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研究生:江文基
研究生(外文):Wun-Ji Jiang
論文名稱:有關電腦使用與性別差異之研究
論文名稱(外文):Essays on Computer Use and Gender Inequality
指導教授:陸怡蕙陸怡蕙引用關係
指導教授(外文):Yir-Hueih Luh
口試委員:陶宏麟方珍玲莊慧玲詹滿色
口試委員(外文):Hung-Lin TaoChen-Ling FangHwei-Lin ChuangMan-Ser Jan
口試日期:2016-01-24
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:農業經濟學研究所
學門:農業科學學門
學類:農業經濟及推廣學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:116
中文關鍵詞:電腦使用網路使用性別差異薪資差異Blider-Oaxaca拆解台灣
外文關鍵詞:Computer useInternet useGender differenceWage gapBlider-Oaxaca decompositionTaiwan
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本論文包含兩篇有關電腦使用與性別差異的實證研究。
第一篇(本文第貳章):
從網路採用、使用與使用模式探討台灣性別數位落差
本研究由網路採用、使用與使用模式三個面向來探討台灣目前性別數位落差情況。利用「台灣個人/家戶數位機會2012年調查資料」,實證結果發現性別在網路採用方面並未存在顯著差異。然而,在修正樣本選擇偏誤之後,本文發現台灣女性網路使用時間顯著低於男性。此外,拆解結果進一步顯示網路使用時間之性別差異有34-47%可被兩者之社會經濟差異所解釋,有48-66%是來自性別特定因素。最後,在其他條件不變之下,本研究之模擬結果發現若網路使用時間之性別差異可以被消弭,女性會有較高的機率使用網路搜尋健康與政府資訊,表示加快網路使用時間性別差異的彌合速度對相關單位而言是重要的。
第二篇(本文第參章):
電腦使用與性別薪資差異─台灣之實證研究
過去已有相當多的文獻探討工作上電腦使用與薪資之間的關聯,然而,針對電腦使用與性別薪資差異的討論卻是相對較少。本研究旨在分析電腦使用對於性別薪資結構影響的差異,並彌補過去文獻不足之處。利用台灣資料,本研究首先發現工作經驗、教育程度、廠商規模與職業別是影響電腦使用的重要因素。其次,雖然OLS估計結果顯示電腦使用對於男女薪資皆有正向影響,然而,在修正電腦使用可能的內生性問題後,本研究實證結果發現,平均而言,電腦使用的男性薪資報酬率為23%,但對女性薪資卻沒有顯著影響。此結果顯示,在OLS的估計中,女性電腦使用的薪資溢酬是自我「選擇」的結果。第三,應用非條件分量迴歸,本文進一步發現,電腦使用對於低薪資分量的勞工有顯著正向影響,且女性群組的影響效果大於男性群組。此外,無論男女,電腦使用在高薪資分量並沒有顯著的影響效果,此結果說明了電腦使用溢酬在不同薪資分量之間具有異質性。最後,利用Blinder-Oaxaca拆解,本文結果顯示台灣性別薪資差異主要來自於傳統人力資本的稟賦差異與歧視,尤其在低薪資分量的女性,勞動市場對於人力資本評價的歧視情形更為嚴重。此外,電腦使用報酬率與稟賦的差異與對於台灣性別薪資差異的貢獻則是相當小。

This dissertation includes two essays on computer use and gender differences.
Essay 1 (Chapter 2 in this dissertation):
Exploring Gender Digital Divide in Taiwan from the Perspectives of Internet Adoption, Use and Usage Patterns
This paper explores gender digital divide in Taiwan from the perspectives of internet adoption, use and usage patterns. Using 2012 Survey of Digital Divide in Taiwan, it is found that gender is not a significant factor determining internet adoption. However, after correcting for Heckman’s sample selection bias, the result reveals that females in Taiwan spend less time on internet than do males. The Blinder-Oaxaca decomposition results further suggest that the gender gap in usage time is the mixed product of both socio-economic difference, accounting for 34-47% of the gap, and gender specific factors, accounting for 48-66% of the gap. Finally, all else equal, the simulation shows that females are inclined to use internet for health information and e-government as the gender digital divide in internet use is eliminated, suggesting a boost to the elimination of the gender gap in internet use is important for Taiwanese government.
Essay 2 (Chapter 3 in this dissertation):
Computer Use and Gender Wage Differential: Evidence from Taiwan
Although there is a considerable body of literature examining the impact of on-the-job computer use on personal wage, little of them are known about the association between computer use and gender wage differential. In an effort to fill this knowledge void, the present study investigates the differential impacts of computer use on gender wage structures. Using the data from Taiwan, the findings first suggest that working experience, education, firm size and occupation are important determinants of on-the-job computer use. In addition, after correcting for the endogeneity of computer use, it is found that, on average, the rate of returns to computer use is 23% for males while it is not evident for females. This finding suggests the OLS estimates of the returns to computer use for females are biased upward as a result of positive self-selection. Third, by applying unconditional quantile regression, it is found that, no matter for males or females, the returns to computer use are more pronounced for employees at the lower quantile of wage distribution, suggesting the impact of computer use are heterogeneous across different quantiles of wage distribution. Moreover, the result suggests that the females at the lower quantile of wage distribution have higher returns to computer use than their male counterparts. Finally, the result of Blinder-Oaxaca decomposition reveals that most of the gender wage differential can be explained by the discrimination, particularly for those females at the lower quantile of wage distribution. However, the contributions of the coefficient and endowment effects of computer use to the gender wage gap are quite small.

謝辭 i
摘要 ii
Abstract iv
目錄 vi
第壹章 緒論 1
第貳章 從網路採用、使用與使用模式探討台灣性別數位落差 8
第一節 前言 8
第二節 理論背景 12
第三節 資料來源與變數定義 15
一、資料來源 15
二、變數定義與敘述統計 16
第四節 實證模型 18
一、Heckman樣本選擇模型 19
二、Blinder-Oaxaca拆解 20
三、網路使用時間性別差異之細部拆解 22
四、網路使用時間與使用模式之關聯 23
第五節 實證結果 24
一、網路採用之決定因素 25
二、網路使用時間之決定因素 26
三、Blinder-Oaxaca拆解之結果 28
四、網路使用模式估計式之結果 30
第六節 模擬與政策意涵 31
一、模擬分析 31
二、政策意涵 33
第七節 結論 34
參考文獻 56
第參章 電腦使用與性別薪資差異─台灣之實證研究 62
第一節 前言 62
第二節 資料來源與變數定義 66
一、資料來源 66
二、變數定義 67
三、變數之敘述統計 68
第三節 實證模型 69
一、第一階段估計:電腦使用方程式 69
二、第二階段估計:薪資方程式 71
三、第三階段估計:非條件分量迴歸 73
四、電腦使用與性別薪資差距之關聯 77
第四節 實證結果 79
一、OLS估計結果 79
二、電腦使用方程式之估計結果 81
三、薪資方程式之估計結果 83
四、Blinder-Oaxaca拆解結果 86
第五節 結論 87
參考文獻 107
第肆章 總結、研究限制與未來研究方向 113
第一節 總結 113
第二節 研究限制與未來研究方向 114



第壹章 緒論
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第貳章 從網路採用、使用與使用模式探討台灣性別數位落差
一、中文部分
陳碧姬與吳宜鮮(2005),「家庭內兩性數位機會、電腦態度與網路使用行為初探」,《資訊社會研究》,9,295-324。
二、英文部分
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Becker, G. S. (1965), “A Theory of the Allocation of Time,” Economic Journal, 75, 493-517.
Bimber, B. (2000), “Measuring the Gender Gap on the Internet,” Social Science Quarterly, 81, 868-876.
Blinder, A. (1973), “Wage Discrimination: Reduced Forms and Structural Estimation,” Journal of Human Resources, 8, 436-455.
Chang, H. H., and D. R. Just. (2009), “Internet Access and Farm Household Income-Empirical Evidence Using a Semi-parametric Assessment in Taiwan,” Journal of Agricultural Economics, 60, 348-366.
Cheong, P. H. (2007), “Gender and Perceived Internet Efficacy: Examining Secondary Digital Divide Issues in Singapore,” Women’s Studies in Communication, 30, 205-228.
Cotton, J. (1988), “On the Decomposition of Wage Differentials,” Review of Economics and Statistics, 70, 236-243.
Dholakia, R. R. (2006), “Gender and IT in the Household: Evolving Patterns of Internet Use in the United States,” The Information Society, 22, 231-240.
Dickerson, M. D., and J. W. Gentry. (1983), “Characteristics of Adopters and Non-adopters of Home Computers,” Journal of Consumer Research, 10, 225-235.
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Durndell, A., and Z. Hagg. (2002), “Computer Self Efficacy, Computer Anxiety, Attitudes towards the Internet and Reported Experience with the Internet, by Gender, in an East European Sample,” Computers in Human Behavior, 18, 521-535.
Dutton, W, E Helsper, and M Gerber. (2011), The Internet in Britain in 2011. Oxford: Oxford Internet Institute.
Eysenbach, G. (2001), “What is E-health?” Journal of medical Internet research, 3, e20.
Gardeazabal, J., and A. Ugidos. (2004), “More on Identification in Detailed Wage Decompositions,” Review of Economics and Statistics, 86, 1034-1036.
Goldfarb, A., and J. Prince. (2008), “Internet Adoption and Usage Patterns Are Different: Implications for the Digital Divide,” Information Economics and Policy, 20, 2-15.
Heckman, J. (1979), “Sample Selection Bias as a Specification Error,” Econometrica, 47, 153-161.
Hitt, L., and P. Tambe. (2007), “Broadband Adoption and Content Consumption,” Information Economics and Policy, 19, 362-378.
Hoffman, D. L., and T. P. Novak. (1998), “Bridging the Racial Divide on the Internet,” Science, 280, 390-391.
Horrace, W. C., and R. L. Oaxaca. (2001), “Inter-industry Wage Differentials and the Gender Wage Gap: An Identification Problem,” Industrial and Labor Relations Review, 54, 611-618.
Howland, J. (1998), “The ‘Digital Divide’: Are We Becoming a World of Technological ‘Haves’ and ‘Have-nots’?” Electronic Library, 16, 287-289.
Jackson, L. A., K. S. Ervin, P. D. Gardner, and N. Schmitt. (2001), “Gender and the Internet: Women Communicating and Men Searching,” Sex Roles, 44, 363-379.
Jones, F. L. (1983), “On Decomposing the Wage Gap: A Critical Comment on Blinder’s Method,” Journal of Human Resources, 18, 126-130.
Kennedy, T., B. Wellman, and K. Klement. (2003), “Gendering the Digital Divide,” IT & Society, 1, 72-96.
Koch, S. C., S. M. Muller, and M. Sieverding. (2008), “Women and Computers. Effects of Stereotype Threat on Attribution of Failure,” Computers & Education, 51, 1795-1803.
Li, N., and G. Kirkup. (2007), “Gender and Cultural Differences in Internet Use: A Study of China and the UK,” Computers & Education, 48, 301-317.
Liff, S., and A. Shepherd. (2004), “An Evolving Gender Digital Divide?” Oxford Internet Institute, Internet Issue Brief, 2, 1-17.
Losh, S. C. (2004), “Gender, Educational, and Occupational Digital Gaps 1983-2002,” Social Science Computer Review, 22, 152-166.
Malanda, M., V. B. Jenvey, and J. G. Phillips. (2004), “Internet Use in Adulthood: Loneliness, Computer Anxiety and Education,” Behavior Change, 21, 103-114.
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Noriss, P. (2001), Digital Divide: Civic Engagement, Information Poverty and the Internet in Democratic Societies. New York: Cambridge University.
Oaxaca, R. (1973), “Male-Female Wage Differentials in Urban Labor Markets,” International Economic Review, 14, 693-709.
Oaxaca, R. L., and M. R. Ransom. (1999), “Identification in Detailed Wage Decompositions,” Review of Economics and Statistics, 81, 154-157.
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Schumacher, P., and J. Morahan-Martin. (2001), “Gender, Internet and Computer Attitudes and Experiences,” Computers in Human Behavior, 17, 95-110.
Selwyn, N. (2006), “Digital Division or Digital Decision? A Study of Non-users and Low-users of Computers,” Poetics, 34, 273-292.
Shaw, L. H., and L. M. Gant. (2002), “Users Divided? Exploring the Gender Gap in Internet Use,” CyberPsychology & Behavior, 5, 517-527.
Sherman, R. C., C. End, E. Kraan, A. Cole, J. Campbell, Z. Birchmeier, and J. Klausner. (2000), “The Internet Gender Gap among College Students: Forgotten but Not Gone?” CyberPsychology & Behavior, 3, 885-894.
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Van Deursen, A. J. A. M., and J. A. G. M. Van Dijk. (2014), “The Digital Divide Shifts to Differences in Usage,” New Media & Society, 16, 507-526.
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Van Dijk, J. A. G. M. (2012), “The Evolution of the Digital Divide: The Digital Divide Turns to Inequality of Skills and Usage” In Digital Enlightenment Yearbook 2012, edited by J. Bus et al. Amsterdam, Netherlands: IOS Press.
Van Dijk, J. A. G. M., and K. Hacker. (2003), “The Digital Divide as a Complex and Dynamic Phenomenon,” The Information Society: An International Journal, 19, 315-326.
Vicente, M. R., and A. J. López. (2010), “A Multidimensional Analysis of the Disability Digital Divide: Some Evidence for Internet Use,” The Information Society, 26, 48-64.
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Yun, M. S. (2005), “A Simple Solution to the Identification Problem in Detailed Wage Decompositions,” Economic Inquiry, 43, 766-772.

第參章 電腦使用與性別薪資差異─台灣之實證研究
一、中文部分
徐美、陳明郎與方俊德(2006),台灣產業結構變遷和性別歧視對男女薪資溢酬變動趨勢之影響,《經濟論文》,34,505-539。
陳建良與管中閔(2006),台灣工資函數與工資性別歧視的分量迴歸分析,《經濟論文》,34,435-468。
莊奕琦與楊孟嘉(2014),中國農民工與城鎮勞工之薪資差異與歧視,《人文及社會科學集刊》,26,525-553。
劉錦龍、劉錦添(1988),台灣地區公共部門與民間部門工資率的比較,《經濟論文叢刊》,16,393-412。
二、英文部分
Arabsheibani, G. R., J. M. Emami, and A. Marinnn. (2004), “The Impact of Computer Use on Earnings in the UK,” Scottish Journal of Political Economy, 51, 82-94.
Banerjee, S., R. Parai, and A. K. Parai. (2007), “Computer Use and Wage Differentials: US and Foreign Born Male and Female Workers,” Applied Economics Letters, 14, 409-413.
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第肆章 總結、研究限制與未來研究方向
Imbens, G. W., and J. M. Wooldridge. (2009), “Recent Developments in the Econometrics of Program Evaluation,” Journal of Economic Literature, 47, 5-86.
Van Dijk, J. A. G. M. (2012), “The Evolution of the Digital Divide: The Digital Divide Turns to Inequality of Skills and Usage,” In Digital Enlightenment Yearbook 2012, edited by J. Bus et al. Amsterdam, Netherlands: IOS Press.

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