The Impact of Conditional Cash transfers programmes on household - - PowerPoint PPT Presentation

The Impact of Conditional Cash transfers programmes on household work decisions in Ghana.

By E.E-A. Mochiah, R.D. Osei & I.O. Akoto

Outline

• Introduction

– Objectives

• Evidence from other studies

– LEAP program

• Methodology
• Results/Findings
• Conclusions
• Recommendations

Introduction

• In the last decade, CCT programs have been very

popular in developing countries as a policy tool to increase human capital.

• Argument of CCTs creating disincentives to work.
• CCT programs provide cash payments to households

conditional on regular school attendance and visiting health clinics among others.

– CCTs have achieved quantified success in reaching the poor and bringing about short-term improvements in consumption, education, and health (Schultz 2004; Gertler 2004; Rawlings and Rubio 2003),

Evidence in favour of CCTs

• Skoufias and Maro (2008), assesses the impact of Mexico’s

PROGRESA programme on poverty and adult work incentives.

– PROGRESA’s cash transfers have not discouraged people from working

• Ardington et al. (2009) concludes that

– large cash transfers (pensions in South Africa) to the elderly lead to increased employment among prime-aged adults, which occurs primarily through labor migration.

• Ferro et al. (2010) find that the Bolsa Escola CCT program in

Brazil

– increased mothers’ and fathers’ probability of participation in labour force work.

• Oliveira et al., 2007 finds in Brazil’s Bolsa Família that

– Women in benefiting households had labour market participation rates 4.3 percentage points higher than women in non-participating households

Evidence Against CCTs

• Maluccio and Flores (2005) used Nicaragua’s

“Red de Proteccion Social" conditional cash transfer scheme.

– find no effect on labour supply

• Bertrand et al. (2003) use cross-sectional data

in South Africa and estimate that

– pension receipt substantially lowers the labor market participation of working-age adults in the household.

What of Ghana’s LEAP?

• Specifically, the objectives of this paper is to

find out whether or not

– Conditional Cash Transfer scheme has increased households total hours worked (labour supply) generally; – The hours worked on farm (agriculture) ,off-farm (non- farm enterprise) and paid employment has increased with the CCT scheme

LEAP in Ghana

• Provides cash and health insurance to extremely poor

households across Ghana

– to alleviate short-term poverty and – encourage long term human capital development.

• Aimed at improving the basic consumption of beneficiary

households by

– increasing school enrolment, attendance and retention of children, – improving on livelihood income-earned activities like farming.

• GLSS5- 164,370 households (bottom 20% of extremely poor

households in Ghana)

• The target group includes

– subsistence farmers and fisher folk, – extremely poor citizens above 65 years without any subsistence support – persons living with severe disabilities without any productive capacity;

• Care Givers of OVCs-orphans and vulnerable children (particularly Children Affected By AIDS

and children with severe disabilities),

• Incapacitated/extremely poor people living with HIV/AIDS and
• Pregnant Women/Lactating Mothers with HIV/AIDS.

LEAP..cont’d

• For the aged and persons with severe disabilities, the cash transfer

is unconditional.

• As at 2008,each beneficiary receives GH¢8.00 and that could

increase to GH¢15,00, depending on the number of beneficiaries in the family (to a maximum of four)-2(GH¢10),3(GH¢12),4 or more(GH¢15)-Exchange rate at 2008 was about $1 to GH¢1

• In July 2012, this was revised to GH¢12 to GH¢36 during a re-
• launch. Exchange rate at 2012 was $1 to GH¢1.88
• Some recent contributions have came from DFID (£36.4 million),

World Bank (US$20 million), GoG (GH¢18 million)-July 2012

• As at 2010 coverage was 35,000 HH but has increased to 71,456 HH

in 2013 (98 districts) with a target of 150,000 HH in 2014 and 200,000 HH in 2015 (170 districts)

• Amount was to be adequate and acceptable so not to

– encourage unemployment, – create dependency or – benefit beneficiary households excessively compared to the other income groups in the community

Methodology

• The sampling strategy of the LEAP programme entailed a

longitudinal propensity score matching (PSM) design.

• The PSM strategy enables one to attribute changes over time

to the intervention by allowing for the construction of a counterfactual through the matched comparison group

Group LEAP(Treatment) YALE(Control) Survey Baseline Follow up Baseline Follow up Period 2010 2012 2010 2012 No of HH 700 646 5009 858

Methodology cont’d

• Any significant effect of the cash transfer on

household hours worked between the treatment group and the control group?

– overall, for agriculture, paid employment and non- farm enterprise.

• To do this, we adopt difference-in-difference

method

– vastly used in literature to account for differences in outcome variables in randomized experiments.

• Yit = β0 + β1Tit + β2Ait + β3TitAit +β4Xit+ εit (1)
• Where Yit is the number of hours worked by the

household i at time t (t=1, 2),

• Xit is a vector containing covariates which may

influence the number of hours worked by a household.

• Tit is a trend variable (= 1 in follow up and zero (0) for

the baseline period.

• Ait is the treatment dummy
• TitAit is an interactive variable.
• The coefficient of this interactive variable provides a

measure of effect of the intervention which is referred to as the difference in difference estimator and can be expressed as:

• β3 = (Y*a1-Y*c1)-(Y*a2-Y*c2) (2)

Descriptive Results

Sex of Household head

• Dist. of age of HH head

Male 45.5 10-19 1.0 Female 54.5 20-29 5.6 Marital status of Household head 30-39 12.0 Married 42.0 40-49 13.0 Consensual Union 5.9 50-59 17.3 Separated 4.0 60-64 6.7 Divorced 11.1 65+ 44.5 Widowed 32.6 Household size Never Married 4.5 1 18.9 Betrothed 0.0 2-3 32.7 Educational level of head 4-5 24.5 No education 46.5 6-7 15.3 Senior High School and below 49.4 8-9 5.9 Above Senior High School 4.1 10+ 2.7 Mean household size 3.9

Average HH size is 3.9 Sex of household heads was 54.5 for women

Annual Average labour hours/Days per household

Labour Hours Baseline Follow-up Treatment Control Treatment Control Agric 306.1 671.2 349.6 550.5 Paid employment 95.1 106.6 108.4 78.9 Non-farm Enterprise 640.3 673.9 655.9 836.2 Total 1041.5 1451.7 1113.8 1465.7 Days per HH Agric 38 84 44 69 Paid employment 12 13 14 10 Non-farm Enterprise 80 84 82 105 Total 130 181 139 183

Analytical Results

Total labour hrs Agriculture Paid employment Non-farm Enterprise Eqn1 Eqn2 Eqn3 Eqn4 Eqn5 Eqn6 Eqn7 Eqn8 VARIABLES lTotallabhrs lTotagriclabhrs lTpaidemphrswk lTotlabhrs_ent Treatdum

• 0.823***
• 0.070
• 0.914***
• 0.111
• 0.075
• 0.202**
• 0.099

0.042 (0.153) (0.117) (0.149) (0.111) (0.085) (0.086) (0.164) (0.165) Time2 0.659*** 0.540** 0.564*** 0.678***

• 0.052

0.200 0.366**

• 0.006

(0.147) (0.245) (0.143) (0.230) (0.082) (0.177) (0.158) (0.296) Treattime

• 0.398*

0.263

• 0.489**
• 0.074

0.160 0.315*

• 0.218

0.110 (0.216) (0.264) (0.211) (0.249) (0.120) (0.191) (0.232) (0.371) lLabannualinc 0.389***

• 0.121***
• 0.140***

(0.026) (0.024) (0.036) HHhasnonfarm 0.287 0.044

• 0.223*

(0.184) (0.174) (0.133) lEnt_sales1 0.348***

• 0.095***
• 0.003

(0.018) (0.017) (0.013) lagricincome 0.219***

• 0.043***
• 0.039

(0.018) (0.013) (0.026) lLoanamt 0.001 0.018 0.032** 0.121*** (0.019) (0.018) (0.014) (0.027) lLendamt

• 0.044
• 0.004

0.077*** 0.265*** (0.029) (0.027) (0.021) (0.041) lTransfers

• 0.095***
• 0.061***
• 0.045***
• 0.074***

(0.018) (0.017) (0.013) (0.025) TTlTransfer

• 0.101**
• 0.098***
• 0.101***
• 0.006

(0.040) (0.038) (0.029) (0.056) lCompensatn_wage

• 0.028

0.050

• 0.185***
• 0.013

(0.046) (0.043) (0.033) (0.065) cancarryload 0.845*** 0.725*** 0.594*** 1.129*** (0.117) (0.110) (0.086) (0.163) lsize 1.274*** 2.851***

• 0.139**
• 0.596***

(0.088) (0.072) (0.065) (0.123) males_in_hh 0.012 0.388*** 0.414***

• 0.437***

(0.092) (0.086) (0.066) (0.129) hhsize 0.101*** 0.119*** 0.043*** 0.110*** (0.021) (0.020) (0.015) (0.029) HHelectricity

• 0.077
• 0.139*

0.072 0.688*** (0.086) (0.081) (0.063) (0.121) self_employed

• 0.868***

(0.075) Constant 5.031*** 1.390*** 3.696*** 0.845*** 0.486*** 0.755*** 1.840*** 1.306*** (0.104) (0.267) (0.101) (0.251) (0.058) (0.195) (0.111) (0.306) Observations 3,008 3,008 3,008 3,008 3,008 3,008 3,008 3,008 R-squared 0.033 0.490 0.039 0.526 0.001 0.108 0.003 0.093 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Conclusions and Policy Implications

• We find that the programme decreased total hours worked

relative to the control group but specifically

– decreased total labour hours worked for agriculture – increased hours worked for paid employment. – no impact on hours worked for non-farm enterprises.

• Non-institutional transfers into households generally

reduced total household hours worked, hours worked for agriculture, paid employment hours worked and non-farm enterprise hours worked.

• Marginal impacts attributable to non-institutional

transfers (transfers to beneficiary HH)has been a reduction in household labour hours worked by about 10% for Agriculture, paid employment and in Total.

Conclusions and Pol….cont’d

• The health status of household members,

having males in the household coupled with larger household size and larger household cultivated land sizes increased hours worked for agriculture.

• Households with electricity tend to increase

their hours worked for non-farm enterprises.

Recommendations

• The result is suggesting that Cash transfers is leading to reduction in agric labour supply. Possible

explanation: – Children are now attending school as a condition for cash transfer and so decline in HH hours worked

• Positive impacts on children’s schooling: LEAP has increased school among secondary school

aged children by 7 percentage points, and reduced grade repetition among both primary and secondary aged children. Among primary aged children LEAP has reduced absenteeism by 10 percentage points (Handa et al., 2013)

• The use of hired labour and herbicides

– There is a positive impact on productive activity among smaller households. Among households with four members or less there are positive impacts on male hired in to work on the farm (Handa et al., 2013). – Hired labour did not reduce hours worked on the farm and – The use of herbicides did not also reduce the hours worked by household on their farms.

• However, it is highly recommended that the subsequent targeting should be carefully done to yield

expected results.

• We also recommend the continuation of the intervention as it has a broader positive outlook for the

future with regards to its goals.

• Impacts of such programmes highly depend on timely payments of the cash transfers and as such

payments should be made at regular intervals to make household consumption pattern smooth and not to compound and pay in lump sums as it has been so far.

• There also seem to be a drift from household hours worked on farm to paid employment outside the

household. – The question is whether or not the shift in labour is growth-enhancing for the bigger economy? NEXT STEPS FOR RESEARCHERS……….

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