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Saving Behaviour, Expectations and Future Financial Hardship

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

Published in: Economy & Finance
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Saving Behaviour, Expectations and Future Financial Hardship

  1. 1. Sarah Brown and Karl Taylor University of Sheffield, IZA April 2017
  2. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 12. 102030405060 % 1990 1995 2000 2005 2010 year % save % pension % save and pension % no save or pension Types of saving
  13. 13. 2468 % 1990 1995 2000 2005 2010 year save/income pension/income (save+pension)/income Saving as a proportion of income
  14. 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. 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. 16. 20253035 %lowpay 65707580 %notoptimistic 1990 1995 2000 2005 2010 year % not optimistic % in low pay Not financially optimistic and low pay
  17. 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. 18. NO PRIVATE PENSION PRIVATE PENSION NO SAVING 43.8% 4.9% SAVES 44.1% 7.1%
  19. 19.  , binary variable which indicates whether the individual saves, denotes the individual and denotes time.  Dynamic model (Wooldridge, 2005):
  20. 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. 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. 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. 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. 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. 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. 26.  denotes the amount the individual saves/income.  Dynamic model (Wooldridge, 2005):
  27. 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. 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. 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. 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. 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. 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. 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.
  34. 34.  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.
  35. 35. 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
  36. 36. 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
  37. 37. 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
  38. 38. 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
  39. 39. 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
  40. 40. 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
  41. 41. 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
  42. 42. 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
  43. 43.  
  44. 44. 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
  45. 45. 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
  46. 46. 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
  47. 47. 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
  48. 48.  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.
  49. 49.  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.
  50. 50. 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;
  51. 51.  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
  52. 52. 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
  53. 53. 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

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