{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-10-30","version":"1"},"project_desc":{"authoring_entity":[{"name":"Ergys Islamaj","affiliation":"World Bank ","email":"eislamaj@worldbankgroup.org"},{"name":"Aaditya Mattoo","affiliation":"World Bank","email":"amattoo@worldbankgroup.org"},{"name":"Duong Trung Le","affiliation":"World Bank ","email":"dle6@worldbank.org"},{"name":"Agustin Samano Penaloza","affiliation":"World Bank ","email":"asamanopenaloza@worldbankgroup.org"},{"name":"Daisuke Fukuzawa","affiliation":"Japan International Cooperation Agency (JICA)","email":"daisfuk@gmail.com"}],"title_statement":{"title":"Reproducibility package for Growing In China\u2019s Shadow","idno":"RR_WLD_2026_766"},"data_statement":"The reproducibility package relies on 2 types of data: open and limited-access. For the source, access type, file location, and citation of each dataset, refer to the Datasets section and the README file.","software":[{"name":"Stata","version":"19.5 MP"}],"scripts":[{"title":"Reproducibility package for Growing In China\u2019s Shadow","date":"2026-10","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_WLD_2026_766","zip_package":"RR_WLD_2026_766.zip","dependencies":"Stata dependencies (reghdfe, outreg2) are installed from SSC; see the README."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-10-30","abstract":"This paper analyses how China\u2019s rapid expansion has affected growth in other developing economies through the trade channel. The empirical strategy uses a continuous-treatment difference-in-differences (DiD) design that exploits pre-determined variation across countries in the exposure of their exports to China\u2019s import demand and export supply in global markets, well before China became a dominant trader. The paper shows that China\u2019s rising demand for commodities and intermediate goods has had a favorable impact on other developing countries\u2019 growth, while intensified competition from its manufacturing exports has had an adverse effect. The former effect is stronger and therefore the net effect has been positive for most countries. The positive impact is, however, becoming weaker as China\u2019s growth slows down, and developing countries\u2019 longer term growth may also be influenced by the changes in their economic structures induced by China\u2019s trade expansion.","geographic_units":[{"name":"World","code":"WLD"}],"keywords":[{"name":"Unconditional Convergence"},{"name":"China"},{"name":"Export-Import Similarity"},{"name":"Primary Goods"}],"topics":[{"id":"E01","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Measurement and Data on National Income and Product Accounts and Wealth \u2022 Environmental Accounts","parent_id":"E0"},{"id":" E13","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Neoclassical","parent_id":"E1"},{"id":" F10","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"General","parent_id":"F1"},{"id":" F41","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Open Economy Macroeconomics","parent_id":"F4"},{"id":" F62","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Macroeconomic Impacts","parent_id":"F6"},{"id":" O11","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Macroeconomic Analyses of Economic Development","parent_id":"O1"},{"id":" O47","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Empirical Studies of Economic Growth \u2022 Aggregate Productivity \u2022 Cross-Country Output Convergence","parent_id":"O4"}],"output":[{"type":"Working Paper","description":"Policy Research Working Paper (PRWP)","title":"Growing In China\u2019s Shadow"}],"language":[{"name":"English","code":"EN"}],"disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"MIT License","uri":"https:\/\/opensource.org\/license\/mit"},{"name":"World Bank IGO Rider","uri":"https:\/\/github.com\/worldbank\/metadata-editor\/blob\/main\/WB-IGO-RIDER.md"}],"contacts":[{"name":"Ergys Islamaj","affiliation":"World Bank ","email":"eislamaj@worldbankgroup.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"Penn World Tables (Versions 10.01 and 11.0)","note":"Two versions used. (1) Penn World Table 10.01: used for the 1960-2019 GDP series and Figure 1, and as the source for GDP-per-capita growth variables (st_rgdp, st_rgdpchn, st_lag and their ov_* indicators) in main_country_year_inputs.dta and appendix_country_year_inputs.dta. Download: https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/pwt-releases\/pwt1001. (2) Penn World Table 11.0: used for the extended sample through 2023. Download: https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/pwt-releases\/pwt110.  File location: data\/raw_data\/pwt1001.dta; data\/raw_data\/pwt110.dta","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International License (CC BY 4.0)","uri":"https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/","citation":"Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer. 2015. Penn World Table [dataset]. https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/deed.en"},{"name":"International Monetary Fund (IMF) Structural Reform Database \u2014 Minimal Extract","note":" IMF Structural Reform Database (SRD), October 2021 project vintage. A minimal extract from the IMF Structural Reform Database (SRD); the single worksheet 'Reform indices' contains only ISO3, year, and the five reform components used to construct Table 5. Unused worksheets, variables, and observations with no reported reform component have been removed from the archived extract. Reference: Alesina, A., D. Furceri, J. D. Ostry, C. Papageorgiou, and D. Quinn (2020), \"Structural Reforms and Electoral Outcomes: Evidence from a World-Wide Dataset,\" NBER Working Paper 26720. File location: data\/raw_data\/structural_reform_indices_extract.xlsx.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/data.imf.org\/Datasets\/SRD","citation":"Alesina, A., D. Furceri, J. D. Ostry, C. Papageorgiou, and D. Quinn (2020), Structural Reforms and Electoral Outcomes: Evidence from a World-Wide Dataset [dataset], NBER Working Paper 26720. ","license_uri":"https:\/\/www.imf.org\/en\/about\/copyright-and-terms"},{"name":"Economic Complexity and China Trade Series (Figures 2, A2.1 and A4.1)","note":" Minimal archived source series for three figures, stored in a single workbook with no Haver Analytics data. The workbook contains three worksheets, each sourced from the Growth Lab at Harvard University Atlas of Economic Complexity (SITC Rev. 2). (1) Worksheet 'Figure 2 - ECI': Annual Economic Complexity Index (ECI) series for China and the comparison group of other emerging and developing economies, 1995-2021. Source: Growth Lab at Harvard University, Atlas of Economic Complexity, SITC Rev. 2 country data and Economic Complexity Index. Data and methodology: https:\/\/atlas.hks.harvard.edu\/data-downloads\/. ECI definition: https:\/\/atlas.hks.harvard.edu\/glossary\/. (2) Worksheet 'Figure A2.1 - Trade shares': China's shares of world manufacturing and commodity exports and imports, 1985-2023. Commodity products are SITC sections 0-4; manufacturing products are SITC sections 5-8. Source: Growth Lab at Harvard University, Atlas of Economic Complexity, SITC Rev. 2 country-partner-product-section trade data. Data and methodology: https:\/\/atlas.hks.harvard.edu\/data-downloads\/. (3) Worksheet 'Figure A4.1 - End use': Annual merchandise trade between China and emerging and developing economies, split into final and intermediate goods, 1995-2022. BACI trade values (thousand current US dollars) are aggregated using the HS-to-BEC concordance and converted to billion US dollars by data_construction.do. Trade source: CEPII BACI, based on UN Comtrade bilateral merchandise trade. Database: https:\/\/www.cepii.fr\/CEPII\/en\/bdd_modele\/bdd_modele_item.asp?id=37.  File location: data\/raw_data\/exhibit_source_series.xlsx.","access_type":"Data is publicly available and included in the reproducibility package.","citation":"Authors' compilation. 2026.  Economic Complexity and China Trade Series (Figures 2, A2.1 and A4.1) [dataset]. Compiled from: Growth Lab at Harvard University, Atlas of Economic Complexity  SITC Rev. 2 country data and Economic Complexity Index,  country-partner-product-section trade data and CEPII BACI, based on UN Comtrade bilateral merchandise trade."},{"name":"World Development Indicators ","note":"World Development Indicators, indicator NY.GDP.TOTL.RT.ZS (total natural-resource rents as % of GDP), 2019 cross-section, limited to countries represented in the extended panel. File location: data\/raw_data\/wdi_total_natural_resource_rents_2019.csv.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International License (CC BY 4.0)","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-of-use-for-datasets","uri":"https:\/\/data.worldbank.org\/indicator\/NY.GDP.TOTL.RT.ZS","citation":"World Bank. 2021. World Development Indicators [dataset]. Indicator: NY.GDP.TOTL.RT.ZS. https:\/\/data.worldbank.org\/indicator\/NY.GDP.TOTL.RT.ZS."},{"name":"Country Trade Aggregates","note":"Derived file containing country-year manufacturing exports, manufacturing imports, commodity exports, and current-price Gross Domestic Product (GDP). Commodity products are Standard International Trade Classification (SITC) sections 0-4; manufacturing products are SITC sections 5-8. Only variables used by the analysis are retained. Sources: (1) Growth Lab at Harvard University Atlas SITC Rev. 2 country-partner-product-section trade data. Download: https:\/\/atlas.hks.harvard.edu\/data-downloads\/. (2) World Development Indicators current-price GDP (indicator NY.GDP.MKTP.CD). Download: https:\/\/databank.worldbank.org\/source\/world-development-indicators. Construction: the China trade-share and sector-aggregation routines in the archived SITC source-processing script. File location: data\/derived_inputs\/sitc_country_trade_aggregates.dta.","access_type":"Data is publicly available and included in the reproducibility package.","citation":"Authors' compilation. 2026. Country Trade Aggregates [dataset]. Compiled from: Growth Lab at Harvard University, Atlas of Economic Complexity, SITC Rev. 2 country-partner-product-section trade data and World Development Indicators current-price GDP. "},{"name":"Intermediate Goods Exports to China","note":"Country-year intermediate-goods exports to China as a share of GDP. The archived source workflow classifies Basis for International Trade Analysis (BACI) bilateral trade with the UN Broad Economic Categories (BEC) and merges World Development Indicators (WDI) GDP. Historical construction lineage: BACI\/BEC aggregation routines in the archived source-processing scripts. Download instructions: obtain annual BACI bilateral trade files from the Centre for Prospective Studies and International Information (CEPII) BACI portal, the matching Harmonized System (HS) to-BEC concordance from United Nations Statistics Division, and current-price GDP (NY.GDP.MKTP.CD) from WDI. \nSources: CEPII BACI product-level bilateral trade; UN Statistics Division HS-to-BEC concordance; World Development Indicators current-price GDP. URL: CEPII BACI: https:\/\/www.cepii.fr\/CEPII\/en\/bdd_modele\/bdd_modele_item.asp?id=37 . \nFile location: data\/derived_inputs\/baci_exports_to_china_by_end_use.dta.","access_type":"Data is publicly available and included in the reproducibility package.","citation":"Authors' compilation. 2026. Intermediate Goods Exports to China [dataset]. Compiled from: CEPII BACI bilateral trade data; UN Statistics Division HS-to-BEC concordance; World Bank World Development Indicators (GDP, current US$)"},{"name":"Trade Similarity Indices","note":"Derived file containing combined country-year similarity measures for China, the US, and Germany, keyed by wbg_ccode and year. China measures: Finger-Kreinin export similarities (variables: Sim_wCHNexp and Sim_wCHNimp), export- and import-side Spearman measures, and the corresponding fixed 1995 Spearman and Finger-Kreinin measures. US measures: (variables: corrUSAexp and corrUSAimp). Germany measures: (Variables: corrDEUexp and corrDEUimp). China measures are used in Tables 2-4 and Appendix A1 and A3; US and Germany measures are used in Table A3.10. Source: Growth Lab at Harvard University, Atlas of Economic Complexity, four-digit Standard International Trade Classification (SITC) Revision. 2 country-product trade data. Download Instructions: obtain the four-digit SITC country-product trade file and matching product metadata from https:\/\/atlas.hks.harvard.edu\/data-downloads\/. Construction code: do files\/data_construction.do, similarity mode. File location: data\/derived_inputs\/sitc_similarity_indices.dta.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/atlas.hks.harvard.edu\/data-downloads\/","citation":"Authors' compilation. 2026. Trade Similarity Indices [dataset]. Compiled from: Growth Lab at Harvard University, Atlas of Economic Complexity, SITC Rev. 2 country-product trade data.","license_uri":"https:\/\/atlas.hks.harvard.edu\/data-downloads\/"},{"name":"Country-Year Panel Variables (Main and Extended Samples)","note":"Consolidated non-similarity country-year inputs used by the main panel. The file is accepted as a consolidated input; the download source for each retained variable group is listed below. (1) wbg_ccode, country, EMDE, incomelevel: World Bank country metadata, analytical economy classifications, and income groups. Download: https:\/\/databank.worldbank.org\/source\/world-development-indicators. (2) Population_ave: country average calculated from WDI total population, indicator SP.POP.TOTL. Download: https:\/\/data.worldbank.org\/indicator\/SP.POP.TOTL. (3) reform_indx; st_trade, st_extfin, st_domfin, st_prdm, st_labor and their ov_* indicators: IMF Structural Reform Database, October 2021 project vintage. The five components are trade, external finance, domestic finance, product markets, and labor markets. Download: https:\/\/data.imf.org\/Datasets\/SRD. (4) energy_price_index: World Bank Commodity Price Data (Pink Sheet), annual Energy price index. Download: https:\/\/www.worldbank.org\/en\/research\/commodity-markets. (5) us_real_interest_rate: United States real interest rate, WDI indicator FR.INR.RINR. Download: https:\/\/data.worldbank.org\/indicator\/FR.INR.RINR?locations=US. (6) comm: commodity-exporter indicator, equal to one when 2010 fuel plus ores and metals exports exceed 30 percent of merchandise exports. Constructed from WDI indicators TX.VAL.FUEL.ZS.UN and TX.VAL.MMTL.ZS.UN. Download: https:\/\/databank.worldbank.org\/source\/world-development-indicators. (7) st_rgdp, st_rgdpchn, st_lag and their ov_* indicators: GDP-per-capita growth source values from Penn World Table 10.01. Download: https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/pwt-releases\/pwt1001. (8) st_gexp, st_gimp and their ov_* indicators: China manufacturing export and import growth source values calculated from the Harvard Growth Lab Atlas SITC Rev. 2 trade download.\n\nThe extended sample uses; (1) wbg_ccode, country, EMDE, incomelevel:, (2) Population_ave;  (7) st_rgdp, st_rgdpchn, st_lag and their ov_* indicators and (8) st_gexp, st_gimp and their ov_* indicators\n . File location: data\/derived_inputs\/main_country_year_inputs.dta; data\/derived_inputs\/appendix_country_year_inputs.dta","access_type":"Data is publicly available and included in the reproducibility package.","license":"Custom License","citation":"Authors' compilation. 2026. Country-Year Panel Variables (Main and Extended Samples) [dataset]. Compiled from: World Bank World Development Indicators; IMF Structural Reform Database; World Bank Commodity Price Data (Pink Sheet); Penn World Table 10.01; Growth Lab at Harvard University, Atlas of Economic Complexity.\n"},{"name":" Commodity Price Data.","note":"Reported Table A2.1 correlations. The calculation uses annual year-on-year growth in World Bank Pink Sheet commodity-price indices and China's annual Gross Domestic Product (GDP) growth from World Bank Economic Monitoring Macroeconomic Data. Download instructions: obtain annual nominal commodity-price indices from https:\/\/www.worldbank.org\/en\/research\/commodity-markets and China's GDP growth from World Bank Economic Monitoring Macroeconomic Data. Use the historical releases underlying the table and prepare the files specified in the external mode of do files\/data_construction.do. File location: data\/derived_inputs\/table_a2_1_reported_correlations.csv.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International License (CC BY 4.0)","license_uri":"https:\/\/datacatalog.worldbank.org\/public-licenses#cc-by","uri":"https:\/\/www.worldbank.org\/en\/research\/commodity-markets","citation":"World Bank. 2026. Commodity Price Data [dataset]. https:\/\/www.worldbank.org\/en\/research\/commodity-markets"},{"name":"Quarterly Export-Price Indices and China Activity Growth Series.","note":"Reported Table A2.2 coefficients and statistics. The calculation uses a licensed Haver Analytics quarterly export-price series, China activity growth, and a commodity-exporter classification. Source observations cannot be redistributed. Authorized Haver Analytics users should obtain the quarterly export-price indices and China activity series from their licensed data service, then prepare the input format specified in the external mode of do files\/data_construction.do, and run: do \"do files\/data_construction.do\" external. Download: https:\/\/www.haver.com\/. File location: data\/derived_inputs\/table_a2_2_reported_regressions.csv ","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Custom License","uri":"https:\/\/www.haver.com\/","citation":"Haver Analytics. 2026. Quarterly Export-Price Indices and China Activity Growth Series [dataset]. https:\/\/www.haver.com\/."}],"reproduction_instructions":"To reproduce the exhibit in this paper, a new user should do the following;\n1. Access the Haver Analytics dataset (subscription required)\n2. Open the master do file `run_all` and run the script","technology_requirements":"Run time ~ 30 minutes","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise\n\u2022 Processor: Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz (2.30 GHz) (2 processors)\n\u2022 Memory available: 16 GB"},"datacite":{"creators":[{"givenName":"Ergys","familyName":"Islamaj","nameType":"Personal","affiliation":[{"name":"World Bank ","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Aaditya","familyName":"Mattoo","nameType":"Personal","affiliation":[{"name":"World Bank ","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Duong Trung","familyName":"Le","nameType":"Personal","affiliation":[{"name":"World Bank ","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Agustin Samano","familyName":"Penaloza","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Daisuke","familyName":"Fukuzawa","nameType":"Personal","affiliation":[{"name":"Japan International Cooperation Agency (JICA)","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org","affiliationIdentifier":"https:\/\/ror.org\/022es3t03"}]}],"titles":[{"lang":"en","title":"Reproducibility package for Growing In China\u2019s Shadow"},{"title":"RR_WLD_2026_766","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_WLD_2026_766","language":"en"},"tags":[{"tag":"DOI"},{"tag":"Limited-access data"},{"tag":"Open Code"}],"schematype":"script"}