Econometrics, finance, and time series analysis Masanobu Taniguchi, Diane Pierret, Martin Schumann, Thomas A. Severini, Gautam Tripathi, Yujie Xue

Format:

Book

Author/Creator:

Taniguchi, Masanobu, author.

Pierret, Diane, 1986- author.

Schumann, Martin, author.

Severini, Thomas A. (Thomas Alan), 1959- author.

Tripathi, Gautam, author.

Xue, Yujie, author.

Series:

SpringerBriefs in statistics. JSS research series in statistics 2364-0065

JSS research series in statistics 2364-0065

Language:

English

Subjects (All):

Econometrics.

Time-series analysis.

Physical Description:

1 online resource

Place of Publication:

Singapore Springer 2026

Summary:

This book provides a new contemporary time series approach for econometrics and finance. In a concrete manner a very general divergence between spectra is introduced, resulting in the development of a statistical inference that is efficient and robust, and leads to a new perspective. A measure of systemic risk is also developed in the energy market,which quantifies the cost of energy asset distress vis-à-vis the broader economy during crises, and examines the dynamic interaction between solvency and funding liquidity risk in banks using a panel vector autoregressive (VAR) model. This step shows that a forward-looking measure of capital shortfall under stress is both a predictor and an outcome of funding liquidity risk. Additionally, a new integrated likelihood-based approach for estimating nonlinear panel data models is described. Unlike existing integrated likelihoods, the new integrated likelihood is closer to a genuine likelihood. The book explains why this is due to first-order information unbiasedness, and why it seems to matter more for inference than for estimation. Results of studies in econometrics are provided for support

Contents:

1 Introduction

2 Hellinger Distance Estimation for Non-Regular Spectra

3 Local Whittle likelihood approach for generalized divergence

4 Systemic Risk in Energy Markets: Measuring Co-Movements in Energy Asset Prices During Crises

5 Modeling Solvency and Liquidity Interactions in Banking: A Panel VAR Analysis

6 Integrated likelihood based inference for nonlinear panel data models

7 Reducing score and information bias in panel data likelihoods

8 Shrinkage estimators of BLUE for time series regression models

Notes:

Includes bibliographical references

Online resource; title from PDF title page (SpringerLink, viewed July 28, 2026)

ISBN:

9789819580453

9819580455

OCLC:

1608633499

Access Restriction:

Restricted for use by site license