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on Discrete Choice Models |
| By: | Myrto Kalouptsidi; Paul T. Scott; Eduardo Souza-Rodrigues |
| Abstract: | In structural dynamic discrete choice models, the presence of serially correlated unobserved states and state variables that are measured with error may lead to biased parameter estimates and misleading inference. In this paper, we show that instrumental variables can address these issues, as long as measurement problems involve state variables that evolve exogenously from the perspective of individual agents (i.e., market-level states). We define a class of linear instrumental variables estimators that rely on Euler equations expressed in terms of conditional choice probabilities (ECCP estimators). These estimators do not require observing or modeling the agent’s entire information set, nor solving or simulating a dynamic program. As such, they are simple to implement and computationally light. We provide constructive identification arguments to identify the model primitives, and establish the consistency and asymptotic normality of the estimator. A Monte Carlo study demonstrates the good finite-sample performance of the ECCP estimator in the context of a dynamic demand model for durable goods. |
| JEL: | C13 C35 C36 C51 C61 |
| Date: | 2018–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:25134&r=dcm |
| By: | S. Balia; R. Brau; D. Moro |
| Abstract: | We investigate long distance hospitalizations in a setting of patients with free mobility by studying the elective admissions of patients for cancers of the digestive system and distinguishing between local (located in the region of residence) and distant hospitals (located at very long distances in non-boundary regions). We used data from hospital discharge records of patients enrolled in the local healthcare systems of two insular Italian regions. We model mobility towards alternative hospitals as a discrete choice process determined by geographical distance, clinic quality and other hospital characteristics through a mixed logit model that controls for patients' heterogeneity. Quality plays a relevant role in the choice of distant hospitals, whereas it does not affect the choice of local hospitals. Patients are willing to travel at least 14 km farther to be cured in a distant hospital with a clinical quality indicator that increases from the 75th to the 25th percentile. The willingness to travel is greater for younger and higher educated patients. Important differences emerge vis-à-vis the role of hospital pull factors. Our findings support the idea that long-distance mobility is a distinctive phenomenon that requires further study. |
| Keywords: | hospital choice;healthcare demand;quality of care;discrete choice models |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:cns:cnscwp:201810&r=dcm |
| By: | Ma, Yin |
| Keywords: | Experimental Economics, Environmental and Nonmarket Valuation, Natural Resource Economics |
| Date: | 2018–06–20 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea18:274042&r=dcm |