Economics

This study explores how AI-powered digital innovations are reshaping organisational accountability in a transnational governance context. As AI systems increasingly mediate decision-making in domains such as auditing and financial…

Change orders (COs) are a common occurrence in construction projects, leading to increased costs and extended durations. Design-Bid-Build (DBB) projects, favored by state transportation agencies (STAs), often experience a higher frequency…

Seasonal migration plays a critical role in stabilizing rural economies and sustaining the livelihoods of agricultural households. Violence and civil conflict have long been thought to disrupt these labor flows, but this hypothesis has…

Several noteworthy scenarios emerged in the global textile and fashion supply chains during and after the COVID-19 pandemic. The destabilizing influences of a global pandemic and a geographically localized conflict are being acutely noticed…

Large language models (LLMs) are poised to significantly impact software development, especially in the Open-Source Software (OSS) sector. To understand this impact, we first outline the mechanisms through which LLMs may influence OSS…

In an empirical study of persuasion, researchers often use a binary instrument to encourage individuals to consume information and take some action. We show that, with a binary Imbens-Angrist instrumental variable model and the monotone…

This paper introduces a novel spatial interaction model to explore the decision-making processes of a resource allocator and local agents, with central and local governments serving as empirical representations. The model captures two key…

Software development relies on code reuse to minimize costs, creating vulnerability risks through dependencies with substantial economic impact, as seen in the Crowdstrike and HeartBleed incidents. We analyze 52,897 dependencies across…

This paper develops a novel approach to random effects estimation and individual-level forecasting in micropanels, targeting individual accuracy rather than aggregate performance. The conventional shrinkage methods used in the literature,…

With advances in estimating heterogeneous treatment effects, firms can personalize and target individuals at a granular level. However, feasibility constraints limit full personalization. In practice, firms choose segments of individuals…

We propose a weak-identification-robust test for linear instrumental variable (IV) regressions with high-dimensional instruments, whose number is allowed to exceed the sample size. In addition, our test is robust to general error…

We develop misspecification tests for building additive time-varying (ATV-)GARCH models. In the model, the volatility equation of the GARCH model is augmented by a deterministic time-varying intercept modeled as a linear combination of…

This paper introduces a novel Proxy-Enhanced Correlated Random Effects Double Machine Learning (P-CRE-DML) framework to estimate causal effects in panel data with non-linearities and unobserved heterogeneity. Combining Double Machine…

This paper introduces a novel Bayesian reverse unrestricted mixed-frequency model applied to a panel of nine European electricity markets. Our model analyzes the impact of daily fossil fuel prices and hourly renewable energy generation on…

This Policy Comment describes how the Food Policy article entitled 'Cost and affordability of nutritious diets at retail prices: Evidence from 177 countries' (first published October 2020) and 'Retail consumer price data reveal gaps and…

This paper contributes to the limited literature on the temperature sensitivity of residential energy demand on a global scale. Using a Bayesian Partial Pooling model, we estimate country-specific intercepts and slopes, focusing on…

For many economic questions, the empirical results are not interesting unless they are strong. For these questions, theorizing before the results are known is not always optimal. Instead, the optimal sequencing of theory and empirics trades…

This paper was prepared as a comment on "Dynamic Causal Effects in a Nonlinear World: the Good, the Bad, and the Ugly" by Michal Koles\'{a}r and Mikkel Plagborg-M{\o}ller. We make three comments, including a novel contribution to the…

External debt has been identified as the most liable to cause financial crises in developing countries in Asia and Latin America. One recent example of near bankruptcy in Sri Lanka has raised serious concerns among economists about how to…

We study a sequential social learning model in which there is uncertainty about the informativeness of a common signal-generating process. Rational agents arrive in order and make decisions based on the past actions of others and their…