Papers

Forthcoming
Honoré, Bo E., and Luojia Hu. Forthcoming. “Selection Without Exclusion”. Link to Working Paper
2019
Honoré, Bo E., and Ekaterini Kyriazidou. 2019. “Identification in Binary Response Panel Data Models: Is Point-Identification More Common Than We Thought?” Annals of Economics and Statistics, no. 134: 207-226. Publisher's Version Abstract
This paper investigates identification in binary response models with panel data. Conditioning on sufficient statistics can sometimes lead to a conditional maximum likelihood approach that can be used to identify and estimate the parameters of interest in such models. Unfortunately it is often difficult or impossible to find such sufficient statistics, and even if it is possible, the approach sometimes leads to conditional likelihoods that do not depend on some interesting parameters. Using a range of different data generating processes, this paper calculates the identified regions for parameters in panel data logit AR(2) and logit VAR(1) models for which it is not known whether the parameters are identified or not. We find that identification might be more common than was previously thought, and that the identified regions for non-identified objects may be small enough to be empirically useful.
Honoré, Bo E., and Ekaterini Kyriazidou. 2019. “Chapter 8 - Panel Vector Autoregressions With Binary Data.” Panel Data Econometrics, edited by Mike Tsionas, 197 - 223. Academic Press. Publisher's Version
2018
Honoré, Bo E., and Áureo de Paula. 2018. “A new model for interdependent durations.” Quantitative Economics 9 (3): 1299-1333. Publisher's Version Abstract
This paper introduces a bivariate version of the generalized accelerated failure time model. It allows for simultaneity in the econometric sense that the two realized outcomes depend structurally on each other. Another feature of the proposed model is that it will generate equal durations with positive probability. Our approach takes a stylized economic model that leads to a univariate generalized accelerated failure time model as a starting point. In this model, agents decide when to transition from an initial state to a new one, and the covariates influence the difference in the utility flow in the two states. We introduce simultaneity by allowing the utility flow to depend on the status of the other person. The econometric model is then completed by assuming that the observed outcome is the Nash bargaining solution in that simple economic model. The advantage of this approach is that it includes independent realizations from the generalized accelerated failure time model as a special case, and deviations from this special case can be given an economic interpretation. We established identification under assumptions that are similar to those in the literature on nonparametric estimation of duration models. We illustrate the model by studying the joint retirement decisions in married couples using the Health and Retirement Study. In that example, it seems reasonable to allow for the possibility that each partner's optimal retirement time depends on the retirement time of the spouse. Moreover, the data suggest that the wife and the husband retire at the same time for a nonnegligible fraction of couples. The main empirical finding is that the simultaneity is economically important. In our preferred specification, the indirect utility associated with being retired increases by approximately when one's spouse retires.
Honoré, Bo E., and Luojia Hu. 2018. “Easy bootstrap-like estimation of asymptotic variances.” Economics Letters 171: 46 - 50. Publisher's Version Abstract
The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a “Poor (Wo)man’s Bootstrap” based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.
Honoré, Bo E., and Hu Luojia. 2018. “Simpler bootstrap estimation of the asymptotic variance of U-statistic-based estimators.” The Econometrics Journal 21 (1): 1-10. Publisher's Version
2017
Honoré, Bo E., and Michaela Kesina. 2017. “Estimation of Some Nonlinear Panel Data Models With Both Time-Varying and Time-Invariant Explanatory Variables.” Journal of Business & Economic Statistics 35 (4). Taylor & Francis: 543-558. Publisher's Version
Honoré, Bo E., and Luojia Hu. 2017. “Poor (Wo)man's Bootstrap.” Econometrica 85 (4). Blackwell Publishing Ltd: 1277–1301. Publisher's Version
2014
Sule, Alan, Honoré Bo E., Hu Luojia, and Leth-Petersen Søren. 2014. “Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation.” Journal of Econometric Methods 3 (1): 1-20. Publisher's Version Abstract
This paper constructs estimators for panel data regression models with individual specific heterogeneity and two-sided censoring and truncation. Following Powell the estimation strategy is based on moment conditions constructed from re-censored or re-truncated residuals. While these moment conditions do not identify the parameter of interest, they can be used to motivate objective functions that do. We apply one of the estimators to study the effect of a Danish tax reform on household portfolio choice. The idea behind the estimators can also be used in a cross sectional setting.
2012
Honoré, Bo E., Daniel Kaufmann, and Sarah Lein. 2012. “Asymmetries in Price-Setting Behavior: New Microeconometric Evidence from Switzerland.” Journal of Money, Credit and Banking 44. Blackwell Publishing Inc: 211–236. Publisher's Version
2010
D'Addio, Anna, and Bo Honoré. 2010. “Duration Dependence and Timevarying Variables in Discrete Time Duration Models.” Brazilian Review of Econometrics 30 (2): 487–527. Publisher's Version Abstract
This paper considers estimation of a dynamic discrete choice model with second order state dependence in the presence of strictly exogenous time-varying explanatory variables. We propose a new method for estimating such models, and a small Monte Carlo study suggests that the method performs well in practice. The method is used to test for duration dependence in labour market spells for young people in France. The novelty in the application is that we are able to control for time-varying explanatory variables. In a discrete time duration model, duration dependence will result in second order state dependence, and the paper therefore also adds to the literature on estimation of duration models with unobserved heterogeneity.
Honoré, Bo E., and Aureo de Paula. 2010. “Interdependent Durations.” The Review of Economic Studies 77 (3). Oxford University Press: 1138-1163. Publisher's Version Abstract
This paper studies the identification of a simultaneous equation model involving duration measures. It proposes a game theoretic model in which durations are determined by strategic agents. In the absence of strategic motives, the model delivers a version of the generalized accelerated failure time model. In its most general form, the system resembles a classical simultaneous equation model in which endogenous variables interact with observable and unobservable exogenous components to characterize an economic environment. In this paper, the endogenous variables are the individually chosen equilibrium durations. Even though a unique solution to the game is not always attainable in this context, the structural elements of the economic system are shown to be semi-parametrically identified. We also present a brief discussion of estimation ideas and a set of simulation studies on the model.
Honoré, Bo E., and Luojia Hu. 2010. “Estimation of a transformation model with truncation, interval observation and time-varying covariates.” Econometrics Journal 13 (1). Blackwell Publishing Ltd: 127–144. Publisher's Version
2007
Frederiksen, Anders, Bo E. Honoré, and Luojia Hu. 2007. “Discrete time duration models with group-level heterogeneity.” Journal of Econometrics 141 (2): 1014 - 1043. Publisher's Version
Aradillas-Lopez, Andres, Bo E. Honoré, and James L. Powell. 2007. “Pairwise Difference Estimation With Nonparametric Control Variables.” International Economic Review 48 (4): 1119-1158. Publisher's Version
2006
Honoré, Bo E., and Elie T. Tamer. 2006. “Bounds on Parameters in Panel Dynamic Discrete Choice Models.” Econometrica 74 (3): 611-629. Publisher's Version
Honoré, Bo E., and Adriana Lleras-Muney. 2006. “Bounds in Competing Risks Models and the War on Cancer.” Econometrica 74 (6): 1675-1698. Publisher's Version
2005
Honoré, Bo E., and James L. Powell. 2005. “Pairwise Difference Estimators for Nonlinear Models.” Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, edited by Donald W. K. Andrews and James H.Editors Stock, 520–553. Cambridge University Press. Publisher's Version
2004
Honoré, Bo E., and Luojia Hu. 2004. “On the Performance of Some Robust Instrumental Variables Estimators.” Journal of Business and Economic Statistics 22 (1): 30-39. Publisher's Version Abstract
This article considers instrumental variables versions of the quantile and rank regression estimators. The asymptotic properties of the estimators are discussed, and a small-scale Monte Carlo study is used to illustrate the potential advantages of the approach. Finally, the proposed methods are implemented for two empirical examples.

Pages