Mark Bognanni

Board of Governors of the Federal Reserve System

20th Street and Constitution Avenue NW

Washington, DC 20551

United States

SCHOLARLY PAPERS

3

DOWNLOADS

228

SSRN CITATIONS

4

CROSSREF CITATIONS

6

Scholarly Papers (3)

Estimating (Markov-Switching) VAR Models Without Gibbs Sampling: A Sequential Monte Carlo Approach

FRB of Cleveland Working Paper No. 14-27
Number of pages: 50 Posted: 22 Nov 2014 Last Revised: 10 Jan 2015
Mark Bognanni and Edward Herbst
Board of Governors of the Federal Reserve System and Board of Governors of the Federal Reserve System
Downloads 103 (325,419)
Citation 1

Abstract:

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Vector Autoregressions, Sequential Monte Carlo, Regime-Switching Models, Bayesian Analysis

Estimating (Markov-Switching) VAR Models Without Gibbs Sampling: A Sequential Monte Carlo Approach

FEDS Working Paper No. 2015-116
Number of pages: 56 Posted: 22 Dec 2015
Mark Bognanni and Edward Herbst
Board of Governors of the Federal Reserve System and Board of Governors of the Federal Reserve System
Downloads 63 (436,824)

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Economics and Epidemics: Evidence from an Estimated Spatial Econ-Sir Model

FEDS Working Paper No. 2020-91
Number of pages: 59 Posted: 27 Oct 2020
Board of Governors of the Federal Reserve System, University of Pittsburgh, University of Maryland - College Park and Stockholm University
Downloads 26 (618,704)
Citation 1

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Economics and Epidemics: Evidence from an Estimated Spatial Econ-Sir Model

IZA Discussion Paper No. 13797
Number of pages: 60 Posted: 27 Oct 2020
Board of Governors of the Federal Reserve System, University of Pittsburgh, University of Maryland - College Park and Stockholm University
Downloads 9 (754,775)

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Econ-SIR, COVID-19, economic policy, epidemics

3.

A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification

FRB of Cleveland Working Paper No. 18-11
Number of pages: 61 Posted: 21 Sep 2018
Mark Bognanni
Board of Governors of the Federal Reserve System
Downloads 27 (594,963)
Citation 2

Abstract:

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structural vector autoregressions, time-varying parameters, Gibbs sampling, stochastic volatility, Bayesian inference