This investigation seeks to explore the importance of agglomeration mechanisms in the location decisions of new manufacturing firms in Ecuador, based on sector and canton level data for the 2000–2010 period. A model is proposed to explore the relative importance of agglomeration mechanisms in location decisions of new manufacturing companies, a regression is performed using instrumental variables, the econometric estimation is developed, and an identification strategy is proposed. The results of the empirical analysis show that the learning mechanism, and history, have a positive and significant impact on the creation of new firms. An increase of 1% in the transfer of knowledge in the industries and cantons of the country is correlated with the increase in the location of new firms in the order of 9.2%. In turn, history has a positive and significant effect on the creation of new firms, in industries and cantons characterized by a past industrial environment. Even when the learning mechanism and history are controlled by provinces, sectors, and cantons, they continue to be the most important determinants of the location of new firms. This evidence could be attributed to the public investment in Ecuadorian industry in recent years. In this sense, the contribution of this work is found in the empirical distinction of the mechanism that favors or inhibits the location decisions of new companies. The analysis was replicated for a three-digit sectorial disaggregation level, to verify whether the agglomeration mechanisms operate differently on a different industrial scale. The results suggested that there were no differences to be considered. When the analysis was done excluding the cantons of Quito, Guayaquil, and Cuenca, given their high representation in terms of the birth of industries and employment, the results were consistent with those previously mentioned. However, it is so only with respect to history, which in this case accounts for 38.8% of the birth of firms; whereas, matching accounts for an order of 38.9% in the period of analysis. This result is explained in the context of the country’s industrial policy.
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