Impact of agricultural policy intervention on yield and profitability of maize farmers: The case of Planting for Food and Jobs (PFJ) programme in Ghana

Figures & data

Figure 1. Map of Sekyere Kumawu district.

Source: Ghana Statistical Service, GIS, 2020

Table 1. Explanatory variables in the models

Variables	Measurement	Apriori. Exp	Reference
Age	Age of farmer in years	+	Awotide et al. (2015); Baffoe et al. (2014)
Gender (Male)	1 = Male, 0 = Female	+/-
Years of schooling	Years of formal education (years)	+	Khoza et al. (2019); Tanko et al. (2021)
Off-farm income	Off-farm income in Ghanaian cedis (GHS)	+/-
Household size	Number	+
Marital status	Married =1; 0=if otherwise.	+/-	Oladejo et al. (2011); Nnadi and Akwiwu (2008)
Distance to district capital	Distance from district capital to farmer location in kilometers (km)	-	Khoza et al. (2019); Eneyew (2012)
Distance to nearest agro-shop	Distance to nearest agro-inputs shop in kilometres (Km)	-	Khoza et al. (2019); Eneyew (2012)
Extension contact	Number of extension visits received during last year	+	Ngwako et al. (2021)
Credit Access	If farmer’s access to credit during last year (yes=1; 0=otherwise)	+/-	Anang and Ayambila (2020)
FBO Membership	If farmer belongs to farmer-based organization (FBO) =1; 0 if otherwise	+/-	Motsoari et al. (2015)
Experience in maize farming	Number of years of farming maize	+	Tekuni et al. (2021)
Farm size	Size of maize farm measured (Acres)	+	Kuwornu et al. (2014)
Price of maize	Ghanaian cedis (GHS)	+	MoFA (2017)
Fertilizer cost	Ghanaian cedis (GHS)	-	MoFA (2017)
Seed cost	Ghanaian cedis (GHS)	-	Abdulai and Huffman (2014)
Herbicide cost	Ghanaian cedis (GHS)	-	Abdulai and Huffman (2014)
Labor cost	Ghanaian cedis (GHS)		Abdulai and Huffman (2014)
Political affiliation	If member of political affiliation =1; 0=if otherwise	+	Brodie et al. (2009)
Overall perception index	If farmer agree=1; 0=if otherwise	+/-

Source: Field survey, 2020.

Table 2. Descriptive statistics of socio-economics characteristics of maize farmers

Variables	Participants (N=200)		Non-Participants (N=200)		Overall (N=400)		t-stat
	Mean	SD	Mean	SD	Mean	SD
Age (Years)	49.34	8.56	49.71	8.56	49.52	8.95	−0.42
Gender (Male)	0.76	0.42	0.73	0.44	0.74	0.44	0.79
Years of schooling	7.69	5.68	6.25	6.00	6.97	5.89	2.46***
Farm size (Acre)	6.64	4.52	4.93	3.70	5.79	4.26	4.11***
Experience in maize farming (Years)	14.31	9.32	15.24	9.77	14.77	7.54	0.97
Marital status (Married)	0.47	0.18	0.39	0.11	0.72	0.49	−6.11***
Household size (Number)	4.98	1.87	4.77	2.29	4.88	2.101	−1.69*
Political affiliation (Yes)	0.82	0.77	0.68	0.65	0.62	0.47	4.23***
Off-farm income (GHS)	2605.35	1127.74	2647.97	1025.47	2626.66	1078.48	−0.39
Off-farm activities (Yes)	0.67	0.46	0.77	0.41	0.59	0.49	3.90***
Extension contact (Number)	4.02	1.89	3.72	2.54	3.87	2.25	1.36
FBO membership (Yes)	0.27	0.44	0.30	0.45	0.28	0.45	−0.67
Credit access (Yes)	0.26	0.44	0.27	0.44	0.27	0.44	−0.11
Distance to district capital (Km)	0.91	0.82	1.25	1.45	3.50	1.01	−2.86***
Distance to nearest agro-shop (Km)	1.06	0.87	1.33	1.19	1.39	1.10	−2.59**

SD is standard deviation. ***significant at 1%, **significant at 5% and *significant at 10%.

Source: Field survey, 2020.

Table 3. Packages under PFJ programme

Packages	Mean	SD
^aImproved Seed	0.670	0.471
Quantity of Seed Received (kilo)	6.948	6.34
Total value for Seed (GHS)	13.903	12.685
^aFertilizer	0.685	0.466
Quantity Fertilizer Received (kg)	5.182	4.227
Total value for Fertilizer (GHS)	390.34	318.07
^aExtension Service	0.970	0.171
^aReady Market	0.450	0.499

^ameasured as dummies. SD is standard deviation.

Source: Field survey, 2020.

Table 4. Perception of respondents about PFJ programme

Perception statement	SD (1)	D (2)	N (3)	A (4)	SA (5)	MS
The PFJ programme provides farmers with improved seeds on time	2 (1.0%)	1 (0.5%)	5 (2.5%)	89 (44.5%)	103 (51.5%)	4.5
The PFJ programme provides farmers with improve fertilizer on time	6(3%)	5(2.5%)	3(1.5%)	75(37.5)	111(55.5%)	4.4
The PFJ programme provides farmers with quality seeds	1(0.5%)	2(1%)	3(1.5%)	60(30%)	134(67.0%)	4.6
The PFJ programme provides farmers with quality fertilizers	2(1%)	3(1.5%)	6(3.0%)	52(26%)	137(68.5%)	4.6
The PFJ programme provides adequate quantity of seeds	1(0.5%)	5(2.5%)	5(2.5%)	86(43%)	103(51.5%)	4.4
The PFJ programme provides adequate quantity of fertilizers	3(1.5%)	5(2.5%)	6(3.0%)	85(42.5%)	101(50.5%)	4.4
The PFJ programme has improved access to extension services	0	1(0.5%)	7(3.5%)	49(24.5%)	143(71.5%)	4.8
The PFJ programme has enhanced access to improved seeds	0	3(1.5%)	4(2.0%)	79(39.5%)	114(57%)	4.5
The PFJ programme has enhanced access to fertilizers	3(1.5%)	5(2.5%)	6(3.0%)	69(34.5%)	117(58.5%)	4.5
The PFJ programme provides ready market to farmers	13(6.5%)	80(40%)	43(21.5%)	41(20.5%)	23(11.5%)	3.0
The PFJ programme has helped in improving crop productivity	0	0	0	39(19.5%)	161(80.5%)	4.8
The PFJ programme has proper grievance handling mechanism	3(1.5%)	2(1.0%)	11(5.5%)	78(39%)	106(53%)	4.4
PERCEPTION INDEX						4.4

SD=strongly disagree, D=disagree, N=neutral, A=agree, SA=strongly agree, MS=mean score.

Source: Field survey, 2020.

Table 5. Maize revenue and costs analysis during 2019 season for participants and non-participants PFJ programme (per acre basis)

ITEMS	Participant GHS	Non-participant GHS	t-stats
Total Revenue	2,285.05 (389.09)	1,928.10 (328.31)	−5.16***
Variable Costs
Land clearing (man-days)	421.40 (71.75)	402.73 (68.58)	1.17
Plant materials	524.88 (89.37)	449.37 (76.52)	−5.54***
Seed planting (man-days)	24.75 (4.99)	202.67 (34.51)	−4.10***
Herbicide & Pesticide application (man-days)	163.98 (27.92)	131.34 (22.36)	2.32**
Weed control (man-days)	127.39 (21.69)	111.77 (19.03)	−2.85***
Harvesting activities (man-days)	237.09 (4.37)	218.12 (37.14)	3.21***
Less: Total Variable Costs	1,715.49 (292.11)	1,516.00 (258.14)	2.12**
Fixed Costs
Land (in acre)	166.03 (28.27)	164.90 (28.08)	−1.34
Cutlass & Hoe	52.87 (9.00)	45.00 (7.66)	−3.61***
Knapsack sprayer	72.82 (12.40)	67.46 (67.46)	−2.02**
Less: Total Fixed Cost	291.72 (49.67)	277.36 (47.23)	−2.53***
Net Farm Profit	277.84 (47.31)	134.64 (22.93)	−3.12***
Gross Margin	569.56 (96.98)	412.10 (7.17)	−2.62***
BCR	1.14	1.08	2.22***
Land area cultivated (per farmer in acre)	3.5	3.2	3.56***
Maize Yield (100kg per acre)	41.0	34.2	3.56***

Note: Figures in parenthesis () are dollar $ equivalent. $1=GHS5.872. ***significant at 1%, **significant at 5%, *significant at 10%.

Source: Field survey, 2020.

Table 6. Endogenous switching regression results for participation and impact of participation on gross margin and yield

Variable	Selection		Gross Margin				Maize Yield
			Participants		Non-Participants		Participants		Non-Participants
	β	SE	β	SE	β	SE	β	SE	β	SE
Age	0.023***	0.009	0.258	0.816	0.676	0.781	0.115**	0.049	0.070	0.047
Gender (Male)	−0.185	0.159	0.282**	0.128	0.171	0.180	0.223	0.822	0.196***	0.071
Years of schooling	0.140***	0.110	0.333***	0.096	0.122	0.916	0.206***	0.073	0.067	0.045
Off-farm income	−0.000	0.000	−0.050	0.060	−0.045	0.073	−0.001*	0.000	−0.001*	0.000
Household Size	0.026	0.032	−0.612**	0.029	−0.198	0.263	−0.441**	0.193	−0.019	0.181
Marital Status	−0.158***	0.021	0.398	0.255	0.042	0.236	−0.052	0.424	0.744	0.954
Distance to district capital	−0.546***	0.095	−0.148*	0.086	−0.359**	0.182	0.092	0.115	−0.219***	0.048
Distance to nearest agro-shop	−0.172**	0.079	−0.671	0.109	−0.220***	0.077	−0.122**	0.058	0.175***	0.056
Extension contact	0.069**	0.027	0.641**	0.031	0.027	0.219	0.864***	0.272	0.275**	0.123
Credit Access	0.166	0.150	0.216	0.142	−0.108	0.106	0.424***	0.131	0.792	0.748
FBO Membership	0.387**	0.155	0.395	0.133	0.875	0.158	0.990	0.884	0.150	0.872
Experience in maize farming	0.062***	0.017	0.090	0.150	0.329*	0.199	0.178*	0.104	−0.145	0.109
Farm size	0.0575**	0.022	0.106***	0.035	0.694***	0.220	0.201***	0.014	0.193***	0.014
Price of maize	0.0154**	0.007	−0.244**	0.010	−0.785	0.495	−0.319***	0.101	−0.169***	0.038
Fertilizer cost	0.013	0.009	−0.439***	0.130	0.259	0.475	−0.441***	0.124	0.051*	0.028
Seed cost	0.010*	0.006	0.188***	0.054	−0.947	0.408	0.151***	0.036	0.013	0.025
Herbicide cost	−0.009	0.007	0.297***	0.011	0.501	0.419	0.398***	0.116	−0.025	0.031
Labor cost	−0.010***	0.002	0.086	0.278	−0.867	0.959	0.030	0.019	0.008	0.004
Political affiliation	0.363***	0.100
Overall perception index	0.381***	0.103
Constant	0.225***	0.074	0.123***	0.033			0.201***	0.052
athrho			−0.834**	0.380			−0.158**	0.014
lnsigma			6.784***	0.125			1.742***	0.084
Observations	400		400				400
Wald test of independent eqns. (rho = 0): chi2(47)	333.15***		182.7***				162.96***
Prob > chi2	0.000		0.000				0.000
Log pseudolikelihood	−492.597		−257.05				−209.82

Note: SE denote standard error and β denotes the coefficients. ***significant at 1%, **significant at 5%, *significant at 10%.

Source: Field survey, 2020.

Table 7. Impact of PFJ programme on maize productivity and profitability

	Mean outcome
	Treated	Non-treated	ATT	t-values
Gross margin per acre	668.27	478.87	189.40***	5.17
Yield per acre	8.58	3.10	5.48***	2.76

***significant at 1%, **significant at 5%, *significant at 10%. ATT: Average Treatment Effect. 1 bag of maize=100 kg.

Source: Field survey, 2020.

Table 8. Propensity score matching results

Outcome	ATT	Standard Error	t-value
Yield per acre
Nearest Neigbour Matching	6.19***	2.11	2.93
Radius Matching	5.38***	2.14	2.51
Kernel-Based Matching	7.01***	2.55	2.74
Gross margin per acre
Nearest Neigbour Matching	109.84***	15.18	7.23
Radius Matching	147.98***	17.75	8.33
Kernel-Based Matching	257.71***	20.46	12.59

***significant at 1%, **significant at 5%, *significant at 10%. ATT: Average Treatment Effect.

Source: Field survey, 2020.

Table 9. Inverse probability weighted regression adjustment (IPWRA)

Outcome	ATT	Standard Error	t-value
Yield per acre	6.88***	2.61	2.63
Gross margin per acre	262.83***	16.64	15.79

***significant at 1%, **significant at 5%, *significant at 10%. ATT: Average Treatment Effect.

Source: Field survey, 2020.

Figure 2. Distribution of propensity scores.

Source: Field survey, 2020.

Awotide, B. A., Abdoulaye, T., Alene, A., & Manyong, V. M. (2015). Impact of access to credit on agricultural productivity: Evidence from smallholder cassava farmers in Nigeria. International Conference of Agricultural Economists, 1–34. Retrieved from http://purl.umn.edu/210969.

 Google Scholar

Baffoe, G., Matsuda, H., Nagao, M., & Akiyama, T. (2014). The Dynamics of rural credit and its impacts on agricultural productivity: An empirical study in rural Ghana. OIDA International Journal of Sustainable Development, 7(5), 19–34. https://ssrn.com/abstract=2495848

 Google Scholar

Khoza, T. M., Senyolo, G. M., Mmbengwa, V. M., Soundy, P., & Sinnett, D. (2019). Socio-economic factors influencing smallholder farmers ’ decision to participate in agro- processing industry in Gauteng province, South Africa. Cogent Social Sciences, 5(1), 1–14. https://doi.org/10.1080/23311886.2019.1664193

 Web of Science ®Google Scholar

Tanko, M., Ismaila, S., Sadiq, S. A., & Aye, G. (2019). Planting for food and jobs (PFJ): A panacea for productivity and welfare of rice farmers in Northern Ghana. Cogent Economics & Finance, 7(1), 1693121. https://doi.org/10.1080/23322039.2019.1693121

 Web of Science ®Google Scholar

Oladejo, J. A., Olawuyi, S. O., & Anjorin, T. D. (2011). Analysis of Women participation in agricultural production in Egbedore local government area of Osun State, Nigeria. International Journal of Agricultural Economics & Rural Development, 4(1), 1–11. http://www.lautechaee-edu.com/journal/ijaerd5/ijaerd5%20-%201.pdf

 Google Scholar

Nnadi, F. N., & Akwiwu, C. D. (2008). Determinants of Youths’ participation in rural Agriculture in Imo State, Nigeria. Journal of Applied Sciences, 8(2), 328–333. https://doi.org/10.3923/jas.2008.328.333

 Google Scholar

Eneyew, A. (2012). Determinants of livelihood diversification in pastoral societies of Southern Ethiopia. Journal of Agriculture and Biodiversity Research. 1 (3), 43–52. http://www.onlineresearchjournals.org/JABR

 Google Scholar

Ngwako, G., Mathenge, M., Gido, E., & Kgosikoma, K. (2021). Effect of market participation on household welfare among smallholder Goat farmers in Botswana. Journal of Agribusiness and Rural Development, 2(2), 151–160. https://doi.org/10.17306/J.JARD.2021.0t1362

 Google Scholar

Anang, B. T., & Ayambila, S. N. (2020). Participation in agricultural extension and labor productivity: A case study of smallholder farmers in Ghana. International Journal on Food System Dynamics, 11(3), 297–306. https://doi.org/10.18461/ijfsd.v11i3.55

 Google Scholar

Motsoari, C., Cloete, P. C., & van Schalkwyk, H. D. (2015). An analysis of factors affecting access to credit in Lesotho’s smallholder agricultural sector. Development Southern Africa, 32(5), 592–602. https://doi.org/10.1080/0376835X.2015.1044077

 Web of Science ®Google Scholar

Tekuni, N., Kyere, G. H., Anang, S. A., & Mensah, M. O. (2021). Robustness of food security and policy trust on smallholder participation in Ghana’s planting for food and jobs programme. African Journal of Agricultural Research, 17(12), 1517–1523.

 Google Scholar

Kuwornu, J. K. M., Bashiru, M., & Dumayiri, M. (2014). Farm households’ livelihood diversification into agroprocessing and non-agro-processing activities: Empirical evidence from Ghana. Information Management and Business Review, 6(4), 191–199. https://doi.org/10.22610/imbr.v6i4.1114

 Google Scholar

Ministry of Food and Agriculture (MoFA). (2017). Planting for Food and Jobs Concept-A Program to Stimulate Rapid Growth of the Ghanaian Agricultural Sector (Drafted: February 2017).

 Google Scholar

Abdulai, A., & Huffman, W. (2014). The adoption and impact of soil and water conservation Technology: An endogenous switching regression application. Land Economics, 90(1), 26–43. https://doi.org/10.3368/le.90.1.26

 Web of Science ®Google Scholar

Brodie, E., Cowling, E., & Nissen, N. (2009). Understanding participation: A Literature Review. National Council for Voluntary Organisations.

 Google Scholar

Data availability statement

The data that support the findings of this study are openly available in Data_set at https://drive.google.com/file/d/1qaH10NXAuJNcO-EZTkO9Sh8zJO5qmNDt/view?usp=sharing.