This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There are variety of economic applications where the problem of testing many moment in- equalities appears; a notable...

This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There are a variety of economic applications where the problem of testing many moment in- equalities appears; a notable...

We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. The concept of stationarity is refined, allowing for sample size dependence in the array and paying special attention to the rate at which the boundary unit root case is...

In this paper, we investigate the moderate deviations for a customer-arrival-based insurance risk model, in which customer’s actual claim sizes are described as independent and identically distributed heavy-tailed random variables multiplying a shot function, and the model can be treated as a...

In this paper, we obtain the moderate deviation principle for a sequence of Brownian motions defined on the unit sphere in Rd by using the cumulant method introduced by  Puhalskii (1994b) and generalize it to Ornstein–Uhlenbeck processes taking values on the unit sphere in Rd.

This paper mainly discusses the asymptotic properties of multi-casting autoregressive processes. By using the m-dependence of random vectors, we prove that the least squares (LS) estimator of the unknown parameters satisfies the moderate deviation principle. Two examples of regular cases are...

The paper proposes an approach to evaluate hypotheses about transition dynamics when only the distributions at two points in time are observed. Using the principle of statistical mechanics, we show how to adjust in the most probable way a hypothesis so that it becomes compatible with the...