This monograph presents the basics of the composite marginal likelihood (CML) inference approach, discussing the asymptotic properties of the CML estimator and the advantages and limitations of the approach. The composite marginal likelihood (CML) inference approach is a relatively simple...

Nonparametric estimators are widely used to estimate the productive efficiency of firms and other organizations, but often without any attempt to make statistical inference. Recent work has provided statistical properties of these estimators as well as methods for making statistical inference,...

Despite the widespread use of graphs in empirical research, little is known about readers' ability to process the statistical information they are meant to convey ("visual inference"). We study visual inference within the context of regression discontinuity (RD) designs by measuring how...

Statistical inferences for weights of the global minimum variance portfolio (GMVP) are of both theoretical and practical relevance for mean-variance portfolio selection. Daily realized GMVP weights depend only on realized covariance matrix computed from intraday highfrequency returns. In this...

The focus of this paper is on starting a critical discussion on the state of econometrics. The problem of information recovery in economics is discussed, and information theoretic methods are suggested as an estimation and inference framework for analyzing questions of a causal nature and...

The purpose of this article is to propose that we focus the teaching of the introductory statistics course not merely on the statistical tools to be studied, but on the scientific thinking that they engender. Students must be taught that science is based on the testing of theories and shown how...

Motivated by Manski and Tamer (2002) and especially their partial identification analysis of the regression model where one covariate is only interval-measured, we present two extensions. Manski and Tamer (2002) propose two estimation approaches in this context, focussing on general results. The...

Empirical applications of poverty measurement often have to deal with a stochastic weighting variable such as household size. Within the framework of a bivariate distribution function defined over income and weight, I derive the limiting distributions of the decomposable curves. The poverty line...

Kakwani (Econometrica, Vol. 48, No. 2, p. 437-446 (1980)) introduced the S-Gini poverty indices as a generalization of Sen's poverty index. I propose a sample estimator for the indices and establish its asymptotic normality under weak conditions. An explicit variance formula is presented. The...

Quadratic functions are often used in regression to infer the existence of an extremum in a relationship although tests of the location of the extremum are rarely performed. We investigate the construction of the following confidence intervals: Delta, Fieller, estimated first derivative,...