The title of this post is taken from an article by Paul Krugman (Nobel prize winning economist) in the New York Times of the 18th of April 2013. And it really is a good question that sums up the significance of the information quality problems that have emerged in an economic model which has been used to guide the actions of governments and non-governmental organisations in response to the global financial crisis.
Krugman’s article summarises the background very succinctly but we’ll summarise it again here:
- In 2010 two Harvard economists, who between them had served with and advised a number of governmental and supra-governmental organisations, produced a paper that argued that there was a key threshold above which Government debt became unsustainable and had a negative effect on economic growth. That threshold was 90%.
- That threshold was used as a key benchmark to inform policies for dealing with government debt crises in Europe and elsewhere. It became an article of faith (despite some economists questioning the causation/correlation relationship being argued). The official line being taken with countries with sovereign debt challenges was that austerity was required to reduce debt below 90% to prevent a fall off in growth – and there was academic research to prove it.
- However other researchers struggled to replicate the results presented in the original paper – decline in growth was never as severe and the causal relationship was never as definitive. Eventually one researcher got access to the original spreadsheet and uncovered methodological issues and fundamental calculation errors, including a formula calculating an average that left out data points (5 countries were omitted).
The reanalysis of the spreadsheet data, correcting for methodology issues and for calculation errors found no average negative growth above the 90% threshold. According to author Mike Konzcal on economics blog NextNewDeal.net:
They find "the average real GDP growth rate for countries carrying a public debt-to-GDP ratio of over 90 percent is actually 2.2 percent, not -0.1 percent as [Reinhart-Rogoff claim]." [UPDATE: To clarify, they find 2.2 percent if they include all the years, weigh by number of years, and avoid the Excel error.] Going further into the data, they are unable to find a breakpoint where growth falls quickly and significantly.
Konzcal goes on to hope that future historians will recognise that:
one of the core empirical points providing the intellectual foundation for the global move to austerity in the early 2010s was based on someone accidentally not updating a row formula in Excel.
An alternative analysis of the data presented on NextNewDeal.net also raises questions about the causal relationship and dynamic that the original paper proposed (that high government debt causes decline in demand).
Paul Krugman has posted further updates on his NYTimes blog today.
Impact?
As with many information quality errors, the impacts of this error are often not immediate. Among was the potential impacts of this spreadsheet error and the nature of the causal dynamic are:
- Austerity policies in Ireland, Greece, Cyprus, Italy, Portugal, Spain and other countries
- Business failures (due to fiscal contractions in an economy reducing supply of investment finance, weaker demand, longer payment cycles etc)
- Reduction in public services such as health care, and increases in taxation
- Increases in Suicide in Austerity countries (e.g. Greece)
Conclusion
Where data and its analysis becomes an article of faith for policy or strategy it is imperative that attention be paid to the quality of the data and its analysis. In this case, opening up the data for inspection sooner might have allowed for a more timely identification of potential issues.
It also highlights the importance of careful assessment of cause and effect when looking at the relationship between two factors. This is an important lesson that Information Quality professionals can learn when it comes to figuring out the root cause of quality problems in the organisation.