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Three serial correlation tests for panel data regression models

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  • Jesse Wursten

    () (KU Leuven)

Abstract

The default method to calculate standard errors in regression models requires idiosyncratic errors (uncorrelated on any dimension). More general methods exist (e.g. HAC and clustered errors) but are not always feasible, especially in smaller datasets or those with a complicated (correlation) structure. However, if your residuals are uncorrelated, the default standard errors might actually suffice and be more reliable than their cluster robust version. In this presentation, I present three new panel serial correlation tests which can be used to look for correlation along the first dimension (‘within’ groups). Likewise, I present two new(-ish) commands to test for correlation in the second dimension (‘between’ groups). These commands are faster, more versatile and robust than existing ones (e.g. xtserial, abar).

Suggested Citation

  • Jesse Wursten, 2017. "Three serial correlation tests for panel data regression models," United Kingdom Stata Users' Group Meetings 2017 17, Stata Users Group.
  • Handle: RePEc:boc:usug17:17
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