The Global Economic Policy Uncertainty (GEPU) index was at its highest in May 2020, when the COVID-19 pandemic brought global economic uncertainty. The index was also **** after the Russian invasion of Ukraine in February 2022. Moreover, the index rose sharply in November 2024 after Donald Trump was re-elected as President of the United States. Trump promised to impose trade tariffs against a range of countries, and did so against Canada, Mexico, and China in February 2024. As of November 2025, the GEPU index stands at 373.28. The GEPU index is constructed by measuring how often the leading newspapers mention economic policy uncertainty in their articles.

Graph and download economic data for Global Economic Policy Uncertainty Index: PPP-Adjusted GDP (GEPUPPP) from Jan 1997 to Nov 2025 about uncertainty, GDP, and indexes.

Graph and download economic data for Global Economic Policy Uncertainty Index: Current Price Adjusted GDP (GEPUCURRENT) from Jan 1997 to Nov 2025 about uncertainty, adjusted, GDP, indexes, and price.

The Global Economic Policy Uncertainty (GEPU) index was at its highest in May 2020, when the COVID-19 pandemic brought global economic uncertainty. The index was also high after the Russian invasion of Ukraine in February 2022. Moreover, the index rose sharply in November 2024 after Donald Trump was re-elected as President of the United States. Trump promised to impose trade tariffs against a range of countries, and did so against Canada, Mexico, and China in February 2024. The GEPU index is constructed by measuring how often the leading newspapers mention economic policy uncertainty in their articles.

Results of the DCC-MIDAS-GEPU model.

Results of the EGARCH-MIDAS-GEPU model.

This is the package of supporting files. In this package, the readers can find the primary dataset in the XLSX/XLS files. The description of the data is also provided. (ZIP)

View details of Parker Hosiery Co Buyer and Gepu Socks Shanghai Co Limited Supplier data to US (United States) with product description, price, date, quantity, major us ports, countries and more.

Descriptive statistics of the data.

View Foshan Gepu Electrical Technology Co Limited import export trade data, including shipment records, HS codes, top buyers, suppliers, trade values, and global market insights.

View details of Socks Import Data of Gepu Socks Shanghai Co Limited Supplier to US at Charleston Sc Port with product description, price, date, quantity, Countries and more.

Statistical description.

Impact of the Gepu on stops to varying degrees.

This paper develops and validates a spillover-based variable selection approach to improve the forecast precision of oil market spot prices. Leveraging the Total Spillover Index (TSI) as a quantitative measure of dynamic interdependencies, we construct six models within a cointegration framework to capture the behaviour of Brent and West Texas Intermediate (WTI) markets from both isolated and global perspectives. A dynamic spillover analysis encompassing static, frequency-domain, and rolling window techniques shows that models incorporating global market indicators exhibit higher TSI values and are more sensitive to macroeconomic shocks, as evidenced by their comovement with the Global Economic Policy Uncertainty (GEPU) Index. Out-of-sample forecasting experiments using both Fractional Cointegration Vector Autoregressive (FCVAR) framework and Long Short-Term Memory (LSTM) networks demonstrate that the hybrid global model, which integrates Brent and WTI spot prices with global market variables, consistently outperforms isolated market models, particularly over medium and long term horizons. These findings highlights the importance of incorporating global dynamics in variable selection, thus enhancing the endogenous explanatory power of forecasting models in complex, interdependent markets.

Graph and download economic data for Global price of Energy index (PNRGINDEXM) from Jan 1992 to Feb 2026 about energy, World, indexes, and price.

The file "fuels.txt" includes daily data for Brent futures (BrentF) and spot (BrentS) prices obtained from nasdaq.com database and three NASDAQ indices:

1) NASDAQ OMX Bio/Clean Fuels Index (GRNBIO). Source: {https://indexes.nasdaqomx.com/Index/Overview/GRNBIO} 2) NASDAQ OMX Fuel Cell Index (GRNFUEL). Source:{https://indexes.nasdaqomx.com/Index/Overview/GRNFUEL} 3) NASDAQ OMX Transportation Index (GRNTRN). Source: {https://indexes.nasdaqomx.com/Index/Overview/GRNTRN}

The file "fundamentals.txt" includes monthly data for the following variables:

1) WIP: world industrial production index collected from:{https://sites.google.com/site/cjsbaumeister/datasets?authuser=0} 2) COMM: real commodity price factor - obtained from {https://sites.google.com/site/cjsbaumeister/datasets?authuser=0}; 3) GECON: global economic condition indicator (standardised) - obtained from {https://sites.google.com/site/cjsbaumeister/datasets?authuser=0}; 4) S.SH: oil supply shock - obtained from {https://sites.google.com/site/cjsbaumeister/datasets?authuser=0}; 5) OCDSH: oil consumption demand - obtained from {https://sites.google.com/site/cjsbaumeister/datasets?authuser=0}; 6) OIDSH: oil inventory demand- obtained from {https://sites.google.com/site/cjsbaumeister/datasets?authuser=0}; 7) EASH: oil demand shocks driven by global economic activity - obtained from {https://sites.google.com/site/cjsbaumeister/datasets?authuser=0}; 8) GEPU: global economic policy uncertainty index - , a normalised index of the volume of news articles discussing economic policy uncertainty; due to the nonstationarity of the data, obtained from: {https://www.policyuncertainty.com/global_monthly.html} 9) EXPT: Brent spot prices expectations formulated by the U.S. Energy Information Association; 10) SPX - end-of-month data of S&P500 11) SPECUL1: Net position of Money Managers (long-short) for Brent contract - based on the ICE Futures Europe Commitments of Traders Reports ({www.ice.com/marketdata/reports/122}); 12) SPECUL2: Speculation measure analogous to Working's (1960) index, which measures the speculative activity of non-commercial traders in the crude oil market.

Contemporaneous coefficients in the VAR model.

Serie storica del fatturato e indicatori finanziari analizzati tramite intelligenza artificiale.

• Caractéristiques principales : Grand Soissons Agglomération, créée le 1er janvier 2000, est composée de 28 communes et regroupe 52 328 habitants au 31 décembre 2019. Elle dispose notamment des compétences assainissement collectif (AC) et gestion des eaux pluviales urbaines (GEPU), dont le service commun se compose de :