Policy innovations for pro-poor climate support: social protection, small-scale infrastructure, and active citizenship under India’s MGNREGA

Figures & data

Figure 1. Map of the study area (base map from Google Earth; imagery from Google, Maxar Technologies, CNES/Airbus).

Figure 2. Precipitation trends, (A) pre-monsoon and (B) monsoon months (source NASA TRMM_3B43 dataset, 2011).

Figure 3. Count of main project types in the dataset.

Figure 4. 79% of water projects report improving water availability for drinking, domestic use, irrigation, or livestock.

Figure 5. The canal was desilted and widened to improve water flow.

Figure 6. The upper layer of the retaining wall was repaired following damage of a storm, helping to ensure continued water availability downstream.

Figure 7. (A) Total labour days for men and women, (B) median labour days (for those who had received labour), and (C) the proportion of households who have received labour from each gender in the primary data.

Figure 8. (A) Proportion of households who have received labour and (B) Median labour days of those who have received labour from different social groups (2010–2012).

Figure 9. Boxplot of the relationships between total labour days and number of projects that a household has benefitted from.

Table 1. Summary of variables for analysis of household project benefits (1400 households nested in 35 villages).

Variables	Mean	Range	Std. Dev.
Main indicator of household benefits:
Number of labour days a household has received (2010–2012)	81.6	0–300	83.3
Number of MGNREGA projects a household has benefitted from	2.03	0–5	1.26
Household socio-economic characteristics:
Household size (number of persons)	5.13	1–18	2.06
Below poverty line (BPL) (0 = no; 1 = yes)	.15	0–1
Low caste (0 = no; 1 = yes)	.334	0–1
Household member with some college education (0 = no; 1 = yes)	.336	0–1
Proportion of house rooms made of concrete (as opposed to mud)	.370	0–1	.414
Landholding size (in bighas)*	7.02	0–90	7.00
Months of food consumption per year from own land	4.70	0–12	3.57
Steady income from salary or job-related pension (0 = no; 1 = yes)	.591	0–1
Patterns of political engagement:
Number of civic institutions that household is a member of	1.45	0–5	.891
Household interaction with elected Pradhan (1 = low, 2 = medium, 3 = high)	2.60	1–3	.541
Conflict between elected panchayat members (0 = no; 1 = yes)^a	.743	0–1
Proportion of households in attendance at panchayat meetings** ^a	.289	.137–.576	.085
Effective number of candidates standing for panchayat election*** ^a	2.90	1.49–4.82	.751
Positive relationship of panch. leaders with bureaucratic staff (0 = no; 1 = yes)^a	.886	0–1
Block level dummy variable: Lambagaon = 0; Baijnath = 1
All models also include a panchayat-level random intercept

^aPanchayat-level variable (all others measured at household level).

*Land units measured in Bighas; 5 Bighas = 1 acre.

**Proportion in attendance overaged over two years.

***Total number of candidates standing for pradhan, weighted by vote share (following Laakso & Taagepera, 1979). Averaged over two election cycles.

Table 2. Hurdle model part 1: Binary logit model to predict a non-‘0’ value (indicating that a household has received at least some benefits).

Variables	Labour benefits	Project benefits
Household socio-economic characteristics:
Household size	−0.0082 (0.0362)	−0.1087* (0.0497)
Below poverty line (BPL)	1.551*** (0.2651)	0.1393 (0.2908)
Low caste	0.7146*** (0.1663)	0.4996(*) (0.2581)
College education	−0.8126*** (0.1602)	−0.2176 (0.2274)
Proportion of concrete rooms	−0.8393*** (0.1800)	−0.1204 (0.2802)
Log of landholding size	−0.1291 (0.1366)	−0.3542(*) (0.1969)
Subsistence consumption	0.0362 (0.0308)	0.1063* (0.0444)
Steady income	−1.662*** (0.1830)	−0.2650 (0.2665)
Patterns of political engagement:
Number of civic institutions	0.0844 (0.0917)	0.4168** (0.1296)
Interaction with elected Pradhan	0.0215 (0.1594)	0.3248 (0.2101)
Conflict between elected authorities	0.5482(*) (0.3327)	1.080(*) (0.5635)
Attendance at village meetings	4.676** (1.716)	1.190 (3.008)
Effective number of candidates	0.3726* (0.1810)	0.2194 (0.3105)
Positive relationship with technical staff	0.3523 (0.3817)	2.601*** (0.6864)
Block level dummy	0.3650 (0.3104)	−2.520*** (0.5810)

Note: Model includes a panchayat-level random intercept. Coefficients reported with standard errors in parentheses.

(*)p < .10; *p < .05; **p < .01; ***p < .001.

Table 3. Hurdle model part 2: Count model with truncated General Poisson Distribution.

Variables	Labour benefits	Project benefits
Household socio-economic characteristics:
Household size	0.0042 (0.0086)	−0.0024 (0.0065)
Below poverty line (BPL)	0.1187** (0.0426)	0.0833* (0.0352)
Low caste	0.0988** (0.0355)	0.0554* (0.0276)
College education	−0.0411 (0.0413)	−0.0839** (0.0290)
Proportion of concrete rooms	−0.0964* (0.0442)	−0.0584(*) 0.0321
Log of landholding size	−0.0253 (0.0345)	0.0292 (0.0249)
Subsistence consumption	−0.0007 (0.0076)	0.0027 (0.0056)
Steady income	−0.2247*** (0.0386)	−0.1283*** (0.0282)
Patterns of political engagement:
Number of civic institutions	0.0603** (0.0218)	0.1016*** (0.0159)
Interaction with elected Pradhan	0.0657 (0.0400)	0.1634*** (0.0294)
Conflict between elected authorities	−0.0997 (0.1022)	0.2746** (0.1051)
Attendance at village meetings	0.9301(*) (0.4838)	0.5045 (0.5035)
Effective number of candidates	0.0466 (0.0572)	0.0788 (0.0587)
Positive relationship with technical staff	−0.1174 (0.1229)	0.1191 (0.1252)
Block level dummy	−0.3379*** (0.0892)	−0.0155 (0.0911)

Note: Model includes a panchayat-level random intercept; coefficients reported with standard errors in parentheses.

(*)p < .10; *p < .05; **p < .01; ***p < .001.

Tropical Rainfall Measuring Mission (TRMM). (2011). TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC). Retrieved from January 11, 2019.

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Laakso, M., & Taagepera, R. (1979). “Effective” number of parties: A measure with application to West Europe. Comparative Political Studies, 12(1), 3–27.

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