Improving Economic Forecasting With Bayesian Vector Autoregression
نویسندگان
چکیده
منابع مشابه
Forecasting State Tax Revenue: A Bayesian Vector Autoregression Approach By
This paper compares alternative time-series models to forecast state tax revenues. Forecast accuracy is compared to a benchmark random walk forecast. Quarterly data for California is used to forecast total tax revenue along with its three largest components, sales, income, and corporate tax revenue. For oneand four-quarter-ahead forecasts from 2004 to 2009, Bayesian vector autoregressions gener...
متن کاملA Bayesian Poisson Vector Autoregression Model
Multivariate count models are rare in political science, despite the presence of many count time series. This article develops a new Bayesian Poisson vector autoregression (BaP-VAR) model that can characterize endogenous dynamic counts with no restrictions on the contemporaneous correlations. Impulse responses, decomposition of the forecast errors, and dynamic multiplier methods for the effects...
متن کاملOil dependence, institutional quality and economic growth: A panel vector autoregression approach
Resources are the foundation of economic growth. With speedy economic and population growth, economic growth is facing a scarcity of resources worldwide. Resource-economy co-ordination has become every government’s main focus in reaching strategic development goals in countries that are on the path of rapid economic development. Sustainable economic development in a country requires resources a...
متن کاملForecasting government bond yields with large Bayesian vector autoregressions
We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an optimal amount of shrinkage towards univariate AR models. The optimal shrinkage is chosen by maximizing the Marginal Likelihood of the model. Focusing o...
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: Quarterly Review
سال: 1984
ISSN: 0271-5287
DOI: 10.21034/qr.843