Non-clearing goods markets are an important driver of capacity utilisation and total factor productivity (TFP). The trade-off between goods prices and household search effort is central to goods market matching and therefore drives TFP over the business cycle. In this paper, I develop a New-Keynesian DSGE model with capital utilisation, worker effort, and expand it with goods market search-and-matching (SaM) to model non-clearing goods markets. I conduct a horse-race between the different capacity utilisation channels using Bayesian estimation and capacity utilisation survey data. Models that include goods market SaM improve the data fit, while the capital utilisation and worker effort channels are rendered less important compared to the literature. It follows that TFP fluctuations increase for demand and goods market mismatch shocks, while they decrease for technology shocks. This pattern increases as goods market frictions increase and as prices become stickier. The paper shows the importance of non-clearing goods markets in explaining the difference between technology and TFP over the business cycle.

Die führenden Wirtschaftsforschungsinstitute senken ihre BIP-Wachstumsprognose für 2021 von 3,7 % auf 2,4 %. Dafür ist insbesondere die schwächelnde Industrieproduktion verantwortlich, die unter Lieferengpässen leidet. Die internationale Konjunktur erholt sich zwar von den Verwerfungen der Corona-Pandemie, aber nur langsam, da die Impffortschritte regional unterschiedlich sind. Die Verbraucherpreise haben sich 2021 stark erhöht.

We use the World Input–Output Database (WIOD) combined with regional sectoral employment data to estimate the potential regional employment effects of international trade barriers. We study the case of a no-deal Brexit in which imports to the United Kingdom (UK) from the European Union (EU) would be subject to tariffs and non-tariff trade costs. First, we derive the decline in UK final goods imports from the EU from industry-specific international trade elasticities, tariffs and non-tariff trade costs. Using input–output analysis, we estimate the potential output and employment effects for 56 industries and 43 countries on the national level. The absolute effects would be largest in big EU countries which have close trade relationships with the UK, such as Germany and France. However, there would also be large countries outside the EU which would be heavily affected via global value chains, such as China, for example. The relative effects (in percent of total employment) would be largest in Ireland followed by Belgium. In a second step, we split up the national effects on the NUTS-2 level for EU member states and additionally on the county (NUTS-3) level for Germany. The share of affected workers varies between 0.03% and 3.4% among European NUTS-2 regions and between 0.15% and 0.4% among German counties. A general result is that indirect effects via global value chains, i.e., trade in intermediate inputs, are more important than direct effects via final demand.

Das erste Jahr der Corona-Pandemie stand in Deutschland im Zeichen extremer Schwankungen der ökonomischen Aktivität und einer massiv gelähmten Binnenwirtschaft. In ihrem Frühjahrsgutachten gehen die Institute davon aus, dass der derzeitige Shutdown zunächst fortgesetzt und ab Mitte Mai bis zum Ende des dritten Quartals nach und nach aufgehoben wird. Im Zuge der Lockerungen wird sich vor allem der private Konsum kräftig erholen. Insgesamt dürfte das Bruttoinlandsprodukt in diesem Jahr um 3,7 % und im kommenden Jahr um 3,9 % zulegen.

Savings rates among European households have reached record levels during the Corona recession. We investigate three possible explanations for the increase in household savings: precautionary motivations induced by increased economic uncertainty, reduced consumption opportunities due to lockdown measures, and Ricardian Equivalence, i.e. increases in the expected future tax-burden of households driven by increases in government debt. To test these explanations, we compile a monthly panel of euro area countries from January 2019 to August 2020. Our findings indicate that the chief driver of the increase in household savings is supply: As governments restrict households’ opportunities to spend, households spend less. We estimate that going from no lockdown measures to that of Italy’s in March, would have resulted in the growth of Germany’s deposit to Gross Domestic Product (GDP) ratio being 0.6 percentage points higher each month. This would be equivalent to the volume of deposits increasing by roughly 14.3 billion euros or 348 euros per house monthly. Demand effects, driven by either fears of unemployment or fear of infection from COVID-19, appear to only have a weak impact on household savings, whereas changes in government debt are unrelated or even negatively related to savings rates. The analysis suggests that there is some pent-up demand for consumption that may unravel after lockdown measures are abolished and may result in a significant increase in consumption in the late spring/early summer 2021.

While the sovereign-bank loop literature has demonstrated the amplification between sovereign and bank risks in the Euro Area, its econometric identification is vulnerable to reverse causality and omitted variable biases. We address the loop's endogenous nature and isolate the direct bank-to-sovereign distress channel by exploiting the global, non-Eurozone related variation in banks’ stock prices. We instrument banking sector stock returns in the Eurozone with exposure-weighted stock market returns from non-Eurozone countries and take further precautions to remove Eurozone-related variation. We find that the transmission of instrumented bank distress to sovereign distress is around 50% smaller than the corresponding coefficient in the unadjusted OLS framework, confirming concerns on endogeneity. Despite the smaller relative magnitude, increasing instrumented bank distress is found to be an economically and statistically significant cause for rising sovereign fragility in the Eurozone.

When referring to the inflation trends over the last decade, economists speak of "puzzles": a “missing disinflation” puzzle in the aftermath of the Great Recession, and a ”missing inflation” one in the years of recovery to nowadays. To this, a specific "excess deflation" puzzle may be added during the post-crisis depression in the Euro Zone. The standard Phillips Curve model, in this context, has failed as the basic tool to produce reliable forecasts of future price developments, leading many scholars to consider this instrument to be no more adequate. The purpose of this paper is to contribute to this literature through the development of a newly specified Phillips Curve model, in which the inflation-expectation component is rationally related to the business cycle. The model is tested with the Euro Zone data 1999-2019 showing that inflation turns out to be consistently determined by output gaps and and experts' survey-based forecast errors, and that the puzzles can be explained by the interplay between these two variables.