Total tourist arrivals are the sum of disaggregate subcomponent arrivals by country of origin. We use seven time-series models to assess whether the aggregate approach that directly forecasts the total tourist arrivals outperforms the disaggregate approach that produces the total arrival...

This paper reviews various forecast methods including combination using theoretically optimal weights and those under model selection approaches. In addition, we suggest two modified simple averaging forecast combination methods—a mean corrected and a mean and scale corrected method. We...

We consider several geometric approaches for combining forecasts in large samples—a simple eigenvector approach, a mean corrected eigenvector and trimmed eigenvector approach. We give conditions where geometric approach yields identical result as the regression approach. We also consider a...

A panel data method is used to evaluate the impact of the Closer Economic Partnership Agreement (CEPA) signed between Mainland China and Hong Kong. Using the time series data of Hong Kong, Austria, Denmark, Finland, France, Germany, Italy, Japan, Korea, Netherlands, Norway, Singapore, Taiwan,...

Yes. By using real-time structure break monitoring techniques we find evidence against monotonic response pattern, specifically three response structures of US stock market to the federal monetary policy actions based on a sample from 1989-2010. We re-estimate the market response in each of the...

We develop an easy-to-implement method for forecasting a stationary autoregressive fractionally integrated moving average (ARFIMA) process subject to structural breaks with unknown break dates. We show that an ARFIMA process subject to a mean shift and a change in the long memory parameter can...

This paper considers the theoretical justifications of Lütkpohl’s (1988) test statistics when the data-generating process is relaxed to be a stationary ARFIMA process. Under suitable regularity conditions, we prove the applicability of Lütkpohl’s (1988) method to the stationary ARFIMA (p,...

This paper considers the impact of ordinary least squares (OLS) detrending and the first difference (FD) detrending on autocorrelation estimation in the presence of long memory and deterministic trends. We show that the FD detrending results in inconsistent autocorrelation estimates when the...