# Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series

## Abstract

**:**

## 1. Introduction

**Outline of the paper.**Section 2 deals with the spiked covariance model developed in the probability and mathematical statistics literature. This model, indeed, is somewhat similar to the factor-model approach, with an essential difference that helps understand the benefits of the latter. Section 3 features a brief history of the factor-model approach and introduces the general dynamic factor model (GDFM). Section 4 highlights the importance of Manfred Deistler’s contribution to the ultimate development of the GDFM methodology.

## 2. Spiked Covariance Models: A Needle in a Growing Haystack

## 3. Dynamic Factor Models: Pervasive Needles and the Blessing of Dimensionality

## 4. Manfred Deistler and the General Dynamic Factor Model

**Proposition**

**1.**

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**MDPI and ACS Style**

Hallin, M.
Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series. *Econometrics* **2022**, *10*, 37.
https://doi.org/10.3390/econometrics10040037

**AMA Style**

Hallin M.
Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series. *Econometrics*. 2022; 10(4):37.
https://doi.org/10.3390/econometrics10040037

**Chicago/Turabian Style**

Hallin, Marc.
2022. "Manfred Deistler and the General-Dynamic-Factor-Model Approach to the Statistical Analysis of High-Dimensional Time Series" *Econometrics* 10, no. 4: 37.
https://doi.org/10.3390/econometrics10040037