Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts

被引:38
作者
Jansen, W. Jos [1 ]
Jin, Xiaowen [2 ]
de Winter, Jasper M. [3 ]
机构
[1] Minist Finance, Financial & Econ Policy Dept, POB 20201, The Hague, Netherlands
[2] Univ Munich, Munich Grad Sch Econ, POB 1111, Munich, Germany
[3] Nederlandsche Bank, Econ Policy & Res Div, POB 98, NL-1000 AB Amsterdam, Netherlands
关键词
Forecasting competitions; Factor models; Professional forecasters; Judgment; SHORT-TERM INDICATOR; OUTPUT GROWTH; NUMBER; MIDAS; DATASETS;
D O I
10.1016/j.ijforecast.2015.05.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
We conduct a systematic comparison of the short-term forecasting abilities of twelve statistical models and professional analysts in a pseudo-real-time setting, using a large set of monthly indicators. Our analysis covers the euro area and its five largest countries over the years 1996-2011. We find summarizing the available monthly information in a few factors to be a more promising forecasting strategy than averaging a large number of single-indicator-based forecasts. Moreover, it is important to make use of all available monthly observations. The dynamic factor model is the best model overall, particularly for nowcasting and backcasting, due to its ability to incorporate more information (factors). Judgmental forecasts by professional analysts often embody valuable information that could be used to enhance the forecasts derived from purely mechanical procedures. (C) 2015 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:411 / 436
页数:26
相关论文
共 49 条
[1]   The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach [J].
Ager, P. ;
Kappler, M. ;
Osterloh, S. .
INTERNATIONAL JOURNAL OF FORECASTING, 2009, 25 (01) :167-181
[2]   Bridge models to forecast the euro area GDP [J].
Baffigi, A ;
Golinelli, R ;
Parigi, G .
INTERNATIONAL JOURNAL OF FORECASTING, 2004, 20 (03) :447-460
[3]   Determining the number of factors in approximate factor models [J].
Bai, JS ;
Ng, S .
ECONOMETRICA, 2002, 70 (01) :191-221
[4]   Determining the number of primitive shocks in factor models [J].
Bai, Jushan ;
Ng, Serena .
JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2007, 25 (01) :52-60
[5]   MAXIMUM LIKELIHOOD ESTIMATION OF FACTOR MODELS ON DATASETS WITH ARBITRARY PATTERN OF MISSING DATA [J].
Banbura, Marta ;
Modugno, Michele .
JOURNAL OF APPLIED ECONOMETRICS, 2014, 29 (01) :133-160
[6]   A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP [J].
Banbura, Marta ;
Ruenstler, Gerhard .
INTERNATIONAL JOURNAL OF FORECASTING, 2011, 27 (02) :333-346
[7]   LARGE BAYESIAN VECTOR AUTO REGRESSIONS [J].
Banbura, Marta ;
Giannone, Domenico ;
Reichlin, Lucrezia .
JOURNAL OF APPLIED ECONOMETRICS, 2010, 25 (01) :71-92
[8]  
Batbura M., 2011, OXFORD HDB EC FORECA, P63
[9]   How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus [J].
Batchelor, R .
APPLIED ECONOMICS, 2001, 33 (02) :225-235
[10]   Monetary policy in a data-rich environment [J].
Bernanke, BS ;
Boivin, J .
JOURNAL OF MONETARY ECONOMICS, 2003, 50 (03) :525-546