This dissertation collects empirical work in the field of fiscal and monetary policy, and their interaction. It comprises four chapters. In Chapter 1, I investigate the dynamic effects of tax changes on the cross-sectional distribution of disposable income in the US using a narrative identification approach. I distinguish between changes in personal and corporate income taxes and quantify the distributional effects on families and business owners. I document that tax changes affect incomes along the distribution differently and that the family status and the source of income matters. Tax reductions benefit high incomes and disadvantage lower incomes. Entrepreneurs and families benefit more from tax cuts than individuals without business income and non-families.
Chapter 2, also an application in fiscal policy, is a joint work with Alexander Kriwoluzky, Moritz Schularick, and Lucas ter Steege. It studies the most fateful austerity episode in history: Chancellor Brüning’s budget cuts and tax increases in Germany between 1930 and 1932. We introduce a new monthly dataset on German government finances and macroeconomic variables and employ narrative records to identify the causal effects of austerity. We show that Brüning’s belt-tightening aggravated the Great Depression. Without austerity, GDP would have been higher by 4.5 percent and unemployment down by 3.3 million people in 1932, a year with two crucial elections that eventually paved the way for Hitler.
Chapter 3, joint work with Alexander Kriwoluzky, contributes insights for empirically studying the causal effects of monetary policy. We determine the reliability and exogeneity of four popular monetary policy shock measures, namely the narrative series of Romer and Romer (2004), the high-frequency series of Barakchian and Crowe (2013), the high-frequency series of Gertler and Karadi (2015), and the hybrid series of Miranda-Agrippino and Ricco (2021). To this end, we employ the Proxy-SVAR model and different empirical diagnostic tools to determine the shock measures' information content. We find that the measure of Miranda-Agrippino and Ricco (2021), combining the insights from the narrative approach and high-frequency identification, outperforms the other three series.
Chapter 4, co-authored with Alexander Kriwoluzky, analyzes fiscal and monetary policy jointly by asking what role did US fiscal policy play during the Great Inflation. We estimate a DSGE model with three distinct monetary/fiscal policy regimes using a Sequential Monte Carlo (SMC) algorithm to evaluate the posterior distribution. In contrast to standard sampling algorithms, SMC enables us to determine the monetary/fiscal policy mix by sampling simultaneously from all regions of the parameter space, which makes comparing model fit across regimes unnecessary. A differentiated and novel perspective results: pre-Volcker macroeconomic dynamics were similarly driven by passive monetary/passive fiscal policy and fiscal dominance. Fiscal policy actions, especially government spending, were critical in the pre-Volcker inflation build-up.