Limiting experiments for panel-data and jump-diffusion models

I.G. Becheri

Research output: ThesisDoctoral ThesisScientific

361 Downloads (Pure)

Abstract

This work concerns the theory of limiting experiments and its use in econometrics. In Chapter 2, we consider jump-diffusion models and we compare, by means of the limiting experiment, the statistical information contained in continuous-time observations with that contained in discrete-time observations sampled in high frequency. In Chapter 3, we establish the Local Asymptotic Quadratic condition for bivariate hidden Ornstein-Uhlenbeck models using continuous-time observations. We assume that the hidden process is highly persistent and, using the limiting experiment, we discuss some inference procedures. Chapter 4 provides the power envelope for tests of the unit root hypothesis in Gaussian panel data models with cross-sectional dependence. And, it proposes a test statistic which attains the power envelope.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Tilburg University
Supervisors/Advisors
  • Drost, Feike C., Co-promotor
  • van den Akker, Ramon, Co-promotor
  • Werker, Bas, Promotor
Award date21 Dec 2012
Place of PublicationTilburg
Publisher
Print ISBNs9789056683382
Publication statusPublished - 2012

Fingerprint

Jump-diffusion Model
Panel Data
Limiting
Envelope
Discrete Time Observations
Experiment
Continuous-time Model
Unit Root
Econometrics
Data Model
Test Statistic
Continuous Time
Observation

Cite this

Becheri, I. G. (2012). Limiting experiments for panel-data and jump-diffusion models. Tilburg: CentER, Center for Economic Research.
Becheri, I.G.. / Limiting experiments for panel-data and jump-diffusion models. Tilburg : CentER, Center for Economic Research, 2012. 104 p.
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Becheri, IG 2012, 'Limiting experiments for panel-data and jump-diffusion models', Doctor of Philosophy, Tilburg University, Tilburg.

Limiting experiments for panel-data and jump-diffusion models. / Becheri, I.G.

Tilburg : CentER, Center for Economic Research, 2012. 104 p.

Research output: ThesisDoctoral ThesisScientific

TY - THES

T1 - Limiting experiments for panel-data and jump-diffusion models

AU - Becheri, I.G.

PY - 2012

Y1 - 2012

N2 - This work concerns the theory of limiting experiments and its use in econometrics. In Chapter 2, we consider jump-diffusion models and we compare, by means of the limiting experiment, the statistical information contained in continuous-time observations with that contained in discrete-time observations sampled in high frequency. In Chapter 3, we establish the Local Asymptotic Quadratic condition for bivariate hidden Ornstein-Uhlenbeck models using continuous-time observations. We assume that the hidden process is highly persistent and, using the limiting experiment, we discuss some inference procedures. Chapter 4 provides the power envelope for tests of the unit root hypothesis in Gaussian panel data models with cross-sectional dependence. And, it proposes a test statistic which attains the power envelope.

AB - This work concerns the theory of limiting experiments and its use in econometrics. In Chapter 2, we consider jump-diffusion models and we compare, by means of the limiting experiment, the statistical information contained in continuous-time observations with that contained in discrete-time observations sampled in high frequency. In Chapter 3, we establish the Local Asymptotic Quadratic condition for bivariate hidden Ornstein-Uhlenbeck models using continuous-time observations. We assume that the hidden process is highly persistent and, using the limiting experiment, we discuss some inference procedures. Chapter 4 provides the power envelope for tests of the unit root hypothesis in Gaussian panel data models with cross-sectional dependence. And, it proposes a test statistic which attains the power envelope.

M3 - Doctoral Thesis

SN - 9789056683382

T3 - CentER Dissertation Series

PB - CentER, Center for Economic Research

CY - Tilburg

ER -

Becheri IG. Limiting experiments for panel-data and jump-diffusion models. Tilburg: CentER, Center for Economic Research, 2012. 104 p. (CentER Dissertation Series).