Efficiency of SMEs in Africa: Evidence from Congolese Data

The objective of this research is to analyze the explanatory factors of the technical efficiency of small- and medium-sized enterprises (SMEs) operating in the Republic of Congo. To do this, we generate efficiency scores for these SMEs, and then regress these scores on factors (internal and external) that are conducive to the performance of production units, taken from the economic literature and previous studies. To carry out our empirical analysis, we use a data envelopment analysis (DEA) model to calculate efficiency and the truncated bootstrap regression proposed by Simar and Wilson (Journal of Econometrics, 136(2007), 31-64, 2007a, b) that corrects the serial autocorrelation problem posed by the efficiency scores obtained by the DEA. The data we use, come from the National Institute of Statistics (INS), are from 2017 and concern 7029 SMEs. The choice of this dataset is justified by the fact that it is one of the few that obeys two principles, namely, the representativeness of SMEs over the extent of our field of study and the availability of variables that can facilitate the analysis of the efficiency of these same units. Our main results show that the grouping of firms and the size of the SME positively influence the efficiency of SMEs, while age also affects it. In addition, geographical location has a positive influence on the efficiency of SMEs in Brazzaville and a negative influence on those in Pointe-Noire. The other results reveal that only five (05) SMEs are efficient and that on average, 71.36% of them have an efficiency score below 0.1. These results imply that the public authorities should provide better support to Pointe-Noire entrepreneurs by granting loans, improving infrastructure, or implementing new urbanization projects.