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Journal of Geographical Systems

Erschienen in:

01.01.2012 | Original Article

A space-time analysis of knowledge production

verfasst von: Olivier Parent

Erschienen in: Journal of Geographical Systems | Ausgabe 1/2012

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Abstract

Regional growth models often emphasize the importance of research and development activities leading to technological progress. The role of knowledge production and spatiotemporal spillover effects is investigated using a space-time panel data set covering 49 US states over the period 1994–2005. The aim is to test for the existence of regional knowledge spillovers in the context of a space-time dynamic suggested by the knowledge production function. A space-time specification is set forth that can be applied to panel data models that include random effects. We compare alternative models that have been proposed in the panel data literature to provide a better understanding of how new ideas diffuse across space and time. The results indicate that the space-time panel data set is consistent with the presence of strong spatiotemporal regional spillovers of knowledge. The empirical findings are interpreted in light of the existing theoretical and empirical literature on endogenous growth.

Vorheriger Artikel Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes

Nächster Artikel Separable spatial modeling of spillovers and disturbances

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We treat the District of Columbia as a state and use the 48 contiguous states, excluding Alaska and Hawaii.

We will use the term neighboring regions in a broad sense to reflect regions that exhibit both geographic as well as technological proximity throughout this paper. Details are provided regarding the empirical approach to mixing geographic and technological proximity later.

A set of exploratory and spatial modeling functionality with Matlab has been developed by Liu and LeSage (2010).

We do not use metropolitan areas because of the potential conflict with cities spread over different states.

Yearly data on patenting by geographic region, breakout by technology class over the period 1969–2007 are electronically published on the USPTO web site at http://www.uspto.gov/web/offices/ac/ido/oeip/taf/clsstca/stc_cl_gd.htm.

The spatial weight matrix is row normalized so that the maximum eigenvalue ψ_max is equal to one.

The average growth rate of patenting activities per capita over the last four decades (1970–2006) across the 49 states is equal to 0.022.

It might be plausible to argue that inventions have become more accessible in more recent years covered by our panel because of improved telecommunications and Internet data access.

Note that differences in the numerical values of the two criteria are explained by the fact that the marginal likelihoods are based on posterior ordinates that are smaller (in absolute value) than the prior ordinates.

As explained in Hsiao (2003), the stationary assumption can be relaxed for the first period if we assume the process began close to the observed initial period.

Data available at the U.S. Department of Commerce, U.S. Patent and Trademark Office. Patent Counts By Country/State And Year: Utility Patents: January 1, 1963–December 31, 2006

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Titel: A space-time analysis of knowledge production
verfasst von: Olivier Parent
Publikationsdatum: 01.01.2012
Verlag: Springer-Verlag
Erschienen in: Journal of Geographical Systems / Ausgabe 1/2012
Print ISSN: 1435-5930
Elektronische ISSN: 1435-5949
DOI: https://doi.org/10.1007/s10109-011-0151-y

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