We leverage insights from machine learning to optimize the tradeoff between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model. We apply the new alogrithm by nowcasting output growth with a panel of 102 countries and are able to significantly improve forecast accuracy relative to alternative pools. The algortihm improves nowcast performance for advanced economies, as well as emerging market and developing economies, suggesting that machine learning techniques using pooled data could be an important macro tool for many countries.
Mr. Balazs Csonto, Yuxuan Huang, and Mr. Camilo E Tovar Mora
This paper examines the extent to which digitalization—measured by a new proxy based on IP addresses allocations per country—has influenced inflation dynamics in a sample of 36 advanced and emerging economies over 2000-2017. Phillips curve estimates show that digitalization has a statistically significant negative effect on inflation in the short run. Its economic impact is not large but has increased since 2012 and mainly operates through a cost/competition channel. Principal components and cointegration analysis further suggest digitalization is a key driver of lower trend inflation.
Matthew E. Kahn, Mr. Kamiar Mohaddes, Ryan N. C. Ng, M. Hashem Pesaran, Mr. Mehdi Raissi, and Jui-Chung Yang
We study the long-term impact of climate change on economic activity across countries, using a stochastic growth model where labor productivity is affected by country-specific climate variables—defined as deviations of temperature and precipitation from their historical norms. Using a panel data set of 174 countries over the years 1960 to 2014, we find that per-capita real output growth is adversely affected by persistent changes in the temperature above or below its historical norm, but we do not obtain any statistically significant effects for changes in precipitation. Our counterfactual analysis suggests that a persistent increase in average global temperature by 0.04°C per year, in the absence of mitigation policies, reduces world real GDP per capita by more than 7 percent by 2100. On the other hand, abiding by the Paris Agreement, thereby limiting the temperature increase to 0.01°C per annum, reduces the loss substantially to about 1 percent. These effects vary significantly across countries depending on the pace of temperature increases and variability of climate conditions. We also provide supplementary evidence using data on a sample of 48 U.S. states between 1963 and 2016, and show that climate change has a long-lasting adverse impact on real output in various states and economic sectors, and on labor productivity and employment.