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Demand for Inbound Tourism in Russia: Panel Data Analysis

Student: Mamaeva Polina

Supervisor: Tatiana Nikolaeva

Faculty: Faculty of Economics

Educational Programme: Economics (Bachelor)

Year of Graduation: 2020

This paper is focused on determining the most appropriate and significant price and non-price factors regarding international tourism demand by carrying out econometric analysis. Based on theoretical review, the paper empirically examines the data on tourist arrivals from 53 countries over the period of 9 years (2010-2018) using panel data techniques. One of the main contributions of the work is that it compares fixed (FE) and random effects (RE) models in terms of efficiency and statistical significance. As evidenced by the results, the effectiveness of the FE model is confirmed in the case of the best specification, while random effects are preferable in the event of the inclusion of time-dummy variables in the model. This study could be advanced by comparing models with different dependent variables, switching to dynamic panels using the Arellano-Bond procedure and obtaining a more precise tourism price determinant.

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