@article{Lee:330724,
      recid = {330724},
      author = {Lee, Hyungyong},
      title = {Comparison of Time Series Forecasting Models in Garlic's  Wholesale Price},
      journal = {Journal of Rural Development/Nongchon-Gyeongje},
      address = {2017-06-30},
      number = {1071-2023-412},
      month = {Jun},
      year = {2017},
      abstract = {Garlic is an important seasoning vegetable that can not be  excluded from Korean diet. Predicting its supply and demand  situations and price is very important in terms of  producer's income and consumer price stability. This study  estimated the error correction model (ECM) and the Bayesian  VAR model using time series price data of garlic. Also this  study assessed the predictive power of the estimated model  by performing the out-of-sample forecasts. All price data  used in the analysis were identified as non-stationary time  series data. There was a cointegration relationship between  wholesale prices of whole bulbs of garlic and peeled  garlic, so the error correction model and the Bayesian VAR  model were estimated. Estimation results showed that  predictive power of the models was pretty good and the  error correction model had better predictive power than the  Bayesian VAR model. The estimated garlic pricing models in  this study are expected to contribute not only to the  current price prediction model based on quantity  forecasting but also to the efficiency of the model  operation process.},
      url = {http://ageconsearch.umn.edu/record/330724},
      doi = {https://doi.org/10.22004/ag.econ.330724},
}