China’s Trade Dominance and the Role of Industrial Policies, Accessible Data

Figure 1: Change in Share of World Exports

1.A. Change in China’s Sectoral Share of World Exports, 2017—2024 (ppt)

Sector Change (percentage point)
Apparel and textiles 4.3%
Total 3.6%
Chemicals 2.0%
Furniture 5.0%
High-tech goods 1.3%
Metals and its products 6.1%
Other manufactured goods 4.6%
Other machinery 5.3%
Transport equipment 7.5%

1.B. Change in Countries’ Share of World Exports, 2017—2024 (ppt)

Country Change (percentage point)
Canada -0.07%
China 3.65%
United Kingdom -0.19%
Japan -0.84%
South Korea -0.23%
United States -0.11%
Euro area -0.70%

Note: Ppt. denotes percentage points. Sector definitions use SITC codes: Chemicals (5); Furniture (82); High-tech goods (75-77); Apparel and textiles (61, 65, 83-85); Metals and its products (67-69); Other manufactured goods (62-64, 66, 81, 86-89); Transport equipment (78-79); Other machinery (71-74). Trade excludes commodities. Source: UN Comtrade ; Authors’ Calculations.

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Figure 2: China import growth has not kept apace

2.A. Chinese Average Annual Growth in Trade, 2010-2024

Trade Annual Growth (percent)
Imports 4.5%
Exports 6.0%

2.B. Commodity Share of Chinese Imports

Date Percent of Total Import
2010 34.4%
2024 43.9%

2.C. Exports to China as Share of GDP

Date Selected commodity exporters G7 + Korea
2010 1.99% 1.39%
2011 2.37% 1.51%
2012 2.33% 1.47%
2013 2.63% 1.51%
2014 2.39% 1.51%
2015 2.21% 1.42%
2016 2.29% 1.34%
2017 2.63% 1.49%
2018 3.20% 1.53%
2019 3.50% 1.37%
2020 4.08% 1.44%
2021 4.57% 1.55%
2022 4.00% 1.44%
2023 3.95% 1.23%
2024 3.59% 1.15%

Left Figure 2a.

Source: UN Comtrade; Authors' Calculations.

Middle Figure 2b.

Note: Commodities include SITC sections 0, 2, 3, 4, and 68.

Source: UN Comtrade; Authors' Calculations.

Right Figure 2c.

Note: Commodity exporters include Argentina, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Ecuador, Guatemala, Guyana, Honduras, Mexico, Nicaragua, Panama, Peru, Puerto Rico, Paraguay, El Salvador, Uruguay, Venezuela, Guinea, and Australia.

Source: UN Comtrade; Authors' Calculations.

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Figure 3. Chinese Export Growth and Industrial Policy Intensity (%, 2017-2024)

This is a scatter plot showing the relationship between Industrial Policy Intensity (x-axis, ranging from 0 to approximately 1050) and Export Growth in percent (y-axis, ranging from -100% to 500%) for the period 2017-2024. The plot features numerous gray circles of varying sizes representing different product categories, with the circle size corresponding to each category's weight in trade. A blue trend line runs from bottom left to top right, indicating a positive correlation between industrial policy intensity and export growth.

The scatter plot shows data points distributed across the entire range of industrial policy intensity, with most points clustered between 0% and 200% export growth. Several labeled product categories are highlighted: "Batteries (incl. EV)" shows high export growth (approximately 400%) at medium-high policy intensity. "Cars" displays strong export growth (about 300%) at high policy intensity (around 950). "Computing machinery" and "Electronic components" both show moderate export growth (around 100%) at high policy intensity levels. "Chemical products" and "Iron/steel products" exhibit modest export growth at high and medium-high policy intensity respectively. "House appliances" shows moderate export growth (about 100%) at lower policy intensity (around 350). "Clothes" shows neutral growth at medium policy intensity, while "TVs, phones, cameras" displays negative export growth (approximately -75%) at moderate policy intensity levels (around 300).

CPC Code Industrial Policy Intensity Export Growth (2017-2024), percent Weight
22 11 27% 0.000%
24 12 50% 0.000%
21 19 -13% 0.025%
31 22 -84% 0.001%
23 24   0.005%
41 29 33% 0.010%
49 30 100% 0.006%
45 32 -23% 0.001%
43 32 -1% 0.001%
42 32 65% 0.015%
18 32 105% 0.002%
17 35 -46% 0.027%
15 36 -8% 0.021%
44 38 0% 0.014%
11 38 39% 0.006%
29 42 -19% 0.019%
12 42 61% 0.225%
16 48 34% 0.074%
173 50 8% 0.004%
174 50 8% 0.004%
180 50 8% 0.004%
32 51 64% 0.010%
14 55 39% 0.038%
13 57 14% 0.160%
19 57 23% 0.060%
152 63 -38% 0.001%
162 69 42% 0.004%
151 70 -25% 0.003%
172 70    
154 91 17% 0.017%
161 95 95% 0.021%
141 96 596% 0.019%
153 97 -8% 0.013%
163 101 41% 0.057%
223 109    
120 133 27% 0.128%
250 136 -36% 0.058%
142 136 588% 0.005%
218 140 -90% 0.000%
296 141 64% 0.111%
294 142 16% 0.078%
324 144 -4% 0.001%
295 144 23% 0.052%
234 144 140% 0.009%
217 144 147% 0.001%
328 145 48% 0.004%
273 146 60% 0.068%
236 146 75% 0.067%
337 146 343% 0.003%
386 146   0.003%
291 147 82% 0.026%
311 148 -48% 0.009%
110 148 17% 0.048%
292 148 31% 1.236%
332 149 -90% 0.000%
323 149 -82% 0.000%
235 149 11% 0.004%
264 149 24% 0.141%
237 149 55% 0.038%
261 150 -12% 0.047%
331 150 -11% 0.095%
315 150 49% 0.017%
219 150 1667% 0.023%
313 151 -26% 0.000%
272 151 10% 0.120%
376 152 -21% 0.226%
263 152 -21% 0.129%
293 152 1% 1.893%
243 153 114% 0.017%
384 154 73% 0.490%
385 155 42% 1.681%
215 155 243% 0.008%
312 156 -62% 0.019%
325 156 -15% 0.041%
233 156 66% 0.082%
383 157 710% 0.069%
387 158 93% 0.067%
216 160 127% 0.014%
213 161 -13% 0.402%
391 161 -3% 0.083%
314 161 -2% 0.281%
344 161 1425% 0.018%
336 162 175% 0.008%
231 163 18% 0.042%
265 163 29% 0.079%
281 164 44% 0.731%
478 164 49% 0.008%
262 164 54% 0.001%
283 165 -80% 0.162%
335 165 46% 0.057%
211 167 8% 0.154%
327 167 54% 0.072%
322 168 15% 0.072%
375 169 51% 0.152%
212 172 -6% 0.863%
319 172 10% 0.284%
242 173 -85% 0.021%
266 173 -29% 0.595%
494 173 267% 0.014%
221 175 26% 0.001%
374 176 -37% 0.028%
373 177 0% 0.322%
244 177 56% 0.026%
399 179 -30% 0.001%
423 179 -8% 0.071%
381 179 46% 2.301%
334 183 19% 0.032%
214 183 34% 0.247%
372 184 24% 0.576%
484 185 4% 0.201%
267 185 46% 0.888%
171 186 19% 0.062%
447 187 70% 0.006%
422 187 171% 0.040%
279 189 38% 0.641%
268 190 -8% 0.061%
479 190 43% 0.058%
241 192 119% 0.027%
333 201 65% 1.129%
239 204 73% 0.276%
364 205 82% 0.370%
348 211 270% 0.027%
355 212 120% 0.299%
321 213 89% 0.803%
326 214 47% 0.047%
393 215 -23% 0.019%
413 215 712% 0.090%
389 216 72% 1.425%
443 224 317% 0.059%
435 225 114% 0.631%
363 227 99% 0.485%
345 230 330% 0.034%
379 235 79% 0.137%
493 238 119% 1.001%
433 240 44% 0.557%
483 241 -51% 1.827%
343 242 41% 0.230%
434 248 52% 0.069%
446 263 84% 0.279%
495 263 204% 0.113%
351 273 69% 0.082%
431 277 41% 0.630%
463 289 42% 0.980%
416 290 48% 0.142%
473 292 7% 2.452%
441 292 77% 0.209%
414 293 165% 0.154%
499 302 79% 0.759%
448 304 77% 2.129%
445 304 108% 0.072%
496 309 -22% 0.162%
346 310 91% 0.488%
475 313 -7% 0.105%
411 314 325% 0.056%
472 320 -49% 7.801%
444 321 167% 0.607%
476 324 49% 0.016%
465 338 -75% 1.520%
347 348 122% 0.658%
415 392 89% 0.708%
341 427 64% 1.574%
451 435 36% 0.148%
232 551 87% 0.051%
317 552 33% 0.003%
316 562 -60% 0.052%
382 578 1% 0.617%
222 585 107% 0.003%
271 590 21% 1.442%
361 591 56% 0.654%
392 601 51% 0.026%
421 609 97% 0.621%
282 612 -1% 6.744%
362 630 75% 0.238%
371 688 57% 0.695%
369 697 94% 1.550%
481 699 95% 0.558%
474 708 -71% 2.964%
429 716 74% 2.957%
432 726 81% 1.410%
464 729 406% 0.607%
353 737 54% 0.297%
492 751 105% 0.687%
442 765 68% 0.786%
439 783 98% 1.660%
482 789 55% 0.900%
461 809 76% 1.933%
342 819 71% 0.618%
412 824 53% 2.414%
462 855 61% 1.197%
469 908 23% 1.422%
471 914 150% 5.016%
449 934 77% 1.206%
354 950 53% 0.637%
491 950 304% 1.802%
352 959 54% 0.974%
452 1038 83% 8.214%

Source: New Industrial Policy Observatory by Global Trade Alert; UN Comtrade; Authors' Calculations. Regression details: y=6.88+0.09x; R²=0.10; t−statistic=4.50 (***).

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Figure 4. Chinese Trade Balance Change and Industrial Policy Intensity ($bn, 2017-2024)

This is a scatter plot showing the relationship between Industrial Policy Intensity (x-axis, ranging from 0 to approximately 1100) and Change in Trade Balance in billions of dollars (y-axis, ranging from -100 to 200 billion). The plot features numerous gray circles of varying sizes representing different product categories, with a blue trend line moving from bottom left to top right, indicating a positive correlation between industrial policy intensity and trade balance change.

The scatter plot shows most data points clustered at lower industrial policy intensity levels (below 400), with both positive and negative trade balance changes. Several labeled product categories are highlighted: "Cars," "Electronic components," and "Computing machinery" appear in the upper right quadrant with high industrial policy intensity and positive trade balance changes (around +100 billion). "Batteries (incl. EV)" and "Iron/steel products" show moderate positive trade balances with medium-high policy intensity. "Chemical products" shows a slightly positive trade balance at high policy intensity. "House appliances" has a slightly positive trade balance at lower policy intensity. "Clothes" shows a neutral to slightly negative trade balance at medium policy intensity, while "TVs, phones, cameras" shows a significant negative trade balance (approximately -100 billion) at moderate policy intensity levels.

Billions of dollars

CPC Code Industrial Policy Intensity Change in Trade Balance ($bn) Weight
22 11 -0.04 0.000%
24 12 -0.03 0.000%
21 19 -0.01 0.025%
31 22 3.69 0.001%
23 24   0.005%
41 29 -0.06 0.010%
49 30 0.09 0.006%
18 32 -0.11 0.002%
42 32 -0.67 0.015%
43 32 -0.35 0.001%
45 32 -0.01 0.001%
17 35 -1.05 0.027%
15 36 0.79 0.021%
11 38 -9.24 0.006%
44 38 -0.14 0.014%
12 42 3 0.225%
29 42 2.18 0.019%
16 48 -1.06 0.074%
173 50 0.01 0.004%
174 50 0.01 0.004%
180 50 0.01 0.004%
32 51 0.13 0.010%
14 55 -15.86 0.038%
13 57 -10.84 0.160%
19 57 -2.11 0.060%
152 63 -0.03 0.001%
162 69 -0.25 0.004%
151 70 0.51 0.003%
172 70    
154 91 0.03 0.017%
161 95 -4.62 0.021%
141 96 -53.42 0.019%
153 97 -0.29 0.013%
163 101 -0.06 0.057%
223 109    
120 133 -202.52 0.128%
142 136 -67.91 0.005%
250 136 -1.07 0.058%
218 140 0.02 0.000%
296 141 1.78 0.111%
294 142 0.09 0.078%
217 144 -0.89 0.001%
234 144 0.19 0.009%
295 144 0.27 0.052%
324 144 0.15 0.001%
328 145 0.04 0.004%
236 146 0.1 0.067%
273 146 0.92 0.068%
337 146 0.1 0.003%
386 146   0.003%
291 147 2.24 0.026%
110 148 -29.33 0.048%
292 148 5.32 1.236%
311 148 3.36 0.009%
235 149 -1.3 0.004%
237 149 0.26 0.038%
264 149 1.06 0.141%
323 149 0.01 0.000%
332 149 -0.13 0.000%
219 150 6.96 0.023%
261 150 -0.86 0.047%
315 150 -0.1 0.017%
331 150 -0.26 0.095%
272 151 0.32 0.120%
313 151 0.03 0.000%
263 152 1.36 0.129%
293 152 -1.91 1.893%
376 152 -1.09 0.226%
243 153 0.64 0.017%
384 154 8.01 0.490%
215 155 0 0.008%
385 155 15.36 1.681%
233 156 0.71 0.082%
312 156 -1.67 0.019%
325 156 -0.28 0.041%
383 157 8.94 0.069%
387 158 1.42 0.067%
216 160 -2.06 0.014%
213 161 -1.31 0.402%
314 161 -0.52 0.281%
344 161 -1.3 0.018%
391 161 -0.98 0.083%
336 162 -1.22 0.008%
231 163 0.95 0.042%
265 163 0.62 0.079%
262 164 0.02 0.001%
281 164 8.31 0.731%
478 164 0.06 0.008%
283 165 -3.16 0.162%
335 165 -0.43 0.057%
211 167 -13.56 0.154%
327 167 0.88 0.072%
322 168 0.32 0.072%
375 169 0.64 0.152%
212 172 -10.54 0.863%
319 172 0.89 0.284%
242 173 0.75 0.021%
266 173 -3.39 0.595%
494 173 0.87 0.014%
221 175 -0.7 0.001%
374 176 -0.21 0.028%
244 177 -0.29 0.026%
373 177 0.04 0.322%
381 179 25.08 2.301%
399 179 -0.01 0.001%
423 179 -0.34 0.071%
214 183 -1.65 0.247%
334 183 -12.98 0.032%
372 184 2.81 0.576%
267 185 10.06 0.888%
484 185 -0.07 0.201%
171 186 0.48 0.062%
422 187 1.61 0.040%
447 187 0.09 0.006%
279 189 6.34 0.641%
268 190 0.18 0.061%
479 190 0.67 0.058%
241 192 -0.25 0.027%
333 201 1.68 1.129%
239 204 -0.39 0.276%
364 205 6.94 0.370%
348 211 1.18 0.027%
355 212 7.37 0.299%
321 213 8.61 0.803%
326 214 0.06 0.047%
393 215 -8.21 0.019%
413 215 -40.11 0.090%
389 216 22.21 1.425%
443 224 3.78 0.059%
435 225 17.77 0.631%
363 227 10.94 0.485%
345 230 11.01 0.034%
379 235 1.42 0.137%
493 238 27.7 1.001%
433 240 5.84 0.557%
483 241 13.38 1.827%
343 242 2.51 0.230%
434 248 1.62 0.069%
446 263 6.06 0.279%
495 263 2.22 0.113%
351 273 0.46 0.082%
431 277 1.24 0.630%
463 289 9.5 0.980%
416 290 0.05 0.142%
441 292 3.69 0.209%
473 292 2.66 2.452%
414 293 -29.98 0.154%
499 302 12.54 0.759%
445 304 1.6 0.072%
448 304 37.5 2.129%
496 309 15.26 0.162%
346 310 7.39 0.488%
475 313 -0.07 0.105%
411 314 -11.06 0.056%
472 320 -96.7 7.801%
444 321 24.24 0.607%
476 324 0.13 0.016%
465 338 -25.15 1.520%
347 348 23.84 0.658%
415 392 14.65 0.708%
341 427 29.98 1.574%
451 435 1.37 0.148%
232 551 -1.66 0.051%
317 552 -0.02 0.003%
316 562 -0.65 0.052%
382 578 1.22 0.617%
222 585 -1 0.003%
271 590 7.04 1.442%
361 591 8.34 0.654%
392 601 9.48 0.026%
421 609 13.52 0.621%
282 612 -2.9 6.744%
362 630 4.7 0.238%
371 688 9.82 0.695%
369 697 32.81 1.550%
481 699 6.83 0.558%
474 708 -11.46 2.964%
429 716 51.37 2.957%
432 726 23.52 1.410%
464 729 56.75 0.607%
353 737 -5.15 0.297%
492 751 16.65 0.687%
442 765 17.76 0.786%
439 783 35.42 1.660%
482 789 4.77 0.900%
461 809 33.66 1.933%
342 819 2.57 0.618%
412 824 32.79 2.414%
462 855 20.51 1.197%
469 908 10.21 1.422%
471 914 19.61 5.016%
449 934 -0.62 1.206%
354 950 6.07 0.637%
491 950 141.44 1.802%
352 959 -6.79 0.974%
452 1038 102.37 8.214%

Source: New Industrial Policy Observatory by Global Trade Alert; UN Comtrade; Authors' Calculations. Regression details: y=-30.22+0.08x; R2=0.28; t−statistic=8.70 (***).

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Last Update: March 23, 2026