The Global Crisis demonstrated to the world that Ratings Agencies had misled the public about the stability of financial institutions. The Finance literature had decided that it was impossible to have bubbles in financial markets and any surge in the stock market would be self-correcting. Recent papers have discussed the role of "uncertainty" and its measurement in influencing economic decisions. They attempt to measure uncertainty by indexes of volatility of the stock market, GDP, forecaster disagreement, mentions of uncertainty in news media, and the dispersion of productivity shocks to firms. Underlying their measures of uncertainty is the hypothesis that an increase in uncertainty leads to lower consumption by households and lower investment by firms, and hence leads to lower aggregate investment and growth. This paper argues that although risk can be measured, uncertainty cannot be measured. Even though risk can be measured, a simple symmetric measure (variance or standard deviation) is inappropriate because agents are loss averse and treat gains differently from losses. Although, it is clear that an increase in uncertainty worsens economic conditions, in this paper I shall also argue that this attempt at "measuring" risk or (fundamental) uncertainty is flawed.
uncertainty risk Keynes variance measures loss aversion investment