Vivian Parlak, Mr. Gonzalo Salinas, and Mr. Mauricio Vargas
We measure the impact of frequent exogeneous shocks on small ECCU economies, including changes to global economic activity, tourism flows, oil prices, passport sales, FDI, and natural disasters. Using Canonical-Correlation Analysis (CCA) and dynamic panel regression analysis we find significant effects of most of these shocks on output, while only fluctuations in oil prices have significant effects on inflation. Results also suggest a significant impact of FDI and passport sales on the external balance, a link that CCA identifies as the strongest among all analyzed relations. The model also shows how Covid-19 related shocks lead to substantial contractions in output in all ECCU countries and deterioration of the current account balance in most of them, depending on countries’ tourism dependency.
Direct measurement of corruption is difficult due to its hidden nature, and measuring the perceptions of corruption via survey-based methods is often used as an alternative. This paper constructs a new non-survey based perceptions index for 111 countries by applying sentiment analysis to Financial Times articles over 2005–18. This sentiment-enhanced corruption perception index (SECPI) captures not only the frequncy of corruption related articles, but also the articles’ sentiment towards corruption. This index, while correlated with existing corruption perception indexes, offers some distinct advantages, including heightened sensitivity to current events (e.g., corruption investigations and elections), availability at a higher frequency, and lower costs to update. The SECPI is negatively correlated with business environment and institutional quality. Increases in the perceived incidence or scope of corruption influences economic agents’ behaviors, and thus economic dynamics. We found that when the SECPI is at least one standard deviation above the mean, the growth per capita falls by 0.65 percentage point on average, with more pronounced impacts for emerging market and low income countries.
Adalgiso Amendola, Mario di Serio, Matteo Fragetta, and Mr. Giovanni Melina
We build a factor-augmented interacted panel vector-autoregressive model of the Euro Area (EA) and estimate it with Bayesian methods to compute government spending multipliers. The multipliers are contingent on the overall monetary policy stance, captured by a shadow monetary policy rate. In the short run (one year), whether the fiscal shock occurs when the economy is at the effective lower bound (ELB) or in normal times does not seem to matter for the size of the multiplier. However, as the time horizon increases, multipliers diverge across the two regimes. In the medium run (three years), the average multiplier is about 1 in normal times and between 1.6 and 2.8 at the ELB, depending on the specification. The difference between the two multipliers is distributed largely away from zero. More generally, the multiplier is inversely correlated with the level of the shadow monetary policy rate. In addition, we verify that EA data lend support to the view that the multiplier is larger in periods of economic slack, and we show that the shadow rate and the state of the business cycle are autonomously correlated with its size. The econometric approach deals with several technical problems highlighted in the empirical macroeconomic literature, including the issues of fiscal foresight and limited information.
This paper studies changes in the transmission of common versus sectoral idiosyncratic shocks across different U.S. nonfarm business sectors during the Great Recession, and evaluates the cross-sectoral spillovers. Shocks are identified by dynamic factor methods. We find that the Great Recession is largely a time of heightened impact of common shocks— which accounts for 3/4 of aggregate volatility—and large spillovers of negative financerelated shocks. Moreover, in contrast with the earlier literature that failed to find a significant role of sectoral shocks (propagated through the input-output linkages across sectors) in driving variability in aggregate industry output, this study allows spillovers of shocks to operate through other mechanisms intertemporally. We find that prior to the recession the majority of aggregate fluctuations is explained by sector-specific shocks.
Mr. Eugenio M Cerutti, Mr. Stijn Claessens, and Mr. Andrew K. Rose
This study quantifies the importance of a Global Financial Cycle (GFCy) for capital flows. We use capital flow data dis-aggregated by direction and type between 1990Q1 and 2015Q5 for 85 countries, and conventional techniques, models and metrics. Since the GFCy is an unobservable concept, we use two methods to represent it: directly observable variables in center economies often linked to it, such as the VIX; and indirect manifestations, proxied by common dynamic factors extracted from actual capital flows. Our evidence seems mostly inconsistent with a significant and conspicuous GFCy; both methods combined rarely explain more than a quarter of the variation in capital flows. Succinctly, most variation in capital flows does not seem to be the result of common shocks nor stem from observables in a central country like the United States.
Ms. Yevgeniya Korniyenko, Magali Pinat, and Brian Dew
Anecdotal evidence suggests the existence of specific choke points in the global trade network revealed especially after natural disasters (e.g. hard drive components and Thailand flooding, Japanese auto components post-Fukushima, etc.). Using a highly disaggregated international trade database we assess the spillover effects of supply shocks from the import of specific goods. Our goal is to identify inherent vulnerabilities arising from the composition of a country’s import basket and to propose effective mitigation policies. First, using network analysis tools we develop a methodology for evaluating and ranking the supply fragility of individual traded goods. Next, we create a country-level measure to determine each country’s supply shock vulnerability based on the composition of their individual import baskets. This measure evaluates the potential negative supply shock spillovers from the import of each good.
Mr. Nicolas Arregui, Mr. Mohamed Norat, Antonio Pancorbo, Ms. Jodi G Scarlata, Eija Holttinen, Fabiana Melo, Jay Surti, Christopher Wilson, Rodolfo Wehrhahn, and Mamoru Yanase
This paper reviews tools used to identify and measure interconnectedness and raises the awareness of policymakers as to potential cross-sectional implications of prudential tools aimed at controlling interconnectedness. The paper examines two sets of tools—developed at the IMF and externally—to identify the implications of interconnectedness in systemic risk and how these tools have been applied in IMF surveillance. The paper then proposes a preliminary framework to analyze some key internationally-agreed-upon and national prudential tools and finds that while many prudential tools are effective in reducing interconnectedness, the interaction among these tools is far less clear cut.
We present a simple macroeconomic model with a continuum of primary commodities used in the production of the final good, such that the real prices of commodities have a factor structure. One factor captures the combined contribution of all aggregate shocks which have no direct effects on commodity markets other than through general equilibrium effects on output, while other factors represent direct commodity shocks. Thus, the factor structure provides a decomposition of underlying structural shocks. The theory also provides guidance on how empirical factors can be rotated to identify the structural factors. We apply factor analysis and the identification conditions implied by the model to a cross-section of real non-energy commodity prices. The theoretical restrictions implied by the model are consistent with the data and thus yield a structural interpretation of the common factors in commodity prices. The analysis suggests that commodity-related shocks have generally played a limited role in global business cycle fluctuations.