Algorithms penetrate housing markets and have far-reaching effects on household well-being. We study algorithmic buyers (iBuyers) - through which platforms use algorithms to quickly value, buy, and sell homes - and their impact on housing affordability. Using millions of Zillow transaction data...

Multivariate Adaptive Regression Spline (MARS) is a simple and powerful non-parametric technique that automatizes the selection of non-linear terms in regression models. Non-linearities and spatial effects are natural characteristics in numerous spatial hedonic pricing models. In this paper, we...

Vehicle electrification plays a critical role in achieving a Net-Zero economy in the United States. Vehicle electrification relies on the deployment of energy infrastructure to overcome the barriers to wider adoption. Despite the rapid expansion of EV charging stations (EVCSs) in recent years,...

Housing prices are an important reflection of the economy, and housing price ranges are of great interest for both buyers and sellers. The goal of this paper is to empirically conduct the best machine learning regression model for Turkish Housing Market by comparing accuracy scores and absolute...

In this paper, I investigate how predictive algorithms change market outcomes in the housing market. By focusing on the effect of the Zestimate home valuation on housing markets, I investigate to what extent the market participants rely on the Zillow's estimated market value when making the...