The spread of the global financial crisis (GFC) from one country to another over days, weeks and months can now unfold before your eyes thanks to a ground-breaking network model.
The model, which tracks how the financial crisis moved and proliferated like a virus through the governments and banks of 18 countries between 2006 and 2015, has been developed by a research team at the University of Melbourne’s Faculty of Business and Economics.
Dr Matthew Greenwood-Nimmo, who developed the model with the Melbourne Institute’s Dr Viet Nguyen and PhD student Jingong Huang, says this is the first time such a detailed network model has been developed.
The model’s nine-year timeframe covers a key period in modern economic history, starting two years before the catastrophic collapse of Lehman Brothers – once the United States’ fourth largest investment bank – and ending as the Greek government missed its deadline to repay a multimillion dollar debt to the International Monetary Fund.
Supported by a 2015 Australian Research Council Discovery Early Career Research Award, the model forms the core of Dr Greenwood-Nimmo’s ambitious research into the transmission of shocks in the global economy.
“Many of the existing network models consider only risk transmission between banks or between sovereigns, not both,” he says.
“Small, tightly focused models are great for studying specific aspects of a crisis but you need to build global models to get the big picture.
“By focusing on a single country and the events that led to the crisis in that country, you may miss the links to other countries and their institutions.
“Our model has much broader coverage than most. We set out from the beginning to build a sophisticated global model to capture the links between some of Europe’s biggest players – the UK, Ireland, Portugal, Italy and Germany – as well as Scandinavia, the US, China, Japan, Russia and Australia.”
Dr Greenwood-Nimmo says he hopes the model will provide politicians and regulators with a deeper understanding of how crises spread, ensuring they are better prepared in future to break the chain of events caused by bank failures or the collapse of asset market bubbles.
“A lot of economic policy evolves in response to the last crisis rather than in anticipation of the next. For example, after the risks posed by real estate bubbles became evident, a number of countries implemented policies to prevent excessive growth in mortgage debt, such as capping loan-to-value ratios,” he says.
“But banks profit by driving innovation and so when regulation erodes profits in one part of their business, they will develop products to target new profit opportunities. As a result, the next crisis is likely to be caused by a different set of factors.
“The challenge is identifying where the big risks to financial stability are so that regulators can prioritise their efforts.”
Dr Greenwood-Nimmo says the model also identifies links between countries, for example Australia’s dependence on the economic and financial conditions in China.
“If there was an economic crisis in Russia, we probably wouldn’t need to be too worried about the impact on our economy,” he says.
“However, if that same crisis occurred in China it would be a different story.”
Dr Greenwood-Nimmo says Australian prosperity depends on China, and changes in the Chinese economic and financial landscape would have significant implications.
The increasing private ownership of banks in China, where state-ownership has traditionally been the norm, is one such change already under way.
“The credit risk of Chinese state-owned banks has typically been low because they are backed by the government,” he says.
“As private ownership grows, Australian businesses may need to accommodate a higher degree of counterparty risk when dealing with Chinese firms in the future.”
The model was created using nine years of daily data on bank and sovereign credit default swaps, akin to insurance contracts which protect investors against losses in the event that a bank or a government defaults on its debts.
Soon to be publicly available, users will be able to access high resolution network graphics showing the key linkages in the global financial system and how they change over time.
The results can be filtered by date and country to provide a personalised experience.
“We hope that by providing an easy-to-use interface which doesn’t require any formal training in economics and finance, anyone who is interested in our model will be able to explore its results and look into the issues that are specifically relevant to them,” Dr Greenwood-Nimmo says.
“We’d really like to see students engaging with our research because understanding historical crises and attempting to prevent future crises is one of the defining challenges of contemporary economics.”
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