We propose a detailed Monte Carlo study of model selection criteria when the exact maximum likelihood (EML) method is used to estimate ARFIMA processes. More specifically, our object is to assess the performance of two automatic selection criteria in the presence of long-term memory: Akaike and...

We test for long memory in 3- and 6-month daily returns series on Eurocurrency deposits denominated in Japanese yen (Euroyen). The fractional differencing parameter is estimated using the spectral regression method. The conflicting evidence obtained from the application of tests against a unit...

We test for stochastic long memory in the Greek stock market, an emerging capital market. The fractional differencing parameter is estimated using the spectral regression method. Contrary to findings for major capital markets, significant and robust evidence of positive long-term persistence is...

In this paper, we consider the problem of robust estimation of the fractional parameter, d, in long memory autoregressive fractionally integrated moving average processes, when two types of outliers, i.e. additive and innovation, are taken into account without knowing their number, position or...

According to the permanent income hypothesis under rational expectations, variations of consumption should be larger than variations of unanticipated shocks to income. This implication of the theoretical model is not supported by the data since there seems to exist an excess smoothness of...

Cet article présente les contributions originelles et essentielles de T. Sargent et C. Sims à la modélisation macro-économétrique. Après avoir exposé leur critique de la modélisation existante, cet article s'attache à préciser l'originalité de leurs approches respectives. La...

Correlation in time series has recently recieved a lot of attentions. Its usage has been getting an important role in Social Science and Finance. For example, pair trading in Finance is interested with the correlation between stock prices, returns etc. In general, Pearsonís correlation...

We examine the Stein-rule shrinkage estimator for possible improvements in estimation and forecasting when there are many predictors in a linear time series model. We consider the Stein-rule estimator of Hill and Judge (1987) that shrinks the unrestricted unbiased OLS estimator towards a...

In this paper we propose a stationary nonlinear dynamic functional coefficient panel data models with fixed effects and develops semiparametric estimation procedure using series approximation. Convergence rate and asymptotic distribution of the proposed series estimators are derived in which...

In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and...