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Latent Variable Autoregression with Exogenous Inputs

Daniil Bargman

arXiv 4 Jun 2025 · Econometrics · publishedInternational Review of Economics & Finance (2026)

arXiv:2506.04488 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Eugene F. Fama and Kenneth R. French (1993) Common risk factors in the returns on stocks and bonds1.00063100%
2James H Stock and Mark W Watson (2002) Macroeconomic forecasting using diffusion indexes0.87472100%
3Jushan Bai and Serena Ng (2006) Evaluating latent and observed factors in macroeconomics and finance0.81142100%
4Seung C. Ahn, Stephan Dieckmann, and M. Fabricio Perez (2017) Is there a missing factor? a canonical correlation approach to factor models0.73732100%
5Clifford S. Asness, Tobias J. Moskowitz, and Lasse Heje Pedersen (2013) Value and momentum everywhere0.73732100%
6Alison J. Burnham, Roman Viveros, and John F. MacGregor (1996) Frameworks for latent variable multivariate regression0.73732100%
7Yining Dong and S. Joe Qin (2017) Dynamic latent variable analytics for process operations and control0.73732100%
8Christopher Ball and Jack French (2021) Exploring what stock markets tell us about gdp in theory and practice0.64441100%
9Arthur F Burns and Wesley C Mitchell (1946) Measuring business cycles0.64422100%
10H. Hotelling (1933) Analysis of a complex of statistical variables into principal components0.64422100%

Showing the top 10 of 60 scored citations.