The Priorities for Productivity and Income (PPI) project seeks to answer the following key questions:

1. What did successful countries invest in that allowed them to reach higher income per capita groups?

2. Which determinants of productivity are the most important in increasing the likelihood of jumping to a higher income per capita group?

3. How do these determinants change according to the per capita income of the country under analysis?

4. How do these priorities interact in maximizing the probability of reaching a higher income group?

49 countries−including 19 from Latin America and the Caribbean, and 30 from the OECD−were used in the analysis to answer these questions. Countries were first clustered into 4 different income per capita groups (or clusters) depending on how similar their income per capitas are. Performance of each country in each of eight sectors affecting productivity−Labor Markets, Education, Health, Infrastructure, Innovation, Integration and Trade, Telecommunications and Capital Markets−was measured using a set of 34 key indicators.

With this information at hand, an ordered Probit model was estimated to assess which of these sectors make a significant impact in increasing the probability of jumping to the next higher income per capita cluster. Note that priorities differ depending on the cluster a country belongs to, and the probability of jumping to the next cluster depends on a country’s starting point, and how much it can invest on these priorities.

While for low income countries priorities are more basic−i.e., education and health−priorities shift to labor markets and integration and trade for lower-middle income countries. In the case of middle-income countries−including the seven biggest Latin American Economies−priorities change once more to capital markets and infrastructure.

A full description and results of the methodology are available in IDBs Working Paper 680, “In Search of Larger Per Capita Incomes: How to Prioritize Across Productivity Determinants?”, authored by Alejandro Izquierdo, Jimena Llopis, Umberto Muratori and José Juan Ruiz.

In this website you will be able to use the following tools:

• Probability of Jumping to the Next Cluster: This tool lets you estimate the probability of jumping to the next income-per-capita cluster when priorities are increased to new desired levels, based on results of the PPI econometric model.
• Cluster Comparison: This tool lets you compare sectoral indicators against own-group averages and next-group averages
• Individual Indicator Comparison: This tool lets you compare individual indicators in each of the 8 sectors analyzed (capital markets, education, health, infrastructure, innovation, integration and trade, labor markets, telecommunications) across countries and time.
• Database: You can download the database with indicators used in the estimation of the model covering the period 2000-2012 (in their original version and their normalized version), as well as a richer set of more than 80 indicators across different sectors affecting productivity. Most of the historical data are available at an annual frequency for the period 2000-2012, covering 26 LAC and 32 OECD countries. Users can view country PPIs results or download data to track performance in every sector of concern.