High oil prices are normally expected to stimulate exploration and the development of new oil and gas fields. But over the last few years, financial analysts have focused strongly on shortterm accounting return (RoACE) for benchmarking and valuation, and this has led to high capital discipline...

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...

This paper examines the effects of real estate transfer taxes (RETT) on property prices using a rich micro dataset of roughly 17 million German properties for the period from 2005 to 2019. We exploit a 2006 constitutional reform that allows states to set their own RETT rates, leading to frequent...

We review the recent literature on the determinants and effects of housing market expectations. We begin by providing an overview of existing surveys that elicit housing market expectations, and discuss how those surveys may be expanded in the future. We then document a number of facts about...

We study the effects of limited attention on property prices and energy efficiency (EE) investments in the housing market. Using a novel dataset, we analyse over 5 million residential property sale transactions in England and Wales, each containing information about sale price, property and...

Ownership of real estate through corporations in offshore tax havens creates opportunities for tax evasion and money laundering and may have undesirable effects in housing markets. In this paper, we study offshore ownership of real estate in the United Kingdom by combining several data sources:...

This paper investigates the US housing market from just before the Great Recession onward (2006-2019) and assesses the viability of stock-flow matching in generating the observed outcomes. The paper documents that the probability a house sells declines sharply after listing for two weeks....

In this paper we focus on estimating the degree of cross-sectional dependence in the error terms of a classical panel data regression model. For this purpose we propose an estimator of the exponent of cross-sectional dependence denoted by α; which is based on the number of non-zero pair-wise...