scholarly journals TEMPORAL AND SPATIAL DEPENDENCE OF INTERREGIONAL RISK SHARING: EVIDENCE FROM RUSSIA

2019 ◽  
pp. 1-23
Author(s):  
Jarko Fidrmuc ◽  
Moritz Degler
Keyword(s):  
Spatial Dependence ◽  
Risk Sharing ◽  
Fixed Effects ◽  
Dynamic Properties ◽  
Spatial Models ◽  
Estimation Methods ◽  
Time Dynamic ◽  
Temporal And Spatial ◽  
Consumption Risk ◽  
Difference Gmm

We present an analysis of interregional consumption risk sharing in Russia between 1999 and 2009 using novel estimation methods. In addition to standard fixed-effects panel estimations, we use system and difference GMM estimators to reflect time dynamic properties and possible endogeneity between output and consumption. Furthermore, we apply spatial models that control for spatial dependence across regions. The results show that regional consumption deviations from the national average are highly persistent in time and space. Nevertheless, the regional consumption risk sharing in Russia is relatively high with 70%–90% of idiosyncratic risk being smoothed. Finally, fiscal policy and the degree of financial development appear to contribute to the consumption smoothing.

Does digital proximity between countries impact entrepreneurship?

Info ◽  
2015 ◽  
Vol 17 (5) ◽  
pp. 46-65 ◽  
Author(s):  
Maria Veronica Alderete
Keyword(s):  
Panel Data ◽  
Spatial Dependence ◽  
Fixed Effects ◽  
Spatial Models ◽  
Negative Influence ◽  
Entrepreneurial Activity ◽  
Spatial Effects ◽  
Content Type ◽  
Spatial Spillovers ◽  
Information And Communication

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.

scholarly journals Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 282
Author(s):  
Mabel Morales-Otero ◽  
Vicente Núñez-Antón
Keyword(s):  
Infant Mortality ◽  
Count Data ◽  
Spatial Dependence ◽  
Poisson Model ◽  
Mortality Rates ◽  
Estimation Methods ◽  
Neighborhood Structure ◽  
Specific Context ◽  
Count Data Models ◽  
Conditional Mean

In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag–York–Mollié (BYM) models. These overdispersed models assume that excess of dispersion in the data may be partially caused from the possible spatial dependence existing among the different spatial units. Thus, specific regression structures are then proposed both for the conditional mean and for the dispersion parameter in the models, including covariates, as well as an assumed spatial neighborhood structure. We focus on the case of response variables following a Poisson distribution, specifically concentrating on the spatial generalized conditional normal overdispersion Poisson model. Models were fitted by making use of the Markov Chain Monte Carlo (MCMC) and Integrated Nested Laplace Approximation (INLA) algorithms in the specific context of Bayesian estimation methods.

scholarly journals SPATIAL CONVERGENCE OF THE GROSS VALUE OF PRODUCTION OF FIREWOOD IN THE MESOREGIONS OF THE BRAZILIAN NORTHEAST

2018 ◽  
Vol 42 (2) ◽  
Author(s):  
Luiz Moreira Coelho Junior ◽  
Kalyne de Lourdes da Costa Martins ◽  
Magno Vamberto Batista da Silva
Keyword(s):  
Spatial Dependence ◽  
Classical Model ◽  
Spatial Models ◽  
Information Criterion ◽  
Spatial Error ◽  
Spatial Convergence ◽  
Spatial Autoregressive ◽  
Classical Linear Regression ◽  
Object Of Study ◽  
Brazilian Northeast

ABSTRACT This paper analyzed the process of convergence in the gross value of wood production in mesoregions of Northeast Brazil, in the period of 1994 and 2013. The object of study was the Gross Value of Production (GVP) of firewood per km2 of the mesoregions of the Northeast of Brazil. In the methodology the Absolute Convergence Model was applied and estimated through the classical model and spatial models. In the spatial approach we used the Spatial Autoregressive Model (SAR) and the Spatial Error Model (SEM). From the results obtained, the following conclusions were reached: The mesoregions of the Northeast of Brazil had an average fall of 3.94% a.a. of the GVP/km2 of native wood for the period 1994 to 2013. Considering the classical linear regression model, convergence was verified and also the presence of spatial dependence for GVP/km2 of firewood. In order to correct the spatial dependence, the SAR and SEM Models were adequate and according to Akaike's Information Criterion and used the rook matrix the SEM was configured the best model. This study showed the importance of the involvement of the spatial question in the models, either by the overlap of information of the GVP and in the development of public policies that positively affect the neighborhood.

scholarly journals Species richness and diversity in shrub savanna using ordinary kriging

2016 ◽  
Vol 51 (8) ◽  
pp. 958-966 ◽  
Author(s):  
Anderson Pedro Bernardina Batista ◽  
José Márcio de Mello ◽  
Marcel Régis Raimundo ◽  
Henrique Ferraço Scolforo ◽  
Aliny Aparecida dos Reis ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Species Richness ◽  
Spatial Dependence ◽  
Ordinary Kriging ◽  
Diversity Index ◽  
Spatial Models ◽  
Shannon Diversity Index ◽  
Shannon Diversity ◽  
Species Richness And Diversity ◽  
Number Of Species

Abstract: The objective of this work was to analyze the spatial distribution and the behavior of species richness and diversity in a shrub savanna fragment, in 2003 and 2014, using ordinary kriging, in the state of Minas Gerais, Brazil. In both evaluation years, the measurements were performed in a fragment with 236.85 hectares, in which individual trees were measured and identified across 40 plots (1,000 m2). Species richness was determined by the total number of species in each plot, and diversity by the Shannon diversity index. For the variogram study, spatial models were fitted and selected. Then, ordinary kriging was applied and the spatial distribution of the assessed variables was described. A strong spatial dependence was observed between species richness and diversity by the Shannon diversity index (<25% spatial dependence degree). Areas of low and high species diversity and richness were found in the shrub savanna fragment. Spatial distribution behavior shows relative stability regarding the number of species and the Shannon diversity index in the evaluated years.

scholarly journals Banks, Financial Markets and International Consumption Risk Sharing

2012 ◽  
Vol 13 (3) ◽  
pp. 331-351 ◽  
Author(s):  
Markus Leibrecht ◽  
Johann Scharler
Keyword(s):  
Financial Markets ◽  
Risk Sharing ◽  
Banking Sector ◽  
Financial System ◽  
International Diversification ◽  
Oecd Countries ◽  
Idiosyncratic Risk ◽  
Per Se ◽  
Consumption Risk

Abstract In this article, we explore how characteristics of the domestic financial system influence the international allocation of consumption risk in a sample of OECD countries. Our results show that the extent of risk sharing achieved does not depend on the overall development of the domestic financial system per se. Rather, it depends on how the financial system is organized. Countries characterized by developed financial markets are less exposed to idiosyncratic risk, whereas the development of the banking sector contributes little to the international diversification of consumption risk.

scholarly journals A Crook is a Crook . . . But is He Still a Crook Abroad? On the Effect of Immigration on Destination-Country Corruption

2015 ◽  
Vol 16 (4) ◽  
pp. 464-489 ◽  
Author(s):  
Eugen Dimant ◽  
Margarete Redlin ◽  
Tim Krieger
Keyword(s):  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Destination Country ◽  
Estimation Methods ◽  
Econometric Methodology ◽  
Migration Flows ◽  
The Difference ◽  
Method Of Moments Estimator ◽  
The Impact

AbstractThis paper analyzes the impact of migration on destination-country corruption levels. Capitalizing on a comprehensive dataset consisting of annual immigration stocks of OECD countries from 207 countries of origin for the period 1984-2008, we explore different channels through which corruption might migrate. We employ different estimation methods using fixed effects and Tobit regressions in order to validate our findings. Moreover, we also address the issue of endogeneity by using the Difference- Generalized Method of Moments estimator. Independent of the econometric methodology, we consistently find that while general migration has an insignificant effect on the destination country’s corruption level, immigration from corruption-ridden origin countries boosts corruption in the destination country. Our findings provide a more profound understanding of the socioeconomic implications associated with migration flows.

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