As the Financial Times’ economics columnist and podcast host, Keynes specializes in translating complex policy shifts into actionable business insights. Her work bridges academic research and real-world impacts, with particular focus on:
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We’ve followed Soumaya Keynes’s evolution from policy analyst to one of the UK’s most influential economics journalists. After earning first-class honors in economics at Cambridge, she began her career at HM Treasury and the Institute for Fiscal Studies, where she honed her ability to translate complex fiscal concepts into actionable insights. Her 2014 transition to The Economist marked a pivotal shift toward public-facing economic analysis, where she spent eight years dissecting Brexit’s ripple effects and Trump-era trade wars.
Keynes joined the Financial Times in 2023 as part of their podcasting expansion, bringing her signature blend of academic rigor and conversational clarity to audio formats. Her current work focuses on macroeconomic trends, international trade frameworks, and the societal impacts of economic policy decisions.
This groundbreaking investigation revealed systemic gender barriers in economics, showing that only 15-20% of senior economists in Western institutions were women. Keynes combined longitudinal workforce data with personal narratives, exposing how unconscious bias and mentorship gaps create attrition pipelines. The article became a reference point for institutional reforms, cited in OECD policy briefs and university hiring initiatives. Her analysis of “leaky pipeline” dynamics—where women abandon economics careers at twice the rate of male peers—sparked industry-wide conversations about retention strategies.
Through granular analysis of UK customs data, Keynes quantified how post-Brexit trade barriers disproportionately affected SMEs. She tracked a 34% increase in administrative costs for businesses with under 50 employees, contrasted with only 8% for multinationals. The piece featured first-person accounts from manufacturers facing supply chain chaos, illustrating how regulatory complexity stifles innovation. Policymakers referenced this work during debates about simplifying trade documentation for SMEs.
Keynes transformed a seasonal topic into a macroeconomic case study, analyzing how inflation and labor shortages reshaped holiday spending. She identified a 19% surge in “experiential gift” purchases versus traditional retail, linking it to pandemic-era behavioral shifts. The article’s supply chain diagrams and consumer sentiment heatmaps became widely shared visual tools during the 2022 holiday season.
Pitch frameworks that connect technical trade details to real-world business outcomes. Keynes’ 2023 FT podcast episode with Jason Furman on US debt ceilings demonstrated her ability to make bond yield curves accessible through retailer case studies. Successful angles might include: “How EU carbon border taxes impact mid-sized automotive suppliers” or “ASEAN trade pacts reshaping textile industry logistics.”
Propose stories that quantify labor market shifts through sector-specific lenses. Her 2024 analysis of UK nursing strikes combined NHS payroll data with regional cost-of-living variations. Compelling pitches could explore: “AI adoption’s differential impact on male vs female-dominated professions” or “Apprenticeship tax credit utilization across manufacturing subsectors.”
Highlight discrepancies between legislative intent and ground-level execution. Keynes’ 2021 investigation into Madagascar’s customs fraud combined whistleblower interviews with customs declaration audits. Strong pitches might examine: “Post-Brexit food safety inspections backlog” or “Solar panel import tariff enforcement gaps.”
“Keynes possesses that rare ability to make spreadsheet cells tell human stories.” – Martin Wolf, FT Chief Economics Commentator
At PressContact, we aim to help you discover the most relevant journalists for your PR efforts. If you're looking to pitch to more journalists who write on Economics, here are some other real estate journalist profiles you may find relevant:
