Comparison of forecasting performance of time series models for the wholesale price of dried red peppers: focused on ARX and EGARCH

Abstract

Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.

Fig. 2. Wholesale price of dried red pepper (1996.1 - 2107. 12).

Fig. 3. Marketing channel of domestic fried red pepper (aT KAMIS, 2018). The numbers in the graph are the shares (%) of each section and sales root.

Fig. 4. Log diferenced (1^st) prices.

Fig. 1. Structure of Korea Rural Economic Institute (KREI)’s monthly structural model for dried red pepper (Kim et al., 2013).

Table 1. Annual supply situation of dried red pepper in Korea.

Table 2. Representative statistics of wholesale prices in the analysis: 2010. 08 - 2016. 12 (unit: won/600 g).

Table 3. Augmented Dickey-Fuller (ADF) unit root test results of wholesale price.

Table 4. Augmented Dickey-Fuller (ADF) unit root test results of Nonghyup price.

Table 5. Causality test results.

Table 6. ARMA model selection criteria table (1^st diferenced).

Table 7. Estimates of time series forecasting models for wholesale price.

Table 8. Out-of-sample tests results

Table 9. Ex-Post forecasting error test results of the KREI’s monthly structural model.