Bayesian Economics through Numerical Methods: A Guide to Econometrics and Decision-Making with Prior Information
数值方法下的贝叶斯经济学:利用先验信息开展计量分析与决策AI 解读 ↓
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数值方法下的贝叶斯经济学:利用先验信息开展计量分析与决策AI 解读 ↓
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Theory and Basics.- A Quick Course in Bayesian Statistics and Decision Theory.- New Advances in Numerical Bayesian Techniques.- Applications in Econometrics.- Imposing Economic Theory.- Studying Parameters of Interest.- Unit Root and Cointegration Tests.- Model Specification Uncertainty.- Forecasting.- More Realistic Models Through Numerical Methods.- Applications to Economic Decision Making.- Decision Theory Applications.
经济时间序列的贝叶斯预测
A model is suggested to forecast economic time series. This model incorporates some innovative ideas of Harrison and Stevens [20] for building into the forecasting process important external shocks to the systems. Thus the occurrence of possibly significant real-world events may cause a fundamental change in the time series in question. The Jeffreys-Savage (JS) Bayesian theory of hypothesis testing is used to test the hypothesis that a particular event has been such as to…
计量经济模型的确定
This paper is concerned with model determination methods and their use in the prediction of economic time series. The methods are Bayesian but they can be justified by classical arguments as well. The paper continues some recent work on Bayesian asymptotic, develops embedding techniques for vector martingales, and implements the modeling ideas in a multivariate regression framework that includes Bayesian vector autoregression (BVAR's) and reduced rank regressions (RRR's). It…
贝叶斯模型选择与预测及其实证应用
This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the development of ‘Bayes models’ for time series and on the authors' model selection criterion ‘PIC’. The PIC criterion is used in this paper to determine the lag order, the trend degree and the presence or absence of a unit root in an autoregression with deterministic trend. A new forecast-encompassing test for Bayes models is developed which allows one Bayes model to be compared with…
贸易政策对亚洲制造业中心的时空影响:贝叶斯全球 VAR 分析
A novel spatiotemporal framework using diverse econometric approaches is proposed in this research to analyze relationships among eight economy-wide variables in varying market conditions. Employing Vector Autoregression (VAR) and Granger causality, we explore trade policy effects on emerging manufacturing hubs in China, India, Malaysia, Singapore, and Vietnam. A Bayesian Global Vector Autoregression (BGVAR) model also assesses interaction of cross unit and perform…
动态预测计量建模中的大数据
The modern economic environment is awash in Big Data. The business models of many of today’s largest and most innovative firms, for example, are intimately connected to data collection and processing. Closely related, all of science is now similarly awash in Big Data, due to massive advances in data capture and storage technology, typically in conjunction with the internet.1 Time-series econometrics is no exception, and the time-series community is beginning to confront Big…
模型不确定性下利用英国货币总量进行实时预测
A popular account for the demise of the U.K.’s monetary targeting regime in the 1980s blames the fluctuating predictive relationships between broad money and inflation and real output growth. Yet ex post policy analysis based on heavily revised data suggests no fluctuations in the predictive content of money. In this paper, we investigate the predictive relationships for inflation and output growth using both real-time and heavily revised data. We consider a large set of…