The generalized dynamic factor model consistency and rates

Forni, Mario; Hallin, Marc; Lippi, Marco; Reichlin, Lucrezia

doi:10.1016/s0304-4076(03)00196-9

Cited by 230 publications

(141 citation statements)

References 11 publications

Supporting

Mentioning

137

Contrasting

Unclassified

Order By: Relevance

“…Dreger and Schumacher (2004) and Schumacher (2005) are the only known studies to us that apply this methodology for Germany. To this end, our study complements that of Dreger and Schumacher (2004), who investigated the forecasting performance of the diffusion index model of Stock and Watson (2002) against the benchmark autoregressive model and the Ifo business climate indicator, and that of Schumacher (2005), who compared the forecasting performance of alternative methodologies for construction of diffusion indices based on Stock and Watson (2002), Kapetanions and Marcellino (2004), and Forni et al (2002Forni et al ( , 2004. Hence, out of two studies that employed the diffusion index methodology to the German GDP only the former compares its forecasting performance with that of only one alternative leading indicator.…”

Section: Motivationmentioning

confidence: 94%

On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence

Kholodilin

Siliverstovs

2006

Jahrbücher Für Nationalökonomie Und Statistik

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractIn this paper we perform a comparative study of the forecasting properties of the alternative leading indicators for Germany using the growth rates of German real GDP. We use the post-unification data which cover years from 1991 through 2004. We detect a structural break in the growth rates that occurs in the first half of 2001. Our results suggest that the forecasting ability of the leading indicators has been rather good in the pre-break period but it significantly deteriorated in the post-break period, i.e. in [2001][2002][2003][2004]. None of the leading indicator models was able to predict and accommodate the structural break in the growth rates of the time series under scrutiny.

show abstract

Section: Motivationmentioning

confidence: 94%

On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence

Kholodilin

Siliverstovs

2006

Jahrbücher Für Nationalökonomie Und Statistik

View full text Add to dashboard Cite

show abstract

“…In general, factor analysis problems are often solved through a maximum likelihood approach (see Tipping and Bishop, 1999). A more enhanced version of the factor analysis model, the so-called dynamic factor model, is used extensively in econometrics, where the factors f are taken to be time-dependent (Forni et al, 2000(Forni et al, , 2004(Forni et al, , 2005.…”

Section: Background and Motivationmentioning

confidence: 99%

Random matrix theory in statistics: A review

Paul

Aue

2014

Journal of Statistical Planning and Inference

160

113

View full text Add to dashboard Cite

b s t r a c tWe give an overview of random matrix theory (RMT) with the objective of highlighting the results and concepts that have a growing impact in the formulation and inference of statistical models and methodologies. This paper focuses on a number of application areas especially within the field of high-dimensional statistics and describes how the development of the theory and practice in high-dimensional statistical inference has been influenced by the corresponding developments in the field of RMT.

show abstract

“…We focus on the development of the static factor models, which are to be distinguished from dynamic factor models in ways to be made precise. Key results concerning large dynamic factor models are given in Forni et al (2000Forni et al ( , 2004Forni et al ( , 2005. Results concerning the use of factors in forecasting are discussed in Stock and Watson (2006), Banerjee et al (2006), and Giannone et al (2007).…”

mentioning

confidence: 99%

Large Dimensional Factor Analysis

Bai

2008

FNT in Econometrics

279

190

View full text Add to dashboard Cite

Econometric analysis of large dimensional factor models has been a heavily researched topic in recent years. This review surveys the main theoretical results that relate to static factor models or dynamic factor models that can be cast in a static framework. Among the topics covered are how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy of observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, * We are grateful to an anonymous referee for careful reading and constructive comments. This survey was presented by the second author as an invited lecture at the 2007 annual meeting of the Society of Computational Economics in Montreal. Financial support from the National Science Foundation (SES055127 and SES-0549978) is gratefully acknowledged.and how to estimate panel cointegration models. The fundamental result that justifies these analyses is that the method of asymptotic principal components consistently estimates the true factor space. We use simulations to better understand the conditions that can affect the precision of the factor estimates.

show abstract

The generalized dynamic factor model consistency and rates

Cited by 230 publications

References 11 publications

On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence

On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence

Random matrix theory in statistics: A review

Large Dimensional Factor Analysis

Contact Info

Product

Resources

About