Jumping to Higher Productivity and Income

shutterstock_87348338

Spanish

How should Latin American countries invest in capabilities to boost their per capita incomes?   Research at the IDB suggests that much of the gap in income per-capita levels between Latin American countries and the United States  is due not to the amount of capital accumulated. Rather it is a result of drops in the region’s productivity levels vis-à-vis the U.S. The trick is figuring out where investment is going to most increase productivity and help a country jump to a new level in per capita income. Should policy makers prioritize investment in education, health, or infrastructure? Or would it be better to pump money into one of those sectors along with capital markets and innovation?

The question is by no means simple. Increasing investment in one specific sector may have little impact if other particular sectors lag behind, as would be the case of complementarities across sectors. And priorities could change substantially depending on a country’s income level. Moreover, deficiencies or gaps in a particular sector may or may not be relevant to a country’s potential to grow. The principal challenge is identifying which of those gaps represents the most relevant binding constraint: i.e., which gaps are most important at a particular moment in a country’s development. Sometimes the largest gaps may not be binding, while other gaps, which look smaller, could indeed be the binding constraints.

Alejandro Izquierdo, Umberto Muratori, Jimena Llopis and José Juan Ruiz of the IDB address the problem in recently published research. In order to assess differences across different income levels, they divide countries into four clusters ranging from those in the lowest income bracket, like Honduras and Nicaragua, to those in the lower middle income one, like Ecuador and Bolivia, and those in a middle income one, like Argentina, Brazil, and Mexico. A fourth cluster is reserved for wealthy countries outside the region. The authors measure performance across productivity determinants by assigning a large set of indicators to eight sectors including capital markets, education, health, infrastructure, innovation, integration and trade, health and labor markets, all of them with established links to productivity. The impact of investments in different sectors is assessed by measuring their contribution to increasing the likelihood of propelling a country to a higher income per capita level.

The results show persuasively that the effectiveness of investment in given sectors is highly dependent on where a country currently stands. In lower income countries, basic priorities such as education and health matter the most. In lower-middle income countries, by contrast, the priorities shift to labor markets and integration, and, in middle income countries, strengthening access to credit and infrastructure is the most critical for prompting the jump to a higher per capita income level.

Moreover, it doesn’t make sense to invest in individual sectors in isolation. Take, for example the case of Peru, a country that after making substantial efforts has recently entered the ranks of middle income countries. Being a newcomer to this group, Peru would need to make vast improvements to jump to the developed country group. How Peru manages investment in its priorities−i.e., infrastructure, capital markets and health−could have important effects on its probability of jumping to the developed country group: if it increased investment in each of those sectors by 1/2 standard deviation in separate efforts, adding up their overall effect would lead to only a 0.6% probability of entering the highest bracket. But increasing efforts in all three sectors simultaneously would give the country a bigger bang for its buck, raising the probability to 9%.

For many years now, critics have attacked the policy prescriptions offered in the 1990s by Washington-based financial institutions in what was known as the Washington Consensus. These were recipes for improving economic growth, which included investing in a vast range of sectors, including primary health care, primary education, infrastructure and trade liberalization. They yielded meager results. The problem was that many countries made investments across the board without properly identifying the largest constraints to growth or their interactions. Today we have different tools, ranging from growth diagnostics−successfully developed by Hausmann, Rodrick and Velasco in the mid-2000s−to the new tool presented here. They may allow us to prioritize, according to a country’s income level and according to the sectors offering the greatest returns. And they may make a significant difference in increasing productivity and raising per capita income.

Print Friendly, PDF & Email

The Author

Alejandro Izquierdo

Alejandro Izquierdo

Alejandro Izquierdo is currently a Principal Economist at the Research Department of the Inter-American Development Bank. Previously he worked at the World Bank in the Department of Economic Policy, and taught courses on macroeconomics and international finance at several Latin American universities. He holds a Ph.D. in Economics from the University of Maryland, an M.S. from Instituto Torcuato Di Tella, Argentina, and a B.A. in Economics from Universidad de Buenos Aires, Argentina. Alejandro has several publications in professional journals and edited volumes. His current research interests include issues in international finance such as the role of external factors on growth, the relevance of balance-sheet effects and financial integration in determining the likelihood of experiencing Sudden Stops in capital flows, as well as how countries recover from output collapses following Sudden Stops. He has also worked on the impact of Sudden Stops in the variance of relative prices, fiscal sustainability under Sudden Stops, and amplification effects of collateral constraints on the real exchange rate and output. Additionally, he has conducted research on the impact of macroeconomic external shocks and public expenditure allocation on poverty reduction for developing countries using computable general equilibrium models.

Leave a Reply

Your email address will not be published. Required fields are marked *

Ideas matter © 2016