Factors affecting the market outlet choice of bamboo culm producers in Banja district, Awi zone, Ethiopia

Figures & data

Figure 1. Conceptual framework of the study.

Figure 2. Study area.

Table 1. Proportional sample size determination of sampled households

Kebele	Producers	Proportion	Sample size
Kessa	492	0.34	38
Gashena	350	0.24	27
Ledeta	325	0.22	25
Surta	282	0.2	24
Total	1449	1	114

Table 3. Characteristics of bamboo producers

Variables	Measurement	Minimum	Maximum	Mean	SD
Age	Year	26	75	53.11	10.76
Family size	Man equivalent	2	9	5.33	1.55
Total land size	Hectar	0.125	2.75	1.21	0.49
Land size for bamboo	Hectar	0.013	0.75	0.15	0.10
Bamboo farming experience	Year	3	47	19.34	9.03

Source: Field survey result, 2020.

Table 2. Hypothesis of variables used in multivariate probit model

Variable	Measurement/code	Expected outcomes on the market outlets
		Wholesalers	Retailers	Processor	Local trader
Sex	Dummy (1 male, 0 otherwise)	+ve	-ve	+ve	-ve
Education	Categorical	+ve	-ve	-ve	-ve
Family size	Continuous (man equivalent)	+ve	-ve	-ve	-ve
Price	Continuous (in birr)	+ve	-ve	+ve	-ve
Total land size	Continuous (hectar)	+ve	+ve	+ve	-ve
Experience	Continuous (in year)	+ve	-ve	+ve	-ve
Distance to the market	Continuous (walking hour)	-ve	-ve	-ve	+ve
Extension contact	Continuous (number of contact	-ve	-ve	-ve	-ve
Silviculture management	Dummy (1=Yes, 0 otherwise)	+ve	+ve	+ve	-ve
Number of culm harvested	Continuous (in number)	+ve	+ve	+ve	-ve

Table 4. Overall fitness of the model, probabilities and correlation matrix of alternative market outlets

Variable	Wholesalers	Retailers	Processors	Local traders
Marginal probability	16.8	46.2	60.8	54.3
Joint prob (success)	2.5
Joint prob (failure)	2.2
Number of draws	5
Log likelihood	−219.18
Wald $\chi$^2 (48)	102.52***
Prob $\chi$^2	0.000
	ρ1	ρ2	ρ3	ρ4
ρ1	1.00
ρ2	0.0793271	1.00
ρ3	−0.549 ***	−0.174	1.00
ρ4	0.269	−0.388 ***	−0.533 ***	1.00
Log likelihood ratio :	ρ21 = ρ11=	ρ41 = ρ32=	ρ42 = ρ43 = 0:	Chi^2(6) = 29.68*** prob $\chi$^2 =0.000

Note: ***, ** and * indicates the statistical significance at 1%, 5% and 10%, respectively.

Table 5. The results of multivariate probit model

Variable	Wholesaler	Retailers	Processors	Local traders
	Coef(se)	Coef(se)	Coef(se)	Coef(se)
Sex	0.726(0.744)	−0.131(0.506)	0.748(0.533)	0.193(0.426)
Read and write	−0.259(.369)	0.342(0.301)	−0.278(0.329)	−0.087(0.288)
Attend primary school	−0.226(.457)	0.607(0.380)	0.247(0.407)	0.134(0.354)
Attend secondary school	−4.314(103.9)	−0.777(0.845)	0.686(0.755)	−0.716(0.692)
Family size	0.328***(0.123)	0.119(0.089)	−0.231**(0.09)	0.115(0.083)
Price	0.030(0.034)	0.032(0.025)	0.027(0.025)	−0.007(0.023)
Total land size	0.737*(0.397)	0.470(0.320)	0.048(0.341)	−0.101(0.292)
Bamboo farming experience	−0.008(0.019)	−0.05***(0.024)	0.063***(0.023)	−0.037***(0.012)
Distance to the market	−0.001(0.004)	0.003(0.003)	−.02***(0.004)	0.009***(0.003)
Extension contact	−0.1003(0.112)	0.015(0.088)	−0.029(0.095)	−0.048(0.081)
Silviculture management	−0.061(0.370)	0.287(0.303)	0.664**(0.326)	−0.417(0.289)
Number of culm harvested Constant	0.001*(0.001) −4.769(1.604)	0.001*(0.001) −1.392(1.167)	.0003(0.0004) 0.326(1.169)	.0004(0.0004) −0.204(1.064)

Source: Field survey result, 2020.

Note: *** indicate the statistical significance of variables at 1%,

**indicates the statistical significance of variables at 5% and

*indicates the statistical significance of variables at 10%.