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  • Fully revised: Indeterminacy and Imperfect Information with Thomas A. Lubik (FRB Richmond), Christian Matthes (FRB Richmond):We study equilibrium determination in an environment where two types of agents have different information sets: Fully informed agents observe ...
    Posted Aug 20, 2020, 7:22 AM by Elmar Mertens
  • Accepted at QE: Sticky-Information Forecast paper with Jim Nason Using state-of-the-art particle filtering and smoothing, we show that inflation forecasts from the US SPF became “sticky” (more inattentive) only with the decline in inflation persistence that ...
    Posted May 21, 2020, 3:07 AM by Elmar Mertens
  • Replication codes for Johannsen and Mertens Real-Rate Trend Estimate Replication files for my paper with Ben Johannsen on estimating the longer-run level of the real rate from a shadow-rate model are now available on GitHub. The paper ...
    Posted Nov 10, 2019, 5:21 AM by Elmar Mertens
  • REVISED: Time-varying Forecast Stickiness w/Jim Nason Finally, together with Jim Nason, we just finished a thorough revision of our paper on time-varying stickiness --- i.e. a time/varying frequency of updating information -- in professional forecasts ...
    Posted Jun 4, 2019, 11:00 AM by Elmar Mertens
  • Accepted in REStat: Time-varying fan charts around survey forecasts Forthcoming in the Review of Economics and Statistics , with Todd Clark (FRB Cleveland) and Michael McCracken (FRB St. Louis):We estimate uncertainty measures for point forecasts obtained from survey data ...
    Posted Feb 27, 2019, 5:10 AM by Elmar Mertens
Showing posts 1 - 5 of 25. View more »

Fully revised: Indeterminacy and Imperfect Information

posted Aug 19, 2020, 8:25 AM by Elmar Mertens   [ updated Aug 20, 2020, 7:22 AM ]

with Thomas A. Lubik (FRB Richmond), Christian Matthes (FRB Richmond):

We study equilibrium determination in an environment where two types of agents have different information sets: Fully informed agents observe histories of all exogenous and endogenous variables. Less informed agents observe only a strict subset of the full information set and need to solve a dynamic signal extraction problem to gather information about the variables they do not directly observe. Both types of agents  know the structure of the model and form expectations rationally. In this environment, we identify a new channel that generates equilibrium indeterminacy: Optimal information processing of the less informed agent introduces stable dynamics into the equation system that lead to self-fulling expectations. For parameter values that imply a unique equilibrium under full information, the limited information rational expectations equilibrium is indeterminate. We illustrate our framework with a monetary policy problem where an imperfectly informed central bank follows an interest rate rule.  





Accepted at QE: Sticky-Information Forecast paper with Jim Nason

posted May 21, 2020, 3:07 AM by Elmar Mertens

Using state-of-the-art particle filtering and smoothing, we show that inflation forecasts from the US SPF became “sticky” (more inattentive) only with the decline in inflation persistence that occurred after the Volcker disinflation. SPF predictions were much more attentive during the Great Inflation than now.

The Figure below illustrates the importance of time-varying stickiness by comparing compares the MSE of actual SPF forecasts against the MSE of a hypothetical SPF that assumes they had been equally sticky during the Great Inflation as they are now. The MSE losses of those counterfactual forecasts would have been much higher. In contrast, while the stickiness of actual rose, their losses did not deteriorate much, as persistence in inflation declined (and the importance of noise shocks for inflation increased) at the same time. 



More on the paper, including a link to the replication files can be found on mPublications page.

Replication codes for Johannsen and Mertens Real-Rate Trend Estimate

posted Nov 10, 2019, 5:21 AM by Elmar Mertens   [ updated Nov 10, 2019, 5:21 AM ]

Replication files for my paper with Ben Johannsen on estimating the longer-run level of the real rate from a shadow-rate model are now available on GitHub

The paper has also been accepted for publication by the Journal of Money, Credit, and Banking. For the working paper and more, please see here

Compared to other estimates known from the literature, our estimate attributes more of the recent declines in real rates to a cyclical decline, thus seeing a smaller decline in the trend rate. A key feature for this result is to embed stochastic volatility into the model specification.




REVISED: Time-varying Forecast Stickiness w/Jim Nason

posted May 26, 2019, 7:07 AM by Elmar Mertens   [ updated Jun 4, 2019, 11:00 AM ]

Finally, together with Jim Nason, we just finished a thorough revision of our paper on time-varying stickiness --- i.e. a time/varying frequency of updating information -- in professional forecasts. The paper confirms earlier findings (e.g. Coibion and Gorodnichenko, 2015 AER) that SPF predictions are "sticky" in that their forecast errors are predictable, but we also find evidence that stickiness was actually quite low during the Great Inflation of the 1970s and the ensuing Volcker disinflation. Stickiness rose only once inflation became much less persistent, so that updating to more recent information adds much less predictive content.

The paper is here. See below for an abstract.

Here is a picture of the estimated stickiness parameter, as well as confidence bands around changes in the stickiness parameter.



Finally, here we show MSE loss of actual SPF forecasts compared against a counterfactual, where their stickiness is assumed to have been about as high as during the second half of our sample.



ABSTRACT:

Our paper studies the joint dynamics of U.S. inflation and a term structure of average inflation predictions taken from the Survey of Professional Forecasters (SPF).  We combine an unobserved components (UC) model of inflation and a sticky information forecast mechanism to study these dynamics.  The UC model decomposes inflation into a trend and a gap component and measurement error. We innovate by endowing inflation gap persistence and the frequency of sticky information inflation forecast updating with drift. Stochastic volatility is imposed on the innovations to trend and gap inflation. The result is a non-linear state space model.  The model is estimated on a sample from 1968:Q4 to 2018:Q3 using sequential Monte Carlo methods that include a particle learning filter and a Rao-Blackwellized particle smoother. Our estimates show that (i) longer horizon average SPF inflation predictions inform estimates of trend inflation; (ii) inflation gap  persistence is procyclical before the Volcker disinflation and acyclical afterwards; (iii) by 1990 sticky information inflation forecast updating is less frequent than it was earlier in the sample; and (iv) the drop in the frequency of the sticky information forecast updating occurs at the same time persistent shocks become less important for explaining fluctuations in inflation. All told, the data calls for drift in inflation gap persistence and in the frequency of updating sticky information forecasts. 


Accepted in REStat: Time-varying fan charts around survey forecasts

posted Feb 27, 2019, 5:10 AM by Elmar Mertens

Forthcoming in the Review of Economics and Statistics , with Todd Clark (FRB Cleveland) and Michael McCracken (FRB St. Louis):

We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to simple variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts.

This is joint work with Todd Clark (FRB Cleveland) and Michael McCracken (FRB St. Louis)


Here is a link to our earlier draft (Sep 2018): pdf 
And slides for a talk: pdf






Accepted in JMCB: Shadow rates and the long-run level of the real rate

posted May 10, 2018, 12:02 AM by Elmar Mertens   [ updated Nov 10, 2019, 3:14 AM ]

Together with my former Board colleague Ben Johannsen, we revised our work on estimating the long-run level of the real rate from a time-series model with shadow rates. In the revised version we also estimate the effects of monetary policy shocks identified from shadow-rate surprises

 

NEWLY REVISED working paper: pdf; accepted for publication by the JMCB.

Slides for a talk are here: pdf

Here are estimates of the trend level (and uncertainty around the trend estimates) as well as a model-implied measure of the current real rate:



Here we illustrate the construction of non-linear impulse-responses from the actual rate (responses of macro variables can be found in the paper):
 


Part of an earlier version of this work was also featured in the Board’s Monetary Policy Report to the Congress released on Feb 10, 2016, see pages 32-33 of the report and a FEDS note.

   



Kilian and Luetkepohl: Nice Section on Kurmann and Mertens (2014)

posted Mar 19, 2018, 11:21 PM by Elmar Mertens   [ updated Mar 19, 2018, 11:24 PM ]

Kilian and Luetkepohl's SVAR monograph is out; a great book! 

A nice bit is also their description of my paper with Andre Kurmann (2014, AER) that showed how the original news shock identification of Beaudry and Portier (2006, AER; "BP") falls apart when there are more than two variables in their VECM. (The model has a common trend which limits the number of independent long-run restriction to just one.)

See here for more on our paper as well as Chapter 10 of the Kilian and Luetkepohl book.

Here is a figure from our paper that shows the range of impulse responses consistent with the BP news-shock identification:




"Indeterminacy and Imperfect Information" with Thomas Lubik and Christian Matthes

posted Jun 5, 2017, 11:53 AM by Elmar Mertens   [ updated Nov 11, 2019, 2:19 PM ]

This is ongoing work with Thomas A. Lubik (FRB Richmond), Christian Matthes (FRB Richmond):

We study equilibrium determination in an environment where two kinds of agents have different information sets: The fully informed agents know the structure of the model and observe histories of all exogenous and endogenous variables. The less informed agents observe only a strict subset of the full information set. All types of agents form expectations rationally, but agents with limited information need to solve a dynamic signal extraction problem to gather information about the variables they do not observe. We show that for parameters values that imply a unique equilibrium under full information, the limited information rational expectations equilibrium can be indeterminate. We illustrate our framework with a monetary policy problem where an imperfectly informed central bank follows an interest rate rule. 




Here is a slide describing our general setup:



Here is a range of equilibria obtained is a simpler Fisher-equation example (details are in the paper):


Here is a range of equilibria obtained from a richer NK model (details are in the paper):



REVISED: Paper on Time-varying Uncertainty in Survey Forecasts (w/Todd Clark and Michael McCracken)

posted Oct 13, 2016, 9:02 AM by Elmar Mertens   [ updated Sep 21, 2018, 1:49 AM ]

We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to simple variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts.

This is joint work with Todd Clark (FRB Cleveland) and Michael McCracken (FRB St. Louis)


Here is a link to our current draft (Sep 2018): pdf 
And slides for a talk: pdf













FEDS Note on Shadow Rates and the Long-run Level of the Real Rate

posted Feb 10, 2016, 6:27 PM by Elmar Mertens   [ updated Jan 14, 2019, 7:44 AM ]

Together with my Board colleague Ben Johannsen, we just finished a FEDS note describing the latest version of our work on estimating shadow rates from time-series models. 


Part of this work is also featured in the Board’s Monetary Policy Report to the Congress that has just been released on Feb 10, 2016, see pages 32-33 of the report.

   


 

Since last summer we have made the model dynamics more general and are conditioning our estimates not only on macroeconomic aggregates and the federal funds rate, but also on a longer-term interest rate, which (unsurprisingly) provides a particularly useful signal about for inference about the path for short-term interest rates near the effective lower bound.

 

There is also a longer FEDS Working Paper, describing the underlying model, estimation method as well as additional results: pdf (FEDS),

and a NEWLY REVISED working paper: pdf (this site).

Slides for a talk are here: pdf

Here are slides for a shorter talk: pdf

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