Research
Arroyo Marioli, Francisco and Bullano, Francisco and Kucinskas, Simas and Rondón-Moreno, Carlos, Tracking R of COVID-19: A New Real-Time Estimation Using the Kalman Filter (2021). Plos One. https://doi.org/10.1371/journal.pone.0244474.
We develop a new method for estimating the effective reproduction number of an infectious disease (R) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, R is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is very easy to apply in practice, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of R for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.
The semi-structural gap forecasting (MSEP) model is the new gap model used by the Central Bank of Chile to forecast key macroeconomics variables. This document provides the technical details of this model including equations, estimated parameters and transmission mechanisms. The model has been improved relative to its initial version along several dimensions: (i) The parameters have been estimated with Bayesian methods; (ii) it separates core inflation into tradable and non-tradable inflation, linking each component to fundamental drivers; (iii) it explicitly specifies the empirical relationships between terms of trade and real exchange rate. We found that for a typical monetary policy shocks there are similar effects in comparison with the former MEP model.
Arroyo Marioli F. : ”Trading Places: The Role of Agriculture Fundamentals, Information and Speculation". Job Market Paper.
Why did commodity prices fluctuate so much over the last 20 years? Are speculators to be blamed? Do prices reflect full information? These are the main questions I address in this paper, in the context of the corn market. I formulate and calibrate two quantitative models of corn prices formation. The first model is designed to explain prices in the the long run (annual frequency), while the second model applies to prices in the short run (quarterly frequency). For the long run analysis, I find that deviations of theoretical prices from observed ones are very small after 1996, and before 1996 they can be explained by government intervention. For the short run analysis, my model is designed to mimics the typical seasonality seen in agriculture markets, incorporate supply and demand shocks as well as news shocks, and allows for speculative storage decisions. I find that demand and supply fundamentals can account for around 52% of past price changes from 1975 to 2016. I also estimate the impact of information shocks to explain an additional 18% of quarterly deviations. Finally, find that at least 30% of short run price changes seem to have other explanation than supply or demand fundamentals or information, showing that when analyzing quarterly data, prices do not always track closely fundamentals.
Arroyo Marioli F. : ”Old crop versus new crop prices: Explaining the correlation”. Journal of Future Markets.
Although competitive storage theory has proven successful in explaining many patterns for commodity prices, some features are not understood. While standard models predict low correlation between future prices with delivery dates before and after the harvest, the data suggest otherwise. To correct this, I assume that harvests appear continuously rather than at a single moment. This addition to the standard model allows me to link preharvest and postharvest markets to the same source of supply, and hence obtain the empirically observed high correlation. Empirical evidence also suggests that my assumptions are realistic. Results are robust to different parameter specifications.
Arroyo Marioli F. and Letelier F. : "Commodities Fundamental Model". Central bank of Chile Working Paper Series. (No 918).
The price of copper is fundamental for the Chilean economy and, thus, for the Central Bank of Chile’s forecasts. The goal of this document is to provide a theoretical tool that allows not only to understand the determinants of the evolution of copper price but also to forecast it. Likewise, the model and methodology used is applicable to any storable commodity, assuming that supply, demand, price and inventories data are always available. We find that for the short run, temporary shocks play a minor role, whereas the USD Broad index and expectations contribute significantly. Also, in the long run, permanent demand and supply shocks seem to explain the major dynamics. We also present suggestive evidence that imprecise information can explain short-run volatility in expectations.
Arroyo Marioli, F., Becerra J.S, and Solorza M.: “The Credit Channel Through the Lens of a Semi-Structural Model”. Latin American Journal of Central Banking, Volume 3, Issue 2, 2022, 100056, ISSN 2666-1438.
In this paper, we estimate a semi-structural model with a banking sector for the Chilean economy. Our innovation consists of incorporating a system of equations that reflects the dynamics of credit, interest rate spreads, and loan-loss provisions to the Central Bank of Chile’s semi-structural model (modelo semi-estructural de proyección). We estimate the model and analyze the macroeconomic effects of incorporating this sector. We find that the banking sector plays a role in accelerating the business cycle through lower spreads and procyclical credit supply, in contrast to its counter-cyclical role in the COVID-19 crisis. Additionally, we find that credit growth can explain about 0.3 pp of total output gap variation on average. Moreover, we find that in episodes of severe stress, this gap can grow to 1.9 pp, as it did during the COVID-19 pandemic. We also identify a credit multiplier of up to 0.06 pp of GDP for each 1 pp of growth in commercial credit. Our results suggest not only that these nonconventional policies through the credit channel can be useful but also that our model can be used for evaluation purposes.
Policymakers and researchers describe the COVID-19 epidemics by waves without a common vocabulary on what constitutes an epidemic wave, either in terms of a working definition or operationalization, causing inconsistencies and confusions. A working definition and operationalization can be helpful to characterize and communicate about epidemics. We propose a working definition of epidemic waves in the ongoing COVID-19 pandemic and an operationalization based on the public data of the effective reproduction number R. Our operationalization characterizes the numbers and durations of waves (upward and downward) in 178 countries and reveals patterns that can enable healthcare organizations and policymakers to make better description and assessment of the COVID crisis to make more informed resource planning, mobilization, and allocation temporally in the continued COVID-19 pandemic.
Work In Progress
Arroyo Marioli, F., Khadan J., Ohnsorge F., and Yamazaki T.: “Industrial Commodity Prices: Literature Review and a Model Suite”. World Bank.
Arroyo Marioli F. and Vegh C.: “Fiscal Procyclicality in Commodity Exporting Countries: How Much Does It Pour and Why?”. World Bank.
Arroyo Marioli F., Fatas A., and Vasishtha G.: “Fiscal Policy Volatility and Growth”. World Bank.
Arroyo Marioli F., Carrera F., and Richardson G.: “Liquidity, Networks, and Unintended Consequences: The Founding of the Fed and the Great Depression”.
Policy Notes and Reports
“Commodity Markets Outlook”, Oct 2021, Apr 2022, Oct 2022. World Bank.
“Shocks de demanda, inflación y el rol de los inventarios”. Monetary Policy Report, Dec 2020. Central Bank of Chile.
“Perspectivas Para el COVID-19 en el Mundo”. Monetary Policy Report, June 2020. Central Bank of Chile.