-
1also available:Exemplare Uni Bonn from 1998
-
2by Chernozhukov, Victor Chetverikov, Denis Demirer, Mert Duflo, Esther Hansen, Christian Newey, Whitney Robins, James Published in The econometrics journal (01.02.2018)“...Summary We revisit the classic semi‐parametric problem of inference on a low‐dimensional parameter θ0 in the presence of high‐dimensional nuisance parameters...”
-
3“...Summary In this paper, we demonstrate that standard central limit theorem (CLT) results do not hold for means of non‐parametric, conditional efficiency...”
-
4by Ivan A. Canay Published in The econometrics journal (01.01.2011)“...This paper provides a set of sufficient conditions that point identify a quantile regression model with fixed effects. It also proposes a simple transformation...”
-
5by Alexander Chudik M. Hashem Pesaran Elisa Tosetti Published in The econometrics journal (01.01.2011)“...This paper introduces the concepts of time-specific weak and strong cross-section dependence, and investigates how these notions are related to the concepts of...”
-
6“...This paper proposes a bias-adjusted version of Breusch and Pagan (1980) Lagrange multiplier (LM) test statistic of error cross-section independence, in the...”
-
7“...Summary Inference based on cluster‐robust standard errors in linear regression models, using either the Student's t‐distribution or the wild cluster bootstrap,...”
-
8by Charles F. Manski Published in The econometrics journal (01.01.2013)“...This paper studies identification of potential outcome distributions when treatment response may have social interactions. Defining a person's treatment...”
-
9by O. E. Barndorff-Nielsen P. Reinhard Hansen A. Lunde N. Shephard Published in The econometrics journal (01.01.2009)“...Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we...”
-
10“...Summary The estimation of large covariance and precision matrices is fundamental in modern multivariate analysis. However, problems arise from the statistical...”
-
11“...The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in...”
-
12by Galichon, Alfred Published in The econometrics journal (01.06.2017)“...Summary This paper surveys recent applications of methods from the theory of optimal transport to econometric problems...”
-
13by Calonico, Sebastian Published in The econometrics journal (2020)“...Summary Modern empirical work in regression discontinuity (RD) designs often employs local polynomial estimation and inference with a mean square error (MSE)...”
-
14by Josep Lluís Carrion-i-Silvestre Tomás del Barrio-Castro Enrique López-Bazo Published in The econometrics journal (01.01.2005)“...This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different...”
-
15“...Summary In this paper, we introduce quantile coherency to measure general dependence structures emerging in the joint distribution in the frequency domain and...”
-
16“...Abstract When estimating local average and marginal treatment effects using instrumental variables (IV), multivalued endogenous treatments are frequently...”
-
17by Anderson, Gordon Linton, Oliver Pittau, Maria Grazia Whang, Yoon-Jae Zelli, Roberto Published in The econometrics journal (01.02.2021)“...Abstract Multilateral comparison of outcomes drawn from multiple groups pervade the social sciences and measurement of their variability, usually involving...”
-
18“...Summary In order to simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural change, we introduce a time-varying...”
-
19by Kruiniger, Hugo Published in The econometrics journal (12.10.2020)“...Summary Linear generalised method of moments (GMM) estimators for dynamic panel models with predetermined or endogenous regressors suffer from a weak...”
-
20“...Abstract In this paper we consider estimation of dynamic models of recurrent events (event histories) in continuous time using censored data. We develop...”