Addressing accuracy in chronic rice data problem

The Jakarta Post, 14 March 2019

The rice production figure has been a source of policy and political debates in Indonesia for many years now. The disassociation between the development of rice prices in the market and production data happens all the time. In fact, soaring prices that indicate a supply shortage still happens especially when the official figure records a substantial rice surplus. 

Many parties have blamed the official production figures as the main cause of these inconsistencies. It is suspected of suffering from overestimation because of the use of subjective measurements when estimating it.

Technically, rice production is obtained from the production of paddy multiplied by paddy to rice conversion rates, which varies from province to province. Meanwhile, the production figure of a paddy is calculated by multiplying two variables, namely the harvested area and productivity (yield per hectare).

Since 1973, Statistics Indonesia (BPS) and the Agriculture Ministry have collaborated to estimate the production figure of paddy and secondary crops. In practice, the collection of the harvested area data becomes the Ministry’s responsibility while the BPS collects productivity data through a crop-cutting survey (Survei Ubinan). Data compilation and processing, as well as public release, are carried out by the BPS.

However, due to the issue of overestimation, the BPS has suspended to release the production figure officially since 2016 until the new method for harvested area estimation is completely developed.

However, for a policy purpose and the interest of the above ministry, the production data has still being calculated through this business process although it is not officially published by the BPS. In this regard, an official production figure is supposed to be disseminated by the BPS.

The harvested area data is suspected of being the main source of an upward bias in production data because it was collected through subjective measurements, mainly the “eye-estimate” method.

Actually, the issue of overestimation does not only apply to paddies but also to some main food crop commodities, such as maize and soybean that use the same method for harvested area data collection.

A BPS study in 1997, for instance, pointed out that the harvested area of a paddy in Java suffered from an overestimation of around 17 percent. Unfortunately, there was no significant follow-up after this finding. The main obstacle at that time was the availability of technologies and resources, such as remote sensing and satellite imagery data, to make the development of a reliable objective measurement possible.

However, thanks to the development of geospatial technology and the availability of paddy field data based on satellite imagery over the last 10 years, the chance to develop such a method became possible in 2015.

Since then the BPS, in conjunction with other government institutions, has developed an objective measurement, a so-called area sampling frame (ASF) technique, to estimate the harvested area of a paddy.

ASF is a promising method that is designated to produce more accurate harvested area estimation by making use of the newest paddy field area information obtained from satellite imagery as a sampling frame. The new paddy field area used for ASF is only about 7 million hectares, which is well below the figure obtained from the administrative report (around 8 million ha).

As the consequence of ASF implementation, the whole process of paddy production estimation is managed by the BPS. The rice production figure obtained from the new framework was made public for the first time last year.

A BPS study in 1997 [...] pointed out that the harvested area of a paddy field in Java suffered from an overestimation of around 17 percent.

The new figure confirmed that the overestimation in production data obtained from the old method reached around 30 percent due to the subjectivity of the harvested area measurement.

Despite the fact that the new figure has ended the prolonged debate around the accuracy of rice production data and marked a new era of rice data in Indonesia, there are still some issues around food crop statistics that must be addressed. 

First, since the new figure has confirmed the presence of overestimation, the question is what should be done to the previous figures before ASF was implemented? It is a big question to answer as correct past historical data is very critical post-analysis. It is also about how to revise our history of figures in the past. We have to bear in mind that the success story of former president Soeharto in achieving rice self-sufficiency leading him to be praised by the Food and Agricultural Organization in 1986 was based on data that (possibly) was subject to overestimation.

Moreover, to be consistent, all economic indicators, such as gross domestic product in the agricultural sector that used the old data as their input of calculation in the past must also be adjusted accordingly. 

Although there is a “data amnesty” initiative, it is not enough to resolve the issue. It is inevitable that reliable and sensible rice production data must be recalculated for at least the last 10 years.The ASF basically only fixed the problem of paddies. Meanwhile, for secondary food crops, such as maize and soybean, the issue of overestimation is still there.

In fact, the Agriculture Ministry still calculated the production figures of those commodities using the old method in its own interest for policy purposes.

On top of that, as a breakthrough, the ASF is still subject to some limitations. For instance, it still makes use of outdated input in obtaining harvested area estimation, i.e., the galengan conversion rate to exclude parts of a paddy field that are not cultivated, which are instead used as boundaries and embankments.

The conversion rate was obtained from a survey conducted in 1969 and 1970. Some experts suspect that it suffers from underestimation. Another critical issue is that it is costly. To be implemented properly nation-wide, a huge number of surveyors are needed to monitor the growth phase of crops in a selected sample.

Moreover, the issue of human error due to subjectivity in determining the growth phase is still there. Therefore, there is still plenty of room for improvement and new innovations in this area in the future.