Evaluating the Impact of an Interest Rate Increase on Mortgages and

Savings

Daniele Fraietta

Swindon, February 17th

Issues to Be Tackled1. What interest rate?

• BoE’s Main Policy Rate (mpr; source: Boe)

2. How to proxy mortgage demand?• Mortgage affordability (MA, ratio)

MA = Mortgage repayments/ Earnings (source: Halifax) NOTICE: MA ratio and Mortgage Demand: negatively correlated

3. How to proxy savings?• Gross savings (SA, Mil. GBP; source ONS)

4. What affects mortgage affordability?• Savings, mpr, house price index (source: Halifax), unemployment (source:

ONS)

5. What affects savings?• Hicp (source: ONS), mpr, unemployment, mortgage affordability, consumer

confidence (source: EC), debt to gross disposable income (source: ONS)

6. What econometric techniques should be used?• Econometric software: E-views 9• Simultaneous Equations Model, 2SLS (endogeneity issues) and what-if

analysis• Vector Autoregression (IRF, Variance Decomposition)• ARIMA forecasting

SAVINGSt = β0 + β1MORT_AFFt + β2MPRt + β3HICPt-2 + β4UNEMPLt + β5FTSE100t-3 + β6SAVINGSt-1 + β7DEBT_TO_GDIt + εtMORT_AFFt = α0 + α1SAVINGSt + α2MPRt + α3SAVINGSt-1 + α4HPIt-1 + α5UNEMPLt-1 + εt

Structural equations (Endogeneity)

Reduced-form equations

SAVINGSt = П0 + П 1MPRt + П 3HICPt-2 + П 4UNEMPLt + П 5FTSE100t-3 + П 6SAVINGSt-1 + П 7DEBT_TO_GDIt + utMORT_AFFt = П7 + П 8MPRt + П 9UNEMPLt-1 + П 10SAVINGSt-1 + П 11HICPt + П 12FTSE100t-3 +

П13DEBT_TO_GDIt + П13HPIt-1 + utП0 = П1 = П2 = П3 = П4 = П5 = П6 = П7 = П8 = П9 = П10 = П11 = П12 = П13 =

П14 =

• What economic theory tells us about the impact of interest rates on: savings : ambiguous (substitution effect/ income effect) mortgage demand: negative (higher cost of borrowing)

Econometric Analysis  SAVINGS MORT_AFF

2000Q1 – 2015Q4 2000Q1 – 2015Q4

Constant 

0.053 -0.008**0.032 0.004

HICP (-2) 

-0.020*  

0.0123  

MPR 

-0.1372*** 0.0824***0.046 0.0181

UNEMPL 

1.331***  

0.1818  

MORT_AFF 

1.4466***  

0.4222  

FTSE100 (-3) 

-0.6401***  

0.2202  

DEBT_TO_GDI 

-5.1508***  

0.7882  

SAVINGS 

  0.0245*  0.0269

SAVINGS (-1) 

-0.2278** 0.054***0.1075 0.0196

HPI (-1) 

  0.8431***  0.1671

UNEMPL (-1) 

  0.0546*  0.0823

Note: *** indicates statistically significant at 1%, ** indicates statistically significant at 5%, * indicates statistically significant at 10%. Point estimates in bold letters and standard errors below. White cross-section covariance method for serial correlation robust standard errors. All variables were found to be non-stationary; hence, the dlog of each variable has been used.

What-if AnalysisImpulse-Response

FunctionVariance

Decomposition

-.12

-.08

-.04

.00

.04

.08

.12

.16

1 2 3 4 5 6 7 8 9 10

Response of DLOG(SAVINGS) to DLOG(MPR)

Response to Cholesky One S.D. Innovations ± 2 S.E.

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

DLOG(MPR)DLOG(SAVINGS)DLOG(MORT_AFF)

Variance Decomposition of DLOG(SAVINGS)

ARIMA FORECASTS (mpr, exogenous variable)

Thank you