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Determinants of transition in artificially discrete Markov chains using microdata

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  • Vassilopoulos, Achilleas
  • Klonaris, Stathis

Abstract

We describe an econometric procedure to model transitions in Markov chains whose state space is finite and classification stems from observed continuous variables. We show how stationary and non-stationary transition probabilities as well as the marginal effects of continuous and dichotomous variables determining transition can be estimated. The model resembles the ordered probit approach used in Epstein et al. (2006) but allows for the differences in the nature of the dependent variable and suggests some very important extensions pertaining to more meaningful representation of parameter estimates and the simultaneous construction of transition matrices.

Suggested Citation

  • Vassilopoulos, Achilleas & Klonaris, Stathis, 2016. "Determinants of transition in artificially discrete Markov chains using microdata," Economics Letters, Elsevier, vol. 146(C), pages 17-20.
    • Handle: RePEc:eee:ecolet:v:146:y:2016:i:c:p:17-20
    DOI: 10.1016/j.econlet.2016.07.018
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    References listed on IDEAS

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    1. Greene, William, 2010. "Testing hypotheses about interaction terms in nonlinear models," Economics Letters, Elsevier, vol. 107(2), pages 291-296, May.
    2. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, July.
    3. Andrew Hodge & Sriram Shankar, 2014. "Partial Effects in Ordered Response Models with Factor Variables," Econometric Reviews, Taylor & Francis Journals, vol. 33(8), pages 854-868, November.
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