Engelsk

In this paper an agent-based model is used to investigate how tightening loan-to-value and loan-to-income ratios affects house price cycles. The use of an agent-based model allows for the analysis of the effects of these policies on heterogeneous households. I find that these policies reduce house price cycles in a non-linear way that depends crucially on the distribution of households and highlights the importance of macroprudential policymakers taking into account the distributions of households.

I build a DSGE model where households face a loan-to-value (LTV) constraint and a debt-service-to-income (DTI) constraint. From an estimation of the model, I infer when each constraint was binding over the 1975-2017 timespan in the U.S. I also infer that DTI standards were relaxed during the mid-2000s credit boom. In the light of this, the boom could have been avoided by tighter DTI limits, but not by tighter LTV limits. The role of multiple credit constraints for the emergence of nonlinear dynamics is corroborated by county panel data.

Danmarks Nationalbank considers it positive that a new reference rate will be based on actual transactions rather than quoted prices, as the underlying transactions will enhance confidence in the reference rate. With the aim of clarification and of strengthening confidence in reference rates in Denmark, the new reference rate should be implemented rapidly, and the existing one should be phased out. It is essential that the sector now continues this work. Solutions still need to be found for reference rates for longer maturities and for migrating existing contracts from old to new reference rates. Such solutions should match international best practice.

Danish investors increased their outward direct in-vestments abroad by kr. 6.3 billion in the first quar-ter of 2019.

Kronos is Danmarks Nationalbank's payment system for large-value time-critical payments and it is the heart of the Danish financial infrastructure. The analysis assesses the robustness of the system, measured as the change in participants' liquidity needs as well as their ability to settle payments in a timely manner when the system is exposed to stress in three different scenarios: (1) One large participant cannot submit payments for a full business day, (2) the money market is inaccessible, and (3) the participants' access to intraday credit is reduced. The analysis shows that the system is resilient in all three scenarios.