Sarah Brown and Karl Taylor University of Sheffield, IZA Open Seminar in Eesti Pank, April 2017

1. Sarah Brown and Karl Taylor
University of Sheffield, IZA
April 2017

2.  Since 2008, concern amongst policy-makers
over household financial vulnerability.
 Many households hold low levels of savings to
fall back on during times of financial adversity.
 Issues for both the short-term and the long-
term.
 In the UK, the household saving rate has halved
since the middle of 2010 from 11.5% to 5.8% in
the fourth quarter of 2015 (ONS, 2016).

3.  A commonly held view is that individuals are
not saving enough.
 Garon (2012) comments that, in the U.S., ‘it
has become painfully clear that millions lack
the savings to protect themselves against
foreclosures, unemployment, medical
emergencies, and impoverished retirements.’
 UK policies such as automatic pension
enrolment and schemes like ‘Help to Save’
announced in the 2016 budget, are designed
to encourage saving.

4.  Evidence from the Money Advice Service
indicates that 4/10 working-age individuals
in the UK <£100 in savings at a given point in
time.
 In NI, WM, Yorkshire and Humberside, NE and
Wales, more than half the adult population
has savings below that level.
 The research also showed that some people
on low incomes do save money.
 Roughly 1/4 adults with household incomes
<£13,500 have more than £1,000 in savings.

5.  Saving is clearly constrained by income and
financial commitments, including debt servicing.
 Understanding the saving behaviour of
individuals and, in particular, that of the low-
paid, is important from a societal perspective.
 It is important to understand the consequences
of a lack of saving for future financial wellbeing,
as a lack of savings may, for example, lead to
debt accumulation if households are forced to
borrow to deal with unforeseen events.

6.  Investigate the determinants of saving and
private pension contributions over two
decades:
◦ Static and dynamic modelling;
◦ Incidence and amounts;
◦ Role of financial expectations; and
◦ Role of low pay (limited attention so far)
Precautionary saving: households hold a contingency
fund in case of adverse future events, Keynes (1936).

7.  Consider whether saving or employee pension
contributions are a buffer against future financial
hardship.
 Gjertson (2016) presents evidence, based on a
small non-representative sample of low-paid US
households, supporting a protective role for
small amounts of saving for future financial
hardship.
◦ RE and FE count models;
◦ Types of financial problem incurred.

8.  The BHPS is a random sample survey, carried out by the
Institute for Social and Economic Research, of each adult
member from a nationally representative sample of more
than 5,000 private households (yielding approximately
10,000 individual interviews).
 Participants live in Scotland, Wales, Northern Ireland and
England and the BHPS covered the period 1991 to 2008.
 Understanding Society replaced the BHPS after 2008.
 In wave 1 of Understanding Society, over 50,000 individuals
were interviewed between 2009 and 2011, correspondingly
in wave 4 (last one we use) over 47,000 individuals were
interviewed between 2012 and 2014.
 Both surveys contain information about people’s social and
economic circumstances, attitudes, behaviours and health.

9.  Our sample is aged from 25 to 59;
 Focus upon employed individuals only;
 NT = 85,994; N = 14,071 (individuals);
 T = 1991 to 2013/14.
 Information on:
◦ Savings (including amount);
◦ Employee private pension contributions (including
amount);
◦ Financial expectations;
◦ Detailed socio-economic characteristics.

10.  Our measure of monthly saving is based on
the responses to the following question:
 “Do you save any amount of your income, for
example, by putting something away now and
then in a bank, building society, or Post
Office account other than to meet regular
bills? About how much, on average, do you
manage to save a month?”

11.  Information is also available on monthly
private pension contributions:
 “Other than your main employer or
occupational pension scheme, are you
currently a member of any personal pension
scheme or do you currently contribute to any
personal pension scheme? Please include any
Additional Voluntary Contribution scheme
you may belong to.”
 A monthly amount of private pension
contributions is calculated.

12. 102030405060
%
1990 1995 2000 2005 2010
year
% save % pension
% save and pension % no save or pension
Types of saving

13. 2468
%
1990 1995 2000 2005 2010
year
save/income pension/income
(save+pension)/income
Saving as a proportion of income

14.  Looking ahead, how do you think you will be
financially a year from now, will you be:
 Worse off
 About the same
 Better off (i.e. financially optimistic)
Used in previous literature on household
finances: Brown et al. (2005, 2008): more
financially optimistic take on more debt.

15.  Low pay is defined at the individual level
(below 2/3 median gross weekly pay from
ASHE).
 The Annual Survey of Hours and Earnings
(ASHE) is the most comprehensive source of
earnings information on the structure and
distribution of earnings in the UK.
 ASHE is based on a 1% sample of employee
jobs taken from HM Revenue & Customs
(HMRC) PAYE records.

16. 20253035
%lowpay
65707580
%notoptimistic
1990 1995 2000 2005 2010
year
% not optimistic % in low pay
Not financially optimistic and low pay

17. 404550556065
%
1990 1995 2000 2005 2010
year
% save&pen - optimistic % save&pen - not optmistic
% save&pen - in low pay % save&pen - not in low pay
Saving and pension by sub-samples

18. NO PRIVATE
PENSION
PRIVATE
PENSION
NO SAVING 43.8% 4.9%
SAVES 44.1% 7.1%

19.  , binary variable which indicates whether
the individual saves, denotes the individual
and denotes time.
 Dynamic model (Wooldridge, 2005):

20.  Control variables in :
 Indicator of being in low pay at t-1;
 Indicator of not being financially optimistic;
 Gender; Marital Status; Age; Education
(degree, A levels, GCSE, other qualification);
Number of children in household; Number of
adults in household; Housing tenure (own
home outright, own home with mortgage,
rent); Self-reported health status; Region;
Month of interview; Years.

21. Random Effects Probit Model: Probability of saving on a
monthly basis
Key
Variables
M.E. T-stat M.E. T-stat
Not
optimistic
0.0277 6.78 0.0263 5.79
Low paidt-1 -0.0440 6.51 -0.0303 4.21
Savedt-1 - - 0.2176 50.75

22. Random Effects Probit Model: Prob. of saving – year effects
STATIC MODEL DYNAMIC MODEL
M.E. T-Stat M.E. T-Stat
1994 -0.0040 0.39 -0.0082 0.71
1995 -0.0123 1.16 -0.0119 1.02
1996 -0.0105 1.01 -0.0061 0.55
1997 0.0213 1.75 0.0274 2.22
1998 0.0248 2.01 0.0227 1.83
1999 -0.0052 0.60 -0.0101 0.90
2000 0.0121 0.83 0.0191 1.49
2001 0.0024 0.01 0.0046 0.27
2002 0.0045 0.13 0.0118 0.83
2003 0.0059 0.20 0.0131 0.88
2004 -0.0026 0.44 0.0051 0.24
2005 -0.0001 0.27 0.0107 0.63
2006 -0.0228 1.75 -0.0129 1.07
2007 -0.0104 0.93 0.0053 0.19
2008 -0.0280 2.94 -0.0145 2.12
2010 0.0467 2.07 0.0675 3.57
2012 0.0252 0.42 0.0309 1.05

23. Random Effects Probit Model: Probability of saving on a
monthly basis
Key
Variables
M.E. T-stat M.E. T-stat
Not
optimistic
0.0268 6.44 0.0253 5.59
Y < 25th -0.1350 13.25 -0.1276 11.49
Y 25th to 50th -0.0809 10.37 -0.0757 8.89
Y 50th to 75th -0.0424 7.12 -0.0387 5.96
Savedt-1 - - 0.2155 50.53

24. Random Effects Probit Model: Probability of making a
monthly private pension contribution
Key
Variables
M.E. T-stat M.E. T-stat
Not
optimistic
-0.0079 2.88 -0.0075 2.77
Low paidt-1 -0.0125 2.70 -0.0124 2.37
Pensiont-1 - - 0.1161 39.82

25. Random Effects Probit Model: Prob. of pension contribution – year effects
STATIC MODEL DYNAMIC MODEL
M.E. T-Stat M.E. T-Stat
1994 -0.0101 1.84 -0.0144 2.42
1995 -0.0119 2.10 -0.0152 2.49
1996 -0.0276 4.69 -0.0352 5.59
1997 -0.0259 4.32 -0.0250 3.99
1998 -0.0319 5.17 -0.0353 5.55
1999 -0.0497 7.53 -0.0553 8.23
2000 -0.0593 8.73 -0.0594 8.82
2001 -0.0779 10.82 -0.0779 11.09
2002 -0.0838 11.12 -0.0795 11.02
2003 -0.0900 11.28 -0.0833 11.07
2004 -0.1017 11.96 -0.0929 11.73
2005 -0.1162 12.80 -0.1083 12.87
2006 -0.0826 8.93 -0.0666 8.01
2007 -0.0946 9.65 -0.0888 10.05
2008 -0.0959 9.30 -0.0857 9.31
2010 -0.1079 8.93 -0.0981 8.99
2012 -0.1227 9.48 -0.1158 9.94

26.  denotes the amount the individual
saves/income.
 Dynamic model (Wooldridge, 2005):

27. Random Effects Tobit Model: Log (saving on a monthly
basis / income)
Key
Variables
M.E. T-stat M.E. T-stat
Not
optimistic
0.0655 7.00 0.0550 5.90
Low paidt-1 -0.0780 5.07 -0.0677 4.40
Savedt-1 - - 0.2175 51.90

28. Random Effects Tobit Model: log (saving/income) – year effects
STATIC MODEL DYNAMIC MODEL
M.E. T-Stat M.E. T-Stat
1994 -0.0180 0.74 -0.0282 1.16
1995 -0.0330 1.32 -0.0313 1.27
1996 -0.0225 0.89 -0.0141 0.57
1997 0.0378 1.46 0.0403 1.62
1998 0.0478 1.82 0.0356 1.44
1999 -0.0247 0.90 -0.0344 1.34
2000 0.0003 0.01 0.0142 0.56
2001 -0.0121 0.42 -0.0073 0.28
2002 -0.0057 0.19 0.0088 0.33
2003 -0.0118 0.37 0.0010 0.04
2004 -0.0332 0.99 -0.0191 0.66
2005 -0.0335 0.95 -0.0106 0.35
2006 -0.0873 2.35 -0.0619 1.99
2007 -0.0647 1.66 -0.0284 0.87
2008 -0.1079 2.62 -0.0727 2.14
2010 0.0132 0.28 0.0574 1.46
2012 -0.0206 0.40 0.0130 0.31

29. Random Effects Tobit Model: Log (saving on a monthly
basis / income)
Key
Variables
M.E. T-stat M.E. T-stat
Not
optimistic
0.0646 6.90 0.0544 5.83
Y < 25th -0.1628 7.04 -0.1332 5.79
Y 25th to 50th -0.1112 6.37 -0.0849 4.88
Y 50th to 75th -0.0659 5.03 -0.0476 3.63
Savedt-1 - - 0.2172 51.85

30. Random Effects Tobit Model: Log (monthly private
pension contribution / income)
Key
Variables
M.E. T-stat M.E. T-stat
Not
optimistic
-0.0107 2.54 -0.0105 2.51
Low paidt-1 -0.0124 1.71 -0.0188 2.62
Pensiont-1 - - 0.0779 30.19

31. Random Effects Tobit Model: Log (pension/income) – year effects
STATIC MODEL DYNAMIC MODEL
M.E. T-Stat M.E. T-Stat
1994 -0.0185 1.95 -0.0193 2.07
1995 -0.0239 2.42 -0.0212 2.21
1996 -0.0498 4.87 -0.0500 5.05
1997 -0.0471 4.46 -0.0368 3.67
1998 -0.0627 5.72 -0.0530 5.18
1999 -0.0917 7.82 -0.0794 7.33
2000 -0.1088 8.94 -0.0889 8.08
2001 -0.1425 10.98 -0.1185 10.23
2002 -0.1541 11.26 -0.1221 10.15
2003 -0.1638 11.25 -0.1275 10.07
2004 -0.1872 12.02 -0.1441 10.74
2005 -0.2166 13.01 -0.1694 11.87
2006 -0.1593 9.27 -0.1052 7.28
2007 -0.1839 10.08 -0.1367 8.92
2008 -0.1861 9.67 -0.1313 8.17
2010 -0.2149 9.54 -0.1551 8.19
2012 -0.2426 9.86 -0.1807 8.77

32.  From 1996, 8 types of financial hardship over
time:
◦ paying for their accommodation;
◦ loan repayment;
◦ keeping their home adequately warm;
◦ been able to pay for a week’s annual holiday;
◦ replace worn-out furniture;
◦ been able to buy new, rather than second-hand,
clothes;
◦ been able to eat meat, chicken, fish every second
day; and
◦ been able to have friends or family for a drink or
meal at least once a month.

33.  Person in household responsible for
financial decisions.
 Typically head of household, .
 Aged from 25 to 59;
 Employed heads of household;
 NT = 34,496; N = 8,285 (households);
 T = 1996 to 2013/14.

37.  is number of financial problems.
 =1 if saved in t-1, 0=otherwise.
 =1 if low paid in t, 0=otherwise.
 Additional control variables in :
 Gender; Marital Status; Age; Education (degree, A
levels, GCSE, other qualification); labour income;
non-labour income; Number of children in
household; Number of adults in household;
Housing tenure (own home outright, own home
with mortgage, rent); Self-reported health status;
Region; Month of interview; Years.

38. Count Model: Number of Financial Problems
INCLUDE INCOME – WHETHER SAVE
Fixed Effects Random Effects
Key Variables COEF T-stat COEF T-stat
Savingt-1 -0.1210 3.67 -0.3030 10.67
Low paid 0.0128 0.26 0.0368 0.84

39. Count Model: Number of Financial Problems
INCLUDE INCOME – WHETHER PENSION
Fixed Effects Random Effects
Key Variables COEF T-stat COEF T-stat
Pensiont-1 0.0286 0.53 -0.0762 1.68
Low paid 0.0143 0.28 0.0378 0.86

40. Fixed Effects Count Model: Number of Financial Problems
EXCLUDE INCOME – WHETHER SAVE
Fixed Effects Random Effects
Key Variables COEF T-stat COEF T-stat
Savingt-1 -0.1228 3.72 -0.3497 12.28
Low paid 0.0739 2.57 0.2203 5.58

41. Fixed Effects Count Model: Number of Financial Problems
EXCLUDE INCOME – WHETHER PENSION
Fixed Effects Random Effects
Key Variables COEF T-stat COEF T-stat
Pensiont-1 0.0280 0.52 -0.1012 2.22
Low paid 0.0760 2.61 0.2309 5.81

42. Fixed Effects Count Model: Number of Financial Problems
INCLUDE INCOME – LOG AMOUNT SAVED
Fixed Effects Random Effects
Key Variables COEF T-stat COEF T-stat
Log Savingt-1 -0.0347 4.72 -0.0817 13.36
Low paid 0.0133 0.26 0.0409 0.94

43. Fixed Effects Count Model: Number of Financial Problems
INCLUDE INCOME – LOG AMOUNT
PENSION
Fixed Effects Random Effects
Key Variables COEF T-stat COEF T-stat
Log Pensiont-1 0.0056 0.44 -0.0215 2.05
Low paid 0.0142 0.28 0.0381 0.87

44. Fixed Effects Count Model: Number of Financial Problems
INCLUDE INCOME – PENSION AND/OR
SAVINGS
Key Variables COEF T-stat COEF T-stat
Low paid 0.0130 0.26 0.0133 0.27
Savingt-1 -0.1216 3.68 - -
Pensiont-1 0.0343 0.63 - -
Log Savingt-1 - - -0.0348 4.73
Log Pensiont-1 - - 0.0074 0.58

45. Random Effects Count Model: Number of Financial
Problems
INCLUDE INCOME – PENSION AND/OR
SAVINGS
Key Variables COEF T-stat COEF T-stat
Low paid 0.0363 0.83 0.0407 0.93
Savingt-1 -0.3017 10.63 - -
Pensiont-1 -0.0612 1.36 - -
Log Savingt-1 - - -0.0813 13.29
Log Pensiont-1 - - -0.0169 1.62

46. 


47. 1. Accommodation – FE Probit Model: Saving
Whether saved t-1 Amount saved t-1
Key
Variables
M.E. T-stat M.E. T-stat
Savingt-1 -0.0065 3.13 -0.0003 3.18
Low paid 0.0038 1.19 0.0006 0.81

48. 1. Accommodation – FE Probit Model: Private Pension
Whether pension t-1 Amount pension t-1
Key
Variables
M.E. T-stat M.E. T-stat
Pensiont-1 0.0003 0.75 0.0001 0.41
Low paid 0.0003 0.76 0.0003 0.75

49. 2. Loan repayment – FE Probit Model: Saving
Whether saved t-1 Amount saved t-1
Key
Variables
M.E. T-stat M.E. T-stat
Savingt-1 -0.0042 2.38 -0.0019 2.86
Low paid -0.0040 1.82 -0.0206 2.12

50. 2. Loan Repayment – FE Probit Model: Private Pension
Whether pension t-1 Amount pension t-1
Key
Variables
M.E. T-stat M.E. T-stat
Pensiont-1 0.0010 0.12 0.0005 0.27
Low paid -0.0256 2.56 -0.0222 2.13

51.  Effect of saving on financial hardship varies
by type of problem faced;
 Same pattern of results as above found for
affording holidays and new furniture;
 No effects from saving or pensions found for
the probability of reporting problems with:
keeping home warm; new clothes;
 Very small protective effect for saving is
found for ability to afford meat; entertain
friends/family.

52.  Our findings suggest that financial pessimism
is positively associated with active saving and
negatively associated with private pension
contributions;
 Being in low pay is inversely associated with
both types of saving;
 Evidence of persistence in saving behaviour;
 Evidence supports a protective role for saving
with lagged saving being inversely associated
with current financial problems.

53. Five main areas to develop:
 Future research will explore the effects of
subjective measures of job (in)security;
 Accuracy of financial expectations;
 Eligibility and membership of occupational
pension schemes;
 Dynamic zero-inflated Bayesian models of
financial problems;
 Interaction of saving behaviour between
household members;

54.  Employed couples.
 Unit of observation head of household i.e. person
responsible for making financial decisions.
 NT = 21,876; N = 5,681
 Controls as previous, , but now condition on:
◦ Whether head in low pay;
◦ Whether spouse in low pay;
◦ Whether both head and spouse in low pay;
◦ Saving of head and spouse – amounts and whether save

55. Count Model – Poisson Number of Problems
Whether saved by
head and/or
spouse t-1
Amount saved by
head and/or
spouse t-1
Key Variables M.E. T-stat M.E. T-stat
Savingt-1 -0.3095 7.99 -0.0879 11.19
Low paid head 0.1990 1.82 0.1925 1.77
Low paid spouse 0.1750 3.70 0.1548 3.29
Both low paid 0.0786 0.62 0.0911 0.72

56. Count Model – Poisson Number of Problems
Whether saved by
head and/or
spouse t-1
Amount saved by
head and/or
spouse t-1
Key Variables M.E. T-stat M.E. T-stat
Savingt-1 head -0.2167 5.17 -0.0020 9.75
Savingt-1 spouse -0.2233 4.93 -0.0024 2.27
Low paid head 0.1686 1.49 0.1842 1.69
Low paid spouse 0.1482 3.00 0.1815 3.86
Both low paid 0.1180 0.91 0.0873 0.69