Determinants of potato market participation among smallholder farmers in Mida Kegn, Ethiopia

Abstract

In Ethiopia, agricultural output commercialization plays a crucial role in maintaining the share of the sector in the economic growth of the country. This study was designed to analyze determinants of potato market participation among smallholder farmers in the Mida Kegn district of West Shoa Zone. A stage sampling procedure was employed to select 150 sample respondents randomly from the district. To accomplish the study, data were accessed from both primary and secondary data sources. Primary data were accessed through a structured questionnaire. The descriptive result indicated that 38% and 62% of sample households were categorized as non-participant and participant farmers in the potato output market, respectively. Moreover, the result shows that about 54.46% of potato produce was supplied to the market from total produce. The result of the double-hurdle model analysis showed that experience and land allocated for potatoes influenced potato commercialization positively, whereas family size, dependency ratio, and distance to all-weather roads were affected negatively. Consequently, the study suggests that all concerned bodies should focus on facilitating farmers to participate in off/non-farm activities, supporting potato producers through the provision of training and access to improved seed, proper utilization of land resources, and giving enough family planning training by health extension workers.

Keywords:

• commercialization
• probit
• intensity
• smallholder farmers
• Ethiopia

PUBLIC INTEREST STATEMENT

Agriculture is recognized as it plays a crucial role in the economy of Ethiopia. However, the sector is hindered by many constraints. Advancing the commercial orientation of smallholder farmers would have higher implications in improving the share of the agricultural sector to promote food security and enhance the income of smallholder farmers in the country. Nowadays, it needs more work to be done to improve agricultural commercialization for the several benefits that could be obtained from the activities. This study has observed the determinants of potato market participation of farmers in West Shoa, Ethiopia. Policymakers are required to act on the possible means to minimize the challenges of marketing farm produce. Particularly, it requires capacitating farmers through the provision of training and access to improved seed, proper utilization of land resources, and giving due attention to experience sharing and training commercial-oriented production.

1. Introduction

Agriculture accounts for around 32.5% of Ethiopian gross domestic product (GDP) and contributes more than 80% of the country export earnings. Agriculture also enhances economic activities by providing employment opportunities for about 72.7% of the rural farmers and continues as a means of producing income and source of economic welfare for about 83% of the small-scale participants (Gurmu, 2020; National Bank of Ethiopia NBE, 2021).

In the agricultural sector, root crops have the highest share of the traditional food system and are used as a source of income in Ethiopia. Root crops took up about 13.79% of the area under all crops at the national level, which is very low in area coverage when compared to grain crops, which cover about 34.83% at the national level. Among root crops, potatoes are listed in the first stage in terms of the area coverage for cultivation, followed by sweet potato and taro/godere. Therefore, potato is the principal root crop produced in Ethiopia, Africa, and probably has the largest potential area of land for cultivating potatoes. Out of the total crops cultivated area, 2.7% and 14.93% were under potato at the national and regional levels, respectively.

Likewise, among root crops, potatoes shared 29.81% and 42.7% in terms of area coverage at national and regional levels, respectively, concerning the productivity of potatoes 139.20 and 124.5 quintals per hectare at the national and regional levels, respectively (CSA Central Statistical Agency, 2019). In Mida Kegn district, the average productivity per hectare of potato exceeds productivity at the national and regional levels, which are 150, 139.2, and 124.5, respectively, and the smallholder farmers involved in producing this sector are subject to the informal market. The intensity of potato market participation of the farmers is semi-commercial due to the limited supply of potato seeds during planting and also marketing problems such as market infrastructure like roads, transportation, and communication that facilitate the integration of the rural economy and promote market orientation production in the study area (DMO District Market Office annual report, 2020); as a result, farmers were unable to harness existing potential through generating a more marketable surplus.

In Ethiopia, potatoes are mostly sold to the market as fresh produce and seeds, and no potato production-processing-marketing chain is available. Many researchers, in different places, have done commercialization studies in Ethiopia (Regasa et al., 2020; Senbeta, 2018; Tufa et al., 2014; Wonduwossen & Bekabil, 2014). Commercial transformation of subsistence agriculture is among the second growth and transformation plan (GTP-II) and is expected to enhance domestic growth from agricultural returns. However, the majority of potato producers produce potato for home consumption or subsistence-oriented agriculture which diverges from the GTP-II of Ethiopia designed to focus on the commercial transformation of smallholder farmers from subsistence agriculture. This reality shows that commercialization of farming is below expectation, and smallholders are still participating in the home consumption level or subsistence-oriented, how income could be increased. Hence, it is difficult for smallholder farmers to participate in the market and difficult to enjoy the benefits of participating in the market unless restraints are solved and a conducive environment is created (Ministry of Finance and Economic Development MoFED, 2016).

Although the Ethiopian government focused on the commercial transformation of subsistent agriculture, potato market participation by smallholder farmers was not integrated and fragmented by many factors which increased the cost of marketing and thereby reduced farmers’ motives to produce for commercialization. Potato is a vital income-generating crop for smallholder farmers, even though it is a major food crop in Ethiopia. While a large percentage is reserved for family consumption, farmers supply a small part of their potato produce. Hence, most potato produce in the area is not marketed; on the contrary, the farmer uses their produce for family consumption, seed, and possibly other uses (Gebreselassie et al., 2017). Accordingly, increasing market participation among farmers has the potential to boost them to improve income levels by maximizing yield and expanding production. In this study, commercialization of potato production develops an opportunity for enhancement of commercial production of potato, and the farmers in the district require the integration and coordination of various participants like extension, agricultural research institute, marketing, and other institutional services by enhancing the application of improved agricultural technology/inputs, farming techniques, and supply of improved potato seeds for users. Therefore, the objective of the study was to identify determinants of potato market participation and estimate the volume of participation among potato producers in the Mida Kegn district, West Shoa, Ethiopia.

2. Research methodology

The study was undertaken in Mida Kegn woreda of West Shewa, Oromia Region, Ethiopia. Mida Kegn district is located 202 km away from Addis Ababa to the west. It shares borders with Gindaberet to the south, Horo Guduru Wollega to the West Challia and Liban Jawi to the north, and Ambo and Toke Kutaye district to the east. The area covers about 42,421 hectares and has 24 rural and 2 urban kebeles (Figure 1). The woreda total population was 189,336 having a rural population of 170,282 (89.9%) and an urban population of 20,054 (10.1%), of which more than 89% depend on farming activities while the rest 11% depend on off-/non-farm activities. The district is characterized by the main economic activities of a subsistence mixed farming system, which is crop production and livestock raising. The major crops cultivated in a district are maize with an average yield of 60 quintals per hectare, barley 30 quintals per hectare, 40 quintals of wheat per hectare, sorghum 26 quintals per hectare, and potato 150 quintals per hectare (DOANR District Office of Agriculture and Natural Resource, 2021). Livestock production is another source of income next to crop production.

Figure 1. Map of the study area.

Source: Adopted and manipulated from Ethiopian map: GIS, 2023.

Land use of the woreda shows that 23,076 ha is cultivated, 11,340 ha is grazing land, 2,005 ha is covered by bushes, shrubs, and forest, and 6,000.037 ha have been used for rocks, sands, halls, and infrastructural service.

2.1. Sampling procedure and sample size

The district was selected purposively. The reason is that there was potential for potato production in the Mida Kegn district. A stage sampling technique was employed to select representative sample households. In the first stage, the Mida Kegn district was purposively selected from the West Shoa Zone based on the potential of potato production. In the 2nd stage, among 15 kebeles having potential for potato production, 4 kebeles, namely Lalise Gosu Halelu, Baro Bidaru, Damu Wange, and Tuye Goda Chukala, were selected randomly. Lastly, the total number of farmers in the selected kebeles was acquired from the agricultural office, and a total of 2870 farmers were found in four selected kebeles; 150 sample household heads were selected using a simple random sampling technique supported by probability proportional to the target population (Tafesse et al., 2020). The total sample household size selected 150 was determined using a simplified formula given by Yamane (1967). Consequently, as per the Yamane formula, 8% error tolerance was used to compute sample households (see Table 1).

Table 1. Sampling frame and sample size

Name of sampled kebeles	Total potato producers household (HH)	Proportion sampled HH (%)	Number of sampled HH heads (number)
Baro Bidaru	744	25.9	39
Damu Wange	762	26.6	40
Tuye Goda Chukala	628	21.9	33
Lalise Gosu Halelu	736	25.6	38
Total	2,870		150

Source: DOANR and Own Computation, 2020.

n = $\frac{N}{1+N\left(e\right)2}$ where n is the sample households, N is the total target population/households in the four kebeles, and e = 0.08 is the level of precision.

2.2. Method of data collection, type, and sources

Producer’s survey and key informant oral questions were followed to gather primary data on demographic, socioeconomic, institutional, and personal factors that affect the commercialization of individuals. Additionally, a structured questionnaire was employed to collect data from selected producers. To supplement primary data, secondary data were also reviewed from different sources of data. Secondary data that are related to this study were collected from Mida Kegn agriculture and natural resource office, Central Statistical Agency (CSA), Ministry of Agriculture and Rural Development (MoARD), and from published journals, articles, and others.

2.3. Method of data analysis

Descriptive data analysis used mean, standard deviations, and percentages to describe the household’s characteristics. Furthermore, the X² test and t-test are used to compare commercialized and non-commercialized farmers in terms of dummy and continuous explanatory variables, respectively.

In this study, the commercialization of potato production was analyzed from the output side. The advantage of this approach is that commercialization is treated as a range, thereby avoiding crude distinction between commercialized and non-commercialized households (Agwu et al., 2013). Using this approach was more common than the input side. According to Strasberg et al. (1999) and von Braun and Kennedy (1994), commercialization index for crop production can be defined as: $CIp=\frac{Grossvalueofallcropsalesofhhiinyearj}{Grossvalueofallcropproductionofhhiinyearj}X100$

Likewise, to analyze determinants of potato commercialization, double-hurdle model (DHM) was employed. The DHM, introduced by Cragg (1971), embodies the idea that an individual’s decision on the extent of participation in an activity is the result of two processes: the first hurdle determining whether the individual is a zero type and the second hurdle determining the extent of participation given that the individual is not a zero type. A key feature of the model is that there are two types of zero observations: an individual can be a zero type, and the outcome will always be zero whatever his or her circumstances at the time of the decision; alternatively, the individual might not be a zero type, but his or her current circumstances might dictate that the outcome is zero; this sort of zero is usually classified as a censored zero after (Tobin, 1958).

The DHM is a corner solution outcome like Tobit. Contrary to the Tobit model, the double-hurdle approach does not require the assumption that the participation and the intensity of participation can be determined by the same process (Burke et al., 2015). It therefore provides a useful framework to examine separately the effects of variables on the probability of participation in crop markets and the intensity of sale. The model considers that each household has to overcome two hurdles in the marketing decision-making process and specifies for each step of the decision on the corresponding equation. The first equation specifies the decision to participate or not in the agricultural markets, while the second one refers to the equation of the amount of sale.

On the other hand, empirical studies have shown the inadequacy of the standard Tobit model (Tobin, 1958) in cross-sectional analysis to account differences about the generation of zero observations. Since it is nevertheless implausible that all zero observations in the level of commercialization arise from standard corner solutions generated by a constrained budget, I want to emphasize the use of double-hurdle specifications distinguishing between abstentions/no choice and corner solutions. Thus, participation and commercialization decisions are assumed to steam from two separate individual choices, and the determinants of the two decisions are allowed to differ (Blisard & Blaylock, 1993; Blundell & Meghir, 1987; Garcia & Labeaga, 1996; Jones, 1989; Yen & Jones, 1996).

Determinants of potato market participation (output commercialization index greater than 50% as decided to commercialize) were analyzed by first stage of DHM, and intensity of potato market participation was estimated by second stage of DHM, which is truncated regression analysis. According to Habtamu and Krishna (2021), “probit model was estimating the probability participation as function of some socio-economic variables and it estimate quantity used. Therefore, when we have zero observation, we should not use Tobit model or ordinary least estimate (OLS). Tobit model analysis may be applicable only in those cases when the latent variables (Yi*) take negative values, because it assumes the observed zero values are consequence of non-observability. The Heckit and DHM are related in identifying rule of determining the discrete (positive and/or zero) out-comes. However, heckit as opposed to double-hurdles assume’s there were ‘no zero observation’ in the second once the first-stage selection is passed, but in case of the double-hurdle zero values can be reported in both stages” (Tobin, 1958). Therefore, in the first stage, probit model assumes factors that affect market participation decision to potato product by smallholder farmers and takes the values of “1” if smallholder farmers participate and “0” otherwise. The 1st stage (Cragg, 1971) can be given by:

${\mathrm{Y}}_1^{\ast }=\hspace{0.17em}{\beta }_1{\mathrm{X}}_{1\mathrm{i}}+{\epsilon }_{1\mathrm{i}}$ ${{\mathrm{Y}}^{\ast }}_1$= $\left\{\begin{array}{c}1ifrespondentsparticipatetopotatomarket;{\mathrm{Y}}^{\ast }>0\\ 0if{\mathrm{Y}}^{\ast }<0otherwise\end{array}\right.$ where Yi* is a latent variable which represents market participation, $X_{1i}$ represents explanatory variables which affect potato market participation of respondents, ${\beta }_1$ parameter and ${\epsilon }_{1i}$ represent standard error terms. At the second stage, the truncated model was followed to analyze factors determining intensity of potato commercialization (Wooldridge, 2012). That is, the truncated regression uses observations only from farming households, whose commercialization index is positive or greater than zero.

Di = xiβ + µi, µi~ Ν (0, δ) $Di=[[\begin{array}{c}Di\ast ifDi\ast >0andYi=1\\ 0otherwise\end{array}]]$

where Di is the amount of commercialization which depends on latent variable Yi* being greater than zero and conditional to market participation decision. If both decisions (decision to commercialize and level of commercialization) are made by the individual farmer independently, the error terms are assumed to be independently and normally distributed as ui~ N (0, σ²). The log-likelihood functions as the DHM that nests a probit model and a truncated regression model used to interpret coefficients.

2.4. Variables’ definition and working hypothesis

2.4.1. Dependent variables

2.4.1.1. Potato market participation decision

Is a dichotomous variable which assumes 1 if the households included in the sample supply potato to market for sale and 0 otherwise.

2.4.1.2. Intensity of potato commercialization by farmers

Is a continuous dependent variable which assumes output commercialization index greater than 50% and less than 100%, since potato is produced for dual purpose, i.e. for sale and for home consumption.

2.4.2. Independent variables

Independent variables selected for the models are following the reviewed literature, which is physical capital; demographic, infrastructural, and institutional variables are expected to have influence on market participation of potato and level of commercialization of potato. The variables considered for this study are sex, age, land allocated for potato production, family size and dependency ratio, education of household head, off- and non-farm income, livestock holdings, membership to farmers institutions, access to credit, frequency of extension contact, experience in potato production, access to market information, distance to district market, and distance to all-weather road; some variables have high multicollinearity with considered variables and omitted from the analysis (i.e. “land allocated for potato production” with “amount of potato produced”)(See Table 2).

Table 2. Summary of variables’ description and hypothesis

Variable code	Description	Type	Measurement	Expected sign to dependent variables		Supportive studies
PMPD	Dependent variable indicating potato market participation decision	Dummy dependent	1 = yes, 0 = no	PMPD	LPMP
LPMP	Dependent variable indicating level of potato market participation	Continuous dependent	Littre per hectare
SEXHH	Sex of the household head	Dummy	1 = male, otherwise = 0	-	-	Aliyi et al. (2021)
AGEHH	Age of household head	Continuous	Years	-/+	-/+	Endiris et al. (2021)
EXPROD	Years of farmers experience in potato production	Continuous	Number of years	+	+	Habtamu and Krishna (2021)
LANDAL	Land allocated for potato production	Continuous	Hectare	+	+	Endalew et al. (2020)
FASDRA	Family size and dependency ratio of household	Continuous	Number	-	-	Haile et al. (2022)
EDUSHH	Education status of household	Continuous	Year of formal schooling	+	+	Habtamu and Krishna (2021)
OFINCO	Annual earnings of household from off-farm income activities	Dummy	1 = yes, 0 = no	+	+	Emilola et al. (2016)
TLIVO	Number of livestock owned	Continuous	TLU	+	+	Dube and Guveya (2016)
PRCOOP	Participation in cooperative member	Dummy	1 = yes, 0 = no	+	+	Akinlade et al. (2016)
ACRED	Household access to credit service	Continuous	1 = yes, 0 = no	+	+	Haile et al. (2022)
FREXC	Frequency of extension contact	Continuous	Number of contact	+	+	Endalew et al. (2020)
ACCMI	Access to market information	Dummy	1 = yes, 0 = no	+	+	Aliyi et al. (2021)
DTAWRO	Distance to all-weather roads	Continuous	Walking hour	-	-	Melkamu et al. (2017)
DMARK	Distance from the nearest market	Continuous	Walking hour	-	-	Chala and Chalchisa (2017)

Source: Own Computation.

3. Results and discussion

3.1. Description of demographic and socioeconomic variables.

The descriptive statistic results of the socioeconomic, demographic, and institutional characteristics of the sampled households for the study were presented (see Tables 3 and 4). T-test result indicates the significant mean difference between commercialized and non-commercialized sample households at a 5% significance level in terms of family size and dependency ratio. The average age of the sample respondents was found to be 37.92. An independent t-test result indicates the significant mean difference between commercialized and non-commercialized sample households at a 5% significance level in terms of age. Households with better information access are more likely to participate in cash crop production and increase commercialization decisions. Of the total sample respondents interviewed, 59.3% of sample respondents had access to market information. The Chi-square value shows a significant difference between commercialized and non-commercialized sample households at a 1% significance level in terms of access to market information for potato commercialization. Out of the total sampled household heads, about 86% were literate and 14% were illiterate. The t-test value shows significant mean differences between literate and illiterate farmers at a 1% significance level in terms of education.

Table 3. Summary descriptive analysis of sample households for dummy independent variables

Variables’ description	All samples (N = 150)	Commercialization decision				Total sample percent	χ^2 value
	Total	Commercialized (n = 93)		Non commercialized (n = 57)
		Number	Percent	Number	Percent
SEXHH	150	93		57			1.3
Male	141	90	96.77	51	89.47	94
Female	9	3	3.23	6	10.53	6
EDUSHH	150						8.5***
Literate	129	86	92.5	43	75.44	86
Illiterate	21	7	7.5	14	24.56	14
ACRED	35	31	33.3	4	7	23.33	0.5
ACCMI	89	62	66.7	27	47.3	59.33	5.5***
OFINCO	32	22	23.65	10	17.54	21.33	1.7
FREXC	104	69	74.19	35	68.62	69.33	0.8
PRCOOP	62	48	51.6	14	24.6	41.33	1.5

Note: *** shows a statistical significance level.

Table 4. Summary for continuous independent variables

Variables’ description	Commercialization decision			t-value
	Commercialized (n = 93)	Non commercialized (n = 57)	Total
	Mean	Mean	Mean
FASDRA	5.6	7.2	6.4	−6.20***
AGEHH	37	38.84	37.92	−2.42**
EXPROD	9.95	9.5	9.73	1.2
DMARK	9.37	9.45	9.41	1.48
DTAWRO	4.02	3.8	4	0.33
TLIVO	8.26	7.24	7.75	1.87
LANDA	0.56	0.38	0.47	0.13

Note: *** and ** imply statistical significance at 1% and 5% levels.

3.2. Potato production and marketing in Mida Kegn

From West Showa districts, Mida kegn was considered as a potential producer of potato, and potato is produced for both home consumption and market sale in Mida Keng. Among potatoes supplied to the market, 37.3%, 46.7%, and 16% were sold at farm gates, village markets, and district markets, respectively, due to the lack of a well-organized all-weather road to capture the product to the nearest available market center, and there is no market integration of the product for smallholder of potato producer. The major types of crops produced in Mida Kegn woreda were potato, barley, maize, wheat, bean, and teff. Sample households allocated more land for barley and potato, which were on average 0.53 and 0.47 hectares, respectively. Barley production competes with potatoes for land in the study area. The area allocated to those crops is shown in Figure 2.

Figure 2. Land allocations for different crops in hectares.

From a total of sampled households, about 88% of potato producers in the study area produce potatoes rain-fed and 12% twice a year by using irrigation. In the study area, both improved and local seed varieties of potato were used for potato production. The improved seeds of potatoes grown in selected districts are Belete, Gudanie, and Jalannie, and the major local seeds of potatoes grown are Bule and Nech Ababa. Of the total sample households, about 60% used improved potato varieties, while only 15% used local varieties, and about 25% of sample households used both improved and local seeds in the 2019 production season. Of local seed users, about 75.4% and 24.6% use Bule and Nech Ababa, respectively. From improved seed users, about 52% used Belete, 30% used Gudanie, and 18% used Jalannie variety. The average price of potato products was 520 ETB (Ethiopian Birr) per quintal. The average cost of local variety seeds was 450 ETB per quintal, while the average cost of improved seeds (Belete, Gudanie, and Jalannie) was 800,720 and 650 ETB per quintal, respectively. This result shows the presence of a gap between potato product price and seed price. About 55% of sampled households left potato products in the soil traditionally for seeds and future consumption purposes and used intercropping with barley or beans. Forty-five percent store temporarily only for consumption purposes and used the land for other crops. As a result, sample farmers reported that they bought seeds and faced a shortage of supply of potato seeds during planting.

All the respondents produced potatoes each year continuously; fluctuations in price trends of production and seeds from season to season were reported by respondents. Opportunities of producers for potato production in the study area were availability of rainfall and favorable climate conditions reported by about 88% of respondents and 12% of respondents reported irrigation availability. The major constraints of potato producer sample farmers faced were a shortage of supply of improved seeds reported by 30%; diseases and pest problems reported by 20%; high production cost reported by 25%; the low price at harvesting time reported by 10%; and lack of infrastructure like all-weather road reported by 15%. The income of sample respondents from potato production was high in all crops produced. This result implies that potatoes generated significant income for farm households in the study area (see Figure 3).

Figure 3. Average cash annual income in ETB of sample households from sales of different crops.

3.3. Status of potato commercialization in the study area

In this study, the category was based on output crop commercialization index of less than or equal to 50% as non-commercialized and commercialized if crop commercialization indexes are greater than 50%. Depending upon the produce sold in the market from total sample households, about 57 (38%) were none commercialized, because of more than 50% of the value of produce are for home consumption and 62% were commercialized; more than 50% of the produce are for sale. The average intensity of potato commercialization was 54.46% including output commercialization index that results greater than zero (see Table 5). This implies that more than half of potato productions were oriented towards market.

Table 5. Market participation index of potato production

Commodity	Commercialization status		Total
Potato	Commercialized	Non-commercialized
	Mean	Mean	Mean
	63.8	45.12	54.46

Source: Own survey result, 2020.

3.4. Results of the econometric model

Ramsey RESET test was used for model specification and insignificant (prob >F = 0.0274) indicating that there were no omitted variables. A robust method was also employed to analyse the problem of heteroscedasticity. Probit model analysis results show that the decision to potato market participation in the study area is significantly influenced by family size and dependency ratios, distance to all-weather roads, land allocated, and experience in potato production (see Table 6).

Table 6. Estimate of double-hurdle model for potato market participation decision and level of participation

	Commercialized = 1, otherwise = 0
Variables	Coef.	Robust Std. Err.	Z	P>z	mfx
Age of household head	−0.026	0.079	−0.33	0.738	−0.008
Sex of household head	0.094	0.672	0.14	0.888	0.032
Family size and dependency ratio	−0.841***	0.164	−5.13	0	−0.282
Educational status	0.59	0.548	1.08	0.282	0.216
Non/off farm income	0.1952	0.349	0.56	0.577	0.063
Livestock holdings	0.0142	0.044	0.32	0.751	0.004
Experience in potato pro.	0.402**	0.16	2.51	0.012	0.135
Access to credit	−0.463	0.3161	−1.46	0.144	−0.164
Extension services	0.357	0.34	1.05	0.294	0.124
Access to market information	0.275	0.438	0.63	0.53	0.093
Farm distance from all-weather road	−0.631***	0.224	−2.81	0.005	−0.212
Distance from district market	0.075	0.109	0.69	0.493	0.025
Participation in social organization	0.315	0.318	0.99	0.323	0.104
Land allocated for potato	5.130***	1.577	3.25	0.001	1.724
_cons	1.256	2.738	0.46	0.646
	Number of Ob = 150
	Wald chi2 (14) = 65.12
	Prob>chi2 = 0.000
	Pseudo R2 = 0.5278
	Log pseudolikelihood = −47.034

Notes: Computed from survey result, 2020; ***, **, and * represent 1%, 5%, and 10% level of significances, respectively.

3.4.1. Family size and dependency ratio (FASDRA)

Family size and dependency ratio were found to influence potato market participation decisions of farmers negatively and significantly at a 1% probability level. The value of marginal effect shows that, as family size and dependency ratios of smallholder farmers increased by one person, the probability of producers’ decision to commercialize potato produce would be decreased by 28.2% (see Table 6). This indicates that keeping other variables constant the more family size and dependency ratios households have resulting in less participation in potato marketing. This might be due to the majority of potato produce being used for home consumption, and the result of the study was consistent with the finding of Tura et al. (2016).

3.4.2. Distance to all-weather roads (DTAWRO)

Distance to all-weather roads was found to influence farmers’ potato market participation decisions negatively and significantly at a 1% probability level. The marginal effect shows keeping other factors held constant as distance to all-weather roads increase by 1 km, the likelihood of farmers’ decision to supply potato produce would have been reduced by 21.20%. This shows that distances to all-weather roads increase transaction costs and opportunity cost of time. The result is consistent with the findings of Melkamu et al. () and Senbeta (2018).

3.4.3. Experience in potato production (EXPROD)

Experience, which is the number of years a farmer has been involved in the production of potato, influences market participation of potato producers positively and significantly at a 5% probability level. The marginal effect implies that, for each additional experience in potato production, the probability of households’ participation in potato marketing would have increased by 13.5%, keeping all other factors constant. This shows that farmers having more experience in the commercialization of crops which accumulated over time might have been increasing the probability of commercialization when compared with less experienced one. The result is in line with the finding of Abebe (2018) and Habtamu & Krishna (2021) that experienced farmers who have greater access to productive resources can apply improved agricultural technologies and are expected to be faster in adopting improved ideas than less experienced farmers.

3.4.4. Land allocated for potato production (LANDAL)

Holding other explanatory variables constant, land allocated for potato production household head owned found to have positive and significantly affected farmer’s decisions to potato market participation at 1% probability level. The marginal effect implies that, for each additional hectare of land, the probability of households’ potato commercialization would increase on average by 17.24%. This might be due to economies of scale that would encourage farmers to harvest more produce and increase their market participation in potato production. The positive sign of farm size indicated that household heads who devoted more land to potatoes could have more probability of commercialization than those allocated smaller land for potato production. The result is in line with the finding of Chala and Chalchisa (2017) and Tafesse et al. (2020) that size of cultivated land influences commercialization and level of commercialization as buyers of fertilizers improved seed and herbicides positively.

4. Conclusions

Agricultural output commercialization plays a significant role in the share of agriculture in GDP and could solve the agricultural produce supply deficiency problem. Therefore, commercialization of root crops like potatoes should be increased in expectation of poverty alleviation, enhanced income of smallholder farmers, and reduced agricultural output wastages. Thus, the study is designed to analyze determinants of potato market participation and intensity of participation in the Mida Kegn district. The result from the DHM was that the probability of households participating in potato marketing was positively affected by the experience of agricultural product commercialization, livestock holding, and land allocated for potato and non-farm activities, whereas family size and dependency ratio and farmers’ distance from all-weather roads influence potato market participation and intensity of participation negatively.

How to cite

Habtamu Rufe Gurmu, Shibiru Kebede Boka, and Adane Edao Shate (2023). Determinants of Potato Market Participation among Smallholder Farmers in Mida Kegn district of West Shoa, Ethiopia. Cogent Food and Agriculture

Acknowledgment

I would like to express my warm gratitude to Mr. Adane Edao and Mr. Shibiru Kebede for their technical guidance, personal encouragement, and continuous patience from proposal write-up and questionnaire development up to submission of the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Habtamu Rufe Gurmu

Habtamu Rufe Gurmu (MSc in Agricultural Economics) is a Lecturer and Researcher at Dambi Dollo University, Department of Agricultural Economics. His research interests include agricultural productivity and profitability, food security, impact analysis, employment and unemployment analysis, and marketing analysis.

Shibiru Kebede Boka

Shibiru Kebede Boka (MSc in Agricultural Economics) is expert and researcher at Mida Kegn district of Agricultural office. His research interests include agricultural productivity, food security and marketing analysis.

Adane Edao Shate

Adane Edao Shate (MSc in Agricultural Economics) is a Lecturer and Researcher at Dambi Dollo University, Department of Agricultural Economics. His research interests include efficiency, agricultural productivity and profitability, employment and unemployment analysis, and marketing analysis.