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研究生: 王子齊
Tzu-Chi Wang
論文名稱: 區域間薪資差異是否反映生活環境特性? —以大台北地區及高雄市為例
Do wage differences between regions reflect the characteristics of the living environment? Evidence from the Taipei Metropolitan Area and Kaohsiung City.
指導教授: 黃麗璇
Li-Hsuan Huang
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 經濟學系
Department of Economics
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 66
中文關鍵詞: 補償性薪資薪資差異區域勞動市場
外文關鍵詞: Compensating wage differentials, wage differentials, local labor markets
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  • 台北是台灣的首都,也是台灣的經濟重心,國際化的發展提供了大量的就業機會,吸引眾多人才。隨著經濟的迅速發展,台北的生活成本也遠高於其他縣市,使的不少勞工表示在台北存不到錢。而本文則將依據補償性薪資理論,分析生活成本及其他生活環境特性對薪資是否真的無補償效果。
    本文採用「人力運用調查」2011~2020年間大台北地區及高雄市的勞工做為觀察樣本,並結合「家庭收支調查」中的總消費支出、房租,主計處公布的失業率及勞動部公布的產業移工人數等四項區域變數,探討一地區生活環境特性對薪資的補償效果。實證結果首先以Heckman兩階段模型修正樣本選擇偏誤,發現生活環境特性確實對薪資有補償效果,四項區域變數中,總消費支出和房租與薪資關係為向正顯著;與失業率無相關,產業移工人數則僅在台北市與薪資有顯著負相關。之後,再以Oaxaca拆解法分析,得出總消費支出對區域間薪資差異的解釋能力最顯著,約能解釋4成的薪資差異。然而從人口流動的變化看來,台北市的薪資補償效果似乎不足以彌補高生活成本所帶來的效用下降,導致人口流出。因此政策上或許可提高房租等補貼金額,提升勞工生活在台北市之效用,以改善人口流失的問題。


    Taipei is the economic center and the capital of Taiwan. Taipei’s globalization provides a large number of employment opportunities and attracts many talents. However, with the rapid economic development, the cost of living in Taipei is also much higher than that in other counties. Therefore, many workers think that they cannot save money in Taipei. This article aims to analyze whether the cost of living and other characteristics of the living environment have compensation effect on wages based on the theory of compensatory wages.
    To investigate the compensation effect of regional amenities and disamenities on wages, this thesis uses samples in Taipei and Kaohsiung from 2011 to 2020 from the "Manpower Utilization Survey" as the observation sample. On the other hand, this thesis uses the total consumption expenditure and rent from the "The Survey of Family Income and Expenditure", the unemployment rate published by the Directorate-General of Budget, and the number of industrial migrant workers published by the Ministry of Labor as the four regional variables.
    First, I correct the sample selection bias by using the Heckman’s two-stage method and find that regional amenities and disamenities do have a compensatory effect on wages. Among the four regional variables, total consumption expenditure and rent are significant positive correlations with wages; the unemployment rate does not correlate with wages. The number of industrial migrant workers has a significant negative correlation with wages only in Taipei City. Oaxaca decomposition is then used to analyze the source of the wage difference between Kaohsiung City and the Taipei Metropolitan Area. It is concluded that the total consumption expenditure has the most significant power to explain the wage difference between the two regions, which can explain about 40% of the wage difference.
    However, from the perspective of changes in population mobility, the compensation effect on wages in Taipei City seems hardly enough to compensate for the decline in works’ utility caused by the high living cost, resulting in population outflow. Therefore, it is plausibly that the Taipei City government may rise the utility of workers by increasing subsidies such as rent to alleviate the problem of population outflow.

    目錄 中文摘要....................................................Ⅰ 英文摘要...................................................Ⅱ 致謝......................................................Ⅳ 目錄.......................................................Ⅴ 圖目錄....................................................Ⅶ 表目錄...................................................Ⅷ 附表目錄..................................................Ⅸ 1. 緒論....................................................1 2. 北高之區域狀況及薪資水準現況與趨勢.........................3 3. 文獻回顧................................................7 3.1 補償性薪資理論與區域勞動市場之相關理論與實證文獻..........7 3.2 小結.................................................10 4. 資料來源及模型設定......................................11 4.1 資料來源.............................................11 4.2 薪資模型之設定........................................12 4..2.1 混和最小平方法(pooling OLS).......................12 4.2.2 二階段Heckman選擇性偏誤之修正.......................15 4.3.3 以Oaxaca拆解法分析北高薪資差異之來源................16 5. 實證結果...............................................18 5.1 變數的基本統計量......................................18 5.2 不分大台北與高雄地區之實證結果.........................22 5.3 分別針對兩個地區進行迴歸的結果.........................26 5.4 北高兩地薪資差異的原因---Oaxaca拆解法..................29 5.5 頑強檢定(Robustness test)............................32 5.5.1 觀察區域改變對薪資解釋的影響........................32 5.5.2 社福移工對薪資解釋的影響............................35 5.5.3 僅觀察男性樣本的北高薪資差異........................37 6. 結論...................................................40 參考文獻..................................................42 附錄A.....................................................44 附錄B.....................................................45 附錄C.....................................................47   圖目錄 圖1 實質月薪(大台北地區與高雄市).............................4 圖2 實質消費支出(大台北地區與高雄市).........................4 圖3 實質房租(大台北地區與高雄市).............................5 圖4實質房租箱型圖(大台北地區與高雄市).........................5 圖5 薪資減消費支出之餘額(大台北地區與高雄市)..................6 圖6 其他支出佔總消費支出比率.................................6 表目錄 表1:相關文獻之區域變數係數估計..............................9 表2:變數的名稱與定義......................................14 表3:主要變數之基本統計量...................................19 表4:北高薪資差異..........................................21 表5:Heckman修正選擇性偏誤的結果---勞動參與意願..............23 表6:薪資方程式迴歸結果.....................................25 表7:樣本選擇偏誤檢定結果(LR檢定H_0:ρ=0,大台北地區與高雄市)..28 表8:薪資方程式迴歸結果(大台北地區與高雄市)..................28 表9:北高兩地區域變數對薪資水準影響的差異之顯著程度...........29 表10:北高薪資差異分解結果..................................30 表11:樣本選擇偏誤檢定結果(LR檢定H_0:ρ=0,雙北與台北市)......34 表12:薪資差異分解結果(雙北與台北市)........................34 表13:薪資差異分解結果(大台北地區與高雄市)—總移工人數.........36 表14:薪資差異分解結果(男性)................................38 附表目錄 表A1:Probit方程式各變數之基本統計量---全體樣本..............44 表B1:詳細薪資方程式迴歸結果(大台北地區與高雄市)..............45 表C1:薪資方程式迴歸結果(雙北與台北市).......................47 表C2:樣本選擇偏誤檢定結果(LR檢定H_0:ρ=0,總移工人數)........49 表C3:薪資方程式迴歸結果(總移工人數)........................50 表C4:男性薪資方程式迴歸結果(大台北地區與高雄市)..............52

    中文
    1. 張景褔, 盧其宏, & 劉錦添. (2011). 勞工組成特性對工廠生產力及薪資之影響:以台灣電子業工廠為例,經濟論文叢刊, 2011, 39.2: 177-212.
    2. 黃芳玫, 林巍, & 陸怡蕙. (2013). 台灣金融機構間的薪資差異: 農漁會信用部 vs. 其他金融機構. 農業經濟叢刊, 19(1), 1-48.
    3. 陳虹妤. (2013). 區域特性與受雇者薪資差異: 以台北市, 高雄市為例. 2012. PhD Thesis. National Central University.
    4. 江豐富. (2006). 外勞引進對本國勞工失業, 職業選擇及薪資之影響. 臺灣經濟預測與政策, 37(1), 69-111.
    5. 黃台心, 劉洪禎, & 胡聚男. (2018). 考慮樣本選擇下分析兩性勞工薪資低付問題: 關聯結構隨機邊界法之應用. 經濟論文叢刊, 46(3), 401-450.
    6. 許家馨. (2019). 產業結構, 工作型態與兩性薪資差異之探討. 2019. PhD Thesis.
    英文
    1. Albouy, D., Chernoff, A., Lutz, C., & Warman, C. (2019). Local labor markets in Canada and the United States. Journal of Labor Economics, 37(S2), S533-S594.
    2. Roback, J. (1982). Wages, rents, and the quality of life. Journal of political Economy, 90(6), 1257-1278.
    3. Braakmann, N. (2009). Is there a compensating wage differential for high crime levels? First evidence from Europe. Journal of Urban Economics, 66(3), 218-231.
    4. Greenwood, M. J., Hunt, G. L., Rickman, D. S., & Treyz, G. I. (1991). Migration, regional equilibrium, and the estimation of compensating differentials. The American Economic Review, 81(5), 1382-1390.
    5. Heckman, J. J. (1976). The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. In Annals of economic and social measurement, 5(4), 475-492.
    6. Knapp, T. A., & Gravest, P. E. (1989). On the role of amenities in models of migration and regional development. Journal of regional science, 29(1), 71-87.
    7. Oaxaca, R. (1973). Male-female wage differentials in urban labor markets. International economic review, 693-709.
    8. Oshchepkov, A. (2015). Compensating wage differentials across Russian regions. In Geographical Labor Market Imbalances. Springer, Berlin, Heidelberg. 65-105.
    9. Topel, R. H. (1986). Local labor markets. Journal of Political economy, 94(3, Part 2), S111-S143.
    10. Villanueva, E. (2007). Estimating compensating wage differentials using voluntary job changes: evidence from Germany. ILR Review, 60(4), 544-561.

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