This paper develops a new direct approach to approximating suprema of general empirical processes by a sequence of suprema of Gaussian processes, without taking the route of approximating empirical processes themselves in the sup-norm.
This paper studies identification and estimation in a binary response model with random coefficients B allowed to be correlated with regressors X.The objective is to identifiy the mean of the distribution of B and estimate a trimmed mean of this distribution.
In this paper we study nonparametric estimation in a binary treatment model where the outcome equation is of unrestricted form, and the selection equation contains multiple unobservables that enter through a nonparametric random coefficients specification.
Virtually all methods aimed at correcting for covariate measurement error in regressions rely on some form of additional information (e.g. validation data, known error distributions, repeated measurements or instruments). In contrast, we establish that the fully nonparametric classical errors-in-variables mode is identifiable from data on the regressor and the dependent variable alone, unless the model takes a very specific parametric form.
This overview of the recent econometrics literature on measurement error in nonlinear models centres on the question of the identification and estimation of general nonlinear models with measurement error.
This paper considers the case for replacing the Carli index in the Retail Prices Index for calculating price changes at the elementary aggregate level.
In parametric models a sufficient condition for local idenfication is that the vector of moment is differentiable at the true parameter with full rank derivative matrix. This paper shows that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities overwhelming linear effects.
In October 2012, the ONS announced a consultation on whether the statistical methods used to calculate the Retail Prices Index (RPI) should be changed to bring them closer in line to those used in the Consumer Prices Index (CPI). Previous IFS work has looked at how inflation rates varied across different households, using survey data on household expenditure to calculate RPI-based measures of household-specific inflation. This paper analyses whether CPI-based measures give similar results and the reasons behind any differences.
In this paper we look at lifetime inequality to address two main questions: How well does a modern tax system, based on annual information, target lifetime inequality? What aspects of the tranfser system are most progressive from a lifetime perspective?
This report, funded by the Nuffield Foundation, provides findings from a series of focus groups investigating how people think about household expenditure and what issues people may have in reporting household expenditure in a social survey context.
Currently there is no established way to measure expenditure in the context of a general purpose survey. In this report NatCen's Questionnaire Development Testing (QDT) Hub, working in collaboration with the Institute for Fiscal Studies and collaborators from Oxford and Cambridge Universities, look at how best to measure expenditure in a social survey context.
The Nuffield Foundation has funded a collaborative research team from NatCen Social Research, the Institute for Fiscal Studies and Oxford and Cambridge Universities to develop a standard question or questions designed to capture household spending. This report presents the findings of this second round of cognitive testing.
This paper provides a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or equivalently, the value of a linear programming problem with a potentially infinite constraint set.
The primary concern of this article is the provision of definitions and tests for exogeneity appropriate for models defined through sets of conditional moment restrictions.
This paper characterises the semiparametric efficiency bound for a class of semiparametric models in which the unknown nuisance functions are identifi ed via nonparametric conditional moment restrictions with possibly non-nested or over-lapping conditioning sets, and the finite dimensional parameters are potentially over-identi fied via unconditional moment restrictions involving the nuisance functions.
