Centre for microdata methods and practice
The cemmap working paper series publishes papers expanding the frontiers of knowledge in microdata methods and practice. Martin Weidner is the editor of the working paper series.
We study high-dimensional linear models with error-in-variables. Such models are motivated by various applications in econometrics,… Continue reading.
This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions… Continue reading.
One of the main objectives of empirical analysis of experiments and quasi-experiments is to inform policy… Continue reading.
This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization…. Continue reading.
This paper studies inference on fixed effects in a linear regression model estimated from network data…. Continue reading.
This paper studies identification and estimation of the distribution of bidder valuations in an incomplete model… Continue reading.
We revisit the classic semiparametric problem of inference on a low dimensional parameter θ0 in the… Continue reading.
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially… Continue reading.
Robins et al. (2008, 2016b) applied the theory of higher order infuence functions (HOIFs) to derive… Continue reading.
In nonlinear panel models with fixed effects and fixed-T, the incidental parameter problem poses identification difficulties… Continue reading.
We study social learning in a continuous action space experiment. Subjects, acting in sequence, state their… Continue reading.
Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze… Continue reading.
This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments…. Continue reading.
This paper provides a framework for identifying preferences in a large network where links are pairwise… Continue reading.
Since Quetelet’s work in the 19th century social science has iconified “the average man”, that hypothetical… Continue reading.
Models of unobserved heterogeneity, or frailty as it is commonly known in survival analysis, can often… Continue reading.
Nonparametric maximum likelihood estimation of general mixture models pioneered by the work of Kiefer and Wolfowitz… Continue reading.
Statistical models of unobserved heterogeneity are typically formalized as mixtures of simple parametric models and interest… Continue reading.
Saez (2010) introduced an influential estimator that has become known as the bunching estimator. Using this… Continue reading.
There are many interesting and widely used estimators of a functional with finite semi-parametric variance bound… Continue reading.