Table 3.

Factors that are associated with support for subsidy reform: logistic regression estimation results.

	(1)	(2)	(3)
	est1	est2	est3
Queue	1.006	1.000	1.014
	(0.146)	(0.143)	(0.145)
Paid more than the fixed price	1.679∗∗∗	1.698∗∗∗	1.658∗∗∗
	(0.207)	(0.215)	(0.213)
No availability	1.655∗∗∗	1.669∗∗∗	1.672∗∗∗
	(0.252)	(0.254)	(0.252)
General trust in federal government	1.003	1.068	0.969
	(0.106)	(0.116)	(0.103)
Approval of performance by President Buhari		0.927∗∗	0.918∗∗
		(0.032)	(0.031)
Corruption			0.568∗∗∗
			(0.057)
Lack of capacity			0.731∗∗∗
			(0.081)
Opinion about services in the area: Electricity supply	1.082∗∗	1.083∗∗	1.082∗∗
	(0.034)	(0.034)	(0.034)
Opinion about services in the area: Bus services	1.087∗∗∗	1.088∗∗∗	1.072∗∗
	(0.031)	(0.031)	(0.030)
Quality of government services provided by State Govnmt compared to 3 yrs ago	1.036	1.053	1.031
	(0.059)	(0.060)	(0.059)
Membership of religious group	1.192∗∗	1.185∗∗	1.176∗
	(0.103)	(0.102)	(0.101)
Understanding of subsidy granted	0.946	0.958	0.953
	(0.084)	(0.085)	(0.085)
Size of impact of 2016 fuel price increase	0.951	0.950	0.969
	(0.034)	(0.033)	(0.034)
Observations	12,213	12,185	12,185

Robust standard errors clustered at the enumeration area in parentheses.

Region dummies are included in models.

We report the estimated coefficients and standard errors transformed to odds ratios.

Results for control variables in models are omitted.

*p ¡ 0.10, **p ¡ 0.05, ***p ¡ 0.01.