Many instruments and/or regressors: a friendly guide

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985998%3A_____%2F19%3A00517859" target="_blank" >RIV/67985998:_____/19:00517859 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11640/19:00504906

Výsledek na webu

<a href="https://doi.org/10.1111/joes.12295" target="_blank" >https://doi.org/10.1111/joes.12295</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/joes.12295" target="_blank" >10.1111/joes.12295</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Many instruments and/or regressors: a friendly guide

Popis výsledku v původním jazyce

This paper surveys the state of the art in the econometrics of regression models with many instruments or many regressors based on alternative – namely, dimension – asymptotics. We list critical results of dimension asymptotics that lead to better approximations of properties of familiar and alternative estimators and tests when the instruments and/or regressors are numerous. Then, we consider the problem of estimation and inference in the basic linear instrumental variables regression setup with many strong instruments. We describe the failures of conventional estimation and inference, as well as alternative tools that restore consistency and validity. We then add various other features to the basic model such as heteroskedasticity, instrument weakness, etc., in each case providing a review of the existing tools for proper estimation and inference. Subsequently, we consider a related but different problem of estimation and testing in a linear mean regression with many regressors. We also describe various extensions and connections to other settings, such as panel data models, spatial models, time series models, and so on. Finally, we provide practical guidance regarding which tools are most suitable to use in various situations when many instruments and/or regressors turn out to be an issue.

Název v anglickém jazyce

Many instruments and/or regressors: a friendly guide

Popis výsledku anglicky

This paper surveys the state of the art in the econometrics of regression models with many instruments or many regressors based on alternative – namely, dimension – asymptotics. We list critical results of dimension asymptotics that lead to better approximations of properties of familiar and alternative estimators and tests when the instruments and/or regressors are numerous. Then, we consider the problem of estimation and inference in the basic linear instrumental variables regression setup with many strong instruments. We describe the failures of conventional estimation and inference, as well as alternative tools that restore consistency and validity. We then add various other features to the basic model such as heteroskedasticity, instrument weakness, etc., in each case providing a review of the existing tools for proper estimation and inference. Subsequently, we consider a related but different problem of estimation and testing in a linear mean regression with many regressors. We also describe various extensions and connections to other settings, such as panel data models, spatial models, time series models, and so on. Finally, we provide practical guidance regarding which tools are most suitable to use in various situations when many instruments and/or regressors turn out to be an issue.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

<a href="/cs/project/GA17-26535S" target="_blank" >GA17-26535S: Ekonometrie s dimenzionální asymptotikou</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Economic Surveys

ISSN

0950-0804

e-ISSN

—

Svazek periodika

33

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

38

Strana od-do

689-726

Kód UT WoS článku

000460656200013

EID výsledku v databázi Scopus

2-s2.0-85056467488