Impact of energy affordability on the decision-making of rural households in ecologically fragile areas of Northwest China regarding clean energy use

Table 6 Logistic model regression results in decision-making regarding clean energy use for heating

Variable	Model I		Model II		Model III		Model IV
Variable	B	EXP (B)	B	EXP (B)	B	EXP (B)	B	EXP (B)
Income growth	0.055*** (0.002)	1.057	0.058*** (0.002)	1.060
Subsidy growth					0.145*** (0.005)	1.156	0.156*** (0.005)	1.169
Gender			0.135** (0.068)	1.144			0.065 (0.066)	1.067
Age			− 0.097* (0.055)	0.907			− 0.092* (0.053)	0.912
Education			− 0.147** (0.073)	0.864			− 0.067 (0.071)	0.936
Family size			− 0.005 (0.022)	0.995			0.036 (0.022)	1.037
Income type			0.137*** (0.047)	1.146			0.166*** (0.045)	1.181
Income-level			0.530*** (0.039)	1.699			0.587*** (0.038)	1.799
Time dummy variables (2021 as reference)
Year-2022	− 2.362*** (0.101)	0.094	− 2.415*** (0.109)	0.089	2.510*** (0.106)	0.081	− 2.633*** (0.115)	0.072
Area dummy variables (with reference to rural areas in the ecologically fragile region of the Loess Plateau)
Rural Northwest Arid Desert Ecologically Vulnerable Area	0.783*** (0.081)	2.187	0.769*** (0.086)	2.158	0.769*** (0.080)	2.158	0.811*** (0.086)	2.251
Rural areas in the ecologically fragile region of the Tibetan Plateau	− 0.695*** (0.098)	0.499	− 1.181*** (0.113)	0.307	− 0.270*** (0.086)	0.763	− 0.728*** (0.101)	0.483
Cox and Snell R²	0.225		0.257		0.266		0.308
Nagelkerke R²	0.329		0.375		0.371		0.430

*, * *, * * * indicate the 10, 5, and 1% significance levels, respectively; standard errors are in parentheses. The unit of income and subsidy growth is 100 yuan, and the estimated coefficient in the report represents the impact of an increase of 100 yuan in income and subsidies on the probability of households opting for clean energy

ISSN: 2192-0567