I propose a novel argument to identify economically interpretable intertemporal treatment effects in dynamic regression discontinuity designs (RDDs). Specifically, I develop a dynamic potential outcomes model and reformulate two assumptions from the difference-in-differences literature—no anticipation and common trends—to attain point identification of cutoff-specific impulse responses. The estimand of each target parameter can be expressed as the sum of two static RDD contrasts, thereby allowing for nonparametric estimation and inference with standard local polynomial methods. I also propose a nonparametric approach to aggregate treatment effects across calendar time and treatment paths, leveraging a limited path independence restriction to reduce the dimensionality of the parameter space. I apply this method to estimate the dynamic effects of school district expenditure authorizations on housing prices in Wisconsin.

We study how informal family caregiving and formal care interact after severe parental health shocks, and whether they operate as substitutes or complements. Using Danish administrative data, we compare parents of only children who experience a stroke at the same age and differ only in the gender of their child. Before the stroke, parents of daughters and parents of sons follow similar health trajectories, with comparable levels of pre-existing conditions and healthcare utilization. After the stroke, a survival gap opens and grows, and parents of daughters are 1.5 percentage points more likely to be alive by year five. Over the same period, daughters adjust more than sons along several margins: they become more likely to live near their parents, less likely to be married, and have fewer children, consistent with greater involvement in informal caregiving. Crucially, parents of daughters use more physical rehabilitation, an elective type of formal care that requires sustained engagement. Rather than crowding out formal provision, daughters appear more likely to help parents navigate and use professional services. Informal and formal care can therefore operate, at least in part, as complements in the response to severe health shocks.

Local governments in the United States are vertically differentiated: in a given location, multiple overlapping jurisdictions provide distinct local public services and draw revenue from shared portions of the property tax base. This paper estimates the fiscal spillovers generated by this structure and proposes a mechanism that internalizes them in local policy choice. I assemble a new georeferenced dataset covering the universe of local government boundaries and nominal property tax rates nationwide over the past two decades. Using a dynamic regression discontinuity design, I estimate fiscal spillovers from narrowly approved property tax referenda. To extrapolate beyond effects identified at the approval threshold, I develop a spatial equilibrium model with overlapping jurisdictions and majority voting over the provision of local public goods. I use the model to quantify spillovers for all school districts and municipal governments in the United States and find sizable effects. I then evaluate a policy that (i) informs voters about cross-jurisdiction spillovers and (ii) applies symmetric intergovernmental transfers (taxes or subsidies) upon approval of a spending change. The counterfactual regime yields aggregate welfare gains.

We propose a structural approach to extrapolate average partial effects away from the cutoff in regression discontinuity designs (RDDs). Our focus is on applications that exploit closely contested school district referenda to estimate the effects of changes in education spending on local economic outcomes. We embed these outcomes in a spatial equilibrium model of local jurisdictions in which fiscal policy is determined by majority rule voting. This integration provides a microfoundation for the running variable—the share of voters who approve a ballot initiative—and enables identification of structural parameters using RDD coefficients. We then leverage the model to simulate the effects of counterfactual referenda over a broad range of proposed spending changes. These scenarios imply realizations of the running variable away from the threshold, allowing extrapolation of RDD estimates to nonmarginal referenda. Applying the method to school expenditure ballot measures in Wisconsin, we document substantial heterogeneity in housing price capitalization across the approval margin.

I construct a novel, granular georeferenced dataset on the universe of local governments in the United States and their property tax rates from the early 2000s to 2022. Using this dataset, I present new descriptive insights on the geography of the property tax. First, property tax rates exhibit substantial variation within states, surpassing that of any other local tax. Second, rates are higher in locations where a greater number of jurisdictions overlap and thus share tax base. Third, rates are higher in areas with larger dispersion in property values and greater racial and ethnic heterogeneity. Fourth, new local taxing jurisdictions are more likely to be formed in locations where the distribution of income is more even and dispersion in housing values is lower.