Reasons Behind Low Productivity in Latin America

This article was written by Lian Allub and Federico Juncosa

Recent technological progress and adoption of new technologies around the world has led to a breakneck pace of the flow of data available. Companies like Facebook and Alphabet (Google), which did not exist 20 years ago, passed the $500-billion mark in market value with a business model based on capitalizing on the value of data.

In the public sector, the usual interactions of corporations and individuals with governments are often kept in digital records, although there is a clear lag in capitalizing on the potential of these data, in particular, in understanding and boosting productivity of our economies. In this post we will review some ongoing initiatives at CAF that overcome barriers to the use of administrative data and that rely on these data to study productivity.

A far-reaching initiative that was enhanced by the use of administrative data was the latest Economy and Development Report (EDR 2018) entitled Institutions for Productivity: Towards a Better Business Environment. An important part of this study was to establish accurately for all countries in the region the level of aggregation and the particular sector of activity where the lag in productivity compared to developed economies is most notable. To this end, it was necessary to narrow the analysis down to the units, which are ultimately responsible for productivity—the companies that make up the production system—with a view to preserving comparability between countries.

Bringing analytics down to company level requires using data with great availability and confidentiality limitations: They include information about sales, costs, profits and equity of companies, which compromises the confidentiality of their shareholders. To address these issues, the methodology proposed by Bartelsman, Haltiwanger and Scarpetta (2009) called distributed micro-data analysis was adopted. It consists of developing an indicator calculation protocol that is applied in a decentralized manner in the agency holding the data in each country. In other words, a routine is developed, together with a manual, to generate the desired indicators based on the database of each unit. This routine includes safeguards to protect data confidentiality, ensuring that no particular company may be identified from the indicators.

The effort to access these data proved useful: We learned that the region’s low productivity problem compared to developed economies is not due to their sectoral structure, i.e. overuse of resources in low-productive sectors, but that the problem is present in every sector of the economy. In analyzing increasing levels of disaggregation we found that, within each sub-sector, there is a poor allocation of productive factors across companies, where many resources go to low productivity units, particularly within the manufacturing sector. However, even if we devoted all resources to the most productive companies, there would still be a long way to close the productivity gap for developed economies. To achieve this goal, we must increase productivity of all companies.

Committed to the goal of promoting the use of administrative data for productivity analysis, CAF is in the early stages of a partnership with the Competitiveness Research Network (COMPNET). This Network was conceived on an initiative of the European Central Bank, and aims to produce a comprehensive set of productivity indicators based on company-level data that is comparable over time across all members, and is freely available for the academic and public policy community. At CAF, we seek to play an active role in this initiative, coordinating the incorporation of Latin American countries into the Network, as we understand that increased availability of productivity indicators in the region will encourage research and help design better public policies.

Another ongoing CAF initiative that was enhanced by the use of administrative data is the Access to Opportunities and Urban Productivity project. Through administrative social security records, supplemented by company records and georeferencing of productive establishments, we seek to understand the productive dynamics within city limits to study issues such as the distribution of job opportunities, agglomeration economies and urban areas with greater productive activity and greater job creation. The ultimate objective of this line of research is to devise evidence-based policy tools to leverage productivity and social inclusion in the region’s cities.

The urban studies agenda took the city of Buenos Aires as a prototype, which required the joint effort of CAF and Argentina’s Ministry of Production and Labor to enable the use of administrative records for this purpose. The task was performed along two main lines: georeferencing of location of registered production establishments and data aggregation into spatial units to avoid the data confidentiality issue, maintaining at the same time the granularity needed to study these phenomena. This initiative yielded its first results in the working document Spatial distribution of formal jobs in the Autonomous City of Buenos Aires. In addition, aggregated and anonymized data are potentially a high-value input for CAF’s urban interventions.

The cases discussed are promising examples of the use of this new data source—administrative data—for productivity analysis. These examples show that the barriers to the use of this data are substantial, and that they require investments to create the institutions and technological tools necessary to implement them without compromising their confidentiality. However, this is a high-return investment, as the increasing availability, low cost and increased coverage of this data makes them an unparalleled tool for research, and ultimately for the design of public policies that boost productivity and development of the region.