Mongolia
How does Mongolia’s trade profile look? Level of exports and imports over thirty years, structural composition, partner concentration, and the position on the economic-complexity frontier.
where Mongolia is exposed
- Iron or steel: grinding balls and similar articles for mills, forged or stamped, but not further worked (732611): imports 100% from China.
Ranked by import dependency (GeoDep 2022). Single-supplier concentration is the exposure.
Model a supply shock → - Portable computers, up to 10 kg (847130): imports 73% from China.
Ranked by import dependency (GeoDep 2022). Single-supplier concentration is the exposure.
Model a supply shock → - Granite: articles thereof, simply cut or sawn, with a flat or even surface (680223): imports 99% from China.
Ranked by import dependency (GeoDep 2022). Single-supplier concentration is the exposure.
Model a supply shock → - Freight transport containers (860900): imports 93% from China.
Ranked by import dependency (GeoDep 2022). Single-supplier concentration is the exposure.
Model a supply shock → - Non-crude palm oil and fractions (151190): imports 77% from Malaysia.
Ranked by import dependency (GeoDep 2022). Single-supplier concentration is the exposure.
Model a supply shock →
where Mongolia could grow
- Alcohols: cyclanic, cyclenic or cycloterpenic and derivatives, cyclohexanol, methylcyclohexanols and dimethylcyclohexanols (290612): proximity 0.01 to current capabilities, complexity PCI +1.50, world market $126.6m.
Ranked by density × complexity (product space 2024).
See product → - Plastics: plates, sheets, film, foil and strip, of cellulose acetate, non-cellular and not reinforced, laminated, supported or similarly combined with other materials (392073): proximity 0.01 to current capabilities, complexity PCI +2.30, world market $1.3bn.
Ranked by density × complexity (product space 2024).
See product → - Mowers: n.e.s. in item no. 8433.1 (including cutter bars for tractor mounting) (843320): proximity 0.01 to current capabilities, complexity PCI +0.93, world market $1.4bn.
Ranked by density × complexity (product space 2024).
See product → - Machinery: for finishing paper or paperboard (843930): proximity 0.01 to current capabilities, complexity PCI +1.30, world market $684.8m.
Ranked by density × complexity (product space 2024).
See product → - Navigational instruments and appliances: for navigation other than aeronautical or space navigation (excluding direction finding compasses) (901480): proximity 0.01 to current capabilities, complexity PCI +0.91, world market $2.5bn.
Ranked by density × complexity (product space 2024).
See product →
Mongolia trade-riskStored risk rank #81 of 185 (board)
NORMAL-2.5% vs weekday baselineas of 2026-05-24
Dependency diagnosis
- Iron or steel: grinding balls and similar articles for mills, forged or stamped, but not further worked (732611): you import 99.7% from China. STRUCTURAL
Structural scarcity, world export HHI 0.46. Switching suppliers will not fix this; the world itself is concentrated (top alternatives: USA 5.6%, CHL 5.4%, ESP 2.9%, RUS 2.7%). Policy: stockpile, substitute the input, or invest in allied/domestic production. - Portable computers, up to 10 kg (847130): you import 73.3% from China. STRUCTURAL
Structural scarcity, world export HHI 0.51. Switching suppliers will not fix this; the world itself is concentrated (top alternatives: VNM 12.8%, NLD 3.1%, DEU 1.9%, S19 1.8%). Policy: stockpile, substitute the input, or invest in allied/domestic production. - Granite: articles thereof, simply cut or sawn, with a flat or even surface (680223): you import 99.3% from China. STRUCTURAL
Structural scarcity, world export HHI 0.34. Switching suppliers will not fix this; the world itself is concentrated (top alternatives: IND 55.5%, EGY 6.7%, ITA 4.2%, PRT 4.1%). Policy: stockpile, substitute the input, or invest in allied/domestic production. - Freight transport containers (860900): you import 92.9% from China. STRUCTURAL
Structural scarcity, world export HHI 0.28. Switching suppliers will not fix this; the world itself is concentrated (top alternatives: USA 6.7%, DEU 4.2%, POL 3.8%, NLD 3.1%). Policy: stockpile, substitute the input, or invest in allied/domestic production. - Non-crude palm oil and fractions (151190): you import 77.0% from Malaysia. STRUCTURAL
Structural scarcity, world export HHI 0.41. Switching suppliers will not fix this; the world itself is concentrated (top alternatives: IDN 55.2%, NLD 2.5%, ITA 0.9%, EST 0.9%). Policy: stockpile, substitute the input, or invest in allied/domestic production. - Vodka (220860): you import 67.8% from European Union (EU27). DIVERSIFIABLE
Diversifiable, you are single-sourced but world supply is broad (HHI 0.10). Realistic alternatives: SWE 18.7%, FRA 17.2%, USA 11.1%, POL 9.1%. Policy: spread procurement across these suppliers. - Tricycles, scooters, pedal cars and similar wheeled toys: dolls' carriages: dolls: other toys: reduced-size (scale) models and similar recreational models, working or not: puzzles of all kinds (950300): you import 75.6% from China. UNKNOWN
World concentration unavailable for this product code. - Freezers: of the chest type, not exceeding 800l capacity (841830): you import 97.0% from China. STRUCTURAL
Structural scarcity, world export HHI 0.60. Switching suppliers will not fix this; the world itself is concentrated (top alternatives: TUR 4.6%, ITA 2.8%, DNK 1.7%, ZAF 1.5%). Policy: stockpile, substitute the input, or invest in allied/domestic production.
Compound exposures
These flows carry multiple simultaneous stressors on the same product; the averaged risk score understates them.
- Non-crude palm oil and fractions from Malaysia: single-source (77.0%) + price +15% over 12m.
- Automatic watches, precious-metal or precious-metal-clad cases from Switzerland: single-source (98.3%) + transits Strait of Malacca.
- Automatic-winding wristwatches from Switzerland: single-source (92.6%) + transits Strait of Malacca.
- Carpets and other textile floor coverings: woven, (not tufted or flocked), of man-made textile materials, of pile construction, made up, n.e.s. in item no. 5702.10 or 5702.20 from Turkey: single-source (53.6%) + transits Strait of Malacca.
GeoDep 2022, world shares latest BACI year, Pink Sheet 2026M04. Price coverage requires quotes in that month and the same month a year earlier; discontinued and lagging series are excluded. No real-time signal is implied.
Mongolia: merchandise exports and imports, 1996-2024
Exports grew from $297.7M in 1996 to $14.8B in 2024, a CAGR of 15.0%. The merchandise balance sits at $6.4B, which is 43% of exports , a simple scale normalisation over the available BACI series. Both exports and imports use reconciled f.o.b. values: CEPII removes estimated freight and insurance costs from import reports before reconciliation. This BACI balance is not a c.i.f.–f.o.b. gap. The more conventional open-economy metric is the current- account balance as % of GDP, reported on the
Source: CEPII BACI 202601 (retrieved 2026-06-01), country export and import totals from reconciled f.o.b. bilateral flows./macro/MNG page.Query
SELECT year,
SUM(total_exports)*1000 AS exports_usd,
SUM(total_imports)*1000 AS imports_usd,
(SUM(total_exports)-SUM(total_imports))*1000 AS balance_usd
FROM 'data/parquet/country_year_totals.parquet'
WHERE country_code IN (496)
GROUP BY year ORDER BY year;Trade balance, 1996-2024
Export composition
The structural change in what a country exports, from agriculture to manufactures to services, or between HS sections, is one of the most studied transitions in development economics (Imbs & Wacziarg 2003; Hausmann, Hwang & Rodrik 2007). The chart below shows the five largest HS sections of Mongolia’s exports in 2024, plotted back thirty years.
Top-5 HS sections of exports, 1996-2024
In 2024, the top three HS sections account for 97% of merchandise exports that map to a HS96 section, a rough measure of sectoral concentration at the coarsest classification level. Shares here are over BACI exports that carry a valid HS96 section mapping, so the five-section series does not sum to 100% of total exports: some HS6 codes (newer HS revisions, non-standard codes) fall outside the 21-section mapping. Note that the top-5 sections are selected by 2024 share, so a section that was dominant in 1996 but has since fallen out of the top 5 will not appear on the chart.
Source: CEPII BACI 202601 (retrieved 2026-06-01) crossed with HS96 section codes. Shares are over the HS6-mapped universe; HS6 codes without an HS92 section fall outside the 21-section totals.Export basket by HS chapter, 2024 · top-30 $14.8B of $14.8B total
Cell area is proportional to 2024 export value. The treemap shows the top 30 HS chapters (HS2 level) of Mongolia’s exports; cells are colour-coded by HS section so structurally related chapters share a hue (e.g. minerals, machinery, textiles). The largest chapter, HS 27 , Mineral fuels, mineral oils and products of their distillation; bituminous substances; mineral waxes, represents 59.0% of the top-30chapter total shown. Compared to Figure 2’s five-section trajectory, this view exposes which specific chapters within the dominant sections drive the overall composition.
Source: CEPII BACI 202601 (retrieved 2026-06-01), f.o.b. exports of HS6 codes aggregated to HS2 chapters, 2024. Restricted to top 30 chapters by value.Query
SELECT SUBSTRING(product_code, 1, 2) AS chapter_code,
ANY_VALUE(p.chapter) AS chapter_name,
p.section,
SUM(cyp.export_value) * 1000 AS value_usd
FROM 'data/parquet/country_year_product/year=2024/*.parquet' cyp
JOIN products p ON p.code = cyp.product_code
WHERE cyp.country_code IN (496) AND cyp.export_value > 0 AND p.section IS NOT NULL
GROUP BY chapter_code, p.section
ORDER BY value_usd DESC LIMIT 30;Import basket by HS chapter, 2024 · top-30 $7.7B of $8.4B total
Cell area is proportional to 2024 import value. The treemap shows the top 30 HS chapters (HS2 level) of Mongolia’s imports; cells are colour-coded by HS section so structurally related chapters share a hue. The largest import chapter, HS 87 , Vehicles; other than railway or tramway rolling stock, and parts and accessories thereof, represents 27.6% of the top-30 chapter total shown. Read alongside Figure 2b to compare what Mongolia sells abroad against what it buys in.
Source: CEPII BACI 202601 (retrieved 2026-06-01), reconciled f.o.b. imports of HS6 codes aggregated to HS2 chapters, 2024. Restricted to top 30 chapters by value.Query
SELECT SUBSTRING(product_code, 1, 2) AS chapter_code,
ANY_VALUE(p.chapter) AS chapter_name,
p.section,
SUM(cyp.import_value) * 1000 AS value_usd
FROM 'data/parquet/country_year_product/year=2024/*.parquet' cyp
JOIN products p ON p.code = cyp.product_code
WHERE cyp.country_code IN (496) AND cyp.import_value > 0 AND p.section IS NOT NULL
GROUP BY chapter_code, p.section
ORDER BY value_usd DESC LIMIT 30;Who it sells to
World map of export destinations, 2024
Each country is shaded by the bilateral value of Mongolia’s exports to it in 2024, binned into quintiles. Mongolia itself is tinted in amber as the origin; white indicates destinations with no recorded bilateral flow. The map makes regional dependency structures visible, neighbours, former colonial ties, bloc partners, in ways a top-list ordering hides.
Source: CEPII BACI 202601 (retrieved 2026-06-01), bilateral exports 2024. Geometry: world-atlas 110m.Top 12 export destinations, 2024
Partner concentration measures market exposure. The single largest destination absorbs 92% of Mongolia’s exports; the top 3 together take 98%. Concentrated partner bases make bilateral shocks (trade wars, recessions) first-order.
Source: CEPII BACI 202601 (retrieved 2026-06-01), bilateral exports 2024. Shares are over total exports.What moved exports between years
The line charts above show levels over time; they do not answer the analyst’s next question: when exports changed between 2023 and 2024, which partners and which products accounted for how much of it? The two bridge charts below answer that directly. Contributors are ordered by absolute dollar change, largest first, and every line outside the top 8 is collapsed into one residual bar so the columns still sum exactly to the total move.
Partners
Figure 3c. Export change by partner, 2023-2024
Exports moved from $15.9B to $14.8B (−$1.1B).
Scroll horizontally to view the full chart.
Year totalsIncrease on continuing linesEntry from zeroExit to zero / declineAll other residual
Products
Figure 3d. Export change by product, 2023-2024
Exports moved from $15.9B to $14.8B (−$1.1B).
Scroll horizontally to view the full chart.
Year totalsIncrease on continuing linesEntry from zeroExit to zero / declineAll other residual
Economic complexity
The Economic Complexity Index (ECI), building on Hidalgo & Hausmann (2009, PNAS) and formalized as the eigenvalue (second-eigenvector) index in the Atlas of Economic Complexity, ranks countries by the productive knowledge embedded in their export basket. Countries that export many products, and whose products are also exported by few others, score high. ECI is predictive of subsequent income growth and structural transformation; see Hausmann et al. (2014, The Atlas of Economic Complexity, MIT Press) for the full methodology and the comparative country atlas. For a non-linear alternative that ranks fast-diversifying economies differently (China, for instance, sits far higher on fitness than on ECI), compare the Economic Fitness metric of Tacchella et al. (2012).
Mongolia: ECI trajectory, 1996-2024
Current ECI: -1.13, ranked #193 of 226 economies in 2024. ECI is zero-centered; positive values mean above-median complexity.
Method: ECI = second eigenvector of the reflections matrix on the BACI RCA≥1 matrix, z-standardized (eigenvalue method of the Atlas of Economic Complexity, Hausmann et al. 2014). Framework: Hidalgo & Hausmann (2009) “The Building Blocks of Economic Complexity,” PNAS 106(26): 10570-10575, whose method of reflections is equivalent to the eigenvector form (Mealy, Farmer & Teytelboym 2019, Science Advances).Export concentration (HHI) and product count, 1996-2024
2024 HHI = 0.361, equivalent to about 2.8 equally-sized product lines.Mongolia exports 1,144 distinct HS6 products. Rising HHI or falling effective-N indicates loss of diversification.
Method: HHI = Σ sᵢ² over HS6 export shares. Adelman (1969).Effective number of exported products (1/HHI)
Niche leadership
Revealed comparative advantage (Balassa 1965) says a country is specialised in a product when its share of that product’s world exports exceeds the country’s share of all world exports. A stronger version asks: which HS6 lines does the country lead the world in? The table below lists the ten largest export lines (by value) where Mongolia ranks in the world top-5 in 2024, restricted to products with at least US$10M of global trade so tiny niches don’t crowd out economically meaningful positions. This is the “niche leadership” view: products the country is not just diversified in, but competitive at the frontier.
Mongolia: top 10 HS6 lines with world top-5 rank, 2024
Mongolia holds a top-5 world-export position in 9of its largest export lines (HS6 products with ≥ US$10M world trade, 2024). The leading niche is HS 270112 , Bituminous coal, not agglomerated , where it ranks #5 globally with 7.0% of world exports. Dominant niches are the revealed-comparative-advantage anchors a trade-shock or industrial- policy analysis should start from.
Source: CEPII BACI 202601 (retrieved 2026-06-01), HS6 exporter rankings, 2024. Restricted to products with ≥ US$10M world trade. Method: Balassa (1965) RCA taken to its rank-based extreme, top-5 world rank is a stringent specialisation test.Query
WITH prod_year AS (
SELECT product_code, country_code, SUM(export_value) AS v
FROM 'data/parquet/country_year_product/year=2024/*.parquet'
WHERE export_value > 0 GROUP BY product_code, country_code
), ranked AS (
SELECT product_code, country_code, v,
RANK() OVER (PARTITION BY product_code ORDER BY v DESC) AS world_rank
FROM prod_year
WHERE product_code IN (SELECT product_code FROM prod_year GROUP BY product_code HAVING SUM(v)*1000 >= 1e7)
)
SELECT product_code, v*1000 AS value_usd, world_rank
FROM ranked WHERE country_code IN (496) AND world_rank <= 5
ORDER BY v DESC LIMIT 10;Peer countries by structural profile
Which economies share the closest structural profile to Mongolia? Each country is placed in a three-dimensional space of economic complexity (ECI), log GDP per capita, and log total exports, each standardised to zero mean and unit variance in 2024. The five nearest neighbours by Euclidean distance in that space are Mongolia’s closest structural peers, similar on productive-capability, income level, and scale of external trade. This is a trade-specific adaptation of the synthetic-control “donor pool” logic (Abadie, Diamond & Hainmueller 2010).
Mongolia: five closest structural peers, 2024
Closest structural peer: Turkmenistan (ECI -1.19, GDP-pc $6,857, exports $13.5B). Bar length encodes peer proximity in the standardised (ECI, log GDP-pc, log exports) space, shorter bars are closer structural matches. This is the peer set to benchmark trade-policy outcomes against, rather than regional or income-group aggregates. The metric matches on capability frontier and scale, not on sector mix, so countries with similar export composition but different ECI (e.g. higher-complexity apparel exporters) will not appear here.
Method: z-score each dimension (ECI, log GDP-pc, log total exports) across the universe of countries with all three observations in the latest year; rank by Euclidean distance. Abadie, Diamond & Hainmueller (2010) “Synthetic Control Methods for Comparative Case Studies,” JASA 105(490): 493-505.Margins of export growth
Hummels & Klenow (2005, “The variety and quality of a nation’s exports,” American Economic Review95(3): 704-723) introduced the split of a country’s exports into an extensive margin (the set of goods it ships) and an intensive margin (how much of each). In their own measure the extensive margin is nota raw line count: following Feenstra (1994), each category is weighted by its importance in world trade. The figure below applies a simplified, count-based version of that distinction to one country’s export growth over time, so the levels are a proxy, not the Feenstra-weighted index. The two margins still respond to different levers: trade-cost reductions and discovery push the extensive margin (Melitz 2003), while productivity and demand push the intensive.
Margins of export growth, 2014-2024
Over 10 years, total exports grew at 9.1%/yr. Decomposition: HS6 line count moved from 1,469 to 1,144 (extensive margin -2.5%/yr); average value per line moved from $4.2M to $12.9M (intensive margin 11.9%/yr). The intensive margin dominates, which under the extensive/intensive logic indicates growth via deepening sales of existing lines (productivity, scale, or quality).
Method: simplified count-based margin decomposition. The extensive/intensive distinction is from Hummels & Klenow (2005) AER 95(3): 704-723, whose own extensive margin is Feenstra (1994) world-trade-weighted, not a line count. Here, extensive margin = CAGR of distinct HS6 export lines; intensive margin = CAGR of (total exports / line count); total CAGR ≈ extensive + intensive (log-linear approximation).Query
WITH totals AS ( SELECT year, SUM(total_exports)*1000 AS exports_usd FROM 'data/parquet/country_year_totals.parquet' WHERE country_code IN (496) GROUP BY year ) SELECT h.year, h.num_products, t.exports_usd FROM 'data/parquet/country_hhi.parquet' h JOIN totals t USING(year) WHERE h.country_code = 496 AND h.year IN (2014, 2024);
Export basket on the complexity frontier
Mongolia: export value vs. product complexity (PCI), 2024
Each dot is one HS6 product in Mongolia’s basket with more than US$1M in exports in 2024 (long-tail marginal exports below that floor are filtered out so the scatter is legible; the filter drops many HS6 codes for small economies and few for large ones). Horizontal = export value (log), vertical = Product Complexity Index (PCI). Dots upper-right are high-value, high-complexity products (machinery, precision instruments). Lower-left products carry less productive knowledge per dollar. A basket shifted toward the upper-right correlates with higher ECI and higher income.
Method: PCI = product loadings from the second-eigenvector complexity decomposition of the country-product RCA matrix (eigenvalue method of the Atlas of Economic Complexity, Hausmann et al. 2014; framework from Hidalgo & Hausmann 2009, PNAS; eigenvector form equivalent to the method of reflections, Mealy et al. 2019). Basket restricted to HS6 exports > US$1M in the latest year.Related
- Value-chain position, domestic vs foreign value added in Mongolia’s exports, VAX ratio, and upstream/downstream index (OECD TiVA)
- Economic Fitness, the non-linear Tacchella-Pietronero complexity ranking, and how it diverges from ECI
- Research index, analytical pieces grounded in BACI flows and gravity covariates
- Sector monitor, quarterly deep dives on 12 HS-defined sectors
- Compare Mongolia against peer economies
- Exporter profile, basket composition, RCA, and partners