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Carbon dioxide emissions have been commonly modelled as rising and falling with total output. Yet many factors, such as energy-efficiency improvements and shifts to cleaner energy, can break this relationship. We evaluate these factors using US data and find that changes in energy efficiency of consumption goods explain a significant proportion of emissions fluctuations. This finding also implies that models that omit energy efficiency likely overestimate the trade-off between environmental protection and economic performance.

In theory, nominal exchange rate movements can lead to “expenditure switching” when they generate changes in the relative prices of goods across countries. This paper explores whether the expenditure-switching role of exchange rates has changed in the current episode of significant global imbalances.

Should managers be paid in stock options if they provide stock-market participants with information about the firm? This paper studies how firm owners trade off the benefit of stock-price incentives and better-informed market participants against the cost of potential stock-price manipulation.

We introduce a new framework that facilitates term structure modeling with both positive interest rates and flexible time-series dynamics but that is also tractable, meaning amenable to quick and robust estimation.

Most models in finance assume that agents make trading plans over the infinite future. We consider instead that they are boundedly rational and may only form forecasts over a limited horizon.

This paper examines the implications of positive news about future asset values that turn out to be incorrect at a later date in an open economy model with banking. The model captures the patterns of bank credit and current account dynamics in Spain between 2000 and 2010. The model finds that the use of unconventional policies leads to a milder bust.

We estimate the effects of economic uncertainty on time use and discuss its macroeconomic implications. We develop a model to demonstrate that substitution between market and non-market work provides an additional insurance margin to households, weakening precautionary savings and labour supply and lowering aggregate demand, ultimately amplifying the contractionary effects of uncertainty.

We model non-bank entry into fixed-income markets and state-dependent liquidity. Non-bank financial institutions improve liquidity more during normal times than in stress. Banks may become less reliable to marginal clients, exacerbating the difference in liquidity between normal and stressed times. Central bank lending during stress may limit this harmful division.

Exporters frequently change their market destinations. This paper introduces a new approach to identifying the drivers of these decisions over time. Analysis of customs data from China and the UK shows most changes are driven by demand rather than supply-related shocks.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.