COMMERCIALIZATION PERFORMANCE 63


Table 5.3 Social activities and size of cooperative Log na


Characteristic Consumptionc


Literacyc HIV preventionc Public infrastructurec Log (initial number of members) Age Partner at origin Financial help at origin


Controls for market access Controls for population density


Number of observations R2


F-test on significance 171 0.19 0.0004*** (1) 0.908


(0.210)*** 0.759


(0.282)*** 0.407


Log Qb


(2) (3) (4) 0.560


(0.133)*** 0.273


(0.163)*


–0.316 0.055 (0.254) –0.100 (0.275)


(0.110)


(0.242)** 0.537


(0.307)*


–0.277 0.210 (0.233) 0.511


(0.085)*** 0.040


(0.017)** 0.204


(0.122)* –0.384


(0.172)** Yes Yes


Constant 5.821 2.453 (0.217)***


158 0.71 0.000*** 6.333 (0.477)*** (0.236)*** 171 0.07 0.0716


0.046


(0.174) 0.118


(0.183)


–0.257 0.211 (0.309)


(0.338)


(0.141) 0.048


(0.277) 0.535


(0.096)*** 0.054


(0.022)** 0.446


(0.185)** –0.226 (0.234) Yes Yes


2.759 (0.725)*** 158 0.46 0.0000***


Source: Authors’ calculations based on data from ECS (2006). Notes: Robust standard errors are computed with clustering at the woreda level. Standard errors are listed in parentheses. A woreda, or district, is one of the smallest adminis- trative units in Ethiopia. Numbers are significant at the * 10 percent, ** 5 percent, and *** 1 percent levels, respectively.


aDenotes the log value of the cooperative’s membership size. bDenotes the log value of the cooperative’s potential aggregate product. cF-test data given at end of table pertain to this characteristic.


aggregation is accounted for. In all estimations, partial F-tests indicate the joint significance of the variables to be used as instruments later.


Membership and Performance


Table 5.4 further tests the above theory by relating the marketing perfor- mance of a cooperative to its membership and aggregated product. Results from ordinary least squares estimates are shown in the table, with the basic model reported in column (1) and the more controlled one in column (2).5 The


5 The basic model is the simplest estimation containing the fewest number of variables and employing ordinary least squares.


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