Airbnb Pricing in Sydney: Predictive Modelling and Explainable AI

22 Pages Posted: 25 Apr 2024

See all articles by George Milunovich

George Milunovich

Macquarie University - Department of Actuarial Studies and Business Analytics; Macquarie University, Macquarie Business School

Dom Nasrabadi

Macquarie University

Date Written: April 24, 2024

Abstract

We employ predictive models combined with explainable AI techniques to forecast and explain Airbnb rental prices in Sydney, Australia. Our models comprise a range of algorithms from simple linear regression to advanced ensemble methods. We also consider enriching the dataset by adding new variables constructed via feature engineering. We train the models on both the original and feature-engineered datasets and compared their performance using RMSE and MAE metrics. Further, we identify sets of ‘’superior’’ forecasting models with 90 percent confidence. Ensemble methods, particularly stacking regressions, are found to outperform other algorithms using both evaluation metrics, and on both the training and test datasets. In contrast, linear models perform rather poorly, indicating the presence of more complex relationships in the dataset. Shapley values analysis reveals that factors such as property capacity, proximity to popular locations and luxury amenities lead to higher rental price predictions.

Keywords: forecasting, AirBnb rental prices, machine learning, boosting, stacking, regression

JEL Classification: C53, C50

Suggested Citation

Milunovich, George and Nasrabadi, Dom, Airbnb Pricing in Sydney: Predictive Modelling and Explainable AI (April 24, 2024). Available at SSRN: https://ssrn.com/abstract=4805859 or http://dx.doi.org/10.2139/ssrn.4805859

George Milunovich (Contact Author)

Macquarie University - Department of Actuarial Studies and Business Analytics ( email )

Australia

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

Dom Nasrabadi

Macquarie University

North Ryde
Sydney, New South Wales 2109
Australia

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