Productivity Growth: Patterns and Determinants “Across” the World

Abstract

This is the background paper for the productivity extension of the World Bank's Long-Term Growth Model (LTGM). Based on an extensive literature review, the paper identifies the main determinants of economic productivity as innovation, education, market efficiency, infrastructure, and institutions. Based on underlying proxies, the paper constructs indexes representing each of the main categories of productivity determinants and, combining them through principal component analysis, obtains an overall determinant index. This is done for every year in the three decades spanning 1985-2015 and for more than 100 countries. In parallel, the paper presents a measure of total factor productivity (TFP), largely obtained from the Penn World Table, and assesses the pattern of productivity growth across regions and income groups over the same sample. The paper then examines the relationship between the measures of TFP and its determinants. The variance of productivity growth is decomposed into the share explained by each of its main determinants, and the relationship between productivity growth and the overall determinant index is identified. The variance decomposition results show that the highest contributor among the determinants to the variance in TFP growth is market efficiency for Organisation for Economic Co-operation and Development countries and education for developing countries in the most recent decade. The regression results indicate that, controlling for country-and time-specific effects, TFP growth has a positive and significant relationship with the proposed TFP determinant index and a negative relationship with initial TFP. This relationship is then used to provide a set of simulations on the potential path of TFP growth if certain improvements on TFP determinants are achieved. The paper presents and discusses some of these simulations for groups of countries by geographic region and income level. In addition, as a country-specific illustration, the paper presents simulations on the potential path of TFP growth for Peru under various scenarios. An accompanying Excelbased toolkit, linked to the LTGM, provides a larger set of simulations and scenario analysis at the country level for the next few decades.

A dynamic analysis of the income–pollution relationship in a two-country setting

“…In our steady-state analysis we have found that the steady state value of capital positively depends on the TFP level. Therefore, in agreement with relevant studies showing a positive relationship between the development stage of the economy and the associated TFP (see, Kim and Loayza, 2019), it is logical to expect that developing economies will be facing a lower steady state value of capital than the developed economies. According to Proposition 1, in such economies pollution will monotonically increase with income.…”

Leveraging Total Factor Productivity in Developing Countries

“…(The World These results also confirm the conclusions of other empirical studies that the physical capital is considered the main source of growth for developing countries, with a minimal contribution of the TFP, and that the poor economic performance of these countries could be attributed to the low and insufficient productivity growth. Examples of these studies include Pipitone 2009, and Abu-Qarn, A., and S. Abu-Bader 2007 This result is consistent with the results of Kim and Loayza (2019) in which education had the highest contribution to the variance of TFP growth estimated at 49% followed by institutions and market efficiency for the case of developing countries during the period (2004-2014) ▪ The weak contribution of both the infrastructure and innovation in explaining the variance of the TFP in developing countries. In the case of infrastructure, this can be explained partly by the variation between the developing countries in the level of development of their infrastructure, but it is also highly related to what Hulten (1996) referred to as efficiency of infrastructure, that is the adequacy of managing and maintaining the existing infrastructure.…”

The Impacts of China–Africa Economic Relation on Factor Productivity of African Countries

“…The estimates of TFP derived from Table 2 are almost consistent with the growth rate of TFP of Sub-Saharan African countries estimated by Kim and Loayza (2019) for the period 2004-2014. The estimates of TFP derived show the same pattern of TFP growth.…”