The Effect of Free Personal Care
for the Elderly on Informal Caregiving
Sarah Karlsberg Schaffer
Workshop on the Economics...
Agenda
•

Introduction & background to policy of Free Personal Care
(FPC) for elderly

•

Modelling framework: preference ...
Introduction
•

2002: Scotland introduces FPC for elderly

•

Forms natural experiment
−

Allows difference-in-differences...
Background to policy
•

1999: Scottish devolution

•

2002: Scottish parliament introduces FPC for elderly (aged
65+) in n...
Modelling framework (1)
•
•

Model focuses on trade-off between labour supplied for
informal care versus other uses of car...
Modelling framework (2)
•

Additional assumptions:
−
−

No formal care at home before policy change

−

Ignore other uses ...
Pre-policy solutions

16/12/2013
The shift in the PPF

16/12/2013
Post-policy solutions

16/12/2013
Data
•

British Household Panel Survey (BHPS): 1996–2008

•

Survey asks:
−
−
−

Do you provide co-residential care?
Do yo...
Participation: methodology
•
•

p∗ = δt + φS + 𝛄𝛄(t ∗ S) + α𝑋𝑋𝑖𝑖 𝑖𝑖 + εit
it
Probit and LPM regressions
−
−

p∗ = latent p...
Participation: results
(1)
Probit

(2)
Probit

(3)
LPM

(4)
LPM

0.0514***

0.0480***

0.0522***

0.0487***

(3.29)

(3.22...
Participation: interpretation
•

Similar results across specifications: policy associated
with an increase in care partici...
Intensity: methodology
•
•

p∗ = δt + φS + γ(t ∗ S) + α𝑋𝑋𝑖𝑖 𝑖𝑖 + εit
it

This time, define p∗ as set of 6 binary indicator...
Intensity: results
(1)

(3)

(4)

(5)

(6)

(7)

Participation
Treat

(2)
5+

10+

20+

35+

50+

100+

0.0480***

0.0273*...
Intensity: interpretation
•

Increase in probability of supplying 5+ hours of ~ 3
percentage points

•

No statistically s...
Conclusions
•

Concern that policy would “crowd out” informal care

•

This paper finds opposite effect
−
−
−

•

Those wh...
About OHE
To enquire about additional information and analyses, please contact Sarah Karlsberg Schaffer at
sschaffer@ohe.o...
Upcoming SlideShare
Loading in...5
×

The Effect of Free Personal Care for the Elderly on Informal Caregiving

441

Published on

Sarah Karlsberg Schaffer presents her comprehensive analysis based on a “natural experiment”: the introduction of free personal care for the elderly that was implemented in Scotland in 2002, but not elsewhere in the UK.

Published in: Health & Medicine
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
441
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Transcript of "The Effect of Free Personal Care for the Elderly on Informal Caregiving"

  1. 1. The Effect of Free Personal Care for the Elderly on Informal Caregiving Sarah Karlsberg Schaffer Workshop on the Economics of Long-Term Care Brocher Foundation Geneva • 16-17 December 2013
  2. 2. Agenda • Introduction & background to policy of Free Personal Care (FPC) for elderly • Modelling framework: preference of carers • Data: British Household Panel Survey, 1996–2008 • Results − Participation in informal care − Intensity of informal care • Conclusions & discussion 16/12/2013
  3. 3. Introduction • 2002: Scotland introduces FPC for elderly • Forms natural experiment − Allows difference-in-differences approach to be used, with rest of UK (RUK) as control group • This study: what was the effect of this policy on the supply of informal care? • Informal care: care provided by friends or family for free • Around 6.5 million informal carers in the UK • Definitions: − Caregiver = carer/child − Care recipient = caree/parent 16/12/2013
  4. 4. Background to policy • 1999: Scottish devolution • 2002: Scottish parliament introduces FPC for elderly (aged 65+) in nursing home or in own home • No change to RUK policy • Personal care defined by Scottish Executive as: − • Flat rate payment of £145 per week − • “… care which relates to the day to day physical tasks and needs of the person cared for (for example, … eating and washing) and to mental processes related to those tasks (for example, … remembering to eat and wash)” Additional £65 per week if in nursing home Popular policy with high and increasing costs 16/12/2013
  5. 5. Modelling framework (1) • • Model focuses on trade-off between labour supplied for informal care versus other uses of carer’s time “Child’s” utility function: 𝑢𝑢 𝑐𝑐 = 𝑢𝑢 𝑐𝑐 (𝑢𝑢 𝑝𝑝 , 24 − ℎ) − − • 𝑢𝑢 𝑝𝑝 = “parent’s” utility ℎ = hours of informal care Parent’s utility function: − − � 𝑝𝑝 𝑖𝑖 𝑖𝑖 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟 𝑟𝑟𝑟𝑟 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑖𝑖 𝑖𝑖 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 ℎ𝑜𝑜𝑜𝑜𝑜𝑜 𝑢𝑢 𝑁𝑁 𝑢𝑢 𝑝𝑝 = � 𝐻𝐻 𝑢𝑢 𝑝𝑝 ℎ, 𝑓𝑓 𝑖𝑖 𝑖𝑖 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟 𝑟𝑟𝑟𝑟 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑎𝑎𝑎𝑎 ℎ𝑜𝑜𝑜𝑜𝑜𝑜 𝑓𝑓 = hours of formal care 𝐻𝐻 𝜕𝜕2 𝑢𝑢 𝑝𝑝 𝜕𝜕ℎ2 < 0: diminishing returns of hours of informal care 16/12/2013
  6. 6. Modelling framework (2) • Additional assumptions: − − No formal care at home before policy change − Ignore other uses of carer’s time (e.g. labour supply) − • No informal care in nursing home Ignore money (& thus ability to buy additional care in home) Child chooses 𝑚𝑚𝑚𝑚𝑚𝑚 𝑢𝑢 𝑐𝑐 𝑢𝑢 𝑝𝑝 ℎ∗ , 0 , ℎ∗ , 𝑢𝑢 𝑐𝑐 � 𝑝𝑝 , 0 , where ℎ∗ is 𝑢𝑢 𝑁𝑁 the utility-maximising ℎ, given the choice of 𝐻𝐻 16/12/2013
  7. 7. Pre-policy solutions 16/12/2013
  8. 8. The shift in the PPF 16/12/2013
  9. 9. Post-policy solutions 16/12/2013
  10. 10. Data • British Household Panel Survey (BHPS): 1996–2008 • Survey asks: − − − Do you provide co-residential care? Do you provide extra-residential care? How many hours of care do you provide per week? – Intervals of 0-4, 5-9, 10-19, 20-34, 35-49, 50-99, 100+ • Combine two types of care (helps with small Scottish sample size) • No information on age of caree − Most common carer-caree relationship is between middleaged children and parents − Sample: aged 45+, no children in household 16/12/2013
  11. 11. Participation: methodology • • p∗ = δt + φS + 𝛄𝛄(t ∗ S) + α𝑋𝑋𝑖𝑖 𝑖𝑖 + εit it Probit and LPM regressions − − p∗ = latent probability that individual i supplies care in it period t t = observation from 2002 or later 𝑋𝑋𝑖𝑖 𝑖𝑖 = vector of personal characteristics − S = observation from Scotland − 𝛄𝛄 = difference in differences coefficient of interest − 16/12/2013
  12. 12. Participation: results (1) Probit (2) Probit (3) LPM (4) LPM 0.0514*** 0.0480*** 0.0522*** 0.0487*** (3.29) (3.22) (3.40) (3.34) -0.0111 -0.0122 -0.0111 -0.0123 (-0.78) (-0.87) (-0.78) (-0.90) -0.0155** -0.0135** -0.0154** -0.0126* (-2.35) (-1.98) (-2.35) (-1.92) Observations 60122 55155 60122 57424 R2 /Pseudo R2 0.000 0.017 0.000 0.119 No Yes No Yes Treat Scotland After Controls Marginal effects; t statistics in parentheses. * p<0.10, ** p<0.05, *** p<0.01. 16/12/2013
  13. 13. Participation: interpretation • Similar results across specifications: policy associated with an increase in care participation of ~5 percentage points • Perhaps surprising… but interpret in context of model − Suggests some individuals had preferences similar to those represented by blue indifference curves − Before policy: max utility by providing no care − After policy: max utility by supplementing care supplied by state − Policy allowed more elderly people to stay in their own homes 16/12/2013
  14. 14. Intensity: methodology • • p∗ = δt + φS + γ(t ∗ S) + α𝑋𝑋𝑖𝑖 𝑖𝑖 + εit it This time, define p∗ as set of 6 binary indicators: it − Probability of supplying 5+, 10+, 20+, 35+, 50+, 100+ hours per week • Avoids problems of selection bias & data intervals • Allows identification of distributional effects 16/12/2013
  15. 15. Intensity: results (1) (3) (4) (5) (6) (7) Participation Treat (2) 5+ 10+ 20+ 35+ 50+ 100+ 0.0480*** 0.0273** 0.0086 0.0014 -0.0001 -0.0007 -0.0011 (-0.01) (-0.13) (-0.23) 0.0127** 0.0108** 0.0094** (3.22) (2.45) (0.94) (0.07) -0.0122 0.0086 0.0117 0.0146** (-0.87) (0.80) (1.36) (2.26) (2.51) (2.31) (2.15) -0.0135** 0.0023 0.0045 0.0026 0.0024 0.0017 0.0018 (-1.98) (0.44) (1.04) (0.73) (0.81) (0.64) (0.73) Obs 55155 55729 55729 55715 55701 55701 55668 Pseudo R2 0.017 0.061 0.070 0.089 0.110 0.114 0.117 Yes Yes Yes Yes Yes Yes Yes Scotland After Controls Probit marginal effects; t statistics in parentheses. * p<0.10, ** p<0.05, *** p<0.01. 16/12/2013
  16. 16. Intensity: interpretation • Increase in probability of supplying 5+ hours of ~ 3 percentage points • No statistically significant results elsewhere in distribution (negative trend appearing  possible “income effect”) • Those who entered care supply did so at low end of distribution • Suggests move from tails to middle of distribution 16/12/2013
  17. 17. Conclusions • Concern that policy would “crowd out” informal care • This paper finds opposite effect − − − • Those who entered care supply did so at low end of distribution − • Evidence that formal and informal care act as complements (not substitutes) in this case Special circumstances: policy increased state provision of care in the home Estimated 90,000 people opting into care supply Potentially substantial welfare gains, assuming 𝐻𝐻 𝜕𝜕2 𝑢𝑢 𝑝𝑝 𝜕𝜕ℎ2 <0 Whether gains outweigh costs is a topic for future work 16/12/2013
  18. 18. About OHE To enquire about additional information and analyses, please contact Sarah Karlsberg Schaffer at sschaffer@ohe.org To keep up with the latest news and research, subscribe to our blog, OHE News. Follow us on Twitter @OHENews, LinkedIn and SlideShare. The Office of Health Economics is a research and consulting organisation that has been providing specialised research, analysis and expertise on a range of health care and life sciences issues and topics for 50 years. OHE’s publications may be downloaded free of charge for registered users of its website. Office of Health Economics Southside, 7th Floor 105 Victoria Street London SW1E 6QT United Kingdom +44 20 7747 8850 www.ohe.org ©2013 OHE 16/12/2013

×