Nowcasting China’s GDP Using a Bayesian Approach
نویسندگان
چکیده
منابع مشابه
Nowcasting Gdp in the Euro Area
This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MFVAR) approaches to model speci cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients, whereas MF-VAR does not restrict the dynamics and therefore can su¤er from the curse of dimensionality. But if...
متن کاملNowcasting Astronomical Seeing: Towards an Operational Approach
InMurtagh and Sarazin (1993), the ability to regress seeing on a set of near-ground meteorological variables was assessed. The present article proceeds towards the following operational framework: we obtain median seeing estimates for the night, given knowledge of ambient ground meteorological conditions. The data used are extensive meteorological and seeing measurements made at European Southe...
متن کاملMethods for Pastcasting, Nowcasting and Forecasting Using Factor-MIDAS with an Application to Real-Time Korean GDP *
We discuss a variety of recent methodological advances that can be used to estimate mixed frequency factor-MIDAS models for the purpose of pastcasting, nowcasting, and forecasting. In order to illustrate the uses of this methodology, we introduce a new real-time Korean GDP dataset, and carry out a series of prediction experiments, using a two step approach. In a first step, we estimate common l...
متن کاملPooling versus model selection for nowcasting with many predictors: an application to German GDP
This paper discusses pooling versus model selection for nowand forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to di¤erent sampling frequencies and publication delays. Two model classes suited in this context are factor models based on large datasets and mixed-data sampling (MIDAS) regress...
متن کاملMacroeconomic Nowcasting Using Google Probabilities∗
Many recent papers have investigated whether data from internet search engines such as Google can help improve nowcasts or short-term forecasts of macroeconomic variables. These papers construct variables based on Google searches and use them as explanatory variables in regression models. We add to this literature by nowcasting using dynamic model selection (DMS) methods which allow for model s...
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: Journal of Management Science and Engineering
سال: 2018
ISSN: 2096-2320
DOI: 10.3724/sp.j.1383.304013