Backstory
Personal Context
I'll cut to the chase. I'm neither economist nor historian. I'm a full-time carer for my disabled mum - and have been for many years. In what feels like a lifetime ago, I worked in information technology on large-scale accounting and systems integration projects; enterprise resource planning (ERP) to use the lingo. Over time I worked for a Japanese sogo-shosha, a big-four professional services firm, and a major energy transmission company.
My formal education includes an undergraduate degree in Business & Economics (BA) and a postgraduate degree in Computer Security, Forensics & Risk Management (MSc). But the work presented here is primarily the result of long-term independent study, experimentation, and sustained curiosity about how a modern monetary system actually functions.
An Email Out of the Blue
Back in the early 2000s I opened a self-invested private pension (SIPP). I made regular, albeit small, contributions for a few years before life moved in other directions and the account became dormant. Then, in the spring of 2016, I received an email from the SIPP provider: "Your SIPP has a high proportion held as cash." They continued: "... This might be part of your strategy, but it can drag on returns." Strategy! I didn't know whether to laugh or cry. What strategy?
Initially surprised to have heard from them at all, I ignored it. A high proportion of not much is still not much. But it gnawed at me. The years were rolling by. My life as a full-time carer is meaningful, but financially modest. I should probably do something.
It was obvious. I would invest in a government bond fund. The thing is, it suddenly didn't feel obvious. Post-2008, nothing felt entirely obvious anymore. Why were "safe" UK government bonds experiencing such volatility? Why did markets behave the way they did after the financial crisis? More fundamentally: What is this system?
Learning By Reading
I dusted off my old textbooks. Undergraduate economics had taught me something - mostly a generally received narrative to accompany an often disorientating financial news cycle. I increasingly felt that system mechanics remained obscure. Weeks turned into months of reading economic blogs and other published materials. A blog pointed me to a paper written by economist Robert J. Shiller and the role of narratives in economic fluctuations. Interesting - but not where I should begin.
Then, in late 2016, while browsing Amazon, I came across a book with an extraordinary title: Monetary Economics: An Integrated Approach to Credit, Money, Income, Production and Wealth by Wynne Godley and Marc Lavoie. I was intrigued. I read a sample: Balance Sheets, Transaction Matrices and the Monetary Circuit. I was sold! But it was expensive. I hummed and harred for a week before making my purchase. I had to have it. What attracted me wasn't ideology or prediction, but structure. The idea that monetary systems could be understood through interconnected balance sheets and institutional flows felt intuitively powerful - perhaps because of my earlier experience working with large accounting and enterprise systems.
In later years, books such as Adam Tooze's Crashed and Christine Desan's Making Money helped me to appreciate the historical and institutional dimension of the project. Desan's work in particular helped me appreciate that monetary systems are not merely collections of markets, but deeply historical systems shaped by law, politics and institutions. Desan's research has the power to historicise Godley and Lavoie's meticulous monetary models. Over time, I became increasingly interested in the operational mechanics of the UK monetary system itself: reserves, taxation, debt issuance, settlement flows, portfolio adjustment, and the role of government bonds as institutional assets within a modern financial system.
Learning By Doing
The reading alone was fascinating. But I wanted to build something too. That led first to small exploratory agent-based (computational) models, and eventually to the broader Gilt Edged Models (GEM) project and the latest model, ABMLP-X. The model is inspired by Wynne Godley's stock-flow consistent (SFC) approach and focuses heavily on balance-sheet interaction, settlement-constrained flows and operational adjustment processes. GEM began with a simple motivation: curiosity. The goal is to understand, experiment, and reflect - not to optimise for either popularity or institutional approval. GEM is open‑ended by design - there is no fixed end goal for the evolution of the latest model.
More recently, the project has expanded into Gilt Edged Analysis (GEA): a parallel research effort focused on synthetic operational datasets, exploratory time-series analysis, and the study of delayed adjustment dynamics within the UK government monetary system.
Continuing Education
This project is also a form of continuing education. I continue to study monetary economics, data analysis, and financial systems through independent research, formal online courses, and the practical process of building models, synthetic datasets, and exploratory analytical tools.
The objective is not to build a perfect representation of reality. George Box said, "all models are wrong, but some are useful". The aim is to keep learning. The models and datasets developed are best understood as bounded research tools - ways that I hope will help me to think more clearly about a complex and evolving system.
Consultancy
Alongside the intellectual curiosity that drives the project, I also hope that the practical skills developed through this ongoing work - including data analysis, synthetic dataset construction, modelling, and operational research - may evolve into forms of independent consultancy or analytical work connected to financial systems and monetary operations.
Feel free to get in touch. Head straight to GEM.