1. Informal Caregiving
Formal Employment

2. The Relationship between Caregiving & Employment
Delayed Retirement
Aging Population
Caregiving ?
Aging population  postponed retirement & increasing demand of caregiving
Yet postponed retirement may hurt caregiving

3. The Relationship between Caregiving & Employment
The majority of the literature
Delayed Retirement
Aging Population
Caregiving
This study
The Relationship between Caregiving & Employment
Aging population  postponed retirement & increasing demand of caregiving
Yet postponed retirement may hurt caregiving

4. Findings
Work hours %
the probability of informal care percentage points
A. Formal employment reduces the probability of informal caregiving.
A.Formal employment reduces the probability of informal caregiving.
Among women of prime caregiving age, working 10% more hours per week reduces the probability of providing informal care by about 2 percentage points.
B. The effects are stronger when care recipients are household members and when caregiving is more time-intensive.
B.The effects of formal employment on caregiving are heterogeneous.

5. Data & Sample
SIPP – 1996, 2001, 2004
working-age female respondents who are at prime caregiving age (40-64 years old).

6. ——IV Probit Model Model
Pr(care_hoursist > 0)=Φ(δ0 +δ1ln(work_hoursist +1)+δ2Xist +δ3Wst + vs +ηt)
Unemployment rate

7. u A. Instrumental variable (IV) ? Problem: Endogeneity
——IV Probit Model:
Model
A. Instrumental variable (IV)
? Problem: Endogeneity
Y – Caregiving
X – Working hours
u – Unobservable individual
characteristics (error term)
Endogeneity u

8. u Z A. Instrumental variable (IV) √ Solution: X ——IV Probit Model:
Y – Caregiving
X – Working hours
u – Unobservable individual characteristics
Z – State-level unemployment rate (Instrumental variable)
Z must be highly correlated with X; Z must not be correlated with u.

9. B. Probit Model ? Problem: √ Solution: ——IV Probit Model: Model
Many people do not play the role of caregivers
(too many observations of 0 in weekly caregiving time)
√ Solution:
Caregiving hours  whether provide informal care or not

10. ——IV Probit Model:
Model
B. Probit Model

11. Results
To check the strength of the instrumental variable.

12. Results Independent Variable Strong Instrument -- Dependent Variable
log(work_hours+1)
-- Dependent Variable

13. Results
To check the strength of the instrumental variable.
 Large F-statistics indicate a strong instrument.

14. Results
To check the strength of the instrumental variable.
 Large F-statistics indicate a strong instrument.
To estimate the effect of weekly work hours on the probability of providing informal care.

15. Results Independent Variable Care -- Dependent Variable
-Endogeneous Variable
-Instrumental Variable

16. Results
To check the strength of the instrumental variable.
 Large F-statistics indicate a strong instrument.
To estimate the effect of weekly work hours on the probability of providing informal care.
 Probit produces a larger impact, yet loses significance.

17. Results
Workers & non-workers
Only workers ?

18. Results
To check the strength of the instrumental variable.
 Large F-statistics indicate a strong instrument.
To estimate the effect of weekly work hours on the probability of providing informal care.
 Probit produces a larger impact, yet loses significance.
 Imprecise, yet still consistent.

19. Robustness Check
Varying the definitions of
Formal employment
Informal caregiving

20. The strength of the instrument is considerably reduced.
Robustness Check
The strength of the instrument is considerably reduced.

21. the probability of informal caregiving
Conclusion
Formal employment
reduces
the probability of informal caregiving

22. Conclusion
Instrument for individual formal employment using state-level unemployment rates.
Results with consistency. √ ?
A very strong impact. (approximately 8% to 10%) -- Sample
Lack of precision. -- Instrumental variable