@article{LEUV:OOST:08,
 author = {Leuven, Edwin & Oosterbeek, Hessel},
 title = {"An alternative approach to estimate the wage returns to private-sector training"},
 journal = {Journal of Applied Econometrics},
 volume = 23,
 year = 2008,
 pages = 423-434
 }
 

@article{MULL:97,
    author = {Mullahy, John},
    title = "{Instrumental-Variable Estimation of Count Data Models: Applications to Models of Cigarette Smoking Behavior}",
    journal = {The Review of Economics and Statistics},
    volume = {79},
    number = {4},
    pages = {586-593},
    year = {1997},
    month = {11}
}

@article{WILH:08,
author = {Wilhelm, Mark Ottoni},
title = {Practical Considerations for Choosing Between Tobit and SCLS or CLAD Estimators for Censored Regression Models with an Application to Charitable Giving},
journal = {Oxford Bulletin of Economics and Statistics},
volume = {70},
number = {4},
pages = {559-582},
keywords = {C12, C14, C15, C24, C52},
year = {2008}
}

@article{NEWE:85,
 author = {Whitney K. Newey},
 journal = {Econometrica},
 number = {5},
 pages = {1047--1070},
 publisher = {[Wiley, Econometric Society]},
 title = {Maximum Likelihood Specification Testing and Conditional Moment Tests},
 volume = {53},
 year = {1985}
}

@article{TAUC:85,
title = {Diagnostic testing and evaluation of maximum likelihood models},
journal = {Journal of Econometrics},
volume = {30},
number = {1},
pages = {415-443},
year = {1985},
author = {George Tauchen}
}

@article{PAGA:VELL:89,
 author = {Adrian Pagan and Frank Vella},
 journal = {Journal of Applied Econometrics},
 number = {},
 pages = {S29--S59},
 publisher = {Wiley},
 title = {Diagnostic Tests for Models Based on Individual Data: A Survey},
 volume = {4},
 year = {1989}
}

@article{WELL:03,
 author = {Curt Wells},
 journal = {Journal of Applied Econometrics},
 number = {2},
 pages = {237--239},
 publisher = {Wiley},
 title = {Retesting Fair's (1978) Model on Infidelity},
 volume = {18},
 year = {2003}
}

@article{KENK:TERZ:01,
author = {Kenkel, Donald S. and Terza, Joseph V.},
title = {The effect of physician advice on alcohol consumption: count regression with an endogenous treatment effect},
journal = {Journal of Applied Econometrics},
volume = {16},
number = {2},
pages = {165-184},
year = {2001}
}

@article{TERZ:98,
  author={Terza, Joseph V.},
  title={Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects},
  journal={Journal of Econometrics},
  year=1998,
  volume={84},
  number={1},
  pages={129-154},
  month={May}
}

@Inbook{GREE:01,
author="Greene, William H.",
editor="Negishi, Takashi
and Ramachandran, Rama V.
and Mino, Kazuo",
chapter = "6",
title="Fiml Estimation of Sample Selection Models for Count Data",
bookTitle="Economic Theory, Dynamics and Markets: Essays in Honor of Ryuzo Sato",
year="2001",
publisher="Springer US",
address="Boston, MA",
pages="73--91"
}

@Article{ADKI:CART:SIMP:07,
  author={Lee C. Adkins and David A. Carter and W. Gary Simpson},
  title={{Managerial Incentives And The Use Of Foreign‐Exchange Derivatives By Banks}},
  journal={Journal of Financial Research},
  year=2007,
  volume={30},
  number={3},
  pages={399-413},
  month={September}
}

@article{ADKI:12,
author = { Lee   C.   Adkins },
title = {Testing parameter significance in instrumental variables probit estimators: some simulation},
journal = {Journal of Statistical Computation and Simulation},
volume = {82},
number = {10},
pages = {1415-1436},
year  = {2012},
publisher = {Taylor & Francis}
}

@article{ABIA:MODY:05,
Author = {Abiad, Abdul and Mody, Ashoka},
Title = {Financial Reform: What Shakes It? What Shapes It?},
Journal = {American Economic Review},
Volume = {95},
Number = {1},
Year = {2005},
Month = {March},
Pages = {66-88}
}

@article{HAUS:78,
 author = {J. A. Hausman},
 journal = {Econometrica},
 number = {6},
 pages = {1251--1271},
 publisher = {[Wiley, Econometric Society]},
 title = {Specification Tests in Econometrics},
 volume = {46},
 year = {1978}
}


@ARTICLE{SMIT:BLUN:86,
title = {An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply},
author = {Smith, Richard and Blundell, Richard},
year = {1986},
journal = {Econometrica},
volume = {54},
number = {3},
pages = {679-85}
}

@Article{HORO:93,
  author = 	 {Horowitz, Joel L.},
  title = 	 {Semiparametric estimation of a work-trip mode choice model},
  journal = 	 {Journal of econometrics},
  year = 	 {1993},
  OPTkey = 	 {},
  volume = 	 {58},
  number = 	 {1-2},
  pages = 	 {49-70},
  OPTmonth = 	 {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

@Article{VUON:89,
  author = 	 {Vuong, Quang H.},
  title = 	 {Likelihood Ratio Tests for Selection and Non-Nested Hypotheses},
  journal = 	 {Econometrica},
  year = 	 {1989},
  optkey = 	 {},
  volume = 	 {57},
  number = 	 {2},
  pages = 	 {397-333},
  OPTmonth = 	 {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

@Article{SHI:15,
  author = 	 {Shi, Xiaoxia},
  title = 	 {A nondegenerate Vuong test},
  journal = 	 {Quantitative Economics},
  year = 	 {2015},
  OPTkey = 	 {},
  OPTvolume = 	 {6},
  OPTnumber = 	 {},
  pages = 	 {85-121},
  OPTmonth = 	 {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

@article{HAN:LEE:19,
author = {Han, Sukjin and Lee, Sungwon},
title = {Estimation in a generalization of bivariate probit models with dummy endogenous regressors},
journal = {Journal of Applied Econometrics},
volume = {34},
number = {6},
pages = {994-1015},
year = {2019}
}

@article{DEHE:WAHB:02,
    author = {Dehejia, Rajeev H. and Wahba, Sadek},
    title = "{Propensity Score-Matching Methods for Nonexperimental Causal Studies}",
    journal = {The Review of Economics and Statistics},
    volume = {84},
    number = {1},
    pages = {151-161},
    year = {2002},
    month = {02},
    issn = {0034-6535},
    doi = {10.1162/003465302317331982}
}

@article{BECK:ICHI:02,
	author = "Becker, S.O.",
	author = "Ichino, A.",
	title = "Estimation of average treatment effects based on propensity scores",
	journal = "Stata Journal",
	publisher = "Stata Press",
	address = "College Station, TX",
	volume = "2",
	number = "4",
	year = "2002",
	pages = "358-377(20)"
}

@Article{IWAT:01,
  author={Shigeru Iwata},
  title={{Recentered And Rescaled Instrumental Variable Estimation Of Tobit And Probit Models With Errors In Variables}},
  journal={Econometric Reviews},
  year=2001,
  volume={20},
  number={3},
  pages={319-335},
  month={},
  keywords={Instrumental variables; GMM estimator; Nonlinear errors in variables; Elliptically symmetric distrib},
  doi={10.1081/ETC-100104937}
}

@Article{TOBI:58,
  author = 	 {Tobin, James},
  title = 	 {Estimation of Relationships for Limited Dependent Variables},
  journal = 	 {Econometrica},
  year = 	 {1958},
  optkey = 	 {},
  volume = 	 {26},
  number = 	 {1},
  pages = 	 {24-36},
  OPTmonth = 	 {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

@Article{POWE:86,
  author = 	 {Powell, J.},
  title = 	 {Symmetrically trimed least squares estimators for tobit models},
  journal = 	 {Econometrica},
  year = 	 {1986},
  OPTkey = 	 {},
  volume = 	 {54},
  OPTnumber = 	 {},
  pages = 	 {1435--1460},
  OPTmonth = 	 {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

@article{MATS:SHER:06,
Author = {Matschke, Xenia and Sherlund, Shane M.},
Title = {Do Labor Issues Matter in the Determination of U.S. Trade Policy? An Empirical Reevaluation},
Journal = {American Economic Review},
Volume = {96},
Number = {1},
Year = {2006},
Month = {March},
Pages = {405-421}
}

@article{TERZ:WILS:90,
  author={Terza, Joseph V and Wilson, Paul W},
  title={{Analyzing Frequencies of Several Types of Events: A Mixed Multinomial-Poisson Approach}},
  journal={The Review of Economics and Statistics},
  year=1990,
  volume={72},
  number={1},
  pages={108-115},
  month={February}
}

@article{COAT:CONL:04,
Author = {Coate, Stephen and Conlin, Michael},
Title = {A Group Rule-Utilitarian Approach to Voter Turnout: Theory and Evidence},
Journal = {American Economic Review},
Volume = {94},
Number = {5},
Year = {2004},
Month = {December},
Pages = {1476-1504}
}

@article{ICHI:MEAL:NANN:08,
 author = {Andrea Ichino and Fabrizia Mealli and Tommaso Nannicini},
 journal = {Journal of Applied Econometrics},
 number = {3},
 pages = {305--327},
 publisher = {Wiley},
 title = {From Temporary Help Jobs to Permanent Employment: What Can We Learn from Matching Estimators and Their Sensitivity?},
 volume = {23},
 year = {2008}
}

@Article{ZELL:REVA:69,
  author={A. Zellner and N. S. Revankar},
  title={{Generalized Production Functions}},
  journal={Review of Economic Studies},
  year=1969,
  volume={36},
  number={2},
  pages={241-250},
  month={}
}

@ARTICLE{RIVE:VUON:88,
title = {Limited information estimators and exogeneity tests for simultaneous probit models},
author = {Rivers, Douglas and Vuong, Quang H.},
year = {1988},
journal = {Journal of Econometrics},
volume = {39},
number = {3},
pages = {347-366}
}


@article{KERK:KOOR:03,
 author = {Marcel Kerkhofs and Peter Kooreman},
 journal = {Journal of Applied Econometrics},
 number = {3},
 pages = {337--369},
 publisher = {Wiley},
 title = {Identification and Estimation of a Class of Household Production Models},
 volume = {18},
 year = {2003}
}

@article{HECK:79,
 ISSN = {00129682, 14680262},
 abstract = {This paper discusses the bias that results from using nonrandomly selected samples to estimate behavioral relationships as an ordinary specification error or "omitted variables" bias. A simple consistent two stage estimator is considered that enables analysts to utilize simple regression methods to estimate behavioral functions by least squares methods. The asymptotic distribution of the estimator is derived.},
 author = {James J. Heckman},
 journal = {Econometrica},
 number = {1},
 pages = {153--161},
 publisher = {[Wiley, Econometric Society]},
 title = {Sample Selection Bias as a Specification Error},
 volume = {47},
 year = {1979}
}

@Article{HECK:76,
title = {The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models},
author = {Heckman, James J.},
year = {1976},
pages = {475-492},
journal = {Annals of Economic and Social Measurement, Volume 5, number 4},
publisher = {National Bureau of Economic Research, Inc},
}

@article{SARG:58,
 author = {J. D. Sargan},
 journal = {Econometrica},
 number = {3},
 pages = {393--415},
 publisher = {[Wiley, Econometric Society]},
 title = {The Estimation of Economic Relationships using Instrumental Variables},
 volume = {26},
 year = {1958}
}

@Manual{SMYT:CHEN:23,
    title = {statmod: Statistical Modeling},
    author = {Gordon Smyth and Lizhong Chen and Yifang Hu and Peter Dunn and Belinda Phipson and Yunshun Chen},
    year = {2023},
    note = {R package version 1.5.0},
    url = {https://CRAN.R-project.org/package=statmod},
  }

@Article{DUCH:LAFA:10,
    title = {Computing the distribution of quadratic forms: Further comparisons between the Liu-Tang-Zhang approximation and exact methods},
    author = {P. Duchesne and P. Lafaye {de Micheaux}},
    journal = {Computational Statistics and Data Analysis},
    year = {2010},
    pages = {858-862},
    volume = {54},
}

@article{IVAL:LADO:OSSA:SIMI:96,
	title = {Comparing Fourier and translog specifications of multiproduct technology: Evidence from an incomplete panel of French farmers},
	author = {Ivaldi, Marc and Ladoux, Norbert and Ossard, {Hervé} and Simioni, Michel},
	year = {1996},
	month = {11},
	date = {1996-11},
	journal = {Journal of Applied Econometrics},
	pages = {649--667},
	volume = {11},
	number = {6},
	langid = {en}
}

@article{WICH:WILK:08,
 ISSN = {00359254, 14679876},
 abstract = {We consider an extension of conventional univariate Kaplan-Meier-type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas-type estimator which adapts the non-parametric conditional hazard rate estimator of Beran to more typical data situations in applied analysis. We show with simulations that the estimator has nice finite sample properties and our implementation appears to be fast. As an application we estimate non-parametric conditional quantile functions with German administrative unemployment duration data.},
 author = {Laura Wichert and Ralf A. Wilke},
 journal = {Journal of the Royal Statistical Society. Series C (Applied Statistics)},
 number = {1},
 pages = {117--126},
 publisher = {[Wiley, Royal Statistical Society]},
 title = {Simple Non-Parametric Estimators for Unemployment Duration Analysis},
 volume = {57},
 year = {2008}
}

@article{SUEY:95,
 ISSN = {08837252, 10991255},
 abstract = {This paper explores the relationship between conventional models for binary response such as the probit and logit, and the proportional hazard (PH) and related specifications for grouped duration data. I outline a general class of hazard models for grouped duration data based upon the choice of period-specific distribution functions, facilitating a thorough analysis of the implications of various specifications and consideration of various issues of model identification. This class of models nests, among others, the proportional hazard, probit, and logit specifications for interval survival. I consider the implications of various specifications for hazard behaviour, focusing on familiar specifications. While the specifications will generally yield results that are quite similar along a number of dimensions, there are significant differences. The probit model generates non-proportional effects of variables on the discrete hazard, while the logit and PH tend to show only slight non-proportionality. Furthermore, while the effects of variables on the derivatives are considerably larger for the probit specification, the time-pattern of the probit effects is relatively insensitive to changes in explanatory variables. I illustrate these issues by providing an example taken from Katz's (1986) unemployment data from the Panel Study of Income Dynamics.},
 author = {Glenn T. Sueyoshi},
 journal = {Journal of Applied Econometrics},
 number = {4},
 pages = {411--431},
 publisher = {Wiley},
 title = {A Class of Binary Response Models for Grouped Duration Data},
 volume = {10},
 year = {1995}
}

@article{BHAT:95,
title = "A heteroscedastic extreme value model of intercity travel mode choice",
journal = "Transportation Research Part B: Methodological",
volume = "29",
number = "6",
pages = "471 - 483",
year = "1995",
issn = "0191-2615",
url = "https://www.sciencedirect.com/science/article/pii/0191261595000156",
author = "Chandra R. Bhat",
abstract = "Estimation of disaggregate mode choice models to estimate
                  the ridership share on a proposed new (or improved)
                  intercity travel service and to identify the modes
                  from which existing intercity travelers will be
                  diverted to the new or upgraded service constitutes
                  a critical part of evaluating alternative travel
                  service proposals to alleviate intercity travel
                  congestion. This paper develops a new
                  heteroscedastic extreme value model of intercity
                  mode choice that overcomes the ‘independence of
                  irrelevant alternatives’ (IIA) property of the
                  commonly used multinomial logit model. The proposed
                  model allows a more flexible cross-elasticity
                  structure among alternatives than the nested logit
                  model. It is also simple, intuitive and much less of
                  a computational burden than the multinomial probit
                  model. The paper discusses the non-IIA property of
                  the heteroscedastic extreme value model and presents
                  an efficient and accurate Gaussian quadrature
                  technique to estimate the heteroscedastic model
                  using the maximum likelihood method. The multinomial
                  logit, alternative nested logit structures, and the
                  heteroscedastic model are estimated to examine the
                  impact of improved rail service on business travel
                  in the Toronto-Montreal corridor. The nested logit
                  structures are either inconsistent with utility
                  maximization principles or are not significantly
                  better than the multinomial logit model. The
                  heteroscedastic extreme value model, however, is
                  found to be superior to the multinomial logit
                  model. The heteroscedastic model predicts smaller
                  increases in rail shares and smaller decreases in
                  non-rail shares than the multinomial logit in
                  response to rail-service improvements. It also
                  suggests a larger percentage decrease in air share
                  and a smaller percentage decrease in auto share than
                  the multinomial logit. Thus, the multinomial logit
                  model is likely to provide overly optimistic
                  projections of rail ridership and revenue, and of
                  alleviation in inter-city travel congestion in
                  general, and highway traffic congestion in
                  particular. These findings point to the limitations
                  of the multinomial logit and nested logit models in
                  studying intercity mode choice behavior and to the
                  usefulness of the heteroscedastic model proposed in
                  this paper."
}

@article{KOPP:WEN:00,
title = "The paired combinatorial logit model: properties, estimation and application",
journal = "Transportation Research Part B: Methodological",
volume = "34",
number = "2",
pages = "75 - 89",
year = "2000",
issn = "0191-2615",
url = "https://www.sciencedirect.com/science/article/pii/S0191261599000120",
author = "Frank S. Koppelman and Chieh-Hua Wen",
keywords = "Discrete choice, Extreme value models, Intercity travel, Logit, Mode choice",
abstract = "The Independence of Irrelevant Alternatives (IIA) property
                  of the multinomial logit (MNL) model imposes the
                  restriction of zero covariance between the utilities
                  of pairs of alternatives. This restriction is
                  inappropriate for many choice situations; those in
                  which some pairs or sets of alternatives share the
                  same unobserved attributes. The nested logit (NL)
                  model relaxes the zero covariance restriction of the
                  MNL model but imposes the restriction of equal
                  covariance among all alternatives in a common nest
                  and zero covariance otherwise. The paired
                  combinatorial logit (PCL) model relaxes these
                  restrictions further by allowing different
                  covariances for each pair of alternatives. This
                  relaxation enables the estimation of differential
                  competitive relationships between each pair of
                  alternatives. The closed form of the PCL model
                  retains the computational advantages of other logit
                  models while the more flexible error correlation
                  structure, compared to the MNL model and NL models,
                  enables better representation of many choice
                  situations. This paper describes the derivation,
                  structure, properties and estimation of the PCL
                  model. The empirical results demonstrate that the
                  PCL model is statistically superior to the MNL and
                  NL models and may lead to importantly different
                  travel forecasts and policy decisions."
}

@article{WEN:KOPP:01,
title = "The generalized nested logit model",
journal = "Transportation Research Part B: Methodological",
volume = "35",
number = "7",
pages = "627 - 641",
year = "2001",
issn = "0191-2615",
url = "https://www.sciencedirect.com/science/article/pii/S019126150000045X",
author = "Chieh-Hua Wen and Frank S Koppelman",
keywords = "Discrete choice, Random utility models, Travel demand, Logit, Intercity travel",
abstract = "The generalized nested logit (GNL) model is a new member
                  of the generalized extreme value family of
                  models. The GNL provides a higher degree of
                  flexibility in the estimation of substitution or
                  cross-elasticity between pairs of alternatives than
                  previously developed generalized extreme value (GEV)
                  models. The GNL model includes the paired
                  combinatorial logit (PCL) and cross-nested logit
                  (CNL) models as special cases. It also includes the
                  product differentiation (PD) model, which represents
                  the elasticity structure associated with
                  multi-dimensional choices, and the ordered
                  generalized extreme value model, which represents
                  the elasticity structure associated with ordered
                  alternatives, as special cases. The GNL model
                  includes the two-level nested logit (NL) model as a
                  special case and can approximate closely multi-level
                  nested logit models. It accommodates differential
                  cross-elasticity among pairs of alternatives through
                  the fractional allocation of each alternative to a
                  set of nests, each of which has a distinct logsum or
                  dissimilarity parameter. An empirical example of
                  intercity mode choice confirms the statistical
                  superiority of the GNL model to the paired
                  combinatorial logit, cross-nested logit and nested
                  logit models and indicates important differences in
                  cross-elasticity relationships across pairs of
                  alternatives."
}

@article{LEON:MIGU:17,
Author = {León, Gianmarco and Miguel, Edward},
Title = {Risky Transportation Choices and the Value of a Statistical Life},
Journal = {American Economic Journal: Applied Economics},
Volume = {9},
Number = {1},
Year = {2017},
Month = {January},
Pages = {202-28},
DOI = {10.1257/app.20160140},
URL = {https://www.aeaweb.org/articles?id=10.1257/app.20160140}}

@Article{CROI:20,
  author = 	 {Croissant, Yves},
  title = 	 {Estimation of Random Utility  Models in R: The mlogit Package"},
  journal = 	 {Journal of Statistical Software},
  year = 	 {2020},
  OPTkey = 	 {},
  volume = 	 {95},
  number = 	 {11},
  pages = 	 {1--41},
  doi =          {10.18637/jss.v095.i11},
  OPTmonth = 	 {},
  OPTnote = 	 {},
  OPTannote = 	 {}
}

