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Weak and strong cross-sectional dependence: a panel data analysis of international technology diffusion

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  • Ertur, C.
  • Musolesi, A.

Abstract

This paper provides an econometric examination of geographic R&D spillovers among countries by focusing on the issue of cross-sectional dependence. By applying several unit root tests, we first show that when the number of lags of the autoregressive component of augmented Dickey Fuller test-type specifications or the number of common factors is estimated in a model selection framework, the variables (total factor productivity and R&D capital stocks) appear to be stationary. Then, we estimate the model using two complementary approaches, focusing on spatial autoregressive errors and unobserved common correlated factors. These approaches account for different types of cross-sectional dependence and are related to the concepts of weak and strong cross-sectional dependence recently developed in the literature.

Suggested Citation

  • Ertur, C. & Musolesi, A., 2013. "Weak and strong cross-sectional dependence: a panel data analysis of international technology diffusion," Working Papers 2013-09, Grenoble Applied Economics Laboratory (GAEL).
  • Handle: RePEc:gbl:wpaper:2013-09
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    Citations

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    Cited by:

    1. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    2. R. Golinelli & I. Mammi & A. Musolesi, 2018. "Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area," Working Papers wp1120, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. Antonio Musolesi & Michel Simioni & Georgios Gioldasis, 2018. "Nonparametric estimation of international R&D spillovers," Working Papers 2018037, University of Ferrara, Department of Economics.
    4. Diego-Ivan Ruge-Leiva, 2015. "International R&D Spillovers and other Unobserved Common Spillovers and Shocks," Papers 1502.06805, arXiv.org.
    5. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2018. "Nonparametric estimation of international R&D spillovers," SEEDS Working Papers 0318, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2018.
    6. Ruge-Leiva, Diego-Ivan, 2015. "The Online Supplement to “International R&D Spillovers and other Unobserved Common Spillovers and Shocks”," MPRA Paper 62205, University Library of Munich, Germany.
    7. Ruge Leiva, Diego Ivan, 2015. "International R&D Spillovers and other Unobserved Common Spillovers and Shocks," MPRA Paper 63500, University Library of Munich, Germany.
    8. repec:spr:epolit:v:34:y:2017:i:3:d:10.1007_s40888-017-0069-z is not listed on IDEAS

    More about this item

    Keywords

    PANEL DATA; CROSS-SECTIONAL CORRELATION; SPTIAL MODELs; FACTOR MODELS; UNIT ROOT; INTERNATIONAL TECHNOLOGY DIFFUSION; GEOGRAPHY;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F0 - International Economics - - General
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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