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A Nonlinear Dynamic Factor Model for Financial and Macroeconomic Data

Author

Listed:
  • Pablo Guerron-Quintana

    (Boston College
    Boston College)

  • Alexey Khazanov

    (Hebrew University of Jerusalem)

  • Molin Zhong

    (Board of Governors of the Federal Reserve System)

Abstract

We propose a nonlinear dynamic factor model to examine the impact of external shocks and internal forces on macroeconomic and financial data fluctuations. This model permits nonlinear dynamics, enables asymmetric, state-dependent, and size- dependent responses to shocks, and generates time-varying volatility and asymmetric tail risk behavior. We find evidence of nonlinear dynamics in a U.S. application on measuring the credit cycle. The nonlinear factor stimulates credit growth during booms but hinders recovery after crises, with shocks having longer, amplified effects during credit crunches. An extended model that separates first- and second-order effects of the factor reveals that credit cycles exhibit state dependence in which shocks that spur growth during modest credit conditions trigger sharp busts during excessive expansions,thereby predicting how credit conditions can flip from boom to crisis.

Suggested Citation

  • Pablo Guerron-Quintana & Alexey Khazanov & Molin Zhong, 2026. "A Nonlinear Dynamic Factor Model for Financial and Macroeconomic Data," Boston College Working Papers in Economics 1106, Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:1106
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