Theory and Application of Dynamic Spatial Time Series Models

B.P.J. Andree

Theory and Application of Dynamic Spatial Time Series Models

B.P.J. Andree

Research output: PhD Thesis › PhD-Thesis - Research and graduation internal

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Original language	English
Qualification	PhD
Awarding Institution	Vrije Universiteit Amsterdam
Supervisors/Advisors	Scholten, H.J., Supervisor Koomen, Eric, Co-supervisor
Award date	26 May 2020
Publication status	Published - 2020

Keywords

Econometrics
time series
spatial analysis
econometric theory
spatial econometrics
time series econometrics
multivariate analysis
panel data
machine learning
nonlinear analysis
nonparametric modeling
environment
environmental change
pollution
deforestation
carbon
economic development
poverty
urban density
interest rates
biofuels
land use
land-use change
agricultural systems

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coverFinal published version, 5.87 MB
title pageFinal published version, 63.4 KB
abstract dutchFinal published version, 110 KB
abstract englishFinal published version, 110 KB
table of contentsFinal published version, 79 KB
preliminary matterFinal published version, 5.1 MB
chapter 1Final published version, 109 KB
chapter 2Final published version, 358 KB
chapter 3Final published version, 7.58 MB
chapter 4Final published version, 1.58 MB
chapter 5Final published version, 2.64 MB
chapter 6Final published version, 2.46 MB
chapter 7Final published version, 419 KB
chapter 8Final published version, 120 KB
end matterFinal published version, 5.94 MB
appendix BibliographyFinal published version, 197 KB

Persistent URL (handle)

Persistent link

1 Chapter

Conducting Causal Analysis by Means of Approximating Probabilistic Truths
Andree, B. P. J., 17 Jul 2023, Causal Inference for Heterogeneous Data and Information Theory: Reprinted from: Entropy 2022, 24, 92, doi:10.3390/e24010092. Hlavackova-Schindler, K. (ed.). Basel: Multidisciplinary Digital Publishing Institute (MDPI), p. 249-272 13
Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

Open Access

Cite this

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title = "Theory and Application of Dynamic Spatial Time Series Models",

keywords = "Econometrics, time series, spatial analysis, econometric theory, spatial econometrics, time series econometrics, multivariate analysis, panel data, machine learning, nonlinear analysis, nonparametric modeling, environment, environmental change, pollution, deforestation, carbon, economic development, poverty, urban density, interest rates, biofuels, land use, land-use change, agricultural systems",

author = "B.P.J. Andree",

year = "2020",

language = "English",

series = "Tinbergen Institute research series",

type = "PhD-Thesis - Research and graduation internal",

school = "Vrije Universiteit Amsterdam",

}

TY - THES

T1 - Theory and Application of Dynamic Spatial Time Series Models

AU - Andree, B.P.J.

PY - 2020

Y1 - 2020

KW - Econometrics

KW - time series

KW - spatial analysis

KW - econometric theory

KW - spatial econometrics

KW - time series econometrics

KW - multivariate analysis

KW - panel data

KW - machine learning

KW - nonlinear analysis

KW - nonparametric modeling

KW - environment

KW - environmental change

KW - pollution

KW - deforestation

KW - carbon

KW - economic development

KW - poverty

KW - urban density

KW - interest rates

KW - biofuels

KW - land use

KW - land-use change

KW - agricultural systems

M3 - PhD-Thesis - Research and graduation internal

T3 - Tinbergen Institute research series

ER -

Theory and Application of Dynamic Spatial Time Series Models

Keywords

Access to Document

Persistent URL (handle)

Research output

Conducting Causal Analysis by Means of Approximating Probabilistic Truths

Cite this