Generalized information matrix tests for copulas

We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokhorov. The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test’s asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the nonparametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer–von Mises type tests and confirm the desired properties of the new tests in high dimensions.     

Policy advice in an authoritarian environment: urban transport policies in Moscow and Beijing (2010–2017)

ABSTRACT

Fighting traffic congestion is a key policy challenge in large developing countries such as China and Russia. Highly populated, fast-growing cities like Beijing and Moscow develop urban transportation strategies that focus mainly on combating traffic congestion and modernizing existing infrastructure, but these problems are tied in with air pollution, safety on roads, parking issues, and public transport. In authoritarian landscapes, the policy-making process is not widely open to external actors or the general public, but it still requires expert knowledge. The usefulness of the advice offered by policy advisory institutions that are not a part of the bureaucracy depends strongly on authorities’ capacity to absorb their innovative proposals, informal contacts between advisers and authorities, and financial priorities. This paper analyses aspects of current urban transport policies in Beijing and Moscow with a particular focus on the nature of policy advisory practices in this sphere.     

The Effect of Care Setting on Elder Abuse: Results from a Michigan Survey

This study compares abuse rates for elders age 60 and older in three care settings: nursing home, paid home care, and assisted living. The results are based on a 2005 random-digit dial survey of relatives of, or those responsible for, a person in long-term care. Nursing homes have the highest rates of all types of abuse, although paid home care has a relatively high rate of verbal abuse and assisted living has an unexpected high rate of neglect. Even when adjusting for health conditions, care setting is a significant factor in both caretaking and neglect abuses. Moving from paid home care to nursing homes is shown to more than triple the odds of neglect. Furthermore, when computing abuse rates by care setting for persons with specified health conditions, nursing homes no longer have the highest abuse rates.     

Externalities in the wildland–urban interface: Private decisions,collective action,and results from wildfire simulation models for California

Property damage from wildfires occurs from spread into built-up areas, the wildland–urban interface. Fire spread occurs as embers from one burning structure ignite neighboring ones—but mitigation reduces the chances that fire spreads. In this study, we use a simulation model with realistic parameters for a neighborhood in California to illustrate patterns of marginal benefit from mitigation. We extend existing models of fire spread in two novel ways. We show how to describe the no-regulation equilibrium and social optimal levels of mitigation by incorporating data on a key factor, the distribution of house values in the community. We incorporate insurance in the model and show that it improves homeowner decision-making and insurance premium regulation. The fire spread simulations show that under plausible parameter values, there is a pattern in which mitigation's marginal benefit is low at low levels of community mitigation, rises to a maximum, and then falls quickly to a low level. We argue that the maximum marginal benefit is a guide to achieving optimal mitigation in a community. Owner mitigation decisions will depend on the distribution of house values in the neighborhood and other factors. In an illustration, we use the distribution of house values in a California community to illustrate the mitigation owners will choose under independent (Nash) investment decisions, and the efficiency-improving actions involving regulations or insurance premium subsidies that can lead to the social optimum.