Trend-cycle decomposition allowing for multiple smooth structural changes in the trend of US real GDP
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DOI: 10.1016/j.jmacro.2015.02.002
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- Xu, Chang & Katchova, Ani, 2018. "Predicting Soybean Yield with NDVI using a Flexible Fourier Transform Model," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266693, Southern Agricultural Economics Association.
- Magdalena Osińska & Tadeusz Kufel & Marcin Błażejowski & Paweł Kufel, 2020. "Modeling mechanism of economic growth using threshold autoregression models," Empirical Economics, Springer, vol. 58(3), pages 1381-1430, March.
- Banerjee, Piyali & Arčabić, Vladimir & Lee, Hyejin, 2017. "Fourier ADL cointegration test to approximate smooth breaks with new evidence from Crude Oil Market," Economic Modelling, Elsevier, vol. 67(C), pages 114-124.
- Éva Gyurkovics & Tibor Takács, 2023. "Estimation of the potential GDP by a new robust filter method," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1183-1207, December.
- Luo, Shikong & Yan, Xinyan & Yang, Haoyi, 2021. "Let’s take a smooth break: Stock return predictability revisited," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 300-314.
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More about this item
Keywords
Trend-cycle decomposition; Flexible Fourier form; Smooth structural changes;All these keywords.
JEL classification:
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Statistics
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