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Table 26 Robustness check for impact of receiving SSS payouts on total expenditure

From: The effect of non-contributory pensions on labour supply and private income transfers: evidence from Singapore

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIABLES

No leads

Balanced

Ethnic trends

Flat-type trends

Age FE

WIS/ GST

Abadie

1-1 matching

Received SS × Jan

–

9.866

16.57

10.13

9.867

17.50

117.0

–

–

(106.1)

(102.9)

(109.9)

(104.9)

(103.3)

(130.8)

–

Received SS × Feb

–

164.0

170.3

176.2

169.7

143.6

135.7

–

–

(118.0)

(115.1)

(122.9)

(117.4)

(114.6)

(88.12)

–

Received SS × Mar

–

229.0

232.0

249.6

223.1

186.1

245.0*

–

–

(181.2)

(179.8)

(192.1)

(179.4)

(118.7)

(136.4)

–

Received SS × Jan–Mar

–

–

–

–

–

–

–

187.36**

–

–

–

–

–

–

–

P = 0.053

Received SS × announce-to-pay

36.41

91.26

97.47

93.36

91.64

91.10

109.2

158.21*

(75.78)

(96.35)

(93.59)

(99.24)

(95.07)

(88.30)

(68.02)

P = 0.086

Received SS × post-pay

57.10

111.8

115.6

122.8

109.4

91.88

145.6**

170.22*

(72.68)

(93.40)

(91.45)

(95.32)

(91.94)

(89.12)

(69.20)

P = 0.065

Observations

15,970

15,671

15,970

15,970

15,970

11,171

1466

368

R-squared

0.384

0.384

0.386

0.391

0.385

0.501

–

–

  1. Notes:
  2. 1Standard errors clustered at the household level in parentheses. ***, **, and * represent statistical significance at the 1, 5, and 10% level of significance respectively
  3. 2All expenditure values are reported at the couple (respondent and spouse if respondent is married) and monthly level. Total expenditure excludes cash gifts
  4. 3Columns (1)–(8) show results from additional robustness checks carried out. These checks are: (1) removal of the lead terms; (2) restricting the sample to a “balanced” panel, where each individual has at least one observation in the pre-announcement, announcement-to-disbursement, and post-disbursement periods; (3) allowing for ethnicity-specific time fixed effects; (4) allowing for flat-type-specific time fixed effects; (5) adding age fixed effects as a control; (6) adding receipt of additional welfare payments (Workfare Income Supplement; GST Vouchers) as a control—sample is smaller because this data is not collected every wave and not everyone responds every wave; (7) reweighting each observation by their propensity of receiving SSS as in Abadie (2005); and (8) DiD matching with a 1-1 nearest neighbour match. Eq. (1) describes the baseline model used in these checks
  5. 4For columns (1)–(6), the sample is restricted to respondents who are age-eligible for SSS (i.e. aged 65 and above in 2016), Singapore citizens, live in public housing flats, and with a propensity score of 0.2–0.8. The number of observations in these columns refers to the number of individual-month observations. For columns (7) and (8), the number of observations refers to number of respondents, and the sample is not restricted by the propensity score. The sample, however, is smaller than the full sample due to data availability issues specific to the estimation of (7) and (8)
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