future by observing marriages that have recently taken place in their reference group, i.e., their marriage market.

We assume that the relevant marriage markets are based on caste (and religion) and state. This is a reasonable assumption given the highly endogamous nature of the Indian marriage market. In the 2005 IHDS, only 4.4 percent of women were married to a spouse from a different caste.<sup>16</sup> In fact, genetic evidence suggests that the practice of endogamy in India is several thousand years old (Moorjani P. (2013)). In addition to this “horizontal” preference for same-caste marriages, inter- _jati_ marriages are governed by strict rules of hierarchy. Although caste is primarily a Hindu phenomenon, the notion of caste-based hierarchy remains well-preserved among many other religious groups in India.<sup>17</sup> Inter-religious marriages are even less common than inter-caste marriages. While patrilocal exogamy is widely practiced, most people marry within their state. To illustrate, less than 4 percent of the population had moved across states in the last ten years according to the 2001 Census data.<sup>18</sup> Consequently, we define expected dowry as the average net dowry paid by brides or received by grooms from the same caste and state as the child and who married during the year of the child’s birth or the prior four years.<sup>19</sup> This definition essentially assumes that parents have static or adaptive expectations, i.e., they expect the value of dowry next period to be equal to the weighted average of dowry in the past few periods. If dowry follows a random walk, then the static expectation is also the rational expectation. We explicitly test if the dowry data follows a random walk by performing the modified Dickey-Fuller _t_ test for a unit root in which the series has been transformed by a generalized least-squares regression. The results (in Table A.2) show that the null hypothesis of a unit root or random walk is not rejected for all lags in the model.

Our expected dowry variable does not take into account any expectations about inflation that the parents may have. However, previous research (Maertens and Chari (2012)) suggests that households are likely not factoring inflation into their dowry forecasts as their average willingness-to-pay does not increase as they reach closer to the wedding date.

Although, _jati_ is the relevant caste variable for the Indian marriage market, we use 4 broader caste categories: upper castes, SCs, Scheduled tribes (STs), and Other Backward Classes (OBCs). This is because our estimation sample is small relative to the number of jatis, resulting in very 16Using responses to matrimonial advertisements in a Bengali newspaper, Banerjee et al. (2013) find evidence in favor of a strong preference for in-caste marriage – e.g., the bride’s family is willing to trade-off the difference between no education and a master’s degree in the prospective husband to avoid marrying outside their caste. Also see Borker et al. (2017).

> 17For instance, in the 2009 National Sample Survey, 31 percent of Sikh households identified themselves as belonging to a Scheduled Caste (SC).

> 18Similarly, among individuals aged 25 years or older surveyed in the 2008 National Sample Survey, 89 percent of women and 93 percent of men lived in the same state where they were born.

> 19We trim off the top 1 percent of dowry payments before constructing the expected dowry variable. Later, as robustness checks, we use two alternate definitions of dowry by changing the years over which the average is calculated and by using both caste and religion to define the marriage market.

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