How do households respond to uncertainty shocks?

Economic disruptions generally coincide with heightened uncertainty. In the United States, uncertainty increased sharply with the recent housing market crash, financial crisis, deep recession, and uneven recovery. In July 2010 Congressional testimony, Federal Reserve Chairman Bernanke described conditions as "unusually uncertain." The uncertain landscape was also cited as a factor in the slow recovery from the 2001 recession, when the March 2003 Federal Open Market Committee statement highlighted the "unusually large uncertainties" at the time. ; Uncertainty is a standard feature of most macroeconomic models, in which consumers and firms make decisions today based on expectations of an unknown (and hence uncertain) future. But in light of real-world events, economists have begun to think more critically about the role of uncertainty in the economy. Recent research has allowed the degree of uncertainty to vary over time and examined how these fluctuations affect business activity. The results have been mixed thus far, with some authors finding that fluctuations in uncertainty are a key factor in the business cycle, while others have found little such evidence. ; Knotek and Khan take a similar approach in studying levels of uncertainty that can vary over time, but they focus on household responses to changes in uncertainty. Because uncertainty can take many forms, they consider two measures of uncertainty, one based on references to uncertainty in newspaper articles and another derived from the stock market. ; While economic theory predicts sudden, sharp pullbacks of household purchases following increases in uncertainty, the empirical results suggest that household spending reductions are modest and may only appear after a considerable time has passed. In addition, movements in uncertainty account for only a small portion of the total fluctuations in household spending. These results suggest that variations in the amount of uncertainty--at least as they are commonly captured--do not appear to be a key factor driving household spending decisions and, in turn, economic weakness.

A Robust Variable Step Size Fractional Least Mean Square (RVSS-FLMS) Algorithm

In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).Comment: 15 pages, 3 figures, 13th IEEE Colloquium on Signal Processing & its Applications (CSPA 2017