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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. [ABSTRACT FROM AUTHOR]

Summary: Despite the tremendous human suffering caused by natural disasters, their effects on economic growth remain unclear, with some studies reporting negative, and others indicating no or even positive effects. To reconcile these seemingly contradictory findings reported in the literature, this study explores the effects of natural disasters on growth separately by disaster and economic sector. Applying a dynamic generalized method of moments panel estimator to a 1961–2005 cross-country panel dataset, three major insights emerge. First, disasters do affect economic growth but not always negatively, with effects that differ across types of disasters and economic sectors. Second, although moderate disasters (such as moderate floods) can have a positive growth effect in some sectors, severe disasters do not. Third, growth in developing countries is more sensitive to natural disasters than in developed ones, with more sectors affected and the effects larger and economically meaningful. [Copyright &y& Elsevier]