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Application of Vector Error Correction Model (VECM) and Impulse Response Function for Analysis Data Index of Farmers’ Terms of Trade
Objectives: To determine the relationship among Price Index Received by Farmer (PIR), Price Index Paid by the Farmers (PIP) and the Farmers' Terms of Trade (FTT) by using the model VECM, and to attempt to know the behavior of (FTT) if there is a shock in variables PIR and PIP. Methods/Statistical Analysis: Vector Error Correction Model (VECM) is a model Vector Autoregressive (VAR) which can be used for data series which are non stationery and have cointegration relationship (long term relationship). The model VECM can also be used to see the movement in one variable to give a response regarding the shock produce by another variable through the graph of Impulse Response Function (IRF). Findings: Based on the data of Farmers' Terms of Trade in Indonesia over the periods from January 2008 to November 2013, we have determined that the best model VECM is VECM order 2 (VECM (2)). Applications: Based on the graph of the Impulse Response Function (IRF) we have established that the response of FTT toward the shock of a price both received and paid by the farmers is fluctuative and temporary over time.
Farmers’ Terms of Trade (FTT), Impulse Response Function, Price Index Received by Farmer (PIR), Price Index Paid by the Farmers (PIP), VAR, VECM.
- Asteriou D, Hall SG. Applied econometrics: A modern approach. Revised ed. New York: Palgrave Macmillan; 2007. PMCid:PMC1868797.
- Brandt PT, Williams JT. Multiple time series models. Thousand Oaks, California: Sage Publications Inc; 2007. p. 7–148. Crossref
- Enders W. Applied econometric time series. New York: John Wiley and Sons; 2015. p. 1–63.
- Gujarati D. Basic econometrics. 4th ed. Singapore: McGrawHill International Editions; 2003.
- Pala A. Structural breaks, cointegration and causality by VECM analysis of crude oil and food price. International Journal of Energy Economics and Policy. 2013 Jul; 3(3):238–46.
- Tsay RS. Multivariate time series analysis with R and financial applications. New Jersey: John Wiley and Sons; 2014. p. 1–457.
- Engle FR, Granger CWJ. Cointegration and error correction: Representation, estimation and testing. Econometrica. 1987 Mar; 55(2):251–76. https://doi.org/10.2307/1913236
- Kirchgassner G, Wolters J. Introduction to modern time series analysis. Berlin: Springer-Verlag; 2007. p. 1–277. Crossref
- Lutkepohl H. New introduction to multiple time series analysis. Berlin: Springer-Verlag; 2005. p. 1–764. Crossref 10. Harris R, Robert S. Applied econometrics time series. 2nd ed. Canada: John Wiley and Sons; 2005.
- BPS statistics Indonesia. Statistics of Farmers’ Terms of Trade by Month in Indonesia. Jakarta: Central Bureau of Statistics; 2014. p. 1–30.
- BPS statistics Indonesia. Statistical Yearbook Indonesia 2014. Jakarta: BPS Statistics Indonesia; 2014. p. 1–710.
- Khan AA, Ahmed QM. Agriculture terms of trade in Pakistan: Issues of profitability and standard of living of the farmers. Proceedings PSDE Conference; Islamabad. 2005. p. 1–23.
- Loretto R. Calculation and structure of the consumers price index, consumer price index revision advisory committee. New Zealand: Statistics New Zealand; 1997. p. 1–82.
- Pankrazt A. Forecasting with univariate box- jenkins Models: Concepts and cases. New York: John Wiley and Sons; 1983. p. 1–587.
- Pankratz A. Forecasting with dynamic regression models. New York: John Wiley and Sons Interscience Publication; 1991. PMCid:PMC208248. Crossref
- Box GEP, Cox DR. An analysis of transformation. Journal of the Royal Statistical Society (Series B). 1964; 26(2):211–43.
- Montgomery D, Jennings C, Kulahci M. Introduction to time series analysis and forecasting. New York: John Wiley and Sons Interscience Publication; 2008.
- Chatfield C. The analysis of time series: An introduction. 5th ed. Boston: Chapman and Hall; 1995.
- Reinsel GC. Elements of multivariate time series analysis. New York: Springer-Verlag; 1993. Crossref
- Lutkepohl H. Introduction to multiple time series analysis. Berlin: Springer-Verlag; 1991. Crossref
- Johansen S. Statistical analysis of cointegration vectors. Journal of Economic Dynamic and Control. 1988 June; 12(2-3):231–54. Crossref
- Maddala GS, Kim IM. Unit roots cointegration and structural change. UK: Cambridge University Press; 2004.
- Wei WS. Time series analysis univariate and multivariate methods. 2nd ed. Canada: Pearson Education Inc; 2006.
- Sekar P. Diagnostic checking of time series models. Indian Journal of Science and Technology. 2010 Sep; 3(9):1026–31.
- Sekar P. Application of time series models. Indian Journal of Science and Technology. 2010 Sep; 3(9):1032–7.
- Pyndick R, Rubinfeld D. Econometric models and economic forecast. 4th ed. Singapore: McGraw Hill Book Co; 1998.
- Johansen S. Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica. 1991 Nov; 59(6):1551–80. Crossref
- Gunes S. Functional income distribution in Turkey: A cointegration and VECM analysis. Journal of Economic and Social Research. 2007 Jul; 9(2):23–36.
- Sadeghi M, Alavi SY. Modelling the impact of money on GDP and inflation in Iran: Vector Error Correction Model (VECM) approach. African Journal of Business Management. 2013 Sep; 7 (35):3423–34. Crossref
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