Is policy convergence required to improve women’s empowerment in agriculture? Evidence from West Bengal

Figures & data

Table 1. Sample profile.

Description	Female percentage of sample (n = 350)^a	Male percentage of sample (n = 184)^a	Total percentage of sample (n = 534)^a
Total sample responses	65.5	34.4	100
Managed own farm	29.14	51.65	36.84
Tenant farmer	11.71	3.30	8.83
Managed own farm and tenant farmer	11.71	14.29	12.59
Worked on a small farm (less than 2 ha)	98	94.05	96.99
Have access to a tubewell (for drinking water)	12.32	12.15	12.26
Connected to the electricity grid	99.71	100	99.81

Note: ^aRespondents could select more than one response, that is, select all that apply.

Table 2. Notable descriptive responses by gender.

Description	Female percentage of sample (n = 350)^a	Male percentage of sample (n = 184)^a	Total percentage of sample (n = 534)^a
Household head	8.00	75.54	31.27
Spouse of household head	83.14	1.09	54.87
Married	95.71	87.43	92.87
Engaged in unpaid farm/household work	39.10	Nil
Operated a pump set(s)	33.70	91.20	57.19
Owned a pump set(s)	34.83	54.14	44.76
Member of a community groups	45.38	34.25	41.56

Table 3. Survey sample breakdown of how respondents access water for irrigation by gender.

Response	Female percentage of sample (n = 344)^a	Male percentage of sample (n = 181)^a	Total percentage of sample (n = 525)^a
Own pump set(s)	39.83	54.14	44.76
Jointly owned pump set(s)	5.81	4.42	5.33
Community owned pump set(s)	6.98	10.50	8.19
Hired pump set(s)	15.12	5.52	11.81
Buy water	29.36	24.31	27.62
Canal water	2.91	1.10	2.29

Note: ^aRespondents could select more than one response, that is, select all that apply.

Table 4. Community, farm and household decision-making by gender.

Decision-making questions	Response	Female percentage of sample (n = 350)^a	Male percentage of sample (n = 184)^a	Total percentage of sample (n = 534)
Do you feel that a [man/woman] like yourself can generally change things in the community where you live if s/he wants to?	No, not at all	59.31	42.54	53.58
	Yes, but with great difficulty	29.80	42.54	34.15
	Yes, but with a little difficulty	9.46	14.36	11.13
	Yes, fairly easily	0.86	0.55	0.75
	Yes, very easily	0.57	Nil	0.38
Do you feel comfortable speaking up in public to help decide on infrastructure (like roads, small wells, water pumps, water supplies) to be built in your community?	No, not at all	40.11	20.99	33.58
	Yes, but with difficulty	40.97	45.86	42.64
	Yes, comfortable	18.91	33.15	23.77
Are you a member of any group or organization in your community?	Yes	45.38	34.25	41.56
Who in your household makes decisions related to productive resources (i.e., use of land, livestock, water, technology, etc.)?	Both self and spouse	42.77	22.65	35.86
	Male in household	37.86	40.33	38.71
	Female in household	6.94	0.55	4.75
Who in your household makes decisions related to farm income and spending?	Both self and spouse	48.27	20.44	38.71
	Male in household	35.26	39.23	36.62
	Female in household	6.36	1.10	4.55
Who in your household makes decisions related to household income and spending?	Both self and spouse	60.69	38.67	53.13
	Male in household	23.70	24.86	24.09
	Female in household	6.07	2.21	4.74
Who in your household makes decisions related to how your time is spent?	Both self and spouse	55.65	4.97	38.21
	Male in household	3.48	91.16	33.69
	Female in household	39.71	Nil	26.03

Note: ^aChi-squared tests comparing responses from women and men all report p ≤ 0.2.

Table 5. Ordered logistic regression: women speaking up about public infrastructure (model 1).

	Coefficient	SE	Z-statistic
Women own and operate pump set(s)	0.689**	(0.305)	2.46
Women who hire pump set(s)	−0.540	(0.329)	−1.64
Women who buy water	0.464*	(0.258)	1.80
Women who use canal water	−0.918	(0.720)	−1.27
Women part of community groups	0.861***	(0.214)	4.01
Cut points
${\kappa }_1$	0.086	(0.193)
${\kappa }_2$	2.11	(0.230)
Model statistics
LL	−341.57
Observations	343
LR Chi^2	35.17
Prob > Chi^2	<0.001
McFadden’s pseudo-R^2	0.049

Note: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 6. Ordered logistic regression: women’s perceived ability of making changes in their community (model 2).

	Coefficient	SE	Z-statistic
Women own and operate pump set(s)	0.508	(0.316)	1.61
Women who hire pump set(s)	−0.371	(0.356)	−1.04
Women who buy water	0.108	(0.280)	0.39
Women who use canal water	−1.542	(1.089)	−1.41
Women part of community groups	1.142***	(0.230)	4.97
Cut points
${\kappa }_1$	0.939	(0.214)
${\kappa }_2$	2.79	(0.267)
${\kappa }_3$	4.97	(0.497)
${\kappa }_4$	5.89	(0.739)
Model statistics
LL	−314.90
Observations	343
LR Chi^2	34.46
Prob > Chi^2	<0.001
McFadden’s pseudo-R^2	0.053

Note: ***p < 0.01, **p < 0.05, *p < 0.1.

Table A1. Ordered logistic regression: men speaking up about infrastructures.

	Coefficient	SE	Z-statistic
Men operate a pump	0.826	(0.618)	1.34
Men who hire a pump	−0.751	(0.908)	−0.83
Men who buy water	0.165	(0.660)	0.25
Men who use canal water	−1.006	(0.708)	−1.42
Men part of community groups	0.139	(0.298)	0.47
Cut points
$k_1$	−0.757	(0.608)
$k_2$	1.389	(0.615)
Model statistics
LL	−189.21
Observations	185
LR Chi^2	9.89
Prob > Chi^2	0.079
McFadden’s pseudo-R^2	0.026

Table B1. Ordered logistic regression: men’s perceived ability of making changes in their community.

	Coefficient	SE	Z-statistic
Men operate a pump	01.2248*	(0.650)	1.88
Men who hire a pump	−0.276	(0.928)	−0.30
Men who buy water	0.493	(0.698)	0.71
Men who use canal water	1.768	(1.314)	1.34
Men part of community groups	0.378	(0.301)	1.25
Cut points
$k_1$	0.714	(0.643)
$k_2$	2.822	(0.675)
$k_3$	6.373	(1.193)
Model statistics
LL	185.715
Observations	185
LR Chi^2	14.20
Prob > Chi^2	0.014
McFadden’s pseudo-R^2	0.037