identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
Quant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actioncrete choice model with a terminating actionPatrick Bajari1,2 • Chenghuan Sean CI1U* 1 * 3 • Denis Nekipelov4 • Minjung Park5Received: s February 2016 / Accepted: 27 October 20161 Published online: 3 December 2016identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
of agents’ time preferences. Then we prove conditions under which the per-period utilities are identified for all actions in the agent's choice-set. Quant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionr uses a two-step approach that does not use either backward induction or forward simulation. OurChcnghuan Scan Chu's work on this paper was conducted before employment at Facebook.Electronic supplementary material The online version of this article(doi:IO. |(K)7/sl 1129-016-9176-3) contains supplem identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionentary material, which is available to authorized users.S3 Minjung Parkmpark@haas.bcrkclcy.eduPatrick Bajaribajari@uw.eduChcnghuan Scan Chuseanehu@gmaidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
il.comDenis Nekipelovdcnis.nckipclov@gmail.com1 University of Washington, Seattle, WA, USA- NBER. Cambridge. MA. USA4 Facebook. Menlo Park, CA. USA4 UQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actiong standard statistical packages without the need to write specialized computational routines, as it involves linear (or nonlinear) projections only. Monte Carlo studies demonstrate the superior performance of our estimator compared with existing two-step estimation methods. Monte Carlo studies furth identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actioner demonstrate that the ability to identify the per-period utilities for all actions is crucial for counterfactual predictions. As an empirical illustidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
ration, we apply the estimator to the optimal default behavior of subprime mortgage borrowers, and the results show that the ability to identify the dQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actiondictions. These findings highlight the empirical relevance of key identification results of the paper.Keywords Finite horizon optimal stopping problem • Time preferences • Semiparametric estimationJEL Classification C14 • C18 • C501 IntroductionIn this paper, we study finite-horizon dynamic discrete identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action choice problems in which the agent’s set of potential choices includes a terminating action that ends the decision problem. We provide identificationidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
results and a multi-step estimation procedure for this important subset of dynamic discrete choice models.Our first result provides conditions for thQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actioncredit markets, purchases of durable goods, and firms’ investment decisions. In general, it is not possible to identify time preferences in dynamic discrete choice models: doing so rather requires special conditions to hold (Rust 1994: Magnac and Thesmar 2002). Some researchers have obtained identif identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionication using experimental data (see Frederick et al. 2002 for a review of the literature). Likew ise. Dubé et al. (2014) discuss a survey design thatidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
enables joint identification of utility and discount functions.In the non-experimental literature, identification has relied on identification-at-infQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionnac and Thesmar 2002; Fang and Wang 2015). or observing agents' final-period behavior in finite horizon problems. The last approach is obviously only feasible without data truncation. In this case, the period utilities can be identified from the static decision problem in the final period, allow ing identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action the discount factor to be identified based on the remaining temporal variation in observed behavior. For the intuition in the case of continuous choiidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
ce variables, see Duffle and Singleton (1997). Yao et al. (2012) and Chung et al. (2014). Our paper advances this argument further by proving identifiQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionel is “intrinsically” non-stationary even if allIdentification of a finite horizon dynamic discrete choice model273primitive objects are time-homogeneous, allowing US to identify the discount factor based on the variation over time in agents’ choice probabilities.Our second identification result sho identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionws that, under certain conditions (including availability of final period data), the actual levels of agents’ payoffs from various actions—and not jusidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
t the differences in utility between them—are identified alongside the discount factor. In such cases, there is no need to normalize the payoff from oQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action0). Norets and Tang (2014) and Kalouptsidi et al. (2016) showed that certain counterfactual conditional choice probabilities (CCPs) are not identified when only the differences in utility, but not the levels, are known. Our identification result thus has practical importance, given that counterfactu identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actional analysis is often the ultimate goal w hen researchers employ structural models.To the best of our knowledge, this is a novel identification result,identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
as the prior literature on dynamic discrete choice models has typically either normalized or relied on additional data to pin down the per-period payQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actions as follows. In any period before the last, the agent's continuation value from choosing a non-terminal action (but not from choosing the terminal action) includes an option value of being able to choose the terminal action in a future period. This option value depends on the level of the utility a identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionssociated with the terminal action, and also diminishes toward zero in the final period because there are no remaining periods at that point. Thereforidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
e, by examining how the relative choice probabilities between the non-terminating actions and the terminating action differ in the final period comparQuant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actiontion (along w ith utilities of other choices).In addition to providing identification results, we propose an estimation procedure that does not require backward induction or data from the final periods. The procedure is conceptually distinct from multi-step estimation procedures for infinite horizon identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action problems such as Pesendorfer and Schmidt-Dengler (2008). as we must take into account the non-stationarity of agents’ optimal behavior due to the preidentification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action
sence of a final period. Our estimation method exploits Hotz and Miller’s (1993) intuition that, when there is a terminating action, the continuation Quant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic disc identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating actionof the agents’ expectations about their continuation values, and use the estimates to recover agents’ preferences w ithin a regression framework.1 The resulting estimator involves only linear (or nonlinear) projections and does not require simulation. Our method is thus computationally light, easily identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action scalable to data-rich settings, and can be implemented using predefined procedures from standard statistical software such as R. STATA or MATLAB.Quant Mark Econ (2016) 14:271-323 DOI 10.1007/sl 1129-016-9176-3CrossMarkIdentification and semiparametric estimation of a finite horizon dynamic discGọi ngay
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