Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Date: Thursday, 15/Feb/2018
8:00am
-
8:30am
Registration
8:30am
-
9:30am
P1
Location: E02
 

Macroeconomic forecasting with Bayesian time varying parameter VARs

Gianni Amisano

Federal Reserve Board, United States of America

9:30am
-
10:00am
Coffee Break
10:00am
-
12:00pm
S1a
Location: E02
 

How far can we forecast? Statistical tests of the predictive content

Joerg Breitung1, Malte Knueppel2

1: University of Cologne, Germany; 2: Deutsche Bundesbank, Frankfurt


Comparing predictive accuracy in small samples using fixed-smoothing asymptotics

Laura Coroneo1, Fabrizio Iacone1,2

1: University of York; 2: University of Milan


Predicting Relative Forecasting Performance: Conditional Predictive Ability Approach

Eleonora Granziera, Tatevik Sekhposyan

Bank of Finland, Finland


A New Procedure for Detecting Shifts in Forecast Accuracy

Ching-wai {Jeremy} Chiu1, Simon Hayes1, George Kapetanios2, Konstantinos Theodoridis1

1: Bank of England, United Kingdom; 2: King's College, United Kingdom

S1b
Location: SE101
 

Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?

Martin Feldkircher1, Florian Huber2, Gregor Kastner2

1: Österreichische Nationalbank (OeNB); 2: Wirtschaftsuniversität Wien (WU Wien)


Bank capital constraints, lending supply and the real economy: A Large Bayesian VAR perspective

Antonio M. Conti, Andrea Nobili, Federico M. Signoretti

Banca d'Italia, Italy


Exchange rate predictability and dynamic Bayesian learning

Joscha Beckmann1, Gary Koop2, Dimitris Korobilis3, Rainer Alexander Schüssler4

1: University of Bochum, Germany; 2: University of Strathclyde, Scotland; 3: University of Essex, UK; 4: University of Rostock, Germany


Bayesian Compression for Mixed Frequency Vector Autoregressions: A Forecast Study for Germany

Erik Haustein1, Thomas Götz2

1: University of Kiel, Germany; 2: Deutsche Bundesbank

S1c
Location: SE201
 

A Real-Time Prediction and Adjustment Procedure for Portfolio Allocations

Cindy Shin-Huei Wang

National Tsing Hua University, Taiwan and CORE, UC Louvain, Belgium


The Future is Now: How Joint Decision Making Curbs Hyperbolic Discounting but Blurs Social Responsibility in the Intergenerational Equity Public Policy Domain

Julia M. Puaschunder1, Gary Schwarz2

1: Columbia University, The New School Department of Economics, Schwartz Center for Economic Policy Analysis, United States of America; 2: School of Finance and Management, SOAS


Long-Term Prediction Intervals of Economic Time Series

Marek Chudy1, Sayar Karmakar2, Wei Biao Wu2

1: University of Vienna, Austria; 2: University of Chicago, USA

12:00pm
-
1:30pm
Lunch Break
1:30pm
-
2:30pm
P2
Location: E02
 

A Model of the Fed’s View on Inflation

Lucrezia Reichlin

London Business School

2:30pm
-
3:00pm
Coffee Break
3:00pm
-
5:00pm
S2a
Location: E02
 

Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts

Boriss Siliverstovs

Latvijas Banka, Latvia


Advances in Nowcasting Economic Activity

Juan Antolin-Diaz1, Thomas Drechsel2, Ivan Petrella3

1: Fulcrum Asset Management, United Kingdom; 2: London School of Economics, United Kingdom; 3: Warwick Business School, United Kingdom


Uncertain Kingdom: A Framework for Nowcasting GDP and its Revisions

Nikoleta Anesti1, Silvia Miranda-Agrippino1, Ana Galvao2

1: Bank of England, United Kingdom; 2: Warwick Business School


Macroeconomic news and market’s reaction: Surprise indexes meet nowcasting

Alberto Caruso1,2

1: ECARES, Université libre de Bruxelles; 2: Confindustria

S2b
Location: SE101
 

Robust Inference under Time-Varying Volatility:\\ A Real-Time Evaluation of Professional Forecasters

Yves Robinson Kruse-Becher, Christoph Hanck, Matei Demetrescu

University of Cologne, Germany


Evaluation of Economic Forecasts for Austria

Ines Fortin, Sebastian Koch, Klaus Weyerstrass

IHS, Austria


Assessing the uncertainty in central banks' macroeconomic outlooks

Guido Schultefrankenfeld, Malte Knüppel

Deutsche Bundesbank, Germany


Why did we fail to predict GDP? A breakdown of forecast errors for Austria.

Christian Ragacs, Klaus Vondra, Martin Schneider, Gerhard Fenz

Oesterreichische Nationalbank, Austria

S2c
Location: SE201
 

Economic Forecasting with an Agent-based Model

Sebastian Poledna1,2,3, Michael Miess1,2, Stefan Thurner1,2,3,4

1: International Institute for Applied Systems Analysis; 2: Complexity Science Hub Vienna; 3: Section for Science of Complex Systems, Medical University of Vienna; 4: Santa Fe Institute


Simulation-based selection of prediction models

Robert M. Kunst

IHS Vienna, Austria


Nowcasting Finnish Real Economic Activity: a Large Dimensional Approach

Paolo Fornaro, Henri Luomaranta

Research Institute of the Finnish Economy, Finland

5:00pm
-
6:00pm
P3
Location: E02
 

Designing fan charts for GDP growth forecasts to better reflect downturn risks

David Turner

OECD, France

Date: Friday, 16/Feb/2018
8:30am
-
9:30am
P4
Location: E02
 

Regularized Estimation of High Dimensional Auto- and Cross-Covariance Matrices

Tommaso Proietti

University of Rome Tor Vergata, Italy

9:30am
-
10:00am
Coffee Break
10:00am
-
12:00pm
S3a
Location: E02
 

The Informational Content of Commodity Prices for Probabilistic Inflation Forecasts

Anthony Garratt, Ivan Petrella

University of Warwick, United Kingdom


Forecasting Deflation Probability in The Euro Area: A Combinatoric Approach

Luca Brugnolini

University of Rome Tor Vergata and European Central Bank, Italy


Why are inflation forecasts sticky? Theory and application to France and Germany

Frédérique Bec1, Raouf Boucekkine2, Caroline Jardet3

1: University of Cergy-Pontoise, France; 2: Aix-Marseille School of Economics, France; 3: Banque de France


Phillips Curves

Luca Onorante, Laura Moretti, Shayan Zakipour-Saber

Central Bank of Ireland, Ireland

S3b
Location: SE101
 

A Horse Race in the High Dimensional Space

Paolo Andreini, Donato Ceci

University of Rome, Tor Vergata, Italy


Identification of Structural Vector Autoregressions by Stochastic Volatility

Dominik Bertsche, Robin Braun

University of Konstanz, Germany


TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables

Alvaro Nicolas Bonino-Gayoso, Alfredo Garcia-Hiernaux

Universidad Complutense - Madrid, Spain

S3c
Location: SE201
 

Forecasting euro area private consumption using thick modelling

Gabe de Bondt, Arne Gieseck, Zivile Zekaite

European Central Bank, Germany


Forecasting Industrial Production in Germany

Sercan Eraslan, Klemens Hauzenberger

Deutsche Bundesbank, Germany


Forecasting the production side of GDP

Gregor Bäurle1, Elizabeth Steiner1, Gabriel Züllig2

1: Swiss National Bank, Switzerland; 2: Danmarks Nationalbank, Denmark


Predicting Ordinary and Severe Recessions with a Three-State MarkovSwitching Dynamic Factor Model. An Application to the German Business Cycle

Kai Carstensen1,2,3, Markus Heinrich1, Magnus Reif2, Maik H. Wolters4,5

1: University of Kiel, Germany; 2: ifo Institute, Germany; 3: CESifo; 4: University of Jena; 5: Kiel Insitute for the World Economy

12:00pm
-
1:30pm
Lunch Break
1:30pm
-
3:30pm
Panel
Location: E02
2:00pm
-
3:30pm
Poster: Poster Presentation
Location: Lounge
 

A BVAR Model for Forecasting of Czech Inflation

Michal Franta, Frantisek Brazdik

Czech National Bank, Czech Republic


Macroeconomic modeling and forecasting in practice - the Swiss case

Rolf Scheufele

Swiss National Bank (SNB), Switzerland


Overview of the Macedonian Policy Analysis Model (MAKPAM)

Biljana Jovanovic1, Sultanija Bojceva-Terzijan1, Rilind Kabashi1, Tibor Hledik2

1: National Bank of the Republic of Macedonia, Macedonia, Former Yugoslav Republic of; 2: Joint Vienna Institute


Seasonality in shape features of predictive distribution and density forecasting performance in empirical macroeconomics

Błażej Mazur

Cracow University of Economics, Poland


The Montenegrin macroeconomic forecasting model

Yngve Abrahamsen1, Vojin Golubović2, Michael Graff1, Milika Mirković2, Boriss Siliverstovs3

1: ETH Zürich, KOF Swiss Economic Institute; 2: University of Donja Gorica and Institute for Strategic Studies and Prognoses, Podgorica, Montenegro; 3: The Bank of Latvia


Forecasting East German GDP Growth

João Carlos Claudio, Oliver Holtemöller, Katja Heinisch

Halle Institute for Economic Research, Germany


Building singular VAR forecasting models with Lasso

Bernd Funovits1, Alexander Braumann2

1: University of Helsinki, Finland; 2: TU Braunschweig, Germany


The Global Multi-country Model (GM): an Estimated DSGE Model for the Euro Area Forecasts

Massimo Giovannini1, Beatrice Pataracchia1, Marco Ratto1, Werner Roeger2, Lukas Vogel2

1: JRC,European Commission; 2: DG ECFIN, European Commission

3:30pm
-
4:00pm
Coffee Break
4:00pm
-
6:00pm
S4a
Location: E02
 

Adaptive Combination Schemes for Point and Density Forecasts

Leopoldo Catania1,2, Tommaso Proietti3,2

1: Aarhus BBS, Denmark; 2: CREATES; 3: University of Rom, Tor Vergata


Comparison and Elicitation of Density Forecasts with Weighted Scoring Rules

Justinas Pelenis

Institute for Advanced Studies, Austria


From fixed-event to fixed-horizon density forecasts: professional forecasters' view on multi-horizon uncertainty

Gergely Ganics1, Barbara Rossi2, Tatevik Sekhposyan3

1: Banco de España; 2: ICREA - Universitat Pompeu Fabra, Barcelona GSE, CREI; 3: Texas A&M University


Forecasting GDP growth from the outer space

Jaqueson Kingeski Galimberti

ETH Zurich, Switzerland

S4b
Location: SE101
 

Forecasting with FAVAR: Macroeconomic versus Financial Factors

Alessia Paccagnini

University College Dublin, Ireland


Forecasting with Supervised Factor Models

Simon Lineu Umbach

University of Cologne, Germany


Selecting the Number of Factors in Approximate Factor Models using Group Variable Regularization

Maurizio Daniele

Universität Konstanz, Germany


Forecasting with Factor Models based on unbalanced panels

Catalina Martinez Hernandez1,2

1: DIW Berlin, Germany; 2: Free University of Berlin, Germany

S4c
Location: SE201

 
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Conference: Economic Forecasting 2018
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