Chapter 40 Classical estimation methods for LDV models using simulation

Hajivassiliou, Vassilis A.; Ruud, Paul A.

doi:10.1016/s1573-4412(05)80009-1

Cited by 273 publications

(245 citation statements)

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“…This multi-dimensional integration cannot be accomplished using general purpose numerical methods such as quadrature, since quadrature techniques cannot evaluate the integrals with sufficient precision and speed for estimation via maximum likelihood (see Hajivassiliou and Ruud, 1994 …”

Section: Model Estimationmentioning

confidence: 99%

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A joint econometric analysis of seat belt use and crash-related injury severity

Eluru

Bhat

2007

Accident Analysis & Prevention

193

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This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related injury severity analysis. First, the impact of a factor on injury severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to injury severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high injury severity crashes because of their unsafe driving habits.The preceding issues are considered in the current research effort through the development of a comprehensive model of seat belt use and injury severity that takes the form of a joint correlated random-coefficients binary-ordered response system. To our knowledge, this is the first instance of such a model formulation and application not only in the safety analysis literature, but in the econometrics literature in general. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and injury severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of injury severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).

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Section: Model Estimationmentioning

confidence: 99%

“…Under rather weak regularity conditions, the maximum (log) simulated likelihood (MSL) estimator is consistent, asymptotically efficient, and asymptotically normal (see Hajivassiliou and Ruud, 1994;Lee 1992). …”

Section: Model Estimationmentioning

confidence: 99%

A joint econometric analysis of seat belt use and crash-related injury severity

Eluru

Bhat

2007

Accident Analysis & Prevention

193

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“…Further, conventional quadrature techniques cannot be used to compute the integrals with sufficient precision and speed for estimation via maximum likelihood, since the dimension of integration exceeds two (Revelt and Train, 1998;Hajivassiliou and Ruud, 1994).…”

Section: Model Estimationmentioning

confidence: 99%

“…Under rather weak regularity conditions, the maximum simulated log-likelihood (MSL) estimator is consistent, asymptotically efficient, and asymptotically normal (see Hajivassiliou andRuud, 1994 andLee, 1992). However, the MSL estimator will generally be a biased simulation of the maximum log-likelihood (ML) estimator because of the logarithmic transformation of the choice probabilities in the log-likelihood function.…”

Section: Model Estimationmentioning

confidence: 99%

Accommodating flexible substitution patterns in multi-dimensional choice modeling: formulation and application to travel mode and departure time choice

Bhat¹

1998

Transportation Research Part B: Methodological

153

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The nested logit model has been used extensively to model multi-dimensional choice situations. A drawback of the nested logit model is that it does not allow choice alternatives to share common unobserved attributes along all the dimensions characterizing the multi-dimensional choice context. This paper formulates a mixed multinomial logit structure that accommodates unobserved correlation across both dimensions in a two-dimensional choice context. The mixed multinomial logit structure is parsimonious in the number of parameters to be estimated and is also relatively easy to estimate using simulation methods. The mixed multinomial logit model is applied to an analysis of travel mode and departure time choice for home-based social-recreational trips using data drawn from the 1990 San Francisco Bay Area household survey. The empirical results underscore the need to capture unobserved attributes along both the mode and departure time dimensions, both for improved data fit as well as for more realistic policy evaluations of transportation control measures.

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“…To avoid numerical integration in five dimensions, the integral is replaced by a simulated mean: (see, e.g., Train, 2003). If M tends to ∞ at a fast enough rate, the simulated maximum likelihood estimator is asymptotically equivalent to exact maximum likelihood (see, e.g., Gouriéroux andMonfort, 1996, or Hajivassiliou andRuud, 1994 it D  ). Once the model is estimated we can predict the probabilities of all of these types of responses, which will (if the model is correctly specified) add up to the observed fraction of 50 percent answers in the data.…”

Section: R Itmentioning

confidence: 99%

Nonresponse and Focal Point Answers to Subjective Probability Questions

Kleinjans

Soest

2010

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.IZA Discussion Paper No. 5272 October 2010 ABSTRACT Nonresponse and Focal Point Answers to Subjective Probability Questions *We develop and estimate a panel data model explaining the answers to questions about subjective probabilities, using data from the US Health and Retirement Study. We explicitly account for nonresponse, rounding, and focal point "50 percent" answers. Our results indicate that for three of the four questions considered, almost all 50 percent answers can be explained by rounding. We also find observed and unobserved heterogeneity in the tendencies to report rounded values or a focal answer, explaining persistency in 50 percentanswers over time. Incorporating rounding and focal answers changes some of the conclusions about the socio-economic factors that determine expectations.JEL Classification: C81, D84

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Chapter 40 Classical estimation methods for LDV models using simulation

Cited by 273 publications

References 54 publications

A joint econometric analysis of seat belt use and crash-related injury severity

A joint econometric analysis of seat belt use and crash-related injury severity

Accommodating flexible substitution patterns in multi-dimensional choice modeling: formulation and application to travel mode and departure time choice

Nonresponse and Focal Point Answers to Subjective Probability Questions

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