Hello fellow Stata users,
I have a question regarding the forvalues loop, this is the first time I want to use it. I have a variable called "Distmetro" which is the distance to the metro.
The question that needs to be answered is this:
"Now we want to estimate the marginal effect of distmetro for the non-parametric and semi-parametric models. Repeat this approximation for various distances and do this for both the non-parametric and semiparametric estimation. For example, 100m, 200m, 400m, 600m, 1000m, 2000m, 3000m. Tip: It may be useful to code a loop."
I appreciate any help how someone could help me produce the forvalues function!
I have a question regarding the forvalues loop, this is the first time I want to use it. I have a variable called "Distmetro" which is the distance to the metro.
The question that needs to be answered is this:
"Now we want to estimate the marginal effect of distmetro for the non-parametric and semi-parametric models. Repeat this approximation for various distances and do this for both the non-parametric and semiparametric estimation. For example, 100m, 200m, 400m, 600m, 1000m, 2000m, 3000m. Tip: It may be useful to code a loop."
Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input double distmetro
458.2579040527344
1916.4649658203125
1843.400146484375
2018.2406005859375
2277.740478515625
370.2373046875
1131.3287353515625
1156.41015625
309.6813049316406
564.4126586914063
1433.2822265625
1289.849365234375
1385.840087890625
1223.51025390625
1727.3624267578125
1923.1534423828125
2043.496337890625
1678.600830078125
1565.65380859375
1584.6746826171875
1998.6033935546875
371.5183410644531
505.54559326171875
640.9423217773438
640.9423217773438
1321.6929931640625
1045.044921875
2019.236083984375
398.2286376953125
1255.669189453125
2103.856201171875
2463.675537109375
2357.287353515625
1195.438720703125
1594.8824462890625
119.31536102294922
403.8852233886719
1725.53662109375
1744.9683837890625
1658.052001953125
1793.210205078125
712.0525512695313
1101.7047119140625
2019.236083984375
1721.634521484375
1321.6605224609375
911.4725341796875
832.2876586914063
564.3883666992188
619.013671875
277.81719970703125
394.5236511230469
564.499267578125
1278.1434326171875
1095.9532470703125
2109.886962890625
2057.14208984375
2064.8876953125
2503.75927734375
2194.31689453125
1194.3828125
3533.34326171875
362.93072509765625
535.9008178710938
1396.98291015625
312.04754638671875
497.8690185546875
969.5977783203125
1773.638916015625
1527.2176513671875
2009.80126953125
1769.6451416015625
2100.688232421875
1947.579833984375
1914.360595703125
2083.279296875
2499.2138671875
2436.013427734375
972.3533325195313
1372.7518310546875
176.5154266357422
976.3056030273438
1399.171630859375
1081.5009765625
1542.015625
1053.1322021484375
1044.7945556640625
465.8895568847656
993.1671752929688
993.1671752929688
1260.998046875
1839.2691650390625
1806.71484375
1786.1949462890625
2439.008544921875
2524.68505859375
2593.27587890625
753.3658447265625
690.3713989257813
1591.0655517578125
end
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