Women’s rights and development

Abstract

Why has the expansion of women’s economic and political rights coincided with economic development? This paper investigates this question by focusing on a key economic right for women: property rights. The basic hypothesis is that the process of development (i.e., capital accumulation and declining fertility) exacerbated the tension in men’s conflicting interests as husbands versus fathers, ultimately resolving them in favor of the latter. As husbands, men stood to gain from their privileged position in a patriarchal world whereas, as fathers, they were hurt by a system that afforded few rights to their daughters. The model predicts that declining fertility would hasten reform of women’s property rights whereas legal systems that were initially more favorable to women would delay them. The theoretical relationship between capital and the relative attractiveness of reform is non-monotonic but growth inevitably leads to reform. I explore the empirical validity of the theoretical predictions by using cross-state variation in the US in the timing of married women obtaining property and earning rights between 1850 and 1920.

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Notes

  1. 1.

    This process is far from complete globally as is clear from various indices of gender equality (see e.g. the The Global Gender Gap Report (2007) or the World Development Report (2012) devoted to gender equality and development). See Duflo (2005) for a review of the literature on gender and development.

  2. 2.

    See http://www.womeninworldhistory.com.

  3. 3.

    Women today do not enjoy full property rights in several parts of the world, both de jure and de facto.

  4. 4.

    I create a measure of the relevant fertility variable by considering only children above the age of ten as during this time period there was a high degree of child mortality.

  5. 5.

    See, for example, Fogel and Engerman (1974), Galor and Moav (2006), Doepke and Zilibotti (2005), and (Lizzeri and Persico (2004). An alternative view is that rights are ceded in order to forestall revolts (e.g., Acemoglu and Robinson 2000)

  6. 6.

    See, e.g., Edlund and Pande (2002) for evidence on the existence of a gender gap in voting behavior.

  7. 7.

    In 1880, for example, the labor force participation of white married women in the US between the ages of 30 and 40 was below 3 % and rose very slowly over the following 4–5 decades (see Fernández 2011).

  8. 8.

    Kahn investigated the effect of the reforms of women’s property rights on women’s patenting activity.

  9. 9.

    Although Doepke and Tertilt (2009) frame their discussion as fathers’ caring about their daughters, this factor doesn’t play a critical role in their analysis. In particular, if men cared only about their sons the results would go through. What mattes in their model is inefficiently low investment in human capital and finding a way to commit to a higher level of this investment.

  10. 10.

    See Lundberg (2005) for an excellent review of the literature on sons, daughters, and parental preferences.

  11. 11.

    From Blackstone (1765–1769), Book 1, Chap. 15., p. 431.

  12. 12.

    Real property is defined as any property that is attached directly to land, as well as the land itself.

  13. 13.

    See Doepke and Tertilt (2009) for a review of the expansion of some of these rights in the US and England.

  14. 14.

    Mississippi was the first state to pass a married women’s property act in 1839.

  15. 15.

    Furthermore, as will be made clear in Sect. 3.5, the type of paternalism required by the theory is straightforward. In particular, fathers need not care about their grandchildren via their daughter’s utility function as in Doepke and Tertilt (2009)—it is sufficient that they care about their daughter’s utility from consumption.

  16. 16.

    Warbasse (1987), p. 229.

  17. 17.

    This assumption makes the model analytically tractable. In a model with endogenous fertility one could still examine the comparative static properties of variables that change desired fertility (e.g., by modifying an exogenous component of the cost associated with fertility, such as urbanization).

  18. 18.

    This is a fairly standard assumption (see, e.g., Doepke and Tertilt (2009)).

  19. 19.

    See Gall et al. (2009) for a more general discussion of when efficiency obtains in models with non-transferable utility.

  20. 20.

    The externality from a bequest to a child comes from the fact that it also makes her/his spouse better off. This is not taken into account by a parent who is only maximizing parental and child’s welfare. A competitive market internalizes the spouse’s welfare by bidding up the “price” (in the model, the bequest level) one must pay in order to get married. In a random matching marriage market, by way of contrast, there is no price for marriage. Hence investments are inefficient.

  21. 21.

    N.B.: This is simply a method to solve for the efficient equilibrium level of bequests; it is not a description of the marriage market. Agents are not marrying their siblings.

  22. 22.

    We will impose conditions such that the value function is well defined.

  23. 23.

    The same first-order condition is obtained for \(k_{h}^{\prime }\) and \(k_{w}^{\prime }\).

  24. 24.

    Note that all women bring the same capital endowment to the marriage market (as do all men). Thus, unlike in the case of a non-degenerate household capital distribution, solving for equilibrium does not require a condition guaranteeing that a father would not want to marginally increase/decrease a bequest so that his son/daughter gets a different match.

  25. 25.

    To see this right away, note that if a father with capital \(k\) were to bequeath each son-daughter pair \(k\), this would yield him consumption \(c_{h}=Ak-nk-\underline{c}\). This expression must be positive since, by \(A2,\,k^{\prime }>k\) and by \(A1,\,c_{h}>\underline{c}\).

  26. 26.

    If each generation faced instead the option of reforming the regime that period or postponing the choice to the following generation, I conjecture that the Markov Perfect equilibrium would have each generation mixing over whether to reform with a probability that is a function of \(k\).

  27. 27.

    Note that modifying the model to include an endowment of a household good \(z\) and preferences given by \(U_{i}=u(z_{i})+\log c+\beta \left( \frac{U_{h}^{\prime }+U_{w}^{\prime }}{2}\right) , z_{w}+z_{h}=z\), guarantees \(V_{h}^{NR}\left( k\right) > V_{h}^{ER}\left( k\right) \) for \(u^{\prime }(z)\) sufficiently large. Under the NR regime, the husband would set \(z_{h}=z\), whereas under ER, \(z_{h}=z_{w}=z/2\).

  28. 28.

    Why does the effect on \(\Delta V_{h}\) of an increase in \(k\) depend on the initial level of \(k\) whereas the effect of a decrease in \(n\) is always negative? Note that the first is an income effect whereas the second is a price effect—it becomes less expensive to increase the average welfare of a man’s children.

  29. 29.

    Results available from the author on demand.

  30. 30.

    The authors use a Cobb–Douglas production function in husband’s and wife’s human capital (each proportional to the time spent producing rather than rearing children).

  31. 31.

    This discussion is a bit loose as one needs to show that the same investment rule would be followed.

  32. 32.

    One can think of the timing of reform as being probabilistic by adding a random variable \(\varepsilon _{it}\) to men’s relative valuation of the two regimes, \(\Delta V_{h}\), in state \(i\) at time \(t\).

  33. 33.

    See the discussion in Sect. 3.5.

  34. 34.

    Another possible specification is a hazard model although the theory does not call for it since, had the key variables evolved differently, reform could have been overturned. While this did not occur in the US, it has happened elsewhere (see, e.g., Przeworski (2007) for a discussion of how the extension of the suffrage in France or Spain was overturned several times). In addition to this objection, there are several other reasons why a hazard model is not included. First, as will be seen later, some states were part of territories during portions of this time period raising the issue of how duration for these states should be measured. Second, and more importantly, state fixed-effects cannot be incorporated in this specification, raising the usual omitted variable issue.

  35. 35.

    I thank the authors for providing me with the data set containing the timing of the reforms and several state variables.

  36. 36.

    See their working paper (2000) for details on the construction of this variable.

  37. 37.

    Alaska and Hawaii are excluded from the analysis.

  38. 38.

    See Haines (2008). The decrease in mortality was large in every decade with the exception of 1880.

  39. 39.

    A more traditional definition is to include women from age 15 to 44 but I use a tighter age range since I am looking at changes from decade to decade. As shown in the robustness section, the results are robust to the choice of alternative age ranges.

  40. 40.

    I wish to thank Michael Haines for providing me with the raw census data to perform these calculations.

  41. 41.

    This variable was constructed by Geddes and Lueck (2002) to test their hypothesis. See their working paper (2000) for details on how the data was deflated to 1982 dollars. The wealth data is from a special Census publication published in 1924 that compiled all Census wealth estimates from 1850 to 1922 (Wealth, Public Debt and Taxation 1922).

  42. 42.

    Note that it is important not to over-represent states by assigning to each one individually the variable outcome that belongs to the aggregate territory. There is an error in this respect in Geddes and Lueck (2002), though it does not appear to affect the conclusions of the analysis (see Table 2).

  43. 43.

    Basch (1982), pp. 16–17 cites nineteenth century legal analysts as noting that in no other area was the correspondence between the American and English legal systems closer than in the law of wife and husband.

  44. 44.

    See Bishop (1873) for a thorough discussion of how common law and equity differed.

  45. 45.

    The states are: CT, DE, ME, MD, MA, MI, MN, NJ, NH, NJ, NY, RI, SC, and VT.

  46. 46.

    See Salmon (1986) and Chused (1983).

  47. 47.

    The states are: AZ, CA, ID, LA, NV, NM, TX, and WA. See Warbasse (1987) for the experience of Louisiana which was the sole state that had this system in the first quarter of the nineteenth century. See Glaeser and Shleifer (2002) for a discussion of the important differences in other arenas between the English common law and French civil law.

  48. 48.

    If wealth was not required, then the sample size could be increased by three observations. Since the increase was so small, I keep the same 356 sample throughout.

  49. 49.

    The number of observations changes over time since some states were not yet part of the US in some decades and because wealth data was unavailable for some states (territories) in the earliest decades.

  50. 50.

    Throughout, instead of using the raw standard deviation of the variable, I use the SD of the residuals from a regression of the pertinent variable (e.g. wealth) on the relevant fixed effects (e.g., on year dummies or on both year and state dummies). The magnitudes of these are reported in Table 10.

  51. 51.

    See http://en.wikipedia.org/wiki/Territorial_evolution_of_the_United_States.

  52. 52.

    At this point in time, North and South Dakota are not distinct—they constitute Dakota.

  53. 53.

    Using a Probit specification instead drops over 100 observations. The results go through as well with robust standard errors corrected for clustering at the state level.

  54. 54.

    The SD of fertility net of the variation from year and state fixed effects is 0.21.

  55. 55.

    I have also experimented with using other measures that may proxy for wealth. For example, columns 4 and 5 in Table 8 control for the percentage of school-age children (excluding slaves) that attend school. As shown, neither schooling measure is statistically significant.

  56. 56.

    On the other hand, if there is variance in the child mortality rate, risk aversion may lead to a positive correlation.

  57. 57.

    The American experience is distinctive from most other Western countries in that its fertility decline started very early (in the late eighteenth or early nineteenth century) and it preceded the mortality decline. See Haines (2008).

  58. 58.

    I wish to thank Robert Tamura for very kindly making this data available to me.

  59. 59.

    The authors use a fairly complicated procedure to produce their estimates. For each state/territory, they run a quadratic specification of the infant survival rate on time for the years 1890–2000 using the number of observations that exist in the official death registration data (this ranges from a maximum of 12 observations for Massachusetts to seven for Texas). This allows them to obtain extrapolated predictions for infant mortality for each state between 1850 and 1920. They then combine these predictions with the Census data on infant mortality between 1850 and 1920 for each state, and find the convex combination, for each census year, that when aggegated (with appropriate population weights) across states best matches the national infant mortality rate reported in the Historical Statistics of the United States. This procedure yields, for each state and year, their estimate of infant mortality. For measures of mortality to age ten, they apply the same weights obtained for infant mortality on the age-appropriate Census data and death registration extrapolations. See Murphy et al. (2008) for more details.

  60. 60.

    See Preston and Haines (1991) for a thorough account.

  61. 61.

    Preston and Haines (1991), p. 12.

  62. 62.

    What then is driving the variation in child mortality across states? From my reading of the literature, there appears to have been a great deal of idiosyncratic variation in the rate in which municipalities adopted sanitation reforms though it would be good to have systematic evidence for this.

  63. 63.

    All quantitative statements using standard deviations are of SDs net of the variation due to state and year fixed effects.

  64. 64.

    Massachusetts passed the first compulsory school attendance laws in 1852, followed by New York in a year later.

  65. 65.

    The data is from the Department of Education, National Center for Educational Statistics, Digest of Education Statistics, 2004. A table can be found at http://www.infoplease.com/us/states/compulsory-school-attendance-laws.html. The years coincide with those used by Goldin and Katz (2008).

  66. 66.

    See Chused (1983).

  67. 67.

    To calculate the correlation, the states that voted against women’s suffrage and were forced to allow women to vote when the 19th amendment was passed in 1920 were assigned 1930. Similar results are obtained if they are assigned the year 1925. For the regression analysis, the states that voted against women’s rights were assigned a zero in 1920. Note that in general property rights preceded voting rights: only five states allowed women to vote prior to the reform of property rights.

  68. 68.

    In this specification, as in others with state fixed effects, the coefficient on community is not statistically significant. The same specification but with regional rather than state fixed effects restores significance. This is true for all the specifications that follow as well.

  69. 69.

    Women were asked to report all live births.

  70. 70.

    The omitted category is Black and thus the sample contains women from other races but these constitute around a half percent of the sample. Throughout I use person weights.

  71. 71.

    See Shammas et al. (1987). In England, dower rights for women shrank over time before the reform of married women’s property rights.

  72. 72.

    See Lagerlof (2009) for an interesting recent attempt to study the endogenous evolution of property rights in land and people (slavery).

  73. 73.

    See Edlund and Lagerlof (2006), Iyigun and Walsh (2007b) and Tertilt (2006) for interesting work in this area. See Coontz (2005) for a history of marriage.

  74. 74.

    In this case, endogenously different political preferences of men and women may come into play (see, e.g., Edlund and Pande (2002)).

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Acknowledgments

I wish to thank Matthias Doepke, Lena Edlund, Murat Iyigun, Shelly Lundberg, and Matt Wiswall for helpful suggestions on an earlier version which has now been substantially revised. I thank Joyce Cheng Wong and Eduardo Zilberman for providing excellent research assistance and the NSF and the Russell Sage Foundation for financial support. I thank the EIEF for their hospitality during the time I was revising this paper.

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Correspondence to Raquel Fernández.

Appendix

Appendix

Proofs of Lemmas 1 and 2

To prove Lemmas 1 and 2, I guess the following functional forms for the value functions:

$$\begin{aligned}&V_{h}^{NR}\left( k_{h},\widetilde{k}_{h}\right) =a_{h}+b_{h}\log \left( k_{h}+\widetilde{k}_{h}-\frac{\underline{c}}{d}\right) \end{aligned}$$
(31)
$$\begin{aligned}&V_{w}^{NR}\left( k_{w},\widetilde{k}_{w}\right) =a_{w}+b_{w}\log \left( k_{w}+\widetilde{k}_{w}-\frac{\underline{c}}{d}\right) \end{aligned}$$
(32)
$$\begin{aligned}&V_{h}^{ER}\left( k_{h},\widetilde{k}_{h}\right) =\phi +\theta \log \left( k_{h}+\widetilde{k}_{h}\right) \end{aligned}$$
(33)
$$\begin{aligned}&V_{w}^{ER}\left( k_{w},\widetilde{k}_{w}\right) =\phi +\theta \log \left( k_{w}+\widetilde{k}_{w}\right) \end{aligned}$$
(34)

where \(\left\{ a_{h},b_{h},a_{w},b_{w},d,\phi ,\theta \right\} \) is the set of parameters that will be solved for using the method of undetermined coefficients. Recall that \(k=k_{w}+\widetilde{k}_{w}\) and that to solve for the efficient equilibrium we impose \(\widetilde{k}_{h}^{\prime }\equiv k_{w}^{\prime }\) and \(\widetilde{k}_{w}^{\prime }\equiv k_{h}^{\prime }\) before optimizing. Substituting (31) and (32) in the RHS of (3) and (4), and substituting (33) and (34) in the RHS of (16), one obtains

$$\begin{aligned} V_{h}^{NR}(k)&= \underset{c_{h},k_{h}^{\prime },k_{w}^{\prime }}{Max}\left\{ \log c_{h}+\frac{\beta }{2}\left[ a_{h}+a_{w}+\left( b_{h}+b_{w}\right) \log \left( k_{h}^{\prime }+k_{w}^{\prime }-\frac{\underline{c}}{d}\right) \right] \right\} \qquad \\ \text {s.t.} \ \ \ \ Ak&= c_{h}+\underline{c}+nk_{h}^{\prime }+nk_{w}^{\prime } \nonumber \end{aligned}$$
(35)
$$\begin{aligned} V_{w}^{NR}(k)=\log \underline{c}+\frac{\beta }{2}\left[ a_{h}+a_{w}+\left( b_{h}+b_{w}\right) \log \left( k_{h}^{\prime }+k_{w}^{\prime }-\frac{\underline{c}}{d}\right) \right] \end{aligned}$$
(36)
$$\begin{aligned} V_{h}^{ER}(k)+V_{w}^{ER}(k)&= \underset{c_{h},c_{w},k_{h}^{\prime },k_{w}^{\prime }}{Max}\left\{ \log c_{h}+\log c_{w}+2\beta \left[ \phi +\theta \log \left( k_{h}^{\prime }+k_{w}^{\prime }\right) \right] \right\} \nonumber \\ \text {s.t.} \ \ \ \ Ak&= c_{h}+c_{w}+nk_{h}^{\prime }+nk_{w}^{\prime } \end{aligned}$$
(37)

Taking the first-order conditions with respect to \(c_{h},c_{w},k_{h}^{\prime }\) and \(k_{w}^{\prime }\), yields the following optimal policies.

$$\begin{aligned} c_{h}^{NR}&= \frac{Ak-\underline{c}-\frac{n\underline{c}}{d}}{1+\frac{\beta }{2}\left( b_{h}+b_{w}\right) }\\ k_{NR}^{\prime }&= \frac{1}{n}\frac{\frac{\beta }{2}\left( Ak-\underline{c}\right) \left( b_{h}+b_{w}\right) +\frac{n\underline{c}}{d}}{1+\frac{\beta }{2}\left( b_{h}+b_{w}\right) }\\ c_{w}^{ER}&= c_{h}^{ER}=\frac{1}{2}\frac{Ak}{1+\beta \theta }\\ k_{ER}^{\prime }&= \frac{1}{n}\frac{\beta \theta Ak}{1+\beta \theta } \end{aligned}$$

We are now set to use the method of undetermined coefficients for the NR regime by substituting the optimal policies and the value functions in the RHS of (35) and (36), obtaining:

$$\begin{aligned}&a_{h}+b_{h}\log \left( k-\frac{\underline{c}}{d}\right) =\log \frac{Ak-\underline{c}-\frac{n\underline{c}}{d}}{1+\frac{\beta }{2}\left( b_{h}+b_{w}\right) }\nonumber \\&\quad +\frac{\beta }{2}\left[ a_{h}+a_{w}+\left( b_{h}+b_{w}\right) \log \left( \frac{1}{n}\frac{\frac{\beta }{2}\left( Ak-\underline{c}\right) \left( b_{h}+b_{w}\right) +\frac{n\underline{c}}{d}}{1+\frac{\beta }{2}\left( b_{h}+b_{w}\right) }-\frac{\underline{c}}{d}\right) \right] \end{aligned}$$
(38)
$$\begin{aligned}&a_{w}+b_{w}\log \left( k-\frac{\underline{c}}{d}\right) =\log \underline{c}\nonumber \\&\quad +\frac{\beta }{2}\left[ a_{h}+a_{w}+\left( b_{h}+b_{w}\right) \log \left( \frac{1}{n}\frac{\frac{\beta }{2}\left( Ak-\underline{c}\right) \left( b_{h}+b_{w}\right) +\frac{n\underline{c}}{d}}{1+\frac{\beta }{2}\left( b_{h}+b_{w}\right) }-\frac{\underline{c}}{d}\right) \right] \end{aligned}$$
(39)

Following the same procedure for the ER regime yields:

$$\begin{aligned} 2\left[ \phi +\theta \log k\right] =2\log \frac{1}{2}\frac{Ak}{1+\beta \theta }+2\beta \left[ \phi +\theta \log \left( \frac{1}{n}\frac{\beta \theta Ak}{1+\beta \theta }\right) \right] \end{aligned}$$
(40)

After some lengthy algebra, we obtain:

$$\begin{aligned} a_{h}&= \frac{\left( 1-\frac{\beta }{2}\right) \log \frac{A\left( 1-\beta \right) }{\left( 1-\frac{\beta }{2}\right) }+\frac{\beta }{2}\log \underline{c}+\frac{\beta /2}{\left( 1-\beta \right) }\log \left( \frac{A}{n}\frac{\beta /2}{\left( 1-\frac{\beta }{2}\right) }\right) }{\left( 1-\beta \right) } \\ b_{h}&= \frac{1-\beta /2}{1-\beta } \\ a_{w}&= \frac{\frac{\beta }{2}\log \frac{A\left( 1-\beta \right) }{\left( 1-\frac{\beta }{2}\right) }+\left( 1-\frac{\beta }{2}\right) \log \underline{c}+\frac{\beta /2}{\left( 1-\beta \right) }\log \left( \frac{A}{n}\frac{\beta /2}{\left( 1-\frac{\beta }{2}\right) }\right) }{\left( 1-\beta \right) } \\ b_{w}&= \frac{\beta /2}{1-\beta } \\ d&= A-n \\ \phi&= \frac{\log \left( 1-\beta \right) \frac{A}{2}+\frac{\beta }{\left( 1-\beta \right) }\log \beta \frac{A}{n}}{\left( 1-\beta \right) } \\ \theta&= \frac{1}{1-\beta } \end{aligned}$$

Descriptive statistics and correlations

see Tables 10 and 11

Table 10 Descriptive statistics
Table 11 Correlations

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Fernández, R. Women’s rights and development. J Econ Growth 19, 37–80 (2014). https://doi.org/10.1007/s10887-013-9097-x

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Keywords

  • Women’s rights
  • Development
  • Property rights
  • Fertility
  • Patriarchy