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  • Constructing inflation adjusted household income (real income) using nominal income across surveys

    Hi everyone,
    I am working with panel data of individuals surveyed over three waves- 2012, 2014, and 2017. I am pooling together income across the waves and want to make adjustments for inflation. I want to use 2012 as the base year and compute the price index (inflation) and consequently the real household income across waves. Below is a sample of the data capturing nominal income across waves(years). Is there a code I can use to accomplish this objective in Stata? Thanks very much in advance.

    Code:
    * Example generated by -dataex-. To install: ssc install dataex
    clear
    input long pid float(year hhincome)
    401014 2012  3206.335
    401014 2014      4000
    401014 2017  6351.862
    401016 2012  775.9708
    401016 2014 2117.7954
    401016 2017 1502.4348
    401018 2012      1460
    401018 2014       770
    401018 2017      5860
    401020 2012  8035.653
    401020 2014    8198.7
    401020 2017      5610
    401023 2012      3220
    401023 2014      4180
    401023 2017      5850
    401024 2012       740
    401024 2014      4140
    401024 2017 1011.4017
    401028 2012       250
    401028 2014      4620
    401028 2017      1120
    401030 2012 1706.7786
    401030 2014      4420
    401030 2017      1130
    401032 2012 1706.7786
    401032 2014 2643.9346
    401032 2017 16569.648
    401035 2012         .
    401035 2014         .
    401035 2017     27000
    401036 2012      3000
    401036 2014      2700
    401036 2017     24483
    401037 2012      3300
    401037 2014  9897.558
    401037 2017     13800
    401038 2012      3300
    401038 2014  9897.558
    401038 2017     13800
    401040 2012      1060
    401040 2014 4643.1543
    401040 2017      1200
    401043 2012      1060
    401043 2014 4643.1543
    401043 2017      1200
    401044 2012      1500
    401044 2014      5168
    401044 2017     10080
    401045 2012      1500
    401045 2014      1850
    401045 2017      2950
    401048 2012      2900
    401048 2014 11258.066
    401048 2017  17113.63
    401050 2012      2480
    401050 2014      7560
    401050 2017      4280
    401052 2012      3000
    401052 2014      2700
    401052 2017     24483
    401056 2012  9236.194
    401056 2014  2157.317
    401056 2017      3440
    401064 2012      6080
    401064 2014      6400
    401064 2017      9400
    401065 2012      1840
    401065 2014  2558.611
    401065 2017      7070
    401066 2012      1840
    401066 2014  2558.611
    401066 2017      7070
    401068 2012      1900
    401068 2014  799.9885
    401068 2017       970
    401070 2012      6100
    401070 2014      2260
    401070 2017      3720
    401073 2012      1340
    401073 2014   892.996
    401073 2017 1281.3442
    401075 2012       330
    401075 2014      3030
    401075 2017         .
    401077 2012  6371.548
    401077 2014  6338.759
    401077 2017      8220
    401080 2012      5700
    401080 2014     15355
    401080 2017      5500
    401084 2012      2040
    401084 2014  1383.359
    401084 2017  4914.289
    401085 2012 11445.645
    401085 2014     22000
    401085 2017         .
    401087 2012 2661.4946
    401087 2014      4880
    401087 2017      4900
    401088 2012 2661.4946
    401088 2014      4880
    401088 2017      4900
    401089 2012      1560
    401089 2014      3030
    401089 2017         .
    401091 2012      5270
    401091 2014  11122.92
    401091 2017     15260
    401095 2012  4327.884
    401095 2014      4650
    401095 2017  3872.185
    401097 2012 1755.5795
    401097 2014  2951.912
    401097 2017  5831.874
    401101 2012     12680
    401101 2014         .
    401101 2017         .
    401106 2012      1290
    401106 2014      8410
    401106 2017     13880
    401108 2012      7300
    401108 2014         .
    401108 2017      8300
    401111 2012     21000
    401111 2014     11800
    401111 2017     15000
    401112 2012     21000
    401112 2014     11800
    401112 2017     15000
    401114 2012         .
    401114 2014         .
    401114 2017         .
    401115 2012         .
    401115 2014         .
    401115 2017         .
    401120 2012 12945.997
    401120 2014      9200
    401120 2017 24558.635
    401123 2012 2249.4517
    401123 2014      3220
    401123 2017  5264.706
    401124 2012      1860
    401124 2014      2090
    401124 2017      2910
    401129 2012       430
    401129 2014      1120
    401129 2017      3250
    401133 2012      6426
    401133 2014   8763.86
    401133 2017     24000
    401135 2012   6424.81
    401135 2014         .
    401135 2017         .
    401136 2012 12615.625
    401136 2014     12110
    401136 2017 13271.256
    401137 2012 13719.863
    401137 2014     13000
    401137 2017      1080
    401139 2012 13719.863
    401139 2014     13000
    401139 2017     23500
    401140 2012 13719.863
    401140 2014     13000
    401140 2017     23500
    401145 2012         .
    401145 2014         .
    401145 2017         .
    401148 2012     11000
    401148 2014     26500
    401148 2017     19000
    401149 2012 14067.898
    401149 2014      1600
    401149 2017         .
    401150 2012      3730
    401150 2014      5110
    401150 2017  7124.335
    401151 2012      1080
    401151 2014       820
    401151 2017  3324.082
    401152 2012      1060
    401152 2014  967.8239
    401152 2017      5200
    401156 2012 1643.0286
    401156 2014      7420
    401156 2017  8486.299
    401159 2012 1775.5133
    401159 2014  4945.864
    401159 2017      5790
    401160 2012      1080
    401160 2014      1140
    401160 2017      2000
    401161 2012  2715.569
    401161 2014      3580
    401161 2017      2500
    401163 2012         .
    401163 2014         .
    401163 2017         .
    401166 2012      7440
    401166 2014      4020
    end

  • #2
    Not unless you also find the CPI index from somewhere, and you merge it into your data.

    An easy way to control for inflation, is to have year dummies in your panel regression. Then you do not need to bother finding the CPI.

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