Economics

Empirical evidence shows that wealthy households have substantially higher saving rates and markedly lower marginal propensity to consume (MPC) than other groups. Existing theory cannot account for this pattern unless under restrictive…

Accurately forecasting Climate Policy Uncertainty (CPU) is essential for designing climate strategies that balance economic growth with environmental objectives. Elevated CPU levels can delay regulatory implementation, hinder investment in…

While electric vehicle (EV) adoption has been widely studied, most research focuses on the average effects of predictors on purchase intent, overlooking variation across the distribution of EV purchase intent. This paper makes a threefold…

This paper introduces a rule for policy selection in the presence of estimation uncertainty, explicitly accounting for estimation risk. The rule belongs to the class of risk-aware rules on the efficient decision frontier, characterized as…

What happens to pollution when developing countries open their borders to trade? Theoretical predictions are ambiguous, and empirical evidence remains limited. We study the effects of the 1991 Indian trade liberalization reform on water…

The long term estimation of the Marxist average rate of profit does not adhere to a theoretically grounded standard regarding which economic activities should or should not be included for such purposes, which is relevant because…

This paper investigates whether spatial proximity shapes psychological-pricing choices on Austria's C2C marketplace willhaben. Two web-scraped snapshots of 826 Woom Bike listings - a standardised product sold on the platform reveal that…

We revisit the identification of the conduct parameter in homogeneous goods markets. Lau (1982) argues that the conduct parameter is not identified if and only if the inverse demand function is separable, except for a specific separable…

Current AI systems are better than humans in some knowledge dimensions but weaker in others. Guided by the long-standing vision of machine intelligence inspired by the Turing Test, AI developers increasingly seek to eliminate this "jagged"…

When we interpret linear regression as estimating causal effects justified by quasi-experimental treatment variation, what do we mean? This paper formalizes a minimal criterion for quasi-experimental interpretation and characterizes its…

We develop a framework for composite likelihood estimation of parametric continuous-time stationary Gaussian processes. We derive the asymptotic theory of the associated maximum composite likelihood estimator. We implement our approach on a…

A new version of the database for the meta-analysis of estimates of the social cost of carbon is presented. New records were added, and new fields on gender and stochasticity.

This note discusses the interpretation of event-study plots produced by recent difference-in-differences methods. I show that even when specialized to the case of non-staggered treatment timing, the default plots produced by software for…

We develop a marginal treatment effect based method to learn about causal effects in multiple treatment models with discrete instruments. We allow selection into treatment to be governed by a general class of threshold crossing models that…

In this paper, we develop a novel large volatility matrix estimation procedure for analyzing global financial markets. Practitioners often use lower-frequency data, such as weekly or monthly returns, to address the issue of different…

We apply artificial neural networks (ANNs) to nowcast quarterly GDP growth for the U.S. economy. Using the monthly FRED-MD database, we compare the nowcasting performance of five different ANN architectures: the multilayer perceptron (MLP),…

We evaluate two interventions facilitating technology-sector transitions for women in Poland: Mentoring, focused on expanding professional networks, and Challenges, focused on building credible skill signals. Randomizing oversubscribed…

I propose a framework for learning individualized policy rules in observational data settings characterized by endogenous treatment selection and the availability of an instrumental variable. I introduce encouragement rules that manipulate…

The random values and volumes of consecutive trades made at the exchange with shares of security determine its mean, variance, and higher statistical moments. The volume weighted average price (VWAP) is the simplest example of such a…

Functional linear regression gets its popularity as a statistical tool to study the relationship between function-valued response and exogenous explanatory variables. However, in practice, it is hard to expect that the explanatory variables…