We study the aggregate, distributional, and welfare effects of fiscal policy responses to Germany’s energy crisis arising in 2022 using a novel ten-agent New Keynesian (TENK) model. The crisis, compounded by the COVID-19 pandemic, led to sharp price increases and significant consumption disparities. Our model, calibrated to Germany’s income and consumption distribution, evaluates key policy interventions. We find that non-targeted transfers had the largest short-term aggregate impact, while targeted transfers for lower income households were more cost-effective. The energy cost brake and reductions in gas and oil taxes have shown very little effect, but were comparatively cost-effective under the assumption of exogenous prices. Our results highlight how targeted fiscal measures can address distributional effects and stabilize consumption during crises.

Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.

Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.

We document and dissect a new stylized fact about firm growth: the shift from labor to intermediate inputs. This shift occurs in input quantities, cost and output shares, and output elasticities. We establish this fact using German firm-level data and replicate it in administrative firm data from 11 additional countries. We also document these patterns in micro-aggregated industry data for 20 European countries (and, with respect to industry cost shares, for the US). We rationalize this novel regularity within a parsimonious model featuring (i) an elasticity of substitution between intermediates and labor that exceeds unity, and (ii) an increasing shadow price of labor relative to intermediates, due to monopsony power over labor or labor adjustment costs. The shift from labor to intermediates accounts for one half to one third of the decline in the labor share in growing firms (the remainder is due to wage markdowns and markups) and rationalizes most of the labor share decline in growing industries.

We document and dissect a new stylized fact about firm growth: the shift from labor to intermediate inputs. This shift occurs in input quantities, cost and output shares, and output elasticities. We establish this fact using German firm-level data and replicate it in administrative firm data from 11 additional countries. We also document these patterns in micro-aggregated industry data for 20 European countries (and, with respect to industry cost shares, for the US). We rationalize this novel regularity within a parsimonious model featuring (i) an elasticity of substitution between intermediates and labor that exceeds unity, and (ii) an increasing shadow price of labor relative to intermediates, due to monopsony power over labor or labor adjustment costs. The shift from labor to intermediates accounts for one half to one third of the decline in the labor share in growing firms (the remainder is due to wage markdowns and markups) and rationalizes most of the labor share decline in growing industries.

This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.