53% 700 48% 43% 600 35% 500 US$ M 400 300 200 12% 100 - AV VILLAS BANCAFE COLMENA COLPATRIA CONAVI DAVIVIENDA GRANAH

  10. Disbursements of Mortgage Loans Billions of 1998 pesos

  11. Outstanding mortgage loans(1998 pesos, % of GPD, and % of total credit) 18 27% 16 % of Total credit 14 22% 12 10 17% % Constant pesos billions of 1998 pesos 8 12% 6 4 7% 2 % of GDP 2% 0 2000 2001 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

  12. Non-performing mortgage loans(as % of total mortgage loans) 25 20 15 Debt restructuring % 10 5 0 Dic-97 Dic-98 Dic-99 Dic-01 Dic-00 Dic-96 Dic-94 Dic-95 Jun-02 Jun-97 Jun-98 Jun-99 Jun-00 Jun-95 Jun-96 Jun-01

  13. Mortgage Banks Composition of Assets 100% 80% 60% 40% 20% 0% 1999 2000 2001 1990 1991 1992 1993 1994 1995 1996 1985 1986 1987 1988 1989 1997 1998 Ag-02 Mortgage Loans Other Loans Portfolio Investments Other assets

  14. Mortgage BanksComposition of Liabilities 100% 80% 60% 40% 20% 0% 2000 2001 1990 1991 1992 1993 1994 1995 1996 1997 1999 1985 1986 1987 1988 1989 1998 Ag-02 Indexed Liabilities Peso liabilities Other liabilities

  15. Mortgage BanksComposition of Deposits 100% 80% 60% 40% 20% 0% 1990 1991 1992 1993 1994 1995 1996 2001 2002 1989 1997 2000 1985 1986 1987 1988 1998 1999 Savings and current account Less than one year More than one year

  16. Summary • Disbursements currently at their historically lowest point. • 21.5% of the mortgage portfolio was delinquent by February 2003. • Interest rate and maturity mismatch.

  17. The perils of indexation

  18. Yearly Growth Rates: UPAC and CPI 38% 33% CPI 28% 23% 18% UPAC 13% 8% Oct-93 Oct-94 Oct-95 Oct-96 Oct-97 Oct-98 Oct-99 Oct-73 Oct-74 Oct-75 Oct-76 Oct-77 Oct-78 Oct-79 Oct-80 Oct-81 Oct-82 Oct-83 Oct-84 Oct-85 Oct-86 Oct-87 Oct-88 Oct-89 Oct-90 Oct-91 Oct-92

  19. Real UPAC (UPAC / CPI) 100 90 80 Sep. 1972 = 100 Real UPAC 70 New UPAC for “restructured” loans 60 50 Sep-96 Sep-97 Sep-98 Sep-99 Sep-80 Sep-81 Sep-82 Sep-83 Sep-84 Sep-85 Sep-86 Sep-87 Sep-88 Sep-89 Sep-90 Sep-91 Sep-92 Sep-95 Sep-72 Sep-73 Sep-74 Sep-75 Sep-76 Sep-77 Sep-78 Sep-79 Sep-93 Sep-94

  20. UPAC, UVR and CPI: Monthly percent changes 7% 6% % CPI % UPAC - UVR 5% 4% 3% 2% 1% 0% -1% Oct-98 Oct-99 Oct-00 Oct-01 Oct-82 Oct-83 Oct-84 Oct-85 Oct-86 Oct-87 Oct-88 Oct-89 Oct-90 Oct-91 Oct-92 Oct-93 Oct-94 Oct-97 Oct-72 Oct-73 Oct-74 Oct-75 Oct-76 Oct-77 Oct-78 Oct-79 Oct-80 Oct-81 Oct-95 Oct-96

  21. OTHER CAUSES (AND CONSEQUENCES)

  22. Housing Price Index (HPI)Deflated by CPI 140 130 120 110 April 1998=100 100 90 80 70 60 nov-00 nov-01 nov-02 nov-90 nov-91 nov-92 nov-93 nov-94 nov-95 nov-96 nov-97 nov-99 nov-86 nov-87 nov-88 nov-89 nov-98 HPI DNP BOGOTA HPI DNP MEDELLIN HPI DANE HPI Camacol

  23. Unemployment rate (observed and simulated) 20% Unemployment (keeping the December 1997 construction employment constant) 18,0% Unemployment (keeping the September 95) 17,8% 16,6% Observed unemployment rate 15% 10% 5% Mar-01 Mar-02 Mar-94 Mar-95 Mar-96 Mar-97 Mar-98 Mar-99 Mar-90 Mar-91 Mar-92 Mar-93 Mar-00 80.000 employees 196.000 employees *Unemployment rate in 13 metropolitan areas (Jan 00 – Jun-02) applying growth to seven areas (Mar 90 – Dec 99)

  24. The role of creditor protection

  25. Foreclosure Proceedings Request of embargo and sequestration of assets Presentation of the defendants pleadings (10 days) LAWSUIT Due Notified to the defendant (20 days) No presentation of the defendants pleadings Order of embargo (30 d) and sequestration (90d) Acceptance (30 days) Non acceptance (30 days) Correction (5 days) SENTENCE: -Orders to continue the proceedings of the lawsuit. -Orders to estimate the price and the sale by auction of the assets under embargo -Orders to liquidate the credit. Rejection (Delay 2 months) Non corrections Liquidation of credit and expenses by the defendant if is not done by the plaintiff (10 days and 3 of notice for the plaintiff) Liquidation of credits and expenses by the plaintiff (10 days and 3 of notice for the defendant) Definitive Liquidation by the court (It has no dateline) ESTIMATE OF ASSETS PRICE Approved by the Judge Order of sale by auction (No dateline) (Embargo, sequestration and estimated) PUBLICATION OF ADS (5 days before the auction) Sale by auction (1 day) (BID, AWARD, NO DATELINES FOR BIDDERS) LEGALIZATION AND DELIVER OF THE ASSET SOLD BY AUCTION

  26. Average Time of Foreclosure ICAV (2002) CEJ (1998) CSJ (1998) Normative time 0 200 400 600 800 1000 1200 1400 1600 # of calendar days

  27. Foreclosure proceedings 130.000 5.300.000 128.316 5.252.000 Number Balance 5.200.000 124.116 125.000 5.100.000 5.119.104 120.000 5.000.000 Millions of Pesos 4.900.000 114.766 115.000 Number 4.831.195 4.800.000 110.000 4.700.000 105.000 4.600.000 Dic-01 Mar-02 Jun-02

  28. Probability of property being foreclosed 100% 90% 80% Bank 3 Bank 2 70% 60% Bank 1 Cumulative probability 50% 40% 30% 20% 10% 0% 0 10 20 30 40 50 60 70 80 90 100 110 120 Months in delinquency

  29. ECONOMETRIC ANALYSIS

  30. Data Aggregation Level: Individual Loans. Number of banks: 2. Scope: Approx. 30% of housing credit. Sample: January 1994 - June 2002. Size: 240,350 loans, with an outstanding balance of 2.3 billions pesos (June 2002) and an original balance of 8.8 billions pesos.

  31. Mortgage Loans by Origination Year %Créditos en Plazo Año de % Saldo % Número de % LTV Altura de dación de Original*** Originación Inicial* Créditos** pago (meses) % Tasa*** Original*** Mora*** antes de 1980 0,0 0,0 4,5 176,9 8,3 0,24 158,8 1980 - 1984 2,2 1,9 0,4 179,5 6,8 0,38 2,7 1985 - 1989 8,6 10,3 0,4 177,1 6,8 0,48 1,8 1990 - 1992 6,2 5,8 0,6 178,1 9,0 0,45 1,6 1993 - 1994 13,2 13,0 1,1 177,8 9,7 0,53 1,5 1995 - 1996 20,7 16,3 4,4 179,3 12,4 0,51 2,1 1997 - 1998 29,3 26,4 5,2 175,5 13,0 0,52 2,3 1999 - 2000 17,0 21,2 3,1 172,6 12,1 0,55 1,7 2001 - 2002 1,9 3,2 0,0 162,3 11,9 0,52 0,3 2002 0,9 1,8 0,0 163,6 11,9 0,55 0,0 Total 100,0 100,0 3,0 176,1 11,3 0,52 1,9

  32. Mortgage Loans by Rate Range

  33. Origination Rate for VIS and Non VIS Mortgage loans* *Origination Rate = Value of Originated Loans in t / Value of Outstanding loans in t-1.

  34. Determinants of the Origination Rate LOG(ORIGTOT) LOG(ORIGVIS) LOG(ORIGNOVIS) Variable Dependiente OLS OLS OLS Procedimiento -3,75 1,91 1,89 Constante -2,31 0,95 0,96 Estadístico t 0,02 0,34 0,34 Probabilidad -0,55 -0,33 -0,42 DUM99-01 -4,45 -2,50 -3,10 Estadístico t 0,00 0,01 0,00 Probabilidad 0,29 0,60 0,27 LOG(Variable Dependiente (-1)) 3,08 7,60 2,80 Estadístico t 0,00 0,00 0,01 Probabilidad -0,28 0,03 -0,34 LOG(VENCIDA(-1)) -2,65 0,27 -2,56 Estadístico t 0,01 0,79 0,01 Probabilidad -0,55 -0,29 -0,95 LOG(CUBRIMIENTO(-1)) -5,25 -2,80 -6,10 Estadístico t 0,00 0,01 0,00 Probabilidad -0,18 -0,31 -0,10 LOG(LIQUIDEZ(-1)) -1,07 -1,50 -0,49 Estadístico t 0,29 0,14 0,63 Probabilidad 1,93 1,13 1,88 LOG(SOLVENCIA(-1)) 4,46 2,31 3,84 Estadístico t 0,00 0,02 0,00 Probabilidad -1,65 -1,16 -2,38 LOG(TASA(-1)) -3,07 -1,88 -3,46 Estadístico t 0,00 0,06 0,00 Probabilidad 0,94 0,83 0,94 R2 ajustado -2,26 -17,23 -21,20 Log verosimilitud 2,08 2,36 2,11 Durbin Watson 87 87 87 Número Observaciones

  35. Origination Rate: Observed, Fitted and Forecasted with and without Legal Instability

  36. Determinants of Delinquency Levels

  37. Months in Delinquency: Observed, Fitted y Forecasted without Legal Instability

  38. Determinants of the Default Probability Método: PROBIT BINARIO Regresión 1 2 C -6,37 -7,87 Probabilidad 0,00 0,00 Efecto marginal -0,31 -0,35 DUM99 1,02 Probabilidad 0,00 Efecto marginal 0,05 DUM00 0,32 Probabilidad 0,00 Efecto marginal 0,01 DUM01 -1,26 Probabilidad 0,00 Efecto marginal -0,06 VIS/NOVIS -0,14 -0,10 Probabilidad 0,00 0,00 Efecto marginal -0,01 0,00 BANCO -0,17 -0,10 Probabilidad 0,00 0,00 Efecto marginal -0,01 0,00 AMORT -0,30 -0,36 Probabilidad 0,00 0,00 Efecto marginal -0,01 -0,02 LOG(PLAZO) 0,43 0,61 Probabilidad 0,00 0,00 Efecto marginal 0,02 0,03 LOG(1+TASA) 4,71 6,17 Probabilidad 0,00 0,00 Efecto marginal 0,23 0,27 LOG(1+SALDOI) 0,25 0,13 Probabilidad 0,00 0,00 Efecto marginal 0,01 0,01 LOG(1+LTVORI) 1,36 1,32 Probabilidad 0,00 0,00 Efecto marginal 0,07 0,06 LOG(1+MORAPROM) 0,64 0,70 Probabilidad 0,00 0,00 Efecto marginal 0,03 0,03 LOG(1+GANCAP) -3,02 -3,47 Probabilidad 0,00 0,00 Efecto marginal -0,15 Observaciones incluidas 161.491 161.491 R2 de Mcfadden 0,32 0,40 Log verosimilitud -15294 -13436 Iteraciones hasta convergencia 7 14

  39. Marginal Effect Over the Default Probability

  40. Default Probability as a Function of Original LTV

  41. THE COSTS OF THE CRISIS

  42. Financial Sector Bailout Cost

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