Rare Macroeconomic Disasters

Barro, Robert J.; Ursúa, José F.

doi:10.3386/w17328

Cited by 94 publications

(82 citation statements)

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“…Output, consumption, and investment are deflated by the GDP deflator and in per capita terms. We start our data set with countries that have output and consumption data in Barro and Ursua (). We exclude large countries such as the United States, Japan, Germany, France, and the United Kingdom, which represented more than 2% of the world's GDP in the year 2000.…”

Section: Business Cycles In Small Open Economies: 1900–2013mentioning

confidence: 99%

Business Cycles in Small Open Economies: Evidence From Panel Data Between 1900 and 2013

Miyamoto

Nguyen

2017

Int Economic Review

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. ii Terms of use: Documents in EconStor may AbstractUsing a novel data set for 17 countries dating from 1900 to 2013, we characterize business cycles in both small developed and developing countries in a model with financial frictions and a common shock structure. We estimate the model jointly for these 17 countries using Bayesian methods. We find that financial frictions are an important feature for not only developing countries but also small developed countries. Furthermore, business cycles in both groups of countries are marked with trend productivity shocks. Non-Technical Summary Motivation and QuestionBusiness cycles in emerging economies are marked with highly volatile consumption and countercyclical trade balance. There are two views in the literature to explain these features: Aguiar and Gopinath (2007) argue that business cycles in emerging economies can be well explained by a frictionless real business cycle model with shocks to trend productivity, reflecting frequent regime switches in economic policies and market failures in emerging economies. In contrast, Garcia-Cicco et al. (2010) argue that a model with financial frictions can better capture the dynamics of emerging economies and in that case trend shocks are not necessary. Given these contrasting views, we characterize the important features of business cycles in developing countries and compare with those in advanced countries using long historical data for 17 small open economies. MethodologyWe build a small open economy real business cycle model with reduced-form financial frictions and trend productivity shocks augmented with common shocks. We estimate the model using Bayesian methods jointly for 17 countries between 1900 and 2013. Key ContributionsWe make three contributions to the literature. First, we collect a new data set of macroeconomic variables covering 17 small open economies, for both advanced and developing countries between 1900 and 2013. This is motivated by the fact that most of the previous studies rely on only a few countries' data. Furthermore, while it is important to use long data to identify trend shocks, except for Garcia-Cicco et al. (2010), previous papers use relatively short data due to the limitation of public data, especially for emerging economies. Second, we estimate a model that nests two important features in the literature-trend productivity shocks and financial frictions-to quantify the importance of these two features. Third, we augment the model wi...

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Section: Business Cycles In Small Open Economies: 1900–2013mentioning

confidence: 99%

Business Cycles in Small Open Economies: Evidence From Panel Data Between 1900 and 2013

Miyamoto

Nguyen

2017

Int Economic Review

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“…A consideration of the variety of real rates of return and an analysis of which rates are pertinent for environmental issues requires a stochastic model that gets into the ballpark of accounting for the equity premium. My approach relies on a rare‐disasters framework of the sort surveyed in Barro and Ursúa (). This literature (Rietz ; Barro ; Barro and Jin ; Barro and Ursúa ) argues that an unlevered equity premium around 5% per year is consistent with the long‐term international history of macroeconomic disasters with a reasonable coefficient of relative risk aversion in the neighbourhood of 3.0–3.5.…”

Section: Introductionmentioning

confidence: 99%

Environmental Protection, Rare Disasters and Discount Rates

Barro

2014

Economica

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The Stern Review's evaluation of environmental protection stresses low discount rates and uncertainty about environmental effects. An appropriate model for analysing this uncertainty and the associated discount rates requires sufficient risk aversion and fat-tailed uncertainty to account for the observed equity premium. Calibrations based on Epstein-Zin preferences and existing analyses of rare macroeconomic disasters suggest that optimal environmental investment can be a significant share of GDP even with reasonable rates of time preference. Optimal environmental investment increases with risk aversion and the probability and typical size of environmental disasters, but decreases with uncertainty about policy effectiveness.

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“…As part of the survey, we alerted experts to problems of overconfidence and include a warm-up section that was designed to increase awareness of their personal overconfidence. In addition, we asked experts about any ambiguities that they experienced in the survey and provided them with historical data on growth rates for the period 1900-2000 from Barro and Ursúa (2010) and Maddison (2003). 9 The survey was comprised of 4 sets of questions about growth rates: (1) central estimates (50 th percentile) for growth rates for 2010-2050 and 2010-2100, (2) estimates of uncertainty based on providing the 10 th , 25 th , 75 th , and 90 th percentiles of the growth rates, (3) the projected magnitude of effects of positive and negative shocks to the economy, and (4) near-term predictions (for the following year).…”

Section: B1 Survey Designmentioning

confidence: 99%

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

et al. 2016

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The MIT Joint Program on the Science and Policy of Global Change combines cutting-edge scientific research with independent policy analysis to provide a solid foundation for the public and private decisions needed to mitigate and adapt to unavoidable global environmental changes. Being data-driven, the Program uses extensive Earth system and economic data and models to produce quantitative analysis and predictions of the risks of climate change and the challenges of limiting human influence on the environment-essential knowledge for the international dialogue toward a global response to climate change.To this end, the Program brings together an interdisciplinary group from two established MIT research centers: the Center for Global Change Science (CGCS) and the Center for Energy and Environmental Policy Research (CEEPR). These two centers-along with collaborators from the Marine Biology Laboratory (MBL) at Woods Hole and short-and longterm visitors-provide the united vision needed to solve global challenges.At the heart of much of the Program's work lies MIT's Integrated Global System Model. Through this integrated model, the Program seeks to: discover new interactions among natural and human climate system components; objectively assess uncertainty in economic and climate projections; critically and quantitatively analyze environmental management and policy proposals; understand complex connections among the many forces that will shape our future; and improve methods to model, monitor and verify greenhouse gas emissions and climatic impacts.This reprint is one of a series intended to communicate research results and improve public understanding of global environment and energy challenges, thereby contributing to informed debate about climate change and the economic and social implications of policy alternatives.

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Rare Macroeconomic Disasters

Cited by 94 publications

References 40 publications

Business Cycles in Small Open Economies: Evidence From Panel Data Between 1900 and 2013

Business Cycles in Small Open Economies: Evidence From Panel Data Between 1900 and 2013

Environmental Protection, Rare Disasters and Discount Rates

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

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