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We use a switching probit model and the income-limit-based structure of Medicaid eligibility for children to estimate treatment effects of nonmarginal Medicaid expansions on Medicaid takeup, private i...
We estimate the labor market effect of attending a highly selective college, using the College and Beyond Survey linked to Social Security Administration data. We extend earlier work by estimating eff...
We investigate peer effects in weight gain by exploiting a natural experiment, roommate assignments of 751 male and 845 female first-year college students. Results indicate that females are subject to...
The Centers for Medicare and Medicaid Services (CMS) has calculated and disseminated an overall contract quality star rating system (from one to five stars) for all Medicare Advantage (MA) contracts s...
Spatial autocorrelation is a parameter of importance for network data analysis. To estimate spatial autocorrelation, maximum likelihood has been popularly used. However, its rigorous implementation re...
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
We describe the spivreg command, which estimates the parameters of linear cross-sectional spatial-autoregressive models with spatial-autoregressive disturbances, where the model may also contain add...
Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets.
We study the estimation of tail probabilities in a queue via a semi-parametric estimator based on the maximum value of the workload, observed over the sampled time interval. Logarithmic consistency an...
Although Strategy research aims to understand how firm actions have differential effects on performance, most empirical research estimates the average effects of these actions across firms. This paper...
This paper presents a randomization-based framework for estimating causal effects under interference between units. We develop the case of estimating average unit-level causal effects from a randomize...
When evaluating the efficacy of social programs and medical treatments using randomized experiments, the estimated overall average causal effect alone is often of limited value and the researchers mus...
Estimation of the long-term health effects of air pollution is a challenging task, especially when modelling small-area disease incidence data in an ecological study design. The challenge comes from t...
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...

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