Price analysis between commodity groups of inflation in Banten province from 2008 to 2018

https://doi.org/10.35912/ijfam.v2i4.447
Published: Mar 25, 2021

Abstract:

Purpose: This study aimed to see how each commodity group's movement pattern that forms inflation between one commodity group and another, and to see any major linkages between groups of inflation-forming commodities in Banten Province.

Research methodology: The research is undergone by using the Vector Auto Regressive (VAR) model approach through testing of Impulse Response Function (IRF) and Variance Decomposition (VD).

Results: The results show that the inflation rate in the goods/services commodity groups in Banten Province have a dynamic relationship between one another. The group itself dominates inflationary movements in all commodity groups. Monthly time series data is used for 2008-2018 time spans.

Limitation: The linkages presented as the results are performed in commodity groups; thus, further research would inform more about inter-linkage between commodities.

Contribution: The insight of knowing the pattern is beneficial for implication policy in regional inflation targeting especially in Banten Province.

Keywords: Inflation, IRF, VAR, VD

Keywords:
1. Inflation
2. IRF
3. VAR
4. VD
Authors:
1 . Deswita Herlina
Fakultas Ekonomi dan Bisnis, Universitas Sultan Ageng Tirtayasa
2 . Amalia Romadhona
Fakultas Ekonomi dan Bisnis, Universitas Sultan Ageng Tirtayasa
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How to Cite
Herlina, D., & Romadhona, A. (2021). Price analysis between commodity groups of inflation in Banten province from 2008 to 2018. International Journal of Financial, Accounting, and Management, 2(4), 321–341. https://doi.org/10.35912/ijfam.v2i4.447
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Issue & Section
Vol. 2 No. 4 (2021): March
Articles
References

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  2. Bima, JJA. (2017). Analysis of inflation relationship between group of goods/services commodity in Central Java 2009.1-2015.12. Diponegoro University.
  3. Boediono. (2014). Ekonomi Moneter (Edisi ketiga). Yogyakarta: BPFE.
  4. [BPS] Central Bureau of Statistics of Banten. (2018). Consumer price index and inflation of Banten 2018. Central Bureau of Statistics of Banten.
  5. [BPS] Central Bureau of Statistics of Banten. (2017). Consumer price index and inflation of Banten 2017. Central Bureau of Statistics of Banten.
  6. [BPS] Central Bureau of Statistics of Banten. (2016). Consumer price index and inflation of Banten 2016. Central Bureau of Statistics of Banten.
  7. [BPS] Central Bureau of Statistics of Banten. (2015). Consumer price index and inflation of Banten 2015. Central Bureau of Statistics of Banten.
  8. [BPS] Central Bureau of Statistics of Banten. (2014). Consumer price index and inflation of Banten 2014. Central Bureau of Statistics of Banten.
  9. [BPS] Central Bureau of Statistics of Banten. (2013). Consumer price index and inflation of Banten 2013. Central Bureau of Statistics of Banten.
  10. [BPS] Central Bureau of Statistics of Banten. (2012). Consumer price index and inflation of Banten 2012. Central Bureau of Statistics of Banten.
  11. [BPS] Central Bureau of Statistics of Banten. (2011). Consumer price index and inflation of Banten 2011. Central Bureau of Statistics of Banten.
  12. [BPS] Central Bureau of Statistics of Banten. (2010). Consumer price index and inflation of Banten 2010. Central Bureau of Statistics of Banten.
  13. [BPS] Central Bureau of Statistics of Banten. (2009). Consumer Price Index and Inflation of Banten 2009. Central Bureau of Statistics of Banten.
  14. [BPS] Central Bureau of Statistics of Banten. (2008). Consumer price index and inflation of Banten 2008. Central Bureau of Statistics of Banten.
  15. Carlino, Gerald and Robert Defina. (1998). The differential regional effects of monetary policy. The Review of Economics and Statistics, 80(4), 572-587.
  16. Clements, Kenneth W. and HY Izan. (1987) The measurement of inflation: a stochastic approach. Journal of Business and Economic Statistics, 5(3), 339-350.
  17. Darman. (2013). Effect of economic growth on unemployment rate: analysis of okun law. Journal The Winners, 14(1), 1-12.
  18. Dickey.DA and WAFuller., (1979). Distribution of estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427-443.
  19. Gujarati, DN. & Porter, DC. (2013). Basic Econometrics. Jakarta Salemba Empat.
  20. Hartanto, Tri. 2011. Analisis keterkaitan harga antar kelompok komoditas pembentuk inflasi di Indonesia periode 2004-2010. Skripsi Thesis, Universitas Airlangga. Un-Published
  21. Ichsandimas, M. & Cahyadin, M. (2014). World oil prices and indonesia macroeconomic. Journal of Development Economics, 15(1), 27-33.
  22. Mankiw, NG. (2019). Macroeconomics, 10th Edition. New York Macmillan International.
  23. Phillips, AW. (1958). The relation between unemployment and the rate of change of money wage rates in the United Kingdom, 1861-1957. Ecnomica, 25(100), 283-299.
  24. Pindyck, S., Robert and Daniel L, Rubinfeld. (1998). Economectrics Models and Economic Forecast, Fourth Edition. Singapore. McGraw Hill International Edition.
  25. Ramadhan, Gaffari. (2009). Analisis keterkaitan harga antar kelompok komoditas pembentuk inflasi di Sumatera Barat. Buletin Ekonomi Moneter dan Perbankan, 11(3), 233-274.
  26. Sims, Christopher A. (1980). Comparison of interwar and postwar business cycles: monetarism reconsidered. American Economic Review, 70(4), 250-257.
  27. Stock, J.H. and Watson, M.W. (2005). Implications of dynamic factor models for VAR analysis. NBER working paper, No. W11467
  28. Suharyadi. & Purwanto, SK. (2013). Statistika untuk ekonomi dan keuangan modern. Jakarta. Salemba Empat.
  29. Wimanda, Rizki E. (2006). Regional inflation in Indonesia: characteristic, convergence, and determinants. Bank Indonesia Working Paper, No.13.