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...

Family ties and kinship networks play an important role in sharing risk under unanticipated shocks, especially under insufficient social security. In this paper, we use panel data based on a massive household survey to examine the risk-sharing networks and their heterogeneous impacts on...

This paper investigates the impact of offspring’s uncertainty on intergenerational decisions. We exploit the experiment of the national college entrance examination (NCEE) reform in China, which increases the income uncertainty of households with compulsory education students. Based on...

Employing an agent-based model of the Spanish housing market, this paper explores the main drivers behind the large amplitude of the Spanish house price cycle —as compared to most other European countries—, as well as the scope for macroprudential policy to reduce this amplitude. First, we...

The aim of this paper is to empirically identify the state of the US housing market and to set state-dependent policy rules to smooth the housing cycle. I do so by estimating a three-state Markov-switching model of housing prices in which mortgage debt is the state-dependent variable. As a...

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...

I show that home ownership decisions across countries and individuals are shaped by a cultural heritage from agriculture. For centuries, dominant assets in pre-industrial economies were either land or cattle. Consequently, the type of farming prevailing locally shaped preferences and believes...

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...

We analyze the impact of the introduction of a Loan-to-Value (LTV) limit in The Netherlands on the probability for first time buyers to become homeowner using a duration model. Our research design is underpinned by a theoretical model that shows that a lower LTV limit results in suspending or...

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...