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In this article, we examine the usefulness of Google Trends data in predicting monthly tourist arrivals and overnight stays in Prague during the period between January 2010 and December 2016. We offer two contributions. First, we analyze whether Google Trends provides significant forecasting improvements over models without search data. Second, we assess whether a high-frequency variable (weekly Google Trends) is more useful for accurate forecasting than a low-frequency variable (monthly tourist arrivals) using mixed-data sampling (MIDAS). Our results suggest the potential of Google Trends to offer more accurate predictions in the context of tourism: we find that Google Trends information, both 2 months and 1 week ahead of arrivals, is useful for predicting the actual number of tourist arrivals. The MIDAS forecasting model employing weekly Google Trends data outperforms models using monthly Google Trends data and models without Google Trends data.

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The existing literature on fiscal policy has mainly employed linear models that found a small fiscal multiplier in developing economies. These findings challenge the importance and effectiveness of fiscal policy for these countries. However, linear models are not capable of distinguishing the size of a fiscal multiplier in the different phases of economic cycles. Responding to previous studies that confirm the regime dependency of a fiscal multiplier, we develop a non-linear panel threshold vector autoregression model to measure the size of the fiscal multiplier for developing countries. Our findings confirm asymmetry in the response of GDP to government expenditure shock during periods of recovery and downturn. Our main result shows that the response of GDP to government expenditure shock during a recovery period in developing countries is double that for developed ones. Our results also confirm a significantly larger fiscal multiplier during recovery than in an economic downturn. (JEL codes: E32, E62, G15, and C54)

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The purpose of this paper is to test whether institutional governance and its performance is a main driving force to achieve a positive relationship between natural resources and economic growth in the long run. The main objective is to ascertain what kind of institutional governance would be needed to distribute natural resource wealth in such a way so as to achieve economic stability, and what specific policies are needed to avoid the curse in resource-rich developing countries. The research makes an attempt to interpret the role of institutional governance, as reflected by the indicators, in the context of resource-rich, post-Soviet countries. The main finding is that an abundance of natural resources does not guarantee economic growth, where sustainable economic growth can be guaranteed, only if the resource-rich country has good institutional governance.JEL Classification: O11, O43, O53, Q32