The uncertainty hypothesis
What’s at stake: Uncertainty is frequently blamed for the sorry state of the economy. In the US, the Speaker of the House John Boehner, for example, recently declared that regulatory, tax, and trade uncertainties are playing a hampering role on the recovery from the Lesser Depression by straining the incentives for companies to invest. After […]
What’s at stake: Uncertainty is frequently blamed for the sorry state of the economy. In the US, the Speaker of the House John Boehner, for example, recently declared that regulatory, tax, and trade uncertainties are playing a hampering role on the recovery from the Lesser Depression by straining the incentives for companies to invest. After reviewing conditions under which an increase in uncertainty (second moment) – as opposed to a decrease in prospects (first moment) – can have a detrimental impact on the economy, we review the empirical evidence on the topic. We start by the specific type of uncertainty outlined by Boehner and then turn to another kind of uncertainty: our lack of knowledge about the shape of post-financial crisis recoveries.
Is uncertainty necessarily bad?
Antonio Fatas points to the importance of differentiating between uncertainty and bad news. One is that the future is more difficult to predict (and this truly matches the notion of uncertainty) but the second one is that future scenarios are simply worse than what we thought before.
David Romer furthermore argues that uncertainty does not necessarily reduce spending. What is key in terms of impact on aggregate spending is the asymmetry of the costs of doing more or less than you would have done had you known for sure. To build an argument based on uncertainty, it is therefore necessary to either assume an asymmetric objective function, or be in a situation where the value of waiting is increasing as uncertainty grows. In a set-up where durables purchases are irreversible and consumers choose not only the quantity but also the quality of durable goods they purchase, a temporary increase in uncertainty would reduce spending.
Nick Bloom of Stanford University reviews research on 16 previous shocks – such as September 11 and the Enron scandal – and concludes that today’s uncertainty shock will create a short, sharp contraction in late 2011 of about 1% with a rebound coming in spring 2012. Following disruptive events, he observes a sharp rise in the VIX index, followed by a large short run recession. In the end of August, the level of uncertainty had reached the same levels as during the post September 11 weeks.
In a recent NBER working paper, Ruediger Bachmann, Eric Sims, and Steffen Elstner found no evidence that changes in uncertainty cause a wait-and-see effect, defined as a large decline in economic activity when uncertainty hits followed later by fast rebounds. The economists used the Philadelphia Fed’s manufacturing survey since 1968 and the German Ifo business sentiment survey since 1980 and calculated uncertainty in various ways. Using as an indicator the divergence between prediction and real conjuncture, they conclude that uncertainty does not cause a wait-and-see impact on production and employment.
Policy and regulatory uncertainty
John Taylor makes the case against active interventionist policies. Stop all the interventions — the short-term discretionary fiscal stimulus packages and the massive quantitative easings and the operation twists of monetary policy. The unpredictability caused by these policies is causing uncertainty and holding the recovery back. Instead put in place more permanent reforms which will create economic recovery and return the economy to the kind of performance we saw in the 1980s and 1990s when rules-based, less interventionist policies were followed.
Robert Barro and Greg Mankiw argue that uncertainties on taxes and regulation reduce the returns of current investments. Mankiw points to the counterexample of the Reagan recovery in 1982, where non-residual fixed investment grew by 27% two years after the trough. As investment leads recoveries, taxes should be shifted to other bases to lower its cost. In a similar vein, Barro suggests establishing a VAT to lower the cost of capital.
Menzie Chinn, however, points that the “jobless recovery” does not seem to be an “investment-less recovery”: non-residential investment has rebounded faster than on average in other recessions (the Reagan recovery should be treated as a special case, precisely because of the particular macro and monetary environment at the time), whatever the metric used (from peak or from trough). The econometric relation between output and business investment is, if anything, more stable than in previous years.
Bruce Bartlett reports that, according to a BLS survey, the number of jobs involved mass lay-offs by companies citing new government regulations as a reason for is a mere 1% of the ones citing “lack of demand”. The number of small businesses reporting the regulatory environment as a problem is higher, but still accounts for less than half of the demand factor. Lawrence Michel, of the think tank EPI, adds that those concerns have always been high and roughly constant for small businesses, but that the lack of demand has suddenly risen as the main hurdle. Challenged by James Pethokoukis of the American Enterprise Institute, Michel further notes that investment in equipment and software during the 2009-2011 recovery has been more dynamic than in any of the four preceding ones.
Greg Ip argues regulations are sector-specific, and if they have an impact, it might be non-perceived at the macroeconomic level. They could also have a cost as part of a trade off (for example, in the case of the financial industry, a higher cost of capital against more financial stability).
One particular type of non-policy uncertainty is due to our limited knowledge about the shape of recoveries following a financial crisis.
Christina Romer argues that the sources of uncertainty holding the recovery are far more fundamental than the tax and environmental issues that typically top the list of complaints. The deepest and most destructive uncertainty we face centers on the overall health of the economy. Unlike other postwar recessions that were caused by tight monetary policy and high interest rates, the recent downturn resulted from the bursting of a housing bubble and a financial crisis. Because we are in largely uncharted territory, figuring out how and when the economy will recover is much harder than usual. One sign of heightened macroeconomic uncertainty is that the forecasts of respected analysts are all over the map. The difference between the highest and the lowest forecasts of unemployment a year from now is about twice as large as it was before the crisis. And forecasters’ reported uncertainty about their longer-run forecasts has shown no sign of improving over the last year.
Studying the 1825-1929 period in the US, Andrew Jalil argues that the sluggish output growth the U.S. economy has experienced in the aftermath of the Great Recession is consistent with the U.S. historical experience following major banking panics. Although policymakers often see Reinhart and Rogoff as the best work on recoveries following financial crises, Jalilforcefully reveals in the first part of his paper the major inconsistencies that the RR series on financial crises contain – sometimes even incorrectly identifying foreign banking panics as domestic ones. Armed with a better-identified series, Jalil investigates the shape of recoveries following banking crises in the US over the 1825-1929 period. Following three of the four major banking panics of the post-Jacksonian period, output did not rapidly revert back to its pre-panic trend. Moreover, following two of these panics, trend output growth declined substantially.
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