Why do cocoa farmers use unapproved pesticides? Empirical evidence from Obuasi Municipality, Ghana

Figures & data

Table 1. Use of unapproved pesticides.

Unapproved pesticides	Frequency	Percent
Yes	163	42.34
No	222	57.66
Total	100	100.00

Source: Hyde-Cooper et al., 2023.

Table 2. Types of unapproved pesticides mostly used by cocoa farmers (multiple responses).

Unapproved pesticides	Frequency	Percent
Consider	33	8.25
Super10	21	5.25
Argine	11	2.75
Fastrack	10	2.50
Polythrine	15	3.75
Dursban	16	4.00
Kombat	17	4.25
Pyrethroids	18	4.50
Topsin	19	4.75
Sumitor	19	4.75
Sumico	19	4.75
Lamtor	21	5.25
Controller	22	5.5
Sunpyrifof	23	5.75
Confidiz	29	7.25
Akatesuro	32	8.00
DDT	32	8.00
AcetaStar	41	10.25
Okumakate	62	15.5
Actara	21	5.25
Confider	19	4.75
Gramaxone	63	15.75

Source: Hyde-Cooper et al., 2023.

Table 3. Farmers’ source of information on unapproved pesticides.

Responses	Frequency	Percent
Friends and family	18	11.04
Media	11	6.75
Cocoa extension agents	5	3.07
Agro-chemical shops	129	79.14
Total	163	100.0.

Source: Hyde-Cooper et al., 2023.

Table 4. Perception of farmers on the use of unapproved pesticides.

Perceptions of farmers on the use of unapproved pesticides	Mean	Std. Dev
Farmers who use unapproved pesticides should face legal consequences	2.33	1.23
The government should impose stricter regulations on the use of unapproved pesticides	2.64	0.57
The effects of unapproved pesticides are observable	3.11	0.89
Unapproved pesticides are easy to use	3.20	0.85
Unapproved pesticides are compatible with my beliefs and culture	3.35	0.78
I am confident in my ability to identify and avoid unapproved pesticides in the market	3.38	0.80
Unapproved pesticides are more effective than some approved pesticides	3.58	0.79
Unapproved pesticides are more affordable than approved alternatives	3.92	0.03
Unapproved pesticides can be tried on a small scale	4.16	0.81
I trust the safety standards of unapproved pesticides more than approved ones	4.29	0.20
I feel pressured to use unapproved pesticides due to market demands	4.74	0.13
Mean perception index = 3.41

Source: Hyde-Cooper et al., 2023.

Table 5. Socio-economic characteristics of farmers.

Continuous variables	Min	Max	Mean	Std. Dev
Age	22	91	54.00	12.76
Household size	1	32	7.30	4.25
Number of dependents	0	30	5.58	4.03
Years of farming experience	1	70	21.86	12.83
Farm age	1	70	20.74	12.52
Farm size	1	32	6.92	5.48
Years of formal education	0	16	9.02	3.37
Income	500	205000	6483.5	15177.69
Discrete variables	Frequency			Percent
Gender
Male	263			65.75
Female	137			34.25
Religion
Christianity	300			75.00
Islam	100			25.00
Marital status
Married	234			58.50
Not Married	166			41.50
Access to Knapsack sprayer
Yes	250			62.50
No	150			37.50
Access to labour
Yes	270			67.50
No	130			32.50
Access to traceability
Yes	237			59.25
No	163			40.75
Access to cooperative services
Yes	343			85.75
No	57			14.25
Access to Extension services
Yes	370			92.50
No	30			7.50

Source: Hyde-Cooper et al., 2023.

Table 6. Socioeconomic factors influencing farmers’ use of unapproved pesticides.

Characteristics	Coef	Std. Err
Education	0.05**	0.01
Age	0.01	0.03
Sex	−0.07	0.07
Dependents	−0.01	0.01
Ownership status	0.02	0.09
Farming experience	0.21**	0.01
Farm size	0.01**	0.01
Farm age	0.01	0.01
Access to knapsack sprayer	0.05***	0.08
Access to traceability	−0.05	0.07
Access to labour	0.14***	0.08
Membership of cooperative	−0.05	0.10
Access to extension services	0.19	0.13
Income	1.63	2.17
Constant	4.04	0.22

Hyde-Cooper et al., 2023.

NB: ***1%, **5%, *10% Significance level.

Log pseudo likelihood=-51.124; Wald chi²=47.28, Prob > chi²=0.00; Pseudo R²=0.38.

Data availability statement

Data will be made available upon request