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52

Appendix A: Theoretical Framework of Delay in Payments
The theoretical framework can be conceptualized as follows.

Consider M amount of money has to be disbursed by the BPM but she
holds it for time period, t before distributing it to the beneficiaries.
Hence her earnings is the interest earned given by I(t) = M (1+r )t – M,
where r is the interest rate and r > 0. Here I(t) is a convex function of t.
Now consider that the probability of the BPM being caught and punished
is given by p(t), where p'(t)>0, p''(t)>0, and p(t) → 1 for large t. The fine
imposed is also assumed to be a function of t and is denoted by
F(t) such that F'(t) > 0 and F" (t) > 0. Hence the expected fine at t would
be p(t) x F(t). The BPM would delay till time period, t if I(t)> p(t)x F(t)
The graphical representation of the same looks as follows:
Figure A1: Theoretical Framework of Delay in Payments

I (t),
P(t), F (t)

Here we consider two situations: pre-intervention and post-
intervention periods, denoted by the subscript 1 and 2 respectively. t1*
is the equilibrium time period till when would the BPM hold the money
that needs to be distributed in the absence of treatment. Since the
intervention essentially increases the level of p(t), there would be an
inward shift of p(t) x F (t) as well and hence t2* would be the new
equilibrium during the intervention, which would shift towards left as
the number of list pasting in the GPs increases.

53

Figure B1: Kernel density plots

We plot a set of Kernel density plots for the treated and control
GPs for a number of GP level indicators as shown below. The plots
clearly indicate close match of these characteristics between the
intervention and control GPs.

54

Table B1: Basic characteristics of the selected blocks

Block Proportion Proportion Proportion of Proportion
of SC of literates agricultural of casual
laborer

Damaragidda 0.185 0.439 0.181 0.208
Maddur 0.164 0.459 0.160 0.167
Hanwada 0.147 0.489 0.222 0.143
Koilkonda 0.133 0.507 0.238 0.160

Notes: This data is presented as given in Census (2011). (https://censusindia.gov.in/
2011-common/censusdata 2011.html (accessed on July 2, 2020). SC stands for
scheduled caste. The four blocks were situated in the Mehbubnagar district of
Telangana.

55

Table B2: Difference between the resurveyed and non-resurveyed
households

Variables Not Mean Resur- Mean Mean

resur veyed differ-
veyed
house ence
in
holds in (2) – (4)
endline
endline

(1) (2) (3) (4) (5)

Select outcome variables and household characteristics

Work entitlement 92 0.685 1352 0.632 0.052

Work application 92 0.207 1352 0.237 -0.031

Unemployment allowance 92 0.033 1352 0.048 -0.015

Payment duration 92 0.152 1352 0.104 0.048

Wage rate 92 0.033 1352 0.037 -0.004

Job card update by 65 0.246 992 0.298 -0.052

Field Assistant

Got receipt of application 92 0.217 1352 0.180 0.037

Travelled more than 92 0.880 1352 0.866 0.014

once for wages

Attended Gram 87 0.299 1281 0.335 -0.036

Sabha meeting

Attended social 91 0.165 1341 0.192 -0.028

audit meetings

Raised issues on 92 0.076 1352 0.095 -0.019

MGNREGA

Non cemented house 92 0.413 1352 0.385 0.028

Gender of the respondent 84 1.512 1352 1.488 0.024

Education of the 84 0.571 1347 0.868 -0.296

respondent

MGNREGA work days 84 25.09 1347 28.99 -3.893

of the respondent

Occupation: agriculture 92 0.815 1352 0.797 0.018

worker

Occupation: casual laborer 92 0.707 1352 0.696 0.011

Scheduled Caste/ 92 0.315 1352 0.258 0.057

Scheduled Tribe

Livestock 92 0.989 1352 1.457 -0.468**

Watches Television 92 0.522 1349 0.560 -0.039

Flush toilet 92 0.207 1352 0.245 -0.038

Cont'd.....

56

Government/Private toilet 92 0.293 1352 0.246 0.048

Main water source 92 0.935 1352 0.918 0.017
Main cooking source 92 0.098 1352 0.107 -0.009

Number of boys 92 0.891 1351 0.967 -0.076

Number of girls 92 0.913 1352 0.757 0.156

Note: This table is based on the surveyed baseline data conducted from
September to October, 2017. Mean difference test using ttest command

in STATA 14 is used for computation. *** p<0.01, ** p<0.05, * p<0.1.

Table B3: Kolmogorov Smirnov tests

Variables Combined K-S P-value
From survey statistic
0.966
Average proportion of Scheduled Castes 0.142 0.989
0.572
Average proportion of Upper Castes 0.127 0.418
0.572
Average ownership of mobile phones 0.224 0.304
0.973
Education of FA 0.253
0.973
Average GP level days of work 0.224 0.779
0.594
Average GP level delay in payments 0.278 0.981
0.525
Average GP level delay in payorder generation 0.139
From Census 2011

Total number of households 0.141

Total SC population 0.192

Total female population 0.225

Distance from the nearest town 0.092

Distance from the block office 0.232

Note: We perform the Kolmogorov-Smirnov (K-S) test to examine if the
distributions of the two groups are equal separately for both, treated and control
GPs. The null hypothesis is both the groups are equal and we are unable to reject the
null for the all the variables presented. We used data from Census 2011 (https://
censusindia.gov.in/2011-common/censusdata2011.html-(accessed on July 2, 2020))
as well as baseline survey data conducted from September to October, 2017. SC
stands for Scheduled Caste; FA for Field Assistant and GP or Gram Panchayat. The
command ksmirnov in STATA 14 is used to obtain the K-S statistics and p-values.

Table B4: Placebo test

Awareness indicators

Work Work Unemployment Payment Wage rate Delay

entitlement application allowance duration compensation

(1) (2) (3) (4) (5) (6)

Fake randomized treatment 0.013 0.006 -0.003 0.017 0.008 0.015
(0.020) (0.013)
(0.030) (0.043) (0.010) (0.032)

Process mechanism and meeting attendance indicators

Jobcard Got receipt Travelled more Attendance Attendance Raised

update by for work than once in GS in social issue on

FA for wages meetings audit meetings MGNREGA

(1) (2) (4) (5) (6) (7)

Fake randomized treatment 0.006 0.01 -0.011 0.059* 0.017 -0.027
(0.057) (0.033) (0.032) (0.033) (0.034) (0.027)

Note: The following control variables have been incorporated in all the regressions: respondent gender, age education, SC/ST, number of
adults in the household, type of house (non-cemented or not), land cultivated in acre, total number of livestock (cows, bullocks and oxen),
whether household has a toilet in the household and if its members watches TV along with main occupation of the household and block
dummies. The regressions have been run on sampled jobcards from all the control GPs. The marginal effects from ANCOVA pooled probit
regression are reported and the bootstrapped standard errors clustered at the GP level are reported in parenthesis. *** p<0.01, ** p<0.05,

*p<0.

57

58

Table B5: Heterogeneous impact for mobile phone owners and literate
(Impact on uptake)

Impact on Impact on
literates mobile phone

owners

Treatment 0.153 0.204
Post (0.263) (0.319)
Literate -0.396*** -0.372**
Post*Treatment (0.150) (0.163)
Literate*Treatment -0.539**
Literate*Post (0.256) -0.192
Literate*Post*Treatment -0.253 (0.227)
Mobile*Treatment (0.208)
Mobile*Post 0.077 -0.083
Mobile*Post*Treatment (0.309) (0.239)
0.327 0.081
(0.231) (0.192)
0.132 -0.032
(0.313) (0.238)

Constant 3.054*** 2.939***
Observations (0.327) (0.362)
1308 1314

Note: Since the outcome variable is defined at household level, we only used the
household level control variables. The following control variables have been
incorporated in all the regressions: education, SC/ST, number of adults in the
household, type of house (non-cemented or not), land cultivated in acre, total
number of livestock (cows, bullocks and oxen), whether household has a toilet in
the household and if its members watches TV along with main occupation of the
household and block dummies. The marginal effects from ANCOVA pooled
probit regression are reported along with the bootstrapped standard errors clustered
at the Gram Panchayat (GP) level in parenthesis. *** p<0.01,** p<0.05, * p<0.1.

Table B6: Heterogeneous impact for literate population on awareness

Comparison of treatment GPs with all GPs

Work Work Unemployment Payment Wage Delay
entitlement rate compensation
application allowance duration
(6)
(1) (2) (3) (4) (5)
0.166***
Treatment 0.119*** 0.241*** 0.139*** 0.225*** 0.193*** (0.022)
literate (0.043) (0.050) (0.022) (0.057) (0.032) 0.010
Interaction (0.023)
-0.015 0.124*** -0.030 0.070** -0.018 0.007
Treatment (0.029) (0.039) (0.034) (0.033) (0.025) (0.026)
literate
Interaction 0.011 -0.121* 0.048 -0.074 0.053 0.358***
(0.074) (0.043) (0.081)
(0.066) (0.036) (0.065) 0.027
(0.039)
Comparison of treatment GPs with control GPs -0.069
(0.054)
0.117*** 0.229*** 0.236*** 0.232*** 0.260***
(0.040) (0.051) (0.036) (0.058) (0.041)

0.052 0.071 -0.062 0.121* 0.108**
(0.061) (0.092) (0.086) (0.063) (0.048)

-0.051 -0.077 0.101 -0.11 -0.049
(0.088) (0.106) (0.086) (0.085) (0.067)

Note: The marginal effects from ANCOVA pooled probit regression are reported along with the bootstrapped standard errors clustered 59
at the Gram Panchayat (GP) level in parenthesis. *** p<0.01, ** p<0.05, * p<0.1.

Table B7: Heterogeneous impact for literate population on process mechanisms and attendance in meetings 60
Comparison of treatment GPs with all GPs

Jobcard Got receipt Travelled more Attendance in Attendance in Raised issue
update by FA for work than once for wages GS meetings social audit on MGNREGA

meetings

(1) (2) (3) (4) (5) (6)

Treatment -0.023 0.070* -0.100** 0.127** 0.139*** 0.085***
literate (0.032)
Interaction (0.070) (0.038) (0.045) (0.051) (0.047) 0.034
(0.032)
-0.103** 0.007 0.004 0.088** 0.064** 0.002
(0.047)
(0.049) (0.028) (0.033) (0.044) (0.031)

0.028 0.097* 0.01 -0.016 0.062

(0.079) (0.052) (0.055) (0.071) (0.060)

Comparison of treatment GPs with control GPs of intervention block

Treatment -0.030 0.089** -0.115** 0.116** 0.170*** 0.132***
literate (0.070) (0.042) (0.050) (0.054) (0.048) (0.045)
Interaction -0.089 0.056 -0.032 -0.014 0.064 0.054
(0.089) (0.061) (0.091) (0.093) (0.051) (0.081)
0.051 0.054 0.063 0.089 0.053 -0.002
(0.107) (0.074) (0.097) (0.104) (0.069) (0.086)

Note: The marginal effects from ANCOVA pooled probit regression are reported along with the bootstrapped standard errors clustered at
the Gram Panchayat (GP) level in parenthesis. *** p<0.01, ** p<0.05, * p<0.1.

Table B8: Heterogeneous impact for mobile phone owners on awareness

Comparison of treatment GPs with all GPs

Work Work Unemployment Payment Wage rate Delay
compensation
entitlement application allowance duration (5)
(6)
(1) (2) (3) (4) 0.160***
(0.047) 0.190***
Treatment 0.132** 0.255*** 0.181*** 0.208*** 0.063*** (0.036)
Possess a mobile phone (0.022) 0.038
Interaction (0.057) (0.070) (0.029) (0.068) 0.069 (0.024)
(0.044) -0.038
0.131*** -0.033 0.063** 0.112*** (0.026)

(0.027) (0.037) (0.028) (0.033)

-0.02 -0.071 -0.054* -0.001

(0.066) (0.068) (0.030) (0.063)

Comparison of treatment GPs with control GPs

Treatment 0.068 0.212** 0.329*** 0.208*** 0.111* 0.337***
Possess a mobile phone (0.061) (0.084) (0.061) (0.073) (0.057) (0.095)
Interaction 0.024 0.135* 0.136** -0.063 -0.043
(0.041) -0.1 (0.073) (0.057) (0.047) (0.059)
0.068 (0.072) -0.122* -0.001 0.214*** 0.007
(0.069) -0.001 (0.073) (0.076) (0.063) (0.066)
(0.091)

Note: The marginal effects from ANCOVA pooled probit regression are reported along with the bootstrapped standard errors clustered at the
Gram Panchayat (GP) level in parenthesis. *** p<0.01, ** p<0.05, * p<0.1.

61

Table B9: Heterogeneous impact for mobile phone owners on process mechanisms and attendance in meetings 62

Comparison of treatment GPs with all GPs

Jobcard Got receipt Travelled Attendance in Attendance in Raised issue
update by for work more than GS meetings social audit on MGNREGA
once for wages
FA meetings

(1) (2) (3) (4) (5) (6)
0.112**
Treatment -0.126 0.078 -0.051 0.112* 0.100 (0.048)
Possess a mobile phone -0.011
Interaction (0.086) (0.057) (0.055) (0.064) (0.066) (0.031)
-0.044
Treatment 0.182*** 0.169*** -0.051 0.065* -0.025 (0.056)
Possess a mobile phone
Interaction (0.046) (0.033) (0.033) (0.036) (0.035) 0.260***
(0.064)
0.186** 0.027 -0.072 0.019 0.089 0.119**
(0.047)
(0.091) (0.062) (0.065) (0.069) (0.072) -0.205***
(0.076)
Comparison of treatment GPs with contaminated control GPs

-0.236*** 0.078 -0.066 0.101 0.217***

(0.090) (0.076) (0.068) (0.069) (0.071)

-0.007 0.172** -0.051 0.052 0.145**

(0.074) (0.081) (0.069) (0.067) (0.067)

0.368*** 0.035 -0.054 0.055 -0.054

(0.096) (0.100) (0.092) (0.086) (0.093)

Note: The marginal effects from ANCOVA pooled probit regression are reported along with the bootstrapped standard errors clustered at
the Gram Panchayat (GP) level in parenthesis. *** p<0.01, **p<0.05, * p<0.1.

63

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W.P. 496 SUNIL MANI India's Quest for Technological Self
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W.P. 495 SUDIP CHAUDHURI Evolution of the Pharmaceutical
Industry in Bangladesh, 1982 to 2020. July 2020.

W.P. 494 THIAGU RANGANATHAN, AVINA MENDONCA
Relative Educational Status and Women’s Autonomy:
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W.P. 493 ANURAG ANAND Economic Policy Reforms, Foreign Direct
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W.P. 492 S IRUDAYA RAJAN, UDAYA S. MISHRA Resource
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64

W.P. 486 CHANDRIL BHATTACHARYYA, Unionised Labour
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W.P. 485 PULAPRE BALAKRISHNAN, M. PARAMESWARAN,
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W.P. 482 K.P. KANNAN, Wage Inequalities in India. December 2018

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W.P. 480 SUNANDAN GHOSH, Enlargement Decisions of Regional
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W.P. 479 BEENA P.L. Outward FDI and Cross-Border M&As by
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W.P. 478 A.V. JOSE, Changing Structure of Employment in Indian
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W.P. 477 P. KAVITHA, Trends and Pattern of Corporate Social
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W.P. 476 MANMOHAN AGARWAL , International Monetary Affairs
In the Inter War Years: Limits of Cooperation. June 2018.

W.P. 475 R. MOHAN, D. SHYJAN, N. RAMALINGAM Cash
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W.P. 473 MANMOHAN AGARWAL The Operation of the Gold
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65

W.P. 472 S.IRUDAYA RAJAN, BERNARD D' SAMI, S.SAMUEL
ASIR RAJ Tamil Nadu Migration Survey 2015. February
2017.

W.P. 471 VINOJ ABRAHAM, MGNREGS: Political Economy, Local
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W.P. 470 AMIT S RAY, M PARAMESWARAN, MANMOHAN
AGARWAL, SUNANDAN GHOSH, UDAYA S MISHRA,
UPASAK DAS, VINOJ ABRAHAM Quality of Social
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W.P. 469 T. M THOMAS ISAAC, R. MOHAN Sustainable Fiscal
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W.P. 468 K. C. ZACHARIAH, Religious Denominations of Kerala,
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W.P. 467 UDAYA S. MISHRA, Measuring Progress towards MDGs
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Response of Developing Countries to its shortcomings,
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W.P. 465 MANMOHAN AGARWAL, SUNANDAN GHOSH
Structural Change in the Indian Economy, November 2015.

W.P. 464 M. PARAMESWARAN, Determinants of Industrial
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W.P. 463 K. C. ZACHARIAH, S. IRUDAYA RAJAN, Dynamics of
Emigration and Remittances in Kerala: Results from the
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W.P. 462 UDAYA S MISHRA, VACHASPATI SHUKLA, Welfare
Comparisons with Multidimensional Well-being Indicators:
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W.P. 461 AMIT S RAY, SUNANDAN GHOSH Reflections on India’s
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W.P. 460 KRISHNAKUMAR S Global Imbalances and Bretton
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66

W.P. 459 SUNANDAN GHOSH Delegation in Customs Union
Formation December 2014.

W.P. 458 M.A. OOMMEN D. SHYJAN, Local Governments and the
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W.P. 457 R. MOHAN, N. RAMALINGAM, D. SHYJAN, Horizontal
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W.P. 456 PRAVEENA KODOTH, Who Goes ? Failures of Marital
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W.P. 455 J. DEVIKA, Land, Politics, Work and Home-life at
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