Econometrics
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Benchmarks
BIG-bench
Most implemented
Multi-Paradigm Analysis of Thai Capital Market Linkages: Bivariate/Vine Copulas, Granger Causality, Network Centrality, and Graph Neural Network/Graph Embedding Approaches
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Global Public Sentiment on Decentralized Finance: A Spatiotemporal Analysis of Geo-tagged Tweets from 150 Countries
Convex Total Least Squares
Diffusion Factor Models: Generating High-Dimensional Returns with Factor Structure
When can we get away with using the two-way fixed effects regression?
Papers
Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond
Solving conditional moment restrictions (CMRs) is a key problem considered in statistics, causal inference, and econometrics, where the aim is to solve for a function of interest that satisfies some conditional moment eq…
Causal InferenceEconometricsEvaluating Large Language Model Capabilities in Assessing Spatial Econometrics Research
This paper investigates Large Language Models (LLMs) ability to assess the economic soundness and theoretical consistency of empirical findings in spatial econometrics. We created original and deliberately altered "count…
counterfactualEconometricsLanguage ModelingLanguage Modelling+1Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Can AI effectively perform complex econometric analysis traditionally requiring human expertise? This paper evaluates AI agents' capability to master econometrics, focusing on empirical analysis performance. We develop a…
AI AgentEconometricsBayesian Deep Learning for Discrete Choice
Discrete choice models (DCMs) are used to analyze individual decision-making in contexts such as transportation choices, political elections, and consumer preferences. DCMs play a central role in applied econometrics by …
Bayesian InferenceDeep LearningDiscrete Choice ModelsEconometrics+1Hierarchical Representations for Evolving Acyclic Vector Autoregressions (HEAVe)
Causal networks offer an intuitive framework to understand influence structures within time series systems. However, the presence of cycles can obscure dynamic relationships and hinder hierarchical analysis. These networ…
EconometricsTime SeriesCLT and Edgeworth Expansion for m-out-of-n Bootstrap Estimators of The Studentized Median
The m-out-of-n bootstrap, originally proposed by Bickel, Gotze, and Zwet (1992), approximates the distribution of a statistic by repeatedly drawing m subsamples (with m much smaller than n) without replacement from an or…
Econometrics