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Growth, Cycles and Convergence in US Regional Time Series

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  • Vasco M.Carvalho
  • Andrew C.Harvey

Abstract

This article reports the results of fitting unobserved components (structural) time series models to data on real income per capita in eight regions of the United States. The aim is to establish stylised facts about cycles and convergence. A new model is developed in which convergence components are combined with a common trend and cycles. These convergence components are formulated as a second-order error correction mechanism which allows temporary divergence while imposing eventual convergence. This model is able to characterise the convergence patterns of all but the two richest US regions; these appear to have been diverging from the others in recent years. The use of unit root tests for testing convergence is critically assessed in the light of these results.

Suggested Citation

  • Vasco M.Carvalho & Andrew C.Harvey, 2002. "Growth, Cycles and Convergence in US Regional Time Series," Cambridge Working Papers in Economics 0221, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:0221
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    References listed on IDEAS

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    More about this item

    Keywords

    balanced growth; error correction mechanism; Kalman filter; signal extraction; unobserved components;
    All these keywords.

    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
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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