User
Short Bio
Ulrich Gunter is an Assistant Professor at the Department of Tourism and Service Management. He holds a Diplom "with Honors" (roughly equivalent to MSc) in Economics from the University of Regensburg (2007, study program within the Elite Network of Bavaria), a PhD in Economics from the University of Vienna (2010, full scholarship from the University of Vienna as "Kollegassistent" for the structured PhD program Issues in the Global Economy: Dynamics, Governance, and Information), as well as an MA in Latin American Studies from the University of Vienna (2015). In 2006, he was a visiting undergraduate student at Santa Clara University.
Ulrich was a visiting researcher at the University of Surrey (November 2013) and at the University of Sao Paulo (July to September 2014), where he concluded a Brazilian Pós-Doutorado. Ulrich is founding co-editor of the MODUL University Working Paper Series (together with H. Goldstein). In addition, he is a member of the University Senate and the chair of the Merit Scholarship Committee at MODUL University Vienna. He acts as the Liaison Officer for outgoing exchange students to the University of Florida and the University of Surrey. Ulrich is a member of the International Association for Tourism Economics (IATE) and the International Institute of Forecasters (IIF).
Research Interests
Ulrich's research interest is in applied econometrics, with a particular focus on time-series analysis (including forecasting) and panel-data analysis. His primary fields of thematic interest are the economics of tourism and sustainability. His secondary fields include macroeconomics, monetary policy, banking, and financial stability.
Awards
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2017 : Wirtschaftskammerpreis 2017 (Wirtschaftskammer Wien)
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2014 : Wirtschaftskammerpreis 2014 (Wirtschaftskammer Wien)
Projects
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Sharing Economy: The Competitive Standing of Viennese Airbnb Accommodations
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Bozana Zekan, Irem Önder, Ulrich Gunter
Date: 01.10.2017 - 30.09.2018
Managed By: MODUL University Vienna
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Status Quo of Airbnb in Vienna and in its Main Competitors
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Irem Önder, Bozana Zekan
Date: 01.08.2016 - 31.01.2017
Managed By: MODUL University Vienna
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TRIANGLE - The Tourism Research, Innovation and Next Generation Learning Experience
The Tourism Research, Innovation And Next Generation Learning Experience (TRIANGLE) Program is creating a Knowledge Alliance of HEIs and businesses across Europe, delivering a common sustainable tourism training system for protected area and green tourism destinations. Within the framework of the EU’s Erasmus Knowledge Alliance program, the European-wide Ecotrans Network for Sustainable Tourism has teamed up with leading universities (Algarve, Eberswalde, Sorbonne, Vienna), and businesses with core ICT and tourism interests (Eau de Web, Forum Anders Reisen) to create a European-wide collaborative online learning system for Higher Education Institutes (HEIs) to offer quality sustainability training and education to tourism destination administrators, SMEs workforce individuals and students linked to tourism activity in Europe’s protected areas and green destinations.
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Dagmar Lund-Durlacher
Date: 01.11.2016 - 31.10.2019
Managed By: MODUL University Vienna
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Statistical Report on Tourism Accommodation Establishments
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Egon Smeral, Irem Önder, Ulrich Gunter
Date: 01.01.2016 - 31.12.2017
Managed By: MODUL University Vienna
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Forecasting Tourism Demand for Vienna with Google Trends
The purpose of this study is to investigate whether using Google Trends indices for web and image searches improves tourism demand forecast accuracy relative to a purely autoregressive baseline model. To this end, Vienna, one of the top-10 European city destinations, is chosen as a case example, for which the predictive power of Google Trends is evaluated at the total demand and at the source market levels. The effect of the search query language on predictability of arrivals is considered and differences between seasonal and seasonally-adjusted data are investigated. The results confirm that the forecast accuracy is improved when Google Trends data are included across source markets and forecast horizons for seasonal and seasonally-adjusted data, leaning towards native-language searches. This outperformance not only holds relative to purely autoregressive baseline specifications, but also relative to time-series models such as Holt-Winters and naïve benchmarks, where the latter are significantly outperformed on a regular basis.
Organisations: MODUL University Vienna, Department of Tourism and Service Management
Author: Ulrich Gunter, Irem Önder
Date: 01.10.2014 - 30.06.2015
Managed By: MODUL University Vienna
Research Output
- 2017
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"Book Review: Tourism, Public Transport and Sustainable Mobility, C.M. Hall, D.-T. Le-Klähhn, Y. Ram."2017 in: Tourism Management. Volume: 63. Pages: 366-367
Author(s): Ulrich Gunter
Publication date: 12. 2017
Volume: 63
Pages: 366-367
Electronic version(s), related files and links: http://dx.doi.org/ https://doi.org/10.1016/j.tourman.2017.07.010
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"How Do Macroeconomic and Bank-specific Variables Influence Profitability in the Austrian Banking Sector? Evidence from a Panel Vector Autoregression Analysis"2017 in: Economic Notes.
We examine the determinants of the net interest margin (NIM) and the net fee and commission income ratio (NFCIR) of Austrian banks as well as their interrelationship and whether portfolio separation between loan and deposit categories holds. We describe a conceptual framework for the profit optimization problem faced by banks as a Bertrand game with differentiated products and intrafirm product interactions. We contribute to the literature by factoring in banks’ business models in terms of their balance sheet structure. We empirically assess the implications of our conceptual framework using a unique supervisory data set of around 48,000 observations between 1998 and 2014. We estimate two panel vector autoregression models with a novel panel vector autoregression code. Apart from quantifying the contributions of the determinants (e.g., risk weighted assets, leverage ratio, loan loss provision ratio) to NIM and NFCIR, the empirical results show that interest income and fee and commission income should be regarded as strategic complements within a bank. We further conclude that portfolio separation between different loan and deposit categories does not hold.
Author(s): Michael Sigmund, Ulrich Gunter, Gerald Krenn
Publication date: 21. 6. 2017
Electronic version(s), related files and links: http://dx.doi.org/10.1111/ecno.12088
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"Benchmarking of Airbnb Providers: How Competitive Are European Cities?"2017
Author(s): Bozana Zekan, Irem Önder, Ulrich Gunter
Publication date: 6. 2017
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"European outbound tourism in times of economic stagnation"2017 in: International Journal of Tourism Research. Volume: 19. Issue number: 3 Pages: 269–277
Accounting for the instability of tourism income elasticities in the European Union-15 since 2004, estimations show that income elasticities in the period 2004–2014 were greater in slow-growth periods (above 1) than in fast-growth periods (below 1). Due to the gradual deterioration of the economic environment since 2004, the small income improvements in the fast-growth periods were used relatively more for satisfying pent-up demand for necessary consumer goods or precautionary savings than for traveling abroad. The relatively high income elasticities in the slow-growth periods resulted from negative adjustments due to the effects of the economic downturn.
Author(s): Ulrich Gunter, Egon Smeral
Publication date: 5. 2017
Volume: 19
Issue number: 3
Pages: 269–277
Electronic version(s), related files and links: http://dx.doi.org/10.1002/jtr.2108
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"Forecast Combinations in a DSGE-VAR Lab"2017 in: Journal of Forecasting. Volume: 36. Issue number: 3 Pages: 305–324
We explore the benefits of forecast combinations based on forecast-encompassing tests compared to simple averages and to Bates–Granger combinations. We also consider a new combination algorithm that fuses test-based and Bates–Granger weighting. For a realistic simulation design, we generate multivariate time series samples from a macroeconomic DSGE-VAR (dynamic stochastic general equilibrium–vector autoregressive) model. Results generally support Bates–Granger over uniform weighting, whereas benefits of test-based weights depend on the sample size and on the prediction horizon. In a corresponding application to real-world data, simple averaging performs best. Uniform averages may be the weighting scheme that is most robust to empirically observed irregularities.
Author(s): Mauro Costantini, Ulrich Gunter, Robert M. Kunst
Publication date: 4. 2017
Volume: 36
Issue number: 3
Pages: 305–324
Electronic version(s), related files and links: http://dx.doi.org/10.1002/for.2427
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