The Typical Spectral Shape of an Economic Variable: A Visual Guide with 100 Examples

Medel, Carlos A. (2014): The Typical Spectral Shape of an Economic Variable: A Visual Guide with 100 Examples.

Abstract

Granger (1966) describes how the spectral shape of an economic variable concentrates spectral mass at low frequencies, declining smoothly as frequency increases. Despite a discussion about how to assess robustness of his results, the empirical exercise focused on the evidence obtained from a handful of series. In this paper, I focus on a broad range of economic variables to investigate their spectral shape. Hence, through different examples taken from both actual and simulated series, I provide an intuition of the typical spectral shape of a wide range of economic variables and the impact of their typical treatments. After performing 100 different exercises, the results show that Granger's assertion holds more often than not. I also confirm that the basic shape holds for a number of transformations, time aggregations, series' anomalies, variables of the real economy, and also, but to a lesser extent, financial variables. Especially fuzzy cases are those that exhibit some degree of transition to a different regime, as are those estimated with a very short bandwidth.

• Item Type: MPRA Paper
• Language: English
• Keywords: Frequency domain; spectral analysis; nonparametric econometrics; busness cylces
• Subjects: A - General Economics and Teaching > A2 - Economic Education and Teaching of Economics > A20 - General; C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles

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