El constructo Ansiedad

The full estimation of equations (5.11) and (5.12) for both sub-samples is presented in

Table 5- 3. Columns 1-6 present estimation results for treatment equations for both types of crops; the autarky regime is overlooked as it stands for the control group; the last 2 columns present results for the two outcome equations. The likelihood-ratio test for exogeneity of treatment, which is a test for the joint hypothesis that coefficients associated to the latent factors (unobserved heterogeneities) are jointly equal to zero, shows that the null hypothesis is rejected in both cases; therefore, unobserved heterogeneities are critical when explaining market choice and its linkage with a farm’s net revenue.

For the market choice decisions, results (columns 1-6) suggest that these decisions are quite distinct and that the factors driving the participation decision across groups are different. This suggests that analyzing participation as we have done may bring more insights than the common approach of market participation that separately analyzed input market participation and output market participation. In addition, results are quite different between staples producers and groundnut producers, thus revealing the critical role played by the crop selection. Ownership of transport means (cart) has a positive and significant effect on market participation regimes. Households that owned carts had fewer constraints to transport purchased inputs (products to sell) from (to) local markets to farms. In addition, in rural

116 Senegal, these households may rent their owned assets to other households, thus allowing them to generate more income. Alene et al. (2008) and Teklewold (2016) found similar results. Membership in farmer organizations increases the probability that staple food producers intervene in the inputs market and in the two markets. For groundnut producers, being a member of a farmer organization has a positive effect on the probability to sequentially participate in both input and output markets. In general, farmer organizations increase market access for their members by reducing search and information costs or by increasing their bargaining power (Holloway et al. 2000; Teklewold 2016). For example, Burke et al. (2015) showed that the presence of milk cooperative in the village is likely to increase milk market participation in Kenya; and Fan and Salas Garcia (2018) revealed that being a member of an association increases farmers’ market participation in Peru.

Other proxy variables for transaction costs are the distance from the household’s location to some infrastructures such as market, road, and regional city. Results show that distance to the nearest market has a strong negative effect on groundnut input market participation. A similar result is found for Ethiopia by Woldeyohanes et al. (2017). Regarding distance to the nearest paved road, results are a bit ambiguous. A positive correlation is found for staples input market participation, groundnut joint market participation, while a negative and significant effect is observed for staples output and joint market participation. Distance to the regional city is found to have a very limited impact on market participation regimes. These ambiguous results may be due to the fact that agroecological zone dummies may already account partly for regional accessibility effects.

Access to extension service is found to decrease the probability to be connected to output market participation for staples food. Opposite results were found by Alene et al. (2008). Education (literacy rate) improves the bargaining power of farmers, therefore it increases the probability of intervention in the input market, and both markets for staple food producers. Household heads' gender and age seem to not have significant impacts on market choice decisions for farmers in the sample. Access to credit helps to relieve financial constraints for cash crop producers who are connected to both markets; therefore, it positively affects market participation. In the milk sector in Kenya, Burke et al. (2015) found similar results. The impact of credit is very limited in the case of staples crops, the associated coefficient is positive and significant at a 10 percent level.

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Table 5- 3: Estimation results based on the mixed multinomial logit model

To buy inputs To sell output Joint participation Net crop revenue per hectare

(1) (2) (1) (2) (1) (2) (1) (2) Treatment: Input 0.348 -27.705*** (11.919) (4.674) Treatment: Output -0.284 38.140*** (7.179) (5.755) Treatment: Joint 69.959*** 13.934*** (14.376) (4.568) HH gender (1=Female) 0.037 -0.129 -0.324 0.458 0.459 0.473* 7.096 5.175 (0.178) (0.286) (0.281) (0.304) (0.307) (0.285) (7.239) (6.786) HH age (years) 0.013 -0.051 0.026 -0.041 0.031 -0.024 -0.930 1.282** (0.022) (0.038) (0.035) (0.036) (0.031) (0.034) (0.860) (0.637) HH age squared -0.000 0.001 -0.000 0.000 -0.000 0.000 0.012 -0.011* (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.008) (0.006) HH education 0.283*** -0.234 0.189 -0.170 0.260* 0.122 -1.796 3.948 (0.097) (0.167) (0.157) (0.156) (0.134) (0.146) (3.656) (3.821) Organization membership 0.787*** 0.515 -0.205 0.240 1.366*** 0.874** 38.783*** 0.659 (0.189) (0.388) (0.407) (0.377) (0.204) (0.341) (10.638) (5.179) Extension services -0.018 0.459 -0.743** -0.069 0.225 0.342 77.885*** 12.331* (0.165) (0.283) (0.349) (0.283) (0.210) (0.255) (11.013) (6.297) Access to credit 0.092 0.527 -0.234 0.876 0.620* 1.832*** -24.976*** -10.696** (0.300) (0.724) (0.536) (0.706) (0.341) (0.651) (7.653) (4.620)

Livestock income dummy 0.415*** 0.160 0.088 -0.043 0.636*** 0.342** 4.105 8.793**

(0.098) (0.170) (0.161) (0.160) (0.138) (0.149) (3.955) (4.396)

Off-farm income dummy -0.254** -0.128 -0.445** -0.410** 0.015 -0.026 -0.632 -5.419

(0.106) (0.183) (0.190) (0.174) (0.153) (0.159) (4.120) (3.469)

Remittances income dummy 0.086 -0.023 0.341 -0.302 -0.286 -0.535** -19.136*** 15.334

(0.155) (0.240) (0.235) (0.238) (0.225) (0.224) (5.194) (9.881) Wealth index (0/6) 0.129*** 0.113** 0.066 0.024 0.219*** 0.066 4.360*** 1.679* (0.029) (0.050) (0.048) (0.047) (0.040) (0.044) (0.988) (0.949) Transport equipment 0.355*** -0.321** 0.711*** 0.173 0.522*** 0.552*** (0.096) (0.160) (0.148) (0.153) (0.135) (0.143) Mechanization 0.092 -0.412 0.394 -0.587** -0.399 -0.278 24.611*** 16.039*** (0.176) (0.289) (0.287) (0.257) (0.277) (0.240) (6.555) (4.621)

Land holding (ha) 0.080*** 0.097*** 0.063*** 0.126*** 0.155*** 0.174*** -4.770*** -2.006***

(0.016) (0.033) (0.020) (0.032) (0.019) (0.033) (0.402) (0.364) distance to market, KM 0.001 -0.042*** 0.012 -0.007 -0.002 -0.009 (0.004) (0.009) (0.008) (0.008) (0.007) (0.008) distance to road, KM 0.017*** 0.019* -0.018** -0.005 -0.010** 0.019** (0.004) (0.010) (0.008) (0.010) (0.005) (0.009) Distance to city 0.003 0.002 -0.002 0.005* -0.000 0.001

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(0.002) (0.003) (0.003) (0.002) (0.002) (0.002)

Produced also staples -1.809*** -1.104*** -1.646*** -54.429*** (0.352) (0.359) (0.338) (13.670) Produced also groundnut 0.111 -0.384** -0.245 -63.177***

(0.120) (0.195) (0.166) (4.285)

Produced also other cash crops -0.029 0.095 0.590** 0.569* 0.310 0.484 -18.037*** -12.110* (0.197) (0.371) (0.262) (0.337) (0.245) (0.330) (4.797) (6.234) AEZ: Agro Sylvo Pastorales 0.249 0.453 2.084*** -0.168 1.523*** 0.057

(0.163) (0.350) (0.319) (0.340) (0.271) (0.346)

AEZ: Groundnut Basin -0.108 0.409 1.649*** 0.755*** 1.069*** 1.950***

(0.135) (0.296) (0.311) (0.280) (0.230) (0.289)

AEZ: Senegal River 0.054 0.514 2.835***

(0.344) (0.680) (0.355)

AEZ: Littoral and Niayes 3.097*** -37.634*** 5.001***

(1.146) (1.113) (1.164)

AEZ: Sylvo-pastoral of Ferlo -1.897*** 1.388*** 1.033***

(0.255) (0.409) (0.322) AEZ: Casamance -0.027 2.630*** 2.536*** (0.362) (0.315) (0.321) lnSigma 4.587*** 4.423*** (0.049) (0.156) Lambda (Input) -8.548 4.981*** (13.985) (0.694) Lambda (Output) 25.251*** -18.215*** (4.691) (5.105) Lambda (Joint) -20.396 7.086*** (12.686) (1.330) Constant -2.133*** 2.219* -4.430*** 0.623 -5.813*** -0.330 115.483*** 59.388*** (0.618) (1.156) (1.021) (1.079) (0.925) (1.030) (24.128) (17.889) Observations 3,880 2,917 3,880 2,917 3,880 2,917 3,880 2,917

LR test for treatment exogeneity (Lambdas=0) 13.43*** 15.73***

Log-Likelihood -27661 -20461

Number of simulations 5000 5000

Notes: ***P < 0.01, **P < 0.05, *P < 0.1. Robust standard errors in parentheses. AEZ refers to agroecological zones. Note: HH stands for household head.

Farm size is a critical determinant of market participation for both types of producers. This finding is common in the literature on market participation (Alene et al. 2008; Burke et al. 2015). Farmers with larger farms show a greater propensity to participate in markets. The

119 largest coefficients are associated with the joint market participation. This suggests that increased farm size has a great impact on joint market participation.

Households that received income from livestock activities seem to be more integrated into markets, especially the input market for staples producers, and both markets for groundnut and staples producers. Therefore, a complementarity may exist between livestock and crop production as livestock activities help farmers to produce organic fertilizer (manure), thus increasing crop productivity. This finding is in line with results by Woldeyohanes et al. (2017). However, being involved in off-farm activity is shown to reduce the propensity to participate in the input market for staples food and output market for both groundnut and staples. Participating in off-farm activities is likely to reduce the time allocated to farming and thus, may reduce the productivity and likelihood to sell output. Farmers that received remittances similarly tend to reduce their joint participation in the two markets. The overall household wealth index is positively correlated with market participation, especially input market participation for both products, and the joint market participation for staples producers. This confirms that financial constraints may seriously reduce market choice in rural Senegal. Finally, results show that staples producers that also produce groundnut appear to participate less in markets for staples. On the other hand, when groundnut producers also produce staples, they commercialize less on the groundnut output market. This suggests that market participation regimes depend on the crop under consideration and also on the mix of crops produced.

5.4.2. Effects of market participation regimes