We develop a portmanteau test of extremal serial dependence. The test statistic is asymptotically chi-squared under a null of "extremal white noise", as long as extremes are Near-Epoch-Dependent, covering linear and nonlinear distributed lags, stochastic volatility, and GARCHprocesses with possib ly unit or explosive roots. We apply tail speci...c tests to equity market and exchange rate return...

In this paper we generalize the KPSS-type test to allow for two structural breaks. Seven models have been de…ned depending on the way that the structural breaks a¤ect the time series behaviour. The paper derives the limit distribution of the test both under the null and the alternative hypotheses and conducts a set of simulation experiments to analyse the performance in …nite samples. Keywords:...

A new approach to robust testing in cointegrated systems is proposed using nonparametric HAC estimators without truncation. While such HAC estimates are inconsistent, they still produce asymptotically pivotal tests and, as in conventional regression settings, can improve testing and inference. JEL Classi…cation: C12; C14; C22 Keywords: Cointegration, HAC estimation, robust inference, steep orig...

as the main element of economy, human being has requirements the main one of which is the need for food security and healthy nutrition. unfortunately, in the iranian society there are two groups of people who do not enjoy food security. these groups include people who either do not have the financial means to provide healthy and nutritious food or those who, despite having the financial means, ...

This article proposes a functional dynamic factor model for the evaluation of the impact of scalar– and curve–valued factors on the shapes of intraday price curves. The asymptotic theory leads to practically useful confidence intervals for the factor coefficients. The main findings pertain to the impact of the shapes of intraday oil futures on the shapes of intraday prices of blue chip stocks. ...

This paper discusses the existence of spurious long memory in common nonlinear time series models, namely Markov switching and threshold models. We describe the asymptotic behavior of the process in terms of autocovariance and autocorrelation function and support the theoretical evidences by providing Monte Carlo simulation. The existence of long memory in these nonlinear processes is induced b...

This paper develops a method for testing for the presence of a single structural break in dynamic panel data models with a multi-factor error structure. The test statistic is developed by combining a modified version of the GMM approach of Robertson and Sarafidis (2015) with the testing procedure of De Wachter and Tzavalis (2012). We focus on the case where N is large and T fixed. The asymptoti...

This paper is concerned with tests and con…dence intervals for parameters that are not necessarily identi…ed and are de…ned by moment inequalities. In the literature, di¤erent test statistics, critical value methods, and implementation methods (i.e., the asymptotic distribution versus the bootstrap) have been proposed. In this paper, we compare these methods. We provide a recommended test stati...

– This paper applies neural network methodology to inßation forecasting in the Euro-area and the USA. Neural network methodology outperforms linear forecasting methods for the Euro Area at forecast horizons of one, three, and six month horizons, while the linear model is preferable for US data. The nonlinear estimation shows that unemployment is a signiÞcant predictor of inßation for the Euro A...

This study complements existing literature by examining the nexus between energy consumption (EC), CO2 emissions (CE) and economic growth (GDP) in 24 African countries using a panel ARDL approach. The following findings are established. First, there is a long run relationship between EC, CE and GDP. Second, a long term effect from CE to GDP and EC is apparent, with reciprocal paths. Third, the ...