Advances in Crop Science and Technology
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Sorghum; Smallholder; Commercialization; Market participation; Probit model

Introduction

The Ethiopian agriculture is dominated by smallholder farmers which accounts for 96% of the total area cultivated and more than 90% of agricultural output produced (Birhanu F, 2021). Studies indicated that, smallholder farmers are a key solution for economic growth, and for alleviation of poverty and food security problems in developing countries. Considering this issue, Ethiopian government has targeted smallholder farmers as the focal point for economic transformation and agricultural development, and for meeting the current growing food demand (Dorosh P et al.,2018). In the country, smallholder farmers are highly characterized by their shortage of resources, heavily dependence on subsistence agriculture, household labor dependability, exposures of reduction of yields and lower price of their products (Addisu, 2018) [1].

So, in the long run, this subsistence agricultural production may not be a viable production system to ensure food security (Pingali, 1997). Commercial transformation of subsistence agriculture is an indispensable pathway towards economic growth and development for many agriculture dependent famers in developing countries including Ethiopia (Mitku A.2014). As known, in Ethiopia, cereals are the major food crops both in terms of the area they are planted, marketing and volume of production obtained. Out of the total grain crop area, 81.97 % (9,997,511.08 hectares) was under cereals and it contributed 88.69 % (about 290,808,263.25 quintals) of the grain production (CSA, 2022).

In Ethiopia among the cereal crops, sorghum is the fourth most important cereal crop after tef, maize and wheat in terms of area coverage and total production (CSA, 2022). It accounts for 13.50 % of the area covered by cereals (CSA, 2022). Sorghum is a multipurpose crop with more than 35% of it grown directly for human consumption and the rest used primarily for animal feed, alcohol, and industrial products (Nangobi and Mugonola, 2018). The main sorghum producing regions are Oromia and Amhara, accounting for nearly 80 % of the total production. The leading sorghum producing zones are East and West Hararge in Oromiya and North Gondar and North Shoa in Amhara (CSA, 2021) [2].

The share of sorghum in total cereal consumption at national level has been tended to increase in recent years. Moreover, because of the high prices of teff in recent years, even middle class households increased sorghum consumption, mixing sorghum with teff to make injera (USDA, 2012). According to UN COMMTRADE data, the country which was a net exporter in the first three years of the study period (2005-07) was a net importer in 2008-10. However, the volume of import was relatively significant in 2008 and 2010 (113 000 tonnes) and this is mainly attributed to food aid import, originating mainly from the US (Demeke M and Di Marcantonio F., 2013).

The marketing system for sorghum in Ethiopia is poorly developed, and has limited industrial use. In the country, only 11.5 percent of the crop is sold 74.0 percent being consumed at the local level. The remaining 9.2 percent is retained as seed and the rest is used as payment of wages in kind (1.2 percent) and animal feed (0.9 per cent) (AATF, 2011). This result shows, majority of Ethiopia’s smallholder farmers grow sorghum mostly for subsistence-oriented production. So, rural households’ participation in agricultural markets is vital important strategy for poverty alleviation and food security in developing countries (Heltberg R, and Tarp F., 2001) [3].

Being cognizant of role of market participation, Ethiopia has taken agricultural transformation as a means to tackle poverty and food insecurity problems through empowering smallholder farmers and pastoralists with tools, knowledge, and support needed to transition from a traditional subsistence orientation to one that is market focused and more commercialized (ATA, 2015). Even if the government of Ethiopia focused on commercialization of subsistence agriculture as priority policy decision, market participation by smallholder farmers in Ethiopia is limited and agricultural markets are fragmented and not well integrated into wider market systems which increases transaction costs and reduces farmers’ incentive to produce for the market (Mitku A., 2014) [4].

The reason for this is, specific study areas commercialization affected by institutional factors, infrastructural and market-related factors, resource factors, and household specific characteristics that marketing (Bekele A et al.,2010). Although there is a wealth of literature on smallholder commercialization in Ethiopia, it is mainly on grain crops and livestock and livestock product however market participation of the smallholder sorghum crops farmers in the country is still limited. However, the national marketed surplus ratio of sorghum which describes the commercialization level is 16.15%, which is perceived as low (CSA,2021).Therefore, it is vital to identify the determinant factors which influence sorghum producer farmers’ decision to participate in the market in order to benefit smallholder farmers from the marketing of sorghum in the study area [5].

Research Methodology

Description of the study area

The study area Gololcha and Shene Kolu Districts are located in Arsi Zone Oromia regional sate of Ethiopia. Arsi zone is found in the central part of the Oromiya National Regional State. The zone astronomically lies between 60 45’ N to 58‘N and 38 32 E to 4050’ E. It shares borderlines with the Regional State of Nations, Nationalities and People of Southern Ethiopia and also shares borderlines with East Shewa, Bale and West Hararge Zones. The Zone has the longest borderline of 450km with East Shewa Zone accounting about 43 percent of its total boundary length. It has the second longest line (350km) with Bale Zone. It shares the least borderline (43km) with the Regional State of Nations, Nationalities and People of Southern Ethiopia. Asela is the capital town of the zone. It is located at 175 km from Finfinne on Finfinne-Adama-Bale Robe main road. Also Asela is located at 75 km south of Adama town (Abdi, 2017) [6].

A brief description of study districts goes as follows. Shenen Kolu district is one of the district among 26 districts which are found in Arsi zone Oromia regional state, Ethiopia. The district is located at about 316 km from Addis Ababa, the capital city of Ethiopia and 241 km from Asella, which is the capital town of Arsi zone. The District is situated at northeast of Aseko and Anchar, Seru district in the south, Daro Lebu district in the east and Gololcha district in the west. The altitude of the district ranges from 1400 to 2000 metres. Generally, the district has a total area of 112,101 hectares and is classified into two agro-ecologies, highland (2%) the midland (28%) and the lowland (70%). The average temperature of the district is 32 °C and the average rainfall is 800 mm/year. The main rainy season of the district is in April, May, June, July, August and September. The soil type of the district is clay soil and sandy soil. Major crops produced in the district are coffee, maize, sorghum, teff and groundnut (SKWoA, 2022).

The second Gololcha district is bordered by Aseko district in the north, Amigna district in the south, Shenan Kolu district in the east and Chole district in the west. The altitude of the woreda is ranging from 1400 and 2500 meters above sea level. Generally, the district has a total area of 178,102 hectares and is classified into two agro-ecologies, the midland and the lowland with a share of 25% and 75% respectively. The average temperature of the district is 35˚C and the average rainfall is 900 mm/year. The main rainy season of the district is in April, May, June, July, August and September. The soil type of the district is silt and sandy soil. Major crops produced in the district include Coffee, Maize, Sorghum, Teff and Groundnut (GWoA, 2022) (Figure 1) [7].

Figure 1: Skeck of study area; Source: GIS shape file of Ethiopian administrate map.

Data type, source and method of data collection

This study used household survey data collected from Gololcha and Shene Kolu districts. Both primary and secondary data were used in this study. Before a start of actual data collection, facilitative works such as training of enumerators on interview procedures, and preliminary assessment to sampled kebeles was made. Primary data were collected using semi-structured questionnaire by trained enumerators. Both open and close-ended questions in line with the objective of the study were included in the questionnaire. Semi-structured questionnaire was administered on selected households to collect data on household characteristics, resource ownership, access and institutional variables relevant to meet the objective of the study. Secondary data helpful to the study were gathered from statistical Breau of Agriculture of Gololcha and Shenen Kolu districts, journals, research findings and different reports [8].

Sampling techniques and sample size determination

Smallholder sorghum producers are the target population for this study. To draw representative sample the research study has followed a three stage random sampling technique to select the study area and representative sample households. In the first stage Gololcha and Shene kolu districts were selected by using purposive sampling based on the potential sorghum production and accessibility to market among Arsi zone districts. In the second stage, three kebeles from Gololcha district and two kebeles from Shene Kolu district were selected purposively. In the third stages a total of 130 sorghum producer farm households during 2021/22 production year were selected randomly from the selected sample kebeles by using simple random sampling technique (SRS) based on probability proportional to size (PPS) using sample size determination formula developed by  Yamane, (1967) indicated in equation below. Several authors used this sample size determination approaches for instance (Haile et al., 2018) and (Ahmed et al., 2016) used this sample size determination formula. The sample size for the study was determined based on the following yamanes formula:

Where; Where: n = is the desired sampled size, N = is the total population(N=) and e = is the desired level of precision(0.09) as suggested by (Haile et al., 2018) to get desired minimum sample size of households at 91% level of significance with variability of 9%. Finally, a total of 130 sample households were selected for interview using probability proportional to size from each kebeles as presented (Table 1) [9].

Table 1: Sample size determination of smallholder sorghum farmers.

Method of data analysis

Both descriptive and econometrics methods of data analysis were employed to assess the determinants of Sorghum market participation.

Descriptive method of data analysis

Descriptive statistical analysis such as mean, percentages, and standard deviations was used in the process of examining and describing farm households’ demographic characteristics, resource ownership,  institutional and infrastructural service, production characteristics and farm input use. T-test and Chi-square test were used for the existence of any statistically verifiable differences among farmers participated and their counterfactuals.

Econometric analysis

This part of the analysis deals with identifying determining factors of sorghum market participation decision of households. So far, different limited models having their positive and negative part such as restrictive Tobit, double hurdle model, probit and Heckman two stage selection model have been used to study crop market participation. As to which type of model to use among these models depends up on the nature of dataset and underlying assumptions of the model. The dependent variable is dichotomous, representing farmers’ decision to participate or not in sorghum marketing [10].

For such a dummy dependent variable, probit model is appropriate (Gujarati, 1995). Different authors used probit analysis on the decision to market participation (Egbetokun & Omonona, 2012; Mbitsemunda & Karangwa, 2017). Hence, to analyze the determinants of smallholder farmers’ participation in the sorghum marketing probit model was used. In this model, the probability that Y = 1 (the probability that the household participates in sorghum marketing) was estimated using the cumulative standard normal distribution function. The researchers opted to use the probit regression model to identify the factors that determine the decision of smallholders to participate in the sorghum market hence the dependent variable is dichotomous [11].

Accordingly, the dependent variable assumes only two values; 1 if the household participates in the sorghum market and 0 if he/she does not. Assume that Y can be represented by market participation and the regression equation is representing market participation (dependent variable, Y) and we also have a vector of regressors X, which are assumed to influence the dependent variable (Y). The probit model is built on a latent variable with the following formula (Wooldridge, 2002):

Where: Yi *= is a latent variable representing farmers discrete decision whether to participate in sorghum market or not; Xi= is explanatory variables hypothesized to affect farmers decision to participate in sorghum market, βi= is a vector of parameters to be estimated which measure the effect of explanatory variables on household decision to participate in sorghum market.

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