Abstract

Smallholder rice farming is central to poverty reduction, food security, and rural development in the Philippines. One key issue is that around 41 percent of the country's irrigable land is not irrigated. Moreover, many irrigation systems are suggested to be poorly managed with unequal water distribution.

The Irrigated Rice Production Enhancement Project (IRPEP) was implemented in three regions (VI, VII and X) of the Philippines, between 2010-2015. It was designed to improve rice productivity and smallholder livelihoods by strengthening canal irrigation infrastructure of Communal Irrigation Systems (CIS), improving the capacity of the Irrigators' Associations (IAs) that manage the CIS, and offering complementary marketing support, Farmer Field Schools, and emergency seed buffer stocks.

The data collected are used to test the effectiveness of the 5-year Irrigated Rice Production Enhancement Project to improve the livelihoods of smallholder rice farmers in the Philippines.

For more information, please, click on the following link https://www.ifad.org/en/web/knowledge/-/publication/impact-assessment-irrigated-rice-production-enhancement-project.

Geographic coverage

Rural coverage. Sample covers six provinces of the Philippines across three regions (Region VI, VIII, X).

Analysis unit

Households

Universe

Smallholder farmer households

Kind of data

Sample survey data [ssd]

Sampling procedure

The analysis is based on quantitative data from 2,104 households and 113 IAs covering beneficiary and non-beneficiary groups, along with qualitative data from project and IA staff. The IRPEP's impact is estimated by comparing beneficiary and nonbeneficiary households and IAs using statistical matching techniques to ensure a clean and unbiased comparison. This process resulted in a household dataset used for analysis that covers 1,015 treatment and 664 control households, and an IA dataset used to assess impact on IA level indicators from 58 treatment and 55 control IAs.

To identify a well-matched set of treatment and control CISs and households, the sample selection for the impact assessment sought to mirror IRPEP's beneficiary selection process by initially conducting the identification at the CIS level. At the start of the process there were a number of non- beneficiary CIS in the project provinces, allowing for control CIS to be selected from within the same provinces. Using these IRPEP and non-IRPEP CIS, a two-stage process was used to select the final set of treatment and control CIS. This involved both data analysis and the knowledge of local staff.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The household and IA questionnaires collected a wide range of information, which was then used to create the impact indicators and other variables to be used in the data analysis. The household questionnaire included detailed questions on agricultural production and marketing collected by season, parcel and crop for the previous 12 months, as well as socio-demographic characteristics, other income generating activities, asset ownership, experience of shocks, access to credit, and receipt of external support from various sources. The IA questionnaire gathered information on their structure and facilities, irrigation water coverage, gender differentiated membership, and income and expenditures over the past 12 months, including irrigation fee collection and operation and maintenance spending.

Note: some variables have missing labels. Please, refer to the questionnaire for more details.

The HiH Agricultural Typology analysis targets the identification of micro-regional level innovation opportunities, bottlenecks, and investment gaps. This concept is based on the production possibilities frontier applied to farm activities. It draws on household-level surveys and geospatial data on agroecological conditions, accessibility, and poverty.

The final Agricultural Typology consists of a classification representing a combination of agricultural potential, agricultural efficiency, and priority (poverty) components in each region. The 7 classes are as follows:

• Critical with moderate agricultural opportunities.

• Medium priority with moderate agricultural opportunities.

• Low priority.

• High priority.

• Medium priority with high agricultural opportunities.

• Low priority with high agricultural opportunities.

• High-performance.

** Data Components**

The Agricultural Potential component provides the maximum agricultural income smallholder farmers can attain if performing at maximum capacity (their own, as well as of the markets, productive infrastructure, and basic services surrounding them). It is determined by both the biophysical and economic factors. The interaction of these two sets of elements establishes the maximum income a farmer can earn from agricultural activities.

The Agricultural Efficiency component defines how much of the potential is attained by farmers in a region under current conditions. To increase their efficiency, farmers need to reduce transaction costs in agricultural production and marketing through improved infrastructure (such as roads) and services (such as market information), overcome market failures (access to credit, insurance, land markets, etc.), and receive better access to basic services (such as education and extension services).

The Priority component reveals a region’s degree of urgency for investments in development, measured in terms of the wellbeing of the local population, the target beneficiaries of agricultural innovation efforts.

For more information please refer to the Guidance note listed under Data and Resources section.

Supplemental Information

The HiH Agricultural Typology analysis is a dataset developed in the framework of the Hand-in-Hand (HIH), which is an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) aiming to accelerate the agricultural transformation and sustainable rural development to eradicate poverty, and end hunger and all forms of malnutrition.