China announced record export numbers for 2025, a year when US President Donald Trump's tariffs and trade policy caused turmoil in the global economy. Beijing on Wednesday reported the world's largest-ever trade surplus - the value of goods and services sold overseas compared to its imports - at $1.19tn (£890bn). It's the first time China's full-year trade surplus has passed $1tn, beating 2024's record figure of $993bn. China's monthly export surpluses passed $100bn seven times last year - a sign that Trump's tariff campaign have barely affected its overall trade with the rest of the world. Trade with the US did weaken, but this was made up for by a rise in Chinese exports elsewhere, especially to South East Asia, Africa and Latin America.

The vast datacentres required are so expensive that many are financed by debt secured against future revenue. The vast datacentres required are so expensive that many are financed by debt secured against future revenue. Sun 4 Jan 2026 07.18 ESTLast modified on Sun 4 Jan 2026 08.47 EST The US dictionary Merriam-Websterâ s word of the year for 2025 was â slopâ, which it defines as â digital content of low quality that is produced, usually in quantity, by means of artificial intelligenceâ . The choice underlined the fact that while AI is being widely embraced, not least by corporate bosses keen to cut payroll costs, its downsides are also becoming obvious. In 2026, a reckoning with reality for AI represents a growing economic risk.

B rendan Foody is 22 years old and runs a company worth billions. This August, I met the young CEO in a glass conference room overlooking the San Francisco Bay. While his peers are searching for their first jobs, Foody is pursuing a " master plan," as he calls it, to upend the global labor market. His start-up, Mercor, offers an AI-powered hiring platform: Bots weed through résumés, and even conduct interviews. In the next five years, Foody told me, AI could automate 50 percent of the tasks that people do today.

Global growth is holding up better than expected as an artificial intelligence (AI) investment boom helps offset some of the shock from United States tariff hikes, according to the Organisation for Economic Co-operation and Development (OECD). The Paris-based organisation, however, warned on Tuesday that global growth was vulnerable to any new outbreak of trade tensions, while investor optimism about AI could trigger a stock market correction if expectations are not met. It predicted a rebound to 3.1 percent in 2027. OECD head Mathias Cormann said the trade shocks triggered by US President Donald Trump's tariff hikes had so far proved relatively mild, but added their costs were likely to rise. "The full effects of those higher tariffs since the start of the year will become clearer as firms run down the inventories that they built up," he told a press conference.

The growth of artificial intelligence (AI) may eventually lead to fewer entry-level graduates being hired, the boss of accountancy giant PwC has told the BBC. However, global chairman Mohamed Kande said AI was not behind recent job cuts at the firm, adding that the company actually needed to hire hundreds of new AI engineers but was struggling to find them. But some observers say the technology itself threatens thousands of junior jobs across the professional services industry. Speaking on the sidelines of a business summit in Singapore, Mr Kande also said big changes in the global economy, such as US President Donald Trump's sweeping tariffs, had been good for the firm's consulting business. He also addressed the company's suspension in China last year over its work on the collapsed property giant Evergrande, promising that the same mistakes would not happen again.

China will soon have a new Five Year Plan. Here's how they have changed the world so far China's top leaders are gathering in Beijing this week to decide on the country's key goals and aspirations for the rest of the decade. Every year or so, the country's highest political body, the Central Committee of the Chinese Communist Party, convenes for a week of meetings, also known as a Plenum. What it decides at this one will eventually form the basis of China's next Five Year Plan - the blueprint that the world's second largest economy will follow between 2026 and 2030. The full plan won't come until next year, but officials are likely to hint at its contents on Wednesday and have previously given more details within a week of that.

The UK is forecast to be the second-fastest growing of the world's most advanced economies this year and next, according to new projections from the International Monetary Fund (IMF). The rates of growth remain modest at 1.3% for both years, but that outperforms the other G7 economies apart from the US, in a torrid year of trade and geopolitical tensions. However, UK inflation is set to rise to the highest in the G7 in 2025 and 2026, the IMF predicts, driven by larger energy and utility bills. UK inflation is forecast to average 3.4% this year and 2.5% in 2026 but the IMF says this will be temporary, and fall to 2% by the end of next year. The G7 are seven advanced economies - the US, UK, France, Germany, Italy, Canada and Japan - but the group doesn't include fast-growing economies such as China and India.

Jointly modeling and forecasting economic and financial variables across a large set of countries has long been a significant challenge. Two primary approaches have been utilized to address this issue: the vector autoregressive model with exogenous variables (VARX) and the matrix autoregression (MAR). The VARX model captures domestic dependencies, but treats variables exogenous to represent global factors driven by international trade. In contrast, the MAR model simultaneously considers variables from multiple countries but ignores the trade network. In this paper, we propose an extension of the MAR model that achieves these two aims at once, i.e., studying both international dependencies and the impact of the trade network on the global economy. Additionally, we introduce a sparse component to the model to differentiate between systematic and idiosyncratic cross-predictability. To estimate the model parameters, we propose both a likelihood estimation method and a bias-corrected alternating minimization version. We provide theoretical and empirical analyses of the model's properties, alongside presenting intriguing economic insights derived from our findings.

In 2024, both cutting-edge technology and the companies controlling it grew increasingly powerful, provoking euphoric wonderment and existential dread. Companies like Nvidia and Alphabet soared in value, fueled by expectations that artificial intelligence (AI) will become a cornerstone of modern life. While those grand visions are still far into the future, tech undeniably shaped markets, warfare, elections, climate, and daily life this year. Perhaps technology's biggest impact this year was on the global economy. The so-called Magnificent Seven--the stocks of Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla--thrived in large part because of the AI boom, propelling the S&P 500 to new highs.

The sectors of the global economy most heavily exposed to artificial intelligence (AI) are witnessing a marked productivity increase and command a significant wage premium, according to a report. Boosting hopes that AI might help lift the global economy out of a 15-year, low-growth trough, a PwC study found productivity growth was almost five times as rapid in parts of the economy where AI penetration was highest than in less exposed sectors. PwC said that in the UK, one of the 15 countries covered by the report, job postings that require AI skills were growing 3.6 times faster relative to all job listings. On average, UK employers were willing to pay a 14% wage premium for jobs that require AI skills, with the legal and information technology sectors experiencing the highest premiums. The uptick in productivity in sectors more exposed to AI – such as financial services, information technology, and professional services – was marginally higher in the UK than the global average.