We study changes in business dynamism in Europe after 2000 using novel micro-aggregated data that we collected for 19 European countries. In all countries, we document a broad-based decline in job reallocation rates that concerns most economic sectors and size classes. This decline is mainly driven by dynamics within sectors, size, and age classes rather than by compositional changes. Large and mature firms experience the strongest decline in job reallocation rates. Simultaneously, the employment shares of young firms decline. Consistent with US evidence, firms’ employment has become less responsive to productivity shocks. However, the dispersion of firms’ productivity shocks has decreased too. To enhance our understanding of these patterns, we derive and apply a novel firm-level framework that relates changes in firms’ sales, market power, wages, and production technology to firms’ responsiveness and job reallocation.

This paper derives a European Herfindahl–Hirschman concentration index from 15 micro-aggregated country datasets. In the last decade, European concentration rose due to a reallocation of economic activity toward large and concentrated industries. Over the same period, productivity gains from an increasing allocative efficiency of the European market accounted for 50% of European productivity growth while markups stayed constant. Using country-industry variation, we show that changes in concentration are positively associated with changes in productivity and allocative efficiency. This holds across most sectors and countries and supports the notion that rising concentration in Europe reflects a more efficient market environment rather than weak competition and rising market power.

The international co-movement of interest rates reflects correlated business-cycle fluctuations, largely driven by demand shocks. Monetary policy in advanced economies follows domestic mandates – inflation and the output gap – and does not respond to foreign policy shocks. We derive this result from a Bayesian structural panel vector autoregression with informative priors, homogeneity restrictions on contemporaneous relations, a hierarchical Minnesota prior with cross-sectional shrinkage, and a factor structure for structural shocks.

Bitcoin plunged by 30% on May 19, 2021. We examine the outage the largest crypto exchange Binance experienced during the crash, when it halted trading for retail clients and stopped providing transaction data. We find evidence that Binance back-filled these missing transactions with data that does not conform to Benford‘s Law. The Bitcoin futures price difference between Binance and other exchanges was seven times larger during the crash period compared to a prior reference period. Data manipulation is a plausible explanation for our findings. These actions are in line with Binance aiming to limit losses for its futures-related insurance fund.

Asset prices are a valuable source of information about financial market participants' expectations about key macroeconomic variables. However, the presence of time-varying risk premia requires an adjustment of market prices to obtain the market's rational assessment of future price and policy developments. This paper reviews empirical approaches for recovering market-based expectations. It starts by laying out the two canonical modeling frameworks that form the backbone for estimating risk premia and highlights the proliferation of risk pricing factors that result in a wide range of different asset-price-based expectation measures. It then describes a key methodological innovation to evaluate the empirical plausibility of risk premium estimates and to identify the most accurate market-based expectation measure. The usefulness of this general approach is illustrated for price expectations in the global oil market. Then, the paper provides an overview of the body of empirical evidence for monetary policy and inflation expectations with a special emphasis on market-specific characteristics that complicate the quest for the best possible market-based expectation measure. Finally, it discusses a number of economic applications where market expectations play a key role for evaluating economic models, guiding policy analysis, and deriving shock measures.

This paper analyzes how firm-specific forecast errors derived from survey data of German manufacturing firms over 2007–2011 relate to firms' investment propensity. Our findings reveal that asymmetries arise depending on the size and direction of the forecast error. The investment propensity declines if the realized situation is worse than expected. However, firms do not adjust investment if the realized situation is better than expected suggesting that the uncertainty component of the forecast error counteracts good surprises of unexpectedly favorable business conditions. This asymmetric mechanism can be one explanation behind slow recovery following crises.

I derive a micro-founded framework showing how rising firm market power on product and labor markets and falling aggregate labor output elasticities provide three competing explanations for falling labor shares. I apply my framework to 20 years of German manufacturing sector micro data containing firm-specific price information to study these three distinct drivers of declining labor shares. I document a severe increase in firms’ labor market power, whereas firms’ product market power stayed comparably low. Changes in firm market power and a falling aggregate labor output elasticity each account for one half of the decline in labor's share.