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Difference Equations and Stochastic Processes

In: Dynamic General Equilibrium Modeling

Author

Listed:
  • Burkhard Heer

    (University of Augsburg)

  • Alfred Maußner

    (University of Augsburg)

Abstract

Stochastic processes are an integral part of all models examined in Parts I and II of this book. Linear difference equations, the building blocks of (vector) autoregressive stochastic processes, are reviewed in the first part of the chapter. Subsequently, Heer and Maußner formally introduce readers to stochastic processes in discrete time, before analyzing Markov chains and techniques used to approximate continuously valued autoregressive processes via finite-state Markov chains. The final part of the chapter considers time series filters, which can help to extract stochastic trends from nonstationary stochastic processes.

Suggested Citation

  • Burkhard Heer & Alfred Maußner, 2024. "Difference Equations and Stochastic Processes," Springer Texts in Business and Economics, in: Dynamic General Equilibrium Modeling, edition 3, chapter 0, pages 847-869, Springer.
    • Handle: RePEc:spr:sptchp:978-3-031-51681-8_16
    DOI: 10.1007/978-3-031-51681-8_16
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