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Table 3 Regression results of elderly support expenditure on different types of consumption

From: The crowding-out effect of elderly support expenditure on household consumption from the perspective of population aging: evidence from China

Variable

con

ccr

mcr

(1)

(2)

(3)

(4)

(5)

(6)

FE

GMM

FE

GMM

FE

GMM

pod

−0.3826c (− 5.64)

−0.30464c (− 9.88)

−0.3637c (− 5.59)

−0.5008b (− 2.03)

−0.2537c (− 5.26)

2.5472c (10.96)

pcai

−0.00003 (− 0.02)

0.0023c (2.74)

−0.0061c (− 3.15)

−0.0051c (− 7.67)

0.0061c (4.76)

0.0028c (4.52)

scale

−0.0076c (− 3.22)

−0.0075c (− 6.64)

0.0083c (3.70)

0.0024c (2.68)

− 0.0007 (− 0.48)

0.0051 (5.96)

gen

0.0022 (0.27)

0.0059b (1.75)

−0.0092 (− 1.21)

− 0.0074c (− 2.73)

0.007 (1.41)

0.0015 (0.58)

mar

0.0024 (0.31)

0.0072a (1.82)

0.0007 (0.1)

−0.0025 (− 0.79)

−0.0031 (− 0.69)

−0.0047 (− 1.57)

house

−0.0092 (− 1.26)

−0.0075c (− 2.78)

−0.0216c (− 3.29)

−0.0077c (− 3.56)

0.0308c (6.00)

0.0152c (7.49)

old

−0.182c (− 5.27)

0.0052b (2.39)

0.0249c (7.81)

0.0107c (6.16)

−0.0067c (− 3.00)

− 0.0158c (− 9.72)

Intercept term

0.6944c (30.42)

0.7447c (61.68)

0.2785c (12.26)

0.3011c (31.1)

−0.0074 (− 0.5)

−0.0457b (−5.02)

Instrument variable

edu

age

Weak IV test

128.915

128.915

128.915

Sargan P-value

0.5102

0.2570

0.7394

Sample size

27,264

27,264

27,264

27,264

27,264

27,264