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CONGRESSIONAL BUDGET OFFICE
Modeling the Subsidy
Rate for Federal Single-
Family Mortgage
Insurance Programs
January 2018
1
CBO
Objective
 In preparing its baseline projections of the federal budget, CBO
estimates the budgetary costs of programs that insure single-family
mortgages.
 To estimate those costs, CBO models the programs’ subsidy rates.
– The subsidy rate measures the difference between the value of a
loan guarantee and any fees received by the guarantor as a
percentage of the original unpaid principal balance.
– The budgetary cost is equal to the product of the original unpaid
principal balance and the subsidy rate.
2
CBO
Federal Single-Family Mortgage Insurance
Programs
 Several programs insure single-family mortgages:
– The Federal Housing Administration (FHA);
– Government-sponsored enterprises (GSEs) Fannie Mae and
Freddie Mac, which CBO treats as government entities;
– The Department of Veterans Affairs (VA); and
– The Rural Housing Service (RHS).
3
CBO
Federal Mortgage Insurance
 FHA, the GSEs, VA, and RHS insure mortgages made by private lenders
against borrower default.
– The insurers receive up-front and annual fees in exchange.
– The terms of the insurance make those mortgages less costly for
borrowers than privately insured mortgages.
 Fees, which are set by the insurers, and insurance claims determine
subsidy rates and, in turn, federal costs.
 Insured mortgages are pooled into mortgage-backed securities (MBSs),
which are sold to investors.
– MBSs are more liquid than the underlying mortgages.
4
CBO
Basis of Estimates
 CBO estimates the subsidy rate of federal single-family mortgage
insurance programs on one or both of two present-value accrual bases:
– A Federal Credit Reform Act (FCRA) basis, which reflects
probabilities of default and other events that affect payments. Cash
flows are discounted using interest rates on Treasury securities.
– A fair-value basis, which additionally accounts for market risk. Cash
flows are discounted at rates based on market prices (or
approximations, when market prices are not available).
 GSE subsidy rates are calculated on a fair-value basis.
 FHA, VA, and RHS subsidy rates are calculated on a FCRA basis.
Supplemental fair-value estimates are also calculated, in part, to
facilitate comparisons with GSE subsidy rates and budgetary costs.
5
CBO
CBO’s Modeling Approach for FHA and the GSEs
 CBO’s models for FHA and the GSEs capture how changes in the
mortgage market and in macroeconomic conditions affect mortgage
performance. The models’ inputs include:
– Home price projections,
– Interest rate projections,
– Unemployment rate projections, and
– Total mortgage originations in the market, insurers’ market shares,
and mortgage characteristics.
 The model estimations are based on FHA’s and the GSEs’ reported data
on mortgage performance from 2000 to 2015.
 VA and RHS subsidy rates are estimated using a different process,
based in part on the estimates provided by the Administration in the
Federal Credit Supplement.
6
CBO
CBO’s Modeling Approach for FHA and the GSEs
(Continued)
 CBO uses a stochastic simulation of 1,000 economic scenarios to
generate path-specific projections of
– Defaults,
– Prepayments, and
– Losses given default (severity).
 CBO estimates subsidy rates by computing path-specific cash flows and
applying the appropriate discount rates.
7
CBO
Statistical Models for FHA and the GSEs
Prepayment Model Default Model Severity Model
Objective Predict the probability of
voluntary prepayment
depending on borrower,
mortgage, and market
characteristics
Predict the probability of
default depending on
borrower, mortgage, and
market characteristics
Predict losses in the event of
a default depending on
borrower, mortgage, and
market characteristics
Key Inputs
Borrower
characteristics
Credit score
Debt-to-income ratio
Credit score
Debt-to-income ratio
Credit score
Mortgage
characteristics
Loan age
Loan size
Loan-to-value ratio
Property type
Occupancy type
Loan purpose (purchase,
refinance)
Refinance incentive
Loan age
Loan size
Loan-to-value ratio
Property type
Occupancy type
Loan purpose (purchase,
refinance)
Refinance incentive
Loan age
Loan type
Loan-to-value ratios (current
and original)
Property type
Occupancy type
Mortgage insurance coverage
Market
characteristics
Unemployment rate Unemployment rate Foreclosure laws
8
CBO
Cash Flow Estimation for FHA and the GSEs
 For each fiscal year, CBO estimates the characteristics of the mortgages
that federal insurers will guarantee.
 For FHA and the GSEs, those mortgages are aggregated in
representative groups, or “bins.”
– For each fiscal year, there are approximately 75 bins.
– Each bin is weighted to represent a portion of borrowers, ranging
from less than 1 percent to greater than 20 percent.
– Borrowers are assigned to bins on the basis of their credit scores
and their mortgages’ loan-to-value ratios.
9
CBO
Cash Flow Estimation for FHA and the GSEs
(Continued)
 Each bin is run through the statistical models using a combination of
quarterly interest rates, unemployment rates, and home price changes to
generate quarterly principal and interest (P&I) payments, voluntary
prepayments, defaults, and losses given a default.
 Quarterly cash flows are used to calculate the components of the
subsidy rate (see the following slides) and are aggregated across
simulations and bins.
– For each bin, the cash flows of all simulations are averaged.
– For each fiscal year, a weighted average of those bin-level results
reflects total federal subsidy rates.
10
CBO
Subsidy Rate Calculation for FHA and the GSEs
 Loan guarantees shield MBS investors from credit risk.
 In the event of a borrower’s default,
– The holder of an MBS receives P&I payments, voluntary
prepayments, and the full value of the defaulted principal.
– By contrast, the holder of whole loans receives P&I payments,
voluntary prepayments, and any recoveries from defaulted principal.
 Thus, the value of a loan guarantee is calculated as the difference
between the value of a security without credit risk (MBS) and the value
of securities with credit risk (whole loans).
 The subsidy rate is calculated as the difference between the value of the
loan guarantee and any fees received by the guarantor, expressed as a
percentage of the loan amounts guaranteed.
– Negative subsidy rates indicate that the federal guarantor’s expected
income from fees is greater than the expected cost of the guarantee.
11
CBO
Subsidy Rate Calculation: Example
This example excludes compensation paid to mortgage servicers and compensation required by mortgage investors to bear prepayment
risk, which CBO incorporates into its estimates of FHA and GSE costs.
Model Inputs
Mortgage rate: 4.00%; fees paid to guarantor: 0.25%; annual prepayments: 5.00%; annual
defaults: 0.50%; severity (loss given default): 25.00%; Treasury rate: 2.00%; risk premium: 0.50%
Component
Expressed as a percentage of the loan amount guaranteed FCRA Fair-Value
Value of MBS
Present value of P&I payments (including defaults) and voluntary prepayments, discounted at the
Treasury rate
114.3 114.3
Value of Whole Loans
Present value of P&I payments, voluntary prepayments, and recoveries from defaulted principal,
discounted at the Treasury rate (FCRA) or the Treasury rate plus a risk premium (fair-value)
113.2 108.2
Value of Guarantee
Value of an MBS minus value of whole loans
1.1 6.1
Value of Fees
Present value of fees paid to guarantor, discounted at the Treasury rate (FCRA) or the Treasury
rate plus a risk premium (fair-value)
2.1 2.0
Subsidy Rate
Value of guarantee minus value of fees paid to the guarantor
−1.0 +4.1
12
CBO
Variable Value
Default
Coefficient
Prepayment
Coefficient
Age
(Calendar year quarters)
1–8 0.3129 0.0917
9–16 0.0341 -0.0916
17–24 -0.0026 -0.0153
25–40 0.0088 -0.0361
40–120 - -
Refinance Incentive
(Percentage points)
Less than -1 - -
-1–0 - 0.2219
0–1 - 1.5329
1–2 - 0.4861
2–3 - 0.2914
Greater than 3 - -
Current Loan-to-Value Ratio
(Percent)
0–60 0.0641 -0.0070
60–70 0.0539 -0.0090
70–85 0.0471 -0.0271
85–95 0.0566 -0.0327
Greater than 95 0.0189 -0.0127
Credit Score
300–680 -0.0040 0.0031
680–720 -0.0081 0.0025
720–750 -0.0096 0.0026
750–780 -0.0177 0.0002
780–900 -0.0111 -0.0057
GSE Statistical Models: Prepayment and Default
Values are multinomial logit coefficients estimated using loan-level data reported by Fannie Mae and Freddie Mac. The estimation
sample consists of mortgages that originated between calendar years 2000 and 2012, tracked through the first six months of 2015. All
variables shown in this table are modeled as spline functions. Coefficients may change with future baselines.
13
CBO
GSE Statistical Models: Prepayment and Default
(Continued)
Values are multinomial logit coefficients estimated using loan-level data reported by Fannie Mae and Freddie Mac. The estimation
sample consists of mortgages that originated between calendar years 2000 and 2012, tracked through the first six months of 2015. For
missing debt-to-income ratios, borrowers’ debt or income was not reported. Coefficients may change with future baselines.
Variable Default Coefficient
Prepayment
Coefficient
Relative Loan Size (Proportion) -0.1491 0.6355
Debt-to-Income Ratio (Percent) 0.0134 -0.0024
Debt-to-Income Ratio Missing 0.6597 -0.0568
Condominium 0.0764 -0.0038
Duplex 0.1026 -0.3629
Planned Unit Development 0.0381 -0.0182
Second Home 0.0037 -0.2407
Investment Property 0.3490 -0.3814
Refinance, No Cash Out 0.3225 -0.0311
Refinance, Cash Out 0.3096 -0.1682
Note Rate Spread (Percentage point) 0.4945 0.5857
State Unemployment Rate (Percentage point) 0.0968 -0.0721
2nd Quarter Calendar Year -0.0744 0.1306
3rd Quarter Calendar Year 0.0418 0.1547
4th Quarter Calendar Year 0.1614 0.0301
Constant -11.7163 -6.1472
14
CBO
Variable Severity Coefficient
Age (Quarters) 0.0085
Mortgage Insurance Amount (Percent) -0.0090
Current Loan-to-Value Ratio (Percent) 0.0049
Original Loan-to-Value Ratio (Percent) 0.0011
Relative Loan Size (Fraction) -0.2225
Credit Score -0.0003
Condominium -0.0204
Duplex 0.1228
Planned Unit Development -0.0703
Other Property Type 0.0323
Second Home 0.0338
Investment Property 0.0760
Refinance, Cash Out 0.0987
Refinance, No Cash Out 0.0700
Judicial Foreclosure State 0.0131
Nonjudicial Foreclosure State -0.1161
Deficiency Judgment State -0.0085
Constant 0.2287
GSE Statistical Models: Severity
Values are ordinary least squared coefficients estimated using loan-level data reported by Fannie Mae and Freddie Mac. The estimation
sample consists of mortgages that originated between calendar years 2000 and 2012, tracked through the first six months of 2015.
Quarters are for calendar years. Coefficients may change with future baselines.
15
CBO
Variable Mean Minimum Maximum
Credit Score 752 625 824
Debt-to-Income Ratio 34 4 50
Loan-to-Value Ratio 77 14 97
Borrower and Mortgage Characteristics
GSE Mortgage Data for 2018
Values were estimated using loan-level data reported by Fannie Mae and Freddie Mac.
16
CBO
GSE Mortgage Data for 2018 (Continued)
Values were estimated using loan-level data reported by Fannie Mae and Freddie Mac.
Occupancy Type Percent Share
Primary Residence 86
Investment Property 10
Second Home 4
Shares of Mortgages by Occupancy and Property Type
Property Type Percent Share
Single-Family Home 72
Planned Unit Development 25
Duplex 3
17
CBO
About This Document
These slides were prepared to enhance the transparency of the work of
the Congressional Budget Office and to encourage external review of that
work. In keeping with CBO’s mandate to provide objective, impartial
analysis, this document makes no recommendations.
Mitchell Remy composed this document and Christine Browne edited it. An
electronic version is available on CBO’s website
(www.cbo.gov/publication/53402).

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Modeling the Subsidy Rate for Federal Single-Family Mortgage Insurance Programs

  • 1. CONGRESSIONAL BUDGET OFFICE Modeling the Subsidy Rate for Federal Single- Family Mortgage Insurance Programs January 2018
  • 2. 1 CBO Objective  In preparing its baseline projections of the federal budget, CBO estimates the budgetary costs of programs that insure single-family mortgages.  To estimate those costs, CBO models the programs’ subsidy rates. – The subsidy rate measures the difference between the value of a loan guarantee and any fees received by the guarantor as a percentage of the original unpaid principal balance. – The budgetary cost is equal to the product of the original unpaid principal balance and the subsidy rate.
  • 3. 2 CBO Federal Single-Family Mortgage Insurance Programs  Several programs insure single-family mortgages: – The Federal Housing Administration (FHA); – Government-sponsored enterprises (GSEs) Fannie Mae and Freddie Mac, which CBO treats as government entities; – The Department of Veterans Affairs (VA); and – The Rural Housing Service (RHS).
  • 4. 3 CBO Federal Mortgage Insurance  FHA, the GSEs, VA, and RHS insure mortgages made by private lenders against borrower default. – The insurers receive up-front and annual fees in exchange. – The terms of the insurance make those mortgages less costly for borrowers than privately insured mortgages.  Fees, which are set by the insurers, and insurance claims determine subsidy rates and, in turn, federal costs.  Insured mortgages are pooled into mortgage-backed securities (MBSs), which are sold to investors. – MBSs are more liquid than the underlying mortgages.
  • 5. 4 CBO Basis of Estimates  CBO estimates the subsidy rate of federal single-family mortgage insurance programs on one or both of two present-value accrual bases: – A Federal Credit Reform Act (FCRA) basis, which reflects probabilities of default and other events that affect payments. Cash flows are discounted using interest rates on Treasury securities. – A fair-value basis, which additionally accounts for market risk. Cash flows are discounted at rates based on market prices (or approximations, when market prices are not available).  GSE subsidy rates are calculated on a fair-value basis.  FHA, VA, and RHS subsidy rates are calculated on a FCRA basis. Supplemental fair-value estimates are also calculated, in part, to facilitate comparisons with GSE subsidy rates and budgetary costs.
  • 6. 5 CBO CBO’s Modeling Approach for FHA and the GSEs  CBO’s models for FHA and the GSEs capture how changes in the mortgage market and in macroeconomic conditions affect mortgage performance. The models’ inputs include: – Home price projections, – Interest rate projections, – Unemployment rate projections, and – Total mortgage originations in the market, insurers’ market shares, and mortgage characteristics.  The model estimations are based on FHA’s and the GSEs’ reported data on mortgage performance from 2000 to 2015.  VA and RHS subsidy rates are estimated using a different process, based in part on the estimates provided by the Administration in the Federal Credit Supplement.
  • 7. 6 CBO CBO’s Modeling Approach for FHA and the GSEs (Continued)  CBO uses a stochastic simulation of 1,000 economic scenarios to generate path-specific projections of – Defaults, – Prepayments, and – Losses given default (severity).  CBO estimates subsidy rates by computing path-specific cash flows and applying the appropriate discount rates.
  • 8. 7 CBO Statistical Models for FHA and the GSEs Prepayment Model Default Model Severity Model Objective Predict the probability of voluntary prepayment depending on borrower, mortgage, and market characteristics Predict the probability of default depending on borrower, mortgage, and market characteristics Predict losses in the event of a default depending on borrower, mortgage, and market characteristics Key Inputs Borrower characteristics Credit score Debt-to-income ratio Credit score Debt-to-income ratio Credit score Mortgage characteristics Loan age Loan size Loan-to-value ratio Property type Occupancy type Loan purpose (purchase, refinance) Refinance incentive Loan age Loan size Loan-to-value ratio Property type Occupancy type Loan purpose (purchase, refinance) Refinance incentive Loan age Loan type Loan-to-value ratios (current and original) Property type Occupancy type Mortgage insurance coverage Market characteristics Unemployment rate Unemployment rate Foreclosure laws
  • 9. 8 CBO Cash Flow Estimation for FHA and the GSEs  For each fiscal year, CBO estimates the characteristics of the mortgages that federal insurers will guarantee.  For FHA and the GSEs, those mortgages are aggregated in representative groups, or “bins.” – For each fiscal year, there are approximately 75 bins. – Each bin is weighted to represent a portion of borrowers, ranging from less than 1 percent to greater than 20 percent. – Borrowers are assigned to bins on the basis of their credit scores and their mortgages’ loan-to-value ratios.
  • 10. 9 CBO Cash Flow Estimation for FHA and the GSEs (Continued)  Each bin is run through the statistical models using a combination of quarterly interest rates, unemployment rates, and home price changes to generate quarterly principal and interest (P&I) payments, voluntary prepayments, defaults, and losses given a default.  Quarterly cash flows are used to calculate the components of the subsidy rate (see the following slides) and are aggregated across simulations and bins. – For each bin, the cash flows of all simulations are averaged. – For each fiscal year, a weighted average of those bin-level results reflects total federal subsidy rates.
  • 11. 10 CBO Subsidy Rate Calculation for FHA and the GSEs  Loan guarantees shield MBS investors from credit risk.  In the event of a borrower’s default, – The holder of an MBS receives P&I payments, voluntary prepayments, and the full value of the defaulted principal. – By contrast, the holder of whole loans receives P&I payments, voluntary prepayments, and any recoveries from defaulted principal.  Thus, the value of a loan guarantee is calculated as the difference between the value of a security without credit risk (MBS) and the value of securities with credit risk (whole loans).  The subsidy rate is calculated as the difference between the value of the loan guarantee and any fees received by the guarantor, expressed as a percentage of the loan amounts guaranteed. – Negative subsidy rates indicate that the federal guarantor’s expected income from fees is greater than the expected cost of the guarantee.
  • 12. 11 CBO Subsidy Rate Calculation: Example This example excludes compensation paid to mortgage servicers and compensation required by mortgage investors to bear prepayment risk, which CBO incorporates into its estimates of FHA and GSE costs. Model Inputs Mortgage rate: 4.00%; fees paid to guarantor: 0.25%; annual prepayments: 5.00%; annual defaults: 0.50%; severity (loss given default): 25.00%; Treasury rate: 2.00%; risk premium: 0.50% Component Expressed as a percentage of the loan amount guaranteed FCRA Fair-Value Value of MBS Present value of P&I payments (including defaults) and voluntary prepayments, discounted at the Treasury rate 114.3 114.3 Value of Whole Loans Present value of P&I payments, voluntary prepayments, and recoveries from defaulted principal, discounted at the Treasury rate (FCRA) or the Treasury rate plus a risk premium (fair-value) 113.2 108.2 Value of Guarantee Value of an MBS minus value of whole loans 1.1 6.1 Value of Fees Present value of fees paid to guarantor, discounted at the Treasury rate (FCRA) or the Treasury rate plus a risk premium (fair-value) 2.1 2.0 Subsidy Rate Value of guarantee minus value of fees paid to the guarantor −1.0 +4.1
  • 13. 12 CBO Variable Value Default Coefficient Prepayment Coefficient Age (Calendar year quarters) 1–8 0.3129 0.0917 9–16 0.0341 -0.0916 17–24 -0.0026 -0.0153 25–40 0.0088 -0.0361 40–120 - - Refinance Incentive (Percentage points) Less than -1 - - -1–0 - 0.2219 0–1 - 1.5329 1–2 - 0.4861 2–3 - 0.2914 Greater than 3 - - Current Loan-to-Value Ratio (Percent) 0–60 0.0641 -0.0070 60–70 0.0539 -0.0090 70–85 0.0471 -0.0271 85–95 0.0566 -0.0327 Greater than 95 0.0189 -0.0127 Credit Score 300–680 -0.0040 0.0031 680–720 -0.0081 0.0025 720–750 -0.0096 0.0026 750–780 -0.0177 0.0002 780–900 -0.0111 -0.0057 GSE Statistical Models: Prepayment and Default Values are multinomial logit coefficients estimated using loan-level data reported by Fannie Mae and Freddie Mac. The estimation sample consists of mortgages that originated between calendar years 2000 and 2012, tracked through the first six months of 2015. All variables shown in this table are modeled as spline functions. Coefficients may change with future baselines.
  • 14. 13 CBO GSE Statistical Models: Prepayment and Default (Continued) Values are multinomial logit coefficients estimated using loan-level data reported by Fannie Mae and Freddie Mac. The estimation sample consists of mortgages that originated between calendar years 2000 and 2012, tracked through the first six months of 2015. For missing debt-to-income ratios, borrowers’ debt or income was not reported. Coefficients may change with future baselines. Variable Default Coefficient Prepayment Coefficient Relative Loan Size (Proportion) -0.1491 0.6355 Debt-to-Income Ratio (Percent) 0.0134 -0.0024 Debt-to-Income Ratio Missing 0.6597 -0.0568 Condominium 0.0764 -0.0038 Duplex 0.1026 -0.3629 Planned Unit Development 0.0381 -0.0182 Second Home 0.0037 -0.2407 Investment Property 0.3490 -0.3814 Refinance, No Cash Out 0.3225 -0.0311 Refinance, Cash Out 0.3096 -0.1682 Note Rate Spread (Percentage point) 0.4945 0.5857 State Unemployment Rate (Percentage point) 0.0968 -0.0721 2nd Quarter Calendar Year -0.0744 0.1306 3rd Quarter Calendar Year 0.0418 0.1547 4th Quarter Calendar Year 0.1614 0.0301 Constant -11.7163 -6.1472
  • 15. 14 CBO Variable Severity Coefficient Age (Quarters) 0.0085 Mortgage Insurance Amount (Percent) -0.0090 Current Loan-to-Value Ratio (Percent) 0.0049 Original Loan-to-Value Ratio (Percent) 0.0011 Relative Loan Size (Fraction) -0.2225 Credit Score -0.0003 Condominium -0.0204 Duplex 0.1228 Planned Unit Development -0.0703 Other Property Type 0.0323 Second Home 0.0338 Investment Property 0.0760 Refinance, Cash Out 0.0987 Refinance, No Cash Out 0.0700 Judicial Foreclosure State 0.0131 Nonjudicial Foreclosure State -0.1161 Deficiency Judgment State -0.0085 Constant 0.2287 GSE Statistical Models: Severity Values are ordinary least squared coefficients estimated using loan-level data reported by Fannie Mae and Freddie Mac. The estimation sample consists of mortgages that originated between calendar years 2000 and 2012, tracked through the first six months of 2015. Quarters are for calendar years. Coefficients may change with future baselines.
  • 16. 15 CBO Variable Mean Minimum Maximum Credit Score 752 625 824 Debt-to-Income Ratio 34 4 50 Loan-to-Value Ratio 77 14 97 Borrower and Mortgage Characteristics GSE Mortgage Data for 2018 Values were estimated using loan-level data reported by Fannie Mae and Freddie Mac.
  • 17. 16 CBO GSE Mortgage Data for 2018 (Continued) Values were estimated using loan-level data reported by Fannie Mae and Freddie Mac. Occupancy Type Percent Share Primary Residence 86 Investment Property 10 Second Home 4 Shares of Mortgages by Occupancy and Property Type Property Type Percent Share Single-Family Home 72 Planned Unit Development 25 Duplex 3
  • 18. 17 CBO About This Document These slides were prepared to enhance the transparency of the work of the Congressional Budget Office and to encourage external review of that work. In keeping with CBO’s mandate to provide objective, impartial analysis, this document makes no recommendations. Mitchell Remy composed this document and Christine Browne edited it. An electronic version is available on CBO’s website (www.cbo.gov/publication/53402).