How do weather shocks affect labor productivity? Evidence from the UKHLS Interviewers Fieldwork
Abstract: I study how weather affects individual-level labor productivity in a high-income, service-sector context. Using detailed panel data on UKHLS survey interviewers linked to weather data, I examine how variation in weather conditions influences their work output. My findings show that extreme temperatures significantly reduce workers' productivity both on the extensive and intensive margins: on hotter days, interviewers are more likely to be absent, complete fewer interviews, work shorter hours, and collect more low-quality responses. Weather shocks also generate negative effects, suggesting that workers respond not only to temperature itself but also to unexpected deviations from historical conditions. Importantly, lagged models show significant compensating reallocation: interviewer productivity falls on hot days, but increases on subsequent mild days, partially offsetting lost work. Additional evidence from variance decompositions and web interviewing suggests that temperature effects are driven mostly by interviewers rather than respondents.
Winter Is Coming: Can a Labelled Cash Transfer Increase Household Fuel Spending and Well-being?
(Best Paper Award for Rising Star at the International Behavioural Public Policy Conference)
Abstract: The Winter Fuel Payment (WFP) is an annual cash transfer paid to all UK individuals above the female state pension age. I examine whether the label of this transfer increases households' fuel spending and, consequently, improves health status and home temperature. Using data from the UK Household Longitudinal Survey (2009–2017) and implementing a Multi-Cutoff Regression Discontinuity Design, I find that WFP-eligible households increase their annual fuel spending by 6.4% compared to the non-eligible group. This effect is particularly driven by unhealthy individuals and individuals not on benefits, who have to actively apply for the payment and, thus being more in contact with the label. Linkage with temperature data also shows that the effect is more pronounced during milder winter conditions when heating is more discretionary, as indicated by significant increases in home temperature.
AI Adoption and Workforce Change in SMEs (link here)
with David Bharier and Ben Etheridge
Abstract: This paper investigates Artificial Intelligence (AI) adoption and its labour market consequences among UK small and medium enterprises, using novel data from the British Chambers of Commerce Business Outlook Survey, collected in early 2026. AI adoption is increasingly widespread, with over half of responding firms currently using AI, up from around a third in 2025. Most users rely on generic tools such as ChatGPT or Copilot, but around one in ten firms have adopted bespoke AI implementations. We find that bespoke adoption in particular is associated with a coherent bundle of workforce adjustment. Approximately one-fifth of bespoke users report staffing reductions attributable to AI, and bespoke adopters are roughly three times more likely to have restructured job roles. Restructuring is in turn strongly associated with headcount reductions and shifts in skills requirements. Surprisingly, firms investing in AI-related training are significantly more likely to anticipate headcount reductions than those not investing in training. We also find that current AI users are substantially more optimistic about future productivity gains than non-users. Our findings provide a novel firm-level picture of how SMEs are reorganising work, adjusting workforces, and investing in skills in response to AI.
Outdoor Temperature and Cognitive Performance: Evidence from the UK
Abstract: I analyze the impact of temperature on cognition using the cognitive ability measures from the UKHLS, which provide a clean measure of mental proficiency. To answer my research question I rely on linear and non-linear empirical specifications. My non-linear specification shows the effect of daily temperature falling in a certain compared to a (moderate) baseline bin that is omitted in the regression. My linear specification quantifies the effect of an increase or decrease in temperature after a certain threshold. I also study the cumulative effect of temperature, that is whether a sequence of hot and cold days yields a larger effect compared to an isolated day of extreme weather. Finally, I perform heterogeneity analysis, across a wide range of subgroups, splitting the sample by age, gender, income and health status.
Examining the health drivers of older workers’ labour market participation and job search decisions.
with Alex Clymo, Carlos Carrilo-Tudella, Francesca Salvati and David Zentler-Munro