Author's Keywords: LDV, lagged dependent variables, autocorrelation, time series, GLS, Newey-West	Convention Need a solution for abstract management? All Academic can help! Contact us today to find out how our system can help your annual meeting. Submission - Custom fields, multiple submission types, tracks, audio visual, multiple upload formats, automatic conversion to pdf. Review - Peer Review, Bulk reviewer assignment, bulk emails, ranking, z-score statistics, and multiple worksheets! Reports - Many standard and custom reports generated while you wait. Print programs with participant indexes, event grids, and more! Scheduling - Flexible and convenient grid scheduling within rooms and buildings. Conflict checking and advanced filtering. Communication - Bulk email tools to help your administrators send reminders and responses. Use form letters, a message center, and much more! Management - Search tools, duplicate people management, editing tools, submission transfers, many tools to manage a variety of conference management headaches! Click here for more information.
Association: Name: American Political Science Association URL: http://www.apsanet.org
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Baker, Regina. "Lagged Dependent Variables and Reality: Did You Specify that Autocorrelation a priori?" Paper presented at the annual meeting of the American Political Science Association, Hyatt Regency Chicago and the Sheraton Chicago Hotel and Towers, Chicago, IL, Aug 30, 2007 <Not Available>. 2011-06-08 <http://www.allacademic.com/meta/p209695_index.html>

Baker, R. M. , 2007-08-30 "Lagged Dependent Variables and Reality: Did You Specify that Autocorrelation a priori?" Paper presented at the annual meeting of the American Political Science Association, Hyatt Regency Chicago and the Sheraton Chicago Hotel and Towers, Chicago, IL Online <APPLICATION/PDF>. 2011-06-08 from http://www.allacademic.com/meta/p209695_index.html

Publication Type: Conference Paper/Unpublished Manuscript Abstract: Recent work in time series analysis emphasizes the importance of omitted exogenous variables as a cause of autocorrelation. While autocorrelation by itself does not affect point estimates, then, the omitted variables driving it may introduce substantial bias in the estimates of coefficients on included exogenous variables. This suggests that analysts correcting for autocorrelation should consider not only the effects on estimated standard errors, but also the extent to which the correction technique mitigates omitted variables bias. In this paper, I show that in the case of an omitted contemporaneous explanatory variable, the coefficients estimated from Ordinary Least Squares (OLS) and Newey-West methods are biased. If the omitted variable is strongly autocorrelated, which is typically the case, a lagged dependent variable (LDV) can be a good proxy for the omitted variable -- even if the omitted variable is unknown and/or unmeasurable -- and the LDV therefore mitigates the specification bias. Concerns that addressing autocorrelation by adding a LDV results in attenuated coefficient(s) on the variable(s) of interest, then, have the problem reversed: the LDV estimate is less biased than the OLS estimate.

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