Gender differences in willingness to pay for capital-intensive agricultural technologies: the case of fish solar tent dryers in Malawi

Agricultural and Food Economics

Table 1 Descriptive statistics of fish processors in Mangochi and Salima districts in Malawi

Variable	Female (n = 220)		Male (n = 162)		Whole sample (n = 382)
Variable	Mean	Std. dev.	Mean	Std. dev.	Mean	Std. dev.
Dependent variables
Level of WTP (MK)	15,379.55	19,906.70	16,990.88	19,119.52	16,062.88	19,567.59
Willing to pay (1/0)	0.76	0.43	0.72	0.45	0.74	0.44
Explanatory variables
Age (years)	37.482	11.095	37.815	10.440	37.623	10.809
Married (1/0)	0.768	0.423	0.877	0.330	0.814	0.390
Education attainment (count)	2.723	1.098	3.259	1.214	2.950	1.177
Processing site market (1/0)	0.086	0.282	0.074	0.263	0.081	0.273
Local market (1/0)	0.050	0.218	0.062	0.241	0.055	0.228
Distant market (1/0)	0.836	0.371	0.858	0.350	0.846	0.362
Own savings account (1/0)	0.359	0.481	0.370	0.484	0.364	0.482
Knowledge	0.159	0.367	0.123	0.330	0.144	0.352
Self-income decisions (1/0)	0.345	0.477	0.525	0.501	0.421	0.494
ln (fishing assets)	2.266	4.986	3.490	5.920	2.785	5.428
ln (processing assets)	8.259	3.619	7.253	5.127	7.832	4.345
Madzedze	0.427	0.496	0.154	0.362	0.312	0.464
Malembo	0.173	0.379	0.352	0.479	0.249	0.433
Msaka	0.309	0.463	0.160	0.368	0.246	0.431
Chikombe	0.005	0.067	0.136	0.344	0.060	0.238
Lifuwu	0.086	0.282	0.198	0.399	0.134	0.341