@article{Hoa:294965,
      recid = {294965},
      author = {Hoa, Tran Thanh},
      title = {Forecasting inflation in Vietnam with univariate and  vector autoregressive models},
      publisher = {The Graduate Institute of International and Development  Studies, International Economics Department},
      address = {Geneva. 2017},
      number = {BOOK},
      series = {Graduate Institute of International and Development  Studies Working Paper ; no. 05/2017},
      pages = {35 p. : ill.},
      year = {2017},
      abstract = {In this paper, I apply univariate and vector  autoregressive (VAR) models to forecast inflation in  Vietnam. To investigate the forecasting performance of the  models, two naïve benchmark models (one is a variant of a  random walk and the other is an autoregressive model) are  first built based on Atkeson-Ohanian (2001), Gosselin-Tkacz  (2001) and the specific properties of inflation in Vietnam.  Then, I compute the pseudo out-of-sample root mean square  error (RMSE) as a measure of forecast accuracy for the  candidate models and benchmarks, using rolling window and  expanding window forecasting evaluation strategies. The  process is applied to both monthly and quarterly data from  Vietnam for the period from 2000 through the first half of  2015. I also apply the forecastencompassing Diebold-Mariano  test to support choosing statistically better forecasting  models from among the different candidates. I find that  VAR_m2 is the best monthly model to forecast inflation in  Vietnam, whereas AR(6) is the best of the quarterly  forecasting models, although it provides a statistically  insignificantly better forecast than the benchmark BM2_q.},
      url = {http://repository.graduateinstitute.ch/record/294965},
      doi = {https://doi.org/10.71609/iheid-cq2j-3d16},
}