Mariana Petrova

Purposeful and reasonable state vision of the long-term tourism development strategy determines the success of a country in the world market of tourist services. Many countries have officially approved program documents that clearly outline the main goals and objectives of the state policy in the sphere of tourism, highlighting the resource potential, recreational infrastructure and preferred consumer markets, but there may be no idea of respecting the interests of domestic consumers. The maintenance of local tourism infrastructure is becoming an increasingly important prerequisite for the country’s competitiveness, as mass tourism is now replaced by individual travels. The article is aimed at studying the dependencies between the main macroeconomic indicators of the tourism industry, assessing the efficiency of foreign trade. The correlation-regression and cluster analysis has been used in order to confirm or refute the hypothesis if the effectiveness of the state support of the national tourism industry is dependent on the stable functioning of the domestic tourism market, e.g. stimulation of travels by residents. Based on the main macroeconomic indicators of the tourism industry for 136 countries of the world and overview of some national tourism development program, the analysis output has rejected the direct correlation between the support of the domestic market and export potential of the national tourism industry, but has proved the significance of the inner consumer power during the periods of downturns in the global economy for strengthening the country’s export potential.

Accurate housing price forecasts play a critical role in balancing supply and demand in the residential real estate market, as well as in achieving the goals of various stakeholders – buyers, investors, construction contractors, public administration, real estate agencies, special investment purpose companies, etc. The present study aims to investigate the relationship between specific predictors and build a suitable model for forecasting housing prices in Bulgaria. In this regard, a study was conducted on transactions with residential real estate in the city of Sofia for the period from the first quarter of 2016 to the fourth quarter of 2021. The ARIMA model is used in the development to predict the values of the variables. Eight models are tested for the researched factors (24 in total). On this basis, the price per square meter of residential property was predicted, including estimated values from the ARIMA model for the parameters involved in the regression equation. The result showed that there is a strong relationship between the analyzed predictors and the studied variable – price per square meter of housing. The tested models are adequate and the statistical requirements for forecasting the prices of residential properties in Bulgaria are complied.