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How do differences in within-country income and wealth inequality shape governments’ incentives when competing to attract mobile capital? To answer this, I develop a multi-country dynamic incomplete-markets model with an open capital market, non-cooperative tax-setting by governments, and household heterogeneity in both physical and human capital. I derive an analytical welfare decomposition that highlights the efficiency, redistributive, and tax-base erosion trade-offs governments face when setting capital taxes in such a model. The analysis shows that within-country inequalities intensify the short-run downward pressure on capital tax-rates, while long-run savings responses moderate this effect. A quantitative application to the four largest EU economies demonstrates that cross-country asymmetries in aggregate marginal propensities to consume—rooted in differences in within-country income and wealth inequality—imply that neither capital market autarky nor full tax harmonisation would receive unanimous support among governments. This provides an economic explanation for why, despite repeated initiatives and a highly integrated capital market, EU members have failed to agree on coordinated tax policies.

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I develop new perturbation methods for solving discrete time rational expectations models in which the state of the economy is an infinite-dimensional distribution. I propose a general template for such models that encompasses, as special cases, the incomplete market models that have become the mainstay of quantitative work on fiscal and monetary policy analysis, as well as spatial and trade models in which agents' decisions depend on a continuum of prices. For this broad class of models, I derive an analytical linear state-space representation that accommodates kinked decision rules and the emergence of mass-points in the endogenous distribution. My approach does not impose certainty equivalence and achieves accuracy levels comparable to global methods, even in highly nonlinear environments. These features make it particularly well-suited for studying the distributional consequences of aggregate uncertainty and long-run structural changes that are poorly approximated by dynamics close to the time-invariant steady-state. My method relies exclusively on first-order Taylor approximations, and therefore unlike other perturbation methods that rely on second-order Taylor approximations to break certainty equivalence and capture nonlinearities, its numerical implementation does not suffer from the curse of dimensionality.

Draft coming soon.

This paper studies the different mechanisms for regional risk sharing available to fiscal and monetary unions. I focus on the US, which is particularly interesting in this regard because it combines a high degree of regional economic integration with a sizeable federal tax-and-transfer system. Using methodological advances from Jain (2025), I solve a spatial HANK model that incorporates incomplete markets, wage rigidities, frictional trade between states, a realistic federal fiscal system and both demand- and supply-side sources of aggregate uncertainty. Drawing on quarterly regional data for the post-war period, I estimate the sources of US business cycle fluctuations and assess the extent of inter-state insurance. Counterfactual simulations quantify the importance of four key mechanisms shaping the nature of regional risk sharing: (i) the federal tax-and-transfer system, (ii) interstate trade costs, (iii) monetary policy, and (iv) the nature of underlying shocks.