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230404 ||| eng |
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|a 9798400224690
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| 100 |
1 |
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|a Bespalova, Olga
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| 245 |
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|a Modeling and Forecasting Monthly Tourism Arrivals to Aruba Since COVID-19 Pandemic
|c Olga Bespalova
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2022
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| 300 |
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|a 38 pages
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| 651 |
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|a Aruba, Kingdom of the Netherlands
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| 653 |
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|a Income economics
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| 653 |
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|a Tourism
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| 653 |
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|a Diseases: Contagious
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| 653 |
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|a Forecasting
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| 653 |
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|a Diffusion Processes
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| 653 |
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|a Production and Operations Management
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| 653 |
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|a Economic sectors
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| 653 |
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|a Recreation
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| 653 |
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|a Communicable diseases
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| 653 |
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|a Industrial capacity
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| 653 |
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|a Unemployment: Models, Duration, Incidence, and Job Search
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| 653 |
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|a Currency crises
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| 653 |
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|a Health
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| 653 |
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|a Macroeconomics: Production
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| 653 |
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|a Gambling
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| 653 |
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|a Production
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Health Behavior
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| 653 |
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|a Economic & financial crises & disasters
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| 653 |
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|a Labor
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| 653 |
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|a Industries: Hospital,Travel and Tourism
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| 653 |
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|a Forecasting and Other Model Applications
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| 653 |
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|a Economics of specific sectors
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| 653 |
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|a Time-Series Models
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| 653 |
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|a Macroeconomic Aspects of International Trade and Finance: Forecasting and Simulation
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| 653 |
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|a Labour
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| 653 |
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|a Economic Forecasting
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| 653 |
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|a Sports
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| 653 |
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|a Infectious & contagious diseases
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| 653 |
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|a Restaurants
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| 653 |
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|a Unemployment rate
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| 653 |
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|a Economic forecasting
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| 653 |
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|a Economics: General
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| 653 |
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|a Dynamic Quantile Regressions
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| 653 |
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|a Covid-19
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| 653 |
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|a Capacity utilization
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| 653 |
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|a Unemployment
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| 653 |
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|a Informal sector
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| 653 |
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|a Economics
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| 653 |
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|a Dynamic Treatment Effect Models
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| 653 |
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|a Hospitality, leisure & tourism industries
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b IMF
|a International Monetary Fund
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| 490 |
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|a IMF Working Papers
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| 028 |
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|a 10.5089/9798400224690.001
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| 856 |
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|u https://elibrary.imf.org/view/journals/001/2022/226/001.2022.issue-226-en.xml?cid=525638-com-dsp-marc
|x Verlag
|3 Volltext
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| 082 |
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|a 330
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| 520 |
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|a This paper improves short-term forecasting models of monthly tourism arrivals by estimating and evaluating a time-series model with exogenous regressors (ARIMA-X) using a case of Aruba, a small open tourism-dependent economy. Given importance of the US market for Aruba, it investigates informational value of Google Searches originating in the USA, flight capacity utilization on the US air-carriers, and per capita demand of the US consumers, given the volatility index in stock markets (VIX). It yields several insights. First, flight capacity is the best variable to account for the travel restrictions during the pandemic. Second, US real personal consumption expenditure becomes a more significnat predictor than income as the former better captured impact of the COVID-19 restrictions on the consumers' behavior, while income boosted by the pandemic fiscal support was not fully directed to spending. Third, intercept correction improves the model in the estimation period. Finally, the pandemic changed econometric relationships between the tourism arrivals and their main determinants, and accuracy of the forecast models. Going forward, the analysts should re-estimate the models. Out-of-sample forecasts with 5 percent confidence intervals are produced for 18 months ahead
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