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The UK government borrows to fund day-to-day spending as well as long-term infrastructure projects.

The UK government borrowed slightly less than expected in June, according to official figures published as new prime minister Andy Burnham began setting out measures to cut living costs for households. Borrowing - the difference between spending and income from taxes - was £16bn last month, £7.9bn lower than at the same point last year, the Office for National Statistics (ONS) said. Separate figures also showed the unemployment rate remained unchanged between March and May, with the UK statistics body saying the labour market was relatively steady. However while the borrowing figures were better than forecast, the UK is still carrying significant public debt. 'I made £100,000 of TikTok sales in one day': The business of live shopping The Papers: 'Burnham era begins' and'King Kev' Your tips on getting a fussy child to eat, and six recipes they'll love Mum's'tears of joy' as daughter released from hospital What will Andy Burnham's first day be like?

Russians are returning to cash, as mobile internet shutdowns disrupt card payments, and more businesses seek to dodge tax under mounting financial pressure more than four years into the war with Ukraine. Russia has added 1.56tn roubles (£14.8bn; The spike comes amid a wave of Ukrainian drone attacks, which have repeatedly led the Kremlin to shut down mobile internet across large swathes of the country, leaving many unable to pay by card. The government says the aim of the shutdowns is to counter the drone strikes. Having cash on hand gives you some sense of control and security, one woman in Moscow told the BBC on condition of anonymity.

Software programmers, accountants, receptionists and advertising and marketing professionals are among the most at risk of losing their jobs to AI, according to a government report. Software programmers, accountants, receptionists and advertising and marketing professionals are among the most at risk of losing their jobs to AI, according to a government report. Artificial intelligence has yet to cause widespread job losses but the federal government has warned that telemarketers, advertising staff and accountants are among the occupations "most exposed" to being replaced by the technology. According to a first-of-its-kind national report, people in the more exposed occupations are more likely to be women and have university qualifications. They include clerks, retail managers, software programmers, accountants, receptionists and advertising and marketing professionals, according to data from Jobs and Skills Australia (JSA) contained in the AI and Employment in Australia report. Sign up for the Breaking News Australia email Jobs deemed as the "least exposed" to AI displacement are filled by those with the lowest level of university qualifications and the highest level of vocational training, including tradespeople and aged care workers.

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It will be updated monthly. California has launched a new portal, which tracks AI-related job losses in the state. According to the office of California Governor Gavin Newsom, it's meant to serve as an early warning system for widespread job cuts due to artificial intelligence, allowing the government to proactively determine where interventions may be needed the most. The website says Newsom's office worked with the California Employment Development Department, as well as with the California Policy Lab at the University of California to conduct research to measure AI-related job losses. They use Unemployment Insurance claims data combined with AI exposure measures to come up with the figures in the tracker.

This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury market and bonds issued by the European Central Bank (ECB). To enhance predictive performance, macroeconomic variables are incorporated. The findings for both markets are separately analyzed and compared. To this end, we propose a robust model evaluation framework combining statistical accuracy metrics - such as RMSE, MAE, and directional accuracy - with the economic relevance of a quantitative bond trading strategy. Results show that NNs consistently outperform traditional models in both forecasting accuracy and portfolio performance. For the U.S., the most effective approach is a direct-forecasting NN that incorporates DNS factors to reduce the dimensionality of zero-rate data and an Autoencoder (AE) to extract macroeconomic features, while for Europe, the optimal model is a factor-based NN using PCA-derived zero-rate factors without the integration of macroeconomic variables. Overall, the paper demonstrates how combining traditional modeling approaches with modern ML techniques and evaluation can improve yield curve forecasts and support applications in fixed-income portfolio construction.

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Who Is the Real Kevin Warsh? Before the new Fed chairman got the job, he intimated that the central bank could cut interest rates, but last week he assumed the role of an inflation hawk. Kevin Warsh, the Republican financier who recently took over as the chairman of the Federal Reserve, holds economic views that could, kindly, be described as adaptable. Last summer, he said that the Fed had committed "the greatest mistake in macroeconomic policy in forty-five years" by allowing inflation to surge post- . This statement marked out Warsh as an inflation hawk, but late last year, after his name had surfaced as a possible candidate to succeed Jerome Powell as chair of the central bank, Warsh publicly argued that A.I. could generate big gains in productivity and be "structurally disinflationary."