Ostalo
https://doi.org/10.20867/thm.28.3.16
Implementation of Vector Auto-Regression Models in Tourism: State Of The Art Analysis and Further Development, Doctoral Dissertation Summary
Sergej Gričar
; The University of Rijeka, Faculty of Tourism and Hospitality Management
Sažetak
Purpose
The dissertation focuses on time series analysis and is based on several research strategies
and methods.
The methodology used in the research process was published in four papers as part of
international scientific journals indexed in the Web of Science database. Since tourism
is one of the most lagged industries in science there is need for new and innovative
approaches in key tourist sector determinants modelling and forecasting.
This doctoral thesis introduces an extension of time series methodology that focuses
on investigating and testing the normal distribution of residuals, as a key adequacy
prerequisite of econometric models. This issue has not systematically been considered in
quantitative approaches in tourism.
The motivation for research of the doctoral thesis are multidimensional: to filter previous
research on time series in tourism and to theoretically and empirically improve and
redesign time series methodology and methods for tourism. Both issues were successfully
presented in one of the published papers. Finally, tourism forecasts should be based on
reliable models as evident, from the most recent shocks, ex-ante tourism forecasting has
to be considered crucial in evaluating model efficiency.
The dissertation aimed to research and develop appropriate econometric models able to
capture the specifics of multiple interactions in the tourism market. The research seeks
to develop econometric models for the Republics of Slovenia and Croatia, two countries
whose economic development is predicated on tourism. Four goals and four specific objectives have been specified during the research process:
1) To introduce an improved time series approach in cointegrated panels. The first specific
objective (SO1) is to test at least ten econometric modelling structures that reduce cycle
breaks. 2) To examine previous theoretical thinking regarding the cointegration of
time series, cross-sectional data, and panels. The second specific objective (SO2) is to
outline at least 250 previous empirical studies for the tourism industry. 3) To examine
cointegration in tourism data for Slovenia and Croatia. The third objective (SO3) is
to model at least three econometric time series equations and mathematical theorems/
lemmas for the tourism industry. 4) To improve and better understand unit root tests in
tourism. The specific objective (SO4) is to approach the design of at least three stable
and innovative models.
Ključne riječi
Croatia; Econometric analysis; Time series Forecasting; Secondary Data; Slovenia; Tourist Arrivals
Hrčak ID:
290251
URI
Datum izdavanja:
16.9.2022.
Posjeta: 324 *