2017, 28 ( 3) , 617–624
비정형 농업기상자료를 활용한 배추 도매가격 예측모형 연구 †
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ᅡᆼ수희
1
· 전희주2
·조인호3
· 김동환4
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TheIMC ·
2ᄃ ᅩ ᆼᄃ ᅥ ᆨᄋ ᅧᄌ ᅡᄃ ᅢᄒ ᅡ ᆨᄀ ᅭ ᄌ ᅥ ᆼᄇ ᅩᄐ ᅩ ᆼ ᄀ ᅨᄒ ᅡ ᆨᄀ ᅪ ·
4ᄋ ᅡ ᆫᄋ ᅣ ᆼᄃ ᅢᄒ ᅡ ᆨᄀ ᅭ ᄀ ᅮ ᆨ ᄌ ᅦᄐ ᅩ ᆼ ᄉ ᅡ ᆼᄋ ᅲᄐ ᅩ ᆼ ᄒ ᅡ ᆨᄀ ᅪ ᄌ ᅥ
ᆸᄉ ᅮ 2017ᄂ ᅧ ᆫ 5ᄋ ᅯ ᆯ 2ᄋ ᅵ ᆯ, ᄉ ᅮᄌ ᅥ ᆼ 2017ᄂ ᅧ ᆫ 5ᄋ ᅯ ᆯ 23ᄋ ᅵ ᆯ, ᄀ ᅦᄌ ᅢ ᄒ ᅪ ᆨᄌ ᅥ ᆼ 2017ᄂ ᅧ ᆫ 5ᄋ ᅯ ᆯ 25ᄋ ᅵ ᆯ
요 약 ᄌ
ᅮᄅ ᅩ ᄂ ᅩᄌ ᅵᄋ ᅦᄉ ᅥ ᄌ ᅢᄇ ᅢᄃ ᅬᄂ ᅳ ᆫ ᄇ ᅢᄎ ᅮᄂ ᅳ ᆫ ᄀ ᅵᄉ ᅡ ᆼ ᄋ ᅧᄀ ᅥ ᆫᄋ ᅦ ᄄ ᅡᄅ ᅡ ᄉ ᅢ ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅴ ᄇ ᅧ ᆫᄒ ᅪᄀ ᅡ ᄏ ᅳᄀ ᅩ, ᄃ ᅢᄎ ᅦ ᄌ ᅡ ᆨᄆ ᅮ ᆯ ᄋ ᅴ ᄌ ᅩ ᆫ ᄌ ᅢᄅ ᅩ ᄋ ᅵ ᆫᄒ ᅢ ᄀ
ᅡᄀ ᅧ ᆨ ᄇ ᅧ ᆫᄃ ᅩ ᆼ ᄋ ᅵ ᄏ ᅳᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆫᄃ ᅡ. ᄀ ᅵᄌ ᅩ ᆫ ᄋ ᅴ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥᄂ ᅳ ᆫ ᄉ ᅵ ᆯᄌ ᅦ ᄀ ᅵᄉ ᅡ ᆼᄌ ᅥ ᆼᄇ ᅩᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅢ ᄇ ᅢᄎ ᅮᄋ ᅴ ᄉ ᅢ ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄋ ᅧ ᆻᄋ ᅳ ᄂ
ᅡ, ᄇ ᅩ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥᄂ ᅳ ᆫ ᄉ ᅵ ᆯᄌ ᅦ ᄀ ᅵᄉ ᅡ ᆼᄌ ᅥ ᆼᄇ ᅩᄀ ᅡ ᄋ ᅡᄂ ᅵ ᆫ ᄋ ᅰ ᆸ ᄉ ᅡ ᆼᄋ ᅴ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅥ ᆼᄇ ᅩᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ
ᅡᄋ ᅧ ᆻᄃ ᅡ. 2009ᄂ ᅧ ᆫ 1ᄋ ᅯ ᆯᄇ ᅮᄐ ᅥ 2016ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵ ᄑ ᅩᄐ ᅥ ᆯᄉ ᅡᄋ ᅵᄐ ᅳᄋ ᅦᄉ ᅥ ᄇ ᅢᄎ ᅮᄅ ᅳ ᆯ ᄑ ᅩᄒ ᅡ ᆷᄒ ᅡ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄅ ᅳ ᆯ ᄉ ᅮᄌ ᅵ ᆸᄒ ᅡᄋ ᅧ, ᄉ ᅮᄌ ᅵ ᆸᄃ ᅬ ᆫ ᄆ
ᅮ ᆫ ᄉ ᅥ ᄂ ᅢᄋ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆫ ᄀ ᅵᄉ ᅡ ᆼ ᄀ ᅪ ᆫᄅ ᅧ ᆫ ᄏ ᅵᄋ ᅯᄃ ᅳᄅ ᅳ ᆯ ᄎ ᅮᄎ ᅮ ᆯ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄆ ᅡ ᆫᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅢ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱ (autoregressive;
AR)ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳᄅ ᅩ ᄌ ᅡ ᆨᄒ ᅧ ᆼᄇ ᅧ ᆯ ᄎ ᅮ ᆯ ᄒ ᅡᄉ ᅵᄀ ᅵᄋ ᅵ ᆫ 1, 5, 8, 11ᄋ ᅯ ᆯᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡ ᆫ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅥ ᆼᄇ ᅩᄅ ᅳ ᆯ ᄎ ᅮᄀ ᅡᄌ ᅥ ᆨ ᄋ
ᅳᄅ ᅩ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅢ ARᄆ ᅩᄒ ᅧ ᆼᄋ ᅳᄅ ᅩ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡ ᆫ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄇ ᅵᄀ ᅭᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄀ ᅳ ᄀ ᅧ ᆯᄀ ᅪ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅥ ᆼᄇ ᅩᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ
ᅡ ᆫ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ ᄉ ᅥ ᆼᄂ ᅳ ᆼ ᄋ ᅵ ᄃ ᅥ ᄋ ᅮᄉ ᅮᄒ ᅡᄀ ᅩ ᄋ ᅨᄎ ᅳ ᆨᄅ ᅧ ᆨᄋ ᅦ ᄃ ᅩᄋ ᅮ ᆷ ᄋ ᅵ ᄃ ᅬᄂ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅳᄅ ᅩ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆻᄃ ᅡ.
ᄌ
ᅮᄋ ᅭᄋ ᅭ ᆼ ᄋ ᅥ: ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ, ᄇ ᅢᄎ ᅮ, ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ, ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼ.
1. 서론
ᄋ
ᅮᄅ ᅵᄂ ᅡᄅ ᅡᄂ ᅳ ᆫ ᄀ ᅡᄀ ᅧ ᆨᄋ ᅡ ᆫᄌ ᅥ ᆼᄋ ᅳ ᆯ ᄋ ᅱᄒ ᅢ ᄉ ᅮᄀ ᅳ ᆸᄌ ᅥ ᆼᄎ ᅢ ᆨᄋ ᅳ ᆯ ᄑ ᅧᄀ ᅩ ᄋ ᅵ ᆻᄋ ᅳᄂ ᅡ, ᄂ ᅩᄌ ᅵᄋ ᅦᄉ ᅥ ᄌ ᅢᄇ ᅢᄃ ᅬᄂ ᅳ ᆫ ᄎ ᅢᄉ ᅩᄅ ᅲᄋ ᅴ ᄀ ᅧ ᆼᄋ ᅮ ᄀ ᅵᄉ ᅡ ᆼ ᄋ ᅧᄀ ᅥ ᆫ ᄋ
ᅦ ᄄ ᅡᄅ ᅡ ᄉ ᅢ ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅴ ᄇ ᅧ ᆫᄒ ᅪᄀ ᅡ ᄏ ᅳᄀ ᅩ, ᄃ ᅢᄎ ᅦ ᄌ ᅡ ᆨᄆ ᅮ ᆯ ᄋ ᅴ ᄌ ᅩ ᆫ ᄌ ᅢᄅ ᅩ ᄋ ᅵ ᆫᄒ ᅢ ᄀ ᅡᄀ ᅧ ᆨ ᄇ ᅧ ᆫᄃ ᅩ ᆼ ᄋ ᅵ ᄏ ᅳᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆫᄃ ᅡ (Namᄀ ᅪ Choe, 2015). ᄋ ᅨᄅ ᅳ ᆯ ᄃ ᅳ ᆯ ᄋ ᅥ, 2010ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯ ᄇ ᅢᄎ ᅮᄂ ᅳ ᆫ ᄀ ᅡᄅ ᅡ ᆨᄉ ᅵᄌ ᅡ ᆼᄋ ᅦᄉ ᅥ ᄒ ᅡ ᆫ ᄑ ᅩᄀ ᅵᄋ ᅦ 12,410ᄋ ᅯ ᆫ ᄋ ᅳᄅ ᅩ ᄀ ᅥᄅ ᅢᄃ ᅬᄋ ᅥ ᆻᄋ ᅳᄂ ᅡ 2011ᄂ ᅧ ᆫ 5ᄋ ᅯ ᆯᄋ ᅦᄂ ᅳ ᆫ ᄒ ᅡ ᆫ ᄑ ᅩᄀ ᅵᄋ ᅦ 600 ∼ 700ᄋ ᅯ ᆫ ᄋ ᅳᄅ ᅩ ᄑ ᅩ ᆨ ᄅ ᅡ ᆨᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄌ ᅥ ᆼᄇ ᅮᄂ ᅳ ᆫ ᄀ ᅡᄀ ᅧ ᆨ ᄑ ᅩ ᆨᄃ ᅳ ᆼ ᄋ ᅳᄅ ᅩ ᄋ ᅵ ᆫᄒ ᅡ ᆫ ᄌ ᅢᄇ ᅢᄆ ᅧ ᆫᄌ ᅥ ᆨ ᄌ ᅳ ᆼ ᄀ ᅡᄋ ᅪ ᄉ ᅩᄇ ᅵᄇ ᅮ ᄌ
ᅵ ᆫᄋ ᅳ ᆯ ᄇ ᅢᄎ ᅮᄑ ᅡᄃ ᅩ ᆼ ᄋ ᅴ ᄋ ᅯ ᆫ ᄋ ᅵ ᆫᄋ ᅳᄅ ᅩ ᄇ ᅮ ᆫᄉ ᅥ ᆨᄒ ᅡᄀ ᅩ, 1ᄆ ᅡ ᆫ ᄐ ᅩ ᆫ ᄋ ᅴ ᄉ ᅡ ᆫᄌ ᅵᄌ ᅡᄋ ᅲ ᆯ ᄑ ᅨᄀ ᅵᄅ ᅳ ᆯ ᄎ ᅮᄌ ᅵ ᆫᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄎ ᅢᄉ ᅩᄀ ᅡ ᆹ ᄑ ᅡᄃ ᅩ ᆼ ᄋ ᅳᄅ ᅩ 2005ᄂ ᅧ ᆫᄇ ᅮ ᄐ
ᅥ 2009ᄂ ᅧ ᆫᄁ ᅡᄌ ᅵ ᄇ ᅢᄎ ᅮ, ᄃ ᅢᄑ ᅡ, ᄆ ᅡᄂ ᅳ ᆯ, ᄋ ᅣ ᆼᄑ ᅡ ᄃ ᅳ ᆼ ᄋ ᅴ ᄎ ᅢᄉ ᅩᄅ ᅳ ᆯ ᄋ ᅣ ᆨ 364,000ᄐ ᅩ ᆫ ᄌ ᅥ ᆼᄃ ᅩ ᄉ ᅡ ᆫᄌ ᅵ ᄑ ᅨᄀ ᅵᄒ ᅡᄋ ᅧ ᆻᄋ ᅳᄆ ᅧ, ᄋ ᅵᄅ ᅳ ᆯ ᄒ ᅪ ᆫ ᄉ ᅡ ᆫᄒ ᅡ ᆫ ᄀ ᅳ
ᆷᄋ ᅢ ᆨᄋ ᅳ ᆫ 290ᄋ ᅥ ᆨ ᄋ ᅯ ᆫ ᄋ ᅵ ᄂ ᅥ ᆷᄂ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅳᄅ ᅩ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆻᄃ ᅡ (Kimᄀ ᅪ Yoon, 2011).
ᄄ
ᅩᄒ ᅡ ᆫ ᄂ ᅩ ᆼ ᄉ ᅡ ᆫᄆ ᅮ ᆯ ᄋ ᅲᄐ ᅩ ᆼᄌ ᅥ ᆼᄇ ᅩᄋ ᅦᄉ ᅥ ᄌ ᅦᄀ ᅩ ᆼ ᄒ ᅡᄂ ᅳ ᆫ ᄋ ᅯ ᆯᄀ ᅡ ᆫ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄉ ᅡ ᆯᄑ ᅧᄇ ᅩᄆ ᅧ ᆫ 2015ᄂ ᅧ ᆫ 9ᄋ ᅯ ᆯ ᄇ ᅢᄎ ᅮᄋ ᅴ ᄀ ᅧ ᆼᄋ ᅮ kgᄃ ᅡ ᆼ 611ᄋ ᅯ ᆫ ᄋ ᅵ ᄋ
ᅥ
ᆻᄃ ᅥ ᆫ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅵ 2016ᄂ ᅧ ᆫ 9ᄋ ᅯ ᆯ 2,104ᄋ ᅯ ᆫ ᄋ ᅳᄅ ᅩ ᄌ ᅥ ᆫᄂ ᅧ ᆫ ᄃ ᅢᄇ ᅵ 244% ᄉ ᅡ ᆼᄉ ᅳ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄀ ᅩ, ᄆ ᅮ ᄋ ᅧ ᆨᄉ ᅵ 2015ᄂ ᅧ ᆫ 9ᄋ ᅯ ᆯ kgᄃ ᅡ ᆼ 455ᄋ ᅯ ᆫ ᄋ ᅵᄋ ᅥ ᆻᄃ ᅥ ᆫ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅵ 2016ᄂ ᅧ ᆫ 9ᄋ ᅯ ᆯ 1,186ᄋ ᅯ ᆫ ᄋ ᅳᄅ ᅩ ᄌ ᅥ ᆫᄂ ᅧ ᆫ ᄃ ᅢᄇ ᅵ 160% ᄉ ᅡ ᆼᄉ ᅳ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄋ ᅵᄋ ᅪ ᄀ ᅡ ᇀᄋ ᅵ ᄀ ᅳ ᆨᄉ ᅵ ᆷᄒ ᅡ ᆫ ᄀ
ᅡᄀ ᅧ ᆨᄇ ᅧ ᆫᄃ ᅩ ᆼᄋ ᅳ ᆯ ᄇ ᅩᄋ ᅵᄂ ᅳ ᆫ ᄎ ᅢᄉ ᅩᄅ ᅲᄋ ᅴ ᄀ ᅧ ᆼᄋ ᅮ ᄉ ᅮᄀ ᅳ ᆸ ᄋ ᅵᄂ ᅡ ᄀ ᅡᄀ ᅧ ᆨ ᄋ ᅨᄎ ᅳ ᆨ ᄋ ᅦ ᄃ ᅢᄒ ᅡ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄂ ᅳ ᆫ ᄋ ᅵᄅ ᅮᄋ ᅥᄌ ᅵᄀ ᅩ ᄋ ᅵ ᆻᄋ ᅳᄂ ᅡ, ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼᄃ ᅦᄋ ᅵᄐ ᅥ ᄅ ᅳ
ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄂ ᅳ ᆫ ᄒ ᅪ ᆯ ᄇ ᅡ ᆯᄒ ᅡᄌ ᅵ ᄋ ᅡ ᆭᄋ ᅡ ᆻᄃ ᅡ.
ᄉ
ᅩᄉ ᅧ ᆯᄆ ᅵᄃ ᅵᄋ ᅥᄋ ᅴ ᄒ ᅪ ᆯᄋ ᅭ ᆼᄋ ᅳ ᆫ ᄋ ᅵ ᆫᄐ ᅥᄂ ᅦ ᆺᄀ ᅪ ᄆ ᅩᄇ ᅡᄋ ᅵ ᆯᄋ ᅴ ᄒ ᅪ ᆨ ᄉ ᅡ ᆫᄋ ᅳᄅ ᅩ ᄃ ᅥᄋ ᅮ ᆨ ᄌ ᅳ ᆼ ᄃ ᅢᄃ ᅬᄀ ᅩ ᄋ ᅵ ᆻᄋ ᅳᄆ ᅧ, ᄉ ᅩᄉ ᅧ ᆯᄆ ᅵᄃ ᅵᄋ ᅥᄋ ᅦᄉ ᅥ ᄉ ᅢ ᆼᄉ ᅥ ᆼᄃ ᅬᄂ ᅳ ᆫ ᄇ ᅵ
ᆨᄃ ᅦᄋ ᅵᄐ ᅥᄂ ᅳ ᆫ ᄉ ᅢᄅ ᅩᄋ ᅮ ᆫ ᄇ ᅮ ᆫᄉ ᅥ ᆨᄋ ᅳ ᆯ ᄀ ᅡᄂ ᅳ ᆼ ᄒ ᅡᄀ ᅦ ᄒ ᅡᄀ ᅩ ᄋ ᅵ ᆻᄃ ᅡ. ᄋ ᅰ ᆸ ᄋ ᅦᄉ ᅥ ᄉ ᅢ ᆼᄉ ᅥ ᆼᄃ ᅬᄂ ᅳ ᆫ ᄃ ᅦᄋ ᅵᄐ ᅥᄂ ᅳ ᆫ ᄑ ᅩ ᆨ ᄇ ᅡ ᆯᄌ ᅥ ᆨᄋ ᅳᄅ ᅩ ᄌ ᅳ ᆼ ᄀ ᅡᄒ ᅡᄀ ᅩ ᄋ ᅵ ᆻᄂ ᅳ ᆫ
†
ᄇ ᅩ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄂ ᅳ ᆫ ᄂ ᅩ ᆼᄅ ᅵ ᆷᄎ ᅮ ᆨ ᄉ ᅡ ᆫᄉ ᅵ ᆨᄑ ᅮ ᆷ ᄇ ᅮ ᄂ ᅩ ᆼᄉ ᅢ ᆼᄆ ᅧ ᆼᄉ ᅡ ᆫᄋ ᅥ ᆸᄀ ᅵᄉ ᅮ ᆯ ᄀ ᅢᄇ ᅡ ᆯᄉ ᅡᄋ ᅥ ᆸ(ᄀ ᅪᄌ ᅦᄇ ᅥ ᆫᄒ ᅩ: 514002-03)ᄋ ᅦ ᄋ ᅴᄒ ᅢ ᄌ ᅵᄋ ᅯ ᆫᄃ ᅬ ᆷ.
1
(04030) ᄉ ᅥᄋ ᅮ ᆯ ᄉ ᅵ ᄆ ᅡᄑ ᅩᄀ ᅮ ᄃ ᅩ ᆼ ᄀ ᅭᄅ ᅩ 142-16, ᄉ ᅡᄋ ᅯ ᆫ.
2
ᄀ ᅭᄉ ᅵ ᆫᄌ ᅥᄌ ᅡ: (02748) ᄉ ᅥᄋ ᅮ ᆯ ᄉ ᅵ ᄉ ᅥ ᆼᄇ ᅮ ᆨ ᄀ ᅮ ᄒ ᅪᄅ ᅡ ᆼᄅ ᅩ 13ᄀ ᅵ ᆯ, ᄃ ᅩ ᆼᄃ ᅥ ᆨᄋ ᅧᄌ ᅡᄃ ᅢᄒ ᅡ ᆨᄀ ᅭ ᄌ ᅥ ᆼᄇ ᅩᄐ ᅩ ᆼ ᄀ ᅨᄒ ᅡ ᆨᄀ ᅪ ᄇ ᅮᄀ ᅭᄉ ᅮ.
E-mail: [email protected]
3
(04030) ᄉ ᅥᄋ ᅮ ᆯ ᄉ ᅵ ᄆ ᅡᄑ ᅩᄀ ᅮ ᄃ ᅩ ᆼ ᄀ ᅭᄅ ᅩ 142-16, ᄋ ᅵᄉ ᅡ.
4
(14028) ᄀ ᅧ ᆼᄀ ᅵᄃ ᅩ ᄋ ᅡ ᆫᄋ ᅣ ᆼᄉ ᅵ ᄆ ᅡ ᆫᄋ ᅡ ᆫᄀ ᅮ ᄉ ᅡ ᆷᄃ ᅥ ᆨᄅ ᅩ 37ᄇ ᅥ ᆫᄀ ᅵ ᆯ 22.
ᄎ
ᅮᄉ ᅦᄌ ᅵᄆ ᅡ ᆫ, ᄋ ᅵᄋ ᅦ ᄇ ᅵᄒ ᅢ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄃ ᅦᄋ ᅵᄐ ᅥᄋ ᅵ ᆫ ᄇ ᅵ ᆨᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄂ ᅳ ᆫ ᄉ ᅵᄃ ᅩᄂ ᅳ ᆫ ᄌ ᅦᄒ ᅡ ᆫᄌ ᅥ ᆨᄋ ᅳᄅ ᅩ ᄋ ᅵᄅ ᅮᄋ ᅥᄌ ᅵᄀ ᅩ ᄋ ᅵ ᆻᄃ ᅡ (Das ᄃ
ᅳ ᆼ, 2013).
ᄎ
ᅢᄉ ᅩᄅ ᅲ ᄉ ᅮᄀ ᅳ ᆸ ᄆ ᅵ ᆾ ᄀ ᅡᄀ ᅧ ᆨ ᄋ ᅨᄎ ᅳ ᆨ ᄀ ᅪ ᄀ ᅪ ᆫᄅ ᅧ ᆫᄃ ᅬ ᆫ ᄉ ᅥ ᆫᄒ ᅢ ᆼ ᄋ ᅧ ᆫᄀ ᅮᄅ ᅩᄂ ᅳ ᆫ Mishra ᄃ ᅳ ᆼ (2013) ᄋ ᅴ ARIMAᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡ ᆫ ᄋ ᅣ ᆼᄑ ᅡ ᄉ ᅢ
ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄋ ᅵ ᄋ ᅵ ᆻᄃ ᅡ. ᄄ ᅩᄒ ᅡ ᆫ Kim (2005)ᄋ ᅳ ᆫ ARIMA ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ GARCH ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄋ ᅣ ᆼᄑ ᅡᄋ ᅴ ᄀ ᅡᄅ ᅡ ᆨᄉ ᅵ ᄌ
ᅡ ᆼ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨᄒ ᅢ ᆻᄂ ᅳ ᆫ ᄃ ᅦ, ᄋ ᅵ ᆫᄀ ᅩ ᆼᄉ ᅵ ᆫᄀ ᅧ ᆼᄆ ᅡ ᆼᄇ ᅩᄃ ᅡ ARIMAᄋ ᅪ GARCHᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ ᄋ ᅨᄎ ᅳ ᆨᄅ ᅧ ᆨᄋ ᅵ ᄃ ᅥ ᄋ ᅮᄉ ᅮᄒ ᅡᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆻ ᄃ
ᅡ. Parkᄀ ᅪ Park (2013)ᄋ ᅳ ᆫ ᄇ ᅢᄎ ᅮᄋ ᅪ ᄆ ᅮᄋ ᅴ ᄌ ᅡ ᆨᄒ ᅧ ᆼᄇ ᅧ ᆯ ᄌ ᅢᄇ ᅢᄆ ᅧ ᆫᄌ ᅥ ᆨᄇ ᅡ ᆫᄋ ᅳ ᆼ ᄒ ᅡ ᆷᄉ ᅮᄋ ᅪ ᄃ ᅡ ᆫᄉ ᅮᄒ ᅡ ᆷᄉ ᅮᄅ ᅳ ᆯ ᄎ ᅮᄌ ᅥ ᆼᄒ ᅢ ᄎ ᅩ ᆼᄉ ᅢ ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄀ ᅨ ᄉ
ᅡ ᆫᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
ᄀ
ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄅ ᅩ Namᄀ ᅪ Choe (2015)ᄋ ᅳ ᆫ ᄒ ᅡ ᆫᄀ ᅮ ᆨᄂ ᅩ ᆼ ᄉ ᅮᄉ ᅡ ᆫᄉ ᅵ ᆨᄑ ᅮ ᆷ ᄋ ᅲᄐ ᅩ ᆼᄀ ᅩ ᆼ ᄉ ᅡᄋ ᅴ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ ᄌ ᅡᄅ ᅭᄋ ᅪ ᄀ ᅵ ᄉ
ᅡ ᆼᄎ ᅥ ᆼᄋ ᅴ ᄀ ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭ, ᄐ ᅩ ᆼ ᄀ ᅨᄎ ᅥ ᆼᄋ ᅴ ᄋ ᅣ ᆼᄑ ᅡ ᄉ ᅢ ᆼᄉ ᅡ ᆫᄌ ᅡᄅ ᅭᄅ ᅩ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄉ ᅵᄎ ᅡ (autoreg ressive and distributed lags;
ARDL) ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄌ ᅢᄇ ᅢᄆ ᅧ ᆫᄌ ᅥ ᆨᄀ ᅪ ᄃ ᅡ ᆫᄉ ᅮᄅ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄀ ᅩ, ᄋ ᅣ ᆼᄑ ᅡᄋ ᅴ ᄎ ᅮ ᆯ ᄒ ᅡᄉ ᅵᄀ ᅵ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄌ ᅥ ᆫᄆ ᅡ ᆼᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄄ ᅩᄒ ᅡ ᆫ Choi ᄋ ᅪ Baek (2016)ᄋ ᅳ ᆫ ᄆ ᅡᄂ ᅳ ᆯ ᄌ ᅮᄉ ᅡ ᆫᄌ ᅵ 15ᄀ ᅩ ᆺ ᄋ ᅴ ᄀ ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄑ ᅢᄂ ᅥ ᆯᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄋ ᅳᄅ ᅩ ᄆ ᅡᄂ ᅳ ᆯ ᄋ ᅴ ᄉ ᅢ ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄎ
ᅮᄌ ᅥ ᆼᄒ ᅡᄋ ᅧ ᆻᄀ ᅩ, Lim ᄃ ᅳ ᆼ (2016)ᄋ ᅳ ᆫ ᄀ ᅮ ᆨ ᄂ ᅢ ᄎ ᅢᄉ ᅩᄌ ᅡ ᆨᄆ ᅮ ᆯ ᄌ ᅮ ᆼ ᄃ ᅢᄑ ᅭᄌ ᅥ ᆨᄋ ᅳᄅ ᅩ ᄂ ᅩ ᇁᄋ ᅳ ᆫ ᄉ ᅢ ᆼᄉ ᅡ ᆫ ᄆ ᅵ ᆾ ᄉ ᅩᄇ ᅵᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄇ ᅩᄋ ᅵᄂ ᅳ ᆫ ᄃ ᅡᄉ ᅥ ᆺ ᄀ ᅡᄌ ᅵ ᄌ ᅡ ᆨ ᄆ
ᅮ ᆯ ( ᄇ ᅢᄎ ᅮ, ᄆ ᅮ, ᄀ ᅩᄎ ᅮ, ᄆ ᅡᄂ ᅳ ᆯ, ᄋ ᅣ ᆼᄑ ᅡ)ᄋ ᅳ ᆯ ᄌ ᅮᄉ ᅡ ᆫᄌ ᅵᄇ ᅧ ᆯ ᄀ ᅵᄉ ᅡ ᆼᄌ ᅥ ᆼᄇ ᅩᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄋ ᅳᄅ ᅩ ᄃ ᅡ ᆫᄉ ᅮᄋ ᅨᄎ ᅳ ᆨ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄀ ᅢᄇ ᅡ ᆯᄒ ᅡ ᄋ
ᅧ ᆻᄃ ᅡ.
ᄇ
ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄅ ᅩ Cho ᄃ ᅳ ᆼ (2016)ᄋ ᅳ ᆫ ᄋ ᅰ ᆸ ᄉ ᅡ ᆼᄋ ᅦᄉ ᅥ ᄂ ᅡᄐ ᅡᄂ ᅡᄂ ᅳ ᆫ ᄎ ᅢᄉ ᅩᄅ ᅲ ᄀ ᅪ ᆫᄅ ᅧ ᆫ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄌ ᅥ
ᆼᄅ ᅣ ᆼᄒ ᅪᄒ ᅡᄋ ᅧ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼᄌ ᅵᄉ ᅮᄅ ᅳ ᆯ ᄀ ᅮᄉ ᅥ ᆼᄒ ᅡᄋ ᅧ ᆻᄋ ᅳᄆ ᅧ, ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼᄌ ᅵᄉ ᅮᄋ ᅪ ᄎ ᅢᄉ ᅩ ᄀ ᅮᄆ ᅢᄅ ᅣ ᆼᄋ ᅴ ᄌ ᅡ ᆼᄀ ᅵᄌ ᅥ ᆨᄋ ᅵ ᆫ ᄀ ᅪ ᆫ ᄀ ᅨᄅ ᅳ ᆯ ᄋ ᅧ ᆫᄀ ᅮᄒ ᅡᄋ ᅧ ᆻᄋ ᅳᄆ ᅧ Hyun ᄃ ᅳ ᆼ (2015)ᄋ ᅳ ᆫ ᄀ ᅵᄒ ᅮᄇ ᅧ ᆫᄒ ᅪᄋ ᅪ ᄉ ᅵ ᆨᄑ ᅮ ᆷᄀ ᅪ ᆫᄅ ᅧ ᆫ ᄂ ᅲᄉ ᅳᄀ ᅵᄉ ᅡᄋ ᅴ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄃ ᅦᄋ ᅵᄐ ᅥ ᄀ ᅡ ᆫᄋ ᅴ ᄀ ᅪ ᆫ ᄀ ᅨᄅ ᅳ ᆯ ᄋ ᅧ ᆫᄀ ᅮᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. Kang ᄃ ᅳ ᆼ (2015)ᄋ ᅳ ᆫ ᄐ ᅦ ᆨᄉ ᅳᄐ ᅳᄆ ᅡᄋ ᅵᄂ ᅵ ᆼᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡ ᆫ ᄀ ᅡ ᆷᄉ ᅥ ᆼᄇ ᅮ ᆫᄉ ᅥ ᆨᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄉ ᅡᄒ ᅬ ᄋ ᅵᄉ ᅲ ᄎ ᅡ ᆫᄇ ᅡ ᆫᄋ ᅳ ᆯ ᄇ ᅮ ᆫ ᄅ ᅲᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
ᄀ
ᅵᄌ ᅩ ᆫ ᄋ ᅴ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥᄂ ᅳ ᆫ ᄌ ᅥ ᆼᄒ ᅧ ᆼᄃ ᅦᄋ ᅵᄐ ᅥᄆ ᅡ ᆫᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄀ ᅥᄂ ᅡ ᄉ ᅢ ᆼᄉ ᅡ ᆫᄉ ᅥ ᆼᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄋ ᅧ ᆻᄋ ᅳᄂ ᅡ, ᄇ ᅩ ᆫ ᄋ ᅧ ᆫᄀ ᅮ ᄋ
ᅦᄉ ᅥᄂ ᅳ ᆫ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄎ ᅢᄉ ᅩᄅ ᅲ ᄌ ᅮ ᆼ ᄇ ᅢᄎ ᅮᄋ ᅴ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄀ ᅩᄌ ᅡ ᄒ ᅡ ᆫᄃ ᅡ. 2009ᄂ ᅧ ᆫ 1ᄋ ᅯ ᆯᄇ ᅮᄐ ᅥ 2016ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵᄋ ᅴ ᄑ ᅩᄐ ᅥ ᆯᄉ ᅡᄋ ᅵᄐ ᅳᄋ ᅴ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅢ ᄉ ᅵᄀ ᅨᄋ ᅧ ᆯᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄀ ᅮᄎ ᅮ ᆨ ᄒ ᅡᄋ ᅧ, ᄀ
ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭᄋ ᅴ ᄇ ᅧ ᆫᄒ ᅪᄋ ᅦ ᄄ ᅡᄅ ᅳ ᆫ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄎ ᅮᄌ ᅥ ᆼᄒ ᅡ ᆫᄃ ᅡ. ᄋ ᅵᄂ ᅳ ᆫ ᄇ ᅵ ᆨᄃ ᅦᄋ ᅵᄐ ᅥ ᄉ ᅡ ᆼ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄌ ᅡᄅ ᅭᄀ ᅡ ᄋ ᅨᄎ ᅳ ᆨᄇ ᅧ ᆫᄉ ᅮᄅ ᅩᄉ ᅥᄋ ᅴ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄋ ᅵ ᄀ
ᅡᄂ ᅳ ᆼ ᄒ ᅡᄃ ᅡᄂ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅳ ᆯ ᄇ ᅩᄋ ᅵᄂ ᅳ ᆫ ᄀ ᅨᄀ ᅵᄀ ᅡ ᄃ ᅬ ᆯ ᄀ ᅥ ᆺᄋ ᅵᄃ ᅡ.
2. 연구방법
2.1. 시계열 모형 ᄉ
ᅵᄀ ᅨᄋ ᅧ ᆯᄇ ᅮ ᆫᄉ ᅥ ᆨ (time-series analysis)ᄋ ᅳ ᆫ ᄉ ᅵᄀ ᅡ ᆫᄋ ᅴ ᄒ ᅳᄅ ᅳ ᆷ ᄋ ᅦ ᄄ ᅡᄅ ᅡ ᄃ ᅩ ᆼᄋ ᅵ ᆯᄒ ᅡ ᆫ ᄀ ᅪ ᆫᄎ ᅳ ᆨ ᄌ ᅮᄀ ᅵᄅ ᅩ ᄀ ᅪ ᆫᄎ ᅳ ᆨᄃ ᅬ ᆫ ᄉ ᅵᄀ ᅨᄋ ᅧ ᆯ ᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄇ ᅮ ᆫ ᄉ
ᅥ ᆨᄒ ᅡᄂ ᅳ ᆫ ᄇ ᅡ ᆼᄇ ᅥ ᆸᄋ ᅵᄃ ᅡ. ᄌ ᅡᄅ ᅭᄀ ᅡ ᄉ ᅢ ᆼᄉ ᅥ ᆼᄃ ᅬ ᆫ ᄉ ᅵᄉ ᅳᄐ ᅦ ᆷᄋ ᅳ ᆯ ᄋ ᅵᄒ ᅢᄒ ᅡᄀ ᅩ ᄀ ᅪᄀ ᅥᄋ ᅴ ᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄉ ᅵᄉ ᅳᄐ ᅦ ᆷᄋ ᅳ ᆯ ᄀ ᅡᄌ ᅡ ᆼ ᄌ ᅡ ᆯ ᄉ ᅥ ᆯᄆ ᅧ ᆼᄒ ᅡ ᄂ
ᅳ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄎ ᅡ ᆽᄋ ᅡ, ᄆ ᅵᄅ ᅢᄅ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄂ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅵ ᄉ ᅵᄀ ᅨᄋ ᅧ ᆯᄇ ᅮ ᆫᄉ ᅥ ᆨᄋ ᅴ ᄆ ᅩ ᆨᄌ ᅥ ᆨᄋ ᅵᄃ ᅡ (Choᄋ ᅪ Lee, 2014). ᄇ ᅩ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥᄂ ᅳ ᆫ ᄒ ᅧ ᆫ ᄉ
ᅵᄌ ᅥ ᆷᄋ ᅴ ᄇ ᅧ ᆫᄅ ᅣ ᆼᄋ ᅵ ᄀ ᅪᄀ ᅥᄋ ᅴ ᄇ ᅧ ᆫᄅ ᅣ ᆼᄃ ᅳ ᆯ ᄋ ᅦ ᄋ ᅴᄒ ᅢ ᄋ ᅧ ᆼᄒ ᅣ ᆼᄋ ᅳ ᆯ ᄇ ᅡ ᆮᄂ ᅳ ᆫ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼ (autoregressive model, AR model)ᄋ ᅳ ᆯ ᄋ
ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
t ᄉ ᅵᄌ ᅥ ᆷᄋ ᅦᄉ ᅥᄋ ᅴ ᄉ ᅵᄀ ᅨᄋ ᅧ ᆯ Z
tᄂ ᅳ ᆫ p ᄀ ᅢᄋ ᅴ ᄀ ᅪᄀ ᅥᄀ ᅡ ᆹᄃ ᅳ ᆯ ᄀ ᅪ ᄋ ᅩᄎ ᅡᄒ ᅡ ᆼ ϵ
tᄋ ᅴ ᄉ ᅥ ᆫᄒ ᅧ ᆼᄀ ᅧ ᆯᄒ ᅡ ᆸᄋ ᅳᄅ ᅩ ᄋ ᅵᄅ ᅮᄋ ᅥᄌ ᅵ ᆫ pᄎ ᅡ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄉ ᅵ ᆨ ᄋ
ᅳ ᆫ ᄉ ᅵ ᆨ (2.1)ᄀ ᅪ ᄀ ᅡ ᇀᄋ ᅵ ᄑ ᅭᄒ ᅧ ᆫᄒ ᅡ ᆫᄃ ᅡ.
Z
t= ϕ
1Z
t−1+ ϕ
2Z
t−2+ · · · + ϕ
pZ
t−p+ ϵ
t. (2.1)
2.2. 연구 과정 ᄇ ᅩ
ᆫ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥ ᄉ ᅵᄒ ᅢ ᆼᄃ ᅬ ᆫ ᄋ ᅧ ᆫᄀ ᅮ ᄀ ᅪᄌ ᅥ ᆼᄋ ᅳ ᆫ ᄃ ᅡᄋ ᅳ ᆷ ᄀ ᅪ ᄀ ᅡ ᇀᄃ ᅡ.
1) ᄇ ᅵ ᆨᄃ ᅦᄋ ᅵᄐ ᅥ ᄇ ᅮ ᆫᄉ ᅥ ᆨ ᄉ ᅩ ᆯ ᄅ ᅮᄉ ᅧ ᆫᄋ ᅵ ᆫ ᄐ ᅦ ᆨᄉ ᅳᄐ ᅩ ᆷ(textom)ᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄂ ᅦᄋ ᅵᄇ ᅥ ᄇ ᅳ ᆯ ᄅ ᅩᄀ ᅳ, ᄏ ᅡᄑ ᅦ, ᄂ ᅲᄉ ᅳ, ᄋ ᅰ ᆸ ᄎ ᅢᄂ ᅥ ᆯᄋ ᅦᄉ ᅥ ‘ᄇ ᅢ ᄎ
ᅮ’ ᄏ ᅵᄋ ᅯᄃ ᅳᄅ ᅳ ᆯ ᄑ ᅩᄒ ᅡ ᆷᄒ ᅡᄀ ᅩ ᄋ ᅵ ᆻᄂ ᅳ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄋ ᅴ ᄋ ᅯ ᆯᄇ ᅧ ᆯ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄉ ᅮᄌ ᅵ ᆸᄒ ᅡ ᆫᄃ ᅡ.
2) ᄉ ᅮᄌ ᅵ ᆸᄃ ᅬ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥ ᄌ ᅮ ᆼ ᄌ ᅡ ᆨᄆ ᅮ ᆯ ᄋ ᅴ ᄉ ᅢ ᆼᄌ ᅡ ᆼᄀ ᅪ ᄀ ᅪ ᆫᄅ ᅧ ᆫᄋ ᅵ ᄋ ᅵ ᆻᄂ ᅳ ᆫ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄏ ᅵᄋ ᅯᄃ ᅳᄅ ᅳ ᆯ ᄉ ᅥ ᆫᄌ ᅥ ᆼᄒ ᅡᄋ ᅧ ᄒ ᅢᄃ ᅡ ᆼ ᄏ ᅵᄋ ᅯᄃ ᅳᄋ ᅴ ᄎ ᅮ ᆯᄒ ᅧ ᆫᄇ ᅵ ᆫᄃ ᅩ ᄅ ᅳ
ᆯ ᄋ ᅯ ᆯᄇ ᅧ ᆯ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅩ ᄀ ᅮᄉ ᅥ ᆼᄒ ᅡ ᆫᄃ ᅡ.
3) ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄏ ᅵᄋ ᅯᄃ ᅳᄋ ᅴ ᄎ ᅮ ᆯᄒ ᅧ ᆫᄇ ᅵ ᆫᄃ ᅩᄂ ᅳ ᆫ ᄋ ᅧ ᆫᄀ ᅡ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ, 2016ᄂ ᅧ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄀ ᅵᄌ ᅮ ᆫ ᄋ ᅳᄅ ᅩ ᄑ ᅭᄌ ᅮ ᆫ ᄒ ᅪᄒ ᅡ ᆫᄃ ᅡ.
4) ᄂ ᅩ ᆼ ᄉ ᅡ ᆫᄆ ᅮ ᆯ ᄋ ᅲᄐ ᅩ ᆼᄌ ᅥ ᆼᄇ ᅩᄋ ᅴ ᄇ ᅢᄎ ᅮ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄀ ᅪ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄉ ᅵᄀ ᅨᄋ ᅧ ᆯᄌ ᅡᄅ ᅭᄅ ᅩ ᄇ ᅧ ᆼᄒ ᅡ ᆸᄒ ᅡ ᆫᄃ ᅡ.
5) ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅴ ᄀ ᅳᄅ ᅢᄑ ᅳᄅ ᅳ ᆯ ᄐ ᅩ ᆼ ᄒ ᅢ ᄎ ᅮᄉ ᅦᄅ ᅳ ᆯ ᄒ ᅪ ᆨ ᄋ ᅵ ᆫᄒ ᅡᄀ ᅩ, DW (Durbin-Watson) ᄀ ᅥ ᆷᄌ ᅥ ᆼᄋ ᅳ ᆯ ᄐ ᅩ ᆼ ᄒ ᅢ ᄌ ᅡᄀ ᅵᄉ ᅡ ᆼ ᄀ ᅪ ᆫ ᄋ ᅵ ᄋ ᅵ ᆻ ᄂ
ᅳ ᆫ ᄌ ᅵ ᄒ ᅪ ᆨ ᄋ ᅵ ᆫᄒ ᅡ ᆫᄃ ᅡ.
6) DF ᄃ ᅡ ᆫᄋ ᅱ ᄀ ᅳ ᆫᄀ ᅥ ᆷᄌ ᅥ ᆼ (Dickey-Fuller unit root tests)ᄋ ᅳ ᆯ ᄉ ᅵᄒ ᅢ ᆼᄒ ᅡᄋ ᅧ ᄌ ᅥ ᆼᄉ ᅡ ᆼᄉ ᅥ ᆼᄋ ᅳ ᆯ ᄒ ᅪ ᆨ ᄋ ᅵ ᆫᄒ ᅡ ᆫᄃ ᅡ.
7) ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ ᄌ ᅡᄅ ᅭᄆ ᅡ ᆫᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄌ ᅥ ᆨᄒ ᅡ ᆸᄒ ᅡ ᆫᄃ ᅡ.
8) ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄀ ᅪ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅡᄅ ᅭᄋ ᅴ ᄀ ᅭᄎ ᅡᄉ ᅡ ᆼ ᄀ ᅪ ᆫᄇ ᅮ ᆫᄉ ᅥ ᆨᄋ ᅳ ᆯ ᄐ ᅩ ᆼ ᄒ ᅢ ᄉ ᅥ ᆫᄒ ᅢ ᆼᄒ ᅡᄂ ᅳ ᆫ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄋ ᅳ ᆯ ᄉ ᅥ ᆫᄇ ᅧ ᆯᄒ ᅡᄀ ᅩ, ᄉ ᅥ ᆫᄒ ᅢ ᆼᄒ ᅡ ᄂ ᅳ
ᆫ ᄉ ᅵᄎ ᅡᄋ ᅴ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄋ ᅳ ᆯ ᄀ ᅧ ᆯᄒ ᅡ ᆸᄒ ᅡᄋ ᅧ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄌ ᅥ ᆨᄒ ᅡ ᆸᄒ ᅡ ᆫᄃ ᅡ.
9) ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ AIC, ᄋ ᅨᄎ ᅳ ᆨ ᄋ ᅩᄎ ᅡ ᄃ ᅳ ᆼᄋ ᅳ ᆯ ᄐ ᅩ ᆼ ᄒ ᅢ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ ᄉ ᅥ ᆼᄂ ᅳ ᆼᄋ ᅳ ᆯ ᄇ ᅵᄀ ᅭᄒ ᅡ ᆫᄃ ᅡ.
3. 실증 분석
3.1. 데이터 ᄃ
ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ ᄌ ᅡᄅ ᅭᄂ ᅳ ᆫ ᄂ ᅩ ᆼ ᄉ ᅡ ᆫᄆ ᅮ ᆯ ᄋ ᅲᄐ ᅩ ᆼᄌ ᅥ ᆼᄇ ᅩ (Kamis)ᄋ ᅦᄉ ᅥ ᄌ ᅦᄀ ᅩ ᆼ ᄒ ᅡᄂ ᅳ ᆫ 2009ᄂ ᅧ ᆫ 1ᄋ ᅯ ᆯᄇ ᅮᄐ ᅥ 2016ᄂ ᅧ ᆫ 11ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵᄋ ᅴ ᄋ ᅯ ᆯᄀ ᅡ ᆫ ᄉ
ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ (kg/ᄋ ᅯ ᆫ)ᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄇ ᅢᄎ ᅮᄂ ᅳ ᆫ ᄋ ᅵ ᆯ ᄂ ᅧ ᆫᄋ ᅦ 4ᄇ ᅥ ᆫ ᄉ ᅮ ᄒ ᅪ ᆨ ᄃ ᅬᄀ ᅵ ᄄ ᅢᄆ ᅮ ᆫ ᄋ ᅦ ᄀ ᅡ ᆨᄀ ᅡ ᆨᄋ ᅴ ᄌ ᅡ ᆨᄒ ᅧ ᆼᄋ ᅦ ᄄ ᅡᄅ ᅡ 1ᄋ ᅯ ᆯᄋ ᅦᄉ ᅥ 4ᄋ ᅯ ᆯᄋ ᅳ ᆫ ᄋ ᅯ ᆯᄃ ᅩ ᆼ, 5ᄋ ᅯ ᆯᄋ ᅦᄉ ᅥ 7ᄋ ᅯ ᆯᄋ ᅳ ᆫ ᄇ ᅩ ᆷ, 8ᄋ ᅯ ᆯᄋ ᅦᄉ ᅥ 10ᄋ ᅯ ᆯᄋ ᅳ ᆫ ᄀ ᅩᄅ ᅢ ᆼᄌ ᅵ, 11ᄋ ᅯ ᆯᄋ ᅦᄉ ᅥ 12ᄋ ᅯ ᆯᄋ ᅳ ᆫ ᄀ ᅡᄋ ᅳ ᆯ ᄌ ᅡ ᆨᄆ ᅮ ᆯ ᄋ ᅴ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄉ
ᅡᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
ᄇ
ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄌ ᅡᄅ ᅭᄂ ᅳ ᆫ ᄇ ᅵ ᆨᄃ ᅦᄋ ᅵᄐ ᅥ ᄇ ᅮ ᆫᄉ ᅥ ᆨ ᄉ ᅩ ᆯ ᄅ ᅮᄉ ᅧ ᆫᄋ ᅵ ᆫ ᄐ ᅦ ᆨᄉ ᅳᄐ ᅩ ᆷ (textom)ᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄑ ᅩᄐ ᅥ ᆯᄉ ᅡᄋ ᅵᄐ ᅳ (ᄂ ᅦᄋ ᅵᄇ ᅥ)ᄋ ᅴ 2009ᄂ ᅧ ᆫ 1ᄋ ᅯ ᆯᄇ ᅮᄐ ᅥ 2016ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵ ‘ᄇ ᅢᄎ ᅮ’ ᄏ ᅵᄋ ᅯᄃ ᅳᄀ ᅡ ᄑ ᅩᄒ ᅡ ᆷᄃ ᅬ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄅ ᅳ ᆯ ᄉ ᅮᄌ ᅵ ᆸᄒ ᅡᄋ ᅧ ᆻᄋ ᅳᄆ ᅧ, ᄉ ᅮᄌ ᅵ ᆸᄃ ᅬ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄋ ᅦᄉ ᅥ ᄌ ᅡ ᆨᄆ ᅮ ᆯ ᄉ ᅢ ᆼᄋ ᅲ ᆨ ᄋ ᅦ ᄋ ᅧ
ᆼᄒ ᅣ ᆼᄋ ᅳ ᆯ ᄆ ᅵᄎ ᅵᄂ ᅳ ᆫ ᄑ ᅮ ᆼ ᄉ ᅮᄒ ᅢ, ᄂ ᅢ ᆼᄒ ᅢ, ᄃ ᅩ ᆼ ᄉ ᅡ ᆼᄒ ᅢ, ᄉ ᅳ ᆸᄋ ᅲ ᆫ ᄒ ᅢ ᄃ ᅳ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄌ ᅢᄒ ᅢ ᄀ ᅪ ᆫᄅ ᅧ ᆫ ᄏ ᅵᄋ ᅯᄃ ᅳᄅ ᅳ ᆯ ᄉ ᅥ ᆫᄌ ᅥ ᆼᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
3.2. 단순모형
Figure 3.1ᄋ ᅳ ᆫ 2009ᄂ ᅧ ᆫ 1ᄋ ᅯ ᆯᄇ ᅮᄐ ᅥ 2016ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵ ᄋ ᅯ ᆯᄇ ᅧ ᆯ ᄇ ᅢᄎ ᅮ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅵᄆ ᅧ, ᄉ ᅵᄀ ᅡ ᆫᄋ ᅦ ᄄ ᅡᄅ ᅳ ᆫ ᄎ ᅮᄉ ᅦᄂ ᅳ ᆫ ᄋ ᅥ ᆹ ᄂ ᅳ
ᆫ ᄀ ᅥ ᆺᄋ ᅳᄅ ᅩ ᄇ ᅩᄋ ᅵ ᆫᄃ ᅡ. ᄄ ᅩᄒ ᅡ ᆫ ᄇ ᅢᄎ ᅮ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆫ ᄋ ᅯ ᆯᄋ ᅦ ᄄ ᅡᄅ ᅡ ᄃ ᅡᄅ ᅳᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡᄂ ᅳ ᆫ ᄃ ᅦ, Figure 3.2ᄅ ᅳ ᆯ ᄇ ᅩᄆ ᅧ ᆫ 3, 4, 8, 9ᄋ ᅯ ᆯ ᄋ
ᅦ ᄀ ᅡᄀ ᅧ ᆨᄋ ᅵ ᄂ ᅩ ᇁᄋ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅳ ᆯ ᄋ ᅡ ᆯ ᄉ ᅮ ᄋ ᅵ ᆻᄃ ᅡ. ᄋ ᅵᄅ ᅳ ᆯ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅦ ᄇ ᅡ ᆫᄋ ᅧ ᆼᄒ ᅡᄀ ᅵ ᄋ ᅱᄒ ᅢ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅦ 3, 4, 8, 9ᄋ ᅯ ᆯᄋ ᅴ ᄀ ᅡᄇ ᅧ ᆫᄉ ᅮᄅ ᅳ ᆯ ᄌ ᅥ ᆨᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻ ᄃ
ᅡ.
DWᄀ ᅥ ᆷᄌ ᅥ ᆼ ᄀ ᅧ ᆯᄀ ᅪ ᄇ ᅢᄎ ᅮ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆫ ᄌ ᅡᄀ ᅵᄉ ᅡ ᆼ ᄀ ᅪ ᆫ ᄋ ᅵ ᄋ ᅵ ᆻᄋ ᅳᄆ ᅧ (DW = 0.6954, p-value < .0001), DF ᄃ ᅡ ᆫᄋ ᅱ ᄀ
ᅳ ᆫᄀ ᅥ ᆷᄌ ᅥ ᆼ ᄀ ᅧ ᆯᄀ ᅪ ᄇ ᅢᄎ ᅮ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆫ ᄋ ᅲᄋ ᅴᄉ ᅮᄌ ᅮ ᆫ 0.1 ᄋ ᅦᄉ ᅥ ᄃ ᅡ ᆫᄋ ᅱ ᄀ ᅳ ᆫ ᄋ ᅵ ᄋ ᅥ ᆹᄂ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅳᄅ ᅩ ᄂ ᅡᄐ ᅡᄂ ᅡ(p-value = 0.0817), ᄌ ᅥ
ᆼᄉ ᅡ ᆼᄒ ᅪ ᄀ ᅪᄌ ᅥ ᆼᄋ ᅳ ᆯ ᄀ ᅥᄎ ᅵᄌ ᅵ ᄋ ᅡ ᆭᄀ ᅩ ARᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ ᄌ ᅥ ᆨᄒ ᅡ ᆸᄋ ᅵ ᄀ ᅡᄂ ᅳ ᆼ ᄒ ᅡᄂ ᅳ ᆫ ᄀ ᅥ ᆺᄋ ᅳᄅ ᅩ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆻᄃ ᅡ. 2016ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵᄋ ᅴ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄉ
ᅡᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄋ ᅦ ᄌ ᅥ ᆨᄒ ᅡ ᆸᄒ ᅡ ᆫ ᄀ ᅧ ᆯᄀ ᅪ (Table 3.1), ARᄆ ᅩᄒ ᅧ ᆼ (p = 1,5,12)ᄋ ᅵ ᄉ ᅥ ᆫᄐ ᅢ ᆨᄃ ᅬᄋ ᅥ ᆻᄋ ᅳᄆ ᅧ, ᄌ ᅡ ᆫᄎ ᅡᄂ ᅳ ᆫ ᄇ ᅢ ᆨ ᄉ ᅢ
ᆨᄌ ᅡ ᆸᄋ ᅳ ᆷ ᄀ ᅪᄌ ᅥ ᆼᄋ ᅳ ᆯ ᄆ ᅡ ᆫᄌ ᅩ ᆨ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄎ ᅮᄌ ᅥ ᆼᄃ ᅬ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆫ ᄉ ᅵ ᆨ (3.1)ᄀ ᅪ ᄀ ᅡ ᇀᄋ ᅳᄆ ᅧ, ᄋ ᅧᄀ ᅵᄉ ᅥ March, April, August, Septem- berᄂ ᅳ ᆫ ᄒ ᅢᄃ ᅡ ᆼ ᄋ ᅯ ᆯᄋ ᅴ ᄀ ᅡᄇ ᅧ ᆫᄉ ᅮᄋ ᅵᄃ ᅡ. ᄎ ᅮᄌ ᅥ ᆼᄃ ᅬ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡ ᆫ 2016ᄂ ᅧ ᆫ 11ᄋ ᅯ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄀ ᅡ ᆹᄋ ᅳ ᆫ 972.7ᄋ ᅯ ᆫ ᄋ ᅵᄆ ᅧ, ᄉ ᅵ ᆯᄌ ᅦ ᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆫ 847ᄋ ᅯ ᆫ ᄋ ᅵᄃ ᅡ.
Z ˆ
t=695.0646 + 167.8650 ∗ March + 260.2382 ∗ April + 266.9272 ∗ August
+ 442.3177 ∗ September − 0.6244Z
t−1− 0.1866Z
t−5+ 0.2438Z
t−12. (3.1)
Figure 3.1 Time series data of cabbage wholesale price
Figure 3.2 Monthly average wholesale price of cabbage Table 3.1 The simple model
Variable Df Estimate S.E. t value p-value
intercept 1 695.0646 58.8896 11.8 <.0001
March 1 167.865 66.1478 2.54 0.013
April 1 260.2382 65.9206 3.95 0.0002
August 1 266.9272 66.0233 4.04 0.0001
September 1 442.3177 66.2062 6.68 <.0001
AR1 1 -0.6244 0.0735 -8.5 <.0001
AR5 1 -0.1866 0.0793 -2.35 0.0209
AR12 1 0.2438 0.0795 3.07 0.0029
Obs. 94
AIC 1298.67428
AICC 1300.3684
3.3. 농업기상모형 ᄂ
ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆫ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼ ᄌ ᅥ ᆯᄎ ᅡᄅ ᅳ ᆯ ᄄ ᅡᄅ ᅳᄃ ᅬ, ᄉ ᅥ ᆫᄌ ᅥ ᆼᄃ ᅬ ᆫ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄀ ᅡ ᆨ ᄏ ᅵᄋ ᅯᄃ ᅳᄋ ᅴ ᄇ
ᅵ ᆫᄃ ᅩᄂ ᅳ ᆫ Table 3.2 ᄋ ᅴ ᄋ ᅧ ᆫᄀ ᅡ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ 2016ᄂ ᅧ ᆫ ᄆ ᅮ ᆫ ᄉ ᅥᄅ ᅣ ᆼᄋ ᅳ ᆯ ᄀ ᅵᄌ ᅮ ᆫ ᄋ ᅳᄅ ᅩ ᄑ ᅭᄌ ᅮ ᆫ ᄒ ᅪᄒ ᅡ ᆫ ᄀ ᅡ ᆹᄋ ᅳ ᆯ ᄉ ᅡᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
Table 3.3ᄋ ᅳ ᆫ ᄑ ᅭᄌ ᅮ ᆫ ᄒ ᅪ ᄃ ᅬ ᆫ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄏ ᅵᄋ ᅯᄃ ᅳᄋ ᅴ ᄎ ᅮ ᆯᄒ ᅧ ᆫᄇ ᅵ ᆫᄃ ᅩᄋ ᅪ ᄇ ᅢᄎ ᅮ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅴ ᄀ ᅭᄎ ᅡᄉ ᅡ ᆼ ᄀ ᅪ ᆫᄇ ᅮ ᆫᄉ ᅥ ᆨ ᄀ ᅧ ᆯᄀ ᅪ ᄉ ᅥ ᆫᄒ ᅢ ᆼ ᄒ
ᅡᄂ ᅳ ᆫ ᄉ ᅡ ᆼ ᄀ ᅪ ᆫᄉ ᅥ ᆼᄋ ᅳ ᆯ ᄀ ᅡᄌ ᅵᄂ ᅳ ᆫ ᄏ ᅵᄋ ᅯᄃ ᅳᄋ ᅵᄆ ᅧ, ᄉ ᅥ ᆫᄒ ᅢ ᆼᄒ ᅡᄂ ᅳ ᆫ ᄉ ᅵᄎ ᅡᄋ ᅴ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄏ ᅵᄋ ᅯᄃ ᅳ ᄇ ᅵ ᆫᄃ ᅩᄅ ᅳ ᆯ ᄉ ᅥ ᆯᄆ ᅧ ᆼᄇ ᅧ ᆫᄉ ᅮᄅ ᅩ ᄉ ᅡᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
Table 3.2 Documents collected by year
year 2009 2010 2011 2012 2013 2014 2015 2016
documents 106,965 157,559 192,839 199,425 260,619 393,358 508,674 558,233
Table 3.3 Keywords and preceding time lags prior to price
keywords cold-weather damage low temperature frost damage cold wave
lags 5 1 1 2
keywords heat wave heavy rain downpour strong wind
lags 1 1 1 4
2016ᄂ ᅧ ᆫ 10ᄋ ᅯ ᆯᄁ ᅡᄌ ᅵᄋ ᅴ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄉ ᅡᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄌ ᅡᄀ ᅵᄒ ᅬᄀ ᅱᄆ ᅩᄒ ᅧ ᆼᄋ ᅦ ᄌ ᅥ ᆨᄒ ᅡ ᆸᄒ ᅡ ᆫ ᄀ ᅧ ᆯᄀ ᅪ (Table 3.4), AR(1)ᄆ ᅩᄒ ᅧ ᆼᄋ ᅵ ᄉ ᅥ ᆫ ᄐ ᅢ
ᆨᄃ ᅬᄋ ᅥ ᆻᄋ ᅳᄆ ᅧ, ᄌ ᅡ ᆫᄎ ᅡᄂ ᅳ ᆫ ᄇ ᅢ ᆨᄉ ᅢ ᆨᄌ ᅡ ᆸᄋ ᅳ ᆷ ᄀ ᅪᄌ ᅥ ᆼᄋ ᅳ ᆯ ᄆ ᅡ ᆫᄌ ᅩ ᆨ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄎ ᅮᄌ ᅥ ᆼᄃ ᅬ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆫ ᄉ ᅵ ᆨ (3.2)ᄋ ᅪ ᄀ ᅡ ᇀᄋ ᅳᄆ ᅧ, ᄋ ᅧᄀ ᅵᄉ ᅥ March, April, August, Septemberᄂ ᅳ ᆫ ᄒ ᅢᄃ ᅡ ᆼ ᄋ ᅯ ᆯᄋ ᅴ ᄀ ᅡᄇ ᅧ ᆫᄉ ᅮ, V1ᄋ ᅳ ᆫ frost damage, V2ᄂ ᅳ ᆫ cold wave, V3ᄂ ᅳ ᆫ heat wave ᄋ ᅵᄃ ᅡ. ᄎ ᅮᄌ ᅥ ᆼᄃ ᅬ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄉ ᅵ ᆨᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡ ᆫ 2016ᄂ ᅧ ᆫ 11ᄋ ᅯ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄀ ᅡ ᆹᄋ ᅳ ᆫ 782.1ᄋ ᅯ ᆫ ᄋ ᅵᄆ ᅧ, ᄉ ᅵ ᆯᄌ ᅦ ᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆫ 847ᄋ ᅯ ᆫ ᄋ ᅵᄃ ᅡ. ᄂ ᅩ ᆼᄋ ᅥ ᆸ ᄀ
ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ AICᄋ ᅪ AICCᄂ ᅳ ᆫ ᄀ ᅡ ᆨᄀ ᅡ ᆨ 1272.65, 1275.06ᄅ ᅩ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ AIC = 1298.67ᄋ ᅪ AICC = 1300.37 ᄇ
ᅩᄃ ᅡ ᄃ ᅥ ᄂ ᅡ ᆽᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡ ᄋ ᅮᄉ ᅮᄒ ᅡ ᆫ ᄉ ᅥ ᆼᄂ ᅳ ᆼᄋ ᅳ ᆯ ᄇ ᅩᄋ ᅧ ᆻᄃ ᅡ. ᄋ ᅨᄎ ᅳ ᆨ ᄋ ᅩᄎ ᅡᄋ ᅴ ᄏ ᅳᄀ ᅵ ᄋ ᅧ ᆨᄉ ᅵ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆫ 64.9 ᄅ ᅩ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ 125.7 ᄇ ᅩᄃ ᅡ ᄂ ᅡ ᆽᄋ ᅡ ᄋ ᅨᄎ ᅳ ᆨᄅ ᅧ ᆨ ᄋ ᅧ ᆨᄉ ᅵ ᄃ ᅥ ᄋ ᅮᄉ ᅮᄒ ᅢ ᆻᄃ ᅡ.
Table 3.4 The unstructured agricultural weather model
Variable Df Estimate S.E. t value p-value
intercept 1 836.3145 103.5127 8.08 <.0001
March 1 100.2882 86.5432 1.16 0.2499
April 1 244.3836 79.4724 3.08 0.0028
August 1 274.8712 78.5987 3.5 0.0008
September 1 332.9209 95.4446 3.49 0.0008
lag1(frost damage) 1 -2.67 1.0246 -2.61 0.0109
lag2(cold wave) 1 0.5119 0.2449 2.09 0.0396
lag1(heat wave) 1 0.6344 0.2877 2.2 0.0302
AR1 1 -0.6435 0.09 -7.15 <.0001
Obs. 92
AIC 1272.86619
AICC 1275.06131
Z ˆ
t=836.3145 + 100.2882 ∗ March + 244.3836 ∗ April + 274.8712 ∗ August
+ 332.9209 ∗ September − 2.6700 ∗ V 1
t−1+ 0.5119 ∗ V 2
t−2+ 0.6344 ∗ V 3
t−1− 0.6435Z
t−1. (3.2)
3.4. 단순모형과 농업기상모형 비교 ᄋ
ᅡ
ᇁ ᄌ ᅥ ᆯᄀ ᅪ ᄀ ᅡ ᇀᄋ ᅳ ᆫ ᄌ ᅥ ᆯᄎ ᅡᄅ ᅩ ᄌ ᅥ ᆫᄋ ᅯ ᆯᄁ ᅡᄌ ᅵᄋ ᅴ ᄀ ᅪ ᆫᄎ ᅳ ᆨ ᄎ ᅵ ᄆ ᅡ ᆫᄋ ᅳ ᆯ ᄉ ᅡᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄌ ᅥ ᆨᄒ ᅡ ᆸᄒ ᅡ ᆫ ᄒ ᅮ, ᄋ ᅯ ᆯᄃ ᅩ ᆼ ᄇ
ᅢᄎ ᅮ, ᄇ ᅩ ᆷ ᄇ ᅢᄎ ᅮ, ᄀ ᅩᄅ ᅢ ᆼᄌ ᅵᄇ ᅢᄎ ᅮ, ᄀ ᅡᄋ ᅳ ᆯ ᄇ ᅢᄎ ᅮᄋ ᅴ ᄎ ᅮ ᆯ ᄒ ᅡᄉ ᅵᄀ ᅵᄋ ᅵ ᆫ 2016ᄂ ᅧ ᆫ 1ᄋ ᅯ ᆯ, 5ᄋ ᅯ ᆯ, 8ᄋ ᅯ ᆯ, 11ᄋ ᅯ ᆯᄋ ᅴ ᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
Table 3.5ᄂ ᅳ ᆫ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ ᄆ ᅩᄒ ᅧ ᆼᄌ ᅥ ᆨᄒ ᅡ ᆸᄃ ᅩᄅ ᅳ ᆯ ᄇ ᅵᄀ ᅭᄒ ᅡ ᆫ ᄀ ᅧ ᆯᄀ ᅪᄋ ᅵᄃ ᅡ. ᄎ ᅮ ᆯ ᄒ ᅡᄉ ᅵᄀ ᅵᄋ ᅴ ᄇ ᅢᄎ ᅮ ᄉ ᅡ ᆼᄑ ᅮ ᆷ ᄃ ᅩᄆ ᅢᄀ ᅡ ᄀ ᅧ
ᆨᄋ ᅳ ᆯ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡᄀ ᅵ ᄋ ᅱᄒ ᅡ ᆫ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄇ ᅵᄀ ᅭᄒ ᅡ ᆫ ᄀ ᅧ ᆯᄀ ᅪ, ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ AICᄋ ᅪ AICCᄀ ᅡ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩ ᄒ ᅧ
ᆼᄇ ᅩᄃ ᅡ ᄂ ᅡ ᆽᄋ ᅡ ᄃ ᅥ ᄋ ᅮᄉ ᅮᄒ ᅡ ᆫ ᄉ ᅥ ᆼᄂ ᅳ ᆼᄋ ᅳ ᆯ ᄇ ᅩᄋ ᅵ ᆫᄃ ᅡ. ᄄ ᅩᄒ ᅡ ᆫ ᄋ ᅨᄎ ᅳ ᆨ ᄀ ᅡ ᆹ ᄋ ᅧ ᆨᄉ ᅵ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅴ ᄋ ᅨᄎ ᅳ ᆨ ᄋ ᅩᄎ ᅡᄋ ᅴ ᄏ ᅳᄀ ᅵᄀ ᅡ ᄃ ᅥ ᄌ ᅡ ᆨᄋ ᅡ ᄃ ᅡ ᆫ ᄉ ᅮ
ᆫ ᄆ ᅩᄒ ᅧ ᆼᄇ ᅩᄃ ᅡ ᄋ ᅨᄎ ᅳ ᆨᄅ ᅧ ᆨᄋ ᅵ ᄃ ᅥ ᄋ ᅮᄉ ᅮᄒ ᅡᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡ ᆻᄃ ᅡ.
Table 3.5 Comparison of the simple and unstructured agricultural weather model
AIC AICC Actual price Forecast price Prediction error
Forecast simple model 1153.9 1155.8 552 527.7 -24.3
January
unstructured agricultural 1077.0 1079.1 553.0 1.0
weather model
Forecast simple model 1210.9 1212.3 1143 1035.8 -107.2
May
unstructured agricultural 1132.7 1134.7 1092.8 -50.2
weather model
Forecast simple model 1252.0 1253.4 1524 1003.4 -520.6
August
unstructured agricultural 1173.4 1175.3 1016.2 -507.8
weather model
Forecast simple model 1298.7 1300.4 847 972.7 125.7
November
unstructured agricultural 1272.9 1275.1 782.1 -64.9
weather model
4. 결론
ᄌ
ᅮᄅ ᅩ ᄂ ᅩᄌ ᅵᄋ ᅦᄉ ᅥ ᄌ ᅢᄇ ᅢᄃ ᅬᄂ ᅳ ᆫ ᄇ ᅢᄎ ᅮᄂ ᅳ ᆫ ᄀ ᅵᄉ ᅡ ᆼ ᄋ ᅧᄀ ᅥ ᆫᄋ ᅦ ᄋ ᅧ ᆼᄒ ᅣ ᆼᄋ ᅳ ᆯ ᄆ ᅡ ᆭᄋ ᅵ ᄇ ᅡ ᆮᄀ ᅵ ᄄ ᅢᄆ ᅮ ᆫ ᄋ ᅦ, ᄉ ᅢ ᆼᄉ ᅡ ᆫᄅ ᅣ ᆼᄋ ᅵᄂ ᅡ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ ᄎ ᅮᄌ ᅥ ᆼ ᄉ ᅵ ᄀ
ᅵᄉ ᅡ ᆼᄋ ᅳ ᆯ ᄀ ᅩᄅ ᅧᄒ ᅢᄋ ᅣ ᄒ ᅡ ᆫᄃ ᅡ. ᄉ ᅵ ᆯᄌ ᅦ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅡᄅ ᅭᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡ ᆫ ᄀ ᅵᄌ ᅩ ᆫ ᄋ ᅴ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅪᄂ ᅳ ᆫ ᄃ ᅡᄅ ᅳᄀ ᅦ ᄇ ᅩ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥᄂ ᅳ ᆫ ᄋ ᅰ ᆸ ᄉ ᅡ ᆼᄋ ᅴ ᄇ ᅵ ᄌ ᅥ
ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼ ᄌ ᅥ ᆼᄇ ᅩᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ. ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨ ᄌ ᅡᄅ ᅭᄆ ᅡ ᆫᄋ ᅳ ᆯ ᄋ ᅵᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ 2016ᄂ ᅧ ᆫ ᄌ ᅡ ᆨᄒ ᅧ ᆼᄇ ᅧ ᆯ ᄎ ᅮ ᆯ ᄒ ᅡᄉ ᅵᄀ ᅵ ᄃ ᅩᄆ ᅢᄀ ᅡᄀ ᅧ ᆨᄋ ᅳ ᆯ ᄋ
ᅨᄎ ᅳ ᆨ ᄒ ᅡ ᆫ ᄃ ᅡ ᆫᄉ ᅮ ᆫ ᄆ ᅩᄒ ᅧ ᆼᄀ ᅪ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄒ ᅪ ᆯᄋ ᅭ ᆼ ᄒ ᅡᄋ ᅧ ᄋ ᅨᄎ ᅳ ᆨ ᄒ ᅡ ᆫ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅳ ᆯ ᄇ ᅵᄀ ᅭᄒ ᅡ ᆫ ᄀ ᅧ ᆯᄀ ᅪ, ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄆ ᅩᄒ ᅧ ᆼᄋ ᅵ ᄃ ᅥ ᄋ
ᅮᄉ ᅮᄒ ᅡᄋ ᅧ ᆻᄃ ᅡ.
ᄀ
ᅵᄉ ᅡ ᆼᄋ ᅴ ᄀ ᅧ ᆼᄋ ᅮ ᄌ ᅵᄋ ᅧ ᆨᄆ ᅡᄃ ᅡ ᄃ ᅡᄅ ᅳᄀ ᅦ ᄂ ᅡᄐ ᅡᄂ ᅡᄌ ᅵᄆ ᅡ ᆫ, ᄇ ᅩ ᆫ ᄋ ᅧ ᆫᄀ ᅮᄋ ᅦᄉ ᅥ ᄉ ᅡᄋ ᅭ ᆼᄃ ᅬ ᆫ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭᄂ ᅳ ᆫ ᄌ ᅵᄋ ᅧ ᆨᄉ ᅥ ᆼᄋ ᅳ ᆯ ᄇ ᅡ ᆫᄋ ᅧ ᆼ ᄒ
ᅡᄌ ᅵ ᄆ ᅩ ᆺ ᄒ ᅡᄂ ᅳ ᆫ ᄒ ᅡ ᆫᄀ ᅨᄌ ᅥ ᆷᄋ ᅵ ᄌ ᅩ ᆫ ᄌ ᅢᄒ ᅡ ᆫᄃ ᅡ. ᄇ ᅵᄅ ᅩ ᆨ ᄌ ᅵᄋ ᅧ ᆨᄉ ᅥ ᆼᄋ ᅳ ᆫ ᄇ ᅡ ᆫᄋ ᅧ ᆼᄒ ᅡᄌ ᅵ ᄆ ᅩ ᆺ ᄒ ᅡᄋ ᅧ ᆻᄌ ᅵᄆ ᅡ ᆫ, ᄌ ᅵᄋ ᅧ ᆨᄇ ᅧ ᆯᄅ ᅩ ᄃ ᅦᄋ ᅵᄐ ᅥᄅ ᅳ ᆯ ᄉ ᅮᄌ ᅵ ᆸ·ᄌ ᅥ ᆨᄋ ᅭ ᆼ ᄒ ᅢ ᄋ
ᅣᄒ ᅡᄂ ᅳ ᆫ ᄇ ᅥ ᆫᄀ ᅥᄅ ᅩᄋ ᅮ ᆫ ᄉ ᅵ ᆯᄌ ᅦ ᄀ ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭᄋ ᅦ ᄇ ᅵᄒ ᅢ ᄇ ᅵᄀ ᅭᄌ ᅥ ᆨ ᄃ ᅦᄋ ᅵᄐ ᅥ ᄉ ᅮᄌ ᅵ ᆸᄀ ᅪ ᄌ ᅥ ᆨᄋ ᅭ ᆼ ᄋ ᅵ ᄋ ᅭ ᆼ ᄋ ᅵᄒ ᅡ ᆫ ᄇ ᅵᄌ ᅥ ᆼᄒ ᅧ ᆼ ᄂ ᅩ ᆼᄋ ᅥ ᆸᄀ ᅵᄉ ᅡ ᆼᄌ ᅡᄅ ᅭᄋ ᅴ ᄒ ᅭ ᄋ
ᅭ ᆼᄉ ᅥ ᆼᄋ ᅳ ᆯ ᄋ ᅵ ᆸᄌ ᅳ ᆼ ᄒ ᅡ ᆯ ᄉ ᅮ ᄋ ᅵ ᆻᄋ ᅥ ᆻᄃ ᅡ.
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2017, 28 ( 3) , 617–624
A study on cabbage wholesale price forecasting model using unstructured agricultural meteorological data †
SooHee Jang
1
· Heuiju Chun2
· Inho Cho3
· DongHwan Kim4
13
TheIMC
2
Department of Statistics and Information, Dongduk Women’s University
4
Department of International Trade and Distribution, Anyang University
Received 2 May 2017, revised 23 May 2017, accepted 25 May 2017
Abstract
The production of cabbage, which is mainly cultivated in open field, varies greatly depending on weather conditions, and the price fluctuation is largely due to the presence of a substitute crop. Previous studies predicted the production of cabbage using actual weather data, but in this study, we predicted the wholesale price using unstructured agricultural meteorological data on the web. From January 2009 to October 2016, we collected documents including the cabbage on the portal site, and extracted keywords related to weather in the collected documents. We compared the forecast wholesale prices of simple models and unstructured agricultural weather models at the time of shipment. The simple model is AR model using only wholesale price, and the unstruc- tured agricultural weather model is AR model using unstructured agricultural weather data additionally. As a result, the performance of unstructured agricultural weather model was has been found to be more accurate prediction ability.
Keywords: Cabbage, wholesale price, unstructured agricultural meteorological, AR model.
†
This research was supported by ‘Agricultural Biotechnology Development Program’, Ministry of Agri- culture, Food and Rural Affairs.
1
Employee, TheIMC, Seoul 04030, Korea.
2
Corresponding author: Associate professor, Department of Statistics and Information Science, Dong- duk Women’s University, Seoul 02748, Korea. Email: [email protected].
3
Director, TheIMC, Seoul 04030, Korea.
4
