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From |
"Jeannette Wicks-Lim" <janetlim@econs.umass.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Fw: Sample size and QREG |

Date |
Mon, 7 Feb 2005 16:17:07 -0500 |

In case my question was unclear, here are some more specifics.

I am trying to estimate something like the following:

qreg lnwage pwl labcon pwllabcon

where pwl=1 when prevailing wage law is in effect and 0 when it is not

labcon=1 if worker is a construction laborer, 0 if not

pwllabcon = pwl*labcon, so that it equals 1 if pwl is in effect and workers is construction laborer, 0 otherwise

sample is restricted to laborers (across industries)

because I am looking at one state, I have only 30 observations on workers for whom pwlabcon=1. I assume that this sample size is too small to estimate anything but the median regression; but what guidelines are there for the necessary cell size if you want to estimate qregs for the 10th or 90th quantile?

Thanks again,

Jeannette

----- Original Message ----- From: "Jeannette Wicks-Lim" <janetlim@econs.umass.edu>

To: <statalist@hsphsun2.harvard.edu>

Sent: Monday, February 07, 2005 9:56 AM

Subject: Sample size and QREG

I have a very basic statistical question about the use of quantiles to tease out policy impacts. I am attempting to use quantile regressions (QREG) to detect the impact of state-level prevailing wage law repeals (the elimination of wage floors for construction workers in publicly funded projects) on very specific groups of workers at different points in their wage distribution -- defined by state and

occupation. I have just over 30 observations who I code as "treated" (treatment is not directly observed -- I am using the CPS, and in fact, I can only assume that a subset of these 30 observations are actually treated).

Is there any rule of thumb about when your sample is too small to reliably estimate percentiles? Are there any guidelines similar to the general rule that 30 observations is (more or less)

sufficient to estimate a mean? Any articles that anyone can point me toward?

Thanks so much,

Jeannette Wicks-Lim

Department of Economics

University of Massachusetts, Amherst

(413) 577-0820

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