Do neighbours influence value-added-tax introduction? A spatial duration analysis

Pavel Cizek, J. Lei, J.E. Ligthart

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. However, the spatial effect may not only exist in the unobserved errors, but it can also be present in the baseline hazards and the dependent variables. A new spatial survival model with these three possible spatial correlation structures is explored and used to investigate the implementation of value-added tax (VAT) in 99 countries over the period 1970–2009. Estimation is performed by a Bayesian approach through the Markov chain Monte Carlo method. The estimation results suggest the presence of a significant spatial correlation among the VAT introductions of neighbouring countries.
Original languageEnglish
Pages (from-to)25-54
JournalOxford Bulletin of Economics and Statistics
Volume79
Issue number1
DOIs
Publication statusPublished - Feb 2017

Fingerprint

value added tax
Survival Model
Spatial Model
Tax
Spatial Correlation
Unobserved Heterogeneity
Frailty
neighboring countries
Markov Chain Monte Carlo Methods
Correlation Structure
Spatial Structure
Bayesian Approach
Hazard
Baseline
Dependent
Influence
Survival model
Duration analysis
Spatial correlation
Value added tax

Cite this

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Do neighbours influence value-added-tax introduction? A spatial duration analysis. / Cizek, Pavel; Lei, J.; Ligthart, J.E.

In: Oxford Bulletin of Economics and Statistics, Vol. 79, No. 1, 02.2017, p. 25-54.

Research output: Contribution to journalArticleScientificpeer-review

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AB - The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. However, the spatial effect may not only exist in the unobserved errors, but it can also be present in the baseline hazards and the dependent variables. A new spatial survival model with these three possible spatial correlation structures is explored and used to investigate the implementation of value-added tax (VAT) in 99 countries over the period 1970–2009. Estimation is performed by a Bayesian approach through the Markov chain Monte Carlo method. The estimation results suggest the presence of a significant spatial correlation among the VAT introductions of neighbouring countries.

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