Forecasting macroeconomic variables is an important issue for decision makers. In thispaper, we analyze 13 univariate models which include linear and non-linear methods to forecastGDP growth and inflation to determine a benchmark. We not only examine the models in singlehorizon by the Diebold-Mariano test, but also apply the multi-horizon analysis from Quaedvlieg(2018). By conducting the research on 4 European countries with different fundamentals, wefind thatAutoregressive methodwith fixed lags performs the best in our sample, which is thebenchmark model that we propose. The multi-horizon superior predictive ability(SPA) test canbe an useful tool in comparing large set of forecasts which delivers reliable results.

Additional Metadata
Thesis Advisor Quaedvlieg, R.
Persistent URL hdl.handle.net/2105/52334
Series Financial Economics
Citation
Xing, X. (2020, July 16). Multi-Horizon Forecast Comparison of Linear and Non-linear Methods for GDP Growth and Inflation. Financial Economics. Retrieved from http://hdl.handle.net/2105/52334