本文參照 Stock and Watson (2002b) 將變數區分類別後再採用擴散指數預測法，比較對 136 個總體經濟變數以不同的方式降維後再進行通貨膨脹率的預測。發現分類後再篩選重要變數後以 PQR 的降維方式能夠提升 25.7% 的預測力。依照該模型探討各類別的因子隨著時間推移對通膨預測重要性的消長，發現通膨的預測主要由利率與匯率、價格因子所主導，於特定區段會發生結構轉變。近期影響通膨的主要因素並非我們直觀認知的勞動市場及利率，而是由價格因子、產出與所得因子及消費與訂單庫存因子共同主導通膨的預測影響力。本文將分量迴歸預測通膨的特性應用於實務上，建立了能夠捕捉通膨極端異常的現象的通膨警示區間，使我們能夠知曉基於當期的經濟環境以及歷史通膨的分位數，能夠容忍的通膨範圍。透過該警示區間我們提早發現近期的通膨有異常過高的現象，且趨勢與 1970 年代非常相似。基於該模型的警示，央行應考慮短期內持續升息的必要性，並審慎的考量可能發生的經濟衰退。

This paper follows the framework of Stock and Watson (2002b) in classifying the variables and then using the diffusion index forecasting method, we compare the inflation forecasts predictability from 136 aggregate economic variables with different downscaling methods. It’s found that the PQR method of downscaling the important variables after classification and improve the predictive power by 25.7%. According to the model, the importance of each factor in the inflation forecast over time is examined, and it’s found that the inflation forecast is mainly dominated by interest and exchange rate, and price factors, with structural changes occurring at specific intervals. The main factors affecting inflation in the near term are not the labor market and interest rates as we know them intuitively, but the price factor, the output and income factor, and the consumption and order inventory factor together dominate the forecast impact of inflation. We apply the characteristics of fractional regression prediction of inflation in practice and establish an inflation warning bound that can capture the extreme abnormalities of inflation, so that we can know the range of inflation we can tolerate based on the current economic environment and the historical inflation fraction. The warning range allows us to identify early that recent inflation has been abnormally high, and the trend is very similar to the 1970s. Based on the model's warning, central banks should consider the need for sustained interest rate increases and carefully consider the possibility of a recession.

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