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Yuriy Gorodnichenko
Researcher at University of California, Berkeley
Publications - 246
Citations - 16187
Yuriy Gorodnichenko is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Inflation & Monetary policy. The author has an hindex of 62, co-authored 230 publications receiving 12735 citations. Previous affiliations of Yuriy Gorodnichenko include University of California & National Bureau of Economic Research.
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Measuring the Output Responses to Fiscal Policy
TL;DR: This paper found large differences in the size of the spending multipliers in recessions and expansions with fiscal policy being considerably more effective in recession than in expansions, with military spending having the largest multiplier.
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Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts
TL;DR: In this article, a new approach is proposed to test the full-information rational expectations hypothesis which can identify whether rejections of the null arise from information rigidities, quantifying the economic significance of departures from the null and the underlying degree of information rigidity.
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Is The Phillips Curve Alive and Well After All? Inflation Expectations and the Missing Disinflation
TL;DR: The authors proposed a new explanation for the absence of disinflation during the Great Recession and found popular explanations to be insufficient, and proposed an explanation for this puzzle within the context of a standard Phillips curve.
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Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts
TL;DR: This article proposed a new approach to test the full-information rational expectations hypothesis which can identify whether rejections of the null arise from irrationality or limited information, and quantified the economic significance of departures from the null by quantifying the underlying degree of information rigidity.
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What Can Survey Forecasts Tell Us About Informational Rigidities
TL;DR: In this paper, the authors derive common and conflicting predictions from models in which agents face information constraints and then assess their validity using surveys of consumers, firms, central bankers, and professional forecasters.