Beta coefficients are the cornerstone of asset pricing theory in the CAPM and multiple factor models. This chapter proposes a review of different time series models used to estimate static and time-varying betas, and a comparison on real data. The analysis is performed on the USA and developed...

The estimation of future sea level rise (SLR) is a major concern for cities near coastlines and river systems. Despite this, current modelling underestimates the future risks of SLR to property. Direct risks posed to property include inundation, loss of physical property and associated economic...

The global economic crisis and deep financialization processes recently suffered by the real estate market have exposed the latter to further and greater risks. Against this, the importance of real estate risk management has noticeably grown within the dynamics of both markets, real estate and...

We study bank credit booms, exploiting the Spanish matched credit register over 2001-2009. We extend Khwaja and Mian (2008)’s loan-level estimator by incorporating firm-level general equilibrium adjustments. Higher ex-ante bank real-estate exposure increases credit supply to non-real-estate...

Real estate markets are subject to dynamic, ever-changing influences from location, amenities and neighborhoods; regulation, zoning and population changes; but also - macroeconomic variables, such as interest rates, inflation and economic cycles. The decision to buy or rent a durable,...

Over the last years, the rise of sustainability and responsibility has drawn considerable attention by the entire society including businesses. Companies have integrated corporate social responsibility into their business model as a kind of self-regulation, and the way businesses invest has led...

Lending standards are a direct measure of credit conditions. We use the micro data merged from three separate sources to construct this measure and document that an uncertain macroeconomic outlook, rather than banks' balance sheet positions, was an important reason that a majority of banks...

This paper provides a synthesis of the state of knowledge on the economics of skyscrapers. First, we document how vertical urban growth has gained pace over the course of the 20th century. Second, we lay out a simple theoretical model of optimal building heights in a competitive market to...

This paper assesses to which degree housing purchase subsidies are capitalized into property prices. Using a large-scale micro data set on German house prices, I exploit the introduction of a new subsidy scheme in the state of Bavaria. My difference-indifference estimations at the Bavarian...

This book addresses challenges that new technologies and the big data revolution pose to existing regulatory and legal frameworks. The volume discusses issues such as blockchain and its implications for property transactions and taxes, three (or four) dimensional title registration, land use and...

Over the last years, the rise of sustainability and responsibility has drawn considerable attention by the entire society including businesses. Companies have integrated corporate social responsibility into their business model as a kind of self-regulation, and the way businesses invest has led...

Real estate markets are subject to dynamic, ever-changing influences from location, amenities and neighborhoods; regulation, zoning and population changes; but also - macroeconomic variables, such as interest rates, inflation and economic cycles. The decision to buy or rent a durable,...

Purpose The purpose of this paper is to investigate whether real estate investment trusts (REITs) have any significant cost-efficiency advantages over real estate operating companies (REOCs). Design/methodology/approach The data for listed companies were extracted from the Bloomberg terminal....

Farmland valuation models usually incorporate local purchasing power as one of the pricing factors. A plausible rationale is that a larger population and higher income per capita imply increasing demand for agricultural products and farmland. In this paper, we study the relationship between the...

This paper follows the recent literature on real estate price prediction and proposes to take advantage of machine learning techniques to better explain which variables are more important in describing the real estate market evolution. We apply the random forest algorithm on London real estate...

Overconfidence is one of the most robust behavioral anomalies in financial markets. By attributing investment gains to their ability, investors become overconfident and trade aggressively in subsequent periods. Evidence from stock markets shows that overconfidence leads to excessive trading and,...

Lending standards are a direct measure of credit conditions. We use the micro data merged from three separate sources to construct this measure and document that an uncertain macroeconomic outlook, rather than banks' balance sheet positions, was an important reason that a majority of banks...