臺灣博碩士論文加值系統

本研究使用雙重差分法(difference-in-difference, DID)分析基本工資調整時，對於不同族群實質薪資成長率的差異。主要探討不同性別之間的差異，另外也討論城鄉差距、公司規模、是否接受高等教育、不同年齡層以及不同行業別等群體間之薪資成長率。本文主要以行政院主計處1998至2016年的「人力運用擬-追蹤調查資料庫」(Manpower Utilization Quasi-Longitudinal Survey Database, MUS-QL)進行實證分析。與文獻較不同之處在於，本研究以分量迴歸的方式選取DID模型所需的控制組。文獻中大多採取薪資水準高於基本工資20%(或30%)的觀察樣本作為分析的控制組，似較為隨性(arbitrary)。基於基本工資調整可能對其他工資率的勞工薪資造成外溢的效果，因此，本文採用分量迴歸的方式選定薪資不受基本工資調整影響的百分位族群，作為DID分析的控制組。將薪資介於兩次基本工資之間者作為實驗組，即薪資直接受到基本工資影響的低薪族群。實證結果發現，
實證結果發現，相對於控制組，基本工資調高對於男性低薪族群薪資成長的影響效果介於-7.85%至-16.8%，女性則為-11%至0.88%。雖然基本工資對女性低薪族群的薪資成長無嚴重負面效果，但女性高薪族群在基本工資調整後，可能因為企業雇用成本提高而影響其就業機率，故基本工資調整的效果有一部分可能是反應在女性控制組就業機會的降低。此外，對於城市及鄉村的受雇勞工薪資成長率都有負向影響，但兩者估計係數不具顯著差異。對於公司規模而言，不論大小公司，基本工資政策對於薪資成長率雖然都有負面影響，二者亦無顯著差異。部分基本工資調高的年份，其對具高學歷但屬低薪的族群薪資成長的衝擊相對較大。由於受過高等教育的低薪族群有63%是未滿30歲的青少年族群，意味著青少年人即使是高學歷，仍可能存在頗明顯的低薪問題。基本工資的調高雖然提高了他們的薪資，但對後續的薪資成長速度反而是不利的。基本工資對15至29歲青少年以及30歲以上受雇者二群體薪資成長率的影響差異雖不顯著，但其調高對於不同年齡層的薪資成長幾乎都有顯著負向的影響，且近年來不斷提高基本工資所造成的負向影響有越來越嚴重的趨勢。最後，本研究發現不論是服務業或製造業，近年連續調整的基本工資顯著不利低薪族群的薪資成長率。金融海嘯之後，基本工資的調漲對於服務業在薪資成長率上的負向影響比製造業更嚴重些。綜合上述各種不同條件的低薪族群實證結果，本研究認為連續調高的基本工資對於台灣薪資成長的速度已經造成明顯負向的影響，且負向效果有逐年加重的趨勢。

In this paper we use an individual-level quasi-longitudinal database to study the impact of changes in legal minimum wages on labor market outcomes. We use difference-in-difference (DID) model to estimate the impact of minimum wage laws on wage growth in Taiwan. This study differs from the literature in that the control group for the DID model is determined by quantile regression. We analyze the minimum wage rate effect on wage growth for both gender and emphasize in particular on urban-rural disparity, company size, educational levels, age groups, and different industrial groups.
Compared to the control group, male low-income group is found to have a larger negative impact on their wage growth than the female low-wage groups. Although there is no serious negative effect on the wage growth rate for female low-wage groups, female high-wage groups may be affected by their employment opportunities after the national minimum wage (NMW) adjustment. Therefore, part of the effect of the NMW adjustment may be reflected in the reduction of employment opportunities for the female control group. Moreover, there is no difference between the impact on urban and rural areas, and among companies of different sizes; however, all of them got negative impacts by the rising NMW. For some years of NMW adjustment, highly educated low-income groups are of relatively larger negatively being shocked by the NMW adjustment on the salary growth than their less educated counterparts. Since about 63% of the low-income groups with higher education are people younger than 30 years old, it means that, obviously, even young people with highly educated may still influenced by the adjustment of NMW negatively. However, there is no difference in the wage growth for workers at various age groups, although all of them are negatively affected by the rising NMW. Overall the continuous adjustment of the NMW is significantly unfavorable for the wage growth rate of the low-income group, no matter in service or manufacturing sectors. After the financial crisis, the negative impact on service sector’s wage growth rate is more serious than that of the manufacturing sector. To sum up, we believe that the continuous increase in the NMW had a significant negative impact on Taiwan's wage growth rate, and the negative effect has been increasing year by year.

目錄
第一章、 序論 1
第二章、 文獻回顧 5
第三章、 資料來源與實證策略及方法 8
3.1 資料來源 8
3.2 DID控制組的選定方式 9
3.3 樣本分組 10
第四章、 計量模型之設定 15
4.1 控制組之決定—分量迴歸模型 15
4.2 薪資成長DID模型 16
第五章、 實證分析結果 18
5.1 基本統計量 18
5.2 最低工資調高的影響效果 19
5.2.1男女薪資成長之實證結果 19
5.2.2城鄉薪資成長之實證結果 25
5.2.3大小公司薪資成長之實證結果 28
5.2.4不同教育程度薪資成長之實證結果 30
5.2.5不同年齡層薪資成長之實證結果 32
5.2.6服務業和製造業薪資成長之實證結果 33
5.2.7兩性基本工資調整效果差異之原因分析 34
第六章、 結論 39
參考文獻 43
附錄A 45
附錄B 50
 
圖目錄
圖 1 基本工資制訂的調整經過 2
圖 2 男性及女性的勞動參與率 10
圖 3 男性及女性低薪比例 11
圖 4 不同族群的低薪比例 14
圖 5 基本工資違反率-城市及鄉村 27
圖 6 基本工資違反率-小大公司 30
 
表目錄
表 1 基本工資制訂的調整經過 1
表 2 近年基本時薪的調整幅度 8
表 3 女性勞動參與決策基本統計量 18
表 4 各組別實質薪資基本統計量 18
表 5 薪資成長率方程式之重要變數基本統計量 19
表 6 分量迴歸結果-男性及女性 19
表 7 薪資成長率之迴歸結果-男性和女性，2007年 21
表 8 薪資成長率之迴歸結果-男性和女性比較，2007-2015 23
表 9 薪資成長率之迴歸結果-男性和女性比較(與文獻相同的做法) 24
表 10 薪資成長率-城市和鄉村的比較 26
表 11 薪資成長率-不同公司規模的比較 29
表 12 薪資成長率-不同教育程度 31
表 13 薪資成長率-不同年齡層的比較 32
表 14 薪資成長率-服務業和製造業的比較 33
表 15 就業保留率-男性及女性比較 36
表 16 勞動參與變化-男性與女性比較 37
附錄A
表A. 1 分量迴歸模型之變數的基本統計量---按樣本特性區分 45
表A. 2薪資成長方程式基本統計量 47
表A. 3 解釋變數POLICY對就業保留率的影響 49
附錄B
表B. 1分量迴歸結果--- 城市 V.S. 鄉村 50
表B. 2分量迴歸結果---不同公司規模 51
表B. 3分量迴歸結果---不同教育程度 52
表B. 4分量迴歸結果---不同年齡層 53
表B. 5分量迴歸結果---服務業 V.S.製造業 54

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