We show an equivalence result in the representative-agent New-Keynesian model after demand, wage-markup and correlated price-markup and TFP shocks: assuming sticky prices and flexible wages yields identical allocations for GDP, consumption, labor, inflation and interest rates to the opposite case—flexible prices and sticky wages. This equivalence arises with identical price and wage Phillips-curve slopes and generalizes to any slopes' pair whose sum and product are identical. Equilibrium profits and wages are, however, substantially different; equivalence breaks when these factor-distributional implications matter for aggregate allocations, e.g. in New-Keynesian models with heterogeneous agents, endogenous firm entry, and non-constant returns to scale.

We study the procurement patterns of non-listed firms and examine how these often-overlooked, yet pivotal players in global supply chains adjust their sourcing when they anticipate accountability for externalities beyond their organizational boundaries. Using granular customs data and a surprise information release about the German Supply Chain Due Diligence Act, product-level regressions reveal that importing firms are 3.5 percentage points less likely to source a product from countries where the relevant production sector exhibits elevated ESG-related risks, suggesting that firms tend to cut ties with higher-risk suppliers. The effects are concentrated among firms with well-diversified supplier networks for a product and higher profitability, suggesting they have the necessary flexibility to respond quickly to anticipated regulatory pressure. Our findings suggest that mandates requiring firms to incorporate broad sustainability considerations into their operational decisions may have limits, particularly for non-listed firms.

The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.

Small and young businesses are essential for job creation, innovation, and economic growth. Even most of the superstar firms start their business life small and then grow over time. Small firms have less internal resources, which makes them more fragile and sensitive to macroeconomic conditions. This suggests the need for frequent and real-time monitoring of the small business sector’s health. Previously this was difficult due to a lack of appropriate data. This paper fills this important gap by developing a new Intuit QuickBooks Small Business Index that focuses on the smallest of small businesses with at most 9 workers in the US and the UK and at most 19 workers in Canada. The Index aggregates a sample of anonymous Quick- Books Online Payroll subscriber data (QBO Payroll sample) from 333,000 businesses in the US, 66,000 in Canada, and 25,000 in the UK. After comparing the QBO Payroll sample data to the official statistics, we remove the seasonal components and use a Flexible Least Squares method to calibrate the QBO Payroll sample data against official statistics. Finally, we use the estimated model and the QBO Payroll sample data to generate a near real-time index of economic activity. We show that the estimated model performs well both in-sample and out-of-sample. Additionally, we use this analysis for different regions and industries. Keywords: