I agree that it seems to be a pretty poor paper. >They even acknowledge that the correlation could be due to a factor that isn't being accounted for. Related

I agree that it seems to be a pretty poor paper. >They even acknowledge that the correlation could be due to a factor that isn't being accounted for. Related to this, they're performing a regression between Airbnb prevalence and crime, but they only control for a single variable: income[0]. They look at others in a robustness check, but a single control variable practically screams p-hacking. They also don't address the fact that both Airbnb prevalence and crime are nonstationary[1]. Regressing two nonstationary time series results in a nonsense coefficient[2]. Two totally unrelated time series will have a high coefficient if both exhibit consistent trends. [0] "We report the results based on using income as the main tract-level control variable" [1] They are consistent trends over time, see https://www.investopedia.com/articles/trading/07/stationary.asp https://www.investopedia.com/articles/trading/07/stationary.... [2] https://stats.stackexchange.com/questions/94723/using-non-stationary-time-series-data-in-ols-regression https://stats.stackexchange.com/questions/94723/using-non-st...