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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