1 |
Andrews DW. 1991. Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59:817-858.
DOI
|
2 |
APQA (Animal and Plant Quarantine Agency). 2020. Slaughter record 2020. Accessed in https://www.qia.go.kr/livestock/clean/listTcsjWebAction.do?clear=1 on 3 May 2022.
|
3 |
Chavas JP, Holt MT. 1991. On nonlinear dynamics: The case of the pork cycle. American Journal of Agricultural Economics 73:819-828.
DOI
|
4 |
Chuluunsaikhan T, Ryu G, Yoo KH, Rah H, Nasridinov A. 2020. Incorporating deep learning and news topic modeling for forecasting pork prices: The case of South Korea. Agriculture 10:513.
DOI
|
5 |
Deaton A, Muellbauer J. 1980. Economics and consumer behavior. Cambridge University press, Cambridge, UK.
|
6 |
Devadoss S, Westhoff PC, Helmar MD, Grundmeier E, Skold KD, Meyers WH, Johnson SR. 1989. The FAPRI modeling system at CARD: A documentation summary. Center for Agricultural and Rural Development, Iowa State University, Ames, IA, USA.
|
7 |
Gouk S, Seo H, Suh T, Kwon S, Kim K. 2021. Situation and implications for recent agricultural product price changes. KREI Agri-Policy Focus, Korea Rural Economic Institute, Naju, Korea. [in Korean]
|
8 |
Greene WH. 2012. Econometric analysis 7th edition. Prentice Hall, England, UK.
|
9 |
Han S. 2020. Study on development of mid- to long-term outlook model based on pig traceability information. Korean Pork Self-Help Fund Management Committee, Seoul, Korea. [in Korean]
|
10 |
Lee H, Ji S, Kim C, Kang J. 2022. Trends and projection of supply of Korean beef, pigs, and dairy cows. Agricultural outlook 2022: Agriculture and rural areas, seeing new hope. Korea Rural Economic Institute, Naju, Korea. [in Korean]
|
11 |
Lee H, Ji S, Suh T. 2021. Monthly Hanwoo supply and forecasting models. Korean Journal of Agricultural Science 48:797-806. [in Korean]
DOI
|
12 |
MAFRA (Ministry of Agriculture, Food and Rural Affairs). 2020. Agriculture, forestry and livestock food statistics 2020. MAFRA, Sejong, Korea. [in Korean]
|
13 |
McKillop W. 1967. Supply and demand for forest products-an econometric study. Hilgardia 38:1-132.
DOI
|
14 |
Newey WK, West KD. 1987. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55:703-708.
DOI
|
15 |
Skold KD, Holt MT. 1988. Dynamic elasticities and flexibilities in a quarterly model of the US pork sector. Proceedings of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management. St. Louis, MO, USA.
|
16 |
Prescott DM, Stengos T. 1987. Bootstrapping confidence intervals: An application to forecasting the supply of pork. American Journal of Agricultural Economics 69:266-273.
DOI
|
17 |
Ryu G, Nasridinov A, Rah H, Yoo KH. 2020. Forecasts of the amount purchase pork meat by using structured and unstructured big data. Agriculture 10:21.
DOI
|
18 |
Seo H, Kim C, Kim J. 2020. A study on development of Korea agricultural outlook model, KREI-KASMO 2020. Korea Rural Economic Institute, Naju, Korea. [in Korean]
|
19 |
Warren GF, Pearson FA. 1928. Interrelationships of supply and price. Cornell University, Ithaca, NY, USA.
|
20 |
Wooldridge JM. 2010. Econometric analysis of cross section and panel data. MIT press, Cambridge, MA, USA.
|
21 |
Zeileis A. 2004. Econometric computing with HC and HAC covariance matrix estimators. Vienna University of Economics and Business, Wien, Austria.
|