Antonio, Ronald Jeremy and Valera, Harold Glenn and Mishra, Ashok and Pede, Valerien and Yamano, Takashi and Vieira, Bernardo Oliva (2024): Rice price inflation dynamics in the Philippines.
![]() |
PDF
MPRA_paper_123641.pdf Download (809kB) |
Abstract
In recent years, prices fertilizer, cereals and rice prices have increased significantly due to the Russia-Ukraine war and the export restrictions imposed by India. Thus resulting in higher rice prices in the Philippines. This paper examines the dynamic relationship between rice price inflation and key drivers in the Philippines by estimating a panel vector auto-regression model using monthly data from 1994 to 2023. We find evidence that the effect of world rice price shock is generally the larger and more persistent than the effects of other factors. We also find that movements in rice price inflation are explained by domestic fuel price shocks and to a lesser extent by the world urea price shocks. The impulse response functions driven by those three shocks vary over the sample, especially before a change in food policy such as the imposition of the rice tariffication in 2019. Further analysis suggests that El Niño Southern Oscillation shocks tend to induce an inflationary effect on rice prices in high-poverty and rice-sufficient regions. Our results have important food policy implications for rice markets, and offer timely insights into the desirability of current proposals to reduce rice prices for consumers and improve existing support for famers to boost rice production.
Item Type: | MPRA Paper |
---|---|
Original Title: | Rice price inflation dynamics in the Philippines |
Language: | English |
Keywords: | Panel data, consumer price index, input prices, weather, fuel price persistence shocks, commodities |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level ; Inflation ; Deflation N - Economic History > N3 - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy > N35 - Asia including Middle East Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q18 - Agricultural Policy ; Food Policy |
Item ID: | 123641 |
Depositing User: | Harold Glenn Valera |
Date Deposited: | 20 Feb 2025 19:16 |
Last Modified: | 20 Feb 2025 19:16 |
References: | Balié, J., Minot, N., & Valera, H. G. A. (2021). Distributional impacts of the rice tariffication policy in the Philippines. Economic Analysis and Policy, 69, 289-306. Balié, J., & Valera, H. G. (2020). Domestic and international impacts of the rice trade policy reform in the Philippines. Food Policy, 92, 101876. Bhattacharya, R., & Jain, R. (2020). Can monetary policy stabilise food inflation? Evidence from advanced and emerging economies. Economic Modelling, 89, 122-141. Bordey, F. H., Castillo, G. T., Moya, P. F., & Padolina, W. G. (2016). Rice self-sufficiency under the lens of provincial analysis: A new way of looking at National Rice Security. National Academy of Science and Technology, Philippines. BusinessWorld (2022). Rice prices set to rise as high input costs dampen farm output. Retrieved from https://www.bworldonline.com/economy/2022/09/28/477277/rice-prices-set-to-rise-as-high-input-costs-dampen-farm-output/. Cao, J., Zhang, Z., Tao, F., Chen, Y., Luo, X., & Xie, J. (2023). Forecasting global crop yields based on El Niño Southern Oscillation early signals. Agricultural Systems, 205, 103564. Chau, N. T., & Ahamed, T. (2022). Analyzing factors that affect rice production efficiency and organic fertilizer choices in Vietnam. Sustainability, 14(14), 8842. Dawe, D., & Kimura, S. (2023). Mitigating emerging food security risks in rice markets. Development Asia. Retrieved from https://development.asia/insight/mitigating-emerging-food-security-risks-rice-markets. Durevall, D., Loening, J. L., & Birru, Y. A. (2013). Inflation dynamics and food prices in Ethiopia. Journal of Development Economics, 104, 89-106. Hammoudeh, S., Nguyen, D. K., & Sousa, R. M. (2015). US monetary policy and sectoral commodity prices. Journal of International Money and Finance, 57, 61-85. Hebebrand, C., & Glauber, J. W. (2023). The Russia-Ukraine war after a year: Impacts on fertilizer production, prices, and trade flows. In: Glauber, J., & Laborde Debucquet, D. (Eds.), The Russia-Ukraine Conflict and Global Food Security; Section One: A conflict with global consequences. Washington, DC: International Food Policy Research Institute. pp. 43-47. Iddrisu, A. A., & Alagidede, I. P. (2020). Monetary policy and food inflation in South Africa: A quantile regression analysis. Food Policy, 91, 101816. Jaworski, K. (2021). Measuring food inflation during the COVID-19 pandemic in real time using online data: a case study of Poland. British Food Journal, 123(13), 260-280. Liaqat, Z. (2019). Does government debt crowd out capital formation? A dynamic approach using panel VAR. Economics Letters, 178, 86-90. Love, I., & Zicchino, L. (2006). Financial development and dynamic investment behavior: Evidence from panel VAR. The Quarterly Review of Economics and Finance, 46(2), 190-210. Lin, F., Li, X., Jia, N., Feng, F., Huang, H., Huang, J., Fan, S., Ciais, P., & Song, X. P. (2023). The impact of Russia-Ukraine conflict on global food security. Global Food Security, 36, 100661. Mottaleb, K. A., Kruseman, G., & Snapp, S. (2022). Potential impacts of Ukraine-Russia armed conflict on global wheat food security: A quantitative exploration. Global Food Security, 35, 100659. National Economic and Development Authority (2022). Rice Tariffication Law is the best model that we have to help both farmers and consumers — NEDA. Retrieved from https://neda.gov.ph/rice-tariffication-law-is-the-best-model-that-we-have-to-help-both-farmers-and-consumers-neda/. Nguyen, A. D., Dridi, J., Unsal, F. D., & Williams, O. H. (2017). On the drivers of inflation in Sub-Saharan Africa. International Economics, 151, 71-84. Poursina, D., Schaefer, K. A., Hilburn, S., & Johnson, T. (2023). Economic impacts of the Black Sea Grain Initiative. Journal of Agricultural Economics. DOI:10.1111/1477-9552.12549. Shan, L. Y. (2023). India’s rice export ban to hurt millions globally. These countries will be the worst hit. CNBC. Retrieved from https://www.cnbc.com/2023/08/02/indias-rice-export-ban-to-impact-millions-in-asia-africa-middle-east.html. Shen, X., Holmes, M. J., & Lim, S. (2015). Wealth effects and consumption: a panel VAR approach. International Review of Applied Economics, 29(2), 221-237. Shively, G., & Thapa, G. (2017). Markets, transportation infrastructure, and food prices in Nepal. American Journal of Agricultural Economics, 99(3), 660-682. Termos, A., Naufal, G., & Genc, I. (2013). Remittance outflows and inflation: The case of the GCC countries. Economics Letters, 120(1), 45-47. Tule, M. K., Salisu, A. A., & Chiemeke, C. C. (2019). Can agricultural commodity prices predict Nigeria’s inflation? Journal of Commodity Markets, 16, 100087. Ubilava, D. (2017). The ENSO effect and asymmetries in wheat price dynamics. World Development, 96, 490-502. Ubilava, D., & Abdolrahimi, M. (2019). The El Niño impact on maize yields is amplified in lower income teleconnected countries. Environmental Research Letters, 14(5), 054008. United States Department of Agriculture (2023). Production, supply, and distribution. Retrieved from https://apps.fas.usda.gov/psdonline/app/index.html#/app/advQuery. Valera, H. G., Balié, J., & Magrini, E. (2022). Is rice price a major source of inflation in the Philippines? A panel data analysis. Applied Economics Letters, 29(16), 1528-1532. Wu, X., & Xu, J. (2021). Drivers of food price in China: a heterogeneous panel SVAR approach. Agricultural Economics, 52(1), 67-79. Zhang, C., Meng, C., & Getz, L. (2014). Food prices and inflation dynamics in China. China Agricultural Economic Review, 6(3), 395-412. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/123641 |