The impact of the Zambia Chid Grant Programme (CGP) on household economic activities and livelihoods
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The impact of the Zambia Chid Grant Programme (CGP) on household economic activities and livelihoods

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http://www.fao.org/economic/PtoP/en/ ...

http://www.fao.org/economic/PtoP/en/

Presented during the From Protection to Production project workshop, 24-25 September 2013, FAO HQ

The From Protection to Production (PtoP) project is a multi-country impact evaluation of cash transfers in sub-Saharan Africa. The project is a collaborative effort between the FAO, the UNICEF Eastern and Southern Africa Regional Office and the governments of Ethiopia, Ghana, Kenya, Lesotho, Malawi, Zambia and Zimbabwe. Project activities are mainly funded by the Regular Fund, the DFID Research and Evidence Division and the EU.

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  • The amount of the grant is the same regardless of household size, in order to reduce the incentive for misrepresenting households’ membership, but also to reduce administrative costs associated with delivering the transfer.As with other transfer programs (such as Oportunidades in Mexico) the primary recipient of the transfer is a female in the household that is considered to be the primary caretaker of the household.
  • Large majority are agricultural producers.Almost 80% produce crops; almost 50% have livestockEach district has quite different crop production patterns. Looking at the share of households producing each crop, Kaputa has mixed maize and cassava production (with a larger share of cassava), while Kalabo has mixed maize and rice production (with larger share of rice). Maize dominates in Shangombo.Most have just a few assets.A bit more than 1/2 HA of agricultural land, a couple of chickens, basic agricultural tools and low levels of education
  • Further, contamination does not appear to be a big issue: thirty-five control households declared to receive CGP payments and thirty-two of them reported having at least one household member currently a beneficiary. There could be a number of reasons for this occurrence: control households received a payment because they moved to a new area or cheated the system and found a way to register in a neighbouring treatment CWAC. Further it is possible that respondents simply lied about receiving the payment or misunderstood the question. In our impact estimates we decided to keep these household to avoid introducing selection bias that we cannot account for. This clearly leads to a lower impact estimate than a pure ATT.
  • Greater impacts for smaller HHs
  • The moderate increase in production seems to go to salesWe don’t find impact on increased home consumption Similar results in amounts
  • No change in participation and increased intensity of on farm labour activities for males
  • No change in participation and increased intensity of on farm labour activities for males
  • No change in participation and increased intensity of on farm labour activities for males
  • So what are these people doing? Are women more involved in domestic chores? Are generally beneficiaries more involved in on-farm labour? We cannot answer to the former question, but we can say that there is no change in participation of on-farm labour and just a moderate increased intensity for males.
  • The results found in this paper paint a promising picture in terms of the impact of the program on investments in productive assets, input use and agricultural production. Households invested more in livestock: large and significant effects are found on both the share of households owning animals and on the number of animals owned, especially for larger sized households. Further, the CGP is facilitating the purchase and/or increased use of agricultural inputs use, especially land, seeds, fertilizers and hired labour, both on the share adopting those inputs and the corresponding monetary amount, especially for smaller households. The increase in the use of agricultural inputs led to expansion in the production of maize and rice, though statistically significant only for smaller sized households—and beneficiary households reduced the production of cassava. In contrast with cash transfer results from other countries such as Malawi and Kenya, the increase in agricultural production did not lead to an increase in consumption of goods produced on farm, but instead to more market participation. More detailed analysis can be carried out to ascertain whether these average impacts are similar across different types of agricultural producers. The program has had a positive and significant impact in improving the livelihood position and options of treated households, which after intervention derive a much greater share of income from off-farm enterprises and much lower from wage employment, especially temporary agricultural labour. Taken together with adult labour supply response, these results suggest that, for some beneficiary households, the programme satisfies a cash flow need that was otherwise met through less preferred casual agricultural work, allowing households to concentrate on household business activities, whether in agriculture or off farm.

The impact of the Zambia Chid Grant Programme (CGP) on household economic activities and livelihoods The impact of the Zambia Chid Grant Programme (CGP) on household economic activities and livelihoods Presentation Transcript

  • The impact of the Zambia CGP on household economic activities and livelihoods Speaker: Silvio Daidone On behalf of the the impact evaluation team: Benjamin Davis, Joshua Dewbre, Mario González-Flores, Sudhanshu Handa, David Seidenfeld, Gelson Tembo Rome September 25, 2013
  • Cash transfers targeted to poorest of the poor can also have productive impacts • Beneficiaries of cash transfer programmes in Sub Saharan Africa predominately rural, most engaged in agriculture • Exit path from poverty not necessarily the formal/informal labor market • Impacts coming from changes in individual / household behaviour and structure of the local economy. • Transfers can relax some of constraints brought on by market failure – Helping households manage risk – Providing households with liquidity • Transfers can reduce burden on social networks and informal insurance mechanisms
  • The CGP programme • Unconditional CT • Targeting: - Geographical: Kaputa, Kalabo, Shangombo - Categorical: any HH with a child under 5 years • Transfer amount independent of HH size (60,000 ZMK per month) • Primary recipient is a female in the HH • Primary goal: build human capital and improve food security
  • Study Design: RTC with several levels of random selection - 90 out of 300 Community Welfare Assistance Committees (CWACs) in the three districts randomly selected and ordered through a lottery - Identification and selection of eligibles - 28 HHs selected in each of 90 communities - Baseline data collected before CWACs assigned to treatment/control group - Randomization of communities done with flip of coin
  • Agriculture is fundamental part of livelihoods of CGP beneficiaries 0 .2 .4 .6 .8 1 control Kaputa Kalabo Shang'ombo 0 .2 .4 .6 .8 1 treatment Kaputa Maize Groundnut Kalabo Cassava Sweet Potatoes Shang'ombo Rice Sorghum Source: CGP Zambia Share of households producing each crop (over all households producing crops). Baseline Millet Other beans
  • Econometric analysis of impact of CGP on household productive activities • High quality data, collected in the same season • Randomization worked, no need of reweighting or matching estimators • Diff-in-diff estimator for indicators available in both waves. Single diff estimator for outcomes only at follow-up. • Attrition not relevant. To avoid any selection bias issues, reweight for inverse of predicted attrition probabilities. • Some issues of contamination: ITT estimator, not pure ATT
  • Hypotheses to be tested • Household investment in productive assets ― Ownership of livestock and agricultural implements • Household impact on agricultural production ― Crop production, crop and livestock labor and input use • Household impact on non agricultural production By household size ― Operation of non farm business enterprise • Impact on individual labor activities ― Participation and intensity of wage labor (agricultural and non agricultural) and own farm labor By gender
  • Large increase in proportion of households with crop input expenditures Impact Baseline Baseline ≤5 HH members All crop expenses Impact Impact Baseline ≥6 HH members 0.225 0.223 0.213 0.134 0.236 seeds 0.100 0.131 0.135 0.12 0.067 0.143 hired labour 0.054 0.029 0.072 0.024 0.038 0.034 fertilizers 0.032 0.009 0.034 0.007 0.029 0.012 other exp N 0.177 0.151 0.104 0.153 0.105 0.150 0.103 4,596 Bold <5% significant, underlined <10% 22% at base 2,336 2,260
  • Large increase in proportion of households with crop input expenditures Impact Baseline Baseline ≤5 HH members All crop expenses Impact Impact Baseline ≥6 HH members 0.225 0.223 0.213 0.134 0.236 seeds 0.100 0.131 0.135 0.12 0.067 0.143 hired labour 0.054 0.029 0.072 0.024 0.038 0.034 fertilizers 0.032 0.009 0.034 0.007 0.029 0.012 other exp N 0.177 0.151 0.104 0.153 0.105 0.150 0.103 4,596 2,336 Bold <5% significant, underlined <10% Stronger in relative terms for inputs with low baseline 2,260
  • Large increase in proportion of households with crop input expenditures Impact Baseline Baseline ≤5 HH members All crop expenses Impact Impact Baseline ≥6 HH members 0.225 0.223 0.213 0.134 0.236 seeds 0.100 0.131 0.135 0.12 0.067 0.143 hired labour 0.054 0.029 0.072 0.024 0.038 0.034 fertilizers 0.032 0.009 0.034 0.007 0.029 0.012 other exp N 0.177 0.151 0.104 0.153 0.105 0.150 0.103 4,596 2,336 2,260 Bold <5% significant, underlined <10% Greater impacts for smaller HHs
  • Increase in the intensity of crop input use Impact Baseline Baseline Impact Baseline ≥6 HH members ≤5 HH members All operated land (ha) Impact 0.179 0.496 0.162 0.43 0.197 0.563 31,174 20,817 42,856 13,331 18,394 28,545 seeds 9,860 6,187 11,092 4,578 8,618 7,848 hired labour 8,417 7,093 14,682 2,845 1,155 11,479 fertilizers 7,606 1,413 8,924 721 6,499 2,127 other exp 5,226 6,092 7,967 5,124 2,092 7,091 crop expenses N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Expenses in Zambian Kwacha Big impact for seeds and fertilizers
  • Increase in the intensity of crop input use Impact Baseline Baseline Impact Baseline ≥6 HH members ≤5 HH members All operated land (ha) Impact 0.179 0.496 0.162 0.43 0.197 0.563 31,174 20,817 42,856 13,331 18,394 28,545 seeds 9,860 6,187 11,092 4,578 8,618 7,848 hired labour 8,417 7,093 14,682 2,845 1,155 11,479 fertilizers 7,606 1,413 8,924 721 6,499 2,127 other exp 5,226 6,092 7,967 5,124 2,092 7,091 crop expenses N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Expenses in Zambian Kwacha 30% increase in land use, but still small average size
  • Increase in the intensity of crop input use Impact Baseline Baseline Impact Baseline ≥6 HH members ≤5 HH members All operated land (ha) Impact 0.179 0.496 0.162 0.43 0.197 0.563 31,174 20,817 42,856 13,331 18,394 28,545 seeds 9,860 6,187 11,092 4,578 8,618 7,848 hired labour 8,417 7,093 14,682 2,845 1,155 11,479 fertilizers 7,606 1,413 8,924 721 6,499 2,127 other exp 5,226 6,092 7,967 5,124 2,092 7,091 crop expenses N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Expenses in Zambian Kwacha Much bigger for smaller HHs
  • Moderate increase in maize and rice production; decrease in cassava production Impact Baseline Impact Baseline ≤5 HH members All Impact Baseline ≥6 HH members maize cassava rice 49.5 148.2 35.1 117.8 63.8 179.5 -68.1 146.6 -17.0 103 -129.2 191.7 20.4 78.9 39.4 78.1 2.7 79.7 N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Production in KGs. Switching out of cassava production? Drop in cassava coincides with consumption results
  • Moderate increase in maize and rice production; decrease in cassava production Impact Baseline Impact Baseline ≤5 HH members All Impact Baseline ≥6 HH members maize cassava rice 49.5 148.2 35.1 117.8 63.8 179.5 -68.1 146.6 -17.0 103 -129.2 191.7 20.4 78.9 39.4 78.1 2.7 79.7 N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Production in KGs. Moderate significant impact on other staple goods
  • Moderate increase in maize and rice production; decrease in cassava production Impact Baseline Impact Baseline ≤5 HH members All Impact Baseline ≥6 HH members maize cassava rice 49.5 148.2 35.1 117.8 63.8 179.5 -68.1 146.6 -17.0 103 -129.2 191.7 20.4 78.9 39.4 78.1 2.7 79.7 N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Production in KGs. Big impact on input use, but not on crop production. 1) Diffuse impacts at crop level? 2) Still not sufficient inputs? 3) Inefficient combination?
  • Increase in market participation Impact Baseline Impact Baseline ≤5 HH members All Impact Baseline ≥6 HH members % selling crops 0.120 0.226 0.144 0.210 0.092 0.242 % consuming crops at home 0.059 0.761 0.063 0.732 0.057 0.790 N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Production in KGs. Moderate increase in home production. Why? Food security achieved with food purchases!
  • Explicit goal of CGP: ”Increase the number of households owning assets such as livestock” Impact Baseline Proportion milk cows Impact Baseline Number 0.033 0.053 -0.061 0.196 other cattle 0.084 0.094 0.263 0.417 chickens 0.154 0.404 1.234 1.949 goats 0.036 0.023 0.142 0.057 ducks 0.030 0.032 0.198 0.129 total 0.209 0.480 0.138 0.347 N 4,596 Bold <5% significant, underlined <10%. Objective met 4,596
  • Labour activities: Cross-section Impact Follow-up All Impact Follow-up Males Impact Follow-up Females paritcipation of HH members in wage labour -0.091 0.497 -0.049 0.439 -0.136 0.405 paid agriculture -0.145 0.337 -0.081 0.261 -0.174 0.292 paid non-agriculture 0.037 0.189 0.040 0.181 0.032 0.112 0.171 0.378 0.120 0.178 0.155 0.327 paid agriculture -13.75 35.7 -3.04 22.3 -12.37 18.6 paid non-agriculture 3.03 19.9 2.08 15.5 1.09 8.1 non-farm enterprise 1.57 2.65 0.62 0.94 0.98 1.76 N 2,296 non-farm enterprise intensity of (days in) 1,764 Bold <5% significant, underlined <10%. Decrease in wage employment driven by agricultural labour … 2,282
  • Labour activities: Cross-section Impact Follow-up All Impact Follow-up Males Impact Follow-up Females paritcipation of HH members in wage labour -0.091 0.497 -0.049 0.439 -0.136 0.405 paid agriculture -0.145 0.337 -0.081 0.261 -0.174 0.292 paid non-agriculture 0.037 0.189 0.040 0.181 0.032 0.112 0.171 0.378 0.120 0.178 0.155 0.327 paid agriculture -13.75 35.7 -3.04 22.3 -12.37 18.6 paid non-agriculture 3.03 19.9 2.08 15.5 1.09 8.1 non-farm enterprise 1.57 2.65 0.62 0.94 0.98 1.76 N 2,296 non-farm enterprise intensity of (days in) 1,764 2,282 Bold <5% significant, underlined <10%. … especially female HH members
  • Labour activities: Cross-section Impact Follow-up All Impact Follow-up Males Impact Follow-up Females paritcipation of HH members in wage labour -0.091 0.497 -0.049 0.439 -0.136 0.405 paid agriculture -0.145 0.337 -0.081 0.261 -0.174 0.292 paid non-agriculture 0.037 0.189 0.040 0.181 0.032 0.112 0.171 0.378 0.120 0.178 0.155 0.327 paid agriculture -13.75 35.7 -3.04 22.3 -12.37 18.6 paid non-agriculture 3.03 19.9 2.08 15.5 1.09 8.1 non-farm enterprise 1.57 2.65 0.62 0.94 0.98 1.76 N 2,296 non-farm enterprise intensity of (days in) 1,764 2,282 Bold <5% significant, underlined <10%. Significant also on the intensity of labour
  • Labour activities: Cross-section Impact Follow-up All Impact Follow-up Males Impact Follow-up Females paritcipation of HH members in wage labour -0.091 0.497 -0.049 0.439 -0.136 0.405 paid agriculture -0.145 0.337 -0.081 0.261 -0.174 0.292 paid non-agriculture 0.037 0.189 0.040 0.181 0.032 0.112 0.171 0.378 0.120 0.178 0.155 0.327 paid agriculture -13.75 35.7 -3.04 22.3 -12.37 18.6 paid non-agriculture 3.03 19.9 2.08 15.5 1.09 8.1 non-farm enterprise 1.57 2.65 0.62 0.94 0.98 1.76 N 2,296 non-farm enterprise intensity of (days in) 1,764 2,282 Bold <5% significant, underlined <10%. So, what are these people now doing? They are running an off-farm business!
  • No impact on child labour Impact Baseline All Impact Baseline Males Impact Baseline Females total 0.047 0.525 0.083 0.512 0.016 0.537 paid -0.018 0.043 -0.017 0.039 -0.014 0.047 unpaid 0.039 0.484 0.079 0.470 0.002 0.498 N 8,054 4,005 Bold <5% significant, underlined <10%. 4,049
  • Consistent story in terms of positive impact on livelihoods • CGP leads to increase in agricultural investment and capital accumulation ― In both crop and livestock production ― Production towards increased market participation instead of increased home consumption of output • Impact on production is still moderate • Shift from agricultural wage labour to non agricultural wage labor and off farm business
  • THANKS FOR YOUR ATTENTION
  • Small, but significant, increase in agricultural implements Impact Baseline Proportion Impact Baseline Number axes 0.008 0.773 0.184 1.114 hoes 0.010 0.912 0.296 1.532 hammers 0.044 0.047 0.042 0.055 shovels 0.031 0.053 0.027 0.063 plough 0.036 0.065 0.033 0.07 N 4,596 4,596 Bold <5% significant, underlined <10%. Low base – impact on proportion owning High base – impact on number
  • Labour supply, baseline Adult, by sector agriculture farming fishing forestry wage labour casual self enterprise not working Children, by age groups female 33.08 32.67 0.10 0.31 male 48.61 41.79 6.46 0.35 0.51 26.11 17.29 23.00 1.86 24.79 8.50 16.25 female overall 5-10 yrs 11-13 yrs 14-18 yrs 5-18 yrs male 40.47 68.39 78.51 54.32 35.73 69.94 76.92 50.91
  • Increase in the intensive margin of crop input use Impact Baseline All operated land (ha) Impact Baseline Impact <6 Baseline >5 0.179 0.496 0.162 0.43 0.197 0.563 31,174 20,817 42,856 13,331 18,394 28,545 seeds 9,860 6,187 11,092 4,578 8,618 7,848 hired labour 8,417 7,093 14,682 2,845 1,155 11,479 fertilizers 7,606 1,413 8,924 721 6,499 2,127 other exp 5,226 6,092 7,967 5,124 2,092 7,091 crop expenses N 4,596 2,336 2,260 Bold <5% significant, underlined <10%. Expenses in Zambian Kwacha Moving from family labour to hired labour?
  • Increase in savings and loan repayments Impact Baseline All HH saved cash 0.240 54,371 0.168 0.017 19,392 -256 0.177 55,198 0.010 0.011 19,820 -2,428 0.251 50,610 0.009 0.020 1,170 1,444 (-1.14) (1.85) 4,596 2,336 2,260 For everyone on both the extensive and intensive margin 18,949 0.011 (2.05) (-0.24) N 0.158 (4.12) (1.07) 895 Baseline (5.54) (4.72) (2.44) loan repayments amount 0.230 Impact HH size>5 (4.78) (5.79) HH repaid loan Baseline HH size<6 (5.73) savings amount Impact Increase just for larger HH 611