Household indebtedness estimations and simulations using microdata canadian case
Download
1 / 19

Household Indebtedness: Estimations and Simulations using Microdata (Canadian case) - PowerPoint PPT Presentation


  • 106 Views
  • Uploaded on

Household Indebtedness: Estimations and Simulations using Microdata (Canadian case). Shubhasis Dey, Ramdane Djoudad and Yaz Terajima Bank of Canada May 2008. Household credit (HH) have considerably grown over 2000-2007

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Household Indebtedness: Estimations and Simulations using Microdata (Canadian case)' - stuart-maldonado


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Household indebtedness estimations and simulations using microdata canadian case

Household Indebtedness: Estimations and Simulations using Microdata (Canadian case)

Shubhasis Dey, Ramdane Djoudad and Yaz Terajima

Bank of Canada

May 2008


Motivation

Household credit (HH) have considerably grown over 2000-2007 Microdata (Canadian case)

HH credit represents about 70% of total Cdn$ loan exposure of commercial banks in Canada.

Assessing credit risk associated with HH sector is an important part of the assessment of risks in the Canadian financial system

Motivation


How do we assess the risks associated with the hh sector at the bank

Aggregate indicators (Debt-service-ratio, arrears, personal bankruptcy rate etc.)

Microdata indicators

Previous indicators are useful but incomplete and “backward-looking”

How do we assess the risks associated with the HH sector at the Bank?


What do we need

A simulation tool for HH Debt-service-ratio bankruptcy rate etc.)

A measure of the probability of delinquency for Cdn HHs

Need to link both indicators and to be forward-looking

What do we need?


Objective of this work

Develop a tool for performing stress testing simulations on microdata to:

Assess the future path as well as the distribution of the DSR given macroeconomic scenarios

Estimate the probability of delinquency for Canadian households

Objective of this work


Literature survey

Literature: few empirical studies on household delinquency and simulation exercises for Canada.

Reason: lack of household-level data

Existing studies: Pyper, 2002; Domowitz and Sartain,1999; Stavins, 2000; Fay, Hurst and White, 2002; Gross and, Risto Souleles,2002; Li and Sarte, 2006; Herrala and Kauko, 2007.

Literature Survey


The data

In practice we use two datasets and simulation exercises for Canada.

Advantages of 2 datasets:

SFS: delinquency and explanatory variables identified in literature. (16 000 HH in 2005, 5000 in 1999)

CFM: available on a frequent and regular basis (12 000 every year)

Data limitations:

SFS data: not available on a regular and frequent basis.

CFM: no delinquency variable, only some of the explanatory variables identified in literature.

The Data


Estimations

For simulations, we need to combine two parts: and simulation exercises for Canada.

On one hand we estimate equations for household credit (total and mortgage credit), to distribute aggregate debt among different households according to: age, education, working status, region of residence, indebtedness, income, interest rates, house prices, wealth.

On the other hand we estimate equations for household’s propensity to be delinquent according to similar sets of variables

Estimations


Simulation

Given: and simulation exercises for Canada.

Estimated equations

A macroeconomic scenario for the path of some economic variables (income, debt, interest rates, house prices)

We evaluate

The implied average DSR along with its distribution over the forecasting horizon

The implicit household’s propensity to be delinquent

Simulation


Stress testing exercise

Objective: assess how shocks would affect the distribution of the DSR, vulnerable households and the probability of delinquency

Stress-testing exercise



Caveats limitations

We limit explanatory variables to those included in CFM (fewer than in SFS)

Implicit assumption: coefficients of the equations are stable over time

Liquid assets scenario: change similar for all households

Stress-test: some variables kept unchanged but it might not be the case

Caveats / Limitations


Conclusion

Objective: simulate the DSR and the probability of default for Cdn households.

Stress-test results: probability of default for most vulnerable households would significantly increase subsequently to negative developments in DSR and liquid assets.

Conclusion


Future work

Robustness check of estimated delinquency equation coefficients

Endogeneity of DSR for household’s delinquency equation

Future work


ad