{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-11-04","version":"1"},"project_desc":{"authoring_entity":[{"name":"Ergys Islamaj","affiliation":"World Bank Group","email":"eislamaj@worldbankgroup.org"},{"name":"Haiqin Liu","affiliation":"World Bank Group","email":"hliu10@worldbank.org"},{"name":"Jongrim Ha","affiliation":"World Bank Group","email":"jongrimha@worldbank.org"},{"name":"Aaditya Mattoo","affiliation":"World Bank Group","email":"amattoo@worldbankgroup.org"}],"title_statement":{"title":"Reproducibility package for The Effects of Global Uncertainty on Firms in Emerging and Developing Economies: Quantifying the Trade and Financial Channels","idno":"RR_WLD_2026_786"},"data_statement":"The reproducibility package relies on two types of data: open and limited-access data. 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"},{"name":"MATLAB","version":"R2024b"}],"scripts":[{"title":"Reproducibility package for The Effects of Global Uncertainty on Firms in Emerging and Developing Economies: Quantifying the Trade and Financial Channels","date":"2026-11","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_WLD_2026_786","zip_package":"RR_WLD_2026_786.zip","dependencies":"Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-11-04","abstract":"We study how global uncertainty affects firms in emerging market and developing economies (EMDEs) and how financial constraints and international trade linkages shape its transmission. We combine equity returns and financial accounts of publicly listed firms with country\u2013sector input\u2013output data for 2000\u201324. Heightened global uncertainty is associated with lower firm valuations, weaker sales, and declining employment. Greater exposure to foreign customers amplifies declines in sales and employment, while reliance on imported inputs and higher leverage are associated with sharper investment contractions. Complementary evidence from a Bayesian panel structural vector autoregression shows that global economic policy and financial uncertainty shocks reduce aggregate output, investment, and consumption in EMDEs. These findings connect firm-level adjustment to macroeconomic outcomes and identify financial vulnerability and international production linkages as key channels through which global uncertainty is transmitted to EMDEs.","geographic_units":[{"name":"World","code":"WLD"}],"keywords":[{"name":"Uncertainty"},{"name":"Firm Behavior"},{"name":"Production Networks"},{"name":"Financial Constraints"},{"name":"EMDEs"}],"topics":[{"id":"D81","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Criteria for Decision-Making under Risk and Uncertainty","parent_id":"D8"},{"id":" E32","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Business Fluctuations \u2022 Cycles","parent_id":"E3"},{"id":" F14","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Empirical Studies of Trade","parent_id":"F1"},{"id":" F44","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"International Business Cycles","parent_id":"F4"}],"output":[{"type":"Working Paper","description":"Policy Research Working Paper (PRWP)","title":"The Effects of Global Uncertainty on Firms in Emerging and Developing Economies: Quantifying the Trade and Financial Channels"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Runtime ~ 30 minutes (Stata ~ 29 minutes; MATLAB ~ 1-2 minutes). ","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 Group","email":"eislamaj@worldbankgroup.org"},{"name":"Reproducibility World Bank Group","affiliation":"World Bank Group","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"Datastream Equities, daily stock prices (LSEG)","note":"Filename: data\/ds_daily.dta. Firm-day dataset built by the authors from LSEG Datastream daily closing prices in US dollars for listed firms in emerging market and developing economies, 2000-2024, retrieved through Wharton Research Data Services (WRDS) in December 2024. It contains annualized daily log returns and 90-day rolling return volatility, winsorized at the 1st and 99th percentiles. Used for Tables 1, 2 and A2. The construction from the raw country-level Datastream extracts is documented in code\/A_collect_firm_data.do; the raw extracts are not included. A list of variables is provided in variable_inventory.csv, and the file hash is in data_hash_report.csv. For more details on the data, interested users can reach out to one of the authors at hliu10@worldbank.org.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Custom","citation":"LSEG Data & Analytics. (2024). Datastream Equities [dataset]. Licensed data accessed through Wharton Research Data Services (WRDS) under an institutional subscription. https:\/\/www.lseg.com\/en\/data-analytics","uri":"https:\/\/www.lseg.com\/en\/data-analytics"},{"name":"Worldscope Fundamentals, quarterly and annual company financial statements (LSEG)","note":"Filename: data\/ws_EMDE.dta. Firm-quarter panel built by the authors from LSEG Worldscope quarterly and annual items (ITEM1001, 2501, 2999, 3051, 3255, 4601, 7011, 7021, 7210, 18198, 18272, 18273), 2000-2024, retrieved through WRDS in December 2024. It contains sales intensity, investment ratio, employment, size, age, leverage, Tobin's Q and external finance dependence for firms in 74 emerging market and developing economies. Used for Tables 1, 3, 4, 5, 6, A1, A3 and A4 and Figure 2. The cleaning of the raw Worldscope extracts is documented in code\/A_collect_firm_data.do; the raw extracts are not included. A list of variables is provided in variable_inventory.csv, and the file hash is in data_hash_report.csv. ","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Custom","citation":"LSEG Data & Analytics. (2024). Worldscope Fundamentals [dataset]. Licensed data accessed through Wharton Research Data Services (WRDS) under an institutional subscription. https:\/\/www.lseg.com\/en\/data-analytics","uri":"https:\/\/www.lseg.com\/en\/data-analytics"},{"name":"Haver Analytics Emerging Markets database (EMERGE)","note":"Filename: PSVAR\/rawdata\/EMDE_q_m.xlsx. Quarterly real GDP, final consumption and gross fixed capital formation for emerging market and developing economies from the Haver Analytics EMERGE database, accessed in January 2026. The Haver series codes (e.g. N186NGPC@EMERGE) are listed as variable names in variable_inventory.csv. Used to build the country-quarter panel for the Bayesian panel SVAR (Figure 3, Table 6, Figure A1, Table A4). A list of variables is provided in variable_inventory.csv, and the file hash is in data_hash_report.csv. ","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Custom","citation":"Haver Analytics. (2026). Emerging Markets Database (EMERGE) [dataset]. Licensed data accessed under an institutional subscription. https:\/\/www.haver.com\/","uri":"https:\/\/www.haver.com\/"},{"name":"Haver Analytics daily stock price indices","note":"Filename: PSVAR\/rawdata\/SP_d.dta. Daily national stock price indices from Haver Analytics, accessed in January 2026, averaged to quarterly frequency for the Bayesian panel SVAR. A list of variables is provided in variable_inventory.csv, and the file hash is in data_hash_report.csv.","access_type":"Data access requires purchase or human approval and is not included in the reproducibility package.","license":"Custom","citation":"Haver Analytics. (2026). Daily stock price indices [dataset]. Licensed data accessed under an institutional subscription. https:\/\/www.haver.com\/","uri":"https:\/\/www.haver.com\/"},{"name":"BACI: International Trade Database at the Product Level, HS 1996 (CEPII)","note":"Filename: data\/CEPII-BACI\/HS96\/BACI_HS96_Y2009_V202501.csv to BACI_HS96_Y2023_V202501.csv; data\/CEPII-BACI\/HS96\/country_codes_V202501.csv; data\/CEPII-BACI\/HS96\/product_codes_HS96_V202501.csv; data\/CEPII-BACI\/HS96\/Readme.txt; data\/CEPII-BACI\/country_codes_V202401.csv; data\/CEPII-BACI\/country_codes_V202401.dta; data\/ALLexports_isic4d_partner.dta (derived). Bilateral trade flows by HS 1996 product, version 202501, accessed in January 2026. code\/B_Exports_HS_ISIC.do aggregates them to ISIC Rev. 4 exporter-partner flows, used for the import and export shares (InDeg, OutDeg) in Tables 6 and A4.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Etalab Open Licence 2.0","license_uri":"https:\/\/www.etalab.gouv.fr\/licence-ouverte-open-licence\/","citation":"Gaulier, G. and Zignago, S. (2010). BACI: International Trade Database at the Product-Level, HS 1996, version 202501 [dataset]. CEPII. https:\/\/www.cepii.fr\/CEPII\/en\/bdd_modele\/bdd_modele_item.asp?id=37","uri":"https:\/\/www.cepii.fr\/CEPII\/en\/bdd_modele\/bdd_modele_item.asp?id=37"},{"name":"Classification Correspondence Tables (HS 1996, CPC, ISIC Rev. 4)","note":"Filename: data\/CEPII-BACI\/CPCv10-HS1996.txt; data\/CEPII-BACI\/CPCv10_CPCv11_full.txt; data\/CEPII-BACI\/CPCv11_CPCv2.txt; data\/CEPII-BACI\/ISIC4-CPC2.txt. Correspondences between HS 1996, Central Product Classification (CPC) versions 1.0, 1.1 and 2, and ISIC Rev. 4, accessed in January 2026. Used in code\/B_Exports_HS_ISIC.do to map BACI products to ISIC Rev. 4.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Public","citation":"United Nations Statistics Division. (2026). Classification Correspondence Tables (HS 1996, CPC, ISIC Rev. 4) [dataset]. United Nations. https:\/\/unstats.un.org\/unsd\/classifications\/Econ","uri":"https:\/\/unstats.un.org\/unsd\/classifications\/Econ"},{"name":"Multiregional Input-Output Tables","note":"Filename: data\/MRIO\/ADB MRIO 2000, at constant 2010 prices.xlsx; data\/MRIO\/ADB MRIO 2007, at constant 2010 prices.xlsx to data\/MRIO\/ADB MRIO 2023, at constant 2010 prices.xlsx; data\/InOutDegree.dta (derived). Multiregional input-output tables for 62 economies at constant 2010 prices, accessed on January 12, 2026. code\/B_MRIOT.m builds the country-sector upstream (InDegree) and downstream (OutDegree) exposure measures used in Table 4.\n\n\n","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 3.0 IGO (CC BY 3.0 IGO)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/igo\/","citation":"Asian Development Bank. (2026). Multiregional Input-Output Tables at constant 2010 prices [dataset]. ADB Key Indicators Database. https:\/\/kidb.adb.org\/globalization\/constant","uri":"https:\/\/kidb.adb.org\/globalization\/constant, https:\/\/kidb.adb.org\/download\/mrio-file\/179"},{"name":"Multiregional Input-Output sector correspondence","note":"Filename: data\/MRIO\/Correspondence_ISIC4-ISIC31-MRIO.xlsx; data\/crosswalk_sic4_MRIO.dta; data\/crosswalk_sic4_3digit_MRIO.dta; data\/crosswalk_sic4_2digit_MRIO.dta; data\/crosswalk_sic31_MRIO.dta; data\/crosswalk_sic31_3digit_MRIO.dta; data\/crosswalk_sic31_2digit_MRIO.dta (derived). Correspondence published by ADB, accessed in January 2026. code\/B_create_sic_MRIO_crosswalk.do builds the crosswalks from firm industry codes to MRIO sectors at 4, 3 and 2 digits, used in Table 4.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 3.0 IGO (CC BY 3.0 IGO)","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/igo\/","citation":"Asian Development Bank. (2026). Multiregional Input-Output sector correspondence [dataset]. ADB Key Indicators Database. https:\/\/kidb.adb.org\/download\/mrio-file\/179","uri":"https:\/\/kidb.adb.org\/download\/mrio-file\/179"},{"name":"Bank for International Settlements (BIS) Effective Exchange Rates","note":"Filename: PSVAR\/rawdata\/WS_EER_csv_row.csv. Monthly nominal broad effective exchange rates from the BIS bulk download, accessed in January 2026. Averaged to quarterly frequency for the country-quarter panel used in the Bayesian panel SVAR.","access_type":"Data is publicly available and included in the reproducibility package.","license":"BIS Terms and Conditions","license_uri":"https:\/\/www.bis.org\/terms_conditions.htm","citation":"Bank for International Settlements. (2026). Effective Exchange Rates [dataset]. BIS Data Portal. https:\/\/data.bis.org\/topics\/EER","uri":"https:\/\/data.bis.org\/topics\/EER"},{"name":"Global Database of Inflation","note":"Filename: PSVAR\/rawdata\/hcpi_q.dta. Quarterly headline consumer price index from the World Bank Prospects Group's Global Database of Inflation (Ha, Kose and Ohnsorge 2023), April 2025 version, accessed in January 2026. Used in the country-quarter panel for the Bayesian panel SVAR.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","license_uri":"https:\/\/www.worldbank.org\/ext\/en\/legal\/terms-conditions","citation":"Ha, J., Kose, M. A. and Ohnsorge, F. (2025). Global Database of Inflation, April 2025 version [dataset]. World Bank. https:\/\/www.worldbank.org\/en\/research\/brief\/inflation-database","uri":"https:\/\/www.worldbank.org\/en\/research\/brief\/inflation-database"},{"name":"Index of Global Real Economic Activity (IGREA)","note":"Filename: PSVAR\/rawdata\/IGREA.xlsx. Quarterly Index of Global Real Economic Activity (Kilian 2009, 2019), downloaded from FRED, Federal Reserve Bank of St. Louis, in January 2026. Used as the global activity variable in the Bayesian panel SVAR.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Public","license_uri":"https:\/\/fred.stlouisfed.org\/legal\/","citation":"Kilian, L. (2026). Index of Global Real Economic Activity [IGREA] [dataset]. FRED, Federal Reserve Bank of St. Louis. https:\/\/fred.stlouisfed.org\/series\/IGREA","uri":"https:\/\/fred.stlouisfed.org\/series\/IGREA"},{"name":"Global Debt Database","note":"Filename: data\/GlobalDebtDatabase_Sep25.dta. Private, household, corporate and public debt as a share of GDP, September 2025 vintage, accessed in January 2026. The country average of private debt (pvd_all) over 2000-2024 is used as a country characteristic in Tables 6 and A4.","access_type":"Data is publicly available and included in the reproducibility package.","license":"IMF Copyright and Usage","license_uri":"https:\/\/www.imf.org\/external\/terms.htm","citation":"International Monetary Fund. (2025). Global Debt Database, September 2025 [dataset]. IMF. https:\/\/www.imf.org\/external\/datamapper\/datasets\/GDD","uri":"https:\/\/www.imf.org\/external\/datamapper\/datasets\/GDD"},{"name":"Global Economic Policy Uncertainty Index","note":"Filename: PSVAR\/rawdata\/All_Measures.xlsx (column GEPU); data\/u_z_scored_lag_q.dta (derived). Global Economic Policy Uncertainty index, PPP-adjusted GDP weights (Baker, Bloom and Davis 2016), accessed on January 12, 2026. code\/A_build_uncertainty_zscore.do standardizes it over 2000Q1-2024Q4; it is the main uncertainty measure in all exhibits.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","citation":"Baker, S. R., Bloom, N. and Davis, S. J. (2026). Global Economic Policy Uncertainty Index [dataset]. Economic Policy Uncertainty. https:\/\/www.policyuncertainty.com\/media\/Global_Policy_Uncertainty_Data.xlsx","uri":"https:\/\/www.policyuncertainty.com\/global_monthly.html","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"name":"World Uncertainty Index","note":"Filename: PSVAR\/rawdata\/All_Measures.xlsx (column WUI); data\/u_z_scored_lag_q.dta (derived). GDP-weighted global World Uncertainty Index (Ahir, Bloom and Furceri 2022), accessed in January 2026. The index is revised over time, so later releases may differ slightly. Standardized by code\/A_build_uncertainty_zscore.do and used as an alternative uncertainty measure in all exhibits.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Public","citation":"Ahir, H., Bloom, N. and Furceri, D. (2026). World Uncertainty Index [dataset]. https:\/\/worlduncertaintyindex.com\/data\/","uri":"https:\/\/worlduncertaintyindex.com\/data\/"},{"name":"Trade Policy Uncertainty Index","note":"Filename: PSVAR\/rawdata\/All_Measures.xlsx (column GTPU); data\/u_z_scored_lag_q.dta (derived). Quarterly Trade Policy Uncertainty index (Caldara, Iacoviello, Molligo, Prestipino and Raffo 2020), accessed in January 2026. Standardized by code\/A_build_uncertainty_zscore.do and used as an alternative uncertainty measure in all exhibits.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International (CC BY 4.0)","citation":"Caldara, D., Iacoviello, M., Molligo, P., Prestipino, A. and Raffo, A. (2026). Trade Policy Uncertainty Index [dataset]. https:\/\/www.matteoiacoviello.com\/tpu.htm","uri":"https:\/\/www.matteoiacoviello.com\/tpu.htm","license_uri":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"name":"Chicago Board Options Exchange Volatility Index (VIX)","note":"Filename: PSVAR\/rawdata\/All_Measures.xlsx (column VIX); data\/u_z_scored_lag_q.dta (derived). CBOE Volatility Index downloaded from FRED at quarterly frequency (average), accessed in January 2026. Standardized by code\/A_build_uncertainty_zscore.do and used as the financial uncertainty measure in all exhibits.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Public","license_uri":"https:\/\/fred.stlouisfed.org\/legal\/","citation":"Chicago Board Options Exchange. (2026). CBOE Volatility Index: VIX [VIXCLS] [dataset]. FRED, Federal Reserve Bank of St. Louis. https:\/\/fred.stlouisfed.org\/series\/VIXCLS","uri":"https:\/\/fred.stlouisfed.org\/series\/VIXCLS"},{"name":"Country Code and country Classification Crosswalks","note":"Filename: data\/ISOCode_Full.dta; data\/MRIOctycode_list.dta; PSVAR\/rawdata\/code_iso_crosswalk.xlsx. Crosswalks prepared by the authors. data\/ISOCode_Full.dta links IMF country codes, ISO2 and ISO3 codes, built from International Financial Statistics (IMF) country lists accessed in December 2023, with the advanced\/emerging economy classification of https:\/\/documents.worldbank.org\/en\/publication\/documents-reports\/documentdetail\/099737510042356177. data\/MRIOctycode_list.dta maps ADB MRIO country codes to ISO3, and PSVAR\/rawdata\/code_iso_crosswalk.xlsx maps Haver country codes to ISO3.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Custom License","citation":"Authors' compilation, World Bank. (2026). Country code and country classification crosswalks [dataset]."}],"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) Platinum 8562Y+ (2 processors)\n\u2022 Memory available: 128 GB\n\u2022 Software version: Stata 19.5 MP; MATLAB R2024b","reproduction_instructions":"To reproduce the findings in this paper, a replicator must:\n1. Secure access to data: obtain the licensed LSEG Datastream and Worldscope data, and the Haver Analytics data (see the Datasets section). Rebuild `data\/ds_daily.dta` and `data\/ws_EMDE.dta` with `code\/A_collect_firm_data.do`, and place `PSVAR\/rawdata\/EMDE_q_m.xlsx` and `PSVAR\/rawdata\/SP_d.dta as listed in `data_hash_report.csv`.\n2. Rebuild the panel SVAR inputs and results, which are not included: run `PSVAR\/create_EMDE_panel.do` (or `PSVAR\/create_EMDE_panel.R`), then `PSVAR\/run_PSVAR.m` with BEAR Toolbox 5 to recreate `PSVAR\/Lag5` and `PSVAR\/Lag8`.\n3. Open the `main` do-file, set the project root on line 16, and run it in Stata.\n4. Run `main.m` in MATLAB from the project root. It produces Figure 3, Table 6, Figure A1, and Table A4.\n\nBecause some of the data is limited-access, the exhibits generated by the replicators are included in the package (table\/, figure\/, and PSVAR\/Figures\/) so that interested users can review them against the paper."},"datacite":{"creators":[{"givenName":"Ergys","familyName":"Islamaj","nameType":"Personal","affiliation":[{"name":"World Bank Group","affiliationIdentifier":"https:\/\/ror.org\/02md09461","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Haiqin","familyName":"Liu","nameType":"Personal","affiliation":[{"name":"World Bank Group","affiliationIdentifier":"https:\/\/ror.org\/02md09461","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Jongrim","familyName":"Ha","nameType":"Personal","affiliation":[{"name":"World Bank Group","affiliationIdentifier":"https:\/\/ror.org\/02md09461","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Aaditya","familyName":"Mattoo","nameType":"Personal","affiliation":[{"name":"World Bank Group","affiliationIdentifier":"https:\/\/ror.org\/02md09461","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]}],"titles":[{"lang":"en","title":"Reproducibility package for The Effects of Global Uncertainty on Firms in Emerging and Developing Economies: Quantifying the Trade and Financial Channels"},{"title":"RR_WLD_2026_786","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_786","language":"en"},"tags":[{"tag":"DOI"},{"tag":"Limited-access Data"},{"tag":"Open Code"}],"schematype":"script"}