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Research Paper#Economics, Econometrics, Industrial Organization, Demand Estimation🔬 ResearchAnalyzed: Jan 3, 2026 19:06

Nonparametric Demand Identification Without Exogenous Characteristics

Published:Dec 29, 2025 05:19
1 min read
ArXiv

Analysis

This paper challenges the conventional wisdom that exogenous product characteristics are necessary for identifying differentiated product demand. It proposes a method using 'recentered instruments' that combines price shocks and endogenous characteristics, offering a potentially more flexible approach. The core contribution lies in demonstrating identification under weaker assumptions and introducing the 'faithfulness' condition, which is argued to be a technical, rather than economic, restriction. This could have significant implications for empirical work in industrial organization, allowing researchers to identify demand functions in situations where exogenous characteristic data is unavailable or unreliable.
Reference

“Price counterfactuals are nonparametrically identified by recentered instruments -- which combine exogenous shocks to prices with endogenous product characteristics -- under a weaker index restriction and a new condition we term faithfulness.”

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research#ai🔬 ResearchAnalyzed: Jan 4, 2026 06:49

Distributed Fusion Estimation with Protecting Exogenous Inputs

Published:Dec 28, 2025 12:53
1 min read
ArXiv

Analysis

This article likely presents research on a specific area of distributed estimation, focusing on how to handle external inputs (exogenous inputs) in a secure or robust manner. The title suggests a focus on both distributed systems and the protection of data or the estimation process from potentially unreliable or malicious external data sources. The use of 'fusion' implies combining data from multiple sources.

Key Takeaways

    Reference

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    Research Paper#Financial Forecasting, Time Series Analysis, Deep Learning🔬 ResearchAnalyzed: Jan 3, 2026 16:33

    Bitcoin Price Forecasting with Global Liquidity using TimeXer

    Published:Dec 26, 2025 15:36
    1 min read
    ArXiv

    Analysis

    This paper addresses the challenge of Bitcoin price volatility by incorporating global liquidity as an exogenous variable in a TimeXer model. The integration of macroeconomic factors, specifically aggregated M2 liquidity, is a novel approach that significantly improves long-horizon forecasting accuracy compared to traditional models and univariate TimeXer. The 89% improvement in MSE at a 70-day horizon is a strong indicator of the model's effectiveness.
    Reference

    “At a 70-day forecast horizon, the proposed TimeXer-Exog model achieves a mean squared error (MSE) 1.08e8, outperforming the univariate TimeXer baseline by over 89 percent.”

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    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 08:33

    Modeling gap acceptance behavior allowing for perceptual distortions and exogenous influences

    Published:Dec 24, 2025 12:06
    1 min read
    ArXiv

    Analysis

    This article describes research on modeling gap acceptance behavior, incorporating perceptual distortions and external factors. The focus is on understanding how individuals make decisions in situations involving gaps, likely in areas like traffic flow or decision-making under uncertainty. The inclusion of perceptual distortions suggests an awareness of cognitive biases and limitations in human perception. The mention of exogenous influences indicates consideration of external factors that might affect decision-making. The source, ArXiv, suggests this is a pre-print or research paper.

    Key Takeaways

      Reference

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      Research#Forecasting🔬 ResearchAnalyzed: Jan 10, 2026 11:57

      UrbanAI 2025 Challenge: Comparing AI Model Architectures for Temperature Forecasting

      Published:Dec 11, 2025 17:59
      1 min read
      ArXiv

      Analysis

      This article likely presents a comparison of linear and transformer models within the context of the UrbanAI 2025 challenge. The focus on long-horizon temperature forecasting highlights a practical application of AI in urban environments.
      Reference

      “The research focuses on long-horizon exogenous temperature forecasting.”

      PermalinkArXiv