Publications - Michael Jansson https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Bcontroller%5D=Publications&cHash=503c577bd38ca268d95182e45c87925c en-us PURE Extension typo3support@science.au.dk (Web Department) 30 <![CDATA[Simple Local Polynomial Density Estimators]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=fcb78b5b-1475-4614-8e82-a047ee9c5a29&tx_pure_pure5%5BshowType%5D=pub&cHash=03c56b8c24a38dffcc06e6da14022102 Cattaneo, M. D., Jansson, M., Ma, X. This article introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automatic, but does not require prebinning or any other transformation of the data. We study the main asymptotic properties of the estimator, and use these results to provide principled estimation, inference, and bandwidth selection methods. As a substantive application of our results, we develop a novel discontinuity in density testing procedure, an important problem in regression discontinuity designs and other program evaluation settings. An illustrative empirical application is given. Two companion Stata and R software packages are provided.

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Forskning Wed, 01 Jul 2020 14:18:08 +0200 fcb78b5b-1475-4614-8e82-a047ee9c5a29
<![CDATA[Bootstrap-Based Inference for Cube Root Asymptotics]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=145da4fc-38ed-4151-9a37-3073d035c191&tx_pure_pure5%5BshowType%5D=pub&cHash=5fb7b5d05b1ec631ea7fd88e0c594a26 Cattaneo, M. D., Jansson, M., Nagasawa, K. This paper proposes a valid bootstrap-based distributional approximation for M-estimators exhibiting a Chernoff (1964)-type limiting distribution. For estimators of this kind, the standard nonparametric bootstrap is inconsistent. The method proposed herein is based on the nonparametric bootstrap, but restores consistency by altering the shape of the criterion function defining the estimator whose distribution we seek to approximate. This modification leads to a generic and easy-to-implement resampling method for inference that is conceptually distinct from other available distributional approximations. We illustrate the applicability of our results with four examples in econometrics and machine learning.

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Forskning Tue, 01 Sep 2020 14:18:08 +0200 145da4fc-38ed-4151-9a37-3073d035c191
<![CDATA[Two-step estimation and inference with possibly many included covariates]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=122ed60b-0d76-4e26-b6ad-d3276dd5a7b4&tx_pure_pure5%5BshowType%5D=pub&cHash=2db603332b25f399ddb5de3170b9d706 Cattaneo, M. D., Jansson, M., Xinwei, M. A. We study the implications of including many covariates in a first-step estimate entering a two-step estimation procedure. We find that a first-order bias emerges when the number of included covariates is “large” relative to the square-root of sample size, rendering standard inference procedures invalid. We show that the jackknife is able to estimate this “many covariates” bias consistently, thereby delivering a new automatic bias-corrected two-step point estimator. The jackknife also consistently estimates the standard error of the original two-step point estimator. For inference, we develop a valid post-bias-correction bootstrap approximation that accounts for the additional variability introduced by the jackknife bias-correction. We find that the jackknife bias-corrected point estimator and the bootstrap post-bias-correction inference perform excellent in simulations, offering important improvements over conventional two-step point estimators and inference procedures, which are not robust to including many covariates. We apply our results to an array of distinct treatment effect, policy evaluation, and other applied microeconomics settings. In particular, we discuss production function and marginal treatment effect estimation in detail.

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Forskning Tue, 01 Jan 2019 14:18:08 +0100 122ed60b-0d76-4e26-b6ad-d3276dd5a7b4
<![CDATA[Improved likelihood ratio tests for cointegration rank in the VAR model]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=406ec12f-d9d8-447b-886e-83fd163e31e7&tx_pure_pure5%5BshowType%5D=pub&cHash=36a3c1466876788c2e421419c09729c7 Boswijk, H. P., Jansson, M., Nielsen, M. Ø. Forskning Thu, 01 Jan 2015 14:18:08 +0100 406ec12f-d9d8-447b-886e-83fd163e31e7 <![CDATA[Manipulation Testing Based on Density Discontinuity]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=f3b1c0d9-5a87-4bbf-a05b-51b936d04d3d&tx_pure_pure5%5BshowType%5D=pub&cHash=78d810943dd08ee0ca4bc095bdee866e Cattaneo, M. D., Jansson, M., Ma, X. Forskning Mon, 01 Jan 2018 14:18:08 +0100 f3b1c0d9-5a87-4bbf-a05b-51b936d04d3d <![CDATA[Alternative asymptotics and the partially linear model with many regressors]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=da048b69-b4c8-4f03-a3d9-03f6774ae89b&tx_pure_pure5%5BshowType%5D=pub&cHash=2400f43c2fa7132d08e955515fd20ce0 Cattaneo, M. D., Jansson, M., Newey, W. K. Forskning Mon, 01 Jan 2018 14:18:08 +0100 da048b69-b4c8-4f03-a3d9-03f6774ae89b <![CDATA[Kernel-Based Semiparametric Estimators: Small Bandwidth Asymptotics and Bootstrap Consistency]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=b408cb3d-880d-4282-adbd-84135fe45ddc&tx_pure_pure5%5BshowType%5D=pub&cHash=ef4a18f110b323933e490ffcc330c9e2 Cattaneo, M. D., Jansson, M. Forskning Mon, 01 Jan 2018 14:18:08 +0100 b408cb3d-880d-4282-adbd-84135fe45ddc <![CDATA[Inference in Linear Regression Models with Many Covariates and Heteroscedasticity]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=650c5354-5342-4667-a9d1-23c127de91c6&tx_pure_pure5%5BshowType%5D=pub&cHash=08dfba602458c43e1b091e513caf67aa Cattaneo, M. D., Jansson, M., Newey, W. K. The linear regression model is widely used in empirical work in economics, statistics, and many other disciplines. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroscedasticity. Our results are obtained using high-dimensional approximations, where the number of included covariates is allowed to grow as fast as the sample size. We find that all of the usual versions of Eicker–White heteroscedasticity consistent standard error estimators for linear models are inconsistent under this asymptotics. We then propose a new heteroscedasticity consistent standard error formula that is fully automatic and robust to both (conditional) heteroscedasticity of unknown form and the inclusion of possibly many covariates. We apply our findings to three settings: parametric linear models with many covariates, linear panel models with many fixed effects, and semiparametric semi-linear models with many technical regressors. Simulation evidence consistent with our theoretical results is provided, and the proposed methods are also illustrated with an empirical application. Supplementary materials for this article are available online.

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Forskning Tue, 03 Jul 2018 14:18:08 +0200 650c5354-5342-4667-a9d1-23c127de91c6
<![CDATA[Bootstrap-Based Inference for Cube Root Consistent Estimators]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=7f06a348-e03f-4618-a726-e64e19f1eb49&tx_pure_pure5%5BshowType%5D=pub&cHash=90fa388f9de77ef23c7a8c2e35b2ea42 Cattaneo, M. D., Jansson, M., Nagasawa, K. Forskning Fri, 05 May 2017 14:18:08 +0200 7f06a348-e03f-4618-a726-e64e19f1eb49 <![CDATA[Treatment Effects with Many Covariates and Heteroskedasticity]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=c029258b-0a50-4392-aeed-f7e3b15e9f69&tx_pure_pure5%5BshowType%5D=pub&cHash=fb9047252c806204187374fecc742404 Cattaneo, M. D., Jansson, M., Newey, W. K. Forskning Mon, 03 Aug 2015 14:18:08 +0200 c029258b-0a50-4392-aeed-f7e3b15e9f69 <![CDATA[Small bandwidth asymptotics for density-weighted average derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=d3731927-c459-4ed9-9c7f-bd5047f953b4&tx_pure_pure5%5BshowType%5D=pub&cHash=6fd3712efe39d22d8008cda13b4bd869 Cattaneo, M. D., Crump, R. K., Jansson, M. This paper proposes (apparently) novel standard error formulas for the density-weighted average derivative estimator of Powell, Stock, and Stoker (Econometrica 57, 1989). Asymptotic validity of the standard errors developed in this paper does not require the use of higher-order kernels, and the standard errors are robust in the sense that they accommodate (but do not require) bandwidths that are smaller than those for which conventional standard errors are valid. Moreover, the results of a Monte Carlo experiment suggest that the finite sample coverage rates of confidence intervals constructed using the standard errors developed in this papercoincide (approximately) with the nominal coverage rates across a nontrivial range of bandwidths.

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Forskning Wed, 01 Jan 2014 14:18:08 +0100 d3731927-c459-4ed9-9c7f-bd5047f953b4
<![CDATA[Bootstrapping density-weighted average derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=71347913-10a5-4b6c-b961-d3e1101d4714&tx_pure_pure5%5BshowType%5D=pub&cHash=97b620095572cdd87e7e268153ecf5dc Cattaneo, M. D., Crump, R. K., Jansson, M. We investigate the properties of several bootstrap-based inference procedures for semiparametric density-weighted average derivatives. The key innovation in this paper is to employ an alternative asymptotic framework to assess the properties of these inference procedures. This theoretical approach is conceptually distinct from the traditional approach (based on asymptotic linearity of the estimator and Edgeworth expansions), and leads to different theoretical prescriptions for bootstrap-based semiparametric inference. First, we show that the conventional bootstrap-based approximations to the distribution of the estimator and its classical studentized version are both invalid in general. This result shows a fundamental lack of robustness of the associated, classical bootstrap-based inference procedures with respect to the bandwidth choice. Second, we present a new bootstrap-based inference procedure for density-weighted average derivatives that is more robust to perturbations of the bandwidth choice, and hence exhibits demonstrable superior theoretical statistical properties over the traditional bootstrap-based inference procedures. Finally, we also examine the validity and invalidity of related bootstrap-based inference procedures and discuss additional results that may be of independent interest. Some simulation evidence is also presented.

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Forskning Wed, 01 Jan 2014 14:18:08 +0100 71347913-10a5-4b6c-b961-d3e1101d4714
<![CDATA[Bootstrapping Kernel-Based Semiparametric Estimators]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=7eff58a9-d068-4d58-85e7-d78bfeef6808&tx_pure_pure5%5BshowType%5D=pub&cHash=9c245631aa1646c146c218943db62d48 Cattaneo, M. D. ., Jansson, M. Forskning Mon, 25 Aug 2014 14:18:08 +0200 7eff58a9-d068-4d58-85e7-d78bfeef6808 <![CDATA[Generalized Jackknife Estimators of Weighted Average Derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=6797a9ff-3fc4-4b9d-b913-c05311ab8b49&tx_pure_pure5%5BshowType%5D=pub&cHash=7183f5406de5207ab251a6130c28ce97 Cattaneo, M. D. ., Crump, R. K., Jansson, M. Forskning Tue, 01 Jan 2013 14:18:08 +0100 6797a9ff-3fc4-4b9d-b913-c05311ab8b49 <![CDATA[Nearly efficient likelihood ratio tests of the unit root hypothesis]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=e94674ed-b351-41ca-9eee-d0392c9fda47&tx_pure_pure5%5BshowType%5D=pub&cHash=8ef7bbbe72d31338b82eeb74f5fba5d4 Jansson, M., Nielsen, M. Ø. Forskning Sat, 01 Sep 2012 14:18:08 +0200 e94674ed-b351-41ca-9eee-d0392c9fda47 <![CDATA[Optimal Inference for Instrumental Variables Regression with non-Gaussian Errors]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=c5109ce3-3c14-43ae-875a-54c8c1cd4c25&tx_pure_pure5%5BshowType%5D=pub&cHash=08916b965324b21bb605323808f8767f Cattaneo, M. D., Crump, R. K., Jansson, M. Forskning Sun, 01 Jan 2012 14:18:08 +0100 c5109ce3-3c14-43ae-875a-54c8c1cd4c25 <![CDATA[Improved Likelihood Ratio Tests for Cointegration Rank in the VAR Model]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=1afad629-2454-4a13-bd49-0697a95e45b4&tx_pure_pure5%5BshowType%5D=pub&cHash=3ddc9f29e27324623379e9bcb03d9bc7 Boswijk, H. P., Jansson, M., Nielsen, M. Ø. Forskning Fri, 21 Sep 2012 14:18:08 +0200 1afad629-2454-4a13-bd49-0697a95e45b4 <![CDATA[Generalized Jackknife Estimators of Weighted Average Derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=c21b1b25-9f7d-4f92-ba23-dcc60e94c5da&tx_pure_pure5%5BshowType%5D=pub&cHash=82c764fcf4c2c01c598f013ea609afe8 Cattaneo, M. D. ., Crump, R. K., Jansson, M. Forskning Sat, 01 Jan 2011 14:18:08 +0100 c21b1b25-9f7d-4f92-ba23-dcc60e94c5da <![CDATA[Bootstrapping Density-Weighted Average Derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=b380c5a0-64c5-11df-8bd0-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=0f4df443ca08b8baa91221a97e0e02b5 Cattaneo, M. D., Crump, R. K., Jansson, M. ]]> Forskning Fri, 01 Jan 2010 14:18:08 +0100 b380c5a0-64c5-11df-8bd0-000ea68e967b <![CDATA[Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=742694c0-d9bf-11de-9e3b-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=cf6e993fbc0a77578aac19b409a5b34d Jansson, M., Nielsen, M. Ø. gressive unit root tests, Hylleberg, Engle, Granger, and Yoo (1990) developed
regression-based tests for unit roots at the seasonal frequencies in quarterly time
series. We develop likelihood ratio tests for seasonal unit roots and show that
these tests are "nearly efficient" in the sense of Elliott, Rothenberg, and Stock
(1996), i.e. that their local asymptotic power functions are indistinguishable
from the Gaussian power envelope. Currently available nearly efficient testing
procedures for seasonal unit roots are regression-based and require the choice
of a GLS detrending parameter, which our likelihood ratio tests do not.]]>
Forskning Thu, 01 Jan 2009 14:18:08 +0100 742694c0-d9bf-11de-9e3b-000ea68e967b
<![CDATA[Robust Data-Driven Inference for Density-Weighted Average Derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=c48a7be0-af2e-11de-a554-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=d83a34e9d02478889cbe0e1f8c4f3155 Cattaneo, M. D., Crump, R. K., Jansson, M. small bandwidth asymptotics developed in Cattaneo, Crump, and Jansson (2009) for density-
weighted average derivatives. The new bandwidth selector is of the plug-in variety, and is
obtained based on a mean squared error expansion of the estimator of interest. An extensive
Monte Carlo experiment shows a remarkable improvement in performance when the bandwidth-
dependent robust inference procedure proposed by Cattaneo, Crump, and Jansson (2009) is
coupled with this new data-driven bandwidth selector. The resulting robust data-driven confi-
dence intervals compare favorably to the alternative procedures available in the literature.]]>
Forskning Thu, 01 Jan 2009 14:18:08 +0100 c48a7be0-af2e-11de-a554-000ea68e967b
<![CDATA[Nearly Efficient Likelihood Ratio Tests of the Unit Root Hypothesis]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=7b69c190-9869-11de-a092-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=f7148491a71c7d86c9237d986eeddcd6 Jansson, M., Nielsen, M. Ø. "nearly efficient" testing procedures for the unit root hypothesis, i.e. tests
whose local asymptotic power functions are indistinguishable from the Gaussian
power envelope, is a test admitting a (quasi-)likelihood ratio interpretation. We
show that the likelihood ratio unit root test derived in a Gaussian AR(1) model
with standard normal innovations is nearly efficient in that model. Moreover,
these desirable properties carry over to more complicated models allowing for
serially correlated and/or non-Gaussian innovations.]]>
Forskning Thu, 01 Jan 2009 14:18:08 +0100 7b69c190-9869-11de-a092-000ea68e967b
<![CDATA[Small Bandwidth Asymptotics for Density-Weighted Average Derivatives]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=9eae28d0-263c-11dd-be51-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=464f96fff7a469ba25ab247ea40ed874 Cattaneo, M. D., Crump, R. K., Jansson, M. average derivative estimator of Powell, Stock, and Stoker (1989). Asymptotic validity of
the standard errors developed in this paper does not require the use of higher-order
kernels and the standard errors are "robust" in the sense that they accommodate
(but do not require) bandwidths that are smaller than those for which conventional
standard errors are valid. Moreover, the results of a Monte Carlo experiment suggest that
the finite sample coverage rates of con…dence intervals constructed using the standard
errors developed in this paper coincide (approximately) with the nominal coverage rates
across a nontrivial range of bandwidths.]]>
Forskning Tue, 01 Jan 2008 14:18:08 +0100 9eae28d0-263c-11dd-be51-000ea68e967b
<![CDATA[Semiparametric Power Envelopes for Tests of the Unit Root Hypothesis]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=3b4aa2b0-e43c-11dc-9afb-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=50269e8cf2dfb203a7c3c32f96752093 Jansson, M. the unit root hypothesis in a zero-mean AR(1) model. The power envelopes are
derived using the limits of experiments approach and are semiparametric in the
sense that the underlying error distribution is treated as an unknown infinitedimensional
nuisance parameter. Adaptation is shown to be possible when the
error distribution is known to be symmetric and to be impossible when the
error distribution is unrestricted. In the latter case, two conceptually distinct
approaches to nuisance parameter elimination are employed in the derivation
of the semiparametric power bounds. One of these bounds, derived under an
invariance restriction, is shown by example to be sharp, while the other, derived
under a similarity restriction, is conjectured not to be globally attainable.]]>
Forskning Mon, 01 Jan 2007 14:18:08 +0100 3b4aa2b0-e43c-11dc-9afb-000ea68e967b
<![CDATA[Optimal Inference for Instrumental Variables Regression with non-Gaussian Errors]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/michael-jansson?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=ae9d4ca0-e43b-11dc-9afb-000ea68e967b&tx_pure_pure5%5BshowType%5D=pub&cHash=d376e92013e897faf2222abeb6de2f2b Cattaneo, M. D., Crump, R. K., Jansson, M. the endogenous regressor in a linear instrumental variables model with a single
endogenous regressor, nonrandom exogenous regressors and instruments,
and i.i.d. errors whose distribution is unknown. It is shown that under mild
smoothness conditions on the error distribution it is possible to develop tests
which are "nearly" efficient when identification is weak and consistent and asymptotically
optimal when identification is strong. In addition, an estimator
is presented which can be used in the usual way to construct valid (indeed,
optimal) confidence intervals when identification is strong. The estimator is of
the two stage least squares variety and is asymptotically efficient under strong
identification whether or not the errors are normal.]]>
Forskning Mon, 01 Jan 2007 14:18:08 +0100 ae9d4ca0-e43b-11dc-9afb-000ea68e967b