A new test is proposed for the null of absence of serial correlation. The test uses a data-driven smoothing parameter. The resulting test statistic has a standard limit distribution under the null. The smoothing parameter is calibrated to achieve rate-optimality against several classes of...

Commonly used tests to assess evidence for the absence of autocorrelation in a univariate time series or serial cross-correlation between time series rely on procedures whose validity holds for i.i.d. data. When the series are not i.i.d., the size of correlogram and cumulative Ljung-Box tests...

We consider changes in the degree of persistence of a process when the degree of persistence is characterized as the order of integration of a strongly dependent process. To avoid the risk of incorrectly specifing the data generating process we employ local Whittle estimates which uses only...

The presence of long memory in Realized Volatility (RV) is a widespread stylized fact. The origins of long memory in RV have been attributed to jumps, structural breaks, non-linearities, or pure long memory. An important development has been the Heterogeneous Autoregressive (HAR) model and its...

Although the properties of the ARCH(∞) model are well investigated, the existence of long memory FIGARCH and IARCH solution was not established in the literature. These two popular ARCH type models which are widely used in applied literature, were causing theoretical controversy because of the...

In this paper, decisions regarding production in oil exporting countries are studied by means of theoretical analysis and empirical investigation. Under the assumptions of exogenous oil prices and world oil demand, we are able to describe the relationship between oil production levels and...

This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

Call centers' managers are interested in obtaining accurate forecasts of call arrivals because these are a key input in staffing and scheduling decisions. Therefore their ability to achieve an optimal balance between service quality and operating costs ultimately hinges on forecast accuracy. We...