The trend towards convergence in road accident fatality rates in Europe: The contributions of non-economic variables

Castillo-Manzano, José I.; Castro‐Nuño, Mercedes; Pedregal, Diego J.

doi:10.1016/j.tranpol.2014.05.021

Cited by 15 publications

(3 citation statements)

References 54 publications

(60 reference statements)

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“…At the same time, Royuela and Artis (2006), Higgins et al. (2008), Castillo-Manzano et al. (2014) and Dvorsky et al.…”

Section: Introductionmentioning

confidence: 92%

“…This may indicate that there is no convergence of food price inflation worldwide. At the same time, Royuela and Artis (2006), Higgins et al (2008), Castillo-Manzano et al (2014) and Dvorsky et al (2021) studied groups of countries which share similar economic conditions and social environment and observed some economic variables convergence among some in these countries. From country level data, there is ample evidence on income convergence (Dawson and Sen, 2007;Stanisic et al, 2018;Hembram and Haldar, 2021;Malc et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Food price inflation convergence: an international study from 2000–2020

Fan

Wang

et al. 2022

BFJ

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PurposeThe purpose of this paper is to investigate the food price inflation convergence across countries and regions. This study aims to identify the key drivers for food price inflation across countries and regions.Design/methodology/approachWe test whether the international food price inflations are converging over time using the log t convergence test and clustering analysis. These inflation data are collected from the Food and Agriculture Organization of the United Nations.FindingsThe test results suggest that there is little evidence of overall convergence. Then we utilize a clustering algorithm and the results support that there is strong evidence of multiple convergence clubs. In addition, we examine the transition path of the various convergence and find that social stability regulation together with economic conditions are important determinants of convergence club membership.Research limitations/implicationsFirst off, local conflict and economic environment result in food supply and prices, but this study is limited to the dynamics of prices.Practical implicationsFood prices inflations are not converging to single common price inflation, but there exist subgroups of countries or regions within which food price inflation tends to converge. These groupings tend to be related to the economic development and social stability of countries and regions.Social implicationsThe authors believe that any analysis of food price inflations that does not consider the political environment and economic conditions dynamics will likely be omitting important components of food price dynamics.Originality/valueThis study uses a unique data set covering 198 countries and regions and provides a comprehensive analysis of international food price inflation convergence identifying the key drivers of convergence club membership.

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“…At the same time, Royuela and Artis (2006), Higgins et al. (2008), Castillo-Manzano et al. (2014) and Dvorsky et al.…”

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Food price inflation convergence: an international study from 2000–2020

Fan

Wang

et al. 2022

BFJ

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“…This is because there are different patterns of economic developments and different types of road safety policies across countries. For instance, the heterogeneity of safety policies in Nordic, Southern, and Eastern parts of Europe raises the problem of convergence between European countries [29]. In a European road safety project, i.e., DaCoTA (details of this project can be found at the link http://www.dacota-project.eu/index.html), strong country-level heterogeneity was found based on long-term statistical models for each involved country [30,31].…”

Section: Literature Reviewmentioning

confidence: 99%

City-Level China Traffic Safety Analysis via Multi-Output and Clustering-Based Regression Models

Yan

Zhu

2020

Sustainability

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In the field of macro-level safety studies, road traffic safety is significantly related to socioeconomic factors, such as population, number of vehicles, and Gross Domestic Product (GDP). Due to different levels of economic and urbanization, the influence of the predictive factors on traffic safety measurements can differ between cities (or regions). However, such region-level or city-level heterogeneities have not been adequately concerned in previous studies. The objective of this paper is to adopt a novel approach for traffic safety analysis with a dataset containing multiple target variables and samples from different subpopulations. Based on a dataset with annual traffic safety and socioeconomic measurements from 36 major cities in China, we estimate single-output regression models, multi-output regression models, and clustering-based regression models. The results indicate that the 36 cities can be clustered into a metropolitan city class and a non-metropolitan city class, and the class-specified models can notably improve the goodness-of-fit and the interpretability of city-level heterogeneities. Specifically, we note that the effect of primary and secondary industrial GDP on traffic safety is opposite to that of tertiary industrial GDP in the metropolitan city class, while the effects of the two decomposed GDP on traffic safety are consistent in the non-metropolitan city class. We also note that the population has a positive effect on the number of fatalities and the number of injures in metropolitan cities but has no significant influence on traffic safety in non-metropolitan cities.

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