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st: Quantile Regression Coefficient Investigation for Individual Observations


From   George Bentley <[email protected]>
To   [email protected]
Subject   st: Quantile Regression Coefficient Investigation for Individual Observations
Date   Wed, 16 Jan 2013 18:24:32 -0500

Good evening,

I am new to Stata software and Statalist.  So far I have been using
Stata solely for quantile regression.  I am able to run quantile
regression without issue but would like to delve deeper and am unsure
of how to proceed.  In a project, I am working with 153 counties where
agricultural cover is the dependent variable and the independent
variables are per capita income, per capita income squared, county
area, county population, and county topography.

Here is an excerpt of my Stata code:

quietly qreg  laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.1)
estimates store QR_10
quietly qreg  laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.2)
estimates store QR_20
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.3)
estimates store QR_30
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.4)
estimates store QR_40
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.5)
estimates store QR_50
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.6)
estimates store QR_60
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.7)
estimates store QR_70
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.8)
estimates store QR_80
quietly qreg   laagrpc  larea  lapop  topo  lainc  lainc2, quantile(.9)
estimates store QR_90
estimates table QR_10 QR_20 QR_30 QR_40 QR_50 QR_60 QR_70 QR_80 QR_90,
b(%7.3f) se


Excerpt of Estimates Table (Standard errors removed):

                                 Q = 0.1    Q = 0.2     Q = 0.3     Q
= 0.4     Q = 0.5     Q = 0.6     Q = 0.7     Q = 0.8     Q = 0.9
Per capita Income        61.581     76.360       65.790      50.775
   3.250       -18.945      -6.001      30.653      17.331

Per Capita Income Sq. -3.039      -3.764        -3.260       -2.553
  -0.209         0.840        0.196       -1.579      -0.885


 From my estimates table I can see that the per capita income term has
a negative coefficient at quantile = 0.6 and quantile = 0.7.  Also, I
can see that the per capita income squared term has a positive
coefficient at quantile = 0.6 and quantile = 0.7.  My main goal is to
determine the counties having a negative coefficient on the per capita
income term and a positive coefficient on the per capita income
squared term simultaneously.  Is this possible and is there any advice
as to how I should proceed?  Thank you for any assistance in advance.

Thank you,
George Bentley
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