MODELLING HOUSEHOLD BEHAVIOUR:

RESPONSE TO MACROECONOMIC

SHOCKS IN THE UK

PAULO ARANA

UNIVERSITY OF ESSEX

28TH OF JUNE 2017

INTRODUCTION AND MOTIVATION

Insolvency Service Agency shows an increment of 9.8% in the

proportion of poor households on debts about the previous year

(2016).

Financial Stability Report (2016) comments on how to reduce

vulnerability to households by increasing caps on loan to income

lending

RESEARCH QUESTION

How do households allocated their assets in response

to macroeconomic shocks?

OBJECTIVES OF THE STUDY

Identify patterns of asset allocation within the WAS

Determining debt relative to their income

Examining whether this debt creates exposure when taking into

account financial shocks

LITERATURE REVIEW (1)

Data mostly gathered from the US and Europe given the availability

of data (SFC, PSID, HFCS)

Literature divided into determinants of allocation of wealth,

household debt and macroeconomic shocks

LITERATURE REVIEW (2)

Studies focused asset allocation (invest or not)

Study Journal Variable of interest Main finding

Ameriks and Zeldes (2004)

Journal of Financial Instability

Age and portfolio changes (US)

As age increases, households become more adamant to include more stocks into their portfolios.

Campbell and Cocco (2007)

Journal of Monetary Economics

Investing wealth (US)

Long-term investors seek to consider opportunities to reinvest wealth at a reasonable rate of return .

Canner et al (1997)

The American Economic Review

Willingness to hold risky assets (US)

Popular advice given by financial advisors does not follow rational behaviour

Cooper and Zhu (2016)

Review of economic dynamics

Influence of age and education for households on stock market participation (US)

Higher amounts of education reduces the costs of participation

Lahey et al (2003) Financial services review

Retirement and allocation of wealth (US)

Newly retirees held a greater amount of fixed income securities before retiring compared to others, signalling a greater degree of risk aversion

Mariotti et al (2014)

Discussion paper (Institute for the Study of Labor)

Wealth diversification across markets (Australia)

Higher amounts of education increases disposition to diversify.

8

LITERATURE REVIEW (3)

Studied focused on household debt Study Journal Variable of interest Main finding

Ampudia et

al (2016)

Journal of

Financial Stability

Shocks to income on

debt (EU)

Debt to income ratios positively affected by income

shocks, particularly to poorer households

Anderloni et

al (2012)

Research in

Economics

Vulnerability indicator

researched (Italy)

DTI ratios are particularly influenced by financial

hardship, whereas house ownership decreases the value

of the vulnerability indicator

Dynan and

Kohn (2007)

Discussion paper

(Division of

Research &

Statistics and

Monetary Affairs)

Determinants of

indebtedness in the US

Increases in age and education seem to increase the

sample’s DTI ratios, mortgages also contributing to this

increase

Studies focused on Macroeconomic Shocks

Study Journal Variable of interest Main finding

Cloyne and

Surico (2014)

Working paper

(Bank of

England)

Effect of income taxes

on household

consumption and

indebtedness (UK)

Mortgages are primarily affected by changes to income

tax than outright house owners

Kick et al

(2014)

Working paper (

European

Central Bank)

Impact of economic

downturn on both

European households

and firms (Germany)

Shocks decrease the amount of asset concentration for

households, primarily risky assets

Tiongson et

al (2010)

Book, The World

Bank.

Identification of

transmission channels

for households

Three channels through which households are affected

are the labour market, product market and the financial

markets

EMPIRICAL FRAMEWORK

Assets Liabilities

Home ownership Credit card use

Deposit/savings accounts Overdraft account

Cash/Investment ISAs Mortgage loans

Fixed term investment

bonds

Company shares

Life insurance

• Based on Brown ands Taylor (2016) – Random effects probit estimation.

EMPIRICAL FRAMEWORK: FIRST STAGE (1)

By identifying the main instruments that households used, I computed the following equation:

𝑌𝑖𝑘 = 1 𝑋𝑖

′𝛽 + 𝜀𝑖 > 0 ,𝑤𝑖𝑡ℎ 𝑘 = 1,2… , 9.

where:

𝑌𝑖𝑘 represents the indicator variable corresponding to the

probability of the household using the instrument, i representing the household and k representing the instrument

𝑋𝑖′𝛽 is a vector of demographic related variables which

accounts for different characteristics of both the household and the household reference person (HRP).

𝜀𝑖 is the regression error term.

EMPIRICAL FRAMEWORK: FIRST STAGE (2)

Demographic variables

HRP

Age (banded)

Gender

Earnings (gross)

Degree

Married

EMPIRICAL FRAMEWORK: SECOND STAGE (1)

Debt to income ratios (DTI)

where 𝐷𝑇𝐼𝑖,𝑡 represents the DTI ratio for household i in time t ( which

corresponds to each wave respectively) , which is defined as the total amount of unsecured debt 𝑡𝑑𝑒𝑏𝑡𝑖,𝑡 over the total amount of

income per household 𝑡𝑖𝑛𝑐𝑜𝑚𝑒𝑖,𝑡 .

𝐷𝑇𝐼𝑖,𝑡 = 𝑡𝑑𝑒𝑏𝑡𝑖,𝑡𝑡𝑖𝑛𝑐𝑜𝑚𝑒𝑖,𝑡

DATA – WEALTH AND ASSETS SURVEY

Linkage within wave and across waves (cross sectional approach

vs. longitudinal approach)

Cross sectional weights used for calibration

Cross sectional approach used to obtain an aggregate amount of

instruments per household

DESCRIPTIVE STATISTICS: ALLOCATION STATISTICS

Variables Wave 1 Wave 2 Wave 3 Wave 4

Unsecured debt

Credit card 41.67% 11.81% 19.88% 17.46%

Overdraft accounts 5.89% 5.64% 5.66% 5.00%

Secured debt

Mortgage loan 43.82% 42.06% 40.37% 38.74%

Housing assets

Home ownership 87.84% 89.26% 84.29% 88.69%

Financial assets

Deposit/Savings account (Ind) 28.08% 31.23% 27.08% 28.48%

Cash/Investment ISA 28.16% 35.64% 33.98% 35.32%

Fixed term investment bonds 5.77% 9.37% 8.85% 7.36%

Shares (Both UK and foreign listed) 10.25% 11.73% 9.29% 9.62%

Another type of assets

Life insurance 14.33% 11.58% 9.59% 9.28%

ESTIMATION RESULTS: ASSET ALLOCATION ( WAVE 1)

Variables (M.E. and S.E.)

Financial instrument

Degree Male married Accom age1 age2 age3

Credit card use

.1378085 .023939 -.0137627 -.0236791 -.0604323 -.018985 .0256666

(.0155859) (.0148634) (.0153479) (.0273907) (.0238218) (.0204237) (.0219797)

Overdrawn account

-.0257398 -.0227651 -.0317027 .0401495 .1083711 .0847494 .052225

(.0134186) (.0130229) (.0131871) (.0224449) (.0218014) (.0194034) (.02056)

Mortgage Contract

.0426555 .0132785 .0547737 -.1428532 .4426007 .4143738 .3072365

(.0165193) (.0161132) (.0164192) (.029545) (.023244) (.0174944) (.0196782)

Savings/Dep

osit accounts

.11696 -.019953 -.1295698 -.064947 -.0982806 -.0829845 -.0690879

(.0180301) (.0178136) (.018209) (.0332484) (.0293676) (.0247288) (.0259804)

Individual

Savings Account

.0532211 -.0594673 .0259719 -.0330253 -.1431474 -.190092 -.0995285

(.018912) (.0185489) (.0192114) (.0353633) (.0302186) (.024902) (.0264737)

Fixed

investment Bonds

.0327963 .0111553 -.0046231 -.0169042 -.1434827 -.1009398 -.0587217

(.0105629) (.0104785) (.0108298) (.0218228) (.0202584) (.0136564) (.0131341)

Shares .121543 .0940361 -.0049569 -.0381271 -.2819949 -.142679 -.0519386

(.0163374) (.0163131) (.0171724) (.0329846) (.0281694) (.0216554) (.0225835)

Insurance -.0173924 .0385822 .0585415 .004888 .2773688 .24208 .1382457

(.0183145) (.0179296) (.0183568) (.0341927) (0284188) (.0231857) (.0248088)

Observations: 4369

ESTIMATION RESULTS: ASSET ALLOCATION (WAVE 2)

Variables

Financial instrument

Degree Male married accom age1 age2 age3

Credit card use .1746617 .0934278 .1479068 -.1075901 -.0359165 .0275575 .068041

(.0335945) (.0317391) (.033522) (.0676962) (.0520709) (.0454169) (.0482817)

Overdrawn account

-.0704858 .002388 .0149211 .1205721 .0982217 .0844741 .0372432

(.0252579) (.0218496) (.02367) (.0378751) (.0366437) (.0333078) (.0362341)

Mortgage Contract

.0117141 .0621037 .1015206 -.095159 .4302827 .3949629 .2701792

(.0309901) (.0285492) (.0301983) (.0569048) (.0402539) (.0329539) (.037769)

Savings/Deposit accounts

.083008 -.0540921 -.0756939 -.0477867 -.1055212 .0303186 -.0324495

(.0351855) (.0324919) (.0351355) (.0659609) (.0521841) (.0460826) (.0487918)

Individual

Savings Account

.1144313 -.0624114 .0227938 -.1300866 -.078604 -.0787167 -.0642499

(.0340502) (.0321705) (.0350263) (.0700141) (.0521075) (.0451778) (.0482118)

Fixed

investment Bonds

.0739036 .0108701 .0066391 -.0860016 -.1743109 -.1046042 -.0885621

(.0197396) (.0192131) (.0212218) (.0539869) (.0362957) (.0241132) (.0254674)

Shares .1447098 .0497331 .030367 -.0889873 -.2684404 -.1206342 -.0404922

(.0233041) (.0238167) (.0266223) (.0580268) (.0465875) (.030645) (.0316229)

Insurance -.0758046 -.0168418 .0611452 -.0002403 .2276711 .1907947 .0897643

(.0318707) (.0301393) (.0321679) (.0593516) (.0473164) (.0401719) (.0429996)

Observations: 902

ESTIMATION RESULTS: ASSET ALLOCATION (3)

Variables

Financial instrument

Degree Male married accom age1 age2 age3

Credit card use .1846797 .134704 .1236406 .2732648 -.0333663 -.0023902 .1161003

(.0422918) (.0402354) (.0442294) (.0953061) (.0679471) (.0583267) (.0583487)

Overdrawn account

.0063725 -.0193317 .004848 -.0740031 .1929625 .0936537 .0579415

(.0285112) (.0272329) (.029481) (.0716151) (.0470811) (.0453059) (.0469097)

Mortgage contract

.0307208 -.0413584 .13395 -.2561061 .4321105 .4071593 .3078242

(.0408681) (.0380418) (.0394475) (.0862111) (.0557852) (.0450981) (.048186)

Savings/Deposit accounts

.2322183 -.0145666 -.0558986 .0108579 -.0329882 -.0020891 -.0618397

(.0420103) (.0422423) (.0457101) (.0975332) (.0694019) (.0595266) (.0602135)

Individual Savings Account

.1933476 -.0670176 .086001 -.0510977 -.0826042 -.1327542 -.2088722

(.0404376) (.0406516) (.0444001) (.094585) (.0655962) (.0560079) (.0565288)

Fixed investment Bonds

.0514182 .001186 .0166822 -.0177927 -.1661474 -.1077486 -.096924

(.0238156) (.022776) (.0257593) (.056592) (.047197) (.0296401) (.0293761)

Shares

.0648646 .0693087 -.0654805 -.0713388 -.2434416 -.0631456 -.1073558

(.0277834) (.0269939) (.0283882) (.0751109) (.0610364) (.0332502) (.0357697)

Insurance -.0430561 -.0504775 -.0379392 .0213879 .1364777 .1626272 .1317854

(.0408417) (.0384909) (.0421448) (.090376) (.0617091) (.0521673) (.052862)

Observations: 541

ESTIMATION RESULTS: ASSET ALLOCATION (4)

Variables

Financial instrument

Degree Male married accom age1 age2 age3

Credit card use

.1879534 .131137 .1867185 -.0038731 -.0240231 -.063891 .0282569

(.0378968) (.0377877) (.0415819) (.0666216) (.0699616) (.0565773) (.0566038)

Overdrawn account

-.0572599 .0016053 -.0175197 -.0870026 .0745224 .0803969 .0231172

(.0290998) (.0269652) (.0294297) (.0589011) (.0497955) (.041612) (.043022)

Mortgage Contract

.04624 .0552967 .0678983 -.1770564 .3868818 .3822321 .2945896

(.0379007) (.0362241) (.0392849) (.058146) (.06027) (.045583) (.0472698)

Savings/Dep

osit accounts

.1598241 -.0539461 -.018606 -.0478786 -.0433379 -.0612053 -.0483008

(.0402696) (.0401625) (.0445143) (.0677934) (.0722954) (.0586716) (.0586145)

Individual

Savings Account

.1330649 -.0445459 .102522 -.0504833 -.0326238 -.1274564 -.1526584

(.0392126) (.0390915) (.0433284) (.0667315) (.0694445) (.0559693) (.0558138)

Fixed

investment Bonds

.0175493 .011899 .0510203 .0363446 -.1060881 -.1105654 -.0437617

(.0170271) (.0169296) (.0230459) (.0229416) (.0393649) (.0292611) (.0191437)

Shares .0819318 .0494611 .0483492 .0352762 -.273355 -.0791615 -.0158422

(.0261809) (.0262899) (.0307484) (.0434815) (.083004) (.0359081) (.0341476)

Insurance -.075526 .0084192 -.044142 -.0813933 .2751836 .1907191 .0894597

(.0366922) (.0361057) (.0403058) (.0601111) (.0652722) (.0493977) (.0492604)

Observations: 602

ESTIMATING THE EFFECT OF MACROECONOMIC

SHOCKS

Stage 3 estimation:

𝐷𝑇𝐼𝑖,𝑡 = 𝛽0 + 𝛽1𝑖𝑛𝑓𝑙𝑡 + 𝛽2𝑖𝑟𝑎𝑡𝑒𝑡 + 𝜀𝑖,𝑡

where 𝐷𝑇𝐼𝑖,𝑡 is defined as the DTI ratios obtained in the previous

step regressed with the general inflation level at time t 𝑖𝑛𝑓𝑙𝑡 and

the interest rate level 𝑖𝑟𝑎𝑡𝑒𝑡.

𝜀𝑖,𝑡 represents the regression’s error term.

ESTIMATION RESULTS: IMPACT OF MACROECONOMIC

SHOCKS (2)

Fig1: DTI ratio frequency over the sample.

ESTIMATION RESULTS: IMPACT OF MACROECONOMIC

SHOCKS (3)

Variables Coefficient Std. Error z P>|z|

Inflation -.0164325 .0468366 -0.35 0.726

Interest rate -.0001662 .0081979 -0.02 0.984

Constant .9722944 .1416598 6.86 0.000

𝜎𝜇=.31697399 𝜎𝑒=.60688668

CONCLUDING REMARKS

Refusal of life-cycle hypothesis.

Marriage doesn’t influence asset market participation.

More complex financial instruments overlooked.

No effect of inflation and interest rates on households.

NEXT STEPS…

Secured Access data (longitudinal purposes)

Exploring other transmission channels

Including financial literacy and exploiting possible regional

differences

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THANKS FOR YOUR ATTENTION!

PCARAN@ESSEX.AC.UK