Gravity trade PPML

[Elin Andersson]

Hi all,

I have trouble to estimate/simulate the effects of a tariff on imports to Sweden. So, I'm only looking at Sweden's imports from other countries. I have to simulate the effect of this tariff, but I am stuck because when using the ppml command it throws out every variable. I have included exporter and importer fixed effects which it just disregards. The data is cross sectional for 59 countries (imports to Sweden from 59 countries). I have tried to attached the code below and a picture of the error I get. I also attached my dataset if it is useful (sorry if it's not).

Would be very grateful for some advice!

Kind regards,
Elin

Delete all
clear all

import excel "FULL DATASET.xlsx", firstrow

**Generate ln distance
gen ln_dist = ln(Distancedistw)

***STATA commands to create importer- and exporter fixed effects
tab (Partner), gen(ex_FE)
tab (Reportcountry), gen(im_FE)

***PPML
ppml ValueEUR RTA ln_dist ex_FE* im_FE*

Overview of the dataset (note same dataset as in the excel sheet)

   
Year
Report CODE
Report SHORT
Report country
Product
Partner CODE
Partner SHORT
Partner
Value USD
Value EUR
GDP in USD
GDP in EUR
Distance (distw)
RTA
MFN
Intensity of embedded CO2 emission in tonnes per million USD
Intensity of embedded CO2 emission in tonnes per million EUR
Intensity of embedded CO2 emission in tonnes per EUR
Price other EUA in TCO2 (non EU ETS)
Price EUA Average price 2023
Price EUA commission prognose 2030
CBAM Average EUA
CBAM commission prognose EUA

2017
752
SWE
Sweden
Iron and Steel
32
ARG
Argentina
660514,007
584686,999
6,4363E+11
5,6974E+11
12404,68
0
1
644,02
570,086504
570086504
0
49,6
60
48361,415
58501,7117

2017
752
SWE
Sweden
Iron and Steel
36
AUS
Australia
901702,407
798186,971
1,3269E+12
1,1746E+12
15385,4
0
1
1016,115
899,464998
899464998
0
49,6
60
55893,5006
67613,1055

2017
752
SWE
Sweden
Iron and Steel
40
AUT
Austria
267064236
236405262
4,1726E+11
3,6936E+11
1228,473
1
0
677,136
599,400787
599400787
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
56
BEL
Belgium
219816389
194581468
5,0276E+11
4,4505E+11
1151,5
1
0
583,353
516,384076
516384076
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
76
BRA
Brazil
49740595,6
44030375,2
2,0635E+12
1,8266E+12
10185,49
0
1
1466,937
1298,53263
1298532632
0
49,6
60
1462,79059
1769,50475

2017
752
SWE
Sweden
Iron and Steel
100
BGR
Bulgaria
2485248,41
2199941,89
5,931E+10
5,2501E+10
1912,318
1
0
697,45
617,38274
617382740
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
124
CAN
Canada
11573879
10245197,7
1,6493E+12
1,4599E+12
6347,801
1
0
652,048
577,19289
577192890
0
49,6
60
2794,35969
3380,27382

2017
752
SWE
Sweden
Iron and Steel
152
CHL
Chile
35393,05
31329,9279
2,7615E+11
2,4445E+11
12956,19
1
0
416,803
368,954016
368954016
0
49,6
60
584109,841
706584,485

2017
752
SWE
Sweden
Iron and Steel
156
CHN
China
339405990
300442182
1,231E+13
1,0897E+13
7276,972
0
1
1521,845
1347,13719
1347137194
0
49,6
60
222,39888
269,030903

2017
752
SWE
Sweden
Iron and Steel
170
COL
Colombia
40666,849
35998,2947
3,1187E+11
2,7606E+11
9491,131
1
0
562,896
498,275539
498275539
0
49,6
60
686545,486
830498,571

2017
752
SWE
Sweden
Iron and Steel
191
HRV
Croatia
2165773,39
1917142,61
5,6062E+10
4,9626E+10
1519,272
1
0
268,231
237,438081
237438081
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
196
CYP
Cyprus
5383259,48
4765261,29
2,2871E+10
2,0245E+10
2955,676
1
0
629
556,7908
556790800
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
203
CZE
Czechia
181997040
161103780
2,1863E+11
1,9353E+11
1009,355
1
0
716,718
634,438774
634438774
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
208
DNK
Denmark
446291477
395057216
3,3212E+11
2,9399E+11
450,0833
1
0
327,052
289,50643
289506430
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
233
EST
Estonia
37557534,3
33245929,4
2,6924E+10
2,3833E+10
595,361
1
0
695,551
615,701745
615701745
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
251
FRA
France
348624590
308602487
2,5952E+12
2,2972E+12
1616,322
1
0
686,378
607,581806
607581806
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
276
DEU
Germany
1738284416
1538729365
3,6908E+12
3,2671E+12
929,3204
1
0
782,549
692,712375
692712375
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
300
GRC
Greece
7502271,85
6641011,04
1,9984E+11
1,769E+11
2353,035
1
0
1110,28
982,819856
982819856
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
344
HKG
Hong Kong SAR
7146231,83
6325844,42
3,4127E+11
3,021E+11
8368,679
0
1
922,535
816,627982
816627982
0
49,6
60
6403,05787
7745,63452

2017
752
SWE
Sweden
Iron and Steel
348
HUN
Hungary
13574406,7
12016064,8
1,4311E+11
1,2668E+11
1315,378
1
0
626,364
554,457413
554457413
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
352
ISL
Iceland
555038,03
491319,664
2,4728E+10
2,1889E+10
2047,326
1
0
191,905
169,874306
169874306
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
699
IND
India
59515406
52683037,4
2,6515E+12
2,3471E+12
6308,107
0
1
2579,465
2283,34242
2283342418
0
49,6
60
2149,72009
2600,46785

2017
752
SWE
Sweden
Iron and Steel
360
IDN
Indonesia
5970409,08
5285006,12
1,0156E+12
8,9903E+11
10632,05
0
1
763,465
675,819218
675819218
0
49,6
60
6342,59118
7672,48934

2017
752
SWE
Sweden
Iron and Steel
372
IRL
Ireland
2625531,46
2324120,45
3,3724E+11
2,9853E+11
1549,426
1
0
260,699
230,770755
230770755
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
376
ISR
Israel
601447,46
532401,292
3,5825E+11
3,1712E+11
3315,602
1
0
287,03
254,078956
254078956
0
49,6
60
23670,7093
28633,9226

2017
752
SWE
Sweden
Iron and Steel
380
ITA
Italy
295898321
261929194
1,9618E+12
1,7366E+12
1833,431
1
0
541,897
479,687224
479687224
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
392
JPN
Japan
41947678,9
37132085,3
4,9308E+12
4,3648E+12
8226,76
0
1
959,6
849,43792
849437920
0
49,6
60
1134,65539
1372,56701

2017
752
SWE
Sweden
Iron and Steel
398
KAZ
Kazakhstan
2253084,06
1994430,01
1,6681E+11
1,4766E+11
3774,624
0
1
1986,055
1758,05589
1758055886
0
49,6
60
43721,5502
52888,972

2017
752
SWE
Sweden
Iron and Steel
428
LVA
Latvia
42814808,6
37899668,6
3,0484E+10
2,6984E+10
591,2189
1
0
486,72
430,844544
430844544
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
440
LTU
Lithuania
121407889
107470263
4,7759E+10
4,2276E+10
676,5552
1
0
325,181
287,850221
287850221
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
442
LUX
Luxembourg
202057048
178860899
6,5712E+10
5,8168E+10
1207,732
1
0
479,01
424,019652
424019652
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
458
MYS
Malaysia
26276995,8
23260396,6
3,1911E+11
2,8248E+11
9568,984
0
1
1133,718
1003,56717
1003567174
0
49,6
60
2139,98637
2588,69319

2017
752
SWE
Sweden
Iron and Steel
470
MLT
Malta
237555,34
210283,987
1,3485E+10
1,1937E+10
2558,882
1
0
512,357
453,538416
453538416
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
484
MEX
Mexico
1732970,3
1534025,31
1,1907E+12
1,054E+12
9357,389
1
0
763,524
675,871445
675871445
0
49,6
60
21853,1099
26435,2135

2017
752
SWE
Sweden
Iron and Steel
504
MAR
Morocco
63285,587
56020,4016
1,1854E+11
1,0493E+11
3274,223
1
0
651,278
576,511286
576511286
0
49,6
60
510438,321
617465,711

2017
752
SWE
Sweden
Iron and Steel
104
MMR
Myanmar
351,587
311,224812
6,6055E+10
5,8472E+10
7752,467
0
1
0
0
0
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
528
NLD
Netherlands
547373442
484534971
8,3387E+11
7,3814E+11
1009,396
1
0
729,565
645,810938
645810938
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
554
NZL
New Zealand
203334,244
179991,473
2,0656E+11
1,8284E+11
17389,62
0
1
499,123
441,82368
441823680
13,457211
49,6
60
88719,4254
114248,225

2017
752
SWE
Sweden
Iron and Steel
579
NOR
Norway
389009818
344351491
4,0175E+11
3,5562E+11
502,6935
1
0
531,742
470,698018
470698018
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
604
PER
Peru
21563,978
19088,4333
2,1101E+11
1,8678E+11
11219,56
1
0
266,157
235,602176
235602176
0
49,6
60
612196,284
740560,021

2017
752
SWE
Sweden
Iron and Steel
608
PHL
Philippines
279745,73
247630,92
3,2848E+11
2,9077E+11
9639,514
0
1
614,462
543,921762
543921762
0
49,6
60
108946,489
131790,108

2017
752
SWE
Sweden
Iron and Steel
616
POL
Poland
275472312
243848091
5,2464E+11
4,6441E+11
848,3859
1
0
767,366
679,272383
679272383
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
620
PRT
Portugal
7306555,32
6467762,77
2,2136E+11
1,9595E+11
2821,618
1
0
384,091
339,997353
339997353
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
642
ROU
Romania
25174654,6
22284604,3
2,1015E+11
1,8602E+11
1640,88
1
0
921,399
815,622395
815622395
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
643
RUS
Russian Federation
62819148
55607509,8
1,5742E+12
1,3935E+12
2081,843
0
1
3053,847
2703,26536
2703265364
0
49,6
60
2411,2204
2916,79887

2017
752
SWE
Sweden
Iron and Steel
682
SAU
Saudi Arabia
18985,676
16806,1204
7,1499E+11
6,3291E+11
4479,738
0
1
854,906
756,762791
756762791
0
49,6
60
2233438,39
2701739,99

2017
752
SWE
Sweden
Iron and Steel
702
SGP
Singapore
737394,275
652741,412
3,4327E+11
3,0387E+11
9782,643
0
1
642,658
568,880862
568880862
0
49,6
60
43227,6706
52291,537

2017
752
SWE
Sweden
Iron and Steel
703
SVK
Slovakia
44597469,8
39477680,3
9,565E+10
8,4669E+10
1176,298
1
0
1190,858
1054,1475
1054147502
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
705
SVN
Slovenia
7787291,38
6893310,33
4,8589E+10
4,3011E+10
1420,52
1
0
398,906
353,111591
353111591
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
710
ZAF
South Africa
54619328,3
48349029,4
3,8145E+11
3,3766E+11
9838,573
1
0
7739,19
6850,73099
6850730988
0
49,6
60
7027,98507
8501,59484

2017
752
SWE
Sweden
Iron and Steel
410
KOR
South Korea
104233236
92267260,2
1,6231E+12
1,4367E+12
7682,775
1
0
1405,425
1244,08221
1244082210
18,1388805
49,6
60
424,204848
564,432866

2017
752
SWE
Sweden
Iron and Steel
724
ESP
Spain
157301364
139243167
1,3132E+12
1,1625E+12
2486,548
1
0
543,175
480,81851
480818510
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
757
CHE
Switzerland
28533830,1
25258146,4
6,952E+11
6,1539E+11
1422,902
1
0
263,958
233,655622
233655622
0
49,6
60
458,83489
555,042206

2017
752
SWE
Sweden
Iron and Steel
764
THA
Thailand
6331957,29
5605048,59
4,5636E+11
4,0397E+11
8415,42
0
1
1032,04
913,561808
913561808
0
49,6
60
8084,2592
9779,34581

2017
752
SWE
Sweden
Iron and Steel
788
TUN
Tunisia
0
0
4,2164E+10
3,7323E+10
2582,251
1
0
0
0
0
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
792
TUR
Türkiye
65640396
58104878,5
8,5899E+11
7,6038E+11
2453,421
1
0
895,526
792,719615
792719615
0
49,6
60
676,688325
818,574586

2017
752
SWE
Sweden
Iron and Steel
826
GBR
United Kingdom
523648848
463533960
2,6801E+12
2,3725E+12
1292,802
1
0
588,791
521,197793
521197793
0
49,6
60
0
0

2017
752
SWE
Sweden
Iron and Steel
842
USA
USA
80454965,7
71218735,7
1,9477E+13
1,7241E+13
7440,511
0
1
563,233
498,573852
498573852
0
49,6
60
347,22974
420,035975

2017
752
SWE
Sweden
Iron and Steel
704
VNM
Viet Nam
13583196,3
12023845,4
2,8135E+11
2,4905E+11
8727,681
0
1
1313,777
1162,9554
1162955400
0
49,6
60
4797,34944
5803,24529

[Kevin Ahrlind]

Hi Elin!

I'm also been having the same issue bit unsure tho on how it can be solved, maybe its something specific with the dataset or the ppml command?

[Joao Santos Silva]

Dear Elin Andersson,

If I understand it correctly, you are including as many fixed effects as observations. No wonder the results are not good ;-)
Maybe Kevin Ahrlind is making the same thing?

Best wishes,

Joao

[Elin Andersson]

Dear Joao Santos Silva ,

Thank you for your reply. I don't think I completely understood, do you have any recommendations on how to handle the issue/create correct fixed effects?

Kind regards,
Elin

[Joao Santos Silva]

Dear Elin Andersson,

Essentially you need panel data and preferably also imports to other countries.

Best wishes,

Joao

[Elin Andersson]

Dear Joao Santos Silva ,

Thank you for your reply! I'm writing my master thesis and am trying to do the same method as another masters student, Teresa Alena Gros, simulating effects of Brexit (https://ulb-dok.uibk.ac.at/ulbtirolh...lFilename=true). What she did was using cross-sectional data for one year, but to my understanding she had data many importers but only included one for the analysis. The method used in that paper is following the same method as Anderson, Larch, Yotov (2017). Is it possible to use PPML with importer and exporter FE if the data is cross-sectional and other countries for imports as well?

I'm trying to figure out how to create a baseline scenario and compare it to a counterfactual scenario.

Kind regards,
Elin

[Joao Santos Silva]

Dear Elin Andersson,

Teresa used 1225 observations, 35 importers and 35 exporters in 2014. That is what you need, a larger dataset. Maybe you should speak to your adviser about this.

Best wishes,

Joao

[Elin Andersson]

Dear

Thank you so much! Hopefully I will figure it out now

Kind regards,
Elin