Caste-gender intersectionalities in wheat-growing communities in Madhya Pradesh, India

Figures & data

Table 1. Respondent classification with respect to caste and age across the studies.

	Gennovate (2015; FGDs)	Qualitative Study (2019)	Quantiative household surveys (2019)
Number of participants
Overall
Male	25	36	413
Female	29	36	405
SC & ST
Male	8	7	132
Female	10	17	136
OMSC & NMC
Male	9	29	273
Female	9	19	277
Youth (<25 years of age)
Male	8	–	5^#
Female	10	–	14^#
Average age in years (range) of respondents
Overall
Male	38.4	49.0	46.8
	(17–55)	(30–70)	(22–84)
Female	30.1	48.3	44.1
	(16–55)	(17–80)	(20–85)
SC & ST
Male	49.1	56.3	45.8
	(39–55)	(35–80)	(23–75)
Female	36.6	41.7	43.3
	(39–55)	(30–60)	(21–85)
OMSC & NMC
Male	45.2	47.2	47.3
	(35–55)	(17–75)	(22–84)
Female	36.4	54.2	44.5
	(25–50)	(40–70)	(20–81)
Youth (<25 years of age)
Male	20.1	––	23.0^#
	(17–24)		(22–24)
Female	17.8	––	22.3^#
	(16–24)		(20–24)

^#Included also in different caste groups.

Table 2. Involvement and decision-making in different economic activities by gender and caste.

	Number [%] of respondents participated in the activity	Conditional on participation, the percentage of household in each caste category where decisions are made by
		Self				Spouse				Others^#
		Overall	SC&ST	OSMC	NMC	Overall	SC&ST	OSMC	NMC	Overall	SC&ST	OSMC	NMC
Self-involvement, according to female respondents (n = 413) in
Cash crops for markets	149 [36.1]	8.1	8.0	8.0	9.1	75.8	74.0	78.4	63.6	16.1	18.0	13.6	27.3
Livestock production	287 [69.5]	13.1	13.8	10.9	33.3	51.9	43.6	58.1	33.3	35.0	42.6	31.0	33.3
Food staples	400 [96.9]	7.6	8.5	7.1	8.3	59.4	54.6	62.9	50.0	33.0	36.9	30.0	41.7
Non-farm businesses	60 [14.5]	30.0	24.0	35.3	INO	41.7	52.0	35.3	INO	28.3	24.0	29.4	INO
Wage employment	80 [19.4]	26.3	36.7	20.0	INO	26.3	16.7	31.1	INO	47.4	46.6	48.9	INO
Self-involvement, according to male respondents (n = 405) in
Cash crops for markets	200 [49.4]***	79.4***	84.8***	76.8***	80.0***	4.0***	3.4***	4.8***	0.0***	16.6	11.9	18.4	20.0
Livestock production	281 [69.4]	53.8***	59.1***	50.9***	53.9	13.4***	14.0***	13.5***	7.7	32.8	26.9**	35.6	38.4
Food staples	398 [98.3]	73.8***	77.2***	72.4***	69.6***	3.6***	3.9***	3.7***	0.0***	22.6***	18.9***	23.9	30.4
Non-farm businesses	80 [19.8]**	65.0***	65.4***	64.0***	INO	10.0***	7.7***	12.0***	INO	25.0	26.9	24.0	INO
Wage employment	162 [40.0]***	60.0***	59.9***	63.7***	INO	9.4***	13.2***	6.3***	INO	30.6***	28.9*	30.0**	INO

^#“Others” category mostly includes parents, elder siblings, or other close relatives of male respondent or husband (in case of female respondents).

***,**, *: The difference with the male respondent group is statistically significant at 0.01, 0.05, and 0.10 levels, respectively.

INO: Insufficient number of observations.

Table 3. Association between decision-making on food crop production and decision-making on household expenditure by gender and caste.

	Involved in decision-making in food production, %		Not involved in decision-making in food production, %
	Participation in activities	Decision-making in activities, Self^#	Participation in activities	Decision-making in activities, Self^#
Self-involvement, according to female respondents (n = 400) in
Major household expenses
Overall	40.0	58.3	34.1	0.2***
SC & ST	45.5	60.0	37.7	2.2***
OMSC	41.1	57.1	32.3	1.4***
NMC	0.0	INO	31.8	0.0
Minor household expenses
Overall	93.3	78.6	97.8	31.1***
SC & ST	90.9	80.0	97.5	31.6***
OMSC	94.1	75.0	97.8	30.8***
NMC	100.0	80.0	INO	INO
Self-involvement, according to male respondents (n = 398), in
Major household expenses
Overall	57.6	86.8	31.5***	29.4***
SC & ST	57.1	83.9	29.0***	33.3***
OMSC	57.4	89.1	34.3***	29.2***
NMC	62.5	80.0	14.3**	INO
Minor household expenses
Overall	94.8	25.6	95.4	9.9***
SC & ST	93.9	23.9	100.0	17.2
OMSC	94.9	26.7	94.3	7.6***
NMC	100.0	25.0	85.7	0.0

^#Conditional on participation. ***,**: The difference with the decision-makers in food crop production is statistically significant at 0.01 and 0.05 levels respectively. INO: Insufficient number of observations.

Table 4. Factors affecting the probability of decision-making on crop production (food and cash crops) and off-farm employment activities by sample respondents.

	Probit models with sample selection
	Model 1	Model 2
I. Crop production (food and cash crops)
Women (=1 if respondent is women; = 0 otherwise)	−0.597***	−0.617***
	(0.028)	(0.030)
SC (=1 if respondent belongs to SC; = 0 otherwise)	0.017	0.033
	(0.070)	(0.074)
ST (=1 if respondent belongs to ST; = 0 otherwise)	0.038	0.080
	(0.048)	(0.059)
Women × SC (interaction term)	−0.192*	−0.197*
	(0.101)	(0.104)
Women × ST (interaction term)	0.029	0.057
	(0.075)	(0.079)
Household specific variables	No	Yes
District dummy variables	No	Yes
II. Off-farm employment
Women (=1 if respondent is women; = 0 otherwise)	−0.129***	−0.142***
	(0.019)	(0.021)
SC (=1 if respondent belongs to SC; = 0 otherwise)	−0.005	−0.002
	(0.045)	(0.031)
ST (=1 if respondent belongs to ST; = 0 otherwise)	0.087***	0.044*
	(0.034)	(0.026)
Women × SC (interaction term)	0.028	0.041
	(0.053)	(0.068)
Women × ST (interaction term)	−0.045	−0.020
	(0.031)	(0.030)
Household specific variables	No	Yes
District dummy variables	No	Yes

Notes: Dependent variable is binary in nature, which takes the value of 1 if farmer is responsible for the decision making and 0 otherwise. The marginal effects are reported with std. errors in parentheses. Due to small number of NMC respondents in the sample, it was clubbed with OSMC as reference category.

***,*: The marginal effects are statistically significant at 0.01 and 0.10 levels, respectively.