Spatial spillovers in emerging market spreads

Dell’Erba, Salvatore; Baldacci, Emanuele; Poghosyan, Tigran

doi:10.1007/s00181-012-0644-7

Cited by 42 publications

(49 citation statements)

References 37 publications

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“…This model adds the lag dependent variable and the spatial lag of independent variables (Anselin, 1988). We choose this model because the dependencies in the spatial relationships take place both in the dependent and independent variables (Anselin, 1988;Brasington and Hite, 2005;Kissling and Carl, 2007;Dell'Erba et al, 2013). Compare to the SAR and Spatial Error Model (SEM) models, the SDM model achieves some advantages (LeSage and Pace, 2009).…”

Section: Methodsmentioning

confidence: 99%

Broadband adoption in Latin American countries: does geographic proximity matter?

Alderete

2019

RPD

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This paper analyzes whether geographic proximity among countries can be a significant factor in explaining fixed and mobile broadband adoption in Latin America. To address the research question if neighbor effects could impact on the broadband penetration of a country, we estimate a Spatial Durbin panel data model over the period 2011-2015, for 18 Latin American countries. Results obtained suggest a significant spatial effect of the broadband penetration. In particular, results show positive spatial effects for fixed broadband (confirming previous studies in Europe) but negative spatial effects for mobile broadband adoption.

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Section: Methodsmentioning

confidence: 99%

Broadband adoption in Latin American countries: does geographic proximity matter?

Alderete

2019

RPD

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“…We augment this otherwise standard LPM specification by including a spatial lag term widely used in the applications of spatial spillovers in regional studies of strategic government interactions (for a literature review, see Brueckner, 2003 andRevelli, 2005). Spatial models have also been used to analyse contagion in the financial markets (Dell'Erba, Baldacci, & Poghosyan, 2013;Kelejian, Prucha, & Yuzefovich, 2006). A key component of the spatial analysis is the coefficient of the spatial lag (ρ).…”

Section: Methodsmentioning

confidence: 99%

Cross‐country spillovers of fiscal consolidations in the euro area

Poghosyan

2019

International Finance

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This paper revisits the issue of cross‐country spillovers from fiscal consolidations using an innovative empirical methodology. We find evidence in support of fiscal spillovers in ten euro area countries. Fiscal consolidation in one country not only reduces domestic output (direct effect) but also reduces the output of other member countries (indirect/spillover effect). Fiscal spillovers are larger for (a) more closely located and economically integrated countries, and (b) fiscal shocks originating from relatively larger countries. On average, 1% of gross domestic product fiscal consolidation in ten euro area countries reduces the combined output by 0.6% on impact, out of which half is driven by indirect effects from fiscal spillovers. The impact peters out and becomes insignificant over the medium term. It is largely driven by tax measures, which have a relatively stronger effect on output compared to expenditure measures. The results are robust to alternative measures of bilateral links across countries.

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“…This model was developed because the dependencies in the spatial relationships not only occur in the dependent variable, but also in the independent variables (Anselin 1988, Brasington and Hite 2005, Kissling and Carl 2007Satolo and Bacchi, 2013;Dell'Erba et al, 2013). According to LeSage and Pace (2009), the SDM model has several advantages with respect to SAR and Spatial Error Model (SEM).…”

Section: As Stakhovych and Bijmoltmentioning

confidence: 99%

Does digital proximity between countries impact entrepreneurship?

Alderete

2015

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Purpose – This paper aims to determine if there is a spatial dependence in the entrepreneurial activity among countries. The existence of a “digital proximity” could explain the spatial pattern of entrepreneurship. Design/methodology/approach – This question is empirically addressed by using a five-period, 2008-2012, panel data for 35 countries. A spatial fixed effects panel data model is estimated by using the total entrepreneurial activity published by the global entrepreneurship monitor as the dependent variable. Findings – A significant negative influence of the digital proximity on the entrepreneurial activity is observed. Mobile broadband (MB) direct effect is positive while the indirect effect (the spatial spillovers) is negative, leading to a negative total effect on the total entrepreneurial activity. This result is contrary to non-spatial models’ results. Besides, a higher MB penetration in a country would lead to a competitive advantage fostering its opportunities for entrepreneurship, but reducing those of its neighbours’. Originality/value – This paper examines the relationship between information and communication technology (ICT) and entrepreneurship, by introducing the spatial effects is the main contribution. This paper expands the scant literature on the ICT impact on entrepreneurship. Results obtained support policies towards enforcing innovation, education and reducing entry regulations for encouraging entrepreneurship. Meanwhile, MB policies could counteract the entrepreneurial policies’ results due to the spatial dependence.

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Spatial spillovers in emerging market spreads

Cited by 42 publications

References 37 publications

Broadband adoption in Latin American countries: does geographic proximity matter?

Broadband adoption in Latin American countries: does geographic proximity matter?

Cross‐country spillovers of fiscal consolidations in the euro area

Does digital proximity between countries impact entrepreneurship?

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