We study how and why local biodiversity affects residential property values. Leveraging remotely sensed greenness indicators and a novel dataset of granular property listings, we examine how changes in vegetation load on real estate prices. Hikes in greenness are associated with higher listing prices, fewer properties listed, and reduced liquidity in housing markets. These results suggest that price hikes in housing markets are driven by supply-side constraints instead of a “greenium” that buyers might be willing to pay due to innate preferences. Exogenous zoning shocks to foster biodiversity corroborate the presence of supply side constraints as price drivers in residential housing markets. Our findings emphasize the need to calibrate biodiversity and (social) housing policy objectives more explicitly.

Seit der Finanzkrise der Jahre 2007 und 2008 diskutiert die Wissenschaft darüber, wie Kreditgeber die Verbriefung von Hypotheken nutzen, um das Kreditrisiko an Dritte weiterzugeben, und wie dies zur Finanzkrise beigetragen hat. Eine aktuelle IWH-Studie betrachtet die Entscheidungssituation des Kreditgebers zwischen Risikoaufschlag und Risikoübertragung. Sie nutzt rechtliche Unterschiede in verschiedenen US-Bundesstaaten bei der Zwangsvollstreckung von Hypotheken, um daraus unterschiedliche regionale Kreditrisiken abzuleiten. Ist dieses regionale Risiko erhöht, reagieren Kreditgeber durch vermehrte Verbriefung, wenn Hypotheken zum Verkauf an halbstaatliche Agenturen (Government Sponsored Enterprises, GSE) wie Fannie Mae und Freddie Mac zugelassen sind und so gegen Ausfall versichert werden können. Bei Hypotheken, für die kein Rückkauf durch GSE infrage kommt, erhöhen die Kreditgeber dagegen die Zinsen, da sie das Kreditrisiko nicht an die Kreditkäufer weitergeben können.

The economy is a complex system because market participants do not act independently but adjust their behavior to other agents and to the outcome which emerges from their joint actions (Arthur, 2014). Dependencies among participants can impede policy makers capabilities to influence or steer the course of the economy. Kambhu et al. (2007) argue that to influence developments in financial markets, for instance to prevent crises from spreading, there are only “coarse or indirect options” available for policy makers. Similar to crises which propagate through a complex system, interventions might result in unintended side effects which can also disseminate through the system. Thus, in a complex system, unintended consequences of policy efforts may well be the rule. Policy makers try to ward off or mitigate negative consequences for the economy and society during periods of crisis. For instance, during the Covid crisis large scale support programs for firms in Western economies were set up to avoid bankruptcies. Similarly, during the sovereign debt crisis in the Eurozone, the European Central Bank (ECB) set up large scale asset purchase programs as well as additionally longer-term refinancing operations (LTRO) which provided immediate support to financial market participants’ liquidity positions and thereby prevented a melt-down of the financial system. During these periods, immediate and abundant liquidity supply is of utmost importance. Meanwhile, crisis measures, due to their massive scale and non-specific target group, may entail unknown or unintended side effects for instance on competition among market participants, firms’ investment behavior, or changes in lending strategies and risk taking behavior of banks. Likewise, new regulatory frameworks such as the introduction of new markets can have consequences previously not thought of. For policy makers it is important to know direct effects of policy interventions but also to be aware of the possibility and impact of indirect or unexpected side effects in order to evaluate measures taken and to learn for future design of regulation or intervention.

Prognosemodelle für die zukünftige wirtschaftliche Entwicklung verwenden häufig marktbasierte Indikatoren wie Spreads von Unternehmensanleihen, die den Risikoaufschlag gegenüber einem Referenzzins angeben. Anleihespreads bilden jedoch nur die Entwicklung von Risiken für Unternehmen ab, die regelmäßig Anleihen emittieren – im Durchschnitt größere, sichere Firmen. Neuartige Daten zu Bankkrediten, die im Sekundärmarkt gehandelt werden, erlauben auch die Konstruktion von Kreditspreads. Kreditmarktdaten umfassen ein breiteres Spektrum an Firmen, inklusive kleinerer Firmen, die stärker von Finanzmarktfriktionen betroffen sind. Tests zeigen, dass Kreditspreads tatsächlich mehr Informationen über wirtschaftliche Entwicklungen beinhalten als Anleihespreads und daher das Potenzial haben, Prognosemodelle zu verbessern.

By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.