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.
Empirical Welfare Maximization (EWM) is a framework that can be used to select welfare program eligibility… Continue reading.
Empirical research typically involves a robustness-efficiency tradeoff. A researcher seeking to estimate a scalar parameter can… Continue reading.
High-dimensional covariates often admit linear factor structure. To effectively screen correlated covariates in high-dimension, we propose… Continue reading.
This paper presents an empirical model of sponsored search auctions where advertisers are ranked by bid… Continue reading.
Standard methods for estimating production functions in the Olley and Pakes (1996) tradition require assumptions on… Continue reading.
We test the null hypothesis that two parameters (μ1,μ2) have the same sign, assuming that (asymptotically)… Continue reading.
We estimate the unconditional distribution of the marginal propensity to consume (MPC) using clustering regression applied… Continue reading.
This paper proposes empirically tractable multidimensional matching models, focusing on worker-job matching. We generalize the parametric… Continue reading.
Slope coefficients in rank-rank regressions are popular measures of intergenerational mobility. In this paper, we first… Continue reading.
The leading strategy for analyzing unstructured data uses two steps. First, latent variables of economic interest… Continue reading.
The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice…. Continue reading.
This article generalizes and extends the kernel block bootstrap (KBB) method of Parente and Smith (2018,… Continue reading.
We investigate the consequences of discreteness in the assignment variable in regression-discontinuity designs for cases where… Continue reading.
This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured…. Continue reading.
We develop a practical way of addressing the Errors-In-Variables (EIV) problem in the Generalized Method of… Continue reading.
When evaluating partial effects, it is important to distinguish between structural endogeneity and measurement errors. In… Continue reading.
Identification based on higher moments has drawn increasing theoretical attention and been widely adopted in empirical… Continue reading.
This paper proposes an information-based inference method for partially identified parameters in incomplete models that is… Continue reading.
Many structural econometric models include latent variables on whose probability distributions one may wish to place… Continue reading.