First time Statalist poster, long time follower. Thanks for this great resource.
I am working with wage data that has 24 time periods. The variables twcwage1, twcwage2, twcwage3,.... twcwage24 represent the time periods and the values are wages that individuals earned. Below is a sample of my data. The variable id is a unique individual identifier.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(id twcwage1 twcwage2 twcwage3 twcwage4 twcwage5 twcwage6 twcwage7 twcwage8 twcwage9 twcwage10 twcwage11 twcwage12 twcwage13 twcwage14 twcwage15 twcwage16 twcwage17 twcwage18 twcwage19 twcwage20 twcwage21 twcwage22 twcwage23 twcwage24) 1 14424.97 5454.47 2172.38 7475.95 3623.67 8266.98 11483.35 13923.77 0 4101.16 10501.73 6994.87 14258.09 7892.02 14677.78 13268.03 2151.58 1632.03 10939.14 8044.03 14966.76 12301.58 6528.78 4526.62 2 4853.76 11903.3 12568.52 8264.54 2947.44 12073.08 6502.1 14233.04 2129.83 8858.49 14747.98 7006.83 6516.13 9847.42 13853.07 8457.29 9351.71 2314.42 4455.06 12297.85 7553.74 12679.37 14903.33 2053.81 3 14598.3 5555.92 12205.94 9665 0 6742.81 1823.49 0 8389.34 0 5454.41 8668.01 6547.18 14457.23 12463.6 6413.48 6634.47 13204.18 12011.79 3101.11 6495.12 4445.22 8546.96 4130.96 4 1932.64 2813.21 3926.87 4650.35 7102.57 4024.89 3343.85 2998.88 3575.33 14957.5 11875.44 10075.93 13262.63 4582.33 14298.61 6373.88 6675.03 5901.78 3962.03 10664.47 12129.49 12443.99 4218.34 8501.03 5 13524.21 2452.5 0 9328.19 6095.36 6538.84 14607.75 10607.04 10080.55 14981.65 1617.54 9529.7 8482.97 13861.68 8083.54 6739.79 12853.41 2370.7 9294.33 2769.99 13772.91 6044.32 7015.51 13075.92 6 7441.03 13554.42 9841.29 13084.98 6017.36 7191.84 2678.67 0 11430.44 10894.58 6929.55 10585.47 5021.61 10027.56 11200.41 4117.87 11682.88 13141.5 11617.82 4261.87 10287.36 14587.11 12735.18 9065.99 7 14334.46 14203.28 13721.12 11842.04 10169.21 5357.79 0 13079.71 13700.71 12950.95 11169.27 3369.16 2625.83 11944.33 0 3927.54 1946.54 9544.32 7571.48 5597.54 9915.25 10330.47 10627 12150.96 8 10374.71 3817.62 11306.05 11455.5 3296.03 9739.45 0 4519.59 7800.11 10514.02 0 11850.34 2562.66 4347.68 5415.03 3034.74 6535.96 7395.3 0 2512.28 5778.15 13878.02 11935.85 8307.78 9 12803.48 13301.84 2004.6 5114.32 13063.29 9699.24 4678.55 14494.23 5102.92 8471.06 7154.6 14570.28 0 7489.07 6247.36 2818.76 6716.95 14427.57 9216.64 0 1626.04 14307.02 5364.81 11395.73 10 13638.55 13023.8 4481.94 13272.87 0 5672.35 6235.91 5701.39 6264.48 12928.25 10047.37 10933.26 10074.58 7893.65 12362.12 7390.65 8461.34 13726.15 7249.6 7075.94 9896.47 11279.99 10610 8096.06 11 14657.92 0 4781.83 14775.16 12370.37 0 6022.28 2563.49 8435.25 9696.16 9035.82 3774.2 2200.07 2335.71 5071.95 4653.26 5219.47 10548.7 13572.9 2468.76 11361.58 14340.73 13982.3 5194.59 12 2758.25 0 6773.04 3081.94 0 2746.19 13877.89 12829.2 12676.14 2211.1 2193.75 9299.16 4549.23 9607.71 1542.08 14655.06 2232.72 13275.68 0 7044.37 12671.71 4263.46 8925.02 8981.86 13 7792.97 7528.4 6251.25 9333.24 9193.49 0 8193.82 13986.84 2028.61 12245.43 14939.55 9983.74 4280.02 3079.87 11707.39 2919.55 0 0 2319.09 6888.25 0 5582.77 13334.77 12475.53 14 6796.29 10506.12 11018.06 8860.01 2954.22 6893.12 13298.65 0 7218.22 2293.77 2592.77 1593.46 6399.95 14825.68 3853.68 7819.25 0 5574.17 0 1624.19 6440.36 5657.44 7928.91 11223.04 15 8689.6 0 8692.99 10680.21 2880.66 11664.42 0 11123.44 11722.5 3595.7 14557.11 2296.03 4935.62 10692.08 0 14927.27 11363.96 3271.04 5536.67 10847.73 7327.8 7010.88 12786.93 11230.23 16 9303.43 9137.99 11439.58 3825.3 7624.42 0 11070.5 10673.43 9135.99 7739.39 2557.49 13181.07 2645.68 6786.95 4265.29 5635.35 4368.09 13144.7 3862.68 4859.06 14449.64 11696.09 5595.21 10853.6 17 2155.19 5470.53 2517.65 11666.24 4765.71 12700.25 5033.77 6397.98 10113.89 8720.9 12151.2 8068.58 4966.89 14398.62 11645.72 12367.92 9802.44 5480.99 5311.36 7278.5 14804.43 8072.8 3511.41 12752.78 18 3886.64 0 5645.1 10753.37 7095.96 0 4477.53 13155.43 9014.54 8202.76 2598.47 14735.47 6442.4 10309.98 11826.95 6354.62 3673.36 4460.37 14855.72 11778.3 0 10759.08 6896.12 8234.72 19 12852.5 10789.16 0 2773.76 1870.67 0 1571.7 7922.01 4682.85 14588.06 12053.67 8589.41 10001.18 3071.72 7899.94 10771.72 1661.51 2132.91 14219.73 1832.53 1595.01 3912.33 4360.58 5302.18 20 0 6876.8 0 8361.33 1892.24 5091.36 6995.07 12046.62 6783.31 2418.21 11333.68 2302.99 12451.49 13446.51 4863.94 6320.14 7015.25 7280.54 6557.88 7571.45 13381.5 14725.07 6633.58 1871.72 end
I am trying to identify individuals who had positive wages for at least 12 consecutive time periods. For example, an individual who had positive wages from twcwage1 to twcwage12 has positive wages for 12 consecutive time periods. Likewise, someone who with positive wages from twcwage3 to twcwage14 also has positive wages for 12 consecutive time periods. Below is the code that I manually wrote to estimate the different possible scenarios.
Code:
* generate time_period0 = 1 if twcwage1>0 & twcwage2>0 & twcwage3>0 & twcwage4>0 & twcwage5>0 & twcwage6>0 & twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 generate time_period1 =1 if twcwage2>0 & twcwage3>0 & twcwage4>0 & twcwage5>0 & twcwage6>0 & twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 generate time_period2 =1 if twcwage3>0 & twcwage4>0 & twcwage5>0 & twcwage6>0 & twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 generate time_period3 =1 if twcwage4>0 & twcwage5>0 & twcwage6>0 & twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 generate time_period4 =1 if twcwage5>0 & twcwage6>0 & twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 generate time_period5 =1 if twcwage6>0 & twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 generate time_period6 =1 if twcwage7>0 & twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 generate time_period7 =1 if twcwage8>0 & twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 & twcwage19>0 generate time_period8 =1 if twcwage9>0 & twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 & twcwage19>0 & twcwage20>0 generate time_period9 =1 if twcwage10>0 & twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 & twcwage19>0 & twcwage20>0 & twcwage21>0 generate time_period10 =1 if twcwage11>0 & twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 & twcwage19>0 & twcwage20>0 & twcwage21>0 & twcwage22>0 generate time_period11 =1 if twcwage12>0 & twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 & twcwage19>0 & twcwage20>0 & twcwage21>0 & twcwage22>0 & twcwage23>0 generate time_period12 =1 if twcwage13>0 & twcwage14>0 & twcwage15>0 & twcwage16>0 & twcwage17>0 & twcwage18>0 & twcwage19>0 & twcwage20>0 & twcwage21>0 & twcwage22>0 & twcwage23>0 & twcwage24>0
Code:
foreach qtr in 0/12 {
local m1 =`qtr'+1
local m2 =`qtr'+2
local m3 =`qtr'+3
local m4 =`qtr'+4
local m5 =`qtr'+5
local m6 =`qtr'+6
local m7 =`qtr'+7
local m8 =`qtr'+8
local m9 =`qtr'+9
local m10 =`qtr'+10
local m11 =`qtr'+11
local m12 =`qtr'+12
generate start`qtr'=1 if twcwage`m1'>0 & twcwage`m2'>0 & twcwage`m3'>0 & twcwage`m4'>0& twcwage`m5'>0 & twcwage`m6'>0 & twcwage`m7'>0 & twcwage`m8'>0 & twcwage`m9'>0 & twcwage`m10'>0 &twcwage`m11'>0 & twcwage`m12'>0
}
0 Response to Writing loop to identify individuals with consecutive positive values (n, n+1, n+2, ...)
Post a Comment