Are there different local patterns of convergence concealed beneath the regional level? An analysis for US states and counties using a multilevel approach

Abstract

The extensive literature on economic convergence has explored a wide variety of ways of measuring convergence in addition to finely tuning and improving the applicable econometric techniques. However, very few contributions analyze the relevance of the spatial level of analysis. Our hypothesis is that studying the convergence at the level of large regions (states) could conceal intraregional heterogeneity. This hypothesis is consistent with the New Economic Geography framework, which highlighted core-periphery patterns at the local level. However, this polarization mechanism may become difficult to identify with aggregated data or neoclassical dynamics operating at the same time. This paper proposes a multilevel approach to study this question. It allows the identification of possible heterogeneous local patterns of behavior within regions. It is applied to the US economy in a hierarchy of two levels: states and counties. The results show high intraclass correlation, indicating significant variance within states. An overall pattern of convergence is observed in line with previous results, although some states present internal patterns of divergence or significant changes in the rate of convergence.

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Fig. 1

Notes

  1. 1.

    The period required to obtain half of the initial difference is given by \(e^{-{\lambda }T}=1/2\), where \(\lambda \), is the speed of convergence and T is the period of time. When the speed of convergence is 2%, \(T = \hbox {ln}(2)/0.02\sim 35\) years.

  2. 2.

    See the references to the so-called Modifiable Areal Unit Problem (MAUP), which explores the consequences of aggregate local information within larger regions: Gehlke and Biehl (1934), subsequently explained in detail by Openshaw and Taylor (1979) and Openshaw (1984).

  3. 3.

    The US economy presents important differences in specialization. Counties in the mid-west region—which is known for its rural sector—have a mean share of the farm income of 14.26%, whereas the rest of the country has a share of 8.56%.

  4. 4.

    Slopes of the conditional random slope model can be consulted in “Appendix”.

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Acknowledgements

Funding was provided by H2020 European Research Council (Grant No. UE-16-726950-IMAJINE); Secretaría de Estado de Investigación, Desarrollo e Innovación (Grant No. MINECO-13-ECO2013-48161-R); Dirección General de Investigación Científica y Técnica (Grant No. FPU Program).

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Correspondence to Fernando Rubiera Morollón.

Appendix

Appendix

See Table 4.

Table 4 Slopes and intercepts of the random intercept model

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Díaz Dapena, A., Rubiera Morollón, F. & Paredes Araya, D. Are there different local patterns of convergence concealed beneath the regional level? An analysis for US states and counties using a multilevel approach. Ann Reg Sci 58, 623–640 (2017). https://doi.org/10.1007/s00168-017-0811-z

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