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Towards a general large sample theory for regularized estimators

Michael Jansson and Demian Pouzo
Cemmap Working Paper CWP63/19

We present a general framework for studying regularized estimators; such estimators are pervasive in estimation problems wherein “plug-in” type estimators are either ill-defined or ill-behaved. Within this framework, we derive, under primitive conditions, consistency and a generalization of the asymptotic linearity property. We also provide data-driven methods for choosing tuning parameters that, under some conditions, achieve the aforementioned properties. We illustrate the scope of our approach by studying a wide range of applications, revisiting known results and deriving new ones.

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Journal article | Macroeconomic Dynamics
Consumption Euler equations are important tools in empirical macroeconomics. When estimated on micro data, they are typically linearized, so standard IV or GMM methods can be employed to deal with the measurement error that is endemic to survey data. However, linearization, in turn, may induce ...