We examine the effects of the big five personalities of CEOs (openness, conscientiousness, extroversion, agreeableness, and neuroticism) on their annual compensation. We hand-collect the tweets of S&P 1500 CEOs and use IBM's Watson Personality Insights to measure their personalities. CEOs with high ratings of agreeableness and conscientiousness get more compensation. We further find that the firms with these CEOs outperform their peers due to better investment efficiency. Firms are willing to pay higher compensation for talent, especially for firms with better operations, located in states with higher labor unionization, or facing higher competition in the product market. Overall, CEO personality is a valid predictor of CEOs' compensation.

We show an equivalence result in the standard 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 result arises if the price and wage Phillips curves' slopes are identical and generalizes to any pair of price and wage Phillips curve slopes such that their sum and product are identical. Nevertheless, the cyclical implications for profits and wages are substantially different. We discuss how the 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 in production. Lastly, we point to an econometric identification problem raised by our equivalence result and discuss possible solutions thereof.

This paper investigates the relationship between heterogeneity in sectoral price stickiness and the response of the economy to aggregate real shocks. We show that sectoral heterogeneity reduces inflation persistence for a constant average duration of price spells, and that inflation persistence can fall despite duration increases associated with increases in heterogeneity. We also find that sectoral heterogeneity reduces the persistence and volatility of interest rate and output gap for a constant price spells duration, while the qualitative impact on inflation volatility tends to be positive. A relevant policy implication is that neglecting price stickiness heterogeneity can impair the economic dynamics assessment.

Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.

We study the corporate-loan pricing decisions of a major, systemic bank during the Greek financial crisis. A unique aspect of our data set is that we observe both the actual interest rate and the “break-even rate” (BE rate) of each loan, as computed by the bank’s own loan-pricing department (in effect, the loan’s marginal cost). We document that low-BE-rate (safer) borrowers are charged significant markups, whereas high-BE-rate (riskier) borrowers are charged smaller and even negative markups. We rationalize this de facto cross-subsidization through the lens of a dynamic model featuring depressed collateral values, impaired capital-market access, and limit pricing.