Decline in Us Output Growth Volatility: A Wavelet Analysis*

Abstract

The aim of the paper is to determine (endogenously) whether the volatility of the US output growth rate has changed since the late 1940s. By applying the discrete wavelet transform to the annualized quarter-toquarter output growth series, we test the homogeneity of the variance on a scale-by-scale basis. A version of the Normalized and Centered Cumulative Sum of Squares test, adapted to wavelets, leads us to reject the null of constant variance in the two levels of decomposition of the highest resolution and to locate a single break in 1982. The economic implications are explored.The signal can then be written as a sum of orthogonal components at resolutions 1 to J: f t d t d t d t d t s t J J J

The Role of Recurrence Plots in Characterizing the Output-Unemployment Relationship: An Analysis

“…This is indeed an important consequence given the current economic climate but it is also of importance within the wider European Community context, as [15] indicates, such nonlinear relationships affect aggregation (from a country level to a multiplicity of countries level, such as with the European community). In the work of [18] it is shown that with the use of wavelets, one can test for the presence of lower output volatility in US output (since the late 1940's). This lower volatility [18] claims to be a consequence of changes in a dynamic process.…”

“…In the work of [18] it is shown that with the use of wavelets, one can test for the presence of lower output volatility in US output (since the late 1940's). This lower volatility [18] claims to be a consequence of changes in a dynamic process. We wonder if this ‘dynamic process’ has a link to what we will call in our paper the periods of ‘dynamic discontinuity’.…”

Monetary policy objectives and economic outcomes: What can we learn from a wavelet‐based optimal control approach?

“…Wavelet analysis examples in the macroeconomics literature include Aguiar‐Conraria and Soares (2011), Gallegati et al. (2011), Lo Cascio (2013), Dar et al (2014), Tiwari et al. (2015), Chen (2016), Crowley and Hughes Hallett (2016), Verona (2016), and Crowley and Hughes Hallett (2018) and Lubik et al.…”