A Spatial Analysis of Creative Class Worker Growth Convergence in Us Counties (original) (raw)
Related papers
Spatial Analysis of Regional Productivity Based on Β-convergence Models
Montenegrin journal of economics, 2022
The convergence of productivity in the regions means their sustainable development and the protection of the national economy from external challenges. Accelerating digitalization of society expands the sphere of services and exacerbates the issue of measuring the productivity of the region's economy and the impact on it of internal knowledge factors (including innovations). The spatial heterogeneity of Russian regions, when identifying interrelationships, requires taking into account the spatial aspect. The main aim of the work is to assess the conditional β-convergence of the gross regional product per capita growth rates of the employed population and the impact of technological innovations on productivity in the regional economy on the basis of spatial-econometric models. Research hypotheses suggest that, spatial dependence contributes to the productivity growth rates convergence in the regional economy, technological innovations have a positive impact on productivity growth in the regional economy. The study uses Moran and Geary global spatial correlation indices, Moran local spatial correlation index, econometric model with spatial auto-regression lag, econometric model with spatial interaction in errors, maximum likelihood estimation. We revealed the spatial positive correlation of labor productivity, while the growth rates of real costs for technological innovations have a spatial negative correlation (strong regions "pull" innovations from weak neighbors). Authors didn't confirm the impact of the patents number for inventions and the use of the Internet in organizations on the growth rate of the gross regional product. Based on spatial-econometric models of panel data analysis, no β-convergence of productivity growth rates in the regions was found.
2006
The traditional view of cities as monocentric conglomerates of people clustered around an employment center, driving economic growth in cities that subsequently trickles down to the hinterland, is increasingly being challenged. In particular, the role of space, technological leadership, human capital, increasing returns to scale and industrial clustering as well as hierarchical organization principles have been emphasized in the more recent literature. This paper utilizes exploratory and spatial econometric data analysis techniques to investigate these issues for US counties using data from 1969 through 2003. Ultimately, contiguous and hierarchical organization and interaction patterns are captured using an endogenous growth model allowing for spatial effects, inspired by earlier work on human capital and technology gaps. We investigate a neoclassical growth model and compare it to a spatial version of an endogenous growth model allowing for "domestic" investment in human capital and catch-up to the technology leader, and find that human capital strongly contributes to growth in a neoclassical setting, but much less so in an endogenous setting. In the endogenous model the catch-up term dominates in comparison to "domestic" human capital effects.
Spatial Empirics for Economic Growth and Convergence
Geographical Analysis, 2010
This paper suggests some new empirical strategies for analyzing the evolution of regional income distributions over time and space. These approaches are based on extensions to the classical Markov transition matrices that allow f o r a more comprehensive analysis of the geographical dimensions of the transitional dynamics. This is achieved by integrating some recently developed local spatial statistics within a Markov framework. Insights to not only the frequency with which one economy m y transition across diferent classes in the income distribution, but also how those transitions m y or m y not be spatially dependent are provided by these new measures. A number of indices are suggested as ways to characterize the space-time dynamics and are illustrated in a case study of U. S. regional income dynamics over the 1929-1 994 period.
2018
Among the theories explaining the relationship between creativity criteria in cities and economic growth, “Human Capital Theory” by Glaeser and “Creative Class theory” by Florida can be mentioned. Accordingly, present paper aimed at analysis of the creativity effect on regional economic growth and is presented in two theoretical and experimental parts. Considering the results of the current paper, there are no studies within new economic geographical theory in which the creativity explicitly points out to the growth model. In this paper, such research gap is filled and a model is presented within a new economic geographical theory as a theoretical achievement. The growth model is solved as a numerical model through using calibration technique as well as required data and information of Iranian Economic. The results obtained from sensitivity analysis show that the relation between growth and creativity is positive and concave. The concave of this model shows that growth in ration of ...
US Regional Income Convergence: A Spatial Econometric Perspective
REY S. J. and M O NT O U RI B. D. (1999) U S regional income convergence: a spatial econometric perspective, Reg. Studies 33, 143± 156. This study reconsiders the question of U S regional economic income convergence from a spatial econometric perspective. Recently developed methods of exploratory spatial data analysis provide new insights on the geographical dynamics of U S regional income growth patterns over the 1929± 94 period. Strong patterns of both global and local spatial autocorrelation are found throughout the study period, and the magnitude of global spatial autocorrelation is also found to exhibit strong temporal co-movement with regional income dispersion. A spatial econometric analysis of the familiar Baumol speci® cation reveals strong evidence of misspeci® cation due to ignored spatial error dependence. Because of this dependence, shocks originating in one state can spillover into surrounding states, potentially complicating the transitional dynamics of the convergence process.
Modelling regional economic growth: the role of human capital and innovation
This thesis investigates the role of human capital and innovation activity in the process of economic growth within a system of regions. It starts by reviewing existing theories of economic growth paying particular attention to the literature on "endogenous growth", the large body of empirical literature addressing economic growth and that has investigated the "convergence issue". A methodology based on the direct analysis of cross-sectional distributions of per capita income is then developed and applied to per capita income data for 122 European Union (EU) functionally defined regions over the period 1979-1990. The results show a clear tendency for some of the richest European regions to grow away from the others. The comparison of these results with those derived from a similar analysis for the commonly used administrative regions of the EU reveals some significant distortions imposed by adopting an administrative definition. A formal theoretical explanation of these results is then offered. In particular, it is argued that regional disparities in per capita income owe their existence to the pattern of specialisation between 'knowledge creating' and 'knowledge applying' regions. Specialisation is explained in terms of differences in the availability of useful knowledge at different locations. In the perfect foresight, stable equilibrium of the two-region model developed here, therefore, the region that specialises in innovation related activities (knowledge creating) enjoys a permanently higher level of per capita income. Moreover, it is shown that, on reasonable assumptions, a process of integration that reduces the cost of physical distance leads to faster growth in the long-run for the system as a whole, but at the expense of an increase in regional disparities. 4 Finally, some predictions are derived and tested empirically. Using cross-sectional regressions, the fundamental determinants of the growth rate of a region are investigated. The results are supportive of the model, confirming the role played by the concentration of innovative activities and spatial spillovers of knowledge.
Sustainability, 2015
A question fundamental to sustainable economic growth is whether a poor region tends to grow faster than a rich one, such that the poor region catches up with the rich region in terms of the level of per capita income. In this article, we apply the spatial panel data approach to the analysis of regional income convergence across 177 economic areas in the contiguous US states over the period from 1969 to 2009. Using data on per capita incomes in the functionally defined economic areas, we find that the absolute value of the estimated coefficient of the initial per capita income decreases in the spatial and time-period fixed effects spatial lag model and increases in the spatial and time-period fixed effects spatial error model. This result implies that the growth rate in a specific economic area will be not only directly affected by an exogenous shock introduced into that economic area but also be impacted more by both the indirect effects of the first-order neighboring economic areas and the induced effects of the higher-order neighboring economic areas. This gives helpful hints on the issue of spatial interaction and regional policy coordination to start a virtuous circle of sustainable economic growth.
Growth and Convergence across the U.S.: Evidence from County-Level Data
Review of Economics and Statistics, 2006
We use U.S. county data (3,058 observations) and 41 conditioning variables to study growth and convergence. Using ordinary least squares (OLS) and three-stage least squares with instrumental variables (3SLS-IV), we report on the full sample and metro, nonmetro, and and regional samples: (1) OLS yields convergence rates around 2%; 3SLS yields 6%–8%; (2) convergence rates vary (for example, the Southern rate is 2.5 times the Northeastern rate); (3) federal, state, and local government negatively correlates with growth; (4) the relationship between educational attainment and growth is nonlinear; and (5) the finance, insurance, and real estate industry and the entertainment industry correlate positively with growth, whereas education employment correlates negatively.
Human capital, creative class and regional economic performance: A dynamic panel analysis
Though the measurement and implication of human capital on economic growth has been well established since the works of Becker in the 1960s, recently Florida has argued that creative class is superior to human capital in explaining economic growth. The underlying difference between the two scholars is a measurement approach in which while Becker uses education as indicator of human capital Florida employs occupation as an identifier of the creative class.
Regional disparities in the spatial correlation of state income growth, 1977–2002
Annals of Regional Science, 2007
This paper presents new evidence of spatial correlation in USA state income growth. We extend the basic spatial econometric model used in the growth literature by allowing spatial correlation in state income growth to vary across geographic regions. We find positive spatial correlation in income growth rates across neighboring states, but that the strength of this spatial correlation varies considerably by region. Spatial correlation in income growth is highest for states located in the Northeast and the South. Our findings have policy implications both at the state and national level, and also suggest that growth models may benefit from incorporating more complex forms of spatial correlation.