Abstract
This study is a specific contribution to investigating normalities in prices to a well-established cointegrated vector autoregressive model (VAR). While the role of prices in computational economics has been investigated, the real prices vis-à-vis nominal prices in the decision process has been neglected. The paper investigates the transition from nominal to real time-series of prices without losing information in the data set when deflating or de-seasonalizing. The likelihood approach is based on careful specifications of the (co)integration characteristics of tourism prices. The results confirm that the transmission of tourism prices in the Eurozone positively impacts Slovenian tourism prices when the spatial consolidated cointegrated VAR model is used. The theoretical-conceptual and empirical contribution is twofold: first, the study develops and empirically applies bona fide divisor of normality consolidation for time-series in levels instead of routinely utilised inflation integers, and second, the study introduces perfection of prices on a long-run time-series treatment.
Highlights
We theoretically investigate how to maintain the normalities in the volatilities of tourism prices using the restricted vector autoregressive (VAR) model, with robust tests in a case of a small open economy where tourism plays a significant role in the economy
This paper aims to develop a contemporary approach to seasonal determined tourism prices in computational economics (Jawadi 2020)
The results show that the forecasts produced using current methods in the scope of cointegration, vector error correction models (VECM), and methodological developments are more precise than those generated by least squares regression models
Summary
This paper is inspired by Johansen (2019) and Juselius (2009, 2021) study on the cointegration method and its application in economic applied research. We start with a theoretical explanation of the normalities and applied examples of one country, robustly extended to five countries of the Eurozone. The research aims to maintain normality in timeseries, which is usually a complex question. Scholars using applied methods usually omit the question of normality in time-series after testing for autocorrelation and homoscedasticity. We theoretically investigate how to maintain the normalities in the volatilities of tourism prices using the restricted vector autoregressive (VAR) model, with robust tests in a case of a small open economy where tourism plays a significant role in the economy
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