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Getting to the policy discussion table is one of the objectives pursued by feminist scholars and advocates. However, some participants in this process have remarked that “you cannot get to the policy discussion table until you have proven that you can crunch the numbers.” This comment highlights the importance of using quantitative methods in order to rank feminist objectives among the leading priorities of policy making bodies. This course provides students with additional opportunities to engage in policy making discourse and broaden their scholarship by offering an introduction to quantitative methods.
The course seeks to develop your skills as a consumer and a producer of quantitative feminist research, with more emphasis on the consumer aspects. The course requirements are designed with this objective in mind. Upon completion of the course you will be a more informed and critical reader of academic work, news accounts, and policy materials that present statistical evidence. You will also be able to conduct and present elementary statistical analyses on your own.
Class 1: Introduction; Feminist Methodological Contributions
Barker, Drucilla. 2005. “Beyond Women and Economics: Rereading ‘Women’s Work,’”Signs 30 (4): 2189-2210.
Tickner, J. Ann. 2005. “Gendering a Discipline: Some Feminist Methodological Contributions to International Relations,” Signs 30 (4): 2173-2189.
Bristor, Julia, and Eileen Fischer. 1993. “Feminist Thought: Implications for Consumer Research,” Journal of Consumer Research 19 (4): 518-538.
Class 2: Feminist Data and Methods
Berik, Gunseli. 1997. “The Need for Crossing the Method Boundaries in Economics Research,” Feminist Economics 3 (2): 121-125.
Van Staveren, Irene. 1997. “Focus Groups: Contributing to a Gender-Aware Methodology,” Feminist Economics 3 (2): 131-135.
Esim, Simel. 1997. “Can Feminist Methodology Reduce Power Hierarchies in Research Settings?” Feminist Economics 3 (2): 137-139.
Olmstead, Jennifer. 1997. “Telling Palestinian Women’s Economic Stories,” Feminist Economics 3 (2): 141-151.
Class 3: Advantages and Disadvantages of Statistical Analyses in Feminist Research
Bennett, Briggs, Triola: Chapter 1.
World Bank. Engendering Development: Through Gender Equality in Rights, Resources, and Voice (New York: Oxford University Press, 2001). Summary Chapter.
Chen, M., J. Sebstad, and L. O’Connell. 1999. “Counting the Invisible Workforce: The Case of Homebased Workers,” World Development 27 (3): 603-10.
Class 4: Navigating Measurement Issues in Published Statistics about Women, Work, and Pay
Bennett, Briggs, Triola: Chapter 2.
Stark, Agneta, et al. 2005. “Gender and Aging: Cross National Contrasts,” Feminist Economics 11(2): 163-197.
Class 5: Using Descriptive Statistics to Send Effective Messages about Women’s Status
Bennett, Briggs, Triola: Chapter 3.
“Gender and Racial Differences in Vocational Education: An International Perspective,” International Journal of Manpower 27 (4), July 2006, 308-320 (with Teresa Boyer).
Class 6: Understanding Statistical Terms in Reports and Articles Relevant to the Feminist Agenda
Bennett, Briggs, Triola: Chapters 4,5.
Alm, James, M.V. Lee Badgett, and Leslie Whittington. 2001. “Wedding Bell Blues: The Income Tax Consequences of Legalizing Same Sex Marriage,” National Tax Journal 53 (2): 201-214.
Class 7: Making Quantitative Arguments in Feminist Policy Dialogues: Correlation and Causality
Bennett, Briggs, Triola: Chapters 6, 7.
Glover, Judith. 2001. “Targeting Women: Policy Issues Relating to Women’s Representation in Professional Scientific Employment,” Policy Studies 22 (2): 69-82.
Class 8: What Data can Feminists Use to Prove Their Point? Samples and Populations
Bennett, Briggs, Triola: Chapter 8.
Jacobsen, Joyce, and Andrew Newman. 1997. “What Data Do Economists Use? The Case of Labor Economics and Industrial Relations,” Feminist Economics 3 (2): 127 - 130.
Class 9: Hypothesis Testing in the Examination of Feminist Perspectives
Bennett, Briggs, Triola: Chapter 9.
Folbre, Nancy, et al. 2005. By What Measure? Family Time Devoted to Children in the U.S.” Demography 42 (2): 373-390.
Class 10: Regression Analysis in Research on Women: Why Learn About this Powerful Tool?
Studenmund: Chapters 1 and 2.
Berik, Gunseli. 2000. “Mature Export-Led Growth and Gender Wage Inequality in Taiwan,” Feminist Economics 6 (3): 1
Class 11: Get a Seat at the Policy Table: Pointers to Understanding Regression Analysis
Studenmund: Chapter 3.
Badgett, M.V. Lee. 1995. “The Wage Effects of Sexual Orientation Discrimination,” Industrial and Labor Relations Review 48 (4): 726-739.
Folbre, Nancy, and M.V. Lee Badgett. 2003. “Job Gendering: Occupational Choice and the Marriage Market,” Industrial Relations 42 (2): 270-298.
Class 12: Joining the Policy Debates: Understanding Hypothesis Testing in Regression Analysis
Studenmund: Chapters 4, 5.
Eaton, Susan. 2003. If You Can Use Them: Flexibility Policies, Organizational Commitment, and Perceived Performance,” Industrial Relations 42 (2): 145-167.
Class 13: Other Econometric Issues in Policy Dialogues and Feminist Research
Studenmund: Chapter 11.
Darity, William, and Patrick Mason. 1998. “Evidence on Discrimination in Employment: Codes of Color, Codes of Gender,” Journal of Economic Perspectives 12 (2): 63-90.
Bertrand, Marianne, and Sendhil Mullainathan. 2004. “Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination,” American Economic Review 94 (4): 991-1013.
Class 14: Overview of Statistical Methods in Feminist Research: Directions for Future Research
MacDonald, Martha. 1995. “Feminist Economics: From Theory to Research,” Canadian
Journal of Economics 28 (1): 159-176.
Nelson, Julie. 1995. “Feminism and Economics” Journal of Economic Perspectives 9 (2): 131-148.
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