Antoine Berthou, John Jong-Hyun Chung, Kalina Manova, and Charlotte Sandoz
We examine the gains from globalization in the presence of firm heterogeneity and potential resource misallocation. We show theoretically that without distortions, bilateral and export liberalizations increase aggregate welfare and productivity, while import liberalization has ambiguous effects. Resource misallocation can either amplify, dampen or reverse the gains from trade. Using model-consistent measures and unique new data on 14 European countries and 20 industries in 1998-2011, we empirically establish that exogenous shocks to export demand and import competition both generate large aggregate productivity gains. Guided by theory, we provide evidence consistent with these effects operating through reallocations across firms in the presence of distortions: (i) Both export and import expansion increase average firm productivity, but the former also shifts activity towards more productive firms, while the latter acts in reverse; (ii) Both export and import exposure raise the productivity threshold for survival, but this cut-off is not a sufficient statistic for aggregate productivity; (iii) Efficient institutions, factor and product markets amplify the gains from import competition but dampen those from export access.
Emerging economies in the post-crisis period increasingly saw portfolio debt inflows from a type of large international investment fund: Multi-Sector Bond Funds (MSBFs). These investors have lacked adequate representation in the literature. This paper constructs a new detailed database from micro-level MSBF emerging market (EM) holdings from 2009:Q4–2018:Q2. Exploiting this data, the paper assesses the risks they pose to the financial stability of specific emerging bond markets. The data shows that MSBFs are highly concentrated–both in their positions and their decision-making. The empirical results further suggest that MSBFs exhibit opportunistic behavior (and more so than other investment funds). In periods of high risk aversion, large MSBF portfolio reallocations out of EMs can be associated with underperformance of the same markets, signaling the importance of monitoring their footprint and better understanding their asset allocation decisions.
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.
This 2019 Article IV Consultation highlights that the Lithuanian economy has continued to enjoy a strong macroeconomic and fiscal performance, but long-term challenges remain largely unaddressed. The continued strong economic performance suggests that a neutral fiscal stance would have been preferable in the year 2019. The report discusses that Lithuania needs sustained productivity gains to ensure higher living standards and convergence with Western Europe. Macroeconomic and financial stability is a prerequisite for sustained growth and has been achieved through prudent policies and labor market flexibility. Nevertheless, significant and well-identified structural challenges have yet to be addressed with ambitiously designed and decisively implemented productivity-enhancing reforms. The current expansionary cyclical environment and strong fiscal and external positions provide an ideal opportunity to address these challenges. Fintech provides big opportunities to improve financial services and produce high-skill jobs; however, it also brings challenges, particularly related to antimoney laundering. The authorities’ efforts to promote fintech are already delivering results.