Showing 1 - 7 of 7
We study the problems of bias correction in the estimation of low order ARMA(p, q) time series models. We introduce a new method to estimate the bias of the parameters of ARMA(p, q) process based on the analytical form of the GLS transformation matrix of Galbraith and Zinde-Walsh (1992). We show...
Persistent link: https://www.econbiz.de/10005609427
This paper studies the finite sample performance of the sieve bootstrap augmented Dickey-Fuller (ADF) unit root test. It is well known that this test’s accuracy in terms of rejection probability under the null depends greatly on the underlying DGP. Through extensive simulations, we find that...
Persistent link: https://www.econbiz.de/10005642188
scalar diusion. Among other examples, Stein equation implies that the mean of Hermite polynomials is zero. The GMM approach … contribution of the paper. The second reason for using GMM is that our tests are also valid for time series. In this case, we adopt …
Persistent link: https://www.econbiz.de/10005353211
In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming that the loading function is ad hoc (e.g., exponential...
Persistent link: https://www.econbiz.de/10005545733
In the present paper, we adopt the collective approach to consumer behavior-which supposes that each household member is characterized by his/her own preferences and that the decision process results in Pareto-efficient outcomes-and assume, in addition, that agents are egoistic and consumption...
Persistent link: https://www.econbiz.de/10005670294
scalar diffusion. Among other examples, Stein equation implies that the mean of Hermite polynomials is zero. The GMM approach … contribution of the paper. The second reason for using GMM is that our tests are also valid for time series. In this case, we adopt …
Persistent link: https://www.econbiz.de/10005729535
. We establish the direct links between the usual parametric estimation methods, namely, the QMLE, the GMM and the M …-estimation. The ususal univariate QMLE is, under non-normality, less efficient than the optimal GMM estimator. However, the bivariate … QMLE based on the dependent variable and its square is as efficient as the optimal GMM one. A Monte Carlo analysis confirms …
Persistent link: https://www.econbiz.de/10005729782