本文旨在重新檢視美國後疫情時期菲利浦曲線 (Phillips curve) 之表現，探討其表面上之平坦化現象，究竟源自結構性轉變，抑或來自變數衡量與模型設定之問題。為此，本文採取兩步驟實證策略。首先，運用 Sparse-Group LASSO (SG-LASSO) 方法，自高維度之勞動市場與總體經濟變數中篩選關鍵解釋因子，並額外納入失業率落後一期作為控制變數，以部分緩解勞動市場與通膨之間潛在的雙向因果問題；其次，結合動態模型平均法 (Dynamic Model Averaging, DMA)，以捕捉通膨與勞動市場關係之時變特性與模型不確定性。實證結果顯示，傳統總體失業率對通膨之解釋能力已明顯下降被模型淘汰，而菲利浦曲線之平坦化現象在不同勞動市場維度下呈現明顯差異。在通過篩選的指標中，以短期失業率衡量時，通膨對勞動市場閒置程度之敏感度確實顯著減弱，符合傳統文獻所稱之平坦化；然而，以職缺與失業比率 (Vacancy-to-Unemployment Ratio, V/U ratio) 衡量時，通膨對勞動市場緊俏程度之敏感度則由疫情前缺乏穩定方向、與通膨關聯有限，轉變為疫情後顯著且穩定之正向關係。此一對比顯示，過去文獻所觀察之平坦化現象，可能主要源自於指標衡量與模型設定不當，而非通膨與勞動市場關係之消失。整體而言，本文透過結合變數篩選與動態模型之方法，提供一個更具彈性之分析架構，以重新理解後疫情時期通膨動態之形成機制，並對相關政策判斷提供實證依據。

This paper re-examines the Phillips curve in the post-pandemic period in the United States, focusing on whether its apparent flattening reflects structural changes or issues related to variable measurement and model specification. To address this question, we employ a two-step empirical strategy. First, we apply Sparse-Group LASSO (SG-LASSO) to select key explanatory factors from a high-dimensional set of labor market and macroeconomic indicators, additionally including a lagged unemployment rate to partially mitigate potential endogeneity arising from the bidirectional relationship between labor market and inflation. Second, we adopt a Dynamic Model Averaging (DMA) framework to capture time-varying relationships and model uncertainty. Our empirical findings reveal that the explanatory power of the traditional aggregate unemployment rate for inflation has diminished significantly, leading to its exclusion from the model. Furthermore, the flattening of the Phillips curve presents markedly different patterns across the remaining labor market dimensions. When measured by short-term unemployment, inflation's sensitivity to labor market slack has weakened substantially, consistent with the flattening documented in prior studies. In contrast, when measured by the vacancy-to-unemployment ratio (V/U ratio), inflation's sensitivity to labor market tightness has shifted from lacking a stable direction and showing a limited correlation with inflation before the pandemic, to a significant and stable positive relationship afterward. This contrast suggests that the perceived flattening of the Phillips curve may largely stem from measurement and specification issues rather than the disappearance of the underlying relationship between inflation and the labor market. Overall, this paper provides a flexible empirical framework that integrates variable selection and time-varying modeling to re-examine the underlying mechanisms of inflation dynamics in the post-pandemic era and to provide empirical evidence for relevant policy assessments.

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