Research ArticleGENDER STUDIES

How many cents on the dollar? Women and men in product markets

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Science Advances  19 Feb 2016:
Vol. 2, no. 2, e1500599
DOI: 10.1126/sciadv.1500599
  • Table 1 Summary statistics of auctions of best-selling products on eBay 2009 to 2012, by gender.
    WomenMenTest for difference in
    means/proportions
    MeanSDMeanSD
    Price101.26154.46136.15181.46P < 0.001
    Number of bids11.689.5114.0210.51P < 0.001
    Percent positive feedback99.602.3599.582.41P < 0.05
    Reputation274.77253.32260.29248.16P < 0.001
    Start price40.24102.2046.57116.93P < 0.001
    Reserve price (dummy)0.030.03
    New0.170.11P < 0.001
    Rating: average4.840.454.840.44
    Rating: description4.860.544.850.56P < 0.001
    Rating: shipping time4.820.604.840.56P < 0.001
    Rating: shipping charges4.830.544.830.54
    Rating: communication4.840.584.840.56
    Bold title0.020.04P < 0.001
    Number of pictures1.361.631.781.92P < 0.001
    Stock photo0.290.21P < 0.001
    Same state0.050.06P < 0.001
    Duration (days)4.812.324.662.40P < 0.001
    Year2010.410.992010.450.98P < 0.001
    Years in eBay9.023.359.813.37P < 0.001
    Sentiments0.0320.210.0300.22P < 0.001
    n148,017483,499
  • Table 2 OLS regression models predicting the number of bids and final price: eBay auctions 2009 to 2012.

    All regressions include year, start month, end month, start day, end day, duration and product fixed effects.

    (1)
    Bids
    (2)
    Price
    (3)
    Log price
    (4)
    Log price
    (5)
    Log price
    (6)
    Log price
    (gift cards)
    Woman−0.885***−4.880***−0.054***−0.029***−0.056***−0.068***
    (0.027)(0.306)(0.002)(0.002)(0.003)(0.016)
    Woman × new−0.190***
    (0.006)
    Woman buyer0.030***
    (0.003)
    Card title price0.006***
    (0.000)
    New1.198***29.447***0.212***0.265***0.210***−0.236
    (0.041)(0.470)(0.003)(0.004)(0.005)(0.189)
    Percent positive feedback0.013**0.0810.0010.0010.000−0.005
    (0.004)(0.051)(0.000)(0.000)(0.001)(0.003)
    Reputation0.003***0.023***−0.000***−0.000***−0.000***−0.000
    (0.000)(0.002)(0.000)(0.000)(0.000)(0.000)
    Reputation × reputation−0.000***−0.000***0.000***0.000***0.000***0.000
    (0.000)(0.000)(0.000)(0.000)(0.000)(0.000)
    Years in eBay0.013***0.248***0.014***0.014***0.013***0.013***
    (0.003)(0.039)(0.000)(0.000)(0.000)(0.002)
    Start price−0.036***0.487***0.002***0.002***0.002***0.001***
    (0.000)(0.001)(0.000)(0.000)(0.000)(0.000)
    Reserve (dummy)0.446***43.648***0.265***0.265***0.279***0.361***
    (0.061)(0.702)(0.005)(0.005)(0.008)(0.078)
    Bold title1.851***36.857***0.155***0.155***0.162***0.020
    (0.060)(0.687)(0.005)(0.005)(0.007)(0.085)
    Number of pictures0.367***3.988***0.037***0.037***0.039***−0.000
    (0.007)(0.084)(0.001)(0.001)(0.001)(0.026)
    Stock photo−0.072*1.474***0.016***0.016***0.015***0.029
    (0.033)(0.380)(0.003)(0.003)(0.004)(0.029)
    Same state−0.110*−2.079***−0.009*−0.008*−0.002−0.033
    (0.046)(0.534)(0.004)(0.004)(0.006)(0.030)
    Constant19.520***186.958***4.819***4.808***3.752***2.545***
    (0.532)(6.124)(0.041)(0.041)(0.057)(0.351)
    R20.3540.7030.7420.7430.7370.637
    n615,735.000615,115.000615,115.000615,115.000259,777.00010,979.000

    *Significance at the 95% level.

    **Significance at the 99% level.

    ***Significance at the 99.9% level.

    Supplementary Materials

    • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/2/2/e1500599/DC1

      According to our agreement with eBay, we cannot use, reproduce, or access the data. The Stata do-file used for conducting the analysis is available online. We also provide the data and do-files for the two experiments conducted.

      Table S1. Distribution of women and men sellers across sale platforms.

      Table S2. Multinomial regression models predicting the sale platform, eBay 2009 to 2012.

      Table S3. Models predicting the likelihood of various seller characteristics, choices, and rating.

      Table S4. Logistic regression models predicting the likelihood of having a woman buyer.

      Table S5. Regression coefficients from OLS models predicting the final price: eBay auctions 2009 to 2012, by product category.

      Table S6. OLS regression models predicting the usage of sentiments in the listing, eBay auctions 2009 to 2012.

      Table S7. OLS regression models predicting the final price, controlling for the sentiments used:eBay auctions 2009 to 2012.

      Table S8. Gender identification of eBay users, experimental results.

      Table S9. Logistic regression model predicting the likelihood of correctly identifying the gender of eBay users.

      Table S10. The value assigned to products by the gender of seller, experimental results.

    • Supplementary Materials

      This PDF file includes:

      • According to our agreement with eBay, we cannot use, reproduce, or access the data.
      • The Stata do-file used for conducting the analysis is available online. We also provide the data and do-files for the two experiments conducted.
      • Table S1. Distribution of women and men sellers across sale platforms.
      • Table S2. Multinomial regression models predicting the sale platform, eBay 2009 to 2012.
      • Table S3. Models predicting the likelihood of various seller characteristics, choices, and rating.
      • Table S4. Logistic regression models predicting the likelihood of having a woman buyer.
      • Table S5. Regression coefficients from OLS models predicting the final price: eBay auctions 2009 to 2012, by product category.
      • Table S6. OLS regression models predicting the usage of sentiments in the listing, eBay auctions 2009 to 2012.
      • Table S7. OLS regression models predicting the final price, controlling for the sentiments used: eBay auctions 2009 to 2012.
      • Table S8. Gender identification of eBay users, experimental results.
      • Table S9. Logistic regression model predicting the likelihood of correctly identifying the gender of eBay users.
      • Table S10. The value assigned to products by the gender of seller, experimental results.

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