This paper develops identification and estimation methods for a semiparametric
dynamic logit model in which a binary outcome depends on observed covariates, the
lagged outcome, and an unknown function of a latent social characteristic that also
governs the formation of social ties. The unobserved characteristic is allowed to vary
across agents and over time, and the network formation process is left completely
unspecified. Identification combines three elements: conditional likelihood arguments
that exploit the logistic structure, network-type matching that eliminates the unknown
social influence function by comparing agents whose observed linking behavior reveals
identical latent characteristics, and local temporal smoothing that handles the interaction between dynamics and time-varying unobserved heterogeneity. A kernel-weighted
conditional maximum likelihood estimator is proposed and shown to be consistent. Its
limiting distribution is derived in two regimes: when network types and covariates have
discrete support, exact matches occur with positive probability, the localized score is
exactly centered, and the estimator is root-n consistent and asymptotically normal; in
general designs, the estimator is asymptotically normal around a pseudo-true value defined as the maximizer of the localized population criterion, the order of the matching
bias is characterized in terms of the bandwidths and the temporal drift of the latent
index, and a generalized jackknife bias correction restores centering at the true parameter, with variance formulas that account for matching on estimated codegree distances.
Monte Carlo simulations show that the estimator substantially reduces the bias present
in naive and control-function approaches across a range of network formation models
and achieves close to nominal coverage at moderate sample sizes. The method is applied to longitudinal data on adolescent smoking and friendship networks from the
Glasgow Teenage Friends and Lifestyle Study. An extension to ordered outcomes is
developed using composite conditional maximum likelihood.
This paper studies identification and estimation in semiparametric logit models when social networks are endogenous.
In many applications, unobserved individual traits shape both the outcome of interest and the formation of social ties,
so standard logit specifications, including those augmented with common network controls, can be biased. I show how network
data can be used to address this endogeneity without imposing a parametric structure on the link formation process.
Although the outcome equation is semiparametric in this social component and the network formation process is left unspecified,
the logistic distribution assumption is crucial for identification. I show that slope parameters are point identified by
pairwise comparisons of agents who share identical network formation behavior. I propose feasible estimators based on matching
agents using network similarity measures and establish their consistency and asymptotic normality. Monte Carlo simulations
demonstrate good finite-sample performance, and an empirical application to microfinance adoption demonstrates that accounting
for endogenous network formation materially affects estimated covariate effects.
This paper studies a nonseparable model for dyadic outcomes, such as bilateral trade flows, in which the outcome depends on both agents' characteristics and on a scalar unobservable through an unknown function increasing in that unobservable. I establish identification of a normalized structural function and the error distribution, propose kernel plug-in estimators, and derive a two-regime central limit theory under dyadic dependence in which a shared-agent variance component generically dominates. An agent-level bootstrap is proved consistent in that regime. Simulations show independence-based intervals undercover severely while the bootstrap substantially improves coverage. In bilateral trade data, conditional dispersion falls by more than half between small and large exporters.
African governments are widely believed to favour the ethnic group of the leader, and two in five
respondents in the pooled sample say their own group is treated unfairly by the state. We ask what
this belief responds to: what the state gives, or who holds it. Following a single question asked of
255,659 Afrobarometer respondents in 42 countries over two decades, and identifying from the 30
ethnic-group-by-country cells in eleven countries whose access to the presidency changes, we find
that gaining the presidency lowers the share of a group’s members reporting frequent unfair treatment
by 3.8 percentage points relative to other groups interviewed in the same country and round, a fifth of
the mean. Inference is at the country level, where the estimate survives a wild cluster bootstrap. Over
the same transitions, the confidence intervals rule out a favourable lived-poverty response larger than
half of the belief response and a favourable local-public-goods response larger than a third of it. In a
stacked design the response appears by the first survey round in which the group holds the presidency,
and it is precisely estimated only for competitive electoral turnovers; successions that change the
president’s ethnicity without an electoral victory are not detectably negative. We therefore cannot
separate ethnic representation from partisan victory, nor a belief about state treatment from a broader
change in perceived group standing. A co-ethnic group’s acquisition of the presidency, particularly
through a competitive electoral turnover, is associated with a substantial relative change in reported
group treatment, while the two contemporaneous material outcomes we observe respond much less.
How does public trust change across institutions during armed conflict? I argue that trust trajectories depend on institutions’ roles in the conflict and on the regional position of the citizens evaluating them. Using repeated cross-sectional Afrobarometer surveys conducted in Cameroon in 2015, 2018, 2021, and 2022, I compare the Northwest and Southwest, the core regions of the Anglophone crisis, with the adjacent West and Littoral regions. Three findings stand out. Police trust fell from about 31% to 10% in the conflict regions while rising from 39% to 47% in the comparison regions, producing a 29-percentage-point divergence; the ruling party and army display the next-largest divergences. Trust in parliament declined in both regional groups, whereas the opposition-party divergence was driven mainly by rising trust outside the conflict regions. Finally, somewhat-or-a-lot trust in traditional leaders partially rebounded by 2022, while the share reporting a lot of trust remained sharply lower. Armed conflict therefore does not produce a uniform loss of institutional confidence. By comparing eleven institutions and making each region’s trajectory visible, the paper shows how institutional roles and citizens’ regional positions together structure changes in trust.
Trust in local institutions matters for trade, public goods provision, conflict resolution, and democratic consolidation. Using individual data from rounds 6 and 7 of the Afrobarometer surveys, I document that respondents in former British colonies are substantially more likely to trust traditional leaders than respondents in former French colonies. Cross-country comparisons of this kind are confounded by unobserved heterogeneity in pre- and post-colonial histories. To make progress on identification, I focus on Cameroon, which contains regions colonized by Britain and regions colonized by France within a single modern state, and I exploit the former colonial partition line as a geographic discontinuity, comparing respondents who live close to either side of the anglophone-francophone boundary. The theoretical argument is that the two colonial powers differed systematically in how they treated customary authority: British indirect rule preserved the governance functions of chiefs, while French direct rule subordinated chiefs to the administration and assigned them its most coercive tasks, taxation and forced labor above all, and these divergent experiences shaped the legitimacy of chieftaincy in ways that persist through institutional continuity and socialization. Consistent with this argument, respondents on the formerly British side are 22 to 26 percentage points more likely to trust traditional leaders than their neighbors on the formerly French side, and they are far more likely to have contacted a traditional leader in the previous year.
WORKS IN PROGRESS
Network-Type Matching with Directed, Censored and Misreported Networks
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