Karim Barhoumi, Seung Mo Choi, Tara Iyer, Jiakun Li, Franck Ouattara, Mr. Andrew J Tiffin, and Jiaxiong Yao
The COVID-19 crisis has had a tremendous economic impact for all countries. Yet, assessing the full impact of the crisis has been frequently hampered by the delayed publication of official GDP statistics in several emerging market and developing economies. This paper outlines a machine-learning framework that helps track economic activity in real time for these economies. As illustrative examples, the framework is applied to selected sub-Saharan African economies. The framework is able to provide timely information on economic activity more swiftly than official statistics.
This paper studies the relationship between export structure and growth performance. We design an export recommendation system using a collaborative filtering algorithm based on countries' revealed comparative advantages. The system is used to produce export portfolio recommendations covering over 190 economies and over 30 years. We find that economies with their export structure more aligned with the recommended export structure achieve better growth performance, in terms of both higher GDP growth rate and lower growth volatility. These findings demonstrate that export structure matters for obtaining high and stable growth. Our recommendation system can serve as a practical tool for policymakers seeking actionable insights on their countries’ export potential and diversification strategies that may be complex and hard to quantify.
The consensus among central bankers is that higher inflation expectations can drive up inflation today, requiring tighter policy. We assess this by devising a novel method for identifying shocks to inflation expectations, estimating a semi-structural VAR where an expectation shock is identified as that which causes measured expectations to diverge from rationality. Using data for the United States, we find that a positive inflation expectations shock is deflationary and contractionary: inflation, output, and interest rates all fall. These results are inconsistent with the standard New Keynesian model, which predicts inflation and interest rate hikes. We discuss possible resolutions to this new puzzle.
Mr. Jean-Francois Dauphin, Mr. Kamil Dybczak, Morgan Maneely, Marzie Taheri Sanjani, Mrs. Nujin Suphaphiphat, Yifei Wang, and Hanqi Zhang
This paper describes recent work to strengthen nowcasting capacity at the IMF’s European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic factor models (DFMs) and several machine learning (ML) algorithms to nowcast GDP growth across a heterogenous group of European economies during normal and crisis times. Most of our methods significantly outperform the AR(1) benchmark model. Our DFMs tend to perform better during normal times while many of the ML methods we used performed strongly at identifying turning points. Our approach is easily applicable to other countries, subject to data availability.
José Garrido, Ms. Yan Liu, Joseph Sommer, and Juan Sebastián Viancha
This note explores the interactions between new technologies with key areas of commercial law and potential legal changes to respond to new developments in technology and businesses. Inspired by the Bali Fintech Agenda, this note argues that country authorities need to closely examine the adequacy of their legal frameworks to accommodate the use of new technologies and implement necessary legal reform so as to reap the benefits of fintech while mitigating risks. Given the cross-border nature of new technologies, international cooperation among all relevant stakeholders is critical. The note is structured as follows: Section II describes the relations between technology, business, and law, Section III discusses the nature and functions of commercial law; Section IV provides a brief overview of developments in fintech; Section V examines the interaction between technology and commercial law; and Section VI concludes with a preliminary agenda for legal reform to accommodate the use of new technologies.