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This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...
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The Hodrick-Prescott filter is a popular tool in macroeconomics for decomposing a time series into a smooth trend and a business cycle component. The last few years have witnessed global events, such as the Global Financial Crisis, the COVID-19 pandemic, and the war in Ukraine, that have had...
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uncertainty into Integrated Assessment Models (IAMs). Uncertainty is transformed into a risk-premium, damage-correction, region …. This risk premium quantifies what society would be willing to pay to insure against the uncertainty of the damages, and it … highly sensitive to the coefficient of relative risk aversion. Once the climate change damage function incorporates the risk …
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We propose a novel framework for the economic assessment of climate-change policy. Our main point of departure from existing work is the adoption of a "satisficing", as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different...
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Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...
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