Interpreting my results with variables for Age Categories

[Darcy Hill]

I am running the following fixed effects regression

xtreg recycling loginc logpopden age1120 age2130 age3140 age4150 age5160 age6170 age7180 age81plus md11 md12 md13 md14 md15 md16 md17 md18 md19 md20 md21 md22 md23 md24 md25 md26 md27 md28 md29 md291 wasteavg dryavg quarter2 quarter3 quarter4 year2 year3 year4 year5, fe vce(cluster acode)

Where age1120...age81 plus are the percentages of people in each a local authority that fall into that age category (0-10 is dropped to avoid multicollinearity). I am trying to understand whether for example having more young people increases the recycling rate (which is also in percentages). How can I interpret the coefficients on age categories?

Is it correct that a 1% increase in the percentage of people aged 11-20 in that local authority it associated with -0.296% decrease in the recycling rate compared with the age 0-10 category?

My results look like this:

Fixed-effects (within) regression Number of obs = 5,862
Group variable: acode Number of groups = 311

R-sq: Obs per group:
within = 0.3716 min = 4
between = 0.1048 avg = 18.8
overall = 0.1549 max = 20

F(39,310) = 43.00
corr(u_i, Xb) = -0.5252 Prob > F = 0.0000

(Std. Err. adjusted for 311 clusters in acode)
------------------------------------------------------------------------------
| Robust
recycling | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
loginc | 12.03771 6.237323 1.93 0.055 -.2351345 24.31055
logpopden | -1.332437 2.427655 -0.55 0.583 -6.109203 3.444329
age1120 | -.2954794 .6908926 -0.43 0.669 -1.654911 1.063953
age2130 | .1885658 .6400376 0.29 0.768 -1.070802 1.447933
age3140 | .7329204 .9751467 0.75 0.453 -1.185823 2.651664
age4150 | -.3526127 1.066931 -0.33 0.741 -2.451955 1.74673
age5160 | 1.275646 .9134214 1.40 0.164 -.5216435 3.072936
age6170 | .024184 .9108853 0.03 0.979 -1.768116 1.816484
age7180 | 1.218289 .8260266 1.47 0.141 -.4070386 2.843617
age81plus | -.3917339 1.448403 -0.27 0.787 -3.241678 2.45821
md11 | .4255393 .4895818 0.87 0.385 -.5377843 1.388863
md12 | -.5535315 .4137792 -1.34 0.182 -1.367703 .2606396
md13 | -.9062759 .5197156 -1.74 0.082 -1.928892 .1163405
md14 | -.1184019 .4622045 -0.26 0.798 -1.027857 .7910528
md15 | .5687996 .58112 0.98 0.328 -.5746388 1.712238
md16 | .0920765 .7555284 0.12 0.903 -1.394536 1.578689
md17 | -.2591195 .3896524 -0.67 0.507 -1.025818 .5075785
md18 | -.051231 .5992336 -0.09 0.932 -1.230311 1.127848
md19 | -.0115919 .4511141 -0.03 0.980 -.8992246 .8760409
md20 | -1.560113 .4897158 -3.19 0.002 -2.5237 -.5965258
md21 | -1.002337 .5052073 -1.98 0.048 -1.996406 -.0082675
md22 | -1.213785 .5130708 -2.37 0.019 -2.223327 -.2042435
md23 | .1537965 .5411894 0.28 0.776 -.9110726 1.218666
md24 | .392942 .4239478 0.93 0.355 -.4412372 1.227121
md25 | .1252963 .871987 0.14 0.886 -1.590465 1.841058
md26 | .5656828 .3854658 1.47 0.143 -.1927775 1.324143
md27 | 1.367237 .367305 3.72 0.000 .6445112 2.089964
md28 | .3488904 .3075395 1.13 0.257 -.2562384 .9540191
md29 | -.0347408 .680321 -0.05 0.959 -1.373372 1.30389
md291 | .3742537 .3683196 1.02 0.310 -.3504689 1.098976
wasteavg | 1.467284 .5581088 2.63 0.009 .3691235 2.565444
dryavg | -.6221646 .6502192 -0.96 0.339 -1.901566 .6572366
quarter2 | -4.480375 .1217009 -36.81 0.000 -4.71984 -4.240911
quarter3 | -4.181014 .1181899 -35.38 0.000 -4.41357 -3.948458
quarter4 | -2.514117 .1012822 -24.82 0.000 -2.713405 -2.31483
year2 | -.3664256 .2981572 -1.23 0.220 -.9530934 .2202422
year3 | -1.513213 .5369766 -2.82 0.005 -2.569793 -.4566336
year4 | -3.069163 .9697009 -3.17 0.002 -4.977191 -1.161135
year5 | -4.18252 1.169431 -3.58 0.000 -6.483547 -1.881493
_cons | -114.9097 80.65038 -1.42 0.155 -273.6011 43.78166
-------------+----------------------------------------------------------------
sigma_u | 4.7016969
sigma_e | 2.5497095
rho | .77274705 (fraction of variance due to u_i)
------------------------------------------------------------------------------

.

[Marcos Almeida]

Two aspects I failed to understand. First, the reason to avoid sharing data under code delimiters, in spite of having posted more than 5 dozen messages. Without code delimiters, you know, it gets quite difficult to read the output. Second, the reason to avoid the use of age group as a categorical (also, year, etc.) instead of creating dummies for each level.

[Darcy Hill]

Hi Marcos,
Is this (below) what you mean by sharing data under code delimiters? I want to control for the fact that different local authorities have different age structures (some have more 0-10 year olds, some have more 40-50 year olds) and observe whether having a greater % of one group causes recycling rates to differ- can you suggest a better way to do this?

Thank You

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(acode recycling loginc logpopden) byte unitarydummy long(md11 md12 md13 md14 md15 md16 md17 md18 md19 md20 md21 md22 md23 md24 md25 md26 md27 md28 md29 md291) float(wasteavg dryavg quarter2 quarter3 quarter4 year2 year3 year4 year5)
6000001  31.64322 9.576926 2.2529745 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 0 0 0 0 0 0 0
6000001  29.11372 9.576926  2.261659 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 1 0 0 0 0 0 0
6000001 24.318804 9.576926  2.261659 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 0 1 0 0 0 0 0
6000001  23.49204 9.576926  2.261659 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 0 0 1 0 0 0 0
6000001  29.75906  9.58011 2.2631164 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 0 0 0 1 0 0 0
6000001 25.608576  9.58011 2.2631164 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 1 0 0 1 0 0 0
6000001  19.14898  9.58011 2.2631164 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 0 1 0 1 0 0 0
6000001 26.363016  9.58011 2.2631164 1 1 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 1 1   1 0 0 1 1 0 0 0
6000001  29.21854 9.606159 2.2677865 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 0 0 0 0 1 0 0
6000001 22.891203 9.606159 2.2631164 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 1 0 0 0 1 0 0
6000001 22.664324 9.606159 2.2677865 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 0 1 0 0 1 0 0
6000001    19.374 9.606159 2.2677865 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 0 0 1 0 1 0 0
6000001  25.64599 9.642772 2.2669578 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 0 0 0 0 0 1 0
6000001 24.093536 9.642772 2.2669578 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 1 0 0 0 0 1 0
6000001 23.910435 9.642772 2.2669578 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 0 1 0 0 0 1 0
6000001  22.74303 9.642772 2.2669578 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1   1 0 0 1 0 0 1 0
6000001 25.628105 9.620527  2.265921 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 1 1 1 0 0 1   1 0 0 0 0 0 0 1
6000001 21.490993 9.620527  2.265921 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 1 1 1 0 0 1   1 1 0 0 0 0 0 1
6000001  20.56008 9.620527  2.265921 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 1 1 1 0 0 1   1 0 1 0 0 0 0 1
6000001  19.26644 9.620527  2.265921 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 1 1 1 0 0 1   1 0 0 1 0 0 0 1
6000002  15.01909 9.554639  3.262778 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 0 0 0 0 0 0 0
6000002 14.171424 9.554639  3.234316 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 1 0 0 0 0 0 0
6000002 13.453314 9.554639  3.234316 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 0 1 0 0 0 0 0
6000002  13.24626 9.554639  3.234316 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 0 0 1 0 0 0 0
6000002  14.57947 9.564863  3.236794 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 0 0 0 1 0 0 0
6000002 14.828068 9.564863  3.236794 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 1 0 0 1 0 0 0
6000002 14.709766 9.564863  3.236794 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 0 1 0 1 0 0 0
6000002  20.44064 9.564863  3.236794 1 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 .75 0 0 1 1 0 0 0
6000002 34.159927 9.601301 3.2381685 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 0 0 0 1 0 0
6000002  24.25953 9.601301  3.236794 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 1 0 0 0 1 0 0
6000002  24.04574 9.601301 3.2381685 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 1 0 0 1 0 0
6000002    24.127 9.601301 3.2381685 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 0 1 0 1 0 0
6000002  27.94404 9.626811  3.239502 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 0 0 0 0 1 0
6000002 23.334343 9.626811  3.239502 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 1 0 0 0 0 1 0
6000002  19.43632 9.626811  3.239502 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 1 0 0 0 1 0
6000002  23.32905 9.626811  3.239502 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 0 1 0 0 1 0
6000002  23.50695 9.613669   3.24228 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 0 0 0 0 0 1
6000002 20.070557 9.613669   3.24228 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 1 0 0 0 0 0 1
6000002 19.601873 9.613669   3.24228 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 1 0 0 0 0 1
6000002  21.82984 9.613669   3.24228 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0   1 0 0 1 0 0 0 1
6000003  23.51096 9.537339  1.728642 1 1 1 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1   1 0 0 0 0 0 0 0
6000003  20.10306 9.537339  1.712536 1 1 1 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1   1 1 0 0 0 0 0 0
6000003  19.72007 9.537339  1.712536 1 1 1 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1   1 0 1 0 0 0 0 0
6000003 22.403687 9.537339  1.712536 1 1 1 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1   1 0 0 1 0 0 0 0
6000003 24.170063 9.545955  1.710911 1 1 1 0 0 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1   1 0 0 0 1 0 0 0
6000003  23.99578 9.545955  1.710911 1 1 1 0 0 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1   1 1 0 0 1 0 0 0
6000003 24.617693 9.545955  1.710911 1 1 1 0 0 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1   1 0 1 0 1 0 0 0
6000003  30.60893 9.545955  1.710911 1 1 1 0 0 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1   1 0 0 1 1 0 0 0
6000003  36.69286 9.575816 1.7105495 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1   1 0 0 0 0 1 0 0
6000003  23.24818 9.575816  1.710911 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1   1 1 0 0 0 1 0 0
6000003  28.21425 9.575816 1.7105495 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1   1 0 1 0 0 1 0 0
6000003    33.378 9.575816 1.7105495 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1   1 0 0 1 0 1 0 0
6000003 34.828026 9.600556  1.711272 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1   1 0 0 0 0 0 1 0
6000003 26.965475 9.600556  1.711272 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1   1 1 0 0 0 0 1 0
6000003 18.484371 9.600556  1.711272 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1   1 0 1 0 0 0 1 0
6000003   22.8024 9.600556  1.711272 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1   1 0 0 1 0 0 1 0
6000003 25.000637 9.583902  1.713077 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1   1 0 0 0 0 0 0 1
6000003  23.34894 9.583902  1.713077 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1   1 1 0 0 0 0 0 1
6000003  20.75586 9.583902  1.713077 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1   1 0 1 0 0 0 0 1
6000003 25.922733 9.583902  1.713077 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1   1 0 0 1 0 0 0 1
6000004  20.72435 9.607841   2.19778 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 0 0 0 0 0
6000004  19.85636 9.607841 2.1946657 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 1 0 0 0 0 0 0
6000004 17.278917 9.607841 2.1946657 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 1 0 0 0 0 0
6000004  20.15345 9.607841 2.1946657 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 1 0 0 0 0
6000004  22.03593 9.608176  2.197891 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 0 1 0 0 0
6000004 18.222332 9.608176  2.197891 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 1 0 0 1 0 0 0
6000004  17.56083 9.608176  2.197891 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 1 0 1 0 0 0
6000004  19.13032 9.608176  2.197891 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 1 1 0 0 0
6000004 21.184946 9.632138  2.201991 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 0 0 1 0 0
6000004 13.187984 9.632138  2.201991 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 1 0 0 0 1 0 0
6000004 16.005465 9.632138  2.201991 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 1 0 0 1 0 0
6000004    18.041 9.632138  2.201991 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 1 0 1 0 0
6000004 20.246767 9.662816  2.206735 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 0 0 0 1 0
6000004 16.660748 9.662816  2.206735 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 1 0 0 0 0 1 0
6000004  15.44666 9.662816  2.206735 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 1 0 0 0 1 0
6000004 18.055502 9.662816  2.206735 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0   1 0 0 1 0 0 1 0
6000004 17.611841 9.641798 2.2102504 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 1 0 0 0   1 0 0 0 0 0 0 1
6000004 14.851618 9.641798 2.2102504 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 1 0 0 0   1 1 0 0 0 0 0 1
6000004 14.507548 9.641798 2.2102504 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 1 0 0 0   1 0 1 0 0 0 0 1
6000004  17.83563 9.641798 2.2102504 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 1 0 0 0   1 0 0 1 0 0 0 1
6000005  42.36351 9.570878 1.6325684 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0   1 0 0 0 0 0 0 0
6000005 32.836056 9.570878  1.678964 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0   1 1 0 0 0 0 0 0
6000005  31.34309 9.570878  1.678964 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0   1 0 1 0 0 0 0 0
6000005   32.1052 9.570878  1.678964 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0   1 0 0 1 0 0 0 0
6000005 28.556936 9.597573 1.6757873 1 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0   1 0 0 0 1 0 0 0
6000005 30.584833 9.597573 1.6757873 1 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0   1 1 0 0 1 0 0 0
6000005  28.63693 9.597573 1.6757873 1 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0   1 0 1 0 1 0 0 0
6000005  21.55379 9.597573 1.6757873 1 0 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0   1 0 0 1 1 0 0 0
6000005  20.11268 9.606159 1.6770965 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 .   . 0 0 0 0 1 0 0
6000005 26.908495 9.606159 1.6757873 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 .   . 1 0 0 0 1 0 0
6000005  25.60923 9.606159 1.6770965 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 .   . 0 1 0 0 1 0 0
6000005  30.62015 9.606159 1.6770965 1 1 1 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 .   . 0 0 1 0 1 0 0
6000005 31.480186  9.65098 1.6769096 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 0 0 0 0 0 1 0
6000005  29.34417  9.65098 1.6769096 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 1 0 0 0 0 1 0
6000005   29.5002  9.65098 1.6769096 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 0 1 0 0 0 1 0
6000005 25.388384  9.65098 1.6769096 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 0 0 1 0 0 1 0
6000005  29.34344 9.647757 1.6770965 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 0 0 0 0 0 0 1
6000005  27.49854 9.647757 1.6770965 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 1 0 0 0 0 0 1
6000005  28.14532 9.647757 1.6770965 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 0 1 0 0 0 0 1
6000005  28.00815 9.647757 1.6770965 1 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 1   1 0 0 1 0 0 0 1
end

[Marcos Almeida]

As pointed out in #2, I believe that having categorical variables ( instead of so many dummies) is a sound starting point.

[Darcy Hill]

Hi Marcos, the Dummies are for methods of collection which is something else I am controlling for, the age categories are categorical variables - age010, age1120, age2130... if you look at the results in the first post. They are the % of people of each age group. This is why I am unsure how to interpret the coefficients?

* Example generated by -dataex-. To install: ssc install dataex
clear
input float(age010 age1120 age2130 age3140 age4150 age5160 age6170 age7180 age81plus)
13.170245   12.6825 12.550265   11.2366 14.780893  13.10196 10.877835 7.582836 4.0168653
13.170245   12.6825 12.550265   11.2366 14.780893  13.10196 10.877835 7.582836 4.0168653
13.170245   12.6825 12.550265   11.2366 14.780893  13.10196 10.877835 7.582836 4.0168653
13.170245   12.6825 12.550265   11.2366 14.780893  13.10196 10.877835 7.582836 4.0168653
13.305346 12.203492  12.76467 11.118905  14.46224  13.35175 11.082212 7.500378 4.2110033
13.305346 12.203492  12.76467 11.118905  14.46224  13.35175 11.082212 7.500378 4.2110033
13.305346 12.203492  12.76467 11.118905  14.46224  13.35175 11.082212 7.500378 4.2110033
13.305346 12.203492  12.76467 11.118905  14.46224  13.35175 11.082212 7.500378 4.2110033
 13.33391 11.958188 12.715158 10.971211 14.132994   13.6773 11.354556  7.45632  4.400363
 13.33391 11.958188 12.715158 10.971211 14.132994   13.6773 11.354556  7.45632  4.400363
 13.33391 11.958188 12.715158 10.971211 14.132994   13.6773 11.354556  7.45632  4.400363
 13.33391 11.958188 12.715158 10.971211 14.132994   13.6773 11.354556  7.45632  4.400363
13.365694 11.674847   12.8046 11.069428 13.747324  14.02625 11.448896 7.436918 4.4260416
13.365694 11.674847   12.8046 11.069428 13.747324  14.02625 11.448896 7.436918 4.4260416
13.365694 11.674847   12.8046 11.069428 13.747324  14.02625 11.448896 7.436918 4.4260416
13.365694 11.674847   12.8046 11.069428 13.747324  14.02625 11.448896 7.436918 4.4260416
13.498842 11.455652 12.889224 11.288707 13.168183 14.253864  11.53643 7.417739 4.4913564
13.498842 11.455652 12.889224 11.288707 13.168183 14.253864  11.53643 7.417739 4.4913564
13.498842 11.455652 12.889224 11.288707 13.168183 14.253864  11.53643 7.417739 4.4913564
13.498842 11.455652 12.889224 11.288707 13.168183 14.253864  11.53643 7.417739 4.4913564
 14.23021 13.688854 15.174517  11.60561 13.470438   12.2796  9.404149 6.527976  3.618644
 14.23021 13.688854 15.174517  11.60561 13.470438   12.2796  9.404149 6.527976  3.618644
 14.23021 13.688854 15.174517  11.60561 13.470438   12.2796  9.404149 6.527976  3.618644
 14.23021 13.688854 15.174517  11.60561 13.470438   12.2796  9.404149 6.527976  3.618644
14.491293 13.237252 15.486895 11.515286  13.06448  12.56848  9.475132 6.516403   3.64478
14.491293 13.237252 15.486895 11.515286  13.06448  12.56848  9.475132 6.516403   3.64478
14.491293 13.237252 15.486895 11.515286  13.06448  12.56848  9.475132 6.516403   3.64478
14.491293 13.237252 15.486895 11.515286  13.06448  12.56848  9.475132 6.516403   3.64478
14.724694 12.886446  15.56216 11.483478 12.740394 12.700103  9.690556 6.465886  3.746286
14.724694 12.886446  15.56216 11.483478 12.740394 12.700103  9.690556 6.465886  3.746286
14.724694 12.886446  15.56216 11.483478 12.740394 12.700103  9.690556 6.465886  3.746286
14.724694 12.886446  15.56216 11.483478 12.740394 12.700103  9.690556 6.465886  3.746286
 14.89484 12.656665  15.72249 11.509583 12.436294 12.788745  9.824133 6.458259 3.7089944
 14.89484 12.656665  15.72249 11.509583 12.436294 12.788745  9.824133 6.458259 3.7089944
 14.89484 12.656665  15.72249 11.509583 12.436294 12.788745  9.824133 6.458259 3.7089944
 14.89484 12.656665  15.72249 11.509583 12.436294 12.788745  9.824133 6.458259 3.7089944
 14.94021 12.611348  15.81674 11.672107 11.951456  12.88856  9.964654 6.405085 3.7498395
 14.94021 12.611348  15.81674 11.672107 11.951456  12.88856  9.964654 6.405085 3.7498395
 14.94021 12.611348  15.81674 11.672107 11.951456  12.88856  9.964654 6.405085 3.7498395
 14.94021 12.611348  15.81674 11.672107 11.951456  12.88856  9.964654 6.405085 3.7498395
12.129563 11.950273 11.622066  10.73302  14.67372  13.24754  12.72078 8.340001  4.583037
12.129563 11.950273 11.622066  10.73302  14.67372  13.24754  12.72078 8.340001  4.583037
12.129563 11.950273 11.622066  10.73302  14.67372  13.24754  12.72078 8.340001  4.583037
12.129563 11.950273 11.622066  10.73302  14.67372  13.24754  12.72078 8.340001  4.583037
 12.35403 11.556758 11.737552 10.499407 14.422791 13.561055 12.768228 8.486959  4.613219
 12.35403 11.556758 11.737552 10.499407 14.422791 13.561055 12.768228 8.486959  4.613219
 12.35403 11.556758 11.737552 10.499407 14.422791 13.561055 12.768228 8.486959  4.613219
 12.35403 11.556758 11.737552 10.499407 14.422791 13.561055 12.768228 8.486959  4.613219
12.508327  11.17822  11.82366 10.366982 14.013856 13.819188 12.875457 8.678628  4.735681
12.508327  11.17822  11.82366 10.366982 14.013856 13.819188 12.875457 8.678628  4.735681
12.508327  11.17822  11.82366 10.366982 14.013856 13.819188 12.875457 8.678628  4.735681
12.508327  11.17822  11.82366 10.366982 14.013856 13.819188 12.875457 8.678628  4.735681
 12.63634 10.952972  11.84786 10.383228 13.535663   14.1091  12.88685 8.934853  4.713133
 12.63634 10.952972  11.84786 10.383228 13.535663   14.1091  12.88685 8.934853  4.713133
 12.63634 10.952972  11.84786 10.383228 13.535663   14.1091  12.88685 8.934853  4.713133
 12.63634 10.952972  11.84786 10.383228 13.535663   14.1091  12.88685 8.934853  4.713133
 12.66827 10.736848  11.82618 10.619502 13.041714 14.381236 12.785617 9.139753   4.80088
 12.66827 10.736848  11.82618 10.619502 13.041714 14.381236 12.785617 9.139753   4.80088
 12.66827 10.736848  11.82618 10.619502 13.041714 14.381236 12.785617 9.139753   4.80088
 12.66827 10.736848  11.82618 10.619502 13.041714 14.381236 12.785617 9.139753   4.80088
 13.49182 12.443438 13.176993 12.116143 14.845678  12.96711  10.47967  6.81033  3.668819
 13.49182 12.443438 13.176993 12.116143 14.845678  12.96711  10.47967  6.81033  3.668819
 13.49182 12.443438 13.176993 12.116143 14.845678  12.96711  10.47967  6.81033  3.668819
 13.49182 12.443438 13.176993 12.116143 14.845678  12.96711  10.47967  6.81033  3.668819
13.742226 11.975723 13.250583 12.000538 14.599887 13.187512 10.636758 6.819416  3.787358
13.742226 11.975723 13.250583 12.000538 14.599887 13.187512 10.636758 6.819416  3.787358
13.742226 11.975723 13.250583 12.000538 14.599887 13.187512 10.636758 6.819416  3.787358
13.742226 11.975723 13.250583 12.000538 14.599887 13.187512 10.636758 6.819416  3.787358
13.838898  11.74141 13.239175   12.0351 14.199966 13.395535 10.776503   6.8675 3.9059165
13.838898  11.74141 13.239175   12.0351 14.199966 13.395535 10.776503   6.8675 3.9059165
13.838898  11.74141 13.239175   12.0351 14.199966 13.395535 10.776503   6.8675 3.9059165
13.838898  11.74141 13.239175   12.0351 14.199966 13.395535 10.776503   6.8675 3.9059165
 13.96263  11.56113 13.130356  12.15766  13.83502 13.525993   10.9154 6.979009  3.932803
 13.96263  11.56113 13.130356  12.15766  13.83502 13.525993   10.9154 6.979009  3.932803
 13.96263  11.56113 13.130356  12.15766  13.83502 13.525993   10.9154 6.979009  3.932803
 13.96263  11.56113 13.130356  12.15766  13.83502 13.525993   10.9154 6.979009  3.932803
 13.98514  11.43102 12.998194 12.378162 13.409506  13.71059  11.01971 7.035691  4.031986
 13.98514  11.43102 12.998194 12.378162 13.409506  13.71059  11.01971 7.035691  4.031986
 13.98514  11.43102 12.998194 12.378162 13.409506  13.71059  11.01971 7.035691  4.031986
 13.98514  11.43102 12.998194 12.378162 13.409506  13.71059  11.01971 7.035691  4.031986
13.253652 11.596827 12.015772 12.431874  14.78536 12.836602 11.214847 7.444338 4.4207273
13.253652 11.596827 12.015772 12.431874  14.78536 12.836602 11.214847 7.444338 4.4207273
13.253652 11.596827 12.015772 12.431874  14.78536 12.836602 11.214847 7.444338 4.4207273
13.253652 11.596827 12.015772 12.431874  14.78536 12.836602 11.214847 7.444338 4.4207273
13.416757 11.264022  11.98097 12.252426   14.7258  13.05639  11.38509 7.487278  4.431266
13.416757 11.264022  11.98097 12.252426   14.7258  13.05639  11.38509 7.487278  4.431266
13.416757 11.264022  11.98097 12.252426   14.7258  13.05639  11.38509 7.487278  4.431266
13.416757 11.264022  11.98097 12.252426   14.7258  13.05639  11.38509 7.487278  4.431266
13.393844 11.264958 11.823153 12.157503 14.419562 13.257837 11.587975 7.557827 4.5373406
13.393844 11.264958 11.823153 12.157503 14.419562 13.257837 11.587975 7.557827 4.5373406
13.393844 11.264958 11.823153 12.157503 14.419562 13.257837 11.587975 7.557827 4.5373406
13.393844 11.264958 11.823153 12.157503 14.419562 13.257837 11.587975 7.557827 4.5373406
13.372894 11.119078 11.604936  12.16438  14.27574 13.504028  11.64456 7.736938  4.577445
13.372894 11.119078 11.604936  12.16438  14.27574 13.504028  11.64456 7.736938  4.577445
13.372894 11.119078 11.604936  12.16438  14.27574 13.504028  11.64456 7.736938  4.577445
13.372894 11.119078 11.604936  12.16438  14.27574 13.504028  11.64456 7.736938  4.577445
13.315527  10.98216 11.620755 12.117336 13.943777 13.857252 11.539872 7.901098 4.7222247
13.315527  10.98216 11.620755 12.117336 13.943777 13.857252 11.539872 7.901098 4.7222247
13.315527  10.98216 11.620755 12.117336 13.943777 13.857252 11.539872 7.901098 4.7222247
13.315527  10.98216 11.620755 12.117336 13.943777 13.857252 11.539872 7.901098 4.7222247
end