– The author adopt a “classical” business cycle framework without using any filtering techniques. However, given the high volatility of carbon emissions data, would filtering (e.g., Hodrick-Prescott or Baxter-King filters) significantly affect the identification of turning points?
– The paper uses the Modified Bry-Boschan Quarterly (MBBQ) algorithm to identify turning points. However, carbon emissions data are annual, and MBBQ is often optimized for higher-frequency datasets (quarterly or monthly). Did the author test whether modifying the MBBQ algorithm for annual data (e.g., adjusting the minimum cycle duration) impacts the number of detected cycles?