axsym engineering

Scientific theories must be validated against empirical data to determine their accuracy and usefulness. This process is also crucial for proving one theory better than another and thereby advancing knowledge. In contrast, current economic theories, such as Utility Theory, Quantity Theory, and Supply and Demand, cannot be validated. As economic policy is based on unvalidated theories, this leads to policies that inevitably have unintended, harmful consequences. Moreover, the list of harmful consequences (such as the failure to address environmental sustainability, the belief in the need for continuous economic growth, and rising poverty in wealthy nations) is dismissed by those who believe in current economic theories as ill-informed opinion.

At the other end of the scale, in engineering, the concept of validation is extended further with a verification process that assesses the applicability and completeness of theories. By validating models progressively—from individual components to subsystems, and finally to complete systems—engineers can effectively manage and understand complex behaviours. This enables complexity to be built up progressively and by teams of independent researchers. This is demonstrably useful for adapting and controlling the world we live in.

With over 25 years of experience developing models for complex systems in engineering and science, as well as a decade running a business and navigating the British economic system, Will Maybury realised that a more rigorous, evidence-based approach to economic theory was both necessary and achievable. So, for the past five years, Axysm has been applying the same engineering rigour to constructing the outline of an economic model that would be applied in any other branch of applied science. The framework we are developing offers a new lens for studying economic behaviour. It lays the groundwork for progressively building knowledge of economic systems, allowing theories to be developed and validated independently, thereby fostering collaboration and advancing the field.

The new framework, known as Economy Dynamics, can be validated against observed features of the economy, such as the change in rate of inflation and GDP. It is presented as an overview in Paper 00 and as modules addressing different aspects of the economy, from household behaviour to the price of supplies, in Papers 01 to 09. The diagram shows the relationship between these modules. The papers completed to date are summarised below and with a hyperlink to download them. In addition, there are links to essays and a draft book.

An overview of the Economy Dynamics methodology for macroeconomic analysis and forecasting. Existing economic forecasting methods are limited by the range of values held within the historical datasets used to correlate the model. Thus, extrapolating the semi-empirical function introduces numerical uncertainty into the forecast results. Our new approach avoids the limitation of extrapolating semi-empirical functions by using the mathematics of dynamic systems. This will enable forecasts to be validated against metrics at a regional level such as economic output, poverty levels and inflation and against the environmental impact, which is not currently possible.

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Household financial decision-making can be captured from population data by using surrogate modelling methods (including AI). The probability of a given financial action can then be modelled under different household financial circumstances by replaying the surrogate model using the revised household financial circumstances. Termed household income forcing this analytical framework requires the economy to be divided into regions based on cost of supplies and local taxes, and households to be separated into economic groups based on their cost of living and financial circumstances. It tests household financial forcing by calculating the difference between household income and running costs, and it evaluates perceived forcing by comparing household income to that of other households. The set of financial decisions a household can make under a given income forcing can be implemented in economic models by using surrogate models of actual household financial behaviour.

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This paper presents a new approach to modelling the dynamic interactions of consumers and suppliers within an economy. It is developed from the observation that businesses have a pivotal role within the continuous dynamic behaviour of an economy as both consumer and supplier. As all entities within an economy are consumers, it is possible to represent all financial interactions by the consumer relationship to suppliers of goods, services, labour and assets. Termed the macroeconomic primitive, it is represented graphically as a consumer-centred diagram showing the transfer of supplies in exchange for money, revealing that financial transactions are not isolated events but are within a continuum of events. It is also presented as an equation in a general form, defining the interdependency between income and expenditure of any entity within the four consumer types: households, businesses, public purse and charity. The primitive equation can be used to build up the interdependencies of all consumers and suppliers of any economy.

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This paper proposes a new, verifiable model for determining the price of goods and services, addressing limitations of existing supply and demand theories. The model accounts for factors influencing production costs, including environmental impact, and incorporates both individual business decisions and large-scale economic forecasting. A key advantage is its potential for validation against real-world economic data, unlike current theories, leading to more informed and justifiable economic policies. Data collection limitations are acknowledged, but the paper demonstrates the model's conceptual soundness. Ultimately, the model aims to improve economic predictions and separate economic policy from political bias.

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This essay considers why no economic theories can provide public understanding of the constraints on economic policy for addressing climate change and poverty. A new approach to economic research is presented and the potential for creating a framework to enable validation of economic forecasts is discussed. This will enable substantial structural change to the economic system and will open up economics to public questioning and enable public participation in political-economic debate.

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This paper explains why economic theories used by current policymakers are not fit for purpose and how to fix this. It discusses an approach to economic forecasting that can be validated, unlike current theories, separating politics from economic analysis. This will provide vital information to address climate change, mitigate current economic instability and tackle rising poverty by provably determining the changes necessary to current policies.

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This essay explains the problems of the current approach to tax revenue collection and how we create an effective tax system. Namely, wealth is generated by businesses and not households. Indeed, one measure of the size of an economy, known as national income, is the sum of business profits and the sum of wages paid by businesses. This means that whatever part of an economy is taxed, such as income or household consumer spending, the revenue raised must originate from the wealth generated by businesses, otherwise this drives wealth inequality. A new simple, equitable, self-regulating approach to tax revenue is defined, and a gradual and robust mechanism for implementation is outlined to ensure a stable transition. Crucially, this new system will enable governments to effectively regulate businesses, which is vital if we are to address the current global crises from global warming to the risk of job losses due to the advancement of technology.

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Economic theories used by policymakers are not fit for purpose. They claim to 'follow the science' but in truth align more closely to a belief system than to scientific methodology. So, if you are scientifically minded you may well despair at the disastrous consequences, to people's lives and to the environment, of current economic thinking. Yet, what is the alternative?

The 'Economy Dynamics' project will create an approach to understanding economy behaviour based on scientific methodology, which includes creating a provable economic theory. Given that the discipline of economics needs a complete overhaul, it's an ambitious project and includes: establishing a new technical language without inherent concept bias due to the use of unnecessary abstract terminology; implementing a framework for understanding dynamic systems, such as those used in science and engineering; and crucially, instilling a different philosophy of knowledge that demands theories to be provable.

As there are no forums or journals in economics to discuss or publish innovation in economic theory, I have published my papers on this webpage and I am writing a book (with draft released on Patreon). The book is intended to convince a general audience that, by following a mechanistic approach to studying economy behaviour, we can prove economic theories. For your support, you will have exclusive access to all works before release, including draft chapters of the book. Let's bring economics into the 21st century.

Patreon Project: Provable Economic Theory

A new approach to the structure of software architecture to integrate analysis software and data in an adaptable and easy to upgrade framework is presented in the Teclab Series publications below. The new approach enables an analysts to select the simulation type, within a single analytical environment, and have full control over the algorithms and options used, without any duplication of software or methods across a department or company. The framework is truly modular, allowing alternative analysis methods to be interchangeable within the simulation, selected at set-up by the analyst. The architecture structure avoids the common problem of analytical tools becoming fragmented and prevents upgrade requirements encountering a dead-end. Implementing our architecture ensures there is no duplication of effort in an analytical processes between staff and that all analysts are working with the latest datasets, reduces data handling errors and reduces analysis turnaround times.