Research
Working papers
An empirical approximation of the effects of trade sanctions with an application to Russia (2023)
with Jean Imbs. Accepted in Economic Policy.
We propose a data-based approximation of the effects of trade sanctions that can readily be computed on the basis of international input-output data. Approximated effects are very close to the exact responses obtained from a canonical multi-country multi-sector model, without having to make difficult calibration choices. We illustrate the approximation with trade sanctions against Russia and obtain estimates well within the existing range. Russia is much more affected by trade sanctions than the EU, even though the importance of EU markets for Russia has been falling, especially since 2014 with China picking up the slack. Within the EU the consequences are largest in ex-“satellite” countries of the Soviet Union: These countries do not typically have access to substitute markets and in fact have historically been highly dependent on Russia. This extreme and persistent dependence is at least partly explained by the existence of specific energy transporting infrastructure (pipelines) that appears to constrain tightly the production of electricity. Our proposed approximation is practical and can be implemented in a variety of contexts: We have developed a web-based dashboard, accessible at exposure.trade that can be used to approximate the costs of trade sanctions for any combinations of sanctioning and sanctioned countries or sectors.
Available at: http://dx.doi.org/10.2139/ssrn.4396080
Keywords: European Energy Imports, Russian Sanctions, Economic Consequences of Sanctions, Global Value Chain.
Measuring foreign exposure (2023)
with Jean Imbs. (Earlier versions of this paper include: “Measuring Openness” and “High Order Trade”.)
We introduce a model-based measure of exposure to foreign shocks that incorporates propagation via high-order trade. The model implies foreign exposure can be approximated by a simple decomposition of output according to the location of final demand. We perform the decomposition using sector data on international input-output trade and evaluate its empirical merits relative to common alternatives. We show the empirical patterns of sector output are mirrored by our proposed measure, but not by any alternative.
Available at: http://dx.doi.org/10.2139/ssrn.3595049.
Keywords: Foreign Shocks, Global Value Chains, Shock Propagation, Growth, Synchronization.
High moment constraints for predictive density combinations (2023)
with Peter Radchenko and Andrey Vasnev
Financial data typically exhibit asymmetry and heavy tails, which makes forecasting the entire density of the returns critically important. We investigate the effects of aggregating, or combining, predictive densities and find that even if the individual densities are skewed and/or heavy-tailed, the combined density often has significantly reduced skewness and kurtosis. This phenomenon has important implications for measuring downside risk in financial assets. When forecasting financial risk, recently proposed combination methods have focused on specific regions of the density support. We propose an alternative approach, which modifies the popular Log-Score weighting scheme by introducing data-driven constraints on the combination weights that control the skewness and kurtosis of the resulting predictive density. An empirical application using S&P 500 daily index returns demonstrates that the corresponding skewness and kurtosis successfully track the respective sample characteristics of the returns over time. Moreover, the proposed approach outperforms its natural competitors at forecasting the 1% Value-at-Risk for a broad range of estimation-window sizes.
Available at: http://dx.doi.org/10.2139/ssrn.3593124
Keywords: Forecasting, Forecast combinations, Predictive densities, Moment constraints, Financial data.
(Most) global and country shocks are in fact sector shocks (2023)
with Lukas Boeckelmann and Jean Imbs.
We construct a multi-country multi-sector model with a rich international input-output structure to separate out the global, country, and sector-level components of economic fluctuations. The model is designed to distinguish country or global shocks from sector-level shocks that propagate via the supply chain. We compare the model-implied decompositions to standard reduced form results and show that the magnitude of true global shocks is significantly smaller than usual. We then show that a closed economy version of the structural model implies a higher contribution of country-level shocks to volatility than is actually the case, because the closed-economy model apportions to domestic aggregate shocks any foreign shock with consequences on more than a few domestic sectors. This is even the case in large economies like the US that are usually assumed to be closed, which we illustrate using the example of the 2011 Japanese earthquake. It is the emergence of vertical trade, in capital and in intermediate goods that explains the bulk of this misallocation.
Coming soon
Keywords: Shock Propagation, Global Supply Chains, Sector Shocks, Aggregate Shocks, Regional Shocks, Global Shocks
Optimal forecast combination with mean absolute error loss (2022)
with Felix Chan
The optimal aggregation of forecasts produced either from models or expert judgments presents an interesting challenge for managerial decisions. Mean absolute error (MAE) and mean squared error (MSE) losses are commonly employed as criteria of optimality to obtain the weights that combine multiple forecasts. While much is known about MSE in the context of forecast combination, less attention has been given to MAE. This paper shows that the optimal solutions from minimizing either MAE or MSE loss functions, i.e., the optimal weights, are equivalent provided that the weights sum to one. The equivalence holds under mild assumptions and includes a wide class of symmetric and asymmetric error distributions. The theoretical results are supported by a numerical study that features skewed and fat- tailed distributions. The practical implications of combining forecasts with MAE and MSE optimal weights are investigated empirically with a small sample of data on expert forecasts on inflation, growth, and unemployment rates for the European Union. The results show that MAE weights are less sensitive to outliers, and MSE and MAE weights can be close to equivalent even when the sample is small.
Available as a CAMA Working Paper
Keywords: Forecasting, forecast combination, optimization, mean absolute error, optimal weights.
Fundamental Moments (2019)
with Jean Imbs
Global trade can give rise to global hubs, centers of activity whose influence on the global economy is large enough that local disturbances have consequences in the aggregate. This paper investigates the nature, existence, and rise of such hubs using Multi-Country Input-Output Data to evaluate the importance of vertical trade in creating global hubs that significantly affect volatility of economic activity at country level and globally. And If it does impact volatility, is it worth it? Our results suggest that the world has become more granular since 1995, with significant consequences on GDP volatility especially in developed countries. These consequences are well explained by international trade.
Available at: https://ssrn.com/abstract=3372861
Keywords: aggregate volatility, GDP synchronization, global hubs, granularity, input-output linkages
Work in progress
- “Pushing the Digital Frontier: Jobs, Competition, and Inclusion” with Pierre-Henri Bono and Jean Imbs.
- “Global Production Network with Heterogeneous Substitution Elasticities,” with Lukas Boeckelmann and Jean Imbs.
- “High order instruments” with Jean Imbs.
Publications
Book chapters
“Frequentist averaging,” In Fuleky P. (eds) Macroeconomic Forecasting in the Era of Big Data. Advanced Studies in Theoretical and Applied Econometrics, vol 52. Springer, 2020. (with F. Chan and S. Soltyk).
Articles
“The Promise of cooperation in Latin America: Building Deforestation-Free Supply Chains,” AJIL Unbound, 2022, Volume 116, 360-366. (with B. Garcia).
“Asymptotic and finite sample properties for multivariate rotated GARCH models,” Econometrics, vol. 9(2):21, 2021 (with M. Asai, C. Chiang, and M. McAleer).
“Some theoretical results on forecast combinations,” International Journal of Forecasting, vol. 34 (1), pp. 64-74, 2018 (with F. Chan).
“Forecast combination for discrete choice models: predicting FOMC monetary policy decisions,” Empirical Economics, vol. 52 (1), pp. 229-54, 2017 (with A. Vasnev).
“A note on estimation of optimal weights for density forecast combinations,” International Journal of Forecasting, vol. 32 (2), pp. 391-97, 2016 (with A. Vasnev).
“Does portfolio margining make borrowing more attractive?” International Review of Financial Analysis, vol. 43, pp. 128-34, 2016 (with D. Matsypura).
“Forecasting monetary policy decisions in Australia: A forecast combination approach,” Journal of Forecasting, vol. 32 (2), pp. 151-66, 2013 (with M. Skirtun and A. Vasnev).
“Testing for structural change in heterogeneous panels with an application to the Euro’s trade effect,” Journal of Time Series Econometrics, vol. 4 (2), 2012 (with F. Chan and T. Mancini).
“Do external pressures affect the Renminbi exchange rate?” Journal of International Money and Finance, vol. 31 (6), pp.1800-1818, 2012 (with L. Liu).
“What prompts the People’s Bank of China to change its monetary policy stance? Evidence from a Discrete Choice Model,” China & World Economy, vol. 16 (6), pp. 1-21, 2008 (with D. He).
“Measuring risk in environmental finance,” Journal of Economic Surveys, vol. 21, pp. 970-998, 2007 (with S. Hoti and M. McAleer)
Reports
“Australia China Entrepreneurs and Cross-border Business Ecosystem.” Joint research report from KPMG, AustCham Shanghai, and the University of Sydney Business School, 2023 (with W. Li, H. Hendrischke, H. Dent, S Qian, and S. Woods). Cited in the Australian Financial Review, ABC (Australia), SBS (Australia).
“Australia’s Asian Business Report: Australia’s Asian business networks and their contribution to economic growth.” Joint research report from the Commonwealth Bank of Australia and the University of Sydney Business School, 2022 (with W. Li, H. Hendrischke, and S. Chu).
“Twenty years of convergence,” ECB Forum on Central Banking 2019: 20 Years of European Economic and Monetary Union, European Central Bank, 2019. (with J. Imbs).