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June 1, 2026Tourism Economics0 citations

Estimating linear regression models for tourist length of stay using on-site and border samples

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ASAndreu SansóHealth Research Institute of the Balearic Islands

Key Points

  • This research aims to evaluate the consistency of linear regression estimators for tourist length of stay using different sample types.
  • Examined Ordinary Least Squares (OLS) estimation for on-site and border-point samples.
  • Applied Weighted Least Squares to address inconsistencies in on-site samples.
  • Analyzed the impact of OLS inconsistency on Accelerated Failure-Time (AFT) survival models.
  • OLS estimates from on-site samples showed inconsistency, while those from border-point samples were consistent.
  • Consistent estimates from on-site samples were achieved after applying Weighted Least Squares.
  • Inconsistent OLS estimates negatively affected survival models that utilize the AFT specification.

Abstract

This study examines the estimation of linear regression models for length of stay using on-site versus border-point samples. We show that Ordinary Least Squares (OLS) based on on-site samples is inconsistent, whereas OLS estimators from border-point samples are consistent. However, consistent estimates can be recovered from on-site samples by applying Weighted Least Squares. We also demonstrate that the inconsistency of OLS affects survival models that admit an Accelerated Failure-Time (AFT) specification. These findings challenge the validity of empirical studies relying on on-site samples and linear regression or survival models that admit an AFT formulation.

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Cite This Study

Andreu Sansó (2026) studied this question.

synapsesocial.com/papers/6a1d22db02fbce913063894ehttps://doi.org/10.1177/13548166261448325
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