Poverty decompositions with counterfactual income and inequality dynamics

Traditional poverty accounting decomposes changes in a country's poverty headcount ratio into changes in income and inequality. We argue that this approach is unsatisfactory from the perspective of policy analysis because it compares a country in two points of time without taking the country's initial situation, and hence its potential for poverty reduction, into account. We thus suggest comparing traditional poverty decompositions with a counterfactual situation. This counterfactual indicates what a country starting from its initial situation could be expected to achieve in terms of income, inequality, and, hence, poverty developments. We construct those counterfactuals by modeling income and inequality trends characterized by convergence and a “Kuznets” relationship between inequality and development. Parameters in those relationships are estimated using PovcalNet survey data from 144 countries and we construct our counterfactual poverty predictions for 71 developing countries. While there is overall a tight relationship between actual developments and counterfactuals, we identify several cases, where both deviate from each other and discuss the policy implications. We also check for commonalities in differently performing countries and find that those who fell particularly short of expectations often underwent political transition and state fragility

Drivers of growth accelerations:What role for capital accumulation?

Economic growth is often episodic but the ultimate drivers of such growth accelerations are not understood very well. We therefore take a different perspective and investigate what happens to production factors and productivity before, during, and after 156 growth accelerations that we identify for 148 countries between 1950 and 2019. We are particularly interested in the role that physical capital accumulation can play in this context, given recent interest in investment surges and several investment-led growth models.Our results show that physical capital accumulation accounts on average for 9% of the increase in the growth rate during an acceleration, with heterogeneity across regions, time periods, and the economies’ capital-output ratio. While growth accelerations are mainly driven by improvements in total factor productivity, we find that physical capital accumulation is an important factor for the sustainability of accelerations. Those findings are robust to various techniques for identifying growth accelerations and growth decompositions. They suggest that large “investment-led” growth accelerations are unlikely but also confirm that growth episodes that are not accompanied by solid investment patterns are likely to run out of steam

Explaining the global landscape of foreign direct investment:Knowledge capital, gravity, and the role of culture and institutions

In this paper, we empirically re-assess the question which theoretical motives and empirical models are most suitable to explain global patterns of foreign direct investment (FDI). Compared with previous studies, we use bilateral FDI positions with a much more comprehensive coverage of emerging and developing economies, the IMF's Coordinated Direct Investment Statistics. We apply cross-validation to assess the performance of the gravity model and the knowledge capital (KK) model and add cultural, institutional and financial factors, as suggested by different theories on FDI determinants. We find the gravity model to achieve the best theory-consistent out-of-sample prediction, particularly when parameter heterogeneity of South and North FDI is allowed for. Controlling for surrounding market potential is important to recover the horizontal effect of the gravity model. Our finding that the gravity model for FDI performs well but requires some degree of parameter heterogeneity and the inclusion of surrounding market potential provides a clear baseline for future empirical studies of FDI determinants. Inclusion of institutional, cultural or financial factors seems less relevant and does not improve the model performance distinctly, although results for those variables are mostly in line with theoretical predictions

There is poverty convergence

Martin Ravallion ("Why Don't We See Poverty Convergence?" American Economic Review, 102(1): 504-23; 2012) presents evidence against the existence of convergence in global poverty rates despite convergence in household mean income levels and the close linkage between income growth and poverty reduction. We show that this finding is driven by a specification that demands more than simple convergence in poverty headcount rates and assumes a growth elasticity of poverty reduction, which is well-known to accelerate with low initial poverty levels. If we motivate the poverty convergence equation using an arguably superior growth semi-elasticity of poverty reduction, we find highly significant and robust evidence of convergence in absolute poverty headcount ratios and poverty gaps. Relatedly, we show that the results in Ravallion (2012) are driven by the special income growth and poverty dynamics in Central and Eastern European transition economies that started with low initial poverty rates and thus observed a high elasticity of poverty reduction. Once we control for their abnormal poverty dynamics, we again find robust evidence of global convergence in poverty, even in the original specification by Ravallion (2012).Series: Department of Economics Working Paper Serie

When Do We See Poverty Convergence?

We show why convergence in mean income levels and the negative relation between mean income growth and poverty changes need not lead to proportionate poverty convergence across countries. We propose an analytical framework that highlights that poverty convergence depends on the speed of income convergence relative to a complex interaction of initial inequality, mean income levels, and inequality dynamics. Our framework allows us to investigate poverty convergence, or the lack thereof, under different plausible dynamics of mean income and inequality

The Rise of Robots and the Fall of Routine Jobs

This paper examines the impact of industrial robots on jobs. We combine data on robot adoption and occupations by industry in thirty-seven countries for the period from 2005 to 2015. We exploit differences across industries in technical feasibility – defined as the industry's share of tasks replaceable by robots – to identify the impact of robot usage on employment. The data allow us to differentiate effects by the routine-intensity of employment. We find that a rise in robot adoption relates significantly to a fall in the employment share of routine manual task-intensive jobs. This relation is observed in high-income countries, but not in emerging market and transition economies

China Scholarship Council is also highly acknowledged. The usual disclaimer applies.

In 2013 all ECB publications feature a motif taken from the €5 banknote. NOTE: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. Acknowledgements This paper has enourmously beneted from an internship at the IMF’s Statistics Department in 2011. I am indebted to my colleague

Empirical Aspects of Foreign Direct Investment and Economic Development

Softcover, 17x24, 186 S.: 25,00 €Softcover, 17x24Increased capital flows in the form of foreign direct investment (FDI) and the growing relevance of multinational corporations are two characteristics of the most recent wave of globalization. This volume extensively discusses how these phenomena are interrelated, what determines FDI flows and which role macroeconomic information plays for the latter. It then empirically investigates what these foreign direct investments mean for economic development, especially for the export prices of developing countries and labor market outcomes