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Trends, Shocks, Persistent Cycles in Evolving Economy

One basic problem in business cycle studies is how to deal with nonstationary time series. Trend-cycle decomposition is critical for testing competing dynamic models, including deterministic and stochastic approaches in business cycle theory.

A new analytical tool of time-frequency analysis, based on the symmetry principle in frequency and time, is introduced for studies of business cycles. The Wigner-Gabor-Qian (WGQ) spectrogram shows a strong capability in revealing complex cycles from noisy and nonstationary time series.

Competing detrending methods, including the first difference (FD) and Hodrick-Prescott (HP) filter, are tested with the mixed case of cycles and noise.FD filter does not produce a consistent picture of business cycles. HP filter provides a good window for pattern recognition of business cycles.

Existence of stable characteristic frequencies from economic aggregates provide strong evidence of endogenous cycles and valuable information about structural changes. Economic behavior is more like an organism instead of random walks. Remarkable stability and resilience of market economy can be seen from the insignificance of the oil price shocks and the stock market crash.Surprising pattern changes occurred during wars, arm races, and the Reagan administration. Like microscopy for biology, nonstationary time series analysis opens a new space for business cycle studies and policy diagnostics.

The role of time scale and preferred reference from economic observation is discussed. Fundamental constraints for Friedman’s rational arbitrageurs are eexamined from the view of information ambiguity and dynamic instability. Nonlinear economic dynamics offers a new perspective in empirical measurement and theoretical analysis.

Trends Shocks Persistent Cycles in Evolving Economy

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