Investigating inflation persistence across monetary regimes

By Luca Benati. 2008

488 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/530b86b6c39487b7e659f31784e50a93072a6bf6

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In Economics and Econometrics

Citations in the corpus

The persistence of inflation in the United States (2007, methodology): “Benati (2002) used a classical autoregressive model allowing for time-varying volatility.”
Credit and Banking in a DSGE Model of the Euro Area (2010, background): “: R t = R d t − κKb ( K t Bt − ν )( K t Bt )2 (6)”
Oil and the Great Moderation (2010, methodology): “Indeed, recent work by Benati and Surico (2007) casts doubt on the ability of VARs to distinguish between the good policyand good luckexplanations for the Great Moderation. Finally, there are a number of alternative (or complementary) explanations for the reduced macroeconomic volatility. Kilian”
Imperfect Information, Real‐Time Data and Monetary Policy in the Euro Area (2012, unknown): “To analyse the monetary policy implications of imperfect information and real-time data, we use a small-scale New Keynesian DSGE model similar to the one in Ehrmann and Smets (2003) and Benati (2008). Though much of the theoretical appeal”
Monetary/Fiscal Policy Mix and Agents’ Beliefs (2017, background): “This is because the change in the balance of power between the monetary and fiscal authorities plays a key role in explaining the break in the volatility and persistence of inflation that occurred in the early ’80s (Stock and Watson (2007), Benati (2008), Cogley et al. (2010)).”
How Structural Are Structural Parameters? [with Comments and Discussion] (2007, unknown): “Benati (2006), elaborating on an argument by Woodford”
Inference in structural vector autoregressions when the identifying assumptions are not fully believed: Re-evaluating the role of monetary policy in economic fluctuations (2018, unknown): “One option would be to take a completely specified dynamic stochastic general 16 Benati (2008) used a mean of 0.5 and standard deviation of 0.25.”