"I found creative ways to navigate new challenges"

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“I found creative ways to navigate new challenges”

Reflections on a Master’s at King’s College London and ESCoE

After working as an Economist in the Civil Service for six years, Anisha was already well-versed in data analysis and applying economic theory. We caught up with Anisha at the end of her Master’s in Economics and Policy at King’s College London, as she returned to work at the Treasury. We spoke about her dissertation in collaboration with ESCoE, what she learnt from the project and the importance of economic measurement.

Anisha with her poster at ESCoE’s early career and PhD workshop in November 2024

Tell us about your master’s dissertation

Having worked on productivity for the two years prior to my masters, I wanted to focus on something relevant to that field. Management practices are a significant part of the literature on the productivity puzzle, and I also wanted to incorporate technology adoption and diffusion into the question; I was intrigued by the fact that higher technology adoption did not always necessarily lead to higher productivity outcomes in practice.

My dissertation title was: Can AI Speak to the Manager? Adaptable management culture in the face of a technology shock. The key hypothesis was that firms with more adaptable management can take greater productivity benefit from technology adoption as mitigation against a negative exogenous productivity shock. This used the Management and Expectations Survey (MES) merged with the Annual Business Survey (ABS) to look at the impact of increased pandemic-induced technology investment in 2020 on short-run productivity, and how impacts diverged between firms with more and less adaptable managers.

The paper compared two models – a simple interaction OLS model and a Fixed Effects model. The results across both models found that an increase in technology without adaptable management caused a reduction in short-run productivity, but when coupled with adaptable management this resulted in positive short-run productivity outcomes. This was an interesting result, as it stressed the importance of managers being adaptable and open to change when adopting new technologies and gaining quick productivity benefit from this. In theory, this could be because more adaptable managers are more open to making use of these technologies, training their staff, and communicating changes effectively. 

Why did you decide to do your master’s dissertation through ESCoE?

I was already familiar with ESCoE’s work, having attended the annual conference in King’s College London the previous year. I think that measurement of the economy is extremely important, and I enjoy getting involved in debates on the best ways to go about these challenges. There are many areas of the current economy that are difficult to measure, and the ESCoE conference did a great job of bringing together economists and statisticians from all areas to discuss these issues. I really wanted to capture the conversations from the previous conference in my dissertation, and I was very lucky that ESCoE was also connected to the MES dataset I wanted to use. 

What did you enjoy about working with ESCoE?

I had a great time working with ESCoE! This 2024 annual conference in Manchester was a really great way to test my ideas and connect with other economists working on similar issues. Rebecca Riley was really helpful in connecting me to other researchers and bringing me into the MES project. I was relatively fresh to academic writing, having only worked as a professional economist in the Civil Service since 2018, so I learnt a lot from everyone. Aside from learning, ESCoE had a welcoming atmosphere, and I felt confident pushing forward with my ideas there. I felt really inspired by all the research and analysis that others were doing and I enjoyed being around such creative thinking.

What did you learn from working on the project?

There were two main areas in this project that I learnt a lot from. I have done a lot of data analysis in my career, and it is something I enjoy. But scoping a research question based on all the data I had available, and narrowing this down into something with useful conclusions, was something new and exciting. Working on my question by myself and solving problems that I hadn’t expected taught me a lot about finding creative ways to navigate new challenges. The actual writing of the dissertation and ensuring I captured all the assumptions and caveats was a new challenge. I often had to take a step back to sense check my analysis during this process, when I felt like I was getting too close to the question.

Why is economic measurement so important?

Much of practical economics and application of economic theory cannot be done without data – and many people underestimate the challenge in managing data accurately. Particularly when looking at the macroeconomy, there is no way of capturing all the activity – where surveys are often self-reported and not all behaviour can be tracked. However, this data still underpins many decisions – at the national but also at the individual level.

When the economy isn’t measured accurately, the conclusions brought out from analysis using that data can be impactful but potentially damaging – particularly when there are unobserved factors at play. We saw this during the COVID-19 pandemic, where the number of workers was difficult to measure as many of them were on furlough. In turn, this meant that productivity measured by output per worker was difficult to measure. This data was used in my dissertation, and an assumption had to be made to get around this.

Why is your research important?

There has been a lot of discourse on the drivers of productivity, and management practices in particular. I’ve also seen a lot of discourse around the fact that technology investment does not always necessarily lead to positive productivity outcomes. I wanted to exploit the widespread increase in technology during the Covid pandemic to see how better management may take effect here, and how this may allow the benefits of technology to be felt at the firm level. Although this analysis is subject to many assumptions, and data restrictions mean that the analysis is limited to the short term, this is helpful if only for comparison between less and more adaptable firms and how they can respond to technology changes in the short-run. This analysis was focused on the Covid pandemic period, in 2019 and 2020. However, these findings are also useful now, particularly in the wake of the AI revolution – where more adaptable management can allow firms to gain productivity benefit from these wider technological improvements.

What would you say to another masters/PhD student thinking of working with ESCoE?

Definitely do it! It’s a really supportive environment. Although I’ve returned to the Treasury, I’m really keen to continue to be connected with ESCoE going forward. The research sharing is invaluable and the analysis that researchers do is creative and interesting. Currently, there is also an opportunity to apply for ESCoE’s Master’s Dissertation Programme 2025.

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