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Latent Variable Autoregression with Exogenous Inputs

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  • Daniil Bargman

Abstract

This paper introduces a new least squares regression methodology called (C)LARX: a (constrained) latent variable autoregressive model with exogenous inputs. Two additional contributions are made as a side effect: First, a new matrix operator is introduced for matrices and vectors with blocks along one dimension; Second, a new latent variable regression (LVR) framework is proposed for economics and finance. The empirical section examines how well the stock market predicts real economic activity in the United States. (C)LARX models outperform the baseline OLS specification in out-of-sample forecasts and offer novel analytical insights about the underlying functional relationship.

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  • Daniil Bargman, 2025. "Latent Variable Autoregression with Exogenous Inputs," Papers 2506.04488, arXiv.org, revised Jun 2025.
    • Handle: RePEc:arx:papers:2506.04488
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    1. Bai, Jushan & Ng, Serena, 2006. "Evaluating latent and observed factors in macroeconomics and finance," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 507-537.
    2. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    3. Vinod, H. D., 1976. "Canonical ridge and econometrics of joint production," Journal of Econometrics, Elsevier, vol. 4(2), pages 147-166, May.
    4. James H. Stock & Francesco Trebbi, 2003. "Retrospectives: Who Invented Instrumental Variable Regression?," Journal of Economic Perspectives, American Economic Association, vol. 17(3), pages 177-194, Summer.
    5. Raymond E. Owens & Pierre-Daniel G. Sarte, 2005. "How well do diffusion indexes capture business cycles? A spectral analysis," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 91(Fall), pages 23-42.
    6. Ball, Christopher & French, Jack, 2021. "Exploring what stock markets tell us about GDP in theory and practice," Research in Economics, Elsevier, vol. 75(4), pages 330-344.
    7. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
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