Bayesian averaging of classical estimates in forecasting macroeconomic indicators with application of business survey data
In this paper, we develop a methodology for forecasting key macroeconomic indicators, based on business survey data. We estimate a large set of models, using an autoregressive specification, with regressors selected from business and household survey data. Our methodology is based on the Bayesian av...
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| Veröffentlicht in: | Empirica 2014-02, Vol.41 (1), p.53-68 |
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| container_title | Empirica |
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| creator | Białowolski, Piotr Kuszewski, Tomasz Witkowski, Bartosz |
| description | In this paper, we develop a methodology for forecasting key macroeconomic indicators, based on business survey data. We estimate a large set of models, using an autoregressive specification, with regressors selected from business and household survey data. Our methodology is based on the Bayesian averaging of classical estimates method. Additionally, we examine the impact of deterministic and stochastic seasonality of the business survey time series on the outcome of the forecasting process. We propose an intuitive procedure for incorporating both types of seasonality into the forecasting process. After estimating the specified models, we check the accuracy of the forecasts. |
| doi_str_mv | 10.1007/s10663-013-9227-x |
| format | Article |
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| subjects | Accuracy Bayesian method Econometrics Economic crisis Economic forecasts Economic growth Economic indicators Economic models Economic statistics Economic theory Economics Economics and Finance Estimates European Integration Federal Reserve monetary policy Forecasting Forecasting techniques GDP Gross Domestic Product Industrial Organization International Economics Macroeconomics Macroeconomics/Monetary Economics//Financial Economics Original Paper Pessimism Polls & surveys Public Finance Seasonal variations Seasonality Stochastic processes Studies Survey data Time series Unemployment |
| title | Bayesian averaging of classical estimates in forecasting macroeconomic indicators with application of business survey data |
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