Purpose – The aim of this paper is to present the relationship between climate and tourism development data as an example of an emerging winter and ski tourism destination in Slovakia. Design/methodology/approach – The method aims to discover the relationship through snow-reliability and regression analyses and to further implicate the consequences of such established relationship under a changing (warming) climate. Findings – As a result of the research, the authors can predict that a 1 per cent fall in snow depth and visibility would erode the ski demand by 1.2 and 0.12 per cent, respectively, a 1°C rise of the mean temperature, on the other hand, would indicate a 6 per cent loss of skipass sales. The latter finding translates into a further 6.6 to 19.2 per cent loss of sales on account of the anticipated temperature increases for the twenty-first century. The capacity of the resort for the utmost adaptation strategy, snowmaking, is also to deteriorate with the daytime/fulltime annual good quality production range to reduce from 33/45 days to 10-26/14-34 days, according to the emissions-related warming scenarios and in terms of the commonly available current technology. Practical implications – The results of the study can help the management of ski resorts to adopt strategies for the future development by taking into account the predicted climatic changes. Originality/value – This study is the first type of study performed in Slovakia and can contribute to the better understanding of the relationship between climate change and the performance of the ski tourism resorts. It also delivers innovation by considering wet-bulb temperature in snow-reliability analyses and also by coining the “climate elasticity” concept.

The effects of climate conditions and weather on ski tourism have become a hot topic as the negative impacts of climate change on ski tourism become increasingly visible. This study aims at measuring the significance and magnitude of long-term diurnal and daily weather conditions on lift frequentation at an Austrian glacier ski area in terms of the winter and the summer skiing offers. In doing so, it utilizes an autoregressive conditional heteroskedasticity (ARCH) model to reveal and quantify any volatility associated with ski area visitation and then employs regression models to account for any microclimatic elasticity of glacier skiing demand. The main findings reveal a significant volatility in ski area visitation, especially during the summer seasons. While this study does not aim for an ultimate determination on the reasons for such volatility, skiing demand models illustrate the importance of thermal comfort, especially wind chill factor (WCF), as a major determinant of demand sensitivity for glacier skiing as well as non-skier visits during the summer season. Significant, albeit inelastic, relationships between other microclimatic characteristics, such as snow depth and relative humidity, with visitation and lift frequentation are also identified. Based on these findings, implications according to a changing climate and practical suggestions on the sustainability of winter and summer skiing activities are provided.

Purpose Might the impact of the global economic policy uncertainty (GEPU) and the long-term bond yields on oil prices be asymmetric? This paper aims to consider the effects of the GEPU and the US long-term government bond yields on oil prices using quantile-based analysis and nonlinear vector autoregression (VAR) model. The author hypothesized whether the negative and positive changes in the GEPU and the long-term bond yields of the USA have different effects on oil prices. Design/methodology/approach To address this question, the author uses quantile cointegration model and the impulse response functions (IRFs) of the censored variable approach of Kilian and Vigfusson (2011). Findings The quantile cointegration test showed the existence of non-linear cointegration relationship, whereas Granger-causality analysis revealed that positive/negative variations in GEPU will have opposite effects on oil prices. This result was supported by the quantile regression model’s coefficients and nonlinear VAR model’s IRFs; more specifically, it was stressed that increasing/decreasing GEPU will deaccelerate/accelerate global economic activity and thus lead to a fall/rise in oil prices. On the other hand, the empirical models indicated that the impact of US 10-year government bond yields on oil prices is asymmetrical, while it was found that deterioration in the borrowing conditions in the USA may have an impact on oil prices by slowing down the global economic activity. Originality/value As a robustness check of the quantile-based analysis results, the slope-based Mork test is used.

This study analyzes the effects of some major macroeconomic variables on construction sector activity in Turkey by employing a Vector Autoregression (VAR) model from 1990Q1 to 2010Q3. The 4-variable VAR model includes the log of construction sector activity (COACT), the log of real gross domestic product (RGDP), weighted averages of 12-month interest rate on deposit (INT) and the log of banking sector total domestic credits (CRE). According to VAR model impulse response analysis, the sector booms related to a positive one standard deviation shock in RGDP. Thereby, the importance of maintaining economic stabilization is revealed since economic contractions may affect the sector negatively. In addition to this finding, impulse response analysis indicates that a positive one standard deviation shock in INT deteriorates the construction sector activity. Therefore, interest rates should be kept low by the coordination of monetary and fiscal policy. Moreover, impulse response analysis results emphasize that credit supply and demand should be equalized for minimizing default risk. On the other hand, forecast error variance decomposition (FEVD) analysis infers the importance of real gross domestic product, weighted averages of 12-month interest rate on deposit and banking sector total domestic credits in determining construction sector activity.

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