Welcome to the PalayStat

The PalayStat system is an interactive web-based system that aims to provide an easy access to the outputs of the Rice-Based Farm Household Survey (RBFHS). Information available in the system includes socioeconomic profiles, technologies adoption, and farm-level input-output, among other things. At present, 43 output tables are available in the system.

Rationale for the Project

There is a demand on rice-based socioeconomic information thus it is necessary to bring together general information about rice in the Philippines. Researchers, developers of rice technologies, economic planners, policymakers, students, and advocacy groups constantly look for rice information for planning, formulating policies, or getting insights about the rice situation. However, much of the data available are on the national level and may not necessarily be suitable for local planning or describing the local situation. There is also a lack on the availability and accessibility of farm-level time series data. Hence, readily available information responsive to the needs at the regional or provincial level is wanting.

To address the issue of data shortage, the Socioeconomics Division (SED) of the Philippine Rice Research Institute (PhilRice) conducted quinquennial surveys to collect information about the technology, social and economic status of rice-based farming households in 30 major rice-producing provinces around the Philippines known as the Rice-Based Farm Household Surveys (RBFHS). The surveys were conducted from 1996-1997, 2001-2002, 2006-2007 and 2011-2012. Nevertheless, the circulation of information from these surveys was limited within the Institute. Only in rare instances when PhilRice was asked to comment about the technological and socioeconomic status of rice farmers that these information were brought to public use. Although there had been attempts to synchronize the RBFHS databases the congruence of the data still fell short of the goal to have a consolidated RBFHS Big Data[1]. The databases and matrices for each RBFHS survey rounds were still stored separately making data processing a time-consuming and painstaking endeavor. Thus, it is important to organize these databases to make it accessible, available, and user-friendly for potential users.

[1]Big Data is used to describe a massive volume of both structured and unstructured data that is so large that it's difficult to process with traditional database and software techniques (UN Global Pulse, 2012:13)

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