MANILA (ANN/PHILIPPINE DAILY INQUIRER) – In recent years, the agricultural landscape has witnessed tumultuous shifts in food supply and pricing, exemplified by staggering increases, such as a sevenfold surge in onion prices, and instances of farmers discarding tomato harvests due to a lack of buyers.
Blamed for inflation spikes, fluctuating food prices often force the government into reactive crisis management rather than proactive prevention, primarily due to a dearth of accurate and timely data. This deficiency results in suboptimal program design, flawed planning, and delayed decision-making.
The recurring challenges in rice supply and prices provide a glaring illustration of this issue.
In January 2021, the Philippine Statistics Authority (PSA) reported a rice inventory of 2.332 million tonnes.
Considering domestic output of just over 13 million tonnes and imports nearing 3 million tonnes, the total supply for the year amounted to approximately 18.4 million tonnes
By December 31, only 1.86 million tonnes remained, indicating a usage of around 16.5 million tonnes. Factoring in quantities for seeds, animal feed, industrial use, and waste, roughly 14.9 million tonnes were consumed as food.
This should have triggered concern, as the consumption figure of 14.9 million tonnes implies an average per capita rice consumption of 135 kilos in 2021, significantly surpassing the Department of Agriculture’s (DA) estimate of 119 kilos.
Unfortunately, this discrepancy went unaddressed, and the PSA’s 2021 ending inventory figure remained unchanged. This oversight subsequently led to statistical anomalies in 2022.
Despite a slight production dip in 2022, the total supply was higher due to increased imports of 3.8 million tons. Yet, the PSA reported a nearly identical ending inventory of 1.85 million tons as in 2021. This discrepancy raises questions about the excess supply.
The PSA maintained its inventory estimates were accurate, assuming a per capita consumption of about 110 kilos in 2022.
Given this, either consumption increased or production decreased. High rice prices in 2022 make a significant increase in consumption unlikely. Total consumption growth likely mirrored the population growth rate, about 1.5 per cent, or roughly 200,000 tonnes.
Thus, the discrepancy likely lies in production estimates. The source’s calculations suggest production was around 9.7 million tonnes, not the reported 12.9 million tonnes. This implies a substantial 25 per cent drop in palay production, 5 million tonnes less than reported. Even using the DA’s higher consumption figure, production still falls short of PSA’s estimate by 3.2 million tonnes.
Industry players note a 30 per cent decline in major fertiliser imports as prices doubled, hinting at reduced fertiliser use.
However, the PSA reported only a one per cent drop in production and yield.
A significant production drop in 2022 suggests reliance on incorrect figures, possibly contributing to the rice crisis in August and September. This overestimation of local production distorted the market’s actual rice supply.
This raises concerns about the effectiveness of investments in the rice industry, suggesting limited improvement in farmers’ productivity and competitiveness. Consequently, reliance on imports increases, along with vulnerability to international market disturbances
Persistent data discrepancies will continue until data collection and analysis improve. The DA’s recent claim of ending 2023 with a 90-day stock level, 78 per cent higher than 2022’s ending inventory, is questionable given modest production increases and significant import reductions.
Effective analysis, planning, and decision-making require accurate information. Addressing recurrent food shortages hinges on resolving data deficits.
The PSA likely needs more staff and technical resources for a dedicated agricultural data system. Within the DA, a system should link data from various agencies and programs, providing implementers and policymakers with timely, relevant information. The private sector can aid by regularly validating data accuracy.
