TY  - JOUR
PY  - 2019//
TI  - Congestion by accident? A two-way relationship for highways in England
JO  - Journal of transport geography
A1  - Pasidis, Ilias
SP  - 301
EP  - 314
VL  - 76
IS  - 
N2  - This paper aims to estimate the causal effect of accidents on traffic congestion and vice versa. In order to identify both effects of this two-way relationship, I use dynamic panel data techniques and open access 'big data' of highway traffic and accidents in England for the period 2012-2014. The research design is based on the daily-and-hourly specific mean reversion pattern of highway traffic, which can be used to define a recurrent congestion benchmark. Using this benchmark, I am able to identify the causal effect of accidents on non-recurrent traffic congestion. A positive relationship between traffic congestion and road accidents would yield multiplicative benefits for policies that aim at reducing either of these issues. Additionally, I explore the duration of the effect of an accident on congestion, the 'rubbernecking' effect, as well as heterogeneous effects in the most congested highway segments. Then, I test the use of methods which employ the bulk of information in big data and other methods using a very reduced sample. In my application, both approaches produce similar results. Finally, I find a non-linear negative effect of traffic congestion on the probability of an accident.<p />  <p>Language: en</p>
LA  - en
SN  - 0966-6923
UR  - http://dx.doi.org/10.1016/j.jtrangeo.2017.10.006
ID  - ref1
ER  -