School of Economics and Management, Xinjiang University · Prof. Zhang Lijie’s team
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CA-TECI

Central Asia Trade and Economic Cooperation Index

Central Asia Trade and Economic Cooperation Index

Coverage · From 2013-01Base: 2015–2019 mean = 100
Latest monthly value · 2026-09127.6
3-month moving average115.6
Monthly change · index points+17.6
Empirical Bayes aggregation136.6

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Base: 2015–2019 mean = 100. In the regional view, the bold line is the 3-month average and the pale line shows monthly values.

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CA-TECICooperation milestones

1. Measuring institutional trade cooperation

Trade policy uncertainty and institutional cooperation affect the conditions for cross-border exchange. Building on the text-based measurement approach of Baker, Bloom and Davis (2016), CA-TECI measures news coverage of trade agreements, reciprocal tariff concessions, customs facilitation and cross-border infrastructure cooperation. The index supports analysis of changes in institutional cooperation and their relationship with trade flows in Central Asia.

The Central Asia Trade and Economic Cooperation Index (CA-TECI) uses the same sample as CA-TPU: 3,084,775 Russian-language articles from eight outlets in Kazakhstan, Uzbekistan, Kyrgyzstan and Tajikistan, covering January 2013 to September 2026. Both indices use a common base period while measuring distinct dimensions of the trade policy environment.

2. News sample and reference population

CA-TECI uses international trade policy coverage as its reference sample to reduce sensitivity to changes in the volume of social and entertainment reporting. Excluding articles on domestic municipal utility charges yields 32,340 reference articles, . Of these, 6,591 meet the cooperation criteria, , corresponding to 20.38% of the reference sample.

Country News outlet Total articles International trade policy articles () Cooperation articles () Base-period mean share (%) Base-period SD (percentage points) Empirical Bayes weight ()
Kazakhstan (KZ) Kazinform 800,664 9,472 2,299 20.47 4.68 11.21%
Forbes Kazakhstan 147,518 3,489 496 13.06 3.78 15.29%
Uzbekistan (UZ) Kun 295,041 3,701 594 14.54 5.42 9.43%
UzA (National Agency) 166,464 2,824 1,013 30.29 5.12 10.25%
Kyrgyzstan (KG) 24 News Agency 386,704 4,209 555 13.38 4.01 13.45%
Kaktus Media 1,090,618 3,795 428 11.15 4.34 12.22%
Tajikistan (TJ) Asia-Plus 114,578 2,850 580 19.86 3.93 13.87%
Avesta 83,188 2,000 626 30.69 3.81 14.28%
Regional total / pooled benchmark 3,084,775 32,340 6,591 17.85 3.23 100.00%

3. Human validation and sensitivity to outlet composition

Two researchers independently coded a double-blind stratified sample of 600 Russian-language articles, including 450 observations in the main sample and 150 supplementary observations containing trade restriction or municipal utility terms. Horvitz–Thompson inverse-probability weighting yields a precision estimate of 86.7%, recall of 86.2% and an score of 86.5%. Inter-coder agreement is . Indices constructed by excluding one outlet at a time have correlations of with the benchmark.

KEY ECONOMETRIC FINDINGS

Key econometric findings

Local projections associate higher CA-TPU with export contraction and higher CA-TECI with export expansion.

01

Cooperation and export expansion

+16.6%cumulative export increase

h = 6 · p < 0.01

A one-standard-deviation increase in CA-TECI is associated with a cumulative export increase of 16.6% at six months, controlling for exchange rates, commodity prices, destination industrial output and seasonality.

02

Market entry and the extensive margin

63.7%extensive-margin contribution

h = 3 · intensive margin: 36.3%

New product–destination relationships account for most early export growth, consistent with lower fixed compliance costs through agreements and trade facilitation.

03

Physical shipment growth

99.5%physical quantity contribution

h = 3 · 94.0% at h = 6

Decomposing export value into net weight and unit value attributes most expansion to greater shipment volumes, supporting cross-border goods flows as a channel linking cooperation to trade.

4. Export responses and margins of trade

Local projections (Jordà, 2005) use 160,722 observations at the eight-digit product, destination and month level. A one-standard-deviation increase in CA-TECI is associated with a cumulative export increase of 16.6% at six months (; ). At three months (), new product–destination relationships account for 63.7% of export growth, while expansion within existing relationships accounts for 36.3%. Physical shipment growth contributes 99.5% of the increase in export value at three months and 94.0% at six months. These estimates support market entry and greater shipment volumes as channels linking cooperation to trade.

5. Index properties and empirical results

Monthly CA-TECI and selected policy events
Figure 1: CA-TECI and selected institutional cooperation events (2013–2026)
News sample and international trade policy reference sample
Figure 2: Total news sample and international trade policy reference sample
Country series: research figure
Country-level CA-TECI series
Figure 3: Country-level CA-TECI series for Kazakhstan, Uzbekistan, Kyrgyzstan and Tajikistan
Aggregation methods and sensitivity to outlet composition
Figure 4: Four aggregation methods and the range of indices excluding one outlet at a time
Local projection responses and trade margin decomposition
Figure 5: Export responses, extensive and intensive margins, and shipment volume contributions

Research data

Monthly series, country indices and alternative aggregations.

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