Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ UPCommons. Portal de...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 2 versions
addClaim

Models dif-in-dif en dades telemàtiques d'accidents d'automòbil

Authors: Orteu i Irurre, Anna-Patrícia;

Models dif-in-dif en dades telemàtiques d'accidents d'automòbil

Abstract

El proyecto analiza cómo cambia el comportamiento de una persona después de haber tenido un accidente de tráfico mediante la técnica econométrica Dif-in-Dif (Difference-in-Difference). Concretamente se comparan los cambios antes y después del accidente en dos grupos: el grupo “tratamiento” (afectados por el accidente) y el grupo “control” (sin accidentes). Se han utilizado varios tipos de modelos econométricos, incluidos modelos de datos de panel, técnicas estadísticas semi-paramétricas y no paramétricas. Asimismo, se han analizado, en primer lugar, todos los accidentes de forma conjunta, en segundo lugar, los accidentes causados por el asegurado y, finalmente, los accidentes causados por terceros. Los distintos modelos incorporan distintas covariables. Se ha usado R como lenguaje de programación para realizar el análisis estadístico. Los datos utilizados han sido recopilados por empresas “insurtech”.

El projecte analitza com canvia el comportament d’una persona després d’haver tingut un accident de trànsit mitjançant la tècnica economètrica Dif-in-Dif (Difference-in-Difference). Concretament es comparen els canvis abans i després de l’accident en dos grups: el grup “tractament” (afectats per l’accident) i el grup “control” (sense accidents). S’ha utilitzat diversos tipus de models economètrics, inclosos models de dades de panell, tècniques estadístiques semi-paramètriques i no paramètriques. Així mateix, s’ha analitzat, en primer lloc, tots els accidents de forma conjunta, en segon, els accidents causats per l’assegurat i, finalment, els accidents causats per tercers. Els diferents models incorporen diverses covariables. S’ha usat R com a llenguatge de programació per a realitzar l’anàlisi estadística. Les dades utilitzades han estat recopilades per empreses “insurtech”.

The project analyzes how a person’s behavior changes after having a traffic accident using the Dif-in-Dif (Difference-in-Difference) econometric technique. Specifically, the changes before and after the accident are compared in two groups: the “treatment” group (affected by the accident) and the “control” group (without accidents). Several types of econometric models have been used, including panel data models, semi-parametric and non-parametric statistical techniques. Also, first all accidents were analyzed together, secondly accidents caused by the insured and finally accidents caused by third parties. The different models incorporate various covariates. R has been used as the programming language to perform the statistical analysis. The data used has been collected by “insurtech” companies.

Country
Spain
Keywords

variables telemàtiques, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Variables (Mathematics), R (Computer program language), Models lineals (Estadística), Linear models (Statistics), R, Difference-in-Difference, R (Llenguatge de programació), accident, Variables (Matemàtica)

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 112
    download downloads 42
  • 112
    views
    42
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
112
42
Green