Using large samples in econometrics

As I document using evidence from a journal data repository that I manage, the datasets used in empirical work are getting larger. When we use very large datasets, it can be dangerous to rely on standard methods for statistical inference. In addition, we need to worry about computational issues. We must be careful in our choice of statistical methods and the algorithms used to implement them.

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Year of publication:	2021
Authors:	MacKinnon, James G.
Publisher:	Kingston (Ontario) : Queen's University, Department of Economics
Subject:	datasets \| clustered data \| statistical computation \| statistical inference \| bootstrap

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Series:	Queen’s Economics Department Working Paper ; 1482
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	1789514134 [GVK] hdl:10419/260487 [Handle] RePEC:qed:wpaper:1482 [RePEc]
Classification:	C10 - Econometric and Statistical Methods: General. General ; C12 - Hypothesis Testing ; C13 - Estimation ; c55
Source:	EconStor

Persistent link: https://www.econbiz.de/10013254704