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.

Banks play a special role in the financial system. According to classical banking theory, they help reduce informational asymmetries and serve as liquidity providers. Banks can, at least partially, lower transaction costs that result from information frictions between investors and firms and thereby alleviate firms’ funding constraints (Diamond, 1984). Moreover, banks create liquidity on their balance sheets by financing comparably illiquid assets with relatively liquid liabilities (Diamond and Dybvig, 1983). Integrating credit and liquidity provision functions, banks have been the object of numerous studies on financial intermediation. A particular focus in recent years has been on banks’ behavior as well as on the con- sequences of their actions for the real economy when hit by adverse shocks. Following the global financial crisis, financial shocks that originate from within the financial sec- tor have received wide attention (Cingano et al., 2016; Chodorow-Reich, 2014; Khwaja and Mian, 2008; Paravisini, 2008; Paravisini et al., 2015; Schnabl, 2012). However, banks are also subject to numerous non-financial shocks, which are the focus of this thesis.

A resolution of the missing deflation puzzle is proposed. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.

Labor is among the most crucial factors of production that maintain a firm's competitiveness. Given its economic importance, drivers of firms' labor investment policy have gained increasing attention in the financial economics literature. This study investigates the relation between stock liquidity and labor investment efficiency. We establish a causal relation between the two phenomena using an exogenous shock to liquidity: the 2001 decimalization of stock trading. We find that labor investment efficiency improves following an increase in stock liquidity, and the effect is prevalent in firms experiencing overinvestment in labor. Our findings further support the argument that stock liquidity improves the efficiency of labor investment by enhancing governance through shareholder exit threat.

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.