We develop a model of a monocentric, oil-exporting city. The model predicts producer price and transportation cost effects of oil price changes on the house price gradient. Empirical findings support the predictions, with house price changes positively linked to the price of oil in cities...

Ride-hailing applications create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing or subsidizing ride-hailing applications, we extend a pseudo-monocentric city model to include multiple...

High-occupancy vehicle (HOV) lanes have been promoted to encourage carpools, reduce traffic congestion, and improve air quality. At the partial equilibrium level, commuting with three workers per automobile clearly reduces highway congestion, lowers carbon emissions, and saves energy compared to...

Transportation network companies (TNCs) create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing TNCs, we extend a pseudo-monocentric city model to include multiple endogenously chosen...

Biodiesel is one of the most important bioenergy products. But the feedstock is the bottleneck of its production. In order to mine potential feedstock from the natural resources, a wild survey was conducted in 10 provinces or cities of North China, and 952 seed samples, which came from 587...

Ride-hailing applications create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing or subsidizing ride-hailing applications, we extend a pseudo-monocentric city model to include multiple...

Ride-hailing applications create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing or subsidizing ride-hailing applications, we extend a pseudo-monocentric city model to include multiple...

This paper assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search-and-matching model illustrate that such indicators can be associated with subsequent...

This paper compares the performance of different forecasting models of California house prices. Multivariate, theory-driven models are able to outperform a theoretical time series models across a battery of forecast comparison measures. Error correction models were best able to predict the...

The major issue which we address in this paper is the one-size-fits-all nature of the typical city-level house price index. In this vein, we make two contributions. First, we develop a new algorithm to ensure feasible estimation of geographically granular repeat-sales house price indices in...