# Enhancing our understanding of short-term rental activity: A daily scrape-based approach for Airbnb listings

## TL;DR

This paper introduces a new method using daily data scraping to better understand Airbnb rental activity, especially during the UK's first COVID-19 lockdown.

## Contribution

The novel contribution is a systematic approach using daily calendar scrapes to measure Airbnb listing activity with greater detail and rigor.

## Key findings

- Daily scrapes of Airbnb calendars can reveal detailed patterns of listing activity.
- The method was validated during the UK’s first COVID-19 lockdown, showing its effectiveness in capturing market changes.
- The approach provides indicators that can help cities design and evaluate housing policies.

## Abstract

The growth of the online short-term rental market, facilitated by platforms such as Airbnb, has added to pressure on cities’ housing supply. Without detailed data on activity levels, it is difficult to design and evaluate appropriate policy interventions. Up until now, the data sources and methods used to derive activity measures have not provided the detail and rigour needed to robustly carry out these tasks. This paper demonstrates an approach based on daily scrapes of the calendars of Airbnb listings. We provide a systematic interpretation of types of calendar activity derived from these scrapes and define a set of indicators of listing activity levels. We exploit a unique period in short-term rental markets during the UK’s first COVID-19 lockdown to demonstrate the value of this approach.