Theme 2:Labor, migration, wages

Implementation of MGNREGA in India:A Review of Impacts for Future Learning

Featuring work completed by IFPRI, Cornell University, and IGIDR with funding from 3ie

Introduction• MGNREGS is a labor-opportunity creation program• Effects and impacts of the program on various labor

measures can be studied at different levels:

• Household labor supply (partial equilibrium: participants)• Total levels• Allocation across tasks and types of work (including migration) • Allocation across household members (gender, age)

• Aggregate labor market (general equilibrium: participants and non-participants) • Total labor days worked • Migration • Wages

Review of literature• Household labor supply (partial equilibrium:

participants)• Imbert and Papp (2014) • Islam and Sivasankaran (2014)• Sheahan, Liu, Narayanan, Barrett (in progress)• Das (2013)• Narayanan and Ranaware (in progress)

• Aggregate labor market (general equilibrium: participants and non-participants) • Imbert and Papp (2014, 2015)• Azam (2012)• Berg et al. (2013) • Zimmermann (2013)• Narayanan (in progress)

Review of literature: Impact on employment

• Overall employment• No fall in unemployment or drop in number of people not in labor

force (Imbert and Papp 2015) • No significant increase in total employment for men or women,

implying the program acts like a safety net (Zimmermann 2013) • Significant increase in public works participation, much higher for

females than males (Azam 2012)• Increase in total labor force participation, also more pronounced for

women (Azam 2012), especially relative to declining trend found in later phased in districts (Chowdhury 2011)

• “Crowding out” of private sector employment• 1.3 percent decrease in private employment days (waged, self-

employed, domestic) in dry season with no significant change in rainy (Imbert and Papp 2015)

Review of literature: Impact on wages

• Most studies use the NSSO data to study wage effects • 4.7 percent increase in casual labor wages, with impacts in agricultural

off season, using data from directly before and after program started (Imbert and Papp 2015)

• Much smaller and less precisely estimated effects, and concentrated in women not men, when using the same data but different estimation method (Zimmermann 2013)

• 8 percent increase in female casual private sector wages relative to a 1 percent increase for males, showing importance of gender-neutral MGNREGS wages (Azam 2012)

• 5.3 percent increase in agricultural wages when looking at the duration of MGNREGS implementation; also finds that wage increases happen 6-11 months after project starts (Berg et al. 2013)

• Wage increases for this segment of the population seen as good given directive to increase welfare and bargaining power of the marginalized

Review of literature: Impact on migration

• Using survey data from villages matched across three states with historically high out migration rates (Gujarat, Rajasthan, Madhya Pradesh), 8 percent of surveyed adults report that MGNREGS benefits were the reason they did not migrate (Imbert and Papp 2014)

• Adults living in states with more MGNREGS work days spend less time outside working outside of their village (Imbert and Papp 2014)

• Lower incidence of short term migration in early phase districts in the 2007/08 NSSO data relative to non-phased in districts (Imbert and Papp 2014)

• A range of qualitative and ethnographic accounts of reduced migration in Madhya Pradesh (Ambasta et al. 2008), Rajasthan (Menon 2008), and Tamil Nadu (Jacob 2008)

Sheahan et al. (in progress) • We study the household-specific labor outcomes by comparing

MGNREGS participants with non-participants• Research questions:

• How does the decision to participate on MGNREGS affect overall household level labor supply and, if so, how?

• Do the days offered to a MGNREGS project displace labor days previously devoted to other types of labor or household tasks?

• How does MGNREGS participation by one household member affect the time allocation of other household members, particularly with respect to gender and age groups (adults, youth, and children)?

• How do these results vary by agricultural season?

• Data: • Household-level panel data from primarily poor households in 5 districts of Andhra

Pradesh collected before (2004 and 2006) and after (2008) full MGNREGS phase in

• Match survey data with MGNREGS admin data using job card numbers of surveyed households

Project paper

Sheahan et al. (in progress) • Results: changes in total labor supply for MGNREGS

participants• MGNREGS participation by any household member increases total

household labor supply in the summer season only, dominated by increases in female work only

• Female participation leads to increases in female labor supply in rabi season (not kharif season)

• Females with lower initial labor supply level are more likely to participate in MGNREGS which then increases their total household labor offerings

• Participating households expand their labor supply by about 13 days in the summer season• Since the average number of days on MGNREGS for participating

households is 23, this suggests that this addition of days worked is likely displacing some non-MGNREGS labor

Project paper

Sheahan et al. (in progress) • Results: mechanisms for expanded labor supply

• 3 possibilities• wage factors• a buffer against a sudden collapse in labor demand• non-wage factors (dignity, safety, flexibility, etc.)

• We look specifically at wage factors, i.e. gap between the household daily wage rate (in 2006) and the village MGNREGS daily wage rate (in 2008)

• The expansion of total household labor supply does not appear to be moderated by the difference between household wages pre-MGNREGS and the village MGNREGS wage

• The female wage gap is an integral component of labor supply expansion for females in MGNREGS participating households in the kharif and rabi seasons

• Suggests that wage factors are not the most important ones driving changes in total or gender-specific household labor supply

Project paper

Sheahan et al. (in progress) • Results: allocation of time across tasks and hh members

• 1 day increase in the number of MGNREGS days provided by any household member “crowds out” 0.9 days of non-MGNREGS labor in the kharif season, 0.7 in the rabi season, and 0.5 in summer• Mostly drawn from private casual labor, however 1 day of MGNREGS

work does not completely displace 1 full day of private casual labor

• No evidence of an increase in time spent on paid or unpaid work for the youth and children of MGNREGS households, even a very modest decrease in time on unpaid work (like household chores)

• MGNREGS “crowds in”:• male migration (although for a very small set of households) and • female time spent on-farm and in non-farm self-employment activities in

rabi and kharif seasons respectively (makes sense given flexibility of MGNREGS days)

Project paper

Das (2015) • Hypothesis

Role of MGNREGA in reducing migration. To gauge the impact of

participation and intensity of participation in terms of number of days

of work and annual earnings from programme.• Field survey in four GPs (two blocks) in the Cooch Behar district,

West Bengal.

Findings• Participation as no impact on short-term migration but intensity has

a negative significant impact.• No impact on longer term migration.

Project paper

Das (2015)

Total

Individuals who migrated in 2011

Individuals who did not migrate

Difference

Number of days worked

in MGNREGA

in 2010

20.3 12.7 20.9 8.2**

Annual earnings

(Rs.)

2378.7 1393.5 2448.5 1054**

Project paper

Das (2015) • Households in Haldibari block migrates due to low demand for

agricultural works in lean season.• Most of the households which receive more than about 50 days have

stopped migrating in Falimari GP.• In Dawaguri GP, earlier migration was high. Has reduced

substantially due to MGNREGA.

• No major effect on longer migration was found. A worker from Falimari GP (marble floor) says:

“Why would I do so? I work in cities to get Rs. 250-300 and if I stay back to work in MGNREGA I would only get Rs. 130 and that too just for 100 days (if at all I get). I can earn the same money if I spent just two months in the cities”

Project paper

Narayanan and Ranaware (in progress)

• Does MGNREGA create dependency ?• Do workers exit the labour market and work exclusively in

MGNREGA? • Or do they “kick away the ladder”?• What is the extent of these two phenomena and who does what

and why?

• Dynamics of Participation • ICRISAT villages in Maharashtra and Andhra Pradesh – Field

survey (funded by ICRISAT), administrative data.

Project paper

Narayanan and Ranaware (in progress)Preliminary Findings

• Women tend to rely on the MGNREGA longer than men, who have a greater rate of attrition from the MGNREGA

• SC/ST and Backward communities/other minorities tend to attrition less quickly than general castes.

• Differentiated role of MGNREGA – some are “stayers”, others are “leavers” who worked in early years and have not returned. Others are late entrants or work in spells.

• Age profile of MGRNEGA workers suggest, older men are more likely to work compared to older women or younger women. Younger women are disproportionately present on worksites in the study villages.

Project paper

Narayanan and Ranaware (in progress)

Narayanan and Ranaware (in progress)

Project paper

Wages in ICRISAT villages• Econometric analysis of high frequency, monthly wage data from these six villages (2005-20013).• High frequency monthly data for different tasks by gender and

village (Since 2005)• Female: Sowing/transplanting, Weeding, Harvesting, Casual,

Construction• Male: Land preparation (ploughing), Weeding, Harvesting, Casual,

Construction• Male and female : farm and construction wages• Wage gaps in farm and construction

• Fieldwork in the six ICRISAT villages (September –October 2014). Funded by VDSA, ICRISAT.

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DOKUR AUREPALLE

Person days of MGNREGA

Wages in ICRISAT villages

Reported wages in MGNREGA

Findings

• MGNREGA is mainly summer work, a majority would do nothing otherwise.

• Latent but unfulfilled demand from SC/DNT in Akola villages

• Limited impact of MGNREGA on wages; intensity of the program has impact on average farm wages.

• Overall farm wages is associated with an increase in MGNREGA wages, but does not hold across tasks with task specific analysis.• Female weeding, but not on other operations• Male land preparation but not on other operations

• Cropping pattern choices in favour of labour intensive crops exert a greater influence (e.g. cotton area expansion for women)

More information about project outputs can be found at:

http://www.igidr.ac.in/mgnrega/