基本薪資作為保證勞工生活水準的一種政策工具，其可能帶來的正負面影響備受學者及大眾討論，支持者認為提升基本薪資可以促進經濟成長；反對者認為可能會造成失業及物價上漲。近年來台灣以逐年的頻率提升基本薪資，因此本研究欲藉此探討基本薪資政策在台灣所帶來的影響，並藉此反思此政策在台灣是利大於弊抑或是弊大於利。
為了同時捕捉提升基本薪資帶來的正負面影響，本研究利用29歲以下失業率及消費者物價指數作為負面因子，批發、零售及食品銷售額作為正面因子，並同時採納各變數，藉此觀測受到基本薪資提升影響之反應。向量自我迴歸模型及向量誤差修正模型作為多變數時間序列模型允許同時存在多個內生變數，因此非常適合本研究使用，由於變數間存在共整合關係，因此本論文將使用向量誤差修正模型進行研究。
結果顯示基本薪資提升短期對批發、零售及食品銷售額有正向影響以及對29歲以下失業率有負向影響，長期下兩者影響不顯著；對消費者物價指數有長期正向影響。

As a policy tool aimed at ensuring the living standards of workers, the minimum wage has been the subject of extensive discussion among scholars and the general public regarding its potential positive and negative effects. Supporters argue that increasing the minimum wage can promote economic growth, while opponents believe it may lead to unemployment and inflation. In recent years, Taiwan has been gradually increasing the minimum wage on an annual basis. Therefore, this study aims to explore the impact of the minimum wage policy in Taiwan and reflect on whether the benefits outweigh the drawbacks or vice versa.
To capture both the positive and negative effects of increasing the minimum wage, this study utilizes the unemployment rate among individuals under 29 years old and the consumer price index as negative factors, while wholesale, retail, and food sales are considered positive factors. To capture the responses of these variables to changes in the minimum wage, we use Vector Autoregression Model or Vector Error Correction Model, which allow multiple endogenous variables. Due to the cointegration among the variables, the VECM is particularly suitable for this study.
The results indicate that a short run increase in the minimum wage has a positive and negative impact on wholesale, retail, and food sales and unemployment rate among individuals under 29 years old, respectively, but no long run effect. It also causes a long run positive impact on the consumer price index.

摘要 i
Abstract ii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 1
1.3 研究方法 2
第二章 文獻回顧 4
2.1 基本薪資與失業率相關文獻 4
2.2 基本薪資與物價相關文獻 5
2.3 基本薪資與消費相關文獻 6
第三章 研究方法 7
3.1 單根檢定 7
3.2 落後期數選擇 9
3.3 Johansen共整合檢定 10
3.4 誤差修正模型 11
3.4.1 向量自迴歸模型 11
3.4.2 誤差修正模型 12
3.5 Granger因果關係檢定 12
3.6 診斷檢定 13
3.6.1 Lagrange Multiplier自我相關檢定 13
3.6.2 Jarque-Bera常態檢定 14
第四章 實證結果 15
4.1 變數、資料來源及模型設定 15
4.2 單根與結構性斷點檢定 21
4.2.1 單根檢定 21
4.2.2 結構性斷點檢定 22
4.3 最適落後期選擇及共整合檢定 24
4.4 向量誤差修正模型及衝擊反應函數 26
4.4.1 向量誤差修正模型 26
4.4.2 衝擊反應函數 29
4.5 Granger因果關係 31
4.6 診斷檢定 34
第五章 結論及討論 35
參考文獻 37

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