Tests for cointegration rank and choice of the alternative

This paper discusses likelihood-ratio (LR) tests on the cointegrating (CI) rank which consider any possible dimension of the CI rank under the alternative. The trace test and lambda-max test are obtained as special cases. Limit quantiles for all the tests in the class are derived. It is found that any of these tests can be used to construct an estimator of the CI rank, with no differences in asymptotic properties when the alternative is fixed. The properties of the class of tests are investigated by local asymptotic analysis, a simulation study and an empirical illustration. It is found that all the tests in the class have comparable power, which deteriorates substantially as the number of random walks increases. Tests constructed for a specific class of alternatives present minor power gains for alternatives in the class, and require the alternative to be far from the null. No test in this class is found to be asymptotically (in-)admissible. Some of the new tests in the class can also be arranged to give a constrained estimator of the CI rank, that restricts the minimum number of common trends. The power gains that these tests can obtain by constraining the minimum number of common trends appears to be limited and outweighted by the risk of inconsistency induced by the constrains. As a consequence, no value of the CI rank should be left untested, unless it can be excluded beyond any reasonable doubt.     

Wild bootstrap seasonal unit root tests for time series with periodic nonstationary volatility

We investigate the behavior of the well-known Hylleberg, Engle, Granger and Yoo (HEGY) regression-based seasonal unit root tests in cases where the driving shocks can display periodic nonstationary volatility and conditional heteroskedasticity. Our set up allows for periodic heteroskedasticity, nonstationary volatility and (seasonal) generalized autoregressive-conditional heteroskedasticity as special cases. We show that the limiting null distributions of the HEGY tests depend, in general, on nuisance parameters which derive from the underlying volatility process. Monte Carlo simulations show that the standard HEGY tests can be substantially oversized in the presence of such effects. As a consequence, we propose wild bootstrap implementations of the HEGY tests. Two possible wild bootstrap resampling schemes are discussed, both of which are shown to deliver asymptotically pivotal inference under our general conditions on the shocks. Simulation evidence is presented which suggests that our proposed bootstrap tests perform well in practice, largely correcting the size problems seen with the standard HEGY tests even under extreme patterns of heteroskedasticity, yet not losing finite sample relative to the standard HEGY tests.     

Evaluation of robinson's (1994) Tests in finite samples

Finite-sample critical values of Robinson's (1994) tests are evaluated in this article by means of Monte-Carlo simulations. The finite-sample behaviour of the tests, based on these finite-sample critical values is compared with those based on asymptotic results and with a number of leading unit root tests. The Monte-Carlo results indicate that the tests perform better when the finite-sample critical values are used and thus, they should be employed rather than the asymptotic ones, especially when working with small samples. An empirical application is also carried out, at the end of the article, comparing the results in both cases.     

The sensitivity of robust unit root tests

The power properties of the rank-based Dickey–Fuller (DF) unit root test of Granger and Hallman [C. Granger and J. Hallman, Nonlinear transformations of integrated time series, J. Time Ser. Anal. 12 (1991), pp. 207–218] and the range unit root tests of Aparicio et al. [F. Aparicio, A. Escribano, and A. Siplos, Range unit root (RUR) tests: Robust against non-linearities, error distributions, structural breaks and outliers, J. Time Ser. Anal. 27 (2006), pp. 545–576] are considered when applied to near-integrated time series processes with differing initial conditions. The results obtained show the empirical powers of the tests to be generally robust to smaller deviations of the initial condition of the time series from its underlying deterministic component, particularly for more highly stationary processes. However, dramatic decreases in power are observed when either the mean or variance of the deviation of the initial condition is increased. The robustness of the rank- and range-based unit root tests and their higher power results relative to the seminal DF test have both been noted previously in the econometrics literature. These results are questioned by the findings of the present paper.     

A Comparison of Two Random Number Generators for the Birnbaum–Saunders Distribution

Abstract

The Birnbaum–Saunders distribution was developed to describe fatigue failure lifetimes, however, the distribution has been shown to be applicable for a variety of situations that frequently occur in the engineering sciences. In general, the distribution can be used for situations that involve stochastic wear–out failure. The distribution does not have an exponential family structure, and it is often necessary to use simulation methods to study the properties of statistical inference procedures for this distribution. Two random number generators for the Birnbaum–Saunders distribution have appeared in the literature. The purpose of this article is to present and compare these two random number generators to determine which is more efficient. It is shown that one of these generators is a special case of the other and is simpler and more efficient to use.     

Confidence Sets for Cointegrating Coefficients Based on Stationarity Tests

Standard methods for inference in cointegrating systems require all the variables to have exact unit roots and are not at all robust even to slight violations of this condition. In this article, I consider an alternative approach to inference in a cointegrating system. This involves testing the hypothesis that a cointegrating vector takes on a specified value by testing for the stationarity of the associated residual. Confidence sets for the cointegrating vector can be constructed by exploiting the equivalence between tests and confidence sets. This method has the advantage that it remains valid even if the regressors have roots that are not exactly equal to unity.     

The problem of confounding in two-factor experiments

The problem of confounding in an axb experiment is studied without indexing the set of levels of each factor a priori by an algebraic object. General arithmetic restrictions on a and b are derived, leading to a'geometric reformulation of the problem when a or b is prime. This reformulation reduces to the problem of the existence of a generalized Hadamard matrix of specified order.     

The problem of confounding in two-factor experiments

The problem of confounding in an axb experinent is studied without indexing the set of levels of each factor a prior by an algebraic object. General arithmetic restrictions on a and b are derived, leading to a geometric reformulation of the problem when a or b is prime. This reformulation reduces to the problem of the existence of a generalized Hadamard matrix of specified order.     

企业与行政事业单位养老金支付水平比较

养老保险是我国社会保障制度的重中之重。我国养老保险制度存在企业与行政事业单位养老金支付水平差异化明显的问题,在全面分析企业与行政事业单位基本养老保险待遇差距现状及产生原因的基础上,提出解决养老金待遇差距问题的对策建议。     

Grass Roots Family Action and Military Policy Responses

No abstract available for this article.