Regional productivity variation and the impact of public capital stock: an analysis with spatial interaction, with reference to Spain

This paper contributes to the literature on regional productivity, complementing previous education and skill-level perspectives with a novel approach analysing the impact of regional skill gaps and skill shortages. This allows us to reflect the idiosyncratic needs of the regional economic structure better, considering both the demand and supply side of the skills equation in localised labour markets. Controlling for unobserved time-invariant firm-level heterogeneity and other region–industry effects across a longitudinal data set for the period 2008–2014, our analysis reveals a negative direct effect of skill shortages on firm productivity. We further find negative spillover effects for both skill gaps and skill shortages in related industries and proximate regions. Results are also shown to be heterogeneous with respect to agglomeration levels and industrial sectors. Stronger negative effects are found in industries defined by a knowledge-intensive skill base, pointing to the loss of learning effects in the presence of skill deficiencies. Conversely, agglomeration effects appear to moderate the impact of skill deficiencies through more efficient matching in the local labour market. The findings presented thus suggest that policies aimed at improving productivity and addressing the increasing regional productivity divide cannot be reduced to a simple space-neutral support for higher education and skill levels but need to recognise explicitly the presence and characteristics of place-specific skills gaps and shortages.

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International R&D Spillovers and Innovation Efficiency

Sustainability ◽

10.3390/su10113974 ◽

2018 ◽

Vol 10 (11) ◽

pp. 3974 ◽

Cited By ~ 9

Author(s):

Jianping Liu ◽

Kai Lu ◽

Shixiong Cheng

Keyword(s):

Capital Stock ◽

Stochastic Frontier Analysis ◽

Stochastic Frontier ◽

Sensitivity Analyses ◽

Frontier Analysis ◽

Country Level ◽

Scientific Papers ◽

Catch Up ◽

The Right ◽

The Impact

The objective of this study is to examine the impact of international research and development (R&D) spillovers on innovation efficiency of specific R&D outcomes, employing the country-level panel data for 44 countries in the 1996–2013 period. Fully considering the heterogeneity of different R&D outputs, scientific papers, PCT (Patent Cooperation Treaty) patents, US patents, and domestic patents are observed separately, which enriches the angles of measuring international R&D spillovers. By applying a stochastic frontier analysis to knowledge production function, we find that foreign R&D capital stock positively contributes to the innovation efficiency of scientific papers, but suppresses the productivity of domestic patents, whereas it does not really matter for PCT or US patents. These results are robust to control for a set of institutional factors and also in sensitivity analyses. Hence, dependence on international R&D spillovers seems neither to be the right way for emerging economies to catch up, nor to be a sustainable model for developing countries to fill the technical gap. Local R&D capital stock, instead, keeps an essential contributor to all four R&D outputs, so raising internal R&D expenditure is actually the key to improving innovation level and sustainable development ability.

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The Impact of Intangible Assets on Regional Productivity Disparities in Great Britain

Environment and Planning A Economy and Space ◽

10.1068/a46236 ◽

2014 ◽

Vol 46 (3) ◽

pp. 629-648 ◽

Cited By ~ 5

Author(s):

Konstantinos A Melachroinos ◽

Nigel Spence

Keyword(s):

Great Britain ◽

Intangible Assets ◽

Regional Productivity ◽

The Impact

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Public Capital and Innovation

Public Capital, Growth and Welfare ◽

10.23943/princeton/9780691155807.003.0005 ◽

2012 ◽

Author(s):

Pierre-Richard Agénor

Keyword(s):

Public Policy ◽

Public Capital ◽

Spillover Effects ◽

Critical Issue ◽

Government Interventions ◽

Trade Offs ◽

Different Types ◽

Innovation Capacity ◽

The Government ◽

The Impact

This chapter extends the Allais–Samuelson Overlapping Generations models presented in chapters 1 and 2 to study interactions between infrastructure and human capital with R&D activities and growth. It begins by providing some background evidence on these interactions. The model is then presented and solved, and the impact of public policy, including potential trade-offs associated with the provision of infrastructure and other services by the government, is discussed. Again, this is a critical issue; if governments have access to limited resources to cover their expenditure, different types of government interventions may entail (temporary or permanent) trade-offs at the macroeconomic level—even though at the microeconomic or sectoral level these interventions are largely complementary. In addition, different types of government intervention may generate spillover effects on other sectors, which may have an indirect impact on innovation capacity.

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The impact of cross-border commuters on occupational wages: Comparison of some nonparametric tests and their application to unemployment in Geneva

Journal of Income Distribution ◽

10.25071/1874-6322.19664 ◽

2014 ◽

Author(s):

Alberto Saez

Keyword(s):

Spatial Interaction ◽

Nonparametric Tests ◽

Wage Distribution ◽

The European Union ◽

Skilled Workers ◽

Cross Border ◽

Free Mobility ◽

Bilateral Agreement ◽

Unemployment Data ◽

The Impact

The bilateral treaty on free mobility between the European Union and Switzerland has adversely affected native private sector low-skilled workers in the lower range of the earnings distribution. If cross-border commuters’ wages are prioritised over the local wages, the (pre-bilateral agreement) wage distribution between cross-border employees and local ones will intersect. This paper considers the statistical methods that can be used to test for this form of spatial interaction affecting the evolution of regional unemployment. Numerical simulations suggest that recently developed tests for distribution-crossing are powerful even when the two distributions under study are fairly similar, and that these tests can be usefully combined with more standard quantile tests to characterise unskilled occupational wages at the bottom. We apply this approach to unemployment data in Geneva and find that workforce participation among the local low-skilled workers was lower than that of low-qualified cross-border commuters.

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Identifying Urban Traveling Hotspots Using an Interaction-Based Spatio-Temporal Data Field and Trajectory Data: A Case Study within the Sixth Ring Road of Beijing

Sustainability ◽

10.3390/su12229662 ◽

2020 ◽

Vol 12 (22) ◽

pp. 9662 ◽

Cited By ~ 1

Author(s):

Disheng Yi ◽

Yusi Liu ◽

Jiahui Qin ◽

Jing Zhang

Keyword(s):

Traffic Management ◽

Spatial Clustering ◽

Spatial Interaction ◽

The Other ◽

Temporal Data ◽

Trajectory Data ◽

Data Field ◽

Spatio Temporal ◽

The Impact

Exploring urban travelling hotspots has become a popular trend in geographic research in recent years. Their identification involved the idea of spatial autocorrelation and spatial clustering based on density in the previous research. However, there are some limitations to them, including the unremarkable results and the determination of various parameters. At the same time, none of them reflect the influences of their neighbors. Therefore, we used the concept of the data field and improved it with the impact of spatial interaction to solve those problems in this study. First of all, an interaction-based spatio-temporal data field identification for urban hotspots has been built. Then, the urban travelling hotspots of Beijing on weekdays and weekends are identified in six different periods. The detected hotspots are passed through qualitative and quantitative evaluations and compared with the other two methods. The results show that our method could discover more accurate hotspots than the other two methods. The spatio-temporal distributions of hotspots fit commuting activities, business activities, and nightlife activities on weekdays, and the hotspots discovered at weekends depict the entertainment activities of residents. Finally, we further discuss the spatial structures of urban hotspots in a particular period (09:00–12:00) as an example. It reflects the strong regularity of human travelling on weekdays, while human activities are more varied on weekends. Overall, this work has a certain theoretical and practical value for urban planning and traffic management.

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