Spatial determinants of U.S. FDI and exports in OECD countries

Boubacar, Inoussa

doi:10.1016/j.ecosys.2015.04.005

Cited by 16 publications

(7 citation statements)

References 42 publications

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“…Overall, studies analyzing causality report mixed results. For instance, Boubacar (2016) employs annual data on U.S. FDI to twenty-five OECD countries between 1999 and 2009. He uses spatial econometrics panel data techniques and finds a complex bidirectional causality between FDI and exports.…”

Section: Introductionmentioning

confidence: 99%

The Role of FDI on Exports Performance: Evidence from the Mexican States

Cabral

Alvarado

2020

International Regional Science Review

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This article examines manufacturing export determinants across Mexican states and regions from 2007 to 2015. Paying particular attention to the role of FDI, the analysis considers internal and external determinants of manufacturing exports under static and dynamic panel data methods. Several interesting results were obtained. First, the ratio of manufacturing to total GDP is the most consistent determinant of exports performance, regardless of the estimation method or specification employed. Second, static panel data estimations under GMM techniques suggest different sensitivity to FDI across regions, with the Mexico-U.S. border region observing the most substantial short-term effect of FDI on manufacturing exports. Finally, using dynamic panel data methods, we found significant persistence and similar long-term effects of FDI across most of the regions.

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Section: Introductionmentioning

confidence: 99%

The Role of FDI on Exports Performance: Evidence from the Mexican States

Cabral

Alvarado

2020

International Regional Science Review

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“…Contiguity variable: Given that, how to choose a spatial variable is very important in this model. Often, two spatial variables are used in spatial econometric studies: One of them is based on the proximity between the countries (Anselin and Arribas-Bel 2013;Birkelof 2010;Najafi Alamdarlo 2016), and the other one is based on the weight matrix of distance between the countries (Blonigen et al 2007;Boubacar 2015), but because of the characteristics of carbon dioxide emissions and water consumption in agricultural sector, the first method has been used. In proximity method, according to studies by Costantini et al (2013) and Germani et al (2014) the spatial variable (indicator) calculated.…”

Section: Resultsmentioning

confidence: 99%

Water consumption, agriculture value added and carbon dioxide emission in Iran, environmental Kuznets curve hypothesis

Alamdarlo

2016

Int. J. Environ. Sci. Technol.

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Agriculture and natural resources have a mutual relationship with each other. The purpose of this study was to evaluate forward and backward relationship between natural resources and agricultural development. The relationship between the consumption of water and agricultural value added per capita income has been studied in order to obtain the forward relationship, and the relationship between carbon dioxide emissions and per capita income of the Iran's agricultural sector has been assessed in order to obtain backward relationship. To test these relationships, the Kuznets theory is used. Therefore, Iran's provinces information from 2001 to 2013 was used and models were estimated by using the panel data and spatial econometric. Results showed that there was an inverted U relationship between per capita income and water consumption and carbon dioxide emissions. Also, spatial estimation showed that both water consumption and carbon dioxide (CO 2 ) emissions in agricultural sector had a direct relationship with the value of these two variables in the neighboring areas.

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“…The generalised spatial two-stage least-squares method (GS2SLS) can be used to deal with it (Ham et al, 2015). The spatial model is estimated based on the 2SLS method, which can control both spatial spillover effects and endogeneity problems (Boubacar, 2016). Therefore, this article uses GS2SLS for regression in Models 1 and 2 to address possible missing variables, measurement errors and bidirectional causality.…”

Section: Spatial Interaction Of Commercialisation Of Academic Patentsmentioning

confidence: 99%

Spatial Interactions and the Commercialisation of Academic Patents: The Chinese Experience

2022

Science, Technology and Society

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Studies on academic patent commercialisation are well documented. However, spatial effects are seldom considered, which could lead to potentially misleading analytical results. This study addresses this concern by applying the spatial analysis method to investigate how university-level factors and commercialising academic patents are related. Using a comprehensive dataset of university patents from 1815 Chinese universities in 2016, we find that public research funding of universities, industrial research funding, the number of scientific research personnel, the number of monographs published, and the number of awarded achievements are positively related to the commercialisation of academic patents. However, the number of teaching and research personnel and the number of academic papers published are negatively related. There are positive spatial spillover effects in commercialising academic patents among neighbouring universities, but there will be negative spatial spillover effects in funding competition.

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Spatial determinants of U.S. FDI and exports in OECD countries

Cited by 16 publications

References 42 publications

The Role of FDI on Exports Performance: Evidence from the Mexican States

The Role of FDI on Exports Performance: Evidence from the Mexican States

Water consumption, agriculture value added and carbon dioxide emission in Iran, environmental Kuznets curve hypothesis

Spatial Interactions and the Commercialisation of Academic Patents: The Chinese Experience

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