Announcement

Collapse
No announcement yet.
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • Including state and district dummies in regression

    This might be more of a "statistics" question rather than a Stata question.

    I have data for one year on child-level outcomes. Suppose I run

    Code:
    reg read_code child_age
    I now want to control for regional variation. So I run

    Code:
    reg read_code child_age i.dist1
    to control for district-level variation.

    I also run

    Code:
    reg read_code child_age i.state1
    to control for state-level variation.


    My understanding is that both state and district dummies should not be included together, because districts are nested within states. However, if I run

    Code:
    reg read_code child_age i.state1 i.dist1
    , I still get the coefficients for most districts and states, even though Stata automatically drops some districts.

    Strangely, if I run

    Code:
    reg read_code child_age i.dist1 i.state1
    , Stata drops all states and reports the coefficients only on districts.

    My questions:

    1. Why does Stata estimate the model with -i.state1 i.dist1- but drops state if I reverse the order? Does the order matter? Should the "higher" level (e.g. state) be always specified last, so that Stata drops them, as needed?

    2. If I use district-level income, instead of district dummy, can/should I include state dummies? Pls note I only have one year of data, so this is not a panel.

    3. If I want to control for village-level variation (e.g village-level school quality, say), is it appropriate to include district and/or state dummies? Villages are nested within districts.

    My data sample is given below. Thank you for your help!

    ----------------------- copy starting from the next line -----------------------
    Code:
    * Example generated by -dataex-. For more info, type help dataex
    clear
    input byte(read_code child_age) long(state1 dist1)
    . 10 25 442
    .  . 10 162
    4 13  4  79
    2  5 25 438
    .  4 15 247
    5 10 13 189
    5 13 29 546
    5  7 13 190
    5  8  9 121
    . 10 14 225
    5  9 11 169
    .  . 19 351
    .  3 14 217
    1  6 14 226
    4 12 24 408
    4  9  1  13
    1 15 29 544
    5 12 14 228
    .  4 29 504
    1  7 22 390
    2 13 16 288
    .  . 24 418
    3  5 18 341
    .  4 29 523
    .  . 29 546
    .  4  4  69
    .  4 21 366
    .  3  5 104
    4 14 29 518
    2  6 29 559
    4  8 22 389
    3 12  3  38
    4 11  4  73
    2 11  4  76
    2  5 22 388
    4  9 27 475
    .  . 29 518
    4 10 14 217
    4 13 27 472
    5 12 14 239
    5 12 10 160
    4 15 16 258
    3 11 29 526
    5 13 16 258
    5 11 11 166
    5 13 24 424
    2  5 21 369
    5 10 12 175
    5 13 10 150
    2 10  4  92
    5 10 16 294
    5 16  3  46
    .  4 21 367
    5 15  3  38
    2  6 27 487
    1  7 25 451
    .  . 13 196
    .  4  9 139
    5 10 13 191
    5 12 10 162
    3 10 17 316
    . 16 22 402
    .  3 29 506
    5 12 22 392
    1  6 29 526
    5  8 14 230
    .  .  7 113
    5 11  9 121
    . 16 17 334
    3  9  4  63
    1  8  3  43
    .  3 30 579
    5 14  3  38
    .  4 17 323
    . 16 27 469
    2  7 31 596
    5 15 25 451
    5 14  4  66
    3 13  9 135
    .  . 30 575
    .  8 16 289
    3 11 29 561
    .  . 24 408
    2  6 14 232
    3  9 17 323
    5 14 29 548
    4 14 16 297
    .  . 27 472
    5 13 16 302
    .  3  9 131
    .  . 27 470
    1  6 29 506
    3 11 22 390
    .  4 19 348
    .  5 13 192
    .  .  3  34
    .  5 16 267
    5 11 17 324
    5 14  4  83
    1  5 16 263
    5 16  4  63
    .  4 29 543
    5  8 20 359
    3  6 31 588
    5 14 13 201
    .  . 29 557
    5 13 17 333
    . 10  8 114
    1  5 22 383
    3 13 19 353
    . 14 25 446
    2  7  5 109
    5 16 16 285
    5 13  4  79
    5 12 14 221
    .  4  1   2
    .  . 11 164
    1  6  9 118
    4  8 30 570
    1  6 29 559
    2  9 29 498
    . 16 25 433
    5 16 26 460
    .  . 15 243
    .  6 25 430
    5 13  9 137
    4 16 29 505
    . 11 11 173
    4 10 25 440
    .  . 14 235
    5 14 17 313
    5 12 16 283
    2  9 29 506
    .  6 29 556
    5 12 10 153
    . 12 22 397
    4 10 29 528
    .  4  4  72
    .  4 22 373
    3  6 10 144
    1  9  4  86
    1 11 29 550
    5 15 29 510
    2  8 22 379
    3 16 24 424
    .  4  4  63
    5 14 29 512
    . 15 29 553
    5  8  4  82
    .  . 11 173
    2  6  4  62
    5 10  4  66
    2 11 31 580
    5  9  4  88
    .  . 24 408
    . 14  4  83
    .  3  4  68
    5 10 29 560
    .  . 31 593
    5 14 29 508
    5 15 29 566
    5 13 15 253
    1  6 29 518
    5 14 12 181
    2  5 22 392
    . 15 16 274
    .  3 31 593
    . 15 31 584
    .  . 29 524
    4 11 17 334
    5 10 11 174
    5 16  2  23
    1  5 16 290
    .  . 17 319
    . 11  3  53
    5 15 30 574
    5 15 24 411
    .  . 16 262
    .  . 18 340
    3  7 24 415
    5 15  9 132
    5 14  4  69
    2  8 29 550
    5 10 16 261
    3  9 14 233
    5 15 29 518
    . 13 16 275
    .  4  4  58
    3  6 16 291
    5  6 29 563
    5 13 14 234
    1  5  5 110
    5 14 10 161
    5 13 13 199
    .  . 22 375
    5 16 25 450
    1  5 29 508
    4  8  3  50
    5 13 13 211
    . 14  4  74
    . 13 16 300
    3 10 14 226
    .  9 25 433
    5 10 11 164
    5 15 29 506
    5 13 31 595
    2  5 18 343
    . 11  1   8
    .  4  3  55
    5 15 22 374
    5 14  2  27
    .  5 25 451
    .  . 11 168
    5 13 26 459
    5 13 29 520
    . 13 10 155
    5 16 29 545
    3 15  1  20
    5 13 27 487
    3 16 29 503
    1  7 16 255
    .  4 24 413
    5 11  9 119
    5  9  7 112
    5  9  7 112
    2  7 16 294
    4  9  1  17
    5 13 15 254
    1  5 13 198
    3 12 13 202
    2 11 30 578
    3  9 11 166
    2 12 22 386
    .  3 29 536
    .  3 29 555
    5  7 10 144
    .  . 16 270
    . 11  4  91
    5 10  4  93
    1  5  4  92
    5  8 11 171
    . 13 29 541
    4 15 10 154
    .  . 29 564
    .  .  4  75
    5 16 21 365
    . 12 29 523
    .  7  3  35
    1 13 13 206
    4 13 13 192
    5 16  4  92
    5 10 14 233
    5 15 31 583
    .  .  3  45
    1  5 19 353
    .  8 14 221
    1 10 25 442
    .  . 11 163
    3 14 16 256
    .  4 31 594
    1  9  4  73
    .  4 10 147
    5  9 29 499
    .  4 25 441
    4 12 18 341
    5 12 12 185
    .  .  1  19
    1  9  4  84
    5 12 13 193
    3  9 12 175
    .  .  5 110
    5 13 25 453
    1  5 12 186
    5 16 20 360
    5 15 29 514
    2  5 29 509
    5 16 29 546
    .  . 10 152
    5  8  4  68
    5 12  4  59
    .  4 31 583
    .  .  1  13
    5  7  5  99
    .  .  3  36
    .  4 29 521
    .  7 24 408
    5 13 29 499
    5 12  9 137
    2  6  2  27
    1  8 25 448
    .  7 16 257
    .  . 25 442
    5 13 25 439
    .  . 27 465
    1  9 14 236
    5 10 11 171
    .  7 16 261
    3  7 27 475
    5 14 17 321
    5 15  2  27
    5 16 24 409
    .  3 17 322
    .  9  4  79
    5 16 30 569
    .  3 17 337
    5 13 17 323
    5 12 29 503
    5 14 30 576
    5 15 13 201
    .  9 30 574
    1  7 25 438
    .  6 29 540
    . 11 30 578
    5 15  4  74
    .  6 29 547
    . 11 16 270
    5 15 30 575
    . 16 17 316
    5 15 11 163
    4 14 10 154
    2  9 25 425
    5 15  3  50
    5 14 11 171
    5 16 22 377
    3  6 24 420
    1  6 12 181
    .  3  5 100
    3  7  4  82
    3 11 22 392
    5 15 29 499
    .  . 27 483
    5 10 14 224
    2  6  9 116
    . 13  2  28
    1  9  4  65
    2  5  2  27
    5 10 27 470
    .  . 27 472
    5 16  4  87
    .  3 22 395
    3 12 28 493
    3 13 27 484
    .  . 24 413
    3  9 17 313
    5 10 16 294
    5  9 18 346
    .  4 29 530
    .  3 25 436
    3 10 13 192
    1 14 29 555
    5 14  4  76
    3  5 29 556
    2  5  3  33
    .  3 27 468
    .  4 12 188
    2  6 13 205
    5 12 21 368
    2  7 19 352
    3  8 27 469
    1  5 17 319
    .  4 16 286
    5 14 29 503
    .  .  3  45
    1  5  4  62
    .  .  3  38
    5 15 25 434
    2  6 13 189
    .  6 30 574
    .  . 29 517
    .  4 29 511
    5 12 22 383
    2  7 17 327
    5 12 25 427
    1  6 29 506
    .  . 26 458
    4 15  1  15
    4  8 18 342
    3 13 31 591
    .  8  1   5
    .  . 30 572
    5 16 31 585
    2  5 29 542
    1  6 29 559
    2  7  5 108
    .  6 16 293
    2  9 16 273
    5 16 29 547
    4 11 22 399
    5 15  3  48
    5 14 27 473
    2  6 31 587
    4  7 27 468
    .  . 25 456
    3  9  3  56
    5 10 22 377
    .  . 29 511
    4 12 10 151
    3  8 17 314
    2  7 16 304
    5 14 29 522
    5 12 29 512
    . 14  4  60
    1  6 29 545
    .  3  9 117
    . 11  4  75
    5 14 29 541
    3  7 11 168
    .  3 14 218
    5 12 27 486
    1 16  5  96
    5 12  4  91
    3  6 29 498
    2  9  3  35
    . 14 25 453
    .  .  3  46
    .  . 17 321
    2 10  4  66
    2  5 27 478
    4 13 13 198
    4  8 10 152
    .  9  3  36
    5 16 10 158
    .  . 27 472
    3 12 10 143
    5 13 29 531
    . 15 10 143
    .  . 14 224
    2 10 19 351
    .  9 29 500
    2  9 12 177
    5 11 24 413
    .  . 17 328
    2 10  5  96
    . 15 29 533
    5 13 19 352
    .  . 13 193
    5  9  5 103
    4  9 10 158
    . 14 29 523
    .  .  3  36
    3  7  7 112
    .  . 25 437
    5 10  5 106
    .  4 29 532
    . 12  3  55
    .  4 27 464
    1  5  1   8
    . 16 16 271
    .  . 15 248
    1  5 13 200
    5 11 16 284
    1  8 29 526
    5 13 21 364
    .  .  3  42
    4 16 21 363
    5 10 29 549
    3 12 17 324
    .  . 27 485
    3 15  3  38
    5  8 10 153
    1  8 31 588
    .  5 17 306
    2  8 13 189
    5 14  9 126
    .  4 29 500
    .  4 25 429
    . 11 14 222
    5 14  9 134
    .  7 16 289
    2  9 13 191
    5 10 14 217
    5 12  4  64
    .  4 17 305
    5 14 29 505
    3  8 10 144
    1  6  2  27
    .  . 11 168
    . 12 17 310
    1  7 13 209
    . 12 30 571
    5 15 29 523
    5  6 11 169
    5 12 14 229
    1  5 13 201
    3 10 27 476
    . 14 15 249
    5 12 27 462
    .  .  1   4
    .  4 31 582
    .  3 25 434
    5 10 18 340
    .  . 15 246
    .  4 14 242
    4 13 16 299
    5 12 25 430
    2  6 29 533
    3 16 18 338
    .  8  7 112
    5 12 21 366
    .  4 16 271
    end
    label values read_code read_code
    label def read_code 1 "Can read nothing", modify
    label def read_code 2 "Can read letters", modify
    label def read_code 3 " Can read words", modify
    label def read_code 4 "Can read class 1 text", modify
    label def read_code 5 "Can read class 2 text", modify
    label values state1 state1
    label def state1 1 "ANDHRA PRADESH", modify
    label def state1 2 "ARUNACHAL PARDESH", modify
    label def state1 3 "ASSAM", modify
    label def state1 4 "BIHAR", modify
    label def state1 5 "CHHATTISGARH", modify
    label def state1 7 "DAMAN & DIU", modify
    label def state1 8 "GOA", modify
    label def state1 9 "GUJARAT", modify
    label def state1 10 "HARYANA", modify
    label def state1 11 "HIMACHAL PRADESH", modify
    label def state1 12 "JAMMU & KASHMIR", modify
    label def state1 13 "JHARKHAND", modify
    label def state1 14 "KARNATAKA", modify
    label def state1 15 "KERALA", modify
    label def state1 16 "MADHYA PRADESH", modify
    label def state1 17 "MAHARASHTRA", modify
    label def state1 18 "MANIPUR", modify
    label def state1 19 "MEGHALAYA", modify
    label def state1 20 "MIZORAM", modify
    label def state1 21 "NAGALAND", modify
    label def state1 22 "ORISSA", modify
    label def state1 24 "PUNJAB", modify
    label def state1 25 "RAJASTHAN", modify
    label def state1 26 "SIKKIM", modify
    label def state1 27 "TAMIL NADU", modify
    label def state1 28 "TRIPURA", modify
    label def state1 29 "UTTAR PRADESH", modify
    label def state1 30 "UTTARANCHAL", modify
    label def state1 31 "WEST BENGAL", modify
    label values dist1 dist1
    label def dist1 2 "ANDHRA PRADESHAnantapur", modify
    label def dist1 4 "ANDHRA PRADESHEastGodavari", modify
    label def dist1 5 "ANDHRA PRADESHGuntur", modify
    label def dist1 8 "ANDHRA PRADESHKrishna", modify
    label def dist1 13 "ANDHRA PRADESHNizamabad", modify
    label def dist1 15 "ANDHRA PRADESHRangareddy", modify
    label def dist1 17 "ANDHRA PRADESHSrikakulam", modify
    label def dist1 19 "ANDHRA PRADESHVizianagaram", modify
    label def dist1 20 "ANDHRA PRADESHWarangal", modify
    label def dist1 23 "ARUNACHAL PARDESHChanglang", modify
    label def dist1 27 "ARUNACHAL PARDESHLowerSubansiri", modify
    label def dist1 28 "ARUNACHAL PARDESHTirap", modify
    label def dist1 33 "ASSAMBongaigaon", modify
    label def dist1 34 "ASSAMCachar", modify
    label def dist1 35 "ASSAMChirang", modify
    label def dist1 36 "ASSAMDarrang", modify
    label def dist1 38 "ASSAMDhubri", modify
    label def dist1 42 "ASSAMGolaghat", modify
    label def dist1 43 "ASSAMHailakandi", modify
    label def dist1 45 "ASSAMKamrup", modify
    label def dist1 46 "ASSAMKarbiAnglong", modify
    label def dist1 48 "ASSAMKokrajhar", modify
    label def dist1 50 "ASSAMMorigaon", modify
    label def dist1 53 "ASSAMSivasagar", modify
    label def dist1 55 "ASSAMTinsukia", modify
    label def dist1 56 "ASSAMUdalguri", modify
    label def dist1 58 "BIHARArwal", modify
    label def dist1 59 "BIHARAurangabad", modify
    label def dist1 60 "BIHARBanka", modify
    label def dist1 62 "BIHARBhagalpur", modify
    label def dist1 63 "BIHARBhojpur", modify
    label def dist1 64 "BIHARBuxar", modify
    label def dist1 65 "BIHARDarbhanga", modify
    label def dist1 66 "BIHARGaya", modify
    label def dist1 68 "BIHARJamui", modify
    label def dist1 69 "BIHARJehanabad", modify
    label def dist1 72 "BIHARKhagaria", modify
    label def dist1 73 "BIHARKishanganj", modify
    label def dist1 74 "BIHARLakhisarai", modify
    label def dist1 75 "BIHARMadhepura", modify
    label def dist1 76 "BIHARMadhubani", modify
    label def dist1 79 "BIHARNalanda", modify
    label def dist1 82 "BIHARPatna", modify
    label def dist1 83 "BIHARPurbaChamparan", modify
    label def dist1 84 "BIHARPurnia", modify
    label def dist1 86 "BIHARSaharsa", modify
    label def dist1 87 "BIHARSamastipur", modify
    label def dist1 88 "BIHARSaran", modify
    label def dist1 91 "BIHARSitamarhi", modify
    label def dist1 92 "BIHARSiwan", modify
    label def dist1 93 "BIHARSupaul", modify
    label def dist1 96 "CHHATTISGARHBilaspur", modify
    label def dist1 99 "CHHATTISGARHDurg", modify
    label def dist1 100 "CHHATTISGARHJanjgir-Champa", modify
    label def dist1 103 "CHHATTISGARHKorba", modify
    label def dist1 104 "CHHATTISGARHKoriya", modify
    label def dist1 106 "CHHATTISGARHRaigarh", modify
    label def dist1 108 "CHHATTISGARHRajnandgaon", modify
    label def dist1 109 "CHHATTISGARHSurguja", modify
    label def dist1 110 "CHHATTISGARHUttarBastarKanker", modify
    label def dist1 112 "DAMAN & DIUDaman", modify
    label def dist1 113 "DAMAN & DIUDiu", modify
    label def dist1 114 "GOANorthGoa", modify
    label def dist1 116 "GUJARATAhmadabad", modify
    label def dist1 117 "GUJARATAmreli", modify
    label def dist1 118 "GUJARATAnand", modify
    label def dist1 119 "GUJARATBanasKantha", modify
    label def dist1 121 "GUJARATBhavnagar", modify
    label def dist1 126 "GUJARATKachchh", modify
    label def dist1 131 "GUJARATPanchMahals", modify
    label def dist1 132 "GUJARATPatan", modify
    label def dist1 134 "GUJARATRajkot", modify
    label def dist1 135 "GUJARATSabarKantha", modify
    label def dist1 137 "GUJARATSurendranagar", modify
    label def dist1 139 "GUJARATTheDangs", modify
    label def dist1 143 "HARYANABhiwani", modify
    label def dist1 144 "HARYANAFaridabad", modify
    label def dist1 147 "HARYANAHisar", modify
    label def dist1 150 "HARYANAKaithal", modify
    label def dist1 151 "HARYANAKarnal", modify
    label def dist1 152 "HARYANAKurukshetra", modify
    label def dist1 153 "HARYANAMahendragarh", modify
    label def dist1 154 "HARYANAMewat", modify
    label def dist1 155 "HARYANAPalwal", modify
    label def dist1 158 "HARYANARewari", modify
    label def dist1 160 "HARYANASirsa", modify
    label def dist1 161 "HARYANASonipat", modify
    label def dist1 162 "HARYANAYamunanagar", modify
    label def dist1 163 "HIMACHAL PRADESHBilaspur", modify
    label def dist1 164 "HIMACHAL PRADESHChamba", modify
    label def dist1 166 "HIMACHAL PRADESHKangra", modify
    label def dist1 168 "HIMACHAL PRADESHKullu", modify
    label def dist1 169 "HIMACHAL PRADESHLahul&Spiti", modify
    label def dist1 171 "HIMACHAL PRADESHShimla", modify
    label def dist1 173 "HIMACHAL PRADESHSolan", modify
    label def dist1 174 "HIMACHAL PRADESHUna", modify
    label def dist1 175 "JAMMU & KASHMIRAnantnag", modify
    label def dist1 177 "JAMMU & KASHMIRBandipore", modify
    label def dist1 181 "JAMMU & KASHMIRKargil", modify
    label def dist1 185 "JAMMU & KASHMIRPunch", modify
    label def dist1 186 "JAMMU & KASHMIRRajouri", modify
    label def dist1 188 "JAMMU & KASHMIRUdhampur", modify
    label def dist1 189 "JHARKHANDBokaro", modify
    label def dist1 190 "JHARKHANDChatra", modify
    label def dist1 191 "JHARKHANDDeoghar", modify
    label def dist1 192 "JHARKHANDDhanbad", modify
    label def dist1 193 "JHARKHANDDumka", modify
    label def dist1 196 "JHARKHANDGodda", modify
    label def dist1 198 "JHARKHANDHazaribagh", modify
    label def dist1 199 "JHARKHANDJamtara", modify
    label def dist1 200 "JHARKHANDKhunti", modify
    label def dist1 201 "JHARKHANDKodarma", modify
    label def dist1 202 "JHARKHANDLatehar", modify
    label def dist1 205 "JHARKHANDPalamu", modify
    label def dist1 206 "JHARKHANDPashchimiSinghbhum", modify
    label def dist1 209 "JHARKHANDRanchi", modify
    label def dist1 211 "JHARKHANDSaraikela-Kharsawan", modify
    label def dist1 217 "KARNATAKABellary", modify
    label def dist1 218 "KARNATAKABidar", modify
    label def dist1 221 "KARNATAKAChikkaballapura", modify
    label def dist1 222 "KARNATAKAChikmagalur", modify
    label def dist1 224 "KARNATAKADakshinaKannada", modify
    label def dist1 225 "KARNATAKADavanagere", modify
    label def dist1 226 "KARNATAKADharwad", modify
    label def dist1 228 "KARNATAKAGulbarga", modify
    label def dist1 229 "KARNATAKAHassan", modify
    label def dist1 230 "KARNATAKAHaveri", modify
    label def dist1 232 "KARNATAKAKolar", modify
    label def dist1 233 "KARNATAKAKoppal", modify
    label def dist1 234 "KARNATAKAMandya", modify
    label def dist1 235 "KARNATAKAMysore", modify
    label def dist1 236 "KARNATAKARaichur", modify
    label def dist1 239 "KARNATAKATumkur", modify
    label def dist1 242 "KARNATAKAYadgir", modify
    label def dist1 243 "KERALAErnakulam", modify
    label def dist1 246 "KERALAKasaragod", modify
    label def dist1 247 "KERALAKollam", modify
    label def dist1 248 "KERALAKottayam", modify
    label def dist1 249 "KERALAKozhikode", modify
    label def dist1 253 "KERALAThiruvananthapuram", modify
    label def dist1 254 "KERALAThrissur", modify
    label def dist1 255 "MADHYA PRADESHAlirajpur", modify
    label def dist1 256 "MADHYA PRADESHAnuppur", modify
    label def dist1 257 "MADHYA PRADESHAshoknagar", modify
    label def dist1 258 "MADHYA PRADESHBalaghat", modify
    label def dist1 261 "MADHYA PRADESHBhind", modify
    label def dist1 262 "MADHYA PRADESHBhopal", modify
    label def dist1 263 "MADHYA PRADESHBurhanpur", modify
    label def dist1 267 "MADHYA PRADESHDatia", modify
    label def dist1 270 "MADHYA PRADESHDindori", modify
    label def dist1 271 "MADHYA PRADESHGuna", modify
    label def dist1 273 "MADHYA PRADESHHarda", modify
    label def dist1 274 "MADHYA PRADESHHoshangabad", modify
    label def dist1 275 "MADHYA PRADESHIndore", modify
    label def dist1 283 "MADHYA PRADESHMorena", modify
    label def dist1 284 "MADHYA PRADESHNarsimhapur", modify
    label def dist1 285 "MADHYA PRADESHNeemuch", modify
    label def dist1 286 "MADHYA PRADESHPanna", modify
    label def dist1 288 "MADHYA PRADESHRajgarh", modify
    label def dist1 289 "MADHYA PRADESHRatlam", modify
    label def dist1 290 "MADHYA PRADESHRewa", modify
    label def dist1 291 "MADHYA PRADESHSagar", modify
    label def dist1 293 "MADHYA PRADESHSehore", modify
    label def dist1 294 "MADHYA PRADESHSeoni", modify
    label def dist1 297 "MADHYA PRADESHSheopur", modify
    label def dist1 299 "MADHYA PRADESHSidhi", modify
    label def dist1 300 "MADHYA PRADESHSingrauli", modify
    label def dist1 302 "MADHYA PRADESHUjjain", modify
    label def dist1 304 "MADHYA PRADESHVidisha", modify
    label def dist1 305 "MAHARASHTRAAhmadnagar", modify
    label def dist1 306 "MAHARASHTRAAkola", modify
    label def dist1 310 "MAHARASHTRABid", modify
    label def dist1 313 "MAHARASHTRADhule", modify
    label def dist1 314 "MAHARASHTRAGadchiroli", modify
    label def dist1 316 "MAHARASHTRAHingoli", modify
    label def dist1 319 "MAHARASHTRAKolhapur", modify
    label def dist1 321 "MAHARASHTRANagpur", modify
    label def dist1 322 "MAHARASHTRANanded", modify
    label def dist1 323 "MAHARASHTRANandurbar", modify
    label def dist1 324 "MAHARASHTRANashik", modify
    label def dist1 327 "MAHARASHTRAPune", modify
    label def dist1 328 "MAHARASHTRARaigarh", modify
    label def dist1 333 "MAHARASHTRASolapur", modify
    label def dist1 334 "MAHARASHTRAThane", modify
    label def dist1 337 "MAHARASHTRAYavatmal", modify
    label def dist1 338 "MANIPURBishnupur", modify
    label def dist1 340 "MANIPURChurachandpur", modify
    label def dist1 341 "MANIPURImphalEast", modify
    label def dist1 342 "MANIPURImphalWest", modify
    label def dist1 343 "MANIPURSenapati", modify
    label def dist1 346 "MANIPURUkhrul", modify
    label def dist1 348 "MEGHALAYAEastKhasiHills", modify
    label def dist1 351 "MEGHALAYASouthGaroHills", modify
    label def dist1 352 "MEGHALAYAWestGaroHills", modify
    label def dist1 353 "MEGHALAYAWestKhasiHills", modify
    label def dist1 359 "MIZORAMMamit", modify
    label def dist1 360 "MIZORAMSaiha", modify
    label def dist1 363 "NAGALANDKiphire", modify
    label def dist1 364 "NAGALANDKohima", modify
    label def dist1 365 "NAGALANDLongleng", modify
    label def dist1 366 "NAGALANDMokokchung", modify
    label def dist1 367 "NAGALANDMon", modify
    label def dist1 368 "NAGALANDPeren", modify
    label def dist1 369 "NAGALANDPhek", modify
    label def dist1 373 "ORISSAAnugul", modify
    label def dist1 374 "ORISSABalangir", modify
    label def dist1 375 "ORISSABaleshwar", modify
    label def dist1 377 "ORISSABaudh", modify
    label def dist1 379 "ORISSACuttack", modify
    label def dist1 383 "ORISSAGanjam", modify
    label def dist1 386 "ORISSAJharsuguda", modify
    label def dist1 388 "ORISSAKandhamal", modify
    label def dist1 389 "ORISSAKendrapara", modify
    label def dist1 390 "ORISSAKendujhar", modify
    label def dist1 392 "ORISSAKoraput", modify
    label def dist1 395 "ORISSANabarangapur", modify
    label def dist1 397 "ORISSANuapada", modify
    label def dist1 399 "ORISSARayagada", modify
    label def dist1 402 "ORISSASundargarh", modify
    label def dist1 408 "PUNJABFaridkot", modify
    label def dist1 409 "PUNJABFatehgarhSahib", modify
    label def dist1 411 "PUNJABGurdaspur", modify
    label def dist1 413 "PUNJABJalandhar", modify
    label def dist1 415 "PUNJABLudhiana", modify
    label def dist1 418 "PUNJABMuktsar", modify
    label def dist1 420 "PUNJABRupnagar", modify
    label def dist1 424 "PUNJABTarnTaran", modify
    label def dist1 425 "RAJASTHANAjmer", modify
    label def dist1 427 "RAJASTHANBanswara", modify
    label def dist1 429 "RAJASTHANBarmer", modify
    label def dist1 430 "RAJASTHANBharatpur", modify
    label def dist1 433 "RAJASTHANBundi", modify
    label def dist1 434 "RAJASTHANChittaurgarh", modify
    label def dist1 436 "RAJASTHANDausa", modify
    label def dist1 437 "RAJASTHANDhaulpur", modify
    label def dist1 438 "RAJASTHANDungarpur", modify
    label def dist1 439 "RAJASTHANGanganagar", modify
    label def dist1 440 "RAJASTHANHanumangarh", modify
    label def dist1 441 "RAJASTHANJaipur", modify
    label def dist1 442 "RAJASTHANJaisalmer", modify
    label def dist1 446 "RAJASTHANJodhpur", modify
    label def dist1 448 "RAJASTHANKota", modify
    label def dist1 450 "RAJASTHANPali", modify
    label def dist1 451 "RAJASTHANPratapgarh", modify
    label def dist1 453 "RAJASTHANSawaiMadhopur", modify
    label def dist1 456 "RAJASTHANTonk", modify
    label def dist1 458 "SIKKIMEastDistrict", modify
    label def dist1 459 "SIKKIMNorthDistrict", modify
    label def dist1 460 "SIKKIMSouthDistrict", modify
    label def dist1 462 "TAMIL NADUAriyalur", modify
    label def dist1 464 "TAMIL NADUCuddalore", modify
    label def dist1 465 "TAMIL NADUDharmapuri", modify
    label def dist1 468 "TAMIL NADUKancheepuram", modify
    label def dist1 469 "TAMIL NADUKanniyakumari", modify
    label def dist1 470 "TAMIL NADUKarur", modify
    label def dist1 472 "TAMIL NADUMadurai", modify
    label def dist1 473 "TAMIL NADUNagapattinam", modify
    label def dist1 475 "TAMIL NADUPerambalur", modify
    label def dist1 476 "TAMIL NADUPudukkottai", modify
    label def dist1 478 "TAMIL NADUSalem", modify
    label def dist1 483 "TAMIL NADUThiruvallur", modify
    label def dist1 484 "TAMIL NADUThiruvarur", modify
    label def dist1 485 "TAMIL NADUThoothukkudi", modify
    label def dist1 486 "TAMIL NADUTiruchirappalli", modify
    label def dist1 487 "TAMIL NADUTirunelveli", modify
    label def dist1 493 "TRIPURADhalai", modify
    label def dist1 498 "UTTAR PRADESHAligarh", modify
    label def dist1 499 "UTTAR PRADESHAllahabad", modify
    label def dist1 500 "UTTAR PRADESHAmbedkarNagar", modify
    label def dist1 503 "UTTAR PRADESHBaghpat", modify
    label def dist1 504 "UTTAR PRADESHBahraich", modify
    label def dist1 505 "UTTAR PRADESHBallia", modify
    label def dist1 506 "UTTAR PRADESHBalrampur", modify
    label def dist1 508 "UTTAR PRADESHBaraBanki", modify
    label def dist1 509 "UTTAR PRADESHBareilly", modify
    label def dist1 510 "UTTAR PRADESHBasti", modify
    label def dist1 511 "UTTAR PRADESHBijnor", modify
    label def dist1 512 "UTTAR PRADESHBudaun", modify
    label def dist1 514 "UTTAR PRADESHChandauli", modify
    label def dist1 517 "UTTAR PRADESHEtah", modify
    label def dist1 518 "UTTAR PRADESHEtawah", modify
    label def dist1 520 "UTTAR PRADESHFarrukhabad", modify
    label def dist1 521 "UTTAR PRADESHFatehpur", modify
    label def dist1 522 "UTTAR PRADESHFirozabad", modify
    label def dist1 523 "UTTAR PRADESHGautamBuddhaNagar", modify
    label def dist1 524 "UTTAR PRADESHGhaziabad", modify
    label def dist1 526 "UTTAR PRADESHGonda", modify
    label def dist1 528 "UTTAR PRADESHHamirpur", modify
    label def dist1 530 "UTTAR PRADESHJalaun", modify
    label def dist1 531 "UTTAR PRADESHJaunpur", modify
    label def dist1 532 "UTTAR PRADESHJhansi", modify
    label def dist1 533 "UTTAR PRADESHJyotibaPhuleNagar", modify
    label def dist1 536 "UTTAR PRADESHKanshiramNagar", modify
    label def dist1 540 "UTTAR PRADESHLalitpur", modify
    label def dist1 541 "UTTAR PRADESHLucknow", modify
    label def dist1 542 "UTTAR PRADESHMahamayaNagar", modify
    label def dist1 543 "UTTAR PRADESHMahoba", modify
    label def dist1 544 "UTTAR PRADESHMahrajganj", modify
    label def dist1 545 "UTTAR PRADESHMainpuri", modify
    label def dist1 546 "UTTAR PRADESHMathura", modify
    label def dist1 547 "UTTAR PRADESHMau", modify
    label def dist1 548 "UTTAR PRADESHMeerut", modify
    label def dist1 549 "UTTAR PRADESHMirzapur", modify
    label def dist1 550 "UTTAR PRADESHMoradabad", modify
    label def dist1 553 "UTTAR PRADESHPratapgarh", modify
    label def dist1 555 "UTTAR PRADESHRampur", modify
    label def dist1 556 "UTTAR PRADESHSaharanpur", modify
    label def dist1 557 "UTTAR PRADESHSantKabirNagar", modify
    label def dist1 559 "UTTAR PRADESHShahjahanpur", modify
    label def dist1 560 "UTTAR PRADESHShrawasti", modify
    label def dist1 561 "UTTAR PRADESHSiddharthnagar", modify
    label def dist1 563 "UTTAR PRADESHSonbhadra", modify
    label def dist1 564 "UTTAR PRADESHSultanpur", modify
    label def dist1 566 "UTTAR PRADESHVaranasi", modify
    label def dist1 569 "UTTARANCHALChamoli", modify
    label def dist1 570 "UTTARANCHALChampawat", modify
    label def dist1 571 "UTTARANCHALDehradun", modify
    label def dist1 572 "UTTARANCHALGarhwal", modify
    label def dist1 574 "UTTARANCHALNainital", modify
    label def dist1 575 "UTTARANCHALPithoragarh", modify
    label def dist1 576 "UTTARANCHALRudraprayag", modify
    label def dist1 578 "UTTARANCHALUdhamSinghNagar", modify
    label def dist1 579 "UTTARANCHALUttarkashi", modify
    label def dist1 580 "WEST BENGALBankura", modify
    label def dist1 582 "WEST BENGALBirbhum", modify
    label def dist1 583 "WEST BENGALDakshinDinajpur", modify
    label def dist1 584 "WEST BENGALHaora", modify
    label def dist1 585 "WEST BENGALHugli", modify
    label def dist1 587 "WEST BENGALKochBihar", modify
    label def dist1 588 "WEST BENGALMaldah", modify
    label def dist1 591 "WEST BENGALNorthTwentyFourParganas", modify
    label def dist1 593 "WEST BENGALPurbaMedinipur", modify
    label def dist1 594 "WEST BENGALPuruliya", modify
    label def dist1 595 "WEST BENGALSouthTwentyFourParganas", modify
    label def dist1 596 "WEST BENGALUttarDinajpur", modify


  • #2
    Parul:
    thanks for your data excerpt.
    this happens bacause each state includes 1 or more districts, whereas 1 or more districts refer to the same state (your specification #2).
    That said, I would go:
    Code:
    reg read_code c.child_age i.dist1, vce(cluster state1)
    Kind regards,
    Carlo
    (Stata 19.0)

    Comment


    • #3
      Thank you for the explanation.

      Could you please clarify:
      1. Why should it matter if I use -i.state1 i.dist1- instead of -i.dist1 i.state1-? Stata drops state coefficients in the latter case but not in former.
      2. Why should the clustering be at state level instead of district level?
      3. If I include village-level variables (e.g. whether village has a school, or village-level school quality), can I still include district or state level dummies? Villages are nested under districts (1 district will have several villages within it).

      Comment


      • #4
        1. Stata's algorithm needs to drop variables or levels of variables that are perfectly collinear with others. The algorithm somehow takes the order of variables into account, but this is without relevance. If you compare, the coefficient of interest, age, it is identical in both models.
        2. This is a good question. How was the sampling strategy? Were individuals sampled from the districts or the states? Usually, you want to take the level where the sampling was done. The number of clusters and the number of cases per cluster can also be relevant for this decision. For instance, the number of clusters should not be too low. If they are, there are analytical alternatives (e.g. boottest).
        3. You can include these variables as long as they are not unique to a specific village. For instance, if you include "number of inhabitants per village" in the model, this is fine as long as the distribution of this variable is not collinear with the district level (e.g. there are small and large villages in every district).
        Best wishes

        Stata 18.0 MP | ORCID | Google Scholar

        Comment


        • #5
          Parul:
          1) as Felis suggestedm it may be that Stata consider the different relationsgip between -state- and -district- (that is, one state included 1 or more districts, but districts belonging to the same jurisdiction refer to the same state).
          2) districts belonging to the same state are, other things being equal, more similar than districts belonging to the different states: that's why I would go -vce(cluster state)-. On the other hand it is true that with 27 states you're on the lower limit of an effective clustering (30 units are the rule of thumb).
          Conversely, clustering at district level does not seem to belpful in your case, if you have a single observation per district.
          3) if that were the case (and your analysis cannot benefit from -mixed- command), you should cluster at -district- level (Felix's recommendation obviously applies).
          Kind regards,
          Carlo
          (Stata 19.0)

          Comment

          Working...
          X