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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]

This paper addresses three questions: (1) what would have been the growth and income trajectory of Syria in the absence of war; (2) given the war, what explains the reduction in economic growth; and (3) what potential growth scenarios for Syria there could be in the aftermath of war. Conflict impact estimates point to negative GDP growth of −12% on average over 2011–2018, with output contracting to about one-third of the 2010 level. In post-conflict simulation scenarios, the growth drivers are affected by the assumed levels of reconstruction assistance, repatriation of refugees, and productivity improvements associated with three political settlement outcomes: a baseline (Sochi-plus) moderate scenario, an optimistic (robust political settlement) scenario, and a pessimistic (de facto balance of power) scenario. Respectively for these scenarios, GDP per capita average growth in the next two decades is projected to be 6.1%, 8.2%, or 3.1%, assuming a final and stable resolution of the conflict. [ABSTRACT FROM AUTHOR]