Research

This project studies how macroeconomic uncertainty impacts the growth dynamics of financially constrained young firms. Using Swedish firm balance sheet data in a local projections setting, I document that high-potential firms (identified using ex ante characteristics of young firms with exceptional ex post growth rates) are the most responsive to uncertainty innovations, compared to established or other young continuing firms. I develop a heterogeneous-firm model with financial frictions to interpret these findings. High-potential firms rely heavily on external finance to scale their operation. When uncertainty rises, investors rebalance towards safe assets and firms postpone investment. Amplified by the financial channel, high-potential firms' response to uncertainty generates a decline in aggregate output and employment.

Stochastic asset price bubbles seem to be only part of the story. Endogenous bubbles can be optimal when they work to alleviate financial frictions and hurry assets towards an emergent technology. Too much, and the bubble bursts. This paper aims to study optimal bubble sustenance from innovating entrepreneurs in a heterogeneous assets model environment, and find optimal portfolio allocations using empirical cases studies.

Work by Canova and De Nicoló (2002) and Uhlig (2005) pioneered the sign restriction identification approach in Structural Vector Autoregression models. The assumption is that macroeconomic fundamentals can be exploited to infer which part of a comovement of macro time series and policy shocks is down to and information channel distortion. Increased awareness of this information channel can be exploited by the announcing authority, leading to a potential distortion of the identification.