DOI: https://doi.org/10.14710/agrisocionomics.v8i3.20468

DETERMINANT OF RICE PRICE IN INDONESIA: A FOURIER ENGLE-GRANGER COINTEGRATION TEST

*Rita Ariani orcid  -  Faculty of Agriculture, Universitas Malikussaleh, Lhokseumawe, Indonesia, Indonesia
Nurjannah Nurjannah orcid scopus publons  -  Faculty of Economics, Universitas Samudra, Langsa, Indonesia, Indonesia
Adhiana Adhiana scopus  -  Faculty of Agriculture, Universitas Malikussaleh, Lhokseumawe, Indonesia, Indonesia
Kamal Fachrurrozi orcid scopus publons  -  Faculty of Economics and Business, Universitas Syiah Kuala, Banda Aceh, Indonesia, Indonesia
Open Access Copyright 2024 Agrisocionomics: Jurnal Sosial Ekonomi Pertanian under http://creativecommons.org/licenses/by-sa/4.0.

Citation Format:
Abstract

The issue of food prices is a critical topic that need to be discussed. Food prices has implications on economic and society. In Indonesia, rice is the most widely comsumed staple. Unfortunately, the prices of rice are often unstable due various factors. This research investigates the relationship between exchange rate, money supply, and volatility of oil prices on rice prices in Indonesia.The research study used data from the period February 2008 to December 2022 based on data availability. All research data used are secondary data with time series type. Rice price data is sourced from the Food and Agriculture Organization (FAO), exchange rates and oil prices are sourced from the Federal Reserve Economic Data (FRED), and money supply is sourced from the Indonesia Economic and Financial Statistics (SEKI). This study uses the Fourier Engle-Granger (FEG) cointegration method as a novelty in looking at cointegration that has structural breaks and the FMOLS, DOLS, and CCR methods as analysis. The results found that the research variables were found to have cointegration in the rice price model. Furthermore, the exchange rate was found to have a significant negative effect (-0.454%, -0.420%, -0.456%) on rice prices. The money supply had a significant positive effect (0.640%, 0.627%, 0.639%), and the volatility of oil prices had a significant positive effect (0.024%, 0.031%, 0.026%) on rice prices. The results of this research have important policy implications for policymakers to control money circulation, maintain exchange rate stability, and use renewable energy alternatives.

Fulltext View|Download
Keywords: exchange rate, fourier cointegration, money supply, rice price, volatility of oil prices

Article Metrics:

Article Info
Section: Articles
Language : EN
Recent articles
DYNAMICS OF COMPETITIVENESS AND MARKET POSITION OF INDONESIAN COCONUT SHELL CHARCOAL EXPORTS IN THE INTERNATIONAL MARKET SOCIAL CAPITAL AND FARMERS' DECISION TO CULTIVATE PULU MANDOTI EMAS (PME) LOCAL RICE: A PROBIT MODEL ADOPTION INNOVATION STRATEGY IN ORGANIC FARMING INNOVATION BASED ON SUSTAINABLE EXTENSION ON DRY LAND IN GUNUNGKIDUL REGENCY More recent articles
  1. Adjemian, M. K., Arita, S., Meyer, S., & Salin, D. 2024. Factors affecting recent food price inflation in the United States. Applied Economic Perspectives and Policy, 46(2), 648–676. https://doi.org/10.1002/aepp.13378
  2. Awan, A. G., & Imran, M. 2015. Food price inflation and its impact on Pakistan’s economy. Food Science and Quality Management, 41, 61–73. https://core.ac.uk/download/pdf/234684073.pdf
  3. Aydoğan, B., & Vardar, G. 2020. Evaluating the role of renewable energy, economic growth and agriculture on CO2 emission in E7 countries. International Journal of Sustainable Energy, 39(4), 335–348. https://doi.org/10.1080/14786451.2019.1686380
  4. Becker, R., Enders, W., & Lee, J. 2006. A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381–409. https://doi.org/10.1111/j.1467-9892.2006.00478.x
  5. Darwez, F., Alharbi, F., Ifa, A., Bayomei, S., Mostfa, E., Lutfi, A., Haya, M. A., & Alrawad, M. (2023). Assessing the Impact of Oil Price Volatility on Food Prices in Saudi Arabia: Insights From Nonlinear Autoregressive Distributed Lags (NARDL) Analysis. ECONOMICS - Innovative and Economics Research Journal, 11(2), 5–23. https://doi.org/10.2478/eoik-2023-0056
  6. Hdom, H. A. D., & Fuinhas, J. A. 2020. Energy production and trade openness: Assessing economic growth, CO2 emissions and the applicability of the cointegration analysis. Energy Strategy Reviews, 30. https://doi.org/10.1016/j.esr.2020.100488
  7. Enders, W., & Lee, J. (2012). The flexible Fourier form and Dickey-Fuller type unit root tests. Economics Letters, 117(1), 196–199. https://doi.org/10.1016/j.econlet.2012.04.081
  8. Engle, R. F., & Granger, C. W. J. 1987. Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251–276. https://doi.org/10.2478/ats-2018-0019
  9. Fachrurrozi, K., Fahmiwati, Hakim, L., Aswadi, & Lidiana. 2021. Pengaruh kemiskinan dan pengangguran terhadap kriminalitas di Indonesia di tahun 2019. Jurnal Real Riset, 3(2), 173–178. https://doi.org/10.47647/jrr
  10. Fachrurrozi, K., Masbar, R., Aliasuddin, & Seftarita, C. 2022. Energy-growth-globalization (EGG) nexus in N-11 countries. Heliyon, 8(9), e10522. https://doi.org/10.1016/j.heliyon.2022.e10522
  11. Faisal, F., Sulaiman, Y., & Tursoy, T. 2019. Does an asymmetric nexus exist between financial deepening and natural resources for emerging economy? Evidence from multiple break cointegration test. Resources Policy, 64(April), 101512. https://doi.org/10.1016/j.resourpol.2019.101512
  12. Fasanya, I. O., & Olawepo, F. 2018. Determinants of food price volatility in Nigeria. Agricultura Tropica et Subtropica, 51(4), 165–174. https://doi.org/10.2478/ats-2018-0019
  13. Gregory, A. W., & Hansen, B. E. 1996. Tests for cointegration in models with regime and trend shifts. Oxford Bulletin of Economics and Statistics, 58(2), 555–560. https://doi.org/10.1111/j.1468-0084.1996.mp58003008.x
  14. Hatemi-J, A. (2008). Tests for cointegration with two unknown regime shifts with an application to financial market integration. Empirical Economics, 35(3), 497–505. https://doi.org/10.1007/s00181-007-0175-9
  15. Hamulczuk, M., & Skrzypczyk, M. 2022. European union agri-food prices during covid-19 and their selected determinants. Problems of Agricultural Economics, 371(2), 5–27
  16. Hermawan, W., Fitrawaty, F., & Maipita, I. 2017. Factors Affecting the Domestic Price of Rice in Indonesia. Jejak, 10(1), 155–171. https://doi.org/10.15294/jejak.v10i1.9133
  17. Hdom, H. A. D., & Fuinhas, J. A. (2020). Energy production and trade openness: Assessing economic growth, CO2 emissions and the applicability of the cointegration analysis. Energy Strategy Reviews, 30. https://doi.org/10.1016/j.esr.2020.100488
  18. Ibrahiem, D. M., & Hanafy, S. A. 2020. Dynamic linkages amongst ecological footprints, fossil fuel energy consumption and globalization: an empirical analysis. Management of Environmental Quality: An International Journal, 31(6), 1549–1568. https://doi.org/10.1108/MEQ-02-2020-0029
  19. Ike, G. N., Usman, O., & Sarkodie, S. A. 2020. Fiscal policy and CO2 emissions from heterogeneous fuel sources in Thailand: Evidence from multiple structural breaks cointegration test. Science of the Total Environment, 702, 134711. https://doi.org/10.1016/j.scitotenv.2019.134711
  20. Ikhsan, I., Fachrurrozi, K., Nasir, M., Elfiana, E., & Nurjannah, N. 2022. Energy-Growth Nexus in Indonesia: Fresh Evidence from Asymmetric Causality Test. International Journal of Energy Economics and Policy, 12(1), 396–400. https://doi.org/10.32479/ijeep.11837
  21. İnal, V., Canbay, Ş., & Kırca, M. 2023. Determinants of Food Prices in Türkiye: Fourier Engle-Granger Cointegration Test. Journal of Economic Policy Researches, 10(1), 133–156. https://doi.org/10.26650/jepr1132061
  22. Ismaya, B. I., & Anugrah, D. F. 2018. Determinant of Food Inflation: the Case of Indonesia. Buletin Ekonomi Moneter Dan Perbankan, 21(1), 81–94. https://doi.org/10.21098/bemp.v21i1.926
  23. Köse, N., & Ünal, E. (2024). The effects of the oil price and temperature on food inflation in Latin America. Environment, Development and Sustainability, 26(2), 3269–3295. https://doi.org/10.1007/s10668-022-02817-2
  24. Lindawati, Emalisa, & Zulfida, I. 2022. Analysis of rice supply determinants in North Sumatera. IOP Conference Series: Earth and Environmental Science, 977(1). https://doi.org/10.1088/1755-1315/977/1/012056
  25. Mahmood, H., Maalel, N., & Zarrad, O. 2019. Trade openness and CO2 emissions: Evidence from Tunisia. Sustainability (Switzerland), 11(12). https://doi.org/10.3390/su10023295
  26. Mgale, Y. J., Timothy, S., & Dimoso, P. 2022. Measuring Rice Price Volatility and Its Determinants in Tanzania: An Implication for Price Stabilization Policies. Theoretical Economics Letters, 12(02), 546–563. https://doi.org/10.4236/tel.2022.122031
  27. Moussa, R. K., Ousseini, B., & Taha, C. K. 2024. Asymmetric effects of oil prices on inflation in Côte d’Ivoire. Resources Policy, 90(August 2023), 104842. https://doi.org/10.1016/j.resourpol.2024.104842
  28. Nwoko, I. C., Aye, G. C., & Asogwa, B. C. 2016. Effect of oil price on Nigeria’s food price volatility. Cogent Food and Agriculture, 2(1). https://doi.org/10.1080/23311932.2016.1146057
  29. Nwoko IC, & Aye GC. (2022). Crude oil price and food price volatility: A conceptual analysis. International Journal of Scientific Research Updates, 4(1), 108–115. https://doi.org/10.53430/ijsru.2022.4.1.0067
  30. Özdurak, C. 2021. Major Determinants of Food Price Volatility in Turkey: Inflation Surge Aftermath of 2016. SSRN Electronic Journal, 2016(Figure 1). https://doi.org/10.2139/ssrn.3904157
  31. Perron, P. 1989. The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis. Econometrica, 57(6), 1361–1401. https://doi.org/10.2307/1913712
  32. Putra, A. W., Supriatna, J., Koestoer, R. H., & Soesilo, T. E. B. 2021. Differences in local rice price volatility, climate, and macroeconomic determinants in the indonesian market. Sustainability (Switzerland), 13(8). https://doi.org/10.3390/su13084465
  33. Raheem, I. D., & Ogebe, J. O. 2017. CO2 emissions, urbanization and industrialization: evidence from a direct and indirect heterogeneous panel analysis. Management of Environmental Quality: An International Journal, 28(6), 851–867. https://doi.org/10.1108/MEQ-09-2015-0177
  34. Raihan, A., & Tuspekova, A. 2022. The nexus between economic growth, renewable energy use, agricultural land expansion, and carbon emissions: New insights from Peru. Energy Nexus, 6(March), 100067. https://doi.org/10.1016/j.nexus.2022.100067
  35. Rehman, F. U., & Khan, D. 2015. The Determinants of Food Price Inflation in Pakistan: An Econometric Analysis. Advances in Economics and Business, 3(12), 571–576. https://doi.org/10.13189/aeb.2015.031205
  36. Rivai, A. 2022. The monetary policy impact on agricultural growth and food prices. International Journal of Research in Business and Social Science, 11(9), 158–165. https://doi.org/10.20525/ijrbs.v11i9.2234
  37. Rodrigues, P. M. M., & Robert Taylor, A. M. 2012. The flexible fourier form and local generalised least squares de-trended unit root tests. Oxford Bulletin of Economics and Statistics, 74(5), 736–759. https://doi.org/10.1111/j.1468-0084.2011.00665.x
  38. Samal, A., Ummalla, M., & Goyari, P. 2022. The impact of macroeconomic factors on food price inflation: an evidence from India. Future Business Journal, 8(1). https://doi.org/10.1186/s43093-022-00127-7
  39. Sarwar, M. N., Hussain, H., & Maqbool, M. B. 2020. Pass through effects of oil price on food and non-food prices in Pakistan: A nonlinear ARDL approach. Resources Policy, 69(September), 101876. https://doi.org/10.1016/j.resourpol.2020.101876
  40. Taghizadeh-Hesary, F., Rasoulinezhad, E., & Yoshino, N. 2019. Energy and Food Security: Linkages through Price Volatility. Energy Policy, 128(November 2018), 796–806. https://doi.org/10.1016/j.enpol.2018.12.043
  41. Teena Lakshmi, B., & Shivakumar, K. M. 2022. An Econometric Analysis of Food Inflation in India. Economic Affairs (New Delhi), 67(3), 301–306. https://doi.org/10.46852/0424-2513.3.2022.22
  42. Ulussever, T., Ertugrul, H. M., Depren, S. K., Kartal, M. T., & Depren, Ö. 2023. Estimation of Impacts of Global Factors on World Food Prices: A Comparison of Machine Learning Algorithms and Time Series Econometric Models. Foods, 12, 873
  43. Umar, U. A., & Umar, A. 2022. Effects of Exchange Rate on Food Inflation in Nigeria: A Non-Linear ARDL Approach. Gusau International Journal of Management and Social Sciences, 5(1), 195–209
  44. Waheed, R., Chang, D., Sarwar, S., & Chen, W. 2018. Forest, agriculture, renewable energy, and CO2 emission. Journal of Cleaner Production, 172, 4231–4238. https://doi.org/10.1016/j.jclepro.2017.10.287
  45. Yilanci, V. 2023. The Determinants of Forest Products Footprint: A New Fourier Cointegration Approach. Forests, 14(5). https://doi.org/10.3390/f14050875
  46. Yilanci, V. 2019. A Residual-Based Cointegration test with a Fourier Approximation. In MPRA (Issue 95395). https://mpra.ub.uni-muenchen.de/95395/
  47. Zhou, J., Ma, Z., Wei, T., & Li, C. 2021. Threshold effect of economic growth on energy intensity— evidence from 21 developed countries. Energies, 14(14), 1–12. https://doi.org/10.3390/en14144199
  48. Zivot, E., & Andrews, D. W. K. 1992. Futher Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270

Last update:

No citation recorded.

Last update:

No citation recorded.