Does poverty affect divorce rates? The role of women’s income as moderating variable

Figures & data

Graph 1. The dynamic of divorce rate by provinces in Indonesia from 2010 to 2018.

Graph 2. The dynamic of the poverty rate across provinces in Indonesia from 2010 to 2018.

Table 1. The descriptive statistics and correlation matrix

Descriptive statistics
	Divorced rate(%)	Poverty rate(%)	Women’s income(%)
Mean	1.749	12.369	32.097
Median	1.670	11.195	33.005
Maximum	3.440	36.800	43.260
Minimum	0.980	3.910	20.580
Std. Dev.	0.478	6.456	4.633
Observations	288	288	288
Correlation matrix
Divorced rate	1.000
Poverty rate	−0.192	1.000
Women’s income	−0.070	0.143	1.000

Source: Author’s computation, 2021.

Table 2. The result of Chow Test and Hausman test

	Chow test				Hausman test
	Effect specification		Stat	p-value	Effect specification	X^2-Stat	p-value
Panelregression	Cross-Section Fixed Effects	Cross-section FCross-section X^2	61.704617.379	0.0000.000	Cross-Section Random Effects	20.901	0.000
	Effect specification		Stat	p-value	Effect specification	X^2-Stat	p-value
Panelmoderated regression	Cross-Section Fixed Effects	Cross-section FCross-section X^2	61.704618.709	0.0000.000	Cross-Section Random Effects	22.084	0.000

Source: Author’s computation, 2021.

Table 3. The result of the fixed-effect approach of panel linear regression and MRA

	Model 1			Model 2
	Estimate coefficient	t-statistic	p-value	Estimate coefficient	t-statistic	p-value
Constant	−5.299	−5.178	0.000	−9.466	−3.968	0.000
Logpov	0.041	0.486	0.627	1.689**	1.970	0.049
logWI	1.656***	6.604	0.000	2.861***	4.257	0.000
logPov*logWI				−0.476*	−1.931	0.055
Effects Specification: Cross-section fixed
R^2	: 0.887			: 0.889
Adjusted-R^2	: 0.873			: 0.874
F-stat	: 60.619			: 59.578
Prob(F-stat)	: 0.000			: 0.000
DW-stat	: 1.606			: 1.623
Residual normality
Jarque-Bera	0.359(0.836)			0.025(0.987)

Source: Author’s computation, 2021.

Note: Numbers in parenthesis are p-value, * is significant at 90% level; ** significant at 95% level; and *** significant at 99% level.

Table 4. The result of panel Granger causality test

Endogenous variables	Exogenous variables
	Lag length of 1			Lag length of 2
	logPR	logDR	logWI	logPR	logDR	logWI
logPR	-	[2,606](0,108)	[3,092](0,079)*	-	[2,229](0,110)	[1,598](0,205)
logDR	[1,241](0,266)	-	[0,269](0,605)	[4,306](0,015)**	-	[0,049](0,953)
logWI	[2,972](0,086)*	[0,506](0,478)	-	[1,129](0,325)	[0,409](0,664)	-
	Lag length of 3			Lag length of 4
	logPR	logDR	logWI	logPR	logDR	logWI
logPR	-	[2,351](0,074)*	[1,551](0,203)	-	[0,685](0,603)	[1,288](0,277)
logDR	[1,412](0,241)	-	[0,252](0,860)	[0,616](0,652)	-	[1,437](0,224)
logWI	[1,272](0,286)	[0,309](0,818)	-	[2,961](0,022)**	[2,177](0,074)*	-

Source: Author’s computation, 2021.

Note: The values in parentheses () are p-value, the values in bracket [] are chi-square. * and ** indicate the significant at 90% and 95% levels, respectively.

Figure 1. The direction of causality relationship between variables.