313. Farm Power in Senegal.Docx

Invited paper presented at the 6th African

Conference of Agricultural Economists, September 23-26, 2019, Abuja, Nigeria

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Farm power transition and access in Senegal: Patterns and constraints

Getaw Tadessea, Anatole Goundanb and Saer Sarrc aAfrica Region, International Food Policy Research Institute, Addis Ababa, Ethiopia bAfrica region, International Food Policy Research Institute, Dakar, Senegal c Macroeconomic Analysis Office of the Senegalese Institute for Agricultural Research

Abstract

This paper aims at documenting evidences on the patterns and constraints affecting the sequential and simultaneous transition of farm power use from manual to animal to engine. It also aims at exploring access to farm equipment through ownership and rental service. Based on a household data collected under the huge and ambitious project called ‘Senegal Agricultural Policy Project’, the result generally confirms the very low use of farm machinery powered by engines despite years of efforts to support agricultural mechanization programs. However, the use of improved farm equipment powered by animals has shown a sharp increase overtime. The study further demonstrated the variation of constraints in farm mechanization transitions defined by sources of power. While demand side constraints such as farm size and off-farm income are more important for machineries than animal plows, supply-side constraints such as rental overhead costs and membership to a producer’s organization are very critical for transition to engine power through facilitating rental service which is the dominant source of access to heavy machineries. Based on these findings, we discussed the strategic interventions that are needed to enhance and sustain agricultural mechanization uptakes in Senegal.

Keywords: Senegal - Farm mechanization - West Africa - Exploitation

INTRODUCTION

Despite many years of efforts to transform the African agriculture through improved agricultural mechanization, the use of engine-powered farm equipment remains very low. Engine-powered machines currently cover only 10% of the total power for land preparation in Sub-Saharan Africa (Side, 2013). Historically, the use of machinery in agriculture in Africa in general had been increasing until the 1980’s structural reforms (Houmy, et al, 2013). Th initial trend was motivated by the emergence of colonization that brought improved equipment for large scale farming. After independence, many governments had interventions to motivate smallholder producers through subsidies and government owned enterprises for the production, importation and maintained of machineries. However, following the 1980’s structural reforms, the trend has been declining overtime. A similar trend has been witnessed in Senegal where the use of motorized farm equipment is below the sub-Saharan African average. Currently, a renewed strong policy interest is waging across African countries including Senegal to recap the declined use of tractor and other machines across the agricultural value chains (MaMo, 2018; Diao et al., 2016). This policy interest is motivated by the need to enhance agricultural transformation as part of the overall economic growth and transformation strategy; increased wage rate associated to the recent economic growth; and the innovation of farm mechanization that fits to the smallholders’ context and uses other sources of power such as wind and solar (Houmy, et al, 2013). Mechanization is supposed to transform agriculture through improved productivity, minimized production cost and reduced post-harvest loses (Pengali, 2007). As a result, many African countries revised their agricultural development strategies and mechanization has returned as an important development agenda. In Senegal, several programs such as the National Food Security Support Program (PNASA) in 2003; the Accelerated Growth Strategy (ACS) in 2005 and the National Rice Self-Sufficiency Program (PNAR) have been initiated to implement the national intensification and diversification of national agricultural production strategy. Since then several other programs including the 2014 Senegalese Agricultural Acceleration Program (PRACAS) were developed and agricultural mechanization has been one of the priority agenda to achieve stated goals and targets (MAER, 2014). However, the planning, strategizing and investment in agricultural mechanization is challenged by several conceptual and empirical puzzles. The most important question that attracts the attention of agricultural strategy planners and researchers alike is “How to encourage and expand the adoption of large-scale and emerging small-scale farm machineries by smallholder farmers?”. A recent research conducted in Ethiopia has found that mechanization is associated with significantly lower labor use, and higher yields—specifically the use of combine harvester—seemingly due to lower post-harvest losses (Berhane, 2017). The study further highlights that the expansion of mechanization is being hampered by farm structures, fragmented plots, crop diversity, physical constraints, such as presence of stones, steepness of fields, and soil types; and economic and financial constraints. In Senegal, a study has been conducted to assess the upper and midstream value chain of farm mechanization (CRES, 2018). This study has abled to estimate the number of firms involved in import, production, maintenance, and distribution of farm equipment across the country. It also evaluated the challenges and opportunities of the firms to supply the equipment and provide the services. However, a comprehensive study on uptakes and drivers of farm mechanization at farmers level is lacking. More specifically, the question “Which constraint is important to which type of farm

2 mechanization transition and access?” remains unanswered. The definition to farm mechanization depends on the type of energy sources—animal and engine; type of farm operations—plowing, seeding, harvesting, threshing; and the size of the equipment—small scale and heavy machineries. Since the transition from manual to animal to engine power is a structural change, the patterns and constraints along the adoption pathways could be different. In this paper, we focus on the downstream of the farm mechanization based on a data collected from the two farming systems. Namely, the irrigated rice production farming systems and the dry cereal production farming systems. Using this farm level data, we assessed two important concerns. First, we examined the patterns of farm power transition from manual to animal to machinery. In this regard, the study demonstrated the very low use of farm mechanization, but with significant variation across regions and farming systems. Second, we explored whether the demand and supply side constraints affect farm power transition from manual to animal to machinery differently. We tested if the supply side constraints such as rental services are more important for transition from animal power to heavy machineries than for transition from manual to animal drawn equipment for which access to cash is important to purchase the equipment privately. Similarly, we examined whether the demand side constraints such as farm size affects machineries and animal tractions differently or not. By doing so, the paper aims to contribute to the general understanding of how farm mechanization must be strategized for small scale farmers in Africa. It could trigger discussion on strategic choice of enhancing small-scale farm machineries through equipment ownership or enhancing large-scale machineries through equipment rental service. Before presenting the results of the study, we explore the policy reforms and directions that Senegal has gone through to enhance the uptakes of farm equipment and transform the sector. In this case, we reviewed the policy initiatives made since the colonial period to the current time. Following this section, we describe the analytical methods used to estimate the pattern and rates of uptake as well as demand and supply ide constraints. The fourth section describes the data collected and used for the study. The fifth section presents the results of the findings. Finally, we summarize the major findings and forward strategic interventions that are needed to enhance and sustain the adoption of agricultural mechanization in Senegal. Farm equipment introduction and supply in Senegal Introduction of farm equipment Since 1900, several agricultural equipment has been introduced in Senegalese agriculture. The first attempt is the introduction of improved animal drawn equipment during the colonial period. Between 1898 and 1901, several types of animal drawn plows were tested at Mbaba (near Tivaouane), Bambey, Kaolack, etc., by Perruchot and his team. From this experiment, equipment such as the Fondeur plow, Oliver plow, Algerian plow Amiot and Bariat, have had satisfactory results (see examples, Figure 1). The Bajac Lever Extractor and the universal E. Puzenat Exopper have also been tried because they were considered as more practical in the preparation of light soil for peanuts. These are cutters equipped with dethatching blades or vibrating blades. Next to animal plows, the Parisian house Pilter has designed and introduced a hand seeder for peanut sowing but also for other seeds such as millet. Though the seeder e has not been widely distributed, it has facilitated other farming practices such as weeding through row-planting. With regards to hoes, mechanical hoes like that of Verity's farmer, J. S. Duncan, were successfully tested and introduced as early as 1900. However, the attempt to the mechanical harvester like that of the potato to replace the hand, suggested by Perruchot, has not been

3 successful. The mechanization of threshing operation goes through trials of trainings from the United States (Perruchot, 1901). It was half a century later that this solution was adopted. For the mechanization to be complete, it was necessary to solve the problem of transport which was made by man's head or back of knickers or even with camels (by the Moorish caravaneers) as a painful operation. In this sense, several types of carts, used in French agricultural regions, are tested. The results were inconclusive, the wheels with narrow rims sank deep into the sandy tracks. Thus, Max Ringelmann, director of the Agricultural Machinery Testing Station in Paris, at the request of Perruchot, was studying a prototype of a suitable cart made by Pilter. The Senegalese cart has thus emerged. This cart has an all-metal wheelset whose bandages measure 30 centimeters in width, weighing 350 kilograms empty. The cart can be loaded up to 650 kilograms and dragged by a pair of oxen though the oxen car has not been successful in Senegal until the appearance of pneumatic wheels. The cart favored equine traction and donkey. The heavy motorization was started for soil works and harvesting by the Society for the Development of Rice Production in Senegal (SDRS) created in 1947. The SDRS gave way to a private organization ORTAL, which later left the place to the Senegalese sugar company (CSS) following a deficit management. Since then, several organizations have been established to facilitate the introduction and adoption of motorized machines in Senegal. The National Society for Development and Land Exploitation of the Delta and the Senegal River and the Senegal and Faleme River Valleys (SAED) was created in 1965 following the abolition of the Autonomous Organization of the Delta (1960 - 1965), with a renewed mission of promoting mechanized intensive rice cultivation. In parallel, the National Office for Cooperation and Assistance for Development (ONCAD) was created in 1966 to distribute spare parts and agricultural equipment. With regard to machinery supply, the Senegalese Industrial Company of Agricultural Equipment Trade (SISCOMA) was responsible to supply agricultural equipment to the rural economy with special emphasis on the setting up of national companies for the manufacture or assembly of agricultural equipment (CTA, 1997). From the research side, the Senegalese Institute for Agricultural Research (ISRA) was created in 1975 for introducing, adapting or developing technical innovations for rural producers. ISRA manages both motorized and animal drawn equipment. During this period, the super-Eco seeder has been massively adopted by farmers since its introduction (HAVARD, 1987). The western hoe was a resounding success but supplanted by hoe sine due to the subsidy of its price since 1966 (Bordet, 1988). With regards to post-harvest equipment, the BS 1000 is the first thresher introduced in rural areas in 1975, manufactured by SISCOMA. Then comes the MAROT thresher in 1978 and the BOURGOIN in 1981. For mills, the first models (hammer mills) with thermal or electric motors appeared in the "50s" and have spread well in urban and in the middle rural areas. This is explained, on the one hand, by the development of the artisanal production, thus showing the dynamism of the local craftsmen in this field (Havard, 1987). In 1970, the Chinese who began their test on tillers at Guédé, they introduced combine harvesters after five years. Current farm equipment supply The Senegalese farm equipment supply service has gone several ups and downs with the gradual withdrawn of the government serves following the 1980s structural adjustment program and the renewed interest to intensification and diversification of national agricultural production since early 2000s. Currently, the private sector plays significant role in importing, distributing and maintaining. Most companies involved in the supply of agricultural equipment in Senegal are from the formal sector, only 22% of suppliers from the informal sector in 2017. These companies are generally owned

4 by a single shareholder employing five (5) people on average (CRES, PAPA survey, 2017). Companies operating in the agricultural equipment supply sector are present in Senegal well before independence. In the course of time, some are created others go bankrupt. Sarr (2013) shows that 22% of companies settled in Senegal before independence in 1960, 22% between independence and the year 2000 and 44% after the year 2000. The companies are active in all the agro-ecological zones of the country, though they are predominantly active in the Senegal River Valley where mechanization is ahead to the other zones.The equipment being supplied in Senegal are of various origins. In fact, 78% of the companies import their equipment from abroad, 11% offer both locally manufactured equipment and imported equipment and the rest 11% sell their own locally produced equipment. Brazil and Turkey are the main countries of origin of agricultural equipment used in Senegal. Of the suppliers, 22% import equipment from these countries. The United States of America, Germany, Italy, Israel, China, Poland and Norway are also countries of origin of equipment for sale in Senegal. Among the suppliers surveyed, 11% source in the latter countries (Sarr, 2013). Importation of agricultural equipment has significantly increased in 2016 compared to 2003, with the exception of motor pumps and sprayers. The number of tractors per imported rose from 14 to 203, the combine harvester from 7 to 205, and the tools of weeding and sowing from 34 to 205. Most of the imports are made using the state credit set up for this purpose. Domestic production is more geared towards tillage and seedling equipment (plows, seed drills, sine and western hoes). Harvest and post- harvest equipment such as lifter, thresher (rice, millet, peanut), huller (rice, peanut) and mill are also manufactured but to a lesser extent. Carts for transport are also available to producers. In 2017, a significant rise in artisanal production is recorded for some equipment (lifter, seeder) compared to 2013 (CRES, PAPA survey, 2017) Hardware maintenance is mainly provided by craft companies. Animal traction equipment is the most well maintained. The maintenance of motorized equipment is marginal. The same trend can be observed roughly between 2013 and 2016 (CRES, PAPA survey, 2017). This same survey shows a low intensity of equipment supply using the number of units per 1000 ha. The intensity of supply has nevertheless changed between 2013 and 2016 on imported equipment but remains low. In 2013, the intensity of tractors was 0.07, this figure has increased to 0.61 in 2016. Local materials experienced a slight decline.

Figure 1: Examples of animal plows introduced in Senegal during the colonial period

A. Fondeur plow B. Oliver plow

Analytical methods

We define agricultural mechanization as a process of moving from the use of simple agricultural tools to the use of a more mechanical and power-intensive agricultural equipment. According to Pingali et al (1987), the level of farm mechanization is defined based on sources of power and intensity of operations. The sources of power in agricultural production, marketing and post-harvest process include human, animal and machine or engine. These powers are used for different farm operations. This study considers only equipment used for production operations, other equipment such as transport and storage equipment are not included-. Farm equipment used for production operations- are broadly classified as Power intensive equipment used for plowing, threshing and harvesting; and control-intensive equipment used for planting, weeding, and spraying. By merging the type of operation and the sources of power, three levels of farm mechanizations are defined such as Machinery, Animal plow and manual tools. For power intensive operations we have all the three groups of equipment but for control-intensive operation we have only the two groups such as animal tractions and manual tools. Operationally, we define a farmer as machinery user if he/she uses machinery for at least one production operations and as animal traction user if he/she doesn’t use machine for any operation but uses at least one animal drawn equipment for one operation. If the farmer didn’t use any machine or animal drawn equipment for any production operation, we consider the farmer as manual tool user. Following these definitions, the patterns of farm power transition is compared across farming systems, sources of power, type of farm operations, and administrative regions. We follow the induced technical theory to explore constraints that affect the transition of farm power. According to this theory, adoption of farm mechanization is endogenous to increasing production or reducing costs (Ruttan, 1997; Binswnger et al, 1978). Thus, in a perfect market condition, the use of improved farm equipment depends on market prices of inputs and outputs. However, in an imperfect condition these prices are endogenous to household and local level factors. We broadly classified these factors in to two; demand side and supply side factors. From the demand side, we tested the relative importance of family labor, farm size and household liquidity constraint on farm power transition from human to animal to machinery uses. The three energy sources—manual, animal and machinery—represent sequential transition of farm mechanization as they define the level of power being used for farm operations. This approach is supported by previous Authors (Pingali et al, 1987), who claim that the demand for farm mechanization is sequential-animal power (where feasible) is adopted before the transition to mechanized power. As a result, we applied an Ordered Probit model to estimate the transition of farm power-- higher in the case of machine, medium in the case of animal and lower in the case manual. The estimation is made only for power-intensive operations in irrigated rice farming systems. This is because the level of machinery use is relatively better in rice farming systems than in dry cereal farming system and better in power-intensive operations than control-intensive operations so that we can have comparable number of samples in each power source. Alternatively, we estimated simultaneous transition models in which farmers could jump from manuals to machineries as well. Thus, we use binary choice models to predict the probability of transiting to machinery from others and to animal power from manuals. A farmer is defined as machinery user, if he/she uses engine powered equipment at least for one operation. If the farmer didn’t t use any machinery but uses animal drawn equipment at least for one operation, then he/she is defined as animal traction user. If the farmer didn’t use any machinery or animal traction, he/she is defined as manual operator.

From the supply side, we explored factors that affect farmers access to improved farm equipment. These constraints include market access variables that proxies transaction costs both in equipment sales and rental markets. The importance of these constraints is analyzed using an empirical estimation that predicts the choice of framers to access farm equipment from different sources but mainly form ownership and rental services. The samples are, therefore, classified as farmers who don’t use any machine, farmers who used only owned machine, farmers who rent at least one machine. A multinomial logit model has been used to estimate the effect of membership, overhead cost and market distance on probability of renting and owning a machine. We included all the resource endowment and household head variables and regional dummies. As expected, the data reveals strong correlation between regional dummies, market distance and rental overhead costs. To avoid such correlation problem and check the robustness of the estimation, three alternative specifications were estimated.

Data and the Study Areas

We used data from a cross-sectional dataset collected in Senegal under the huge and ambitious project called ‘Senegal Agricultural Policy Project’ (Project d’Appui aux Politiques Agricoles, PAPA, in French) funded by USAID under ‘Feed the Future’. The PAPA project is implemented by the Senegalese Government and the local experts with a support of researchers from Michigan State University, the International Food Policy Research Institute, and AfricaLead. The project is still on progress, but a large amount of survey data has been already collected along the different value chains. Among other value chains, there are dry cereals (millet, sorghum, maize, fonio, rainfed rice), irrigated rice, horticulture (banana, onions, tomatoes, melons, …), inputs value chains (seeds, fertilizer, farm implements). Data used in this analysis are from the surveys on dry cereals (rainfed agriculture) and irrigated rice. All the forty-two agricultural departments of Senegal were covered by the dry cereals survey (the country has 45 departments in total). The 2013 census is used to select farmers to be interviewed. The survey sampling design involved two steps. First, between 10 to 36 Enumeration Areas (EAs) were randomly chosen proportionally to their size (total number of farmers) among all EAs in each department. The last step involved random selection of 5 households from each EA. A total of 4, 680 farm households were selected from the 42 departments. However, due to missing values and attrition, the study uses about 4480 of the households. For the rice survey, the same census is used to draw farm households from the two agroecological zones (Senegal River Valley, and Anambe Valley) which contributed to about 70-75% of the country total rice production. Most farmers in these zones are involved in irrigated rice. The Senegal River Valley (SRV) is the largest zone among the selected zones with about 75% of the production. Therefore, the sampling took that into account by selecting 75% of sample size from SRV, while the other 25% are from the Anambe Valley (AV). The survey sampling design involved two steps. First, Enumeration Areas (EAs) were randomly chosen proportionally to their size (total number of farmers) among all EAs in each agroecological zones (AEZ). The last step involved random selection of 5 households from each EA. A total of 780 farm households across both AEZ were selected. However, due to missing values and attrition, most analyses in this study use 730 of the samples. The module on farm equipment provides information on agricultural equipment used by farmers during the production season. It clearly identifies equipment, its mode of acquisition, the year of

7 acquisition, and the price. The mode of acquisition of agricultural equipment include heritage, purchase, rental, and gifts. Information on subsidy to agricultural equipment were also collected. A brief description of the study areas is presented in Table 1. The major agroecology zone of the dry cereal farming systems is the Senegalese Peanut Basin (49% of producers) followed by the Casamance zone (25%). For irrigated rice, it is mainly practiced in the Senegal River Valley (53% of producers), followed by Casamance (32%) and the Ferlo (14%). Table 1 gives also information on farmer's specialization measured here as the total area share allocated to each crop. Results showed that 39% of the total area under rainfed agriculture was allocated to peanut in dry cereal systems. The other two top crops included millet (and maize. On the other hand, irrigated rice producers allocated around 73% of their total land area under cultivation to rice, and the rest to o maize, and peanut. In terms of average resource endowment per farmer, farm size is s larger in the dry cereal systems than in irrigated rice. The small farm size in irrigated system may be due to the investment requirement specific to this system compared to rainfed system where little investment was required. Similarly, the agricultural family labor is larger in dry cereal producing areas than irrigated rice producing areas.

Table 1. Description of the farming systems Irrigated Rice Dry Cereal Farming Characteristics farming system system Agroecology %) Agro-sylvo-pastoralist of the central-east and south- east 0.6 10.5 Peanut Basin 0.0 49.3 Delta / Senegal River Valley 52.7 5.1 Littoral et Niayes 0.0 1.9 Sylvo-pastorales du Ferlo 14.3 8.6 Zone Forestiere du Sud (Casamance) 32.4 24.6 Major crops (area share) Peanut 8.2 38.9 Millet 1.2 32.0 Maize 11.3 11.0 Cowpea 0.0 6.9 Sorghum 0.8 5.0 Rice 72.7 3.9 Agricultural land in ha per farm Mean 2.7 5.8 Median 1.0 4.0 Maximum 170.0 250.0 Full time agricultural labor per farm Mean 2.2 2.8 Median 2.0 2.0 Maximum 15.0 26.0 Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

Results and discussion The patterns of farm power transition in Senegal Table 2 lists the type of farm equipment used by sample farmers in Senegal, the sources of power for each equipment, the operations they used for and the number of farmers using the equipment. Many of the equipment are powered by animals. Only few equipment such as tractor, thresher and combine harvesters are being powered by engine and hence considered as machine. The implements are used for transportation, storage, and production operations.

Table 2. Type of equipment used by farmers in Senegal Percentage of farmers Equipment Powered by Used for used Tractor Machine Land preparation 1.94 Animal Plow Animal Land Preparation 11.02 Seeder Animal Planting 50.06 Local Hoe Animal Weeding 46.05 Western hoe Animal Weeding 27.54 Sprayer Human Spraying pesticides 3.97 Duster Animal Spraying powder 0.02 Thresher Machine Threshing 0.21 Combine harvester Machine Harvesting and threshing 0.08 Sheller Animal Post-harvest 0.48 Donkey Cart Animal Transport 31.71 Ashole Cart Animal Transport 25.45 Cattle Cart Animal Transport 2.53 Warehouse Storage 2.42 Hangar Storage 0.46 Others 16.60 Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

Figure 2 shows the percentage of farmers who use different sources of power for power-intensive, control-intensive and all production operations. For energy-intensive operations (plowing, threshing, harvesting), most of the sample households use manual tools. This can be explained by the fact that plowing is still manual in some areas of Casamance, the peanut threshing remains manual as well as the harvesting of dry cereals. Farmers in Senegal use machinery exclusively for power-intensive operations. About 2.1 percent of the farmers use machinery for energy intensive operations. None of the sample households use equipment powered by machine for control-intensive operations. However, the use of animal traction is much more prevalent for control-intensive than power-intensive operations. Animal power is used by 2/3 of the sample households for control-intensive operations (planting, weeding, winnowing). 1/3 of households perform these activities with human power. In general, close to three-quarter of the farmers use animal power at least for one farm operation. The rest 24 percentage use neither machine nor animal tractions and hence entirely depend on human power. Only 2 percentage of the sample farmers use machinery at least for one farm operation. This figure is comparable to most African countries but lower than the average of the Sub-Saharan Africa.

A study by Side (2013) shows that in Sub-Saharan Africa, the main source of energy in agriculture is human (65%), followed by animals (25%), and machine (10%) for energy intensive operations. A recent study in Ethiopia has shown that the level of machinery is close to 3 percent (Berhane et al, 2017).

Figure 2. The transtion of farm power in Senegal 120.0

100.0 28.2 24.5 80.0

60.0 87.4

% of farmers 40.0 71.8 73.4

20.0 10.5 0.0 0.0 2.1 2.1 Control-intensive Power-intensive Both operations

Machinery Animal Manual

Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

Further disaggregation of the data by farming systems indicate that the use of farm machinery is higher in irrigated rice farming systems than in dry cereal farming systems (Figure 3). About 11% of the sample farmers use machinery in irrigated rice production areas. This figure is closer to the Sub- Saharan average (Side, 2013). The use of animal power is much more prevalent in dry cereals farming systems than irrigated rice farming systems. This can be explained by the fact that this area was the target of the program of introduction of animal traction of the State of Senegal of the year 1980.

Figure 3. The transition of farm powerin Senegal by farming systems 100%

90% 19.24 24.51 80%

70% 56.85

60%

50%

40% 80.11 73.36

30% 31.92 20%

10% 11.23 0% 0.65 2.13 Irrigated Rice Dry Cereals Total

Machinery Animal Manual

Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

The sources of farm power have also shown significant difference across administrative regions (Figure 4). The pattern across regions coincides with the type of farming systems in the region. In the Saint Louis, Matam and Kolda regions, which cover the irrigated rice production area, the use of motorized equipment is more prevalent than the regions in which rainfed cereal farming is predominant such as Thies Louga Kaffrine. In some regions such as Fatick, Kaolack, Kaffrine and Loga more than 90% of the sample farmers depend on animal tractions at least for farm operations. Agriculture in three regions such as Dakar, Ziguinchor and St. Louis relies heavily on hand tools. The operations of rice transplanting and crop maintenance in Ziguinchor as well as in Saint-Louis, are done without equipment. In Dakar, agriculture is practiced in the peri-urban zone where market gardening is developing and hence the activities in this region are being operated with manual equipment.

Figure 4. Farm power transition in Senegal by regions

Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

Factors affecting farm power transitions Table 3 presents the estimation results of the sequential transition of farm power demand from manual to animal to machinery. We estimated four different specifications to capture the nonlinear effect of farm and plot size. The first and the third columns show the linear estimation of farm and plot sizes respectively. The second and the fourth columns show the non-linear estimations of the same variables respectively. Non-linearity is captured by defining categorical variables using the continuous values of the respective variables. Our estimations reveal that the effect of farm size and access to cash on farm power transition (transition from manual to animal to machinery) is highly and consistently significant. However, the effect of family labor is not statistically significant. This doesn’t mean, however, that labor is not a constraint. It means that the labor market is quite functional so that the use of machinery is not dependent on family labor. The wage rate could be a driver of the movement from manual to animal to machinery. But we lack data to test such possibility. Consistent to previous studies (Takeshima, et al, 2013), households who generate higher cash income from off-farm activities have shown higher probability of transiting from manual to animal to machinery use. The effect of off-farm cash income on mechanization could be explained by the higher opportunity cost of family labor or by the access to cash. On one hand, households who generate higher cash may have higher opportunity cost of labor than households who generate less cash income and hence the former households tend to use labor-saving equipment more than the latter households. On the other hand, access to cash increases the probability of renting or purchasing a farm equipment operated by animals or machine as it relaxes the liquidity constraint. In any case, the result suggests the need for rural income diversification as a strategy to expand farm mechanization. Farm size both in its linear and non-linear form has positive and significant effect on probability of using animal tractions and machinery. However, the non-linear effect is quite substantial. The effect becomes bigger and significant when larger farms are compared to smaller farms. There is no statistically significant difference between farms below 2 hectare and farms between 2 and 5 hectares on probability of machinery use. On the contrary the difference in probability of machinery use between farms below 2 hectares and above 5 hectares is significant. This implies that the farm size

12 that attracts the use of existing machinery in Senegal shall be bigger than 5 hectares. In other ways, it implies the existing farm machineries are large-scale equipment that are less feasible to smallholders. Table 3. Factors affecting farm power sequential transition in Senegal Farm power transition; 0=manual, 1=Animal, 2=engine/machinery VARIABLES (1) (2) (3) (4) Sex of household head (0= -0.518** -0.503** -0.605*** -0.546** male, 1=Female) (0.219) (0.219) (0.227) (0.220) 0.015*** 0.014** 0.018*** 0.016*** Age household head (0.005) (0.005) (0.006) (0.005) Household head (1= literate, 0.141 0.108 0.190 0.167 0=illiterate) (0.135) (0.135) (0.134) (0.133) Regions dummy (Saint-Louis=0) 1.943*** 1.922*** 1.894*** 1.914*** Tambacounda (0.282) (0.281) (0.282) (0.280) 1.934*** 1.815*** 2.013*** 2.026*** Kolda (0.204) (0.213) (0.203) (0.201) 1.853*** 1.852*** 1.726*** 1.783*** Matam (0.229) (0.230) (0.230) (0.225) Number of fulltime family -0.028 -0.034 0.006 0.001 labor (0.033) (0.034) (0.032) (0.032) Off-farm cash income 0.507** 0.479** 0.560** 0.556** (millions CFA) (0.222) (0.219) (0.224) (0.222) Farm size in ha 0.049*** (0.013) Non-linear farm size (<1.99 ha) 2.00 to 4.99 ha 0.132 (0.181) 5.00 to 9.99 ha 0.720*** (0.202) >9.99.00 ha 0.913*** (0.258) Plot size in ha 0.023 (0.022) Non-linear plot size (<1.99 ha) 2 to 4.99 ha 0.497** (0.209) Above 4.99 0.232 (0.307) Observations 729 729 729 729 Source: Authors estimation based on the 2017 PAPA irrigated rice survey Note: Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1

In addition to the results presented in table 3, we estimated the simultaneous transition probability of using machinery and animal plow separately to test the relative importance of farm size to machinery and animal plow. The result confirms the fact that farm size is more important to machinery adoption than animal drawn equipment such as animal plow to test the relative importance of farm size and liquidity constraint for the adoption of machinery and animal traction, (Table 6). The effect of farm size on machinery use is highly significant. On the contrary, the effect of farm size on animal traction is weakly significant. The liquidity constraint is also more important to drive machinery adoption than

13 animal traction. This is because animal plow is obtained through ownership (purchase) as opposed to machinery which is mainly obtained through rental service. Unlike rental service, ownership is subsidized by the government and hence households’ cash endowment is more relevant for renting than purchasing. The next sections explain access and subsidy to farm equipment. Table 4. Factors affecting farm power simultaneous transition Machinery vs others Animal plow vs manual VARIABLES (1=Machine, 0=anima/human) (1=Animal, 0=Human) Sex of household head (0= -0.382 -0.495* male, 1=Female) (0.283) (0.270) 0.014** 0.014* Age household head (0.006) (0.007) Household head (1= literate, 0.178 0.124 0=illiterate) (0.166) (0.176) Number of fulltime family -0.029 -0.017 labor (0.041) (0.041) Off-farm cash income 0.675*** -0.662 (millions CFA) (0.240) (0.663) Farm size in ha 0.051*** 0.031* (0.014) (0.018) 1.413*** 2.125*** Tambacounda (0.378) (0.368) 1.470*** 2.065*** Kolda (0.260) (0.286) 1.745*** 1.449*** Matam (0.286) (0.331) Constant -3.374*** -3.296*** (0.473) (0.513) Observations 729 648 Source: Authors estimation based on the 2017 PAPA survey in irrigated rice production areas Note: Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1 Factors affecting equipment access This section assesses the constraints that affect the supply side (access) of farm mechanization uptake in Senegal. Before exploring the supply side constraints, we describe the sources of access to farm equipment. Many of our sample farmers access farm equipment through ownership in the form of inheritance, donation and purchase; and rental services. The relative importance of these modes of acquisition depends on the type of equipment (Table 5). Most of the small equipment operated by animals are obtained through ownership, mainly through purchasing. About 87 and 93 percent the farmers who use seeder and local hoe access the equipment through ownership respectively. Materials that work with animal energy are low-priced and hence mainly owned by farmers. These are more accessible to producers and there is a maintenance and repair device around these materials. Ownership to tractors and combine harvesters are the lowest compared to others. Of the total farmers who use tractor only 17% of them own at least one tractor. This equipment is relatively expensive and inaccessible to producers with low purchasing power. The operational size of the equipment and its price are more important than the source of power for owning an equipment. For example, small-scale machines such as threshers are completely owned by farmers and hence there is no rental service.

Recent innovations in small-scale two-wheel tractors could be an important option to expand mechanizations through ownership. However, we didn’t find any two-wheel tractor in our data. Table 5. Percentage of farmers who own and rent farm equipment

Percentage of Percentage of Type of equipment farmers used farmers own the Percentage depends (N=5210) equipment only on rent Seeder 50.29 86.49 13.51 Local Hoe 46.35 93.25 6.75 Donkey Cart 32.13 99.57 0.43 Western hoe 27.43 98.27 1.73 Ashole Cart 25.53 98.70 1.30 Others 13.22 99.69 0.31 Animal Plow 10.96 95.16 4.84 Sprayer 4.05 88.74 11.26 Warehouse 2.46 62.80 37.20 Cattle Cart 2.44 96.95 3.05 Tractor 1.94 17.13 82.87 Sheller 0.50 100.00 0.00 Hangar 0.46 80.56 19.44 Thresher 0.21 100.00 0.00 Combine harvester 0.08 76.32 23.68 Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

We also explored the dynamics of equipment ownership in the study areas using the year an equipment is purchased/donated/inherited. Using the cumulative percentage of farmers who own the equipment over time, we realized that the trends of ownership for many of the equipment are increasing non- linearly (Figure 5). Until 2000, the trends were flat implying that the number of equipment being purchased (as depicted by the slope of the graphs) every year were not significantly increasing. Since 2000, ownership of the equipment is growing modestly until 2005/06. Since then, the slope becomes very sharp indicating a very fast growth rate of mechanizations in Senegal. This period corresponds to the resumption of mechanization in Senegal. The ideology that modernization rhymes with heavy mechanization came back on the table, and the tractor was starting to be popularized. This period is also marked by a food crisis and the state wanted to boost production at all costs. The distribution of equipment at the subsidized price is resumed. The introduction of the latter was based on cooperation, particularly with the Indians and the Brazilians who allowed credit lines. Brazilian credit, for example, amounted to 45 billion FCFA.

Figure 5. Trends of farm eqipment ownership in Senegal 120

100

Cumulative percentage 20

0 1900 1958 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Animal plow (611) Local hoe(3375) Planter(2909) Tractor(21)

Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys

The use of rental service is a common practice for engine operated equipment (tractor and combine). 83% of the sample producers who use the tractor had access to this equipment through rental service. Other non-motorized equipment such as seeder are rented but only to a small extent. If we follow our previous classification of equipment, the percentage of farmers who rent machinery is by far higher than the percentage of farmers who rent animal tractions (Figure 6). More than three-quarter of the farmers who use machinery rent at least on equipment. Renting of animal tractions such as hoe, seeder and plow is not more than 10 percentage. The pattern is similar across the different farming systems. However, the use of rent for machinery is more important in the zone under irrigation system where some cultural operations (plowing of the clay lands and the harvesting and threshing of the rice) require motorization. Many of the machines are large scale equipment, which require bigger farm size to own them. For large-scale machineries, rental service remains an important option to expand mechanization. One of the advantages of rental service is that its independence from farm size. A simple comparison of average farm size for farmers who used rent and own farm machineries indicates that farmers who rent machineries have significantly smaller farm size than who own machines. An average farmer who rents a machine has 4.4 hectares of land compared to 17.5 hectares for an average farmer who owns a machine.

However, there exist an important policy concern related to the ways and strategies of expanding machinery rental services. Global experience indicates that the private operators and farmers cooperatives are the two most sustainable ways of providing machinery rental services. The major challenge for smallholders to access rental service from the private sector is the huge overhead cost involved in searching, establishing trust for collateral and transporting rental machines. To shed-light on the relevance of membership to an organization and overhead rental costs, we examined the association of these two variables with the probability of renting a machine.

Figure.6. Perecntage of farmers who rent machines and animal tractions

90 83 80 76

60 55

20 11 10 10 5

0 Irrigated Rice Dry Cereals All sample

Machinery Animal traction

Source: Authors estimation based on the 2017 PAPA irrigated rice and dry cereal surveys Note: Animal tractions include animal plow, seeder, and hoe. The results confirm the importance of membership for renting a machine (Table 6). Farmers who are member of an organization have higher and significant probability of renting a machine compared to those who don’t use machinery. Membership to an organization increases the probability of renting a machine by about 7.81 percentage points. However, consistent to our expectation, the effect of membership has little effect on owning a machine. Producers organizations help to facilitate access to rental service or provide the service directly to their members. Table 6. Factors Affecting probability of renting a machine VARIABLES Model 1 Model 2 Model 3 Owning Renting Owning Renting Owning Renting a a a a a a machine machin machin machin machin machin e e e e e Sex of household head (0= male, -14.38 -0.05 -12.45 -0.43 -12.64 -0.66 1=Female) (1160.00 (0.61) (516.10 (0.56) (511.10 (0.55) ) ) )

1 The marginal effect calculated using model 3.

Age household head 0.07** 0.00 0.05* -0.01 0.05** -0.00 (0.03) (0.01) (0.03) (0.01) (0.03) (0.01) Household head (1= literate, 0=illiterate) -0.36 0.34 -0.19 -0.02 -0.01 0.14 (0.75) (0.37) (0.69) (0.31) (0.65) (0.30) Number of fulltime family labor -0.45* -0.10 -0.39* 0.03 -0.26 0.12* (0.24) (0.10) (0.21) (0.08) (0.18) (0.07) Off-farm cash income (millions CFA) 0.03 1.61** -0.57 1.17** -1.95 1.11** * * (1.70) (0.68) (1.56) (0.43) (1.44) (0.39) Total agricultural land size in ha 0.30*** 0.11** 0.27** 0.11** 0.24** 0.10** * * * * (0.07) (0.04) (0.06) (0.04) (0.05) (0.04) Distance from markets in km -0.07 -0.01 -0.08** -0.03* (0.04) (0.03) (0.04) (0.02) Access to Credit (0=No, 1=yes) 0.76 -0.58 0.26 0.01 0.23 0.08 (0.95) (0.42) (0.87) (0.40) (0.83) (0.36) Membership to an organization (0=No, -0.16 1.33** -0.79 1.12** -0.53 1.02** 1=yes) * * * (0.82) (0.36) (0.73) (0.31) (0.68) (0.29) Overhead cost for renting equipment -9.82 0.70 -14.7 -3.36 -15.1 -3.93* (8.1) (2.7) (19.5) (2.1) (18.4) (2.1) Observations 600 600 600 600 600 600 Source: Authors estimation based on the 2017 PAPA surveys in irrigated rice production areas Note: Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1; The models are estimated with flowing multinomial groups 1= farmers don’t use any machine, 2= farmers who used only owned machine, 3= farmers who rent at least one machine

Similarly, households who face smaller rental overhead cost have higher probability of renting a machine than households who have larger rental overhead cost after removing the correlation with market distance (Table 8). Constant to our expectation, rental overhead cost has no effect on probability of owning a machine. Market distance has negative effect both on probability of purchasing (owning) and renting a machine. The effect seems higher on purchasing than renting a machine indicating the importance of rental service even in remote areas. These results imply the importance of market access not only for rental services but also for owning an equipment. The reduction of rental overhead cost seems an important strategy to expand machinery renting. Uberization of tractors has been found an important innovation to expand rental service thereby fast growing of farm mechanization in India (Ganguly et al, 2017). Though the effect of total land size is significant both on purchasing and renting a machine, the effect is much higher on purchasing (owning) than renting. This is consistent to our earlier claim that farm size is less important for renting a machine and makes it a feasible option to access large-scale machineries by smallholder farmers in Africa. Summary and policy implications This study was motivated by the empirical concern that aims at providing evidence for improving the uptakes and impacts of mechanization in Senegalese agriculture. Senegal has long history of supporting agricultural mechanization in the form of introducing new implements and providing

18 technical and commercial supports to smallholders. However, this study has found that the use of engine-powered farm machines is yet very low. Only 2.1 percent of the farmers use machineries powered by engines. However, the effort of introducing animal drawn equipment such as plows, seeders and hoes seems producing significant result. About half of the sample farmers use animal drawn planter. In general, three-quarter of the farmers use at least one agricultural production equipment drawn by animals. The transition from manual to animal to engine powered farm equipment significantly varies across farming systems, regions, farm size and access to off-farm incomes. Households in irrigated rice with larger size and better access to off-farm income have a better probability of transiting to machineries than others. The study generally demonstrated the variation of constraints in farm mechanization transitions defined by sources of power. While demand side constraints such as farm size and off-farm income are more important for transition to machineries than animal plows, supply-side constraints such as rental overhead costs and membership to a producer’s organization are very critical for transition to engine power through facilitating rental service which is the dominant source of access to heavy machineries Farmers access farm equipment through purchase and rental services. While ownership/purchase is the major source of access for animal drawn equipment, rental service is the dominant ways of accessing machineries such as tractors and combine harvesters. Ownership to farm equipment is non- linearly increasing over time. The recent growth since 2005/06 is much faster than before. Rental service seems the feasible option for expanding large-scale agricultural machines as it doesn’t require large farm size. However, the equipment rental service is being constrained by high transactional costs in searching, collateralization, negotiation and transportation of hired equipment. The two most important policy implications that can be derived from this study are expansion of machinery hire service and enhancing rural income diversification. Expansion of machine hire services can be done in three ways: through cooperatives, the private sector and government enterprise. The cooperative and the private sector seem more feasible and efficient options. In addition to empowering existing and establishing new cooperatives and private service providers, an adequate information and collateralization system that can reduce the transaction cost of hiring a machine are very critical. One of such option could be uberization of machineries using the opportunity of ever- expanding mobile phone services.

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