Behavioral response, plan sorting, and financial protection in health insurance markets

In both developed and developing countries, it is important to know about consumer behavior in the health insurance market. The first essay analyzes the behavioral response to income cutoffs of a subsidized health insurance program in the Massachusetts reform. Subsidies in the program are based on household income and have explicit income cutoffs. This feature creates nonlinear budget constraints for households' consumption, and potentially distorts their income and labor supply. I test the existence of income manipulation using the regression discontinuity approach on data from the American Community Survey. I find clear evidence of income discontinuity around the cutoffs of 150% and 300% of the Federal Poverty Level. I construct a structural model to estimate the elasticity of labor supply with respect to wage rates using the discontinuity evidence, suggest a methodology to calculate the welfare loss, and project the magnitude of behavioral response in the national health reform. The second essay analyzes consumer choice of health insurance plans after U.S. health reform. In the new state-run "Health Insurance Exchanges" created as part of the Affordable Care Act, plans with different benefit coverage of health care costs are provided in order to expand consumer choices and increase consumer welfare. According to the Act, premiums can differ based on enrollees' characteristics and plan revenues are risk-adjusted by regulators who transfer revenue from low to high risk plans. This essay examines how risk adjustment and premium discrimination affect consumers' choices of plans theoretically and empirically. I find that under plausible conditions risk adjustment and premium discrimination encourage consumers to enroll in plans with high benefit coverage. The third essay studies how a new Chinese rural health insurance program affects adverse selection and impacts enrollees' out-of-pocket costs. Using a national four-year panel dataset to address households' participating behavior and the impact of the plan, I show that adverse selection was not severe at household level, and the impact of the program on reducing out-of-pocket expense is greater for the rich than that for the poor, although on average was not statistically significant

On the Connections between Intertemporal and Intra-temporal Trades

This paper develops a new theory of international economics by introducing Heckscher-Ohlin features of intra-temporal trade into an intertemporal trade approach of current account. To do so, we consider a dynamic general equilibrium model with tradable sectors of different factor intensities, which allows for substitution between intertemporal trade (current account adjustment) and intra-temporal trade (goods trade). An economy's response to a shock generally involves a combination of a change in the composition of goods trade and a change in the current account. Flexible factor markets reduce the need for the current account to adjust. On the other hand, the more rigid the factor markets, the larger the size of current account adjustment relative to the volume of goods trade, and the slower the speed of adjustment of the current account towards its long-run equilibrium. We present empirical evidence consistent with the theory.

Entanglement-guided architectures of machine learning by quantum tensor network

It is a fundamental, but still elusive question whether the schemes based on quantum mechanics, in particular on quantum entanglement, can be used for classical information processing and machine learning. Even partial answer to this question would bring important insights to both fields of machine learning and quantum mechanics. In this work, we implement simple numerical experiments, related to pattern/images classification, in which we represent the classifiers by many-qubit quantum states written in the matrix product states (MPS). Classical machine learning algorithm is applied to these quantum states to learn the classical data. We explicitly show how quantum entanglement (i.e., single-site and bipartite entanglement) can emerge in such represented images. Entanglement characterizes here the importance of data, and such information are practically used to guide the architecture of MPS, and improve the efficiency. The number of needed qubits can be reduced to less than 1/10 of the original number, which is within the access of the state-of-the-art quantum computers. We expect such numerical experiments could open new paths in charactering classical machine learning algorithms, and at the same time shed lights on the generic quantum simulations/computations of machine learning tasks.Comment: 10 pages, 5 figure

Characterizing the quantum field theory vacuum using temporal Matrix Product states

In this paper we construct the continuous Matrix Product State (MPS) representation of the vacuum of the field theory corresponding to the continuous limit of an Ising model. We do this by exploiting the observation made by Hastings and Mahajan in [Phys. Rev. A \textbf{91}, 032306 (2015)] that the Euclidean time evolution generates a continuous MPS along the time direction. We exploit this fact, together with the emerging Lorentz invariance at the critical point in order to identify the matrix product representation of the quantum field theory (QFT) vacuum with the continuous MPS in the time direction (tMPS). We explicitly construct the tMPS and check these statements by comparing the physical properties of the tMPS with those of the standard ground MPS. We furthermore identify the QFT that the tMPS encodes with the field theory emerging from taking the continuous limit of a weakly perturbed Ising model by a parallel field first analyzed by Zamolodchikov.Comment: The results presented in this paper are a significant expansion of arXiv:1608.0654