Cross-Sibling Linkages in the Marriage Market

There is no field intervention in the conventional sense: this is a survey experiment in which the experimental variation is embedded in hypothetical vignettes administered within the interview. Each respondent evaluates a series of marriage-market scenarios in which we experimentally vary the circumstances of a hypothetical family, including the quality of a proposed match, the composition of the family's children, and the spacing between daughters. Respondents state beliefs about marriage-market outcomes and make advisory choices for these hypothetical families. Scenario content and presentation order are randomised across and within respondents. All scenarios concern fictional families.

The survey has three experimental modules administered, any 2 of which are administered to a respondent in one face-to-face sitting, along with a demographic questionnaire and a closing questionnaire on marriage norms.

Respondents are screened into one of two belief modules: those with at least two daughters are eligible for the bride-side module, and those with at least one son are eligible for the groom-side module; where a household satisfies both screens, assignment follows the pre-printed respondent identifier.

In the bride-side module, respondents advise the parents of two unmarried daughters who receive a proposal for the elder daughter requiring a gift transfer exceeding half of the family's lifetime marriage savings. Respondents are presented with eight scenarios in which we vary: the proposed groom's quality (Medium vs High), the presence of a brother (brother vs no brother), and the age gap between the daughters (2 vs 5 years), creating a 2 x 2 x 2 full factorial. In each scenario, respondents report: whether to accept the proposal; the expected distribution of the younger daughter's future match opportunities across three groom types had the elder daughter accepted; the effect of the elder's match on how groom-side families view the family; and the gift value the younger would require to marry a high-quality groom had the elder married the proposed groom.

In the groom-side module, respondents advise the parents of a son receiving marriage proposals (we vary the qualifications of the son in line with Medium vs High descriptors from the bride module, between respondents). They evaluate a proposal for the younger daughter of a family where the elder daughter has married, but her match is initially unknown. Phase 1 comprises two baseline scenarios, one with and one without a brother, presented in counterbalanced order. The initial offer is half of the family's lifetime marriage savings (0.5W). Respondents state their likelihood to accept and their reservation gift value to accept this match. In Phase 2, the elder daughter's realised match is revealed (High, Medium, or Low) with the offer adjusted (0.3W, 0.4W, 0.7W respectively), in six scenarios (3 match types x 2 brother categories) whose order follows a 6 x 6 Williams design. Respondents restate acceptance likelihood (0-10), their reservation gift value, and also report how they view the family as a result of the elder's realised match.

The allocation module is administered to all respondents. Respondents choose between an unequal split of the family's marriage savings favouring the elder daughter or an equal split, with both daughters' resulting match qualities fully specified on a 7-point ladder. Cells vary whether the unequal split generates a cross-sibling gain, the age gap, and brother status (none, non-contributing, contributing). Each respondent answers six of twelve potential budget-allocation cells (2 x 2 x 3), drawn from 24 pre-generated configurations balanced so that each cell is seen by an equal number of respondents. Because outcomes are supplied, choices reveal allocation preferences uncontaminated by beliefs about the mapping from budgets to matches.

Finally, we vary family lifetime marriage wealth/savings 'W' (Rs. 2,50,000 or 5,00,000), the unequal split level required to facilitate a match (60%-40% or 70%-30%), and the quality of son being advised (High vs Medium) at the block level between respondents - assigned from pre-generated lists balanced within sampling units.

2026-07-16

2026-08-05

Bride-side module: (i) acceptance of the elder daughter's proposal; (ii) the believed distribution of the younger daughter's match opportunities across groom types; (iii) the perceived reputation effect of the elder's match; (iv) the believed gift value required for the younger daughter to marry a fixed high-quality groom.

Groom-side module: (v) acceptance likelihood (0-10); (vi) the reservation gift value at which the respondent would advise accepting the match; (vii) the updated assessment of the proposing family.

Allocation module: (viii) the binary choice between the unequal and equal budget split.

We are interested in three constructed objects. First, a respondent-level spillover belief index, constructed using within-respondent contrasts in the bride-side module. The change in the believed high-type share (outcome ii) and in the required gift for the younger daughter (outcome iv) as the elder daughter's proposed match varies across scenarios, holding all else fixed by construction. Second, a market-updating measure on the groom side. The within-respondent change in the reservation gift (outcome vi) between the baseline phase and each revealed elder-match state, interpretable as a revealed willingness to pay for family reputation; the belief-versus-market wedge is the difference between the bride-side dowry contrast and this groom-side contrast. Third, a belief-action pass-through coefficient. In the allocation module, the interaction between the respondent's spillover belief index and cell characteristics that reward tilting the budget toward the elder daughter; the shortfall of this interaction from full pass-through, in cells where tilting is stipulated to be advantageous, measures the extent to which fairness preferences over unequal giving block belief-consistent allocation.

The study is a within-subject vignette experiment conducted using a face-to-face survey of parents in two districts of Uttar Pradesh, sampled from 26 localities. Eligible respondents are assigned to one of two belief modules according to the composition of their own children, and all respondents complete a common budget-allocation module. Scenario attributes vary within respondent according to a full factorial design; scenario order is balanced across respondents using Williams Latin square designs, so that each scenario appears in each position, and follows every other scenario, with equal frequency. All experimental assignments are pre-generated by seeded computer routines, linked to anonymised respondent identifiers, and delivered automatically by the electronic survey instrument; neither enumerators nor respondents influence any assignment.

Assignment structure: Each sampled locality (PSU) contains 28 pre-assigned respondent identifiers: numbers 1-14 for the bride-side sample and 15-28 for the groom-side sample, of which 10 per side per PSU are targets and the remainder buffer. Every identifier carries a pre-generated assignment row specifying a wealth-split block (W in {2,50,000; 5,00,000} x split in {60-40; 70-30} on the bride side; W x son type on the groom side, with the allocation split assigned orthogonally within block), a scenario-order row from an 8 x 8 (bride) or 6 x 6 (groom) Williams Latin square, a Phase-1 counterbalance (groom side), and six of the twelve allocation cells drawn from 24 balanced configurations. Assignments are balanced within PSU (block counts, order frequencies, no duplicate questionnaire profiles within a PSU) and globally (equal block counts; each allocation cell seen by an equal number of respondents). The electronic form retrieves all assignments by respondent identifier; identifiers failing lookup are rejected at entry.

Identification: Bride-side belief parameters are identified from within-respondent variation across the eight scenarios with respondent fixed effects; block-level magnitudes are absorbed and are used for heterogeneity. Groom-side updating is identified from within-respondent Phase 1 to Phase 2 changes. The allocation analysis interacts the respondent-level belief index with cell attributes; cells in which the unequal option compresses the outcome gap and raises total attainable match quality separate preferences over unequal allocation from preferences over unequal outcomes.

Piloting: Instruments are being revised after a small pilot (wording, screen layout, a hesitation protocol for reservation-gift questions, and consistency prompts for logically inconsistent likelihood-reservation pairs); the registered instruments are the pre-pilot versions, which may be altered after the pilot has concluded.

Randomisation done using computer program seeded scripts generate all assignments (blocks, orders, allocation configurations) attached to pre-printed respondent identifiers; Williams Latin square designs govern within-respondent scenario order.

All experimental assignments are at the individual respondent level. Between-respondent factors (wealth-split block; groom-side son type; allocation split; allocation cell configuration) and within-respondent presentation orders (Williams Latin square rows; Phase-1 counterbalance) are assigned to anonymised respondent identifiers in pre-generated lists, stratified and balanced within primary sampling unit (locality). Sampling, as distinct from experimental assignment, is clustered: localities are selected by systematic PPS within district, and respondents are recruited within locality subject to screening; no treatment is assigned at the cluster level.

No

We survey in 2 districts in Uttar Pradesh (Lucknow and Prayagraj). We intend to sample from 9 urban wards and 4 villages in Lucknow district, and from 3 urban wards and 10 villages in Prayagraj district - to maintain district representativeness. We survey 20 respondents - who meet screening criteria -from each ward.

Each Bride-Side respondent provides : 32 responses from the Belief Module and 6 responses from the Allocation Choice Module. Thus a total of 38 responses. Each Groom-Side respondent provides : 22 responses from the Belief Module and 6 responses from the Allocation Choice Module. Thus a total of 28 responses.

Approximately 500 total respondents: 250 Bride-Side respondents and 250 Groom-side respondents.