{"id":1000442,"date":"2025-12-31T23:46:50","date_gmt":"2026-01-01T04:46:50","guid":{"rendered":"https:\/\/sites.temple.edu\/yangyang\/?page_id=1000442"},"modified":"2026-01-02T18:41:41","modified_gmt":"2026-01-02T23:41:41","slug":"econometric","status":"publish","type":"page","link":"https:\/\/sites.temple.edu\/yangyang\/econometric\/","title":{"rendered":"econometric"},"content":{"rendered":"\t\t
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Econometrics<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Why is this method important?\u00a0<\/b><\/div>
Econometric modeling is essential for establishing causal relationships, forecasting economic trends, and controlling for confounding variables in complex tourism systems. It allows researchers to move beyond simple correlations to understand the structural mechanisms driving phenomena such as hotel performance, regional growth, and inequality. Advanced econometric techniques, such as panel data models and structural equations, are critical for handling the hierarchical and dynamic nature of tourism data, enabling rigorous testing of economic theories, such as the tourism-led growth hypothesis and the Dutch disease effects.<\/span><\/div>
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What has our team done so far?\u00a0<\/b><\/div>
Our work demonstrates a sophisticated application of diverse econometric techniques to solve specific tourism problems. We have extensively utilized panel data models, specifically fixed-effects models, to control for unit-specific heterogeneity when analyzing the impact of COVID-19 government restrictions and the relationship between crime and hotel performance. To address endogeneity and simultaneity, we have employed Dynamic Stochastic General Equilibrium (DSGE) modeling to structurally investigate how tourism booms impact income and wealth inequality in small open economies. In the hospitality sector, we applied Stochastic Frontier Analysis (SFA) to measure hotel efficiency and productivity spillovers, and utilized the Hausman-Taylor model to estimate time-invariant location advantages. Additionally, we have applied mixed-effect ordered logit models to analyze discrete-choice data on hotel location satisfaction, allowing for the decomposition of variance across different levels of the data.<\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Recommendation <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Book Chapter:<\/p>

Econometric Analysis in Hospitality and Tourism Management<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Related Publications (click for all related publication)<\/a><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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