Forecasting using a nonlinear DSGE model
| dc.contributor.author | Ivashchenko, Sergey | |
| dc.contributor.author | Gupta, Rangan | |
| dc.contributor.email | rangan.gupta@up.ac.za | en_ZA |
| dc.date.accessioned | 2019-05-28T13:34:08Z | |
| dc.date.available | 2019-05-28T13:34:08Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | A medium-scale nonlinear dynamic stochastic general equilibrium (DSGE) model was estimated (54 variables, 29 state variables, 7 observed variables). The model includes an observed variable for stock market returns. The root-mean square error (RMSE) of the in-sample and out-of-sample forecasts was calculated. The nonlinear DSGE model with measurement errors outperforms AR (1), VAR (1) and the linearised DSGE in terms of the quality of the out-of-sample forecasts. The nonlinear DSGE model without measurement errors is of a quality equal to that of the linearised DSGE model. | en_ZA |
| dc.description.department | Economics | en_ZA |
| dc.description.librarian | am2019 | en_ZA |
| dc.description.uri | https://content.sciendo.com/view/journals/jcbtp/jcbtp-overview.xml | en_ZA |
| dc.identifier.citation | Ivashchenko, S. & Gupta, R. 2018, 'Forecasting using a nonlinear DSGE model', Journal of Central Banking Theory and Practice, vol. 7, no. 2, pp. 73-98. | en_ZA |
| dc.identifier.issn | 2336-9205 (online) | |
| dc.identifier.other | 10.2478/jcbtp-2018-0013 | |
| dc.identifier.uri | http://hdl.handle.net/2263/69223 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | Sciendo | en_ZA |
| dc.rights | © 2017 Sergey Ivashchenko et al., published by De Gruyter Open. | en_ZA |
| dc.subject | Nonlinear DSGE | en_ZA |
| dc.subject | Quadratic Kalman filter | en_ZA |
| dc.subject | Out-of-sample forecasts | en_ZA |
| dc.subject | Dynamic stochastic general equilibrium (DSGE) | en_ZA |
| dc.subject | Root-mean square error (RMSE) | en_ZA |
| dc.title | Forecasting using a nonlinear DSGE model | en_ZA |
| dc.type | Article | en_ZA |