Applied Big Data Driven Study on Shock Absorption and Tolerance Bands of Staple Food Commodities Price Volatility in East Java
DOI:
https://doi.org/10.46851/248Abstrak
This study investigates the day-to-day volatility dynamics of five staple food commodities in East Java which are Red Bird’s Eye Chili Pepper, Medium Rice, Bendera Powdered Milk, Free-Range Chicken Meat, and Commercial Chicken Eggs. By utilizing daily price data from January 1, 2021, to February 2, 2025, collected via big-data scraping of a government price monitoring website. A GARCH model with Student-t innovations is fitted to each return series, from which one-day 95% Value-at-Risk (VaR) thresholds are derived to establish an evidence-based "tolerance band" for policy intervention. The results show that Red Bird’s Eye Chili Pepper has the widest band, with an allowable daily drop of 2.5% and a rise of 10.14%, whereas Bendera Powdered Milk exhibits the narrowest range. All five series display extreme volatility persistence coefficients are near or above 1, but a critical finding is that the markets for Medium Rice and Free-Range Chicken Meat are not shock absorbent, with persistence values exceeding 1. This indicates that any market disruption has a permanent effect on their future volatility, pointing to deep structural inefficiencies. These empirically derived VaR-based guardrails provide a quantitative framework for timely market stabilization, while the persistence analysis highlights the need for long-term structural reforms, particularly for the rice and chicken sectors.
Keywords: food price volatility; GARCH; value-at-risk; big data.
JEL: C54, Q11, Q1
Referensi
Abaidoo, R., & Agyapong, E. K. (2023). Global food price volatility and inflationary pressures among developing economies. SN Business & Economics, 3, 188. https://doi.org/10.1007/s43546-023-00569-3
Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. https://doi.org/10.1109/TAC.1974.1100705
Amolegbe, K. B., Upton, J., Bageant, E., & Blom, S. (2021). Food price volatility and household food security: Evidence from Nigeria. Food Policy, 102, 102061. https://doi.org/10.1016/j.foodpol.2021.102061
Azmi, U., Siswono, G. O., Syaifudin, W. H., Saputra, W. H., & Ningtyas, P. M. A. (2022). Risk analysis on agricultural commodity portfolio using Value at Risk (VaR) and Expected Shortfall (ES) based on ARIMA–GARCH. In M. S. Mufid & D. Adzkiya (Eds.), 7th International Conference on Mathematics – Pure, Applied and Computation: Mathematics of Quantum Computing (Article 030027, AIP Conference Proceedings, Vol. 2641). American Institute of Physics. https://doi.org/10.1063/5.0115885
Bellemare, M.F. (2015), Rising Food Prices, Food Price Volatility, and Social Unrest. American Journal of Agricultural Economics, 97: 1-21. https://doi.org/10.1093/ajae/aau038
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1
Bollerslev, T. (1987). A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return. The Review of Economics and Statistics, 69(3), 542–547. https://doi.org/10.2307/1925546
Brander, M., Bernauer, T., & Huss, M. (2023). Trade policy announcements can increase price volatility in global food commodity markets. Nature Food, 4(4), 331–340. https://doi.org/10.1038/s43016-023-00729-6
Brooks, C. (2019) Introductory Econometrics for Finance. Cambridge University Press, Cambridge. https://doi.org/10.1017/9781108524872
Carine Meyimdjui, and Jean-Louis Combes. "Food Price Shocks and Household Consumption in Developing Countries: The Role of Fiscal Policy", IMF Working Papers 2021, 012 (2021), accessed 12/9/2025, https://doi.org/10.5089/9781513566887.001
Cavallo, A., & Rigobon, R. (2016). The Billion Prices Project: Using online prices for measurement and research. Journal of Economic Perspectives, 30(2), 151–178. https://doi.org/10.1257/jep.30.2.151
Ceballos, F., Hernandez, M. A., Minot, N., & Robles, M. (2016). Transmission of food price volatility from international to domestic markets: Evidence from Africa, Latin America, and South Asia. In M. Kalkuhl, J. von Braun, & M. Torero (Eds.), Food price volatility and its implications for food security and policy (pp. 303–328). Springer. https://doi.org/10.1007/978-3-319-28201-5_13
Chavas, J., Hummels, D., & Wright, B. D. (2014). The economics of food price volatility. https://doi.org/10.7208/chicago/9780226129082.001.0001
Diawati, L., & Rasyid, A. S. (2025). Mitigating retail rice price volatility for sustainable supply chains: An optimization and regression-based approach. F1000Research, 14, 311. https://doi.org/10.12688/f1000research.161723.2
Dutta, A., Uddin, G. S., Sheng, L. W., Park, D., & Zhu, X. (2024). Volatility dynamics of agricultural futures markets under uncertainties. Energy Economics, 136, 107754. https://doi.org/10.1016/j.eneco.2024.107754
Einav, L., & Levin, J. (2014). Economics In The Age Of Big Data. Science, 346(6210), 715–721. Https://Doi.Org/10.1126/Science.1243089
Engle, R. F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric Reviews, 5(1), 1–50. https://doi.org/10.1080/07474938608800095
Engle, R. F., & Manganelli, S. (2004). CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business & Economic Statistics, 22(4), 367–381. http://www.jstor.org/stable/1392044
Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987–1007. https://doi.org/10.2307/1912773
Gascon, C. S., & Schmitz, A. (2020). Using High-Frequency data to track the regional economy. The Regional Economist, 28(3). https://fedinprint.org/item/fedlre/88936
Gilbert, C. L., & Morgan, C. W. (2010). Food Price Volatility. Philosophical Transactions Of The Royal Society B: Biological Sciences, 365(1554), 3023–3034. Https://Doi.Org/10.1098/Rstb.2010.0139
GLOSTEN, L.R., JAGANNATHAN, R. and RUNKLE, D.E. (1993), On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48: 1779-1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.
Hamzah, I. N., & Huang, W. (2023). The dynamics of strategically important food preference in Indonesia: An empirical evaluation of consumption pattern and welfare loss. Economic Analysis and Policy, 79, 435–449. https://doi.org/10.1016/j.eap.2023.06.024
Hansen, P.R. and Lunde, A. (2005), A forecast comparison of volatility models: does anything beat a GARCH(1,1)?. J. Appl. Econ., 20: 873-889. https://doi.org/10.1002/jae.800
Harding, M., & Hersh, J. (2018). Big Data In Economics. Iza World Of Labor, (451). Https://Doi.Org/10.15185/Izawol.451
Headey, D., Bachewe, F., Marshall, Q., Raghunathan, K., & Mahrt, K. (2024). Food prices and the wages of the poor: A cost-effective addition to high-frequency food security monitoring. Food Policy, 125, 102630. https://doi.org/10.1016/j.foodpol.2024.102630
Headey, D. D., Bachewe, F. N., Marshall, Q., Raghunathan, K., & Mahrt, K. (2023). Food prices and the wages of the poor: A low-cost, high-value approach to high-frequency food security monitoring (IFPRI Discussion Paper No. 2174). International Food Policy Research Institute. https://doi.org/10.2499/p15738coll2.136614
Headey, D. D. (2018). Food Prices and Poverty. The World Bank Economic Review, 32(3) 676–691. https://www.jstor.org/stable/48557126
Imam Mukhlis, and Özlem Sökmen Gürçam. 2022. “The Role of Agricultural Sector in Food Security and Poverty Alleviation in Indonesia and Turkey”. Asian Journal of Agricultural Extension, Economics & Sociology 40 (11):430–436. https://doi.org/10.9734/ajaees/2022/v40i111728.
Isah, K., & Muse, B. (2024). Modelling the volatility inducement of climate change in food prices: The role of technological shocks. Asian Economics Letters, 5. https://doi.org/10.46557/001c.115719
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. Vol. 3, McGraw-Hill, New York.
Kalkuhl, M., Von Braun, J., & Torero, M. (2016). Food price volatility and its implications for food security and policy. https://doi.org/10.1007/978-3-319-28201-5
Kornher, L., & Kalkuhl, M. (2013). Food price volatility in developing countries and its determinants. AgEcon Search (University of Minnesota, USA), 52(4), 277–308. https://doi.org/10.22004/ag.econ.156132
Kumar, A., Kailasam, A. S., Rai, A., Khanna, M., Shukla, S., Das, S., & Chakraborti, A. (2025). The Impact of Meteorological Factors on Crop Price Volatility in India: Case studies of Soybean and Brinjal. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2503.11690
Lambert, L. H., Schoeneman, J. P., Lambert, D. M., & Brienen, M. W. (2025). Road networks and food price volatility. Global Food Security, 47, 100884. https://doi.org/10.1016/j.gfs.2025.100884
Lestari, E. P., Prajanti, S. D. W., Wibawanto, W., & Adzim, F. (2022). ARCH-GARCH Analysis: An Approach to Determine The Price Volatility of Red Chili. AGRARIS: Journal of Agribusiness and Rural Development Research, 8(1), 90–105. https://doi.org/10.18196/agraris.v8i1.12060
Manfredo, M. R., & Leuthold, R. M. (1999). Value-at-Risk Analysis: A Review and the Potential for Agricultural Applications. Review of Agricultural Economics, 21(1), 99–111. https://doi.org/10.2307/1349974
Martin, Will & Mamun, Abdullah & Minot, Nicholas. (2024). Food Trade Policy and Food Price Volatility. https://doi.org/10.13140/RG.2.2.27235.12329
Matondang, M. R., Krisnamurthi, B., & Herawati, H. (2023). PRICE FLUCTUATIONS AND VOLATILITY OF NATIONAL STRATEGIC FOOD COMMODITIES IN INDONESIA. Agrisocionomics Jurnal Sosial Ekonomi Pertanian, 8(1), 134–146. https://doi.org/10.14710/agrisocionomics.v8i1.17753
Minot, N. (2014). Food price volatility in sub-Saharan Africa: Has it really increased? Food Policy, 45, 45–56. https://doi.org/10.1016/j.foodpol.2013.12.008
Muslim, A. (2014). Analyzing volatility of rice price in Indonesia using ARCH/GARCH model. Economic Journal of Emerging Markets, 6(1), 1–12. https://doi.org/10.20885/ejem.vol6.iss1.art1
Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347–370. https://doi.org/10.2307/2938260
Nguyen, H., Randall, M., & Lewis, A. (2024). Factors Affecting Crop Prices in the Context of Climate Change—A Review. Agriculture, 14(1), 135. https://doi.org/10.3390/agriculture14010135
Purwantini, T. B., & Syafrial, S. (2022). The Impact Of Food Price Volatility On Farming Household Welfare In Indonesia. Journal Of Asian Business And Economic Studies, 29(4), 311–326. Https://Doi.Org/10.1108/Jabes-06-2021-0066
Rezitis, A. N., & Tsionas, M. (2018). Modeling asymmetric price transmission in the European food market. Economic Modelling, 76, 216–230. https://doi.org/10.1016/j.econmod.2018.08.004
Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461–464. http://www.jstor.org/stable/2958889
Setiadi, Sumastuti, E., & Rakhmawaty, Y. (2024). Food Price Volatility and Agricultural Welfare in Emerging Economies: Evidence from Provincial Indonesia. Moneta : Journal of Economics and Finance, 2(3), 210–226. https://doi.org/10.61978/moneta.v2i3.824
Swinnen, J. and McDermott, J. (2020), Covid-19 and Global Food Security. EuroChoices, 19: 26-33. https://doi.org/10.1111/1746-692X.12288
Theresia, A., Ikhsan, M., Kacaribu, F. N., & Sumarto, S. (2025). Spillover effect of food producer price volatility in Indonesia. Economies, 13(9), 256. https://doi.org/10.3390/economies13090256
Tsay, R. S. (2010). Analysis Of Financial Time Series (3rd Ed.). John Wiley & Sons.
Umar, Z., Suleman, M. T., & Jarbolov, S. (2021). An Examination Of Food Price Volatility And Its Determinants In Central Asia. Journal Of Commodity Markets, 24, 100171. Https://Doi.Org/10.1016/J.Jcomm.2021.100171
Waiswa, D., & Yavuz, F. (2023). Market integration and asymmetric price transmission in selected domestic markets for major staple foods in Uganda. Future Business Journal, 9(1). https://doi.org/10.1186/s43093-023-00281-6
Waiswa, D., Yavuz, F. Market integration and asymmetric price transmission in selected domestic markets for major staple foods in Uganda. Futur Bus J 9, 97 (2023). https://doi.org/10.1186/s43093-023-00281-6
Wang, L., Duan, W., Qu, D. et al. What matters for global food price volatility?. Empir Econ 54, 1549–1572 (2018). https://doi.org/10.1007/s00181-017-1311-9
Wibowo, R. P., Pebriyani, D., & Indriyanti, T. (2025). Analysis of rice price volatility in Medan City, Indonesia. Agro Bali Agricultural Journal, 8(1), 291–302. https://doi.org/10.37637/ab.v8i1.2216
Zmami, M., & Ben Salha, O. (2023). What factors contribute to the volatility of food prices? New global evidence. Agricultural Economics (AGRICECON). https://doi.org/10.17221/99/2023-AGRICECON
Zmami, M., & Ben-Salha, O. (2023). What factors contribute to the volatility of food prices? New global evidence. Agricultural Economics (Zemedelska Ekonomika), 69(5), 171–184. https://doi.org/10.17221/99/2023-agricecon
Diterbitkan
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 Journal of Business and Political Economy : Biannual Review of The Indonesian Economy
Artikel ini berlisensi Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
