gretl-data 2017d-3build1 / usr / share / gretl / data / data7-18.gdt

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE gretldata SYSTEM "gretldata.dtd">

<gretldata version="1.3" name="data7-18" frequency="1" startobs="1" endobs="58" type="cross-section">
<description>
DATA7-18:
    Cross-sectional data on the 58 California counties for the year
    1990 to explain population differentials - compiled by Alvin Chan.
    Sources: California Statistical Abstract.
             California Cities, Towns, &amp; Counties.
    pop      = county population in thousands, Range 1.192 - 9149.81.
    educexp  = local government expenditures on education per student
               (in dollars), Range 3869-9438.
    recexp   = expenditures per capita on recreation and cultural
               services (in dollars),  Range 0 - 3138.
    policexp = local government expenditures per capita on police
               protection (in dollars), Range 79 - 674.
    vcrime   = number of violent crimes per 100,000 population,
               Range 230 - 1587.
    othrcrim = number of other crimes per 100,000 population,
               Range 2130 - 16946.
    unemprt  = unemployment rate (%), Range 4.8 - 24.9.
    city     = dummy variable that equals 1 if there is a city in the
               county with a population over 100,000 inhabitants.
    inland   = dummy variable that takes the value 1 when the county
               does not border the Pacific ocean.
    central  = dummy variable that takes on the value 1 when the county
               is located in the southern portion of the state and 0
               when it is in either the northern or southern portion of
               the state.
    south    = dummy variable that takes on the value 1 when the county is
               located in the southern portion of the state and 0 if it
               is in the central or northern portion of the state.
</description>
<variables count="11">
<variable name="pop"
 label="county population (000s, 1.192 - 9149.81)"
/>
<variable name="educexp"
 label="local govt expend. on education ($ per student)"
/>
<variable name="recexp"
 label="$ expend. per capita on rec. and cultural services"
/>
<variable name="policexp"
 label="local govt expend. on police ($ per capita)"
/>
<variable name="vcrime"
 label="violent crimes per 100,000 population (230 - 1587)"
/>
<variable name="othrcrim"
 label="Other crimes per 100,000 population (2130 - 16946)"
/>
<variable name="unemprt"
 label="unemployment rate (%), Range 4.8 - 24.9."
/>
<variable name="city"
 label="= 1 if county has a city with &gt; 100,000 inhabitants"
 discrete="true"
/>
<variable name="inland"
 label="= 1 if county does not border the Pacific ocean"
 discrete="true"
/>
<variable name="central"
 label="= 1 if county is in central portion of state"
 discrete="true"
/>
<variable name="south"
 label="= 1 if county is in southern portion of state"
 discrete="true"
/>
</variables>
<observations count="58" labels="false">
<obs>1319.48 4850 484 175 1234 6668 6.2 1 1 0 0 </obs>
<obs>1.192 9438 0 674 755 16946 10.1 0 1 0 0 </obs>
<obs>32.799 4100 503 119 232 2329 8.2 0 1 0 0 </obs>
<obs>192.253 3939 226 103 491 4863 10.2 0 1 0 0 </obs>
<obs>37.146 3869 290 91 269 2907 11.3 0 1 0 0 </obs>
<obs>17.239 4138 0 147 522 3359 17.8 0 1 0 0 </obs>
<obs>862.935 4499 346 149 741 5072 6.4 1 1 0 0 </obs>
<obs>26.867 4494 361 106 525 4191 12 0 0 0 0 </obs>
<obs>144.842 4058 945 119 357 3401 7.5 0 1 0 0 </obs>
<obs>729.736 4504 243 114 1260 7704 13.6 1 1 1 0 </obs>
<obs>25.788 3979 171 111 419 4320 15.6 0 1 0 0 </obs>
<obs>121.749 4403 427 107 554 7042 8.8 0 0 0 0 </obs>
<obs>137.053 4260 166 122 703 5396 24.9 0 1 0 1 </obs>
<obs>18.434 5385 1242 237 391 3569 10.4 0 1 1 0 </obs>
<obs>609.333 4410 236 109 850 5445 14.3 1 1 1 0 </obs>
<obs>110.091 4247 138 101 602 3554 13.7 0 1 1 0 </obs>
<obs>55.766 4092 344 107 931 4463 12.2 0 1 0 0 </obs>
<obs>28.079 4572 281 81 491 2229 10.7 0 1 0 0 </obs>
<obs>9149.811 5111 3138 218 1508 4960 9.4 1 0 0 1 </obs>
<obs>104.925 4237 223 79 756 4707 14.9 0 1 1 0 </obs>
<obs>235.037 4779 1158 156 357 3319 4.8 0 0 0 0 </obs>
<obs>15.637 4752 0 125 1388 4099 9.4 0 1 1 0 </obs>
<obs>81.895 4897 690 126 574 3656 9.7 0 0 0 0 </obs>
<obs>196.85 4365 175 96 529 4877 15.2 0 1 1 0 </obs>
<obs>9.672 4902 0 112 527 2130 11.9 0 1 0 0 </obs>
<obs>10.393 5292 0 280 587 5013 10.1 0 1 1 0 </obs>
<obs>351.927 4676 1277 143 779 4381 11.9 1 0 1 0 </obs>
<obs>114.969 4196 959 150 512 3852 6.9 0 1 0 0 </obs>
<obs>85.832 4099 717 98 362 3015 7.7 0 1 0 0 </obs>
<obs>2543.168 4445 1018 182 551 4480 5.8 1 0 0 1 </obs>
<obs>198.485 4064 611 130 466 4239 7 0 1 0 0 </obs>
<obs>20.511 5631 658 152 283 7927 13.9 0 1 0 0 </obs>
<obs>1352.932 4178 595 132 981 5657 10.6 1 1 0 1 </obs>
<obs>1098.148 4454 565 115 968 7335 7.3 1 1 0 0 </obs>
<obs>40.995 4261 0 94 705 2993 13.3 0 1 1 0 </obs>
<obs>1553.625 4099 299 140 958 5911 8.4 1 1 0 0 </obs>
<obs>2632.078 4715 727 127 888 4917 7.2 1 0 0 1 </obs>
<obs>734.676 5170 2256 224 1489 7126 6.7 1 0 0 0 </obs>
<obs>518.168 4394 199 140 1035 7039 12.3 1 1 0 0 </obs>
<obs>223.71 4681 678 122 709 3400 7.4 0 0 1 0 </obs>
<obs>676.237 4642 985 166 498 3539 4.9 0 0 1 0 </obs>
<obs>380.494 4394 629 133 469 3884 7.3 0 0 0 1 </obs>
<obs>1557.233 4628 539 149 580 3812 6.3 1 1 1 0 </obs>
<obs>234.972 4423 617 156 714 5634 9.8 0 0 1 0 </obs>
<obs>160.021 4112 427 123 552 5102 11.8 0 1 0 0 </obs>
<obs>3.352 6831 0 338 298 2237 10 0 1 0 0 </obs>
<obs>43.928 4611 526 158 232 3902 13.6 0 1 0 0 </obs>
<obs>367.585 4149 333 188 852 5456 7.7 1 1 0 0 </obs>
<obs>410.192 4096 530 123 494 4557 6.2 1 0 0 0 </obs>
<obs>406.764 3928 176 127 976 6583 15 1 1 1 0 </obs>
<obs>73.171 4050 197 113 619 5426 16 0 1 0 0 </obs>
<obs>52.876 4140 155 108 1012 4753 11.1 0 1 0 0 </obs>
<obs>13.482 5449 0 156 230 2388 14.4 0 1 0 0 </obs>
<obs>343.257 4450 170 96 759 4892 15.4 0 1 1 0 </obs>
<obs>51.933 4130 720 91 335 3709 10.9 0 1 1 0 </obs>
<obs>702.741 4325 66 120 471 3220 7.9 1 0 0 1 </obs>
<obs>146.422 4054 549 142 643 6705 6.5 0 1 0 0 </obs>
<obs>62.015 4481 166 86 1587 5510 14.9 0 1 0 0 </obs>
</observations>
</gretldata>