Temporal instability and the analysis of highway accident data

Analytic Methods in Accident Research

Volumn 17, Issue , 2018, Pages 1-13

  Mannering, Fred ^a  

^a University of South Florida   (United States)

Author keywords

Accident likelihood; Accident severity; Attitudes; Cognitive science; Highway safety; Statistical and econometric methods; Temporal stability; Unobserved heterogeneity

Indexed keywords

HIGHWAY ACCIDENTS; HIGHWAY ENGINEERING; INFORMATION ANALYSIS;

ACCIDENT LIKELIHOOD; ACCIDENT SEVERITY; ATTITUDES; COGNITIVE SCIENCE; HIGHWAY SAFETY; STATISTICAL AND ECONOMETRIC METHODS; TEMPORAL STABILITY; UNOBSERVED HETEROGENEITY;

STABILITY;

EID: 85032566625     PISSN: 22136657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amar.2017.10.002     Document Type: Article

References (73)

1. Abay, K., Mannering, F., An empirical analysis of risk-taking in car driving and other aspects of life. Accident Analysis and Prevention 97 (2016), 57–68.
2. Abdelwahab, H., Abdel-Aty, M., Development of artificial neural network models to predict driver injury severity in traffic accidents at signalized intersections. Transportation Research Record 1746 (2001), 6–13.
3. Ajzen, I., Nature and operation of attitudes. Annual Review of Psychology 52:1 (2001), 27–58.
4. American Association of State Highway and Transportation Officials, 2010. Highway Safety Manual, Washington, DC.
5. Angrist, J., Pischke, J.-S., Mastering Metrics: The Path from cause to Effect. 2015, Princeton University Press, Princeton, NJ.
6. Angrist, J., Pischke, J.-S., 2017. Undergraduate econometrics instruction: Throughout classes, darkly. Working paper 23144, National Bureau of Economic Research, Cambridge, MA.
7. Behnood, A., Mannering, F., The temporal stability of factors affecting driver-injury severities in single-vehicle crashes: some empirical evidence. Analytic Methods in Accident Research 8 (2015), 7–32.
8. Behnood, A., Mannering, F., An empirical assessment of the effects of economic recessions on pedestrian-injury crashes using mixed and latent-class models. Analytic Methods in Accident Research 12 (2016), 1–17.
9. Behnood, A., Mannering, F., The effect of passengers on driver-injury severities in single-vehicle crashes: a random parameters heterogeneity-in-means approach. Analytic Methods in Accident Research 14 (2017), 41–53.
10. Behnood, A., Mannering, F., Determinants of bicyclist injury severities in bicycle-vehicle crashes: a random parameters approach with heterogeneity in means and variances. Analytic Methods in Accident Research 16 (2017), 35–47.
11. Benoit, J.-P., Dubra, J., Apparent overconfidence. Econometrica 79:5 (2011), 1591–1625.
12. Benoit, J.-P., Dubra, J., 2017. When do populations polarize? An explanation. Working Paper. London Business School, London, UK.
13. Bhat, C., Dubey, S., A new estimation approach to integrate latent psychological constructs in choice modeling. Transportation Research Part B 67 (2014), 68–85.
14. Bickel, W., Miller, M., Yi, R., Kowal, B., Lindquist, D., Pitcock, J., Behavioral and neuroeconomics of drug addiction: competing neural systems and temporal discounting processes. Drug and Alcohol Dependence 90S (2007), S85–91.
15. Camerer, C., Loewenstein, G., Prelec, D., Neuroeconomics: how neuroscience can inform economics. Journal of Economic Literature 43:1 (2005), 9–64.
16. Chang, L.-Y., Analysis of freeway accident frequencies: negative binomial regression versus artificial neural network. Safety Science 43:8 (2005), 541–557.
17. Chong, M., Abraham, A., Paprzycki, M., Traffic accident analysis using machine learning paradigms. Informatica 29:1 (2005), 89–98.
18. Constantinou, E., Panayiotou, G., Konstantinou, N., Loutsiou-Ladd, A., Kapardis, A., Risky and aggressive driving in young adults: personality matters. Accident Analysis and Prevention 43:1 (2011), 1323–1331.
19. Dale, S., Krueger, A., Estimating the payoff to attending a more selective college: an application of selection on observables and unobservables. Quarterly Journal of Econometrics 117:4 (2002), 1491–1527.
20. Delen, D., Sharda, R., Bessonov, M., Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks. Accident Analysis and Prevention 38:3 (2006), 434–444.
21. Fazio, R., Powell, M., Williams, C., The role of attitude accessibility in the attitude-to-behavior process. Journal of Consumer Research 16:3 (1989), 280–289.
22. Festinger, L., Cognitive dissonance. Scientific American 207:4 (1962), 93–107.
23. Fisher, F., Shell, K., Taste and quality change in the pure theory of the true cost-of-living index. Wolfe, J.N., (eds.) Value, Capital and Growth, 1969, Edinburgh University Press, Edinburgh, UK.
24. Fishhoff, B., Bostrom, A., Quadrel, M., Risk perception and communication. Annual Review of Public Health 14 (1993), 183–203.
25. Glasman, L., Albarracib, D., Forming attitudes that predict future behavior: a meta-analysis of the attitude-behavior relation. Psychological Bulletin 132:5 (2006), 778–822.
26. Green, L., Myerson, J., A discounting framework for choice with delayed and probabilistic awards. Psychological Bulletin 130:5 (2004), 769–792.
27. Gorman, W., Tastes, habits, and choices. International Economic Review 8:2 (1967), 218–222.
28. Guiso, L., Sapienza, P., Luigi, G., 2013. Time varying risk aversion. Working paper 19284, National Bureau of Economic Research, Cambridge, MA.
29. Heckman, J., Sample selection bias as a specification error. Econometrica 47:1 (1979), 153–161.
30. Kahneman, D., Slovic, P., Tversky, A., (eds.) Judgment under Uncertainty: Heuristics and Biases, 1982, Cambridge University Press, New York, NY.
31. Li, X., Lord, D., Zhang, Y., Xie, Y., Predicting motor vehicle crashes using support vector machine models. Accident Analysis and Prevention 40:4 (2008), 1611–1618.
32. Lieberman, M., Gaunt, R., Gilbert, D., Trope, Y., Reflection and reflexion: a social cognitive neuroscience approach to attributional inference. Zanna, M., (eds.) Advances in Experimental Psychology, 2002, Academic Press, New York, NY, 199–249.
33. Lluch, C., Expenditure, savings, and habit formation. International Economic Review 15:3 (1974), 786–797.
34. Lord, C., Ross, L., Lepper, M., Biased assimilation and attitude polarization: the effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology 37:11 (1979), 2098–2109.
35. Lord, D., Mannering, F., The statistical analysis of crash-frequency data: a review and assessment of methodological alternatives. Transportation Research Part A 44:5 (2010), 291–305.
36. Maheshri, V., Winston, C., Did the great depression keep bad drivers off the road?. Journal of Risk and Uncertainty 52:3 (2016), 255–280.
37. Malmendier, U., Nagel, S., Depression babies: do macroeconomic experiences affect risk-taking?. Quarterly Journal of Economics 126:1 (2011), 373–416.
38. Malyshkina, N., Mannering, F., Effect of increases in speed limit on severities of injuries in accidents. Transportation Research Record 2083 (2008), 122–127.
39. Malyshkina, N., Mannering, F., Markov switching multinomial logit model: an application to accident-injury severities. Accident Analysis and Prevention 41:4 (2009), 829–838.
40. Malyshkina, N., Mannering, F., Zero-state Markov switching count-data models: an empirical assessment. Accident Analysis and Prevention 42:1 (2010), 122–130.
41. Malyshkina, N., Mannering, F., Tarko, A., Markov switching negative binomial models: an application to vehicle accident frequencies. Accident Analysis and Prevention 41:2 (2009), 217–226.
42. Maness, M., Cirillo, C., An indirect latent informational conformity social influence choice model: formulation and case study. Transportation Research Part B 93 (2016), 75–101.
43. Maness, M., Cirillo, C., Dugundji, E., Generalizable behavioral framework for choice models of social influence: behavioral and data concerns in travel behavior. Journal of Transport Geography 46 (2015), 137–150.
44. Mannering, F., Bhat, C., Analytic methods in accident research: methodological frontier and future directions. Analytic Methods in Accident Research 1 (2014), 1–22.
45. Mannering, F., Murakami, E., Kim, S.-G., Temporal stability of travelers' activity choice and home-stay duration: some empirical evidence. Transportation 21:4 (1994), 371–392.
46. Mannering, F., Shankar, V., Bhat, C., Unobserved heterogeneity and the statistical analysis of highway accident data. Analytic Methods in Accident Research 11 (2016), 1–16.
47. Mannering, F., Winston, C., Automobile air bags in the 1990's: market failure or market efficiency?. Journal of Law and Economics 38:2 (1995), 265–279.
48. Manski, C., Identification of endogenous social effects: the reflection problem. Review of Economic Studies 60:3 (1993), 531–542.
49. McClure, S., Laibson, D., Loewenstein, G., Cohen, J., Separate neural systems value immediate and delayed monetary rewards. Science 306:5695 (2004), 503–507.
50. National Academies, Frontiers in Massive Data Analysis. 2013, The National Academies Press, Washington, DC.
51. Persaud, B., Lan, B., Lyon, C., Bhim, R., Comparison of empirical Bayes and full Bayes approaches for before–after road safety evaluations. Accident Analysis and Prevention 42:1 (2010), 38–43.
52. Peston, M., Changing utility functions. Shubik, M., (eds.) Essays in Mathematical Economics, 1967, Princeton University Press, Princeton, NJ.
53. Peterman, D., 2013. Federal traffic safety programs: An overview, congressional research service report for congress. Washington, DC.
54. Peters, J., Buchel, C., The neural mechanisms of intertemporal decision-making: understanding variability. Trends in Cognitive Science 15:5 (2011), 227–239.
55. Phlips, L., A dynamic version of the linear expenditure model. The Review of Economics and Statistics 54:4 (1972), 450–458.
56. Pollak, R., Habit formation and dynamic demand functions. Journal of Political Economy 78:4 (1970), 745–763.
57. Pollak, R., Wales, T., Estimation of the linear expenditure system. Econometrica 37:4 (1969), 611–628.
58. Riviere, C., Lauret, P., Ramsamy, J., Page, Y., A Bayesian neural network approach to estimating the energy equivalent speed. Accident Analysis and Prevention 38:2 (2006), 248–259.
59. Rossi, T., Bhat, C., 2014. Guide for travel model transfer. Federal Highway Administration, United States Department of Transportation, FHWA-HEP-15-006, Washington, DC.
60. Ruhm, C., Are recessions good for your health?. Quarterly Journal of Economics 115:2 (2000), 617–650.
61. Savolainen, P., Mannering, F., Lord, D., Quddus, M., The statistical analysis of crash-injury severities: a review and assessment of methodological alternatives. Accident Analysis and Prevention 43:5 (2011), 1666–1676.
62. Seraneeprakarn, P., Huang, S., Shankar, V., Mannering, F., Venkataraman, N., Milton, J., Occupant injury severities in hybrid-vehicle involved crashes: a random parameters approach with heterogeneity in means and variances. Analytic Methods in Accident Research 15 (2017), 41–55.
63. Sumer, N., Personality and behavioral predictors of traffic accidents: testing a contextual mediated model. Accident Analysis and Prevention 35:1 (2003), 949–964.
64. Svenson, O., Are we all less risky and more skillful than our fellow drivers?. Acta Psychologica 94:2 (1981), 143–148.
65. Tversky, A., Kahneman, D., Judgement under uncertainty: heuristics and biases. Science 185:4157 (1974), 1124–1131.
66. Ulleberg, P., Rundmo, T., Personality, attitudes and risk perception as predictors of risky driving behavior among young drivers. Safety Science 41:5 (2003), 427–443.
67. Venkataraman, N., Shankar, V., Blum, J., Hariharan, B., Hong, J., Transferability analysis of heterogeneous overdispersion parameter negative binomial crash models. Transportation Research Record 2583 (2016), 99–109.
68. Washington, S., Karlaftis, M., Mannering, F., Statistical and econometric methods for transportation data analysis. second ed., 2011, Chapman and Hall/CRC, Boca Raton, FL.
69. Winston, C., Maheshri, V., Mannering, F., An exploration of the offset hypothesis using disaggregate data: the case of airbags and antilock brakes. Journal of Risk and Uncertainty 32:2 (2006), 83–99.
70. World Health Organization, Global status report on road safety 2015. 2015, World Health Organization, Geneva, Switzerland.
71. Xie, Y., Lord, D., Zhang, Y., Predicting motor vehicle collisions using Bayesian neural networks: an empirical analysis. Accident Analysis and Prevention 39:5 (2007), 922–933.
72. Xiong, Y., Tobias, J., Mannering, F., The analysis of vehicle crash injury-severity data: a Markov switching approach with road-segment heterogeneity. Transportation Research Part B 67 (2014), 109–128.
73. Yu, R., Abdel-Aty, M., Utilizing support vector machine in real-time crash evaluation. Accident Analysis and Prevention 51 (2013), 252–259.