A Guide to Wavelets for Economists*

“…5 There is also the Discrete Wavelet Transform (DWT), with which we will not deal. For an introduction to the DWT, the reader is referred to Crowley (2007). 6 The conjugate of a complex number, a + bi, is simply a − bi.…”

Section: Wavelets and The Time Frequency Analysis Of Cyclesmentioning

confidence: 99%

“…In section two, we introduce the tools of wavelet analysis. With already broad usage in the physical and biological sciences, wavelet analysis is becoming recognized as a standard econometric tool (Crowley 2007;Aguiar-Conraria et al 2012b;Kennedy 2008;Aguiar-Conraria and Soares 2011;Gallegati et al 2011;Rua 2012). However, other than in economics, and to the best of our knowledge, wavelet analysis has never-with the single exception of Aguiar-Conraria et al (2012a)-been used in other social sciences.…”

Section: Introductionmentioning

confidence: 99%

The nationalization of electoral cycles in the United States: a wavelet analysis

2013

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We take a new look at electoral sectionalism and dynamic nationalization in presidential elections. We treat this problem as one of synchronism of electoral cycles, which we estimate by using wavelets. After providing a self-contained introduction to wavelet analysis, we use it to assess the degree and the dynamics of electoral synchronization in the United States. We determine clusters of states where electoral swings have been more and less in sync with each other and with the national cycle. Then, we analyze how the degree of synchronism of electoral cycles has changed through time, answering questions as to when, to what extent, and where has a tendency towards a "universality of political trends" in presidential elections been more strongly felt. We present evidence strongly in favor of an increase in the dynamic nationalization of presidential elections taking place since the 1950s, largely associated with a convergence in most (but not all) Southern states.

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“…The application of wavelet theory in modeling and analyzing economic data is a recent phenomenon and its applications in economics began in the late nineties by the contribution of Ramsay and his collaborators (see, e.g., [25,26]). Since then wavelets have been used in many areas of economics and finance (see [30,[34][35][36][37]). …”

Section: Wavelet Analysismentioning

confidence: 99%

In Search of Leading Indicator Property of Yield Spread for India: An Approach Based on Quantile and Wavelet Regression

Dar

Shah

2015

Economics Research International

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The leading indicator ability of yield spread for future output growth and inflation is tested for India. Using the yields on securities with maturities ten years and three months to construct yield spread, we study the predictive power of yield spread for output growth and inflation. Our results based on regression of future inflation and output on yield spreads indicate that there is no information in the yield spread about future economic activity and inflation in India. Further, the predictive power of yield spread is analyzed over different quantiles of inflation and output growth using quantile regression; we find that there is again no evidence of predictive information in the yield spreads. Using multiscale wavelet based regression, predictive power is however unveiled at higher time scales for output growth only.

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A Guide to Wavelets for Economists*

Cited by 325 publications

References 52 publications

Timescale-dependent stock market comovement: BRICs vs. developed markets

Timescale-dependent stock market comovement: BRICs vs. developed markets

The nationalization of electoral cycles in the United States: a wavelet analysis

In Search of Leading Indicator Property of Yield Spread for India: An Approach Based on Quantile and Wavelet Regression

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