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This study re-examines the relationship between competition and innovation in a detailed firm-level dataset of publicly traded US companies spanning from 1975 to 2013. Using R&D expenditures, patent counts and patent citations as the measures of innovation, and Herfindahl-Hirschman Index, Lerner Index, Profit Elasticity and Product Market Fluidity as the proxies for competition we document a robust positive association between the two variables, as well as strong evidence of the non-linear relationship known as "inverted-U shape", when controlling for size, distance to technological frontier, level of knowledge spillovers, technological opportunities and other firm- and industry-specific characteristics. We address overdispersion in the data by using negative binomial and zero-inflated negative binomial count data regressions, and the results are robust in these specifications. Additionally, in order to address potential endogeneity issues, we employ a set of instruments based on the import tariff rates and the level of Chinese import penetration, and find a weak evidence of positive relationship as well. Overall the results strongly support the prediction of agency models, "replacement effect" and "escape- competition effect" about the positive influence of competition on innovation. Powered by TCPDF...

Left-turning maneuvers are considered to be the highest risk movements at intersections and two-thirds of the crashes associated with left-turns are reported at signalized intersections. Left-turning vehicles typically encounter conflicts from opposing through traffic. To separate conflicting movements, transportation agencies use a protected-only phase at signalized intersections where each movement is allowed to move alone. However, this could create delays and thus the concept of a protected-permissive phase has been introduced to balance safety and delays. However, the permissive part of this phasing scheme retains the safety concerns and could increase the possibility of conflicts resulting in crashes. This research developed a model that can predict the number of crashes for protected-permissive left-turn phasing, based on traffic volumes and calculated conflicts. A total of 103 intersections with permissive-protected left-turn phasing in Kentucky were simulated and their left-turn related conflicts were obtained from post processing vehicle trajectories through the Surrogate Safety Assessment Model (SSAM). Factors that could affect crash propensity were identified through the Principal Component Analysis in Negative Binomial Regression. Nomographs were developed from the models which can be used by traffic engineers in left-turn phasing decisions with enhanced safety considerations.

Doctor of Philosophy / Civil Engineering / Sunanda Dissanayake / Safe and efficient flow of traffic through work zones must be established by improving work zone conditions. Therefore, identifying the factors associated with the severity and the frequency of work zone crashes is important. According to current statistics from the Federal Highway Administration, 2,372 fatalities were associated with motor vehicle traffic crashes in work zones in the United States during the four years from 2010 to 2013. From 2002 to 2014, an average of 1,612 work zone crashes occurred in Kansas each year, making it a serious concern in Kansas. Objectives of this study were to analyze work zone crash characteristics, identify the factors associated with crash severity and frequency, and to identify recommendations to improve work zone safety. Work zone crashes in Kansas from 2010 to 2013 were used to develop crash severity models. Ordered probit regression was used to model the crash severities for daytime, nighttime, multi-vehicle and single-vehicle work zone crashes and for work zones crashes in general. Based on severity models, drivers from 26 to 65 years of age were associated with high crash severities during daytime work zone crashes and driver age was not found significant in nighttime work zone crashes. Use of safety equipment was related to reduced crash severities regardless of the time of the crash. Negative binomial regression was used to model the work zone crash frequency using work zones functioned in Kansas in 2013 and 2014. According to results, increased average daily traffic (AADT) was related to higher number of work zone crashes and work zones in operation at nighttime were related to reduced number of work zone crashes. Findings of this study were used to provide general countermeasure ideas for improving safety of work zones.

In this paper we study the occurrences of outdoor vehicle fires recorded by the Swedish Civil Contingencies Agency (MSB) for the period 1998-2019, and build static panel data models to predict future occurrences of fire in Stockholm County. Through comparing the performance of different models, we look at the effect of different distributional assumptions for the dependent variable on predictive performance. Our study concludes that treating the dependent variable as continuous does not hamper performance, with the exception of models meant to predict more uncommon occurrences of fire. Furthermore, we find that assuming that the dependent variable follows a Negative Binomial Distribution, rather than a Poisson Distribution, does not lead to substantial gains in performance, even in cases of overdispersion. Finally, we notice a slight increase in the number of vehicle fires shown in the data, and reflect on whether this could be related to the increased population size.

No description available.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-06-02T15:48:39Z No. of bitstreams: 1 veronicadecastrolameira.pdf: 1250198 bytes, checksum: af0c0263e3fc8188a4d53c8627567747 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-07-02T13:16:07Z (GMT) No. of bitstreams: 1 veronicadecastrolameira.pdf: 1250198 bytes, checksum: af0c0263e3fc8188a4d53c8627567747 (MD5) / Made available in DSpace on 2016-07-02T13:16:07Z (GMT). No. of bitstreams: 1 veronicadecastrolameira.pdf: 1250198 bytes, checksum: af0c0263e3fc8188a4d53c8627567747 (MD5) Previous issue date: 2012-12-20 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A análise da mobilidade de trabalhadores exerce papel fundamental na tomada de decisões em políticas públicas. O primeiro ensaio aborda a questão da mobilidade de curta e longa distância, e ainda os fatores regionais da atração de trabalhadores entre as microrregiões do Brasil, utilizando modelo binomial negativo. Houve a constatação da preferência dos trabalhadores por destinos com maior atratividade relativa, admissão de trabalhadores frente aos desligados, densidade, proporção de graduados, menor criminalidade e congestionamento. Para o modelo de longa distância os fluxos são orientados para destinos com menor densidade populacional, menor grau de industrialização, menor criminalidade e maior atração relativa. O congestionamento se mostrou irrelevante na mobilidade de longa distância. A distância figura como fator inibidor para a mobilidade, independente dos cortes de distância. O segundo ensaio adota o modelo logit multinível espacial com o objetivo de identificar os condicionantes individuais e regionais da mobilidade de trabalhadores qualificados nas microrregiões brasileiras. Foi possível verificar que a experiência do trabalhador figura como fator inibidor da mobilidade, a expectativa salarial reflete menor propensão à mudança para trabalhadores em geral, e maior probabilidade para qualificados. Algumas variáveis de contexto também se mostram importantes para explicar a mobilidade, como PIB per capita, proporção de trabalhadores com ensino superior completo, taxa de homicídio, veículos por habitantes, grau de industrialização e rede de migrantes. / The analysis of labor mobility plays a fundamental role in decision-making in public policy. The first essay addresses the issue of mobility by long and short distance, and the regional factors of attraction for workers among Brazilian microregions, by means of negative binomial model. There was the realization of the preferred destinations for workers with higher relative attractiveness, employment of workers off against, density, proportion of graduates, less crime and congestion. To model long-distance flows are oriented destinations with lower population density, lower degree of industrialization, less crime and greater relative attractiveness. Congestion proved irrelevant in the long-distance mobility. The distance appears as an inhibiting factor for mobility, regardless of the cuts away. The second essay adopts a spatial multilevel logit model in order to identify the determinants of individual and regional mobility of skilled workers in the Brazilian microregions. The results indicate that the worker seniority figures as inhibitory factor of mobility, and expected wage decrease the propensity of mobility for workers in general, though it increases the propensity of the more skilled ones. The context variables also show important to explain mobility, such as GDP per capita, proportion of workers with higher education, rate of homicide by vehicle inhabitants, degree of industrialization and net migrants.

Das Radverkehrsaufkommen in Deutschland verzeichnete in den letzten Jahren einen Zuwachs, was sich im Umkehrschluss ebenfalls im Anstieg des Unfallgeschehens mit Radfahrendenbeteiligung widerspiegelt. Um den steigenden Unfallzahlen entgegenzuwirken, empfehlen Politik und Verbände v.a. Infrastrukturmaßnahmen zu ergreifen. Davon ausgehend untersucht die vorliegende Arbeit beispielhaft für die Stadt Dresden, wie sich einzelne Infrastrukturmerkmale auf das Unfallgeschehen zwischen Rad- und motorisiertem Verkehr auswirken. Die Datengrundlage der Untersuchung stellen dabei 548 Unfälle mit Radfahrendenbeteiligung aus den Jahren 2015 bis 2019 sowie die Merkmale von 484 Knotenpunktzufahrten dar. Da die Infrastruktur das Unfallgeschehen nicht allein determiniert, werden zudem Kenngrößen des Verkehrsaufkommens einbezogen. Um das Unfallgeschehen zu untersuchen, kommen das Random Forest-Verfahren sowie die Negative Binomialregression in Form von 'Accident Prediction Models' mit vorheriger Variablenselektion anhand des LASSO-Verfahrens zum Einsatz. Die Verfahren werden jeweils auf zwei spezielle Unfalltypen für Knotenpunkte angewandt, um differenzierte Ergebnisse zu erlangen. Der erste Unfalltyp 'Abbiege-Unfall' umfasst dabei Kollisionen zwischen einem rechtsabbiegenden und einem in gleicher oder entgegengesetzter Richtung geradeausfahrenden Beteiligten, während der zweite Unfalltyp 'Einbiegen-/Kreuzen-Unfall' Kollisionen zwischen einem vorfahrtsberechtigten Verkehrsteilnehmenden und einem einbiegenden oder kreuzenden Wartepflichtigen beinhaltet. Für den Unfalltyp 'Abbiege-Unfall' zeigen die Verfahren bspw., dass eine über den Knotenpunkt komplett oder teilweise rot eingefärbte Radfahrfurt sowie eine indirekte Führung des linksabbiegenden Radverkehrs anstelle dessen Führung im Mischverkehr höhere Unfallzahlen erwarten lässt, wobei letzteres für den untersuchten Sachverhalt irrelevant erscheint und damit auf eine Schwäche bei der Variableneinbeziehung hindeutet. Im Gegensatz dazu schätzen die Verfahren für den Unfalltyp 'Einbiegen-/Kreuzen-Unfall' bspw. höhere Unfallzahlen, wenn die Anzahl der Geradeausfahrstreifen einer Zufahrt zunimmt und wenn der Knotenpunkt durch das Verkehrszeichen Z205 bzw. eine Teil-Lichtsignalanlage anstelle der Vorschrift Rechts-vor-Links geregelt wird. Zudem zeigen die Verfahren bei beiden Unfalltypen zumeist, dass die Zahl der Unfälle ab einem bestimmten Verkehrsaufkommen weniger stark ansteigt. Dieses Phänomen ist in der Wissenschaft unter dem Namen 'Safety in Numbers-Effekt' bekannt. Ein Vergleich der Modellgüten zwischen den Unfalltypen zeigt zudem, dass beide Verfahren mit ihrem Modell des Unfalltyps 'Abbiege-Unfall' bessere Vorhersagen generieren als mit ihrem Modell des Unfalltyps 'Einbiegen-/Kreuzen-Unfall'. Weiterhin unterscheiden sich die Modellgüten nach Unfalltyp nur geringfügig zwischen beiden Verfahren, weshalb davon ausgegangen werden kann, dass beide Verfahren qualitativ ähnliche Modelle des entsprechenden Unfalltyps liefern.:1 Einleitung 2 Literaturüberblick 2.1 Safety in Numbers-Effekt 2.2 Einflussfaktoren von Radverkehrsunfällen 3 Grundlagen der Unfallforschung 3.1 Unfallkategorien 3.2 Unfalltypen 4 Datengrundlage 4.1 Unfalldaten 4.2 Infrastrukturmerkmale 4.3 Überblick über verwendete Variablen 5 Methodik 5.1 Korrelationsbetrachtung 5.2 Random Forest 5.2.1 Grundlagen 5.2.2 Random Forest-Verfahren 5.2.3 Modellgütekriterien 5.2.4 Variablenbedeutsamkeit 5.3 Negative Binomialregression 5.3.1 Grundlagen 5.3.2 Accident Prediction Models 5.3.3 Variablenselektion 5.3.4 Modellgütekriterien 5.3.5 Variablenbedeutsamkeit 5.3.6 Modelldiagnostik 6 Durchführung und Ergebnisse 6.1 Korrelationsbetrachtung 6.2 Random Forest 6.2.1 Modellgütekriterien 6.2.2 Variablenbedeutsamkeit 6.3 Negative Binomialregression 6.3.1 Variablenselektion 6.3.2 Modellgütekriterien 6.3.3 Variablenbedeutsamkeit 6.3.4 Modelldiagnostik 6.4 Vergleich beider Verfahren 6.4.1 Modellgütekriterien 6.4.2 Variablenbedeutsamkeit und Handlungsempfehlungen 6.5 Vergleich mit Literaturerkenntnissen 7 Kritische Würdigung 8 Zusammenfassung und Ausblick

The intent of this thesis is to research the anti-terror legislation of 15 countries and the history of terrorist incidents within those countries. Both the anti-terror legislation and the history of terrorist incidents will be researched within the time period of 1980 to 2009, a 30 year span. This thesis will seek to establish a relationship between the occurrence of terrorist events and when states change their anti-terror legislation. Legislation enacted can vary greatly. Common changes in legislation seek to undercut the financing of terrorist organizations, criminalize behaviors, or empower state surveillance capabilities. A quantitative analysis will be performed to establish a relationship between terrorist attacks and legislative changes. A qualitative discussion will follow to analyze specific anti-terror legislation passed by states in response to terrorist events.

“Vision Zero,” first adopted by Sweden in 1997, is a road safety policy that aims to achieve a transportation system having zero fatalities or serious injuries for all modes of transportation. It takes a proactive approach to road safety system by identifying risk and taking steps to prevent injuries. Historically, traffic related crashes have disproportionately impacted vulnerable communities and system users including people of color, low income individuals, seniors, children, and pedestrians, bicyclists, and transit users (who typically walk to and from public transport). These inequities are addressed in the Vision Zero framework by prioritizing interventions in areas that need safety improvements the most. In 2016, the Alexandria City Council voted unanimously to develop a “Vision Zero” policy and program as a part of its updated transportation master plan. It required an initial equity analysis to assess the impact of traffic crashes on the traditionally underserved communities / groups (groups from at least one of these categories: low-income; minority; elderly; children; limited English proficiency; persons with disabilities; and/or pedestrians/ bicyclists/ transit users). This study combines three different methods to investigate the equity issues regarding traffic safety: 1) descriptive analysis of the spatial pattern of crashes and their relationship with the demographic profiles of neighborhoods at census block group level (for 2010-2014 period); 2) descriptive analysis of the crash trends in Alexandria; and 3) exploratory regression analyses for two different units of analysis (an aggregate regression analysis of crashes at census block group, and a disaggregate regression analysis of the individual level crash reports of traffic crashes). The analysis found that the elderly, school aged children, rail/subway users, and pedestrians had a higher risk of fatalities and severe injuries in traffic crashes. Higher job densities, alcohol impairment, and speeding were significantly related to higher KSI, whereas, smaller block sizes (higher number of street segments per sq. mile area of census block group), higher housing density, and use of safety equipment were related to lower KSI. / Master of Urban and Regional Planning