arXiv preprints from January 1, 2026 through September 5, 2026 — 08:17:24 EST
Forecasting is a central goal of time-series analysis. This review centers on three major developments in recent AI-based time-series forecasting: transformers, large pretrained models for zero-shot forecasting, and diffusion-based generative forecasters. We connect these methods to the econometric tradition built around the vector...
The paper investigates Bayesian Model Averaging and Selection (BMA/S) under non-standard stochastic assumptions, focusing on stochastic frontier analysis (SFA). We propose fast, reliable procedures for inference in the normal-exponential stochastic frontier model and examine whether accounting for asymmetric disturbances affects model...
We study the impact of external stimuli on attention in the Attentional Interference Model, capturing two opposing forces in consideration-set formation: proactive and retroactive interference. Proactive interference limits the permeation of external information, while retroactive interference displaces internally generated...
We propose a novel econometric methodology for Structural Vector Autoregressions with external instruments (`proxy-SVARs' or `SVAR-IVs') in panel data characterized by strong cross-sectional dependence, dynamic heterogeneity, and limited availability of direct external instruments for the shocks of interest. For each unit, we specify...
We develop a novel methodology for estimation and inference in high-dimensional panel network models with latent dual structures. The framework allows outcomes to be affected simultaneously by positive and negative interaction channels, accommodating settings in which some interactions reinforce outcomes while others generate...
This study introduces a novel framework to model cost overruns associated with four key stakeholders in nuclear power plant construction: equipment suppliers, construction subcontractors, the design and management team, and creditors. The framework estimates the share of overruns caused by each stakeholder and the share of overruns...
We study mixed bundling and competitive price-matching guarantees (PMGs) in a duopoly selling complementary products to heterogeneous customers. One retailer offers mixed bundling while the rival sells only a bundle. We characterize unique pure-strategy Nash equilibria across subgames and compare them to a no-bundling benchmark. Mixed...
We examine the new production function developed by Chilarescu, and prove that under certain restrictions, the values of the elasticity can also be less than one. We will also prove that under certain restrictions on the parameters, the production function satisfies the Inada conditions.
Generative AI is changing how software is produced and used. In vibe coding, an AI agent builds software by selecting and assembling open-source software (OSS), often without users directly reading documentation, reporting bugs, or otherwise engaging with maintainers. We study the equilibrium effects of vibe coding on the OSS...
We study optimal dynamic persuasion in a bandit experimentation model where a principal, unlike in standard settings, has a single-peaked preference over the agent's stopping time. This non-monotonic preference arises because maximizing the agent's effort is not always in the principal's best interest, as it may lead to a dead end....
This paper presents the Sequential Rationality Hypothesis, which argues that consumers are better able to make utility-maximizing decisions when products appear in sequential pairwise comparisons rather than in simultaneous multi-option displays. Although this involves higher cognitive costs than the all-at-once format, the current...
We estimate the national social cost of carbon using a recent meta-analysis of the total impact of climate change and a standard integrated assessment model. The average social cost of carbon closely follows per capita income, the national social cost of carbon the size of the population. The national social cost of carbon measures...
We study whether Fintech disrupts the banking sector by intensifying competition for scarce deposits funds and raising deposit rates. Using difference-in-difference estimation around the exogenous removal of marketplace platform investing restrictions by US states, we show the cost of deposits increase by approximately 11.5% within...
This paper provides causal evidence that temporary supply disruptions reshape firms' relationship portfolios in international trade. Using exogenous road disruptions during Colombia's 2010-11 La Niña episode, I identify exposure at the buyer-seller relationship level, exploiting variation within importers' supplier portfolios. Exposed...
How do authoritarian regimes strengthen global support for nondemocratic political systems? Roughly half of the users of the social media platform TikTok report getting news from social media influencers. Against this backdrop, authoritarian regimes have increasingly outsourced content creation to these influencers. To gain...
Using data on shootings in U.S.\ K--12 schools from 1981 to 2022, we estimate the effect of temperature on school shootings and assess climate-change impacts. We find that days with maximum temperatures above 90$^{\circ}$F increase school shooting incidence by approximately 90\% relative to days with maximum temperatures below...
I study the simplest model of revenue management with reusable resources: admission control of two customer classes into a loss queue. This model's long-run average collected reward has two natural upper bounds: the deterministic relaxation and the full-information offline problem. With these bounds, we can decompose the costs faced...
We investigate whether risk and time preferences differ when individuals make decisions for others compared to making decisions for themselves. We introduce a novel ``skin in the game'' experimental design, where choices for others incur a direct cost to the decision-maker, ensuring a genuine trade-off between self-interest and...
In this paper I derive a set of testable implications for econometric models defined by three assumptions: (i) the existence of strictly exogenous discrete instruments, (ii) restrictions on how the instruments affect adoption of a finite number of treatment types (such as monotonicity), and (iii) the assumption that the instruments...
Signaling is wasteful. But how wasteful? We study the fraction of surplus dissipated in a separating equilibrium. For isoelastic environments, this waste ratio has a simple formula: $β/(β+σ)$, where $β$ is the benefit elasticity (reward to higher perception) and $σ$ is the elasticity of higher types' relative cost advantage. The ratio...
The global food system has metamorphosed from a loose aggregation of bilateral exchanges into a highly intricate, interdependent Global Food Trade Network (FTN). This comprehensive review synthesizes the extant literature to examine the FTN through the rigorous lens of complex network science, moving beyond traditional economic trade...
This note presents two results. First, it shows that under mild conditions, a decision problem is quasi-concave if the set of optimal actions is convex under every belief. Second, it shows that if a decision problem is quasi-concave, then it satisfies the local single crossing property after relabeling the states.
These lecture notes provide a comprehensive introduction to Quantitative Methods in Finance (QMF), designed for graduate students in finance and economics with heterogeneous programming backgrounds. The material develops a unified toolkit combining probability theory, statistics, numerical methods, and empirical modeling, with a...
Liability sharing and staffing jointly determine service quality in AI-assisted online medical consultation, yet their interaction is rarely examined in an integrated framework linking contracts to congestion via physician responses. This paper develops a Stackelberg queueing model where the platform selects a liability share and a...
We inspect how accurate machine learning (ML) is at forecasting realized variance of the Dow Jones Industrial Average index constituents. We compare several ML algorithms, including regularization, regression trees, and neural networks, to multiple Heterogeneous AutoRegressive (HAR) models. ML is implemented with minimal...