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Generalized State-Dependent Models: A Multivariate Approach

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  • S. Heravi
  • J. Easaw
  • R. Golinelli

Abstract

The main purpose of this paper is to develop generalized State Dependent Models (SDM) in a multivariate framework for empirical analysis. This significantly extends the existing SDM which only allow univariate analysis following a simple AR process. The extended model enables greater possibility for empirical analysis of economic relationships. The principle advantage of SDM is that it allows for a general form of non-linearity and can be fitted without any specific prior assumption about the form of non-linearity. We describe the general structure of the SDM and the problem of its identification is also considered. Finally, we apply the algorithm to show the impact of sentiment and income when modelling US consumption.

Suggested Citation

  • S. Heravi & J. Easaw & R. Golinelli, 2016. "Generalized State-Dependent Models: A Multivariate Approach," Working Papers wp1067, Dipartimento Scienze Economiche, Universita' di Bologna.
    • Handle: RePEc:bol:bodewp:wp1067
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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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