Marc Francke

How do pandemics affect urban housing markets? This paper studies historical outbreaks of the plague in 17th-century Amsterdam and cholera in 19th-century Paris to answer this question.

The general purpose of a dynamic factor model (DFM) is to summarize a large number of time series into a few common factors. In this paper Alex van de Minne, Marc Francke and David Geltner explore several DFMs on 80 granular, non-overlapping commercial property price indexes in the US, quarterly from 2001Q1 to 2017Q2.

In this paper Dorinth van Dijk and Marc Francke examine co-movements in private commercial real estate index returns and market liquidity in the US (apartment, office, retail) and for eighteen global cities, using data from Real Capital Analytics over the period 2005–2018.

We present a mixed frequency repeat sales model for commercial real estate, taking into account changes in net operating income between the date of buying and selling the property. Moreover, we relate monthly private market index asset returns to lags, up to 1 year, of daily (REIT) index returns.

This article presents a model agnostic methodology for producing property price indices. The motivation to develop this methodology is to include non-linear and non-parametric models, such as Machine Learning (ML), in the pool of algorithms to produce price indices.

How do pandemics affect urban housing markets? This paper studies historical outbreaks of the plague in 17th-century Amsterdam and cholera in 19th-century Paris to answer this question.

The general purpose of a dynamic factor model (DFM) is to summarize a large number of time series into a few common factors. In this paper Alex van de Minne, Marc Francke and David Geltner explore several DFMs on 80 granular, non-overlapping commercial property price indexes in the US, quarterly from 2001Q1 to 2017Q2.

In this paper Dorinth van Dijk and Marc Francke examine co-movements in private commercial real estate index returns and market liquidity in the US (apartment, office, retail) and for eighteen global cities, using data from Real Capital Analytics over the period 2005–2018.