Drivers of smallholder farmers’ organic farming adoption and the organic share of the total cropland in Northern Ghana

Figures & data

Figure 1. Map of the study area. Source: Author's construct.

Table 1. Description of the explanatory variables in regression models.

Variables	Definition	Measurement	OVP adoption	Organic share of the total cropland	Related studies
SEX	Sex of farmer	Dummy; 1 = male; 0 = female	–	+	(Avane et al. 2021; Hoang 2021)
AGE	Age of farmer	Years	+/-	+/-	(Rana et al. 2012; Chatzimichael et al. 2014)
AGE_SQ	The square of age	Years	+	+
HH_SIZE	Household size	Number of people eating from the same pot	+	+	(Sodjinou et al. 2015)
FOREDUC	Formal education	Years of schooling	+	+	(Koesling et al. 2008; Läpple and Kelley 2013)
LND_OWN	Land ownership	Dummy; 1 = landlord; 0 = tenant	+	+	(Hattam and Holloway 2005; Amfo and Ali 2021)
MIDDLE_INCOME	Middle-income households	Dummy; 1 = Yes; 0 = No	-	-	(Sarker et al. 2009; Pradhan et al. 2017;Amfo and Ali 2021)
LOWER_INCOME	Lower-income households	Dummy; 1 = Yes; 0 = No	-	-	(Sarker et al. 2009; Pradhan et al. 2017;Amfo and Ali 2021)
ASSOC	Membership in a farmer group	Dummy; 1 = Member 0 = Non-member	+	+	(Saoke 2011; Wollni and Andersson 2014)
OFF_FARMWORK	Engagement in off-farm work	Dummy; 1 = Yes; 0 = No	+	+	(Sriwichailamphan and Sucharidtham 2014)
EXT_VISITS	Extension visits	Number of a visit to the vegetable farm per season	+	+	(Sodjinou et al. 2015; Ma et al. 2017)
LOCATION	Location of the farmer	Dummy; 1 = Rural; 0 = Urban	+	+	(Sodjinou et al. 2015; Ma et al. 2017)
MKT_INFO	Access to marketing information	Dummy; Yes; 0 = No	+	+
DRY_SEASON	Dry season vegetable production	Dummy; Yes; 0 = No	+/-	+/-
WET_SEASON	Wet season vegetable production	Dummy; Yes; 0 = No	+/-	+/-

Note: High-income households and all-year-round vegetable production are the base categories. Also, the + sign shows a positive correlation between the dependent variable and independent variable, while the – sign shows a negative correlation between the dependent variable and independent variable.

Table 2. Chi-square (${\chi }^2$) test results of the dummy variables by adoption.

	Full sample	Organic	Conventional
Variable	% distribution of categories	% distribution of categories	% distribution of categories	${\chi }^2$ (Sig.)
SEX	Male = 0.818;	Male = 0.875;	Male = 0.760;	8.864***
	Female = 0.182	Female = 0.125	Female = 0.240
LOC	Rural = 0.843;	Rural = 0.875;	Rural = 0.810;	3.184
	Urban = 0.157	Urban = 0.125	Urban = 0.190
HIGH_INC	Yes = 0.220; No = 0.780	Yes = 0.230; No = 0.770	Yes = 0.220; No = 0.780	0.000
MIDDLE_INC	Yes = 0.252; No = 0.747	Yes = 0.250; No = 0.750	Yes = 0.255; No = 0.745	0.013
LOWER_INC	Yes = 0.528; No = 0.472	Yes = 0.520; No = 0.480	Yes = 0.525; No = 0.475	0.010
OFF_FARM	Yes = 0.538; No = 0.462	Yes = 0.535; No = 0.465	Yes = 0.540; No = 0.460	0.010
LND_OWN	Yes = 0.708; No = 0.292	Yes = 0.700; No = 0.300	Yes = 0.715; No = 0.295	0.109
DRYSEASON	Yes = 0.250; No = 0.750	Yes = 0.355; No = 0.645	Yes = 0.145; No = 0.855	23.520***
RAINYSEASON	Yes = 0.300; No = 0.700	Yes = 0.435; No = 0.565	Yes = 0.165; No = 0.835	34.714***
BOTH SEASONS	Yes = 0.450; No = 0.550	Yes = 0.210; No = 0.790	Yes = 0.690; No = 0.310	93.091***
ASSOC	Member = 0.433:	Member = 0.600;	Member = 0.265;	45.723***
	Non-member = 0.567	Non-member = 0.400	Non-member = 0.735
CREDIT	Access = 0.043: No-access = 0.957	Access = 0.045; No-access = 0.955	Access = 0.040; No-access = 0.960	0.061
MKT_INFO	Access = 0.665; No-access = 0.335	Access = 0.780; No-access = 0.220	Access = 0.550; No-access = 0.450	23.746***

Note: *** shows the 1% significance level (p ≤ 0.01), * shows the 10% significance level (p > 0.05 ≤ 0.1).

Source: Field data, 2015.

Table 3. Sample t-test results of the continuous variables by adoption.

	Full sample		Organic		Conventional
Variable	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Test of means
AGE	38.033	8.436	38.260	8.161	37.805	8.436	0.548
HH_SIZE	8.660	3.521	8.560	3.843	8.760	3.173	- 0.568
FOREDUC	4.973	4.893	5.820	5.065	4.125	3.488	3.513***
EXT_VISITS	1.895	2.515	2.645	2.992	1.145	1.612	6.242***

Note: *** shows the 1% significance level (p ≤ 0.01), * shows the 10% significance level (p > 0.05 ≤ 0.1).

Source: Field data, 2015.

Figure 2. Vegetable farm size by OVP adoption, land ownership status, and timing (season) of vegetable production. Source: Field data, 2015.

Table 4. Current organic share of the total cropland by farmer experience on the OVP.

N	Experience in OVP	Mean organic share of the total cropland (%)	Std. Dev.
14	2	0.30	0.19
16	3	0.31	0.16
40	4	0.36	0.18
25	5	0.33	0.19
23	6	0.39	0.16
11	7	0.35	0.21
10	8	0.35	0.29
6	9	0.39	0.15
32	10	0.40	0.16
6	11	0.40	0.08
2	12	0.34	0.45
1	13	0.50	0.00
1	14	0.25	0.00
8	15	0.43	0.21
2	16	0.10	0.03
1	18	0.06	0.00
2	19	0.27	0.09
Full adopter sample (n = 200)	6.77	0.36	0.18

Note: n is the number of organic vegetable producers in each OVP experience category.

Source: Field data, 2015.

Table 5. Results of the Heckman selection model.

	Probit regression			OLS regression
Variables	Coeff.	Robust Std. Err.	P > z	Coeff.	Robust Std. Err.	P > z
SEX	0.338*	0.185	0.068	−0.028	0.047	0.553
AGE	0.049**	0.022	0.026	0.012*	0.007	0.098
AGE_SQ	−0.005*	0.003	0.053	−0.002*	0.001	0.050
HH_SIZE	−0.032	0.021	0.131	0.005	0.003	0.128
FOREDUC	0.035**	0.016	0.026	−0.003	0.003	0.288
LND_OWN	−0.123	0.156	0.430	0.051**	0.025	0.040
MIDDLE_INCOME	−0.234	0.175	0.182	−0.080***	0.026	0.002
LOWER_INCOME	−0.311	0.220	0.157	−0.065*	0.037	0.081
ASSOC	0.595***	0.165	0.000	0.056**	0.028	0.046
OFF_FARMWORK	−0.011	0.154	0.945	0.027	0.024	0.272
EXT_VISITS	0.131***	0.040	0.001	0.002	0.005	0.723
LOCATION	0.287	0.203	0.157	−0.032	0.033	0.328
MKT_INFO	0.502***	0.164	0.002	−0.025	0.031	0.419
DRY_SEASON	1.200***	0.188	0.000
WET_SEASON	1.378***	0.176	0.000
CONS	−2.717	0.603		0.302	0.177	0.088
Rho	−0.403	0.165
Lambda	−0.071**	0.031
Wald Chi-square	31.890	0.000		F(13,387) = 8.14; p < 0.01

Note: ***, **, and * show the 1%, 5%, and 10% significance levels.

Source: Field data, 2015.

Table A1. Results of Cragg’s double hurdle regression model.

	Truncated regression		Probit regression
Variables	Estimate	Std. Err.	Estimate	Std. Err.
SEX	−0.020	0.054	0.092*	0.182
AGE	0.014*	0.008	0.013**	0.022
AGE_SQ	−0.002**	0.001	−0.001*	0.003
HH_SIZE	0.004	0.004	−0.008	0.021
FOREDUC	−0.002	0.003	0.010**	0.016
LND_OWN	0.057*	0.031	−0.031	0.157
MIDDLE_INCOME	−0.100***	0.030	−0.062	0.176
LOWER_INCOME	−0.089**	0.043	−0.087	0.218
ASSOC	−0.035	0.032	0.158***	0.164
OFF_FARMWORK	0.031	0.028	−0.005	0.154
EXT_VISITS	0.001	0.005	0.033***	0.039
LOCATION	−0.032	0.036	0.319	0.198
MKT_INFO	−0.004	0.032	0.358***	0.163
DRY_SEASON			0.079***	0.191
WET_SEASON			0.131***	0.179
CONS	0.175	0.197	−2.777	0.840
Wald Chi-square	177.36	0.000
Tobit Restriction LRChi-square	132.14	0.000
Vuong test (t-stat)	−49.00	0.000

Note: ***, ***, and * show the 1%, 5%, and 10% significance levels.

Source: Field data, 2015.

Table A2. Results of the Standard Tobit regression model.

Variable	Coeff.	Std. Err.	Pvalue
SEX	0.1309	0.0590	0.027
AGE	0.0168	0.0072	0.021
AGE_SQ	−0.0002	0.0001	0.020
HH_SIZE	0.0033	0.0055	0.550
FOREDUC	0.0056	0.0040	0.163
LND_OWN	0.0370	0.0417	0.376
MIDDLE_INCOME	−0.0687	0.0515	0.183
LOWER_INCOME	−0.0577	0.0608	0.343
ASSOC	−0.1747	0.0408	0.000
OFF_FARMWORK	0.0080	0.0400	0.843
EXT_VISITS	0.0254	0.0069	0.000
LOCATION	−0.0572	0.0602	0.343
MKT_INFO	−0.1639	0.0463	0.000
CONS	−0.6631	0.1849	0.000
F(13,387) = 8.14; p < 0.01
Pseudo R^2 = 0.1686

Source: Field data, 2015.

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Data availability

Data supporting the findings of this study are openly available and can be found at https://doi.org/10.6084/m9.figshare.22743437.v1.