The survey data accompanies the working paper, "Mapping the Landscape of Transactions the Governance of Business Relations in Latin America”. This paper provides a picture of the landscape of transactions and one of the central motivations for this analysis is to ascertain whether there are meaningful patterns that emerge from datasets on how firms make agreements with their suppliers and customers.
A new set of survey questions is used to map governance structures that firms employ to support the successful implementation of transactions. Without imposing any a priori model, latent class analysis (LCA) discovers meaningful patterns of governance structures that readily match constructs in the literature. All governance structures use bilateralism. Bilateralism and formal institutions are sometimes complemented but never substitutes. For each firm, LCA provides estimates of the posterior probability that the firm uses each of the discovered governance structures.
These estimates can be used by researchers to go further, testing their own hypotheses relevant to Williamson’s discriminating alignment agenda using additional data from the Enterprise Surveys or elsewhere. Variations in the effectiveness of different governance structures across countries and across different types of firms and transactions are explored. Regional variation within countries is greater than cross-country variation. Foreign-owned firms, exporters, larger firms, and better-managed ones are more likely to use governance structures that complement bilateralism with use of the legal system or with the help of paid third-parties.
The responses were used to a unique set of questions posed in 2017 and 2018 as part of the ES implemented in six Latin American countries: Argentina, Bolivia, Ecuador, Paraguay, Peru, and Uruguay. The surveys are based on interviews with business owners and top managers in a sample of officially registered firms with at least five employees in the manufacturing and services sectors. The surveys are designed to be nationally representative, using a stratified survey design.