Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis
نویسندگان
چکیده
منابع مشابه
Forecasting Singapore ’ s quarterly GDP with monthly external trade *
In this paper we suggest a methodology to formulate a dynamic regression with variables observed at different time intervals. This methodology is applicable if the explanatory variables are observed more frequently than the dependent variable. We demonstrate this procedure by developing a forecasting model for Singapore’s quarterly GDP based on monthly external trade. Apart from forecasts, the ...
متن کاملMultivariate singular spectrum analysis and the road to phase synchronization.
We show that multivariate singular spectrum analysis (M-SSA) greatly helps study phase synchronization in a large system of coupled oscillators and in the presence of high observational noise levels. With no need for detailed knowledge of individual subsystems nor any a priori phase definition for each of them, we demonstrate that M-SSA can automatically identify multiple oscillatory modes and ...
متن کاملForecasting U.S. Tourist Arrivals using Singular Spectrum
5 This paper introduces Singular Spectrum Analysis (SSA) for tourism demand forecasting 6 via an application into total monthly U.S. Tourist arrivals from 1996-2012. The global 7 tourism industry is today, a key driver of foreign exchange inflows to an economy. Here, we 8 compare the forecasting results from SSA with those from ARIMA, Exponential Smoothing 9 (ETS) and Neural Networks (NN). We f...
متن کاملUncertainty Analysis of Monthly Streamflow Forecasting
Streamflow forecasting is an important factor in water resources planning and management. In this study Feed Forward Artificial Neural Network (FFANN) was used for monthly streamflow forecasting. Three scenarios were considered for modeling. Principal Component Analysis (PCA) is used for reducing the model architecture complexity and input data reduction. Twelve statistical criteria were used t...
متن کاملFiltering and frequency interpretations of Singular Spectrum Analysis
New filtering and spectral interpretations of Singular Spectrum Analysis (SSA) are provided. It is shown that the variables reconstructed from diagonal averaging of reduced-rank approximations to the trajectory matrix can be obtained from a noncausal convolution filter with zero-phase characteristics. The reconstructed variables are readily constructed using a two-pass filtering algorithm that ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2019
ISSN: 0169-2070
DOI: 10.1016/j.ijforecast.2019.03.021