Showing 1 - 10 of 45
The Random Utility Model (RUM) is a workhorse model for valuing new products or changes in public goods. But RUMs have been faulted along two lines. First, for including idiosyncratic errors that imply unreasonably high values for new alternatives and unrealistic substitution patterns. Second,...
Persistent link: https://www.econbiz.de/10015171628
The standard Berry, Levinsohn, and Pakes (1995) (BLP) approach to estimation of demand and supply parameters assumes that the product characteristic observed by consumers and producers but not the researcher is conditionally mean independent of observed characteristics. We extend BLP to allow...
Persistent link: https://www.econbiz.de/10013477270
This paper develops a partial-identification methodology for analyzing self-selection into alternative compensation schemes in a laboratory environment. We formulate a model of self-selection in which individuals select the compensation scheme with the largest expected valuation, which depends...
Persistent link: https://www.econbiz.de/10014447251
With count-valued outcomes y in {0,1,...,M} identification and estimation of average treatment effects raise no special considerations beyond those involved in the continuous-outcome case. If partial identification of the distribution of treatment effects is of interest, however, count-valued...
Persistent link: https://www.econbiz.de/10014247925
We use national physician-pair panel data to examine how switching electronic health record (EHR) developers affects out-of-network referrals from primary care physicians (PCPs) to specialists. We estimate a difference-in-differences model, exploiting changes in EHR developer adoption by...
Persistent link: https://www.econbiz.de/10015409894
We propose a conformant likelihood estimator with exogeneity restrictions (CLEER) for random coefficients discrete choice demand models that is applicable in a broad range of data settings. It combines the likelihoods of two mixed logit estimators--one for consumer level data, and one for...
Persistent link: https://www.econbiz.de/10015195043
We introduce a general approach for analyzing large-scale text-based data, combining the strengths of neural network language processing and generative statistical modeling to create a factor structure of unstructured data for downstream regressions typically used in social sciences. We generate...
Persistent link: https://www.econbiz.de/10015145119
Implementing a state-of-the-art machine learning technique for causal identification from text data (C-TEXT), we document that patents authored by female inventors are under-cited relative to those authored by males. Relative to what the same patent would be predicted to receive had the lead...
Persistent link: https://www.econbiz.de/10014337825
We provide a general framework for incorporating many types of micro data from summary statistics to full surveys of selected consumers into Berry, Levinsohn, and Pakes (1995)-style estimates of differentiated products demand systems. We extend best practices for BLP estimation in Conlon and...
Persistent link: https://www.econbiz.de/10014337838
Medical journals have adhered to a reporting practice that seriously limits the usefulness of published trial findings. Medical decision makers commonly observe many patient covariates and seek to use this information to personalize treatment choices. Yet standard summaries of trial findings...
Persistent link: https://www.econbiz.de/10013388817