At long last, economists appreciate that private debt was the catalyst for the crisis

This month saw the tenth anniversary of the collapse of Lehman Brothers, a collapse which precipitated one of the only two global financial crises of the past 150 years.

The late 2000s and early 1930s were the only periods in time when capitalism itself has trembled on the edge of the precipice.

It was in November 2008 that the Queen put her famous question about the crisis to the academics of the London School of Economics: “Why did nobody notice it?”

The answer is simple. In the models of the economy at the time, finance did not matter.

Mainstream economists did not notice the massive financial imbalances in the economy, because in their models, any problems that might link to these imbalances were assumed away.

To be of any use, all scientific models have to make simplifications of reality. But orthodox macroeconomics took a step too far. It assumed that the workings of the whole economy could be explained by analysing the theoretical behaviour of just a single decision maker. In the jargon, this is the “representative agent”.

The agent is a device which economists used to model the economy. It was extremely clever, and could solve hard mathematical problems – calculating how the decisions of average consumers and companies would affect the macroeconomy.

These kinds of models go by the splendid name of “dynamic stochastic general equilibrium models”, or just plain “DSGE” to their friends. But at its most basic, the problem with such economic models was that there was only one decision maker in them.

Having just two, a “creditor” and a “debtor” for example, would have helped a lot.

Over the past decade, economists have been scrambling to incorporate other financial factors into their models, such as household debt. Key contributions to this research are discussed in the latest issue of the Journal of Economic Perspectives.

Bizarre though they may seem, DSGE models now finally recognise the potential importance of household finance in causing crashes.

A particularly interesting paper in the journal is by Atif Mian of Princeton and Amir Sufi of Chicago. Their focus is considerably wider than the crisis of the late 2000s in the United States. They quote empirical studies across some 50 countries with data going back to the 1960s. They found that a rise in household debt relative to the size of the economy is a good predictor of whether GDP growth will slow down.

Rickard Nyman, a computer scientist at UCL, and I applied machine learning algorithms to data on both public and private (households and commercial companies) sector debt in both the UK and America. We find that the recession of 2008 could have been predicted in the middle of 2007.

Perhaps the most striking result is that public sector debt played little role in causing the crisis. The driving force was the very high levels of private sector debt.

A critic might say that this is simply a case of generals fighting the last war.

True, we don’t know whether a completely different nasty event lies around the corner. But at long last, economists appreciate the fundamental importance of debt and finance in Western economies.

Paul Ormerod 

As published in City AM Wednesday 26th September 2018

Image: Her Majesty The Queen by UK Home Office on Flickr licensed under CC-BY 2.0

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ALEX O’BYRNE

Associate

e: aobyrne@volterra.co.uk
t: +44 020 8878 6333

Alex O’Byrne, Associate at Volterra, is an experienced economic consultant specialising in economic, health and social impact, economic strategy, project appraisal and socio-economic planning matters.

Alex has led the socio-economic and health assessments of some of the most high profile developments across the UK, including Battersea Power Station, Olympia London, London Resort, MSG Sphere and Westfield. He has significant experience inputting to EIAs and s106 discussions as well as drafting economic statements, employment and skills strategies and affordable workspace strategies.

Alex is also experienced at economic appraisal for infrastructure. He was project manager of the economic appraisal for the City Centre to Mangere Light Rail in Auckland. He also led the economic and financial appraisals of the third tranche of the Transport Access Program for Transport for New South Wales, in which Alex developed and employed innovative methodological approaches to better capture benefits for individuals with reduced mobility.

He is interested in the limitations of current appraisal methodologies and ways of improving economic and health analysis to ensure it is accessible to as many people as possible. To this end, Alex recognises the importance of transparent and simple to understand analysis and ensuring all work is supported by a robust narrative.

Alex holds a BSc (Hons) in Economics from the University of Manchester and he was a member of the first cohort of the Mayor’s Infrastructure Young Professionals Panel.

ELLIE EVANS

Senior Partner

e: eevans@volterra.co.uk
t: +44 020 8878 6333

Ellie is a partner at Volterra, specialising in the economic impact of developments and proposals, and manages many of the company’s projects on economic impact, regeneration, transport and development.

With thirteen years experience at Volterra delivering high quality projects to clients across the public and private sector, Ellie has expertise in developing methods of estimating economic impact where complex issues exist with regards to deadweight, displacement and additionality.

Ellie has significant experience in estimating the economic impact across all types of property development including residential, leisure, office and mixed use schemes.

Project management of recent high profile schemes include the luxury hotel London Peninsula, Battersea Power Station and the Nova scheme at London Victoria. Ellie has also led studies across the country estimating the economic and regeneration impact of proposed transport investments, including studies on HS2 and Crossrail.

Ellie holds a degree in Mathematics and Economics from the University of Cambridge.