Tax and Education Policy in a Heterogeneous-Agent Economy: What Levels of Redistribution Maximize Growth and Efficiency?
异质主体经济中的税收与教育政策:何种再分配水平使增长与效率最大化?AI 解读 ↓
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异质主体经济中的税收与教育政策:何种再分配水平使增长与效率最大化?AI 解读 ↓
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This paper studies the effects of progressive income taxes and education finance in a dynamic heterogeneous agent economy.Such redistributive policies entail distortions to labor supply and savings, but also serve as partial substitutes for missing credit and insurance markets.The resulting tradeoffs for growth and efficiency are explored, both theoretically and quantitatively, in a model which yields complete analytical solutions.Progressive education finance always leads to higher income growth than taxes and transfers, but at the cost of lower insurance.Overall efficiency is assessed using a new measure which properly reflects aggregate resources and idiosyncratic risks but, unlike a standard social welfare function, does not reward equality per se.Simulations using empirical parameter estimates show that the efficiency costs and benefits of redistribution are generally of the same order of magnitude, resulting in reasonable values for the optimal rates.Aggregate income and aggregate welfare provide only very crude lower and upper bounds around the true efficiency tradeoff.
Background: Generalized Odds (Gen Odds) provide summaries for ordinal outcomes without requiring the proportional odds assumption. However, conventional Gen Odds compares independently drawn treatment and control outcomes and targets a population-level contrast rather than an individual-level contrast. We developed an individual-level causal formulation of Gen Odds and examined its identification. Methods: We defined the Causal Gen Odds using the joint distribution of…
We develop a semiparametric continuous time inferential framework for testing cumulative treatment effects, including both immediate and carryover effects. The latent state process is modeled by an ordinary differential equation (ODE) whose drift depends on state and treatment, while the observed data are noisy measurements of this latent state at irregular, multi resolution time points. We define the average treatment effect (ATE) as the difference of expected cumulative…
Joint-event forecasts combine an estimated dependence model with current marginal forecasts. Retaining historical transforms at the marginal fits available when each outcome arrived creates overlapping estimation errors. We derive their joint influence with the terminal estimates in a stable Vine Copula VAR with normal innovation margins and a fixed, correctly specified Gaussian or positive Clayton vine. An intercept identity and the stable VAR filter reduce the historical…
当处理发生溢出:时空因果效应估计的神经网络框架
Real-world public health policies are often enacted by local jurisdictions, but their effects can ripple through connected populations. For causal evaluation, this creates a difficult spatiotemporal problem: intermittent policy updates create path-level treatments, and because spillover depends on neighboring treatment paths along with the focal-unit's own history, controlling time-varying confounding requires high-dimensional, multimodal information from both sources. To…
时空干扰下用于实验的聚类切换设计
We consider experimentation in the presence of non-stationarity, inter-unit (spatial) interference, and carry-over effects (temporal interference), where we wish to estimate the global average treatment effect (GATE), the difference between average outcomes having exposed all units at all times to treatment or to control. We suppose spatial interference is described by a graph, where a unit's outcome depends on its neighborhood's treatments, and that temporal interference is…
We study inference for continuous linear functionals of solutions to ill-posed inverse problems, including Euclidean parameters arising in nonparametric instrumental variables, proximal causal inference, and shadow-variable models. Although pointwise root-$n$ inference is possible under standard conditions, we show that this need not translate into locally reliable inference. Under a model imposing only minimal regularity conditions, the target is Hellinger discontinuous…