文章基本信息

标题：Solving the Omitted Variables Problem of Regression Analysis Using the Relative Vertical Position of Observations
本地全文：下载
作者：Jonathan E. Leightner ; Tomoo Inoue
期刊名称：Advances in Decision Sciences
印刷版ISSN：2090-3359
电子版ISSN：2090-3367
出版年度：2012
卷号：2012
DOI：10.1155/2012/728980
出版社：Hindawi Publishing Corporation
摘要：The omitted variables problem is one of regression analysis’ most serious problems. The standard approach to the omitted variables problem is to find instruments, or proxies, for the omitted variables, but this approach makes strong assumptions that are rarely met in practice. This paper introduces best projection reiterative truncated projected least squares (BP-RTPLS), the third generation of a technique that solves the omitted variables problem without using proxies or instruments. This paper presents a theoretical argument that BP-RTPLS produces unbiased reduced form estimates when there are omitted variables. This paper also provides simulation evidence that shows OLS produces between 250% and 2450% more errors than BP-RTPLS when there are omitted variables and when measurement and round-off error is 1 percent or less. In an example, the government spending multiplier, , is estimated using annual data for the USA between 1929 and 2010.