Decomposes gross exports (or imports) into value-added and Global Value Chain (GVC) components
following the Borin and Mancini (2019) framework, as implemented in the Stata icio
command (Belotti, Borin and Mancini 2021). It is the R counterpart of the decompose()
function in the Julia package GlobalValueChains.jl, and operates on an icio
object created by load_icio.
Arguments
- x
an object of class
icioobtained fromload_icio.- aggregation
character. The level of the decomposition:
"country"(one row per exporting/importing country),"sector"(one row per exporting country-industry), or"bilateral"(one row per exporting country-industry and importing country for exports, or per importing country and value-added origin for imports). Default"country".- perspective
character. The accounting perspective defining the perimeter for double counting:
"exporter"(exporting-country perimeter, additive across sectors and destinations),"world"(world perimeter, "corrected KWW", country level only),"self"(the export flow's own perimeter, giving the broader Johnson (2018) / Los et al. (2016) value added \(DVA^\star \supseteq DVA\); sector and bilateral levels only), or"importer"(forflow = "imports"). Default"exporter".- approach
character. How double-counted items are allocated across shipments:
"source"(value added recorded the first time it leaves the country of origin) or"sink"(the last time). The two coincide at the whole-country exporter perimeter (country level)."world"accepts both;"self"and imports ignore it. Default"source".- flow
character.
"exports"(default) decomposes gross exports;"imports"decomposes a country's gross imports from the importer perspective (Borin and Mancini 2019, eq. 51) into value added (VA) and double counting (DC).
Value
A data.table with one row per unit and one column per value-added term,
preceded by factor identifier columns: Exporting_Country (country exports);
Exporting_Country, Exporting_Industry (sector); Exporting_Country,
Exporting_Industry, Importing_Country (bilateral exports); Importing_Country (country
imports); or Importing_Country, Origin_Country (bilateral imports). The attribute
"decomposition" is set to "bm".
Details
The supported combinations mirror the Stata icio command and GlobalValueChains.jl:
| flow | aggregation | perspective | approach | terms |
| exports | country | exporter | source(=sink) | 13 |
| exports | country | world | source | 9 |
| exports | country | world | sink | 9 |
| exports | sector | exporter | source | 13 |
| exports | sector | exporter | sink | 9 |
| exports | sector | self | - | 9 |
| exports | bilateral | exporter | source | 13 |
| exports | bilateral | exporter | sink | 10 (adds VAXIM) |
| exports | bilateral | self | - | 9 |
| imports | country | importer | - | 3 (GIMP VA DC) |
| imports | bilateral | importer | - | 2 (VA DC, by origin) |
All terms are in the same units as the input-output table (e.g. millions of USD). The
following accounting identities hold for exports: GEXP = DC + FC, DC = DVA + DDC,
FC = FVA + FDC, DVA = VAX + REF, and (exporter/source only)
GVC = GVCB + GVCF = GEXP - DAVAX and GVCB = FC + DDC; for imports
GIMP = VA + DC.
GEXP | Gross exports. |
DC / FC | Domestic / foreign content. |
DVA / FVA | Domestic / foreign value added. |
DDC / FDC | Domestic / foreign double counting. |
VAX | Domestic value added absorbed abroad (Johnson and Noguera 2012). |
REF | Reflection: domestic value added returning home. |
DAVAX | Domestic value added directly absorbed by the importer (source approach). |
VAXIM | Domestic value added absorbed by the direct importer, incl. re-processing
(sink approach; DAVAX \(\le\) VAXIM \(\le\) VAX). |
GVC | GVC-related trade (value added crossing more than one border). |
GVCB / GVCF | Backward / forward GVC participation. |
GIMP | Gross imports (= VA + DC). |
VA / DC | Value added / double counting in imports (by origin at the bilateral level). |
The exporter / source decomposition is additive: the "sector" result is the sum of the
"bilateral" result over importers, and the "country" result is the sum of the
"sector" result over industries. The "sink" approach shares the domestic content
DC and foreign content FC with "source" at every cell; only the
value-added vs double-counted split differs. The "self" perimeter draws the boundary at
the export flow itself, so DVA (there \(DVA^\star\)) is weakly larger than under either
exporter approach.
References
Borin, A. and Mancini, M. (2019). Measuring What Matters in Global Value Chains and Value-Added Trade. World Bank Policy Research Working Paper 8804.
Belotti, F., Borin, A. and Mancini, M. (2021). icio: Economic analysis with intercountry input-output tables. The Stata Journal, 21(3), 708-755.
Examples
# Load example data and create an 'icio' object
data(leather)
dec <- load_icio(leather)
# Country-level decomposition (exporter perspective, source approach; 13 terms)
bm(dec)
#> Exporting_Country GEXP DC DVA VAX DAVAX REF
#> <fctr> <num> <num> <num> <num> <num> <num>
#> 1: Argentina 64.3 53.68996 52.81756 46.73209 34.79877 6.085473
#> 2: Turkey 113.6 92.46175 89.82482 77.34144 65.50360 12.483373
#> 3: Germany 147.6 111.29058 106.84240 96.71914 89.31689 10.123261
#> DDC FC FVA FDC GVC GVCB GVCF
#> <num> <num> <num> <num> <num> <num> <num>
#> 1: 0.8723949 10.61004 10.43484 0.1752063 29.50123 11.48244 18.01879
#> 2: 2.6369363 21.13825 20.55564 0.5826050 48.09640 23.77518 24.32122
#> 3: 4.4481800 36.30942 35.06489 1.2445289 58.28311 40.75760 17.52551
# Country-level "corrected KWW" (world perspective, sink approach; 9 terms)
bm(dec, perspective = "world", approach = "sink")
#> Exporting_Country GEXP DC DVA VAX REF DDC
#> <fctr> <num> <num> <num> <num> <num> <num>
#> 1: Argentina 64.3 53.68996 52.81756 46.73209 6.085473 0.8723949
#> 2: Turkey 113.6 92.46175 89.82482 77.34144 12.483373 2.6369363
#> 3: Germany 147.6 111.29058 106.84240 96.71914 10.123261 4.4481800
#> FC FVA FDC
#> <num> <num> <num>
#> 1: 10.61004 8.471827 2.138217
#> 2: 21.13825 18.265189 2.873058
#> 3: 36.30942 33.128506 3.180911
# Sector- and bilateral-sector-level decompositions
bm(dec, aggregation = "sector")
#> Exporting_Country Exporting_Industry GEXP DC DVA VAX
#> <fctr> <fctr> <num> <num> <num> <num>
#> 1: Argentina Agriculture 33.2 29.795288 29.493900 26.540382
#> 2: Argentina Textile_and_Leather 28.5 22.056767 21.569374 18.582499
#> 3: Argentina Transport_Equipment 2.6 1.837902 1.754288 1.609208
#> 4: Turkey Agriculture 45.9 38.432068 37.469257 32.468054
#> 5: Turkey Textile_and_Leather 59.2 48.074157 46.789941 39.702280
#> 6: Turkey Transport_Equipment 8.5 5.955528 5.565619 5.171110
#> 7: Germany Agriculture 38.7 33.067867 32.402844 29.139637
#> 8: Germany Textile_and_Leather 31.0 25.719889 25.082406 21.487520
#> 9: Germany Transport_Equipment 77.9 52.502827 49.357153 46.091985
#> DAVAX REF DDC FC FVA FDC GVC
#> <num> <num> <num> <num> <num> <num> <num>
#> 1: 20.385155 2.9535185 0.30138767 3.404712 3.3423229 0.06238937 12.814845
#> 2: 13.084653 2.9868748 0.48739312 6.443233 6.3486717 0.09456147 15.415347
#> 3: 1.328962 0.1450801 0.08361414 0.762098 0.7438425 0.01825550 1.271038
#> 4: 27.673077 5.0012037 0.96281049 7.467932 7.2556717 0.21226046 18.226923
#> 5: 33.025635 7.0876610 1.28421633 11.125843 10.8426216 0.28322154 26.174365
#> 6: 4.804889 0.3945085 0.38990949 2.544472 2.4573486 0.08712297 3.695111
#> 7: 26.657741 3.2632066 0.66502295 5.632133 5.4445468 0.18758643 12.042259
#> 8: 18.915931 3.5948858 0.63748284 5.280111 5.1021480 0.17796309 12.084069
#> 9: 43.743217 3.2651685 3.14567421 25.397173 24.5181932 0.87897942 34.156783
#> GVCB GVCF
#> <num> <num>
#> 1: 3.7060999 9.108745
#> 2: 6.9306263 8.484721
#> 3: 0.8457122 0.425326
#> 4: 8.4307426 9.796180
#> 5: 12.4100595 13.764306
#> 6: 2.9343811 0.760730
#> 7: 6.2971562 5.745103
#> 8: 5.9175939 6.166475
#> 9: 28.5428469 5.613936
bm(dec, aggregation = "bilateral", approach = "sink") # adds VAXIM
#> Exporting_Country Exporting_Industry Importing_Country GEXP DC
#> <fctr> <fctr> <fctr> <num> <num>
#> 1: Argentina Agriculture Turkey 14.0 12.5642780
#> 2: Argentina Textile_and_Leather Turkey 6.8 5.2626672
#> 3: Argentina Transport_Equipment Turkey 0.9 0.6361968
#> 4: Argentina Agriculture Germany 19.2 17.2310098
#> 5: Argentina Textile_and_Leather Germany 21.7 16.7940996
#> 6: Argentina Transport_Equipment Germany 1.7 1.2017051
#> 7: Turkey Agriculture Argentina 10.7 8.9591095
#> 8: Turkey Textile_and_Leather Argentina 12.1 9.8259679
#> 9: Turkey Transport_Equipment Argentina 1.6 1.1210406
#> 10: Turkey Agriculture Germany 35.2 29.4729584
#> 11: Turkey Textile_and_Leather Germany 47.1 38.2481890
#> 12: Turkey Transport_Equipment Germany 6.9 4.8344878
#> 13: Germany Agriculture Argentina 14.9 12.7315559
#> 14: Germany Textile_and_Leather Argentina 10.3 8.5456405
#> 15: Germany Transport_Equipment Argentina 31.6 21.2976809
#> 16: Germany Agriculture Turkey 23.8 20.3363108
#> 17: Germany Textile_and_Leather Turkey 20.7 17.1742484
#> 18: Germany Transport_Equipment Turkey 46.3 31.2051464
#> DVA VAX VAXIM REF DDC FC
#> <num> <num> <num> <num> <num> <num>
#> 1: 12.357451 11.1495220 8.6467883 1.20792920 0.206826787 1.4357220
#> 2: 5.172419 4.5941134 3.3363970 0.57830552 0.090248234 1.5373328
#> 3: 0.631643 0.5994267 0.5204712 0.03221630 0.004553866 0.2638032
#> 4: 16.976780 15.2571096 12.8017283 1.71967093 0.254229282 1.9689902
#> 5: 16.492276 14.0624444 10.6916234 2.42983148 0.301823747 4.9059004
#> 6: 1.186992 1.0694721 0.9062318 0.11752004 0.014713011 0.4982949
#> 7: 8.736465 8.2433496 7.5330947 0.49311499 0.222644951 1.7408905
#> 8: 9.616970 9.1484943 8.4243413 0.46847613 0.208997408 2.2740321
#> 9: 1.110273 1.0804233 1.0374013 0.02984949 0.010767873 0.4789594
#> 10: 28.549111 24.0661500 21.1873007 4.48296078 0.923847609 5.7270416
#> 11: 37.042781 30.4161318 25.8904388 6.62664940 1.205407773 8.8518110
#> 12: 4.769217 4.3868947 4.1249837 0.38232239 0.065270704 2.0655122
#> 13: 11.915655 10.4287782 9.9293481 1.48687667 0.815901115 2.1684441
#> 14: 8.240814 7.6235647 7.3729745 0.61724929 0.304826489 1.7543595
#> 15: 20.852668 19.8817549 19.4540442 0.97091322 0.445012839 10.3023191
#> 16: 19.622631 17.9073356 17.3509403 1.71529555 0.713679736 3.4636892
#> 17: 15.942630 12.9978655 12.0796413 2.94476411 1.231618843 3.5257516
#> 18: 30.268005 27.8798434 27.1400321 2.38816205 0.937140969 15.0948536
#> FVA FDC
#> <num> <num>
#> 1: 1.4120879 0.023634130
#> 2: 1.5109695 0.026363357
#> 3: 0.2619149 0.001888290
#> 4: 1.9399394 0.029050821
#> 5: 4.8177315 0.088168896
#> 6: 0.4921940 0.006100846
#> 7: 1.6976272 0.043263282
#> 8: 2.2256637 0.048368449
#> 9: 0.4743588 0.004600523
#> 10: 5.5475241 0.179517565
#> 11: 8.5728425 0.278968549
#> 12: 2.0376256 0.027886602
#> 13: 2.0294794 0.138964627
#> 14: 1.6917808 0.062578720
#> 15: 10.0870532 0.215265891
#> 16: 3.3421349 0.121554238
#> 17: 3.2729090 0.252842628
#> 18: 14.6415307 0.453322843
# Self (own-flow) perimeter, and the importer-perspective import decomposition
bm(dec, aggregation = "bilateral", perspective = "self")
#> Exporting_Country Exporting_Industry Importing_Country GEXP DC
#> <fctr> <fctr> <fctr> <num> <num>
#> 1: Argentina Agriculture Turkey 14.0 12.5642780
#> 2: Argentina Textile_and_Leather Turkey 6.8 5.2626672
#> 3: Argentina Transport_Equipment Turkey 0.9 0.6361968
#> 4: Argentina Agriculture Germany 19.2 17.2310098
#> 5: Argentina Textile_and_Leather Germany 21.7 16.7940996
#> 6: Argentina Transport_Equipment Germany 1.7 1.2017051
#> 7: Turkey Agriculture Argentina 10.7 8.9591095
#> 8: Turkey Textile_and_Leather Argentina 12.1 9.8259679
#> 9: Turkey Transport_Equipment Argentina 1.6 1.1210406
#> 10: Turkey Agriculture Germany 35.2 29.4729584
#> 11: Turkey Textile_and_Leather Germany 47.1 38.2481890
#> 12: Turkey Transport_Equipment Germany 6.9 4.8344878
#> 13: Germany Agriculture Argentina 14.9 12.7315559
#> 14: Germany Textile_and_Leather Argentina 10.3 8.5456405
#> 15: Germany Transport_Equipment Argentina 31.6 21.2976809
#> 16: Germany Agriculture Turkey 23.8 20.3363108
#> 17: Germany Textile_and_Leather Turkey 20.7 17.1742484
#> 18: Germany Transport_Equipment Turkey 46.3 31.2051464
#> DVA VAX REF DDC FC FVA
#> <num> <num> <num> <num> <num> <num>
#> 1: 12.5408413 11.3093443 1.23149696 0.0234366879 1.4357220 1.4330439
#> 2: 5.2474241 4.6594894 0.58793467 0.0152430467 1.5373328 1.5328800
#> 3: 0.6359948 0.6032297 0.03276518 0.0002019919 0.2638032 0.2637194
#> 4: 17.1754381 15.4311807 1.74425742 0.0555716402 1.9689902 1.9626401
#> 5: 16.6868841 14.2378939 2.44899022 0.1072155581 4.9059004 4.8745805
#> 6: 1.2005992 1.0814895 0.11910974 0.0011059286 0.4982949 0.4978363
#> 7: 8.9460790 8.4231507 0.52292827 0.0130305178 1.7408905 1.7383585
#> 8: 9.7972118 9.3017324 0.49547939 0.0287561155 2.2740321 2.2673771
#> 9: 1.1206087 1.0893588 0.03124996 0.0004319315 0.4789594 0.4787748
#> 10: 29.1787145 24.6186741 4.56004040 0.2942438143 5.7270416 5.6698656
#> 11: 37.8044783 31.0979346 6.70654362 0.4437107309 8.8518110 8.7491227
#> 12: 4.8256250 4.4354571 0.39016788 0.0088628304 2.0655122 2.0617256
#> 13: 12.6972319 11.1461149 1.55111705 0.0343240023 2.1684441 2.1625980
#> 14: 8.5262197 7.8844796 0.64174009 0.0194208287 1.7543595 1.7503725
#> 15: 21.1724475 20.1691229 1.00332460 0.1252334637 10.3023191 10.2417399
#> 16: 20.2439513 18.4771429 1.76680841 0.0923595022 3.4636892 3.4479584
#> 17: 17.0792118 14.0530011 3.02621073 0.0950365762 3.5257516 3.5062413
#> 18: 30.7980923 28.3662260 2.43186631 0.4070541417 15.0948536 14.8979494
#> FDC
#> <num>
#> 1: 2.678114e-03
#> 2: 4.452806e-03
#> 3: 8.375726e-05
#> 4: 6.350180e-03
#> 5: 3.131986e-02
#> 6: 4.585805e-04
#> 7: 2.532027e-03
#> 8: 6.655052e-03
#> 9: 1.845407e-04
#> 10: 5.717602e-02
#> 11: 1.026884e-01
#> 12: 3.786603e-03
#> 13: 5.846079e-03
#> 14: 3.986959e-03
#> 15: 6.057914e-02
#> 16: 1.573071e-02
#> 17: 1.951034e-02
#> 18: 1.969041e-01
bm(dec, flow = "imports")
#> Importing_Country GIMP VA DC
#> <fctr> <num> <num> <num>
#> 1: Argentina 81.2 79.63233 1.567672
#> 2: Turkey 112.5 108.71967 3.780326
#> 3: Germany 131.8 127.14834 4.651660