Revealed! A New Approach to Measuring Farmer Welfare: More Comprehensive, Practical, and Long Overlooked.

A Critical Assessment of Farmer Welfare Measurement Using the Farmer Terms of Trade and the Farmer Welfare Index

1. INTRODUCTION

The agricultural sector plays a vital role in supporting livelihoods and improving farmers’ welfare (Fatimah et al., 2021; Agustian et al., 2022). It also contributes significantly to economic development and growth, food security, and the competitiveness of agricultural products (Pratama & Budhi, 2023). Given these contributions, farmers, as the primary actors in agricultural development, require greater attention to ensure continuous improvements in their welfare (Kurniawan, 2022). In Indonesia, farmer welfare has traditionally been assessed using the Farmer Terms of Trade (FTT), known domestically as Nilai Tukar Petani (NTP). In fact, within the 2020–2024 National Medium-Term Development Plan (RPJMN), NTP was designated as one of the macroeconomic indicators for measuring farmer welfare (Bappenas/Ministry of National Development Planning, 2019).

Initially, the concept of terms of trade was developed in the context of international trade because it was considered to reflect the fairness of the distribution of trade benefits among countries. Consequently, it was regarded as a relevant basis for formulating economic development strategies, particularly for developing countries. The concept was subsequently extended to other contexts, including intersectoral terms of trade, which were applied to barter relationships between the agricultural sector and the industrial sector or other sectors of the economy. Indonesia's Farmer Terms of Trade (NTP) represents an example of terms of trade applied to a particular economic group, namely agricultural business households (Rumah Tangga Usaha Pertanian, RTUP). In general, terms of trade associated with the agricultural sector are referred to as Agricultural Terms of Trade (ATOT). This concept became particularly prominent and widely used during the 1980s (Lewis, 1958), but its application gradually declined during the 1990s and subsequently became less common in empirical economic measurement.

Although the broader concept of terms of trade has increasingly fallen out of use in some areas of economic analysis, NTP remains one of the most widely recognized agricultural development indicators in Indonesia. It continues to be used extensively by academics, government institutions, and economic actors to assess macro-level agricultural conditions. Indonesia may even be regarded as one of the few countries where NTP continues to receive substantial attention from the public, institutions, and academics as an indicator of farmer welfare (Simatupang, 1992). Simatupang (2012) explains that, in a literal sense, terms of trade represent the relative value of exchanges among economic entities, such as countries, sectors, or economic actors. Terms of trade also indicate the purchasing power of sellers relative to the prices of goods they purchase. This exchange ratio represents the relative value of various goods or services being traded. At the national level, terms of trade are generally measured through export–import relationships that reflect the exchange of goods and services between countries. At the sectoral level, terms of trade can be measured in several ways, including the exchange between final outputs, such as the total output of the agricultural sector relative to industrial-sector output; input–output exchanges, such as total agricultural output relative to total agricultural production inputs; and the relationship between total agricultural output and the total final consumption goods purchased by agricultural households.

A terms-of-trade value observed at a particular point in time is primarily useful for understanding relative prices or exchange prices but provides limited information for broader economic analysis. Its analytical significance becomes greater when changes are examined over time. Changes in terms of trade reflect shifts in relative prices, indicating whether the price of a particular good remains stable, declines, or increases relative to other goods. Therefore, terms of trade are commonly expressed as an index using a specified base year to facilitate comparisons across different periods.

According to BPS (2017), NTP is defined as the ratio between the Index of Prices Received by Farmers (It) and the Index of Prices Paid by Farmers (Ib), expressed as a percentage. The It index measures the average change in prices over a given period for a basket of agricultural products at the farm-gate or producer level, using a specified reference period. In contrast, the Ib index measures the average change in the prices of a basket of goods and services associated with production costs, capital goods, and household consumption in rural areas over a specified period. In other words, Ib combines the basket of goods and services associated with production costs and capital formation (Biaya Produksi dan Penambahan Barang Modal, IF) with the basket of goods and services consumed by agricultural households (Konsumsi Rumah Tangga, IK) in rural areas. These indices are calculated using the Laspeyres index method.

Improving farmers’ living standards is one of the major objectives of agricultural development, particularly in achieving food security and enhancing farmer welfare (Ruslan, 2022; Sitorus, 2022). Razi and Wahyuni (2022) noted that farmer welfare has traditionally been assessed through the Farmer Terms of Trade (NTP), rural poverty levels, and the Gini ratio in rural areas. Wahyudi (2024) and Ruslan (2022) define NTP as the ratio between the index of prices received by farmers (It) and the index of prices paid by farmers (Ib). NTP is used to measure farmers’ purchasing power in rural areas. It also reflects the terms of trade or exchange capacity between agricultural products and the goods and services used by farmers, including the costs incurred in agricultural production.

Suhartini and Rusastra (2013) further explained that when the prices of agricultural products increase at a higher rate than the prices of goods and services purchased by farmers, NTP will increase, assuming that production volume remains unchanged. Under such conditions, farmers’ income is expected to increase relatively faster than their expenditures. Nevertheless, in practice, an increase in farmers’ income does not necessarily occur automatically, given that the majority of farmers operate small-scale agricultural enterprises with limited production capacity and economic resources.

Based on the foregoing considerations, Muis and Marlin (2023) and Setiawan et al. (2019) argue that, conceptually, NTP is closely associated with changes in farmers’ income because farmer income is correlated with welfare. Accordingly, NTP has been considered a relevant indicator for representing developments in farmer welfare (Keumala & Zainuddin, 2018; Suhartini & Rusastra, 2013). However, this conceptual relationship requires careful interpretation because changes in relative prices do not necessarily correspond proportionally to changes in absolute income, consumption capacity, or broader dimensions of household welfare.

In response to the continuing debate surrounding the conceptual and empirical adequacy of NTP as a measure of farmer welfare, a meeting of Commission IX of the House of Representatives of the Republic of Indonesia (DPR-RI) with the Ministry of Finance, the Ministry of National Development Planning (Bappenas), Statistics Indonesia (BPS), Bank Indonesia (BI), and the Financial Services Authority (OJK) on June 8, 2022, agreed that BPS should review the methodology and accuracy of NTP and develop an additional indicator to complement NTP in measuring farmer welfare. This new indicator was subsequently referred to as the Farmer Welfare Index (FWI), or Indeks Kesejahteraan Petani (IKP). Compared with NTP, the FWI provides an alternative approach based on a multidimensional conception of welfare encompassing food and nutrition security, education, health, adequate living standards, income and resources, and risk mitigation.

In response to the ongoing debate regarding the conceptual limitations of NTP, various studies have addressed different aspects of the indicator. However, studies conducted by Afifah and Nalurita (2022), BPS West Java (2022), Darwis et al. (2020), Ervianti (2022), Firmansyah et al. (2022), Ilahi and Agustin (2022), Mulyawan (2022), and Sinaga et al. (2022) have primarily focused on NTP and its application to specific agricultural commodities. Studies that have linked NTP to the concept of welfare, such as those by Kurniawan (2022) and Rachmat (2013), have generally focused on the relationship between NTP and farmers’ income. To date, however, there has been limited research explicitly comparing the conceptual foundations, measurement dimensions, and analytical implications of NTP and FWI for assessing farmer welfare. This constitutes the principal research gap addressed by the present study.

Accordingly, this study aims to: (1) examine the dynamics of the national Farmer Terms of Trade (NTP) across agricultural subsectors; (2) assess the current condition and initial development of the Farmer Welfare Index (FWI); (3) critically analyze the strengths and limitations of NTP and FWI in measuring and interpreting farmer welfare; and (4) formulate recommendations and policy implications for improving the measurement of farmer welfare in Indonesia.

 

2. METHODOLOGY

 

2.1 Conceptual Framework

The conceptual framework of this study is grounded in welfare theory, particularly the ideas of Adam Smith (1776), which suggest that individuals are inherently motivated to satisfy their wants and needs. As individuals continuously strive to fulfill their preferences and needs, welfare is achieved when the level of satisfaction reaches its optimal level. From this perspective, welfare can be understood as the outcome of an individual's ability to satisfy various material and non-material needs through economic and social activities.

Yulhendri and Susanti (2017) further emphasize that household welfare, reflected in adequate consumption, improved education, harmonious family relationships, and the long-term existence and well-being of household members, represents a fundamental objective of households in their economic lives. Understanding the factors that determine future welfare enables households to select appropriate economic and social behaviors. In practice, individual welfare encompasses measurable indicators of achievement that can be used to assess the extent to which welfare objectives have been attained (Budy Kusnandar, 2022; Rizal et al., 2021).

Regional welfare is also influenced by the availability and utilization of resources, including human resources, physical resources, and other productive resources. These three categories of resources interact dynamically throughout the development process to promote economic growth and improve community welfare. The relationship between income and welfare may differ across socioeconomic groups. Middle- and upper-income households tend to allocate additional income to luxury goods and discretionary consumption, whereas lower-income groups, which are often characterized by greater vulnerability to poverty and limitations in health, nutrition, and education, can experience substantial improvements in welfare when their income increases (Todaro, 2011).

Welfare can also be assessed from several dimensions, including health, economic conditions, happiness, quality of life, and public perceptions of well-being. A prosperous household is generally better positioned to provide educational opportunities for its members, including access to higher levels of education. Similarly, higher levels of individual education can contribute to greater household welfare because education generates returns in the form of more stable employment opportunities and adequate income (Agustina Mutia et al., 2023; Fausy Ar et al., 2023). Thus, welfare is multidimensional and cannot be adequately represented by a single economic variable.

The level of welfare is closely associated with income. Sukirno (2018) argues that household or community income reflects an important dimension of welfare experienced by society. Nevertheless, income alone does not fully determine welfare because several other socioeconomic factors also influence living conditions and overall well-being. Guritno et al. (2014) similarly argue that changes in income are insufficient as a measure of welfare because they do not take into account expenditures required to meet household consumption needs. Consequently, welfare assessment requires consideration not only of income-generating capacity but also of purchasing power and the allocation of resources to satisfy basic and other household needs.

In assessing the performance of the agricultural sector, the Indonesian government has historically used the Farmer Terms of Trade (NTP) as a proxy indicator of farmer welfare. NTP has even been incorporated as a macroeconomic indicator in national development planning, with the government establishing a target range of approximately 105–108 (Bappenas/Ministry of National Development Planning, 2019). The use of NTP in this context is based on the assumption that the relative movement between prices received by farmers and prices paid by farmers reflects changes in their purchasing power and, consequently, their economic welfare.

The NTP concept was developed by Statistics Indonesia (BPS) as an instrument for evaluating the relative economic conditions and purchasing power of farmers. When it was initially developed, the farmer population covered by NTP measurement was limited primarily to those engaged in food-crop production, horticultural production involving vegetables and fruits, and smallholder plantation activities, and the measurement was conducted only in selected provinces. Over time, BPS improved the methodology and expanded the coverage of NTP measurement. In 2008, significant improvements were made in terms of both the coverage of farmer groups and the geographical coverage of provinces included in the calculation (Setiawan et al., 2019).

The definition of farmers was subsequently expanded to include individuals engaged in food crops, horticulture, plantations, livestock, and fisheries (Dauda, 2019; Yacoub & Mutiaradina, 2020). This broader coverage was intended to provide a more comprehensive representation of the economic conditions of agricultural households across different subsectors.

NTP was designed to allow measurement at both the national and regional levels. At the aggregate level, NTP represents the cumulative outcome of the various agricultural subsectors, thereby enabling the welfare-related conditions of individual subsectors and, where relevant, the commodities constituting those subsectors to be analyzed separately (Rachmat, 2013). Accordingly, NTP provides a framework for examining changes in the relative purchasing power of agricultural households across regions, subsectors, and commodity groups.

However, the conceptual framework underlying NTP primarily captures the economic and purchasing-power dimension of farmer welfare. It does not directly incorporate other important dimensions, such as health, education, food and nutrition security, housing conditions, asset ownership, income diversification, vulnerability, or farmers' capacity to manage economic risks. This limitation provides an important theoretical basis for comparing NTP with a multidimensional welfare measure such as the Farmer Welfare Index (FWI). The present study therefore uses the conceptual distinction between monetary/purchasing-power indicators and multidimensional welfare indicators as the basis for critically examining the strengths, limitations, and complementary roles of NTP and FWI in assessing farmer welfare.

 

Figure 1. Formula for the Farmer Terms of Trade (NTP)

 

The Farmer Terms of Trade (NTP) is defined as the ratio between the index of prices received by farmers and the index of prices paid by farmers. The index of prices received reflects changes in producer prices, whereas the index of prices paid represents changes in the prices of goods and services required by farming households, both for household consumption and agricultural production activities (Wahyudi, 2024).

Based on the NTP concept, farmer welfare is primarily associated with purchasing power, namely the ability of farmers' income to meet their consumption needs. An increase in NTP indicates that the purchasing power of farmers has improved because the prices received for agricultural products have increased relatively faster than the prices of goods and services that farmers purchase. Conversely, a decline in NTP indicates a deterioration in relative purchasing power.

The conceptual description of NTP and the various policies that influence its development are presented in Figure 2.

Figure 2. Description of the Farmer Terms of Trade (NTP) and Policies Influencing NTP

 

According to Darwanto (2005), the Farmer Terms of Trade (NTP) has a significant influence on farmers’ ability to meet their household needs. A low NTP indicates that farmers may face greater difficulties in fulfilling their basic living requirements, whereas a higher NTP generally indicates better purchasing power. Therefore, the level of the NTP ratio can serve as an indicator of farmer welfare, although it does not provide a fully accurate representation of welfare. In line with efforts to improve and comprehensively assess farmer welfare indicators, Statistics Indonesia (BPS) has been conducting surveys related to the Farmer Welfare Index (FWI/IKP) and analyzing data from various locations while gathering inputs from relevant stakeholders.

 

2.2 Scope of the Study

The scope of this study is divided into three main components. First, it examines the dynamics of the Farmer Terms of Trade (NTP) at the national level across agricultural subsectors. Second, it examines the current conditions and initial conceptual development of the Farmer Welfare Index (FWI/IKP). After establishing the conceptual foundations of these two indicators, the study comparatively assesses their respective strengths and limitations in measuring farmer welfare. Finally, the study presents conclusions and policy recommendations for developing a more comprehensive approach to measuring farmer welfare.

 

2.3 Study Coverage and Period

The study has a national scope and was primarily conducted during August–September 2024. Data and information were continuously updated through October 2024. In addition, historical time-series data on NTP developments across agricultural subsectors from 2020 to September 2024 were compiled to support the analysis.

 

2.4 Data Types and Data Collection Methods

Data were collected from various sources and references at the national level. To enrich the analysis, the study also incorporated data and information from previous studies examining NTP in specific cases and contexts. Data collection focused primarily on obtaining information on the development of national NTP values. The data consisted mainly of secondary time-series data, selected according to the requirements of the analytical framework.

The primary institutional sources included Statistics Indonesia (BPS), the Ministry of Agriculture of the Republic of Indonesia, and the Ministry of National Development Planning (Bappenas). In addition to statistical data, supplementary information concerning policies aimed at improving NTP was collected from government institutions, scientific journals, research publications, and other relevant literature.

 

2.5 Data Analysis

Data and information concerning changes in NTP and their implications for agricultural enterprises were collected and analyzed through several complementary approaches, including Focus Group Discussions (FGDs), literature reviews, analytical reviews, and participation in seminars or public hearings concerning NTP.

The analysis of national NTP dynamics across agricultural subsectors and the assessment of the initial conditions and development of the FWI concept employed quantitative descriptive analysis, particularly trend analysis. Meanwhile, the strengths and limitations of the NTP and FWI concepts were examined using a qualitative comparative analysis. Sari (2021) defines qualitative comparative analysis as a research approach that compares two or more objects, phenomena, policies, systems, or variables to identify similarities and differences among them.

 

3. RESULTS AND DISCUSSION

 

3.1 Development of NTP and Agricultural Terms of Trade for Production Costs (NTUP)

The Farmer Terms of Trade (NTP) represents the relative purchasing power of farmers. A higher NTP indicates greater relative purchasing power, whereas a lower NTP indicates a deterioration in farmers’ purchasing power relative to the goods and services they purchase. The calculation of NTP currently applied in Indonesia uses a weighting diagram (diagram timbang) that represents the relative weight or value of each agricultural commodity and the goods and services included in the corresponding commodity basket. The weighting diagram is established for a specific base year, which serves as the reference period for calculating the index. For the 2021–2023 period, NTP data were calculated using 2018 as the base year (2018 = 100).

The weighting values used to construct the Index of Prices Received by Farmers are based on the value of agricultural production sold by farmers for each type of agricultural commodity. Each agricultural subsector and commodity has a different weighting structure, reflecting its relative contribution to the overall index (Figure 3). The underlying data include production volumes, producer prices, and the proportion of each commodity marketed by farmers. Meanwhile, the weighting values used in the Index of Prices Paid by Farmers represent the expenditure or value of goods and services purchased by farmers for household consumption as well as for agricultural production activities (Center for Agricultural Data and Information, Ministry of Agriculture [Pusdatin Kementan], 2023).

This weighting structure is important because differences in commodity composition and expenditure patterns across subsectors directly influence the magnitude and interpretation of NTP. Consequently, changes in the aggregate NTP should be interpreted in conjunction with the underlying subsectoral and commodity-specific weights rather than as a uniform representation of the economic welfare of all farmers.

 

Figure 3. Weighting Scheme of Agricultural Commodity Sub-Sectors

 

The Farmer Terms of Trade (NTP) is used as a proxy for rapidly assessing farmer welfare, particularly in the short term, under the assumption that production quantities remain relatively constant over time. Over the medium and long term, NTP provides a more appropriate measure when complemented by indicators of agricultural output volumes or other sources of household income. NTP can also be used to assess the terms of trade between goods sold by farmers and the goods required for agricultural production and household consumption. In this NTP analysis, the data consist of annual averages from 2020 to 2024, using 2018 as the base year (2018 = 100), with NTP data for 2024 covering the period through September. NTP in the agricultural sector encompasses several subsectors, including food crops, horticulture, smallholder plantations, livestock, and fisheries. However, because the fisheries subsector does not fall under the authority of the Ministry of Agriculture, this study analyzes NTP for the agricultural sector excluding fisheries, hereafter referred to as “NTP for Narrowly Defined Agriculture.”

Based on Table 1, in 2020, the national aggregate agricultural Index of Prices Received by Farmers (It) reached 107.46, indicating an increase of 7.464% in the average price level of agricultural products compared with the average price level of similar products in the 2018 base year. Similarly, the Index of Prices Paid by Farmers (Ib) reached 105.72 in 2020, indicating a 5.72% increase in the prices of goods and services required by farmers compared with their price level in 2018. In 2020, the national aggregate NTP reached 101.65, indicating that farmers’ real purchasing power in 2020 was 1.65% higher than in 2018.

In 2022, the Index of Prices Received by Farmers reached 120.67, indicating that the average prices of agricultural products increased by 20.67% compared with the average prices of similar products in the 2018 base year.

The Index of Prices Paid by Farmers in 2022, which reached 112.43, likewise reflected a 12.43% increase in the prices of goods and services required by farmers compared with their price level in 2018. The combined national NTP in 2022 reached 107.33, indicating that farmers’ real purchasing power in 2022 was 7.33% higher than in 2018.

In the subsequent period, namely 2023, the national agricultural It reached 131.59, indicating a 31.59% increase in the average prices of agricultural products compared with the average prices of similar products in the 2018 base year. The Ib in 2023, which reached 117.01, reflected a 17.01% increase in the prices of goods and services required by farmers compared with their price level in 2018. The combined national NTP in 2023 reached 112.47, indicating that farmers’ real purchasing power in 2023 was 12.47% higher than in 2018.

Table 1. Development of NTP by Agricultural Sub-Sector and NTUP, 2020–2024

In the latest period, through September 2024, the national Index of Prices Received by Farmers for broadly defined agriculture reached 143.55, indicating that the average prices of agricultural products had increased by 43.55% compared with their level in 2018. Meanwhile, the Index of Prices Paid by Farmers reached 120.68, indicating a 20.68% increase in the prices of goods and services required by farmers compared with their price level in 2018. The combined national NTP in 2024 reached 118.96, indicating that farmers’ real purchasing power in 2024 had increased by 18.96% compared with their real purchasing power in 2018.

The aggregate development of NTP indicates that its value increased by 3.3% per year during the 2020–2024 period. Furthermore, the average NTP increased by 7.17 from January–September 2023 to January–September 2024. The prices received by farmers for agricultural commodities tended to increase progressively, suggesting the potential for continued improvement in farmer welfare (Table 2).

When NTP is examined by agricultural subsector, the largest contributions to the overall NTP were observed in the plantation and horticultural subsectors. In the food-crop subsector, NTP increased from 98.21 to 107.63 during 2020–2023, representing an increase of 1.89%. In 2024 (January–September), the average NTP increased further to 110.78, or 5.07% higher than the average NTP during January–September 2023.

In the plantation subsector, NTP recorded the highest values, increasing from 104.32 to 128.49 during 2020–2023. This represented a substantial increase of 6.48%. In 2024 (January–September), the average NTP rose to 145.26, representing a significant increase of 14.13% compared with the average NTP during January–September 2023.

The next significant development occurred in the horticultural subsector, where NTP increased from 101.28 to 111.75 during 2020–2023, representing an increase of 3.64%. In 2024 (January–September), the average NTP reached 119.25, an increase of 7.95% compared with the average NTP during January–September 2023.

In the livestock subsector, NTP increased from 98.99 to 101.81 during 2020–2023, representing an increase of 1.05%. In 2024 (January–September), the average NTP reached 102.57, representing a further increase of 0.55% compared with the average NTP during January–September 2023.

The positive and significant trends in both aggregate NTP and subsectoral NTP indicate that farmers’ real purchasing power during the period under review was higher than their purchasing power in the 2018 base year. The prices received by farmers for agricultural commodities also tended to improve, which may contribute to higher farm income and, consequently, potentially support improvements in farmer welfare.

Table 2. Trends in NTP Values, 2020–2024 (% per year)

 

In contrast, the Agricultural Terms of Trade for Production Costs (NTUP) is an exchange ratio that considers only expenditures associated with farming operations, including production costs and the acquisition of capital goods (BPPBM), without taking household consumption expenditures into account. The movements of NTUP and national NTP for broadly defined agriculture during 2020–2023 (2018 = 100) exhibited similar patterns. NTUP increased at an annual rate of 3.33%. The increase in NTUP, which was broadly in line with the rate of increase in NTP, resulted in similar year-to-year trends in the two indicators, with NTUP increasing from 102.17 in 2020 to 112.21 in 2023. Subsequently, in 2024 (January–September), the average NTUP reached 121.64, representing an increase of 8.08% compared with the average NTUP during January–September 2023.

Figure 4. Development of NTP and NTUP, 2020–2024

 

3.2 Initial Conditions and Development of the Farmer Welfare Index (FWI)

On June 8, 2022, the Government of Indonesia, represented by the Ministry of Finance, the Ministry of National Development Planning (Bappenas), Statistics Indonesia (BPS), Bank Indonesia (BI), and the Financial Services Authority (OJK), held a meeting with Commission IX of the House of Representatives of the Republic of Indonesia (DPR-RI). During the meeting, the government emphasized programs related to the agricultural sector and social assistance for farming households. These programs were expected to stimulate agricultural activities and improve farmers’ purchasing power, with such changes being reflected in the Farmer Terms of Trade (NTP). However, monthly NTP values did not always reflect significant changes, despite NTP being used as a development target, including as a macroeconomic assumption and development target in the 2023 State Budget (RAPBN), the 2020–2024 National Medium-Term Development Plan (RPJMN), and Regional Medium-Term Development Plans (RPJMD). This situation arises because NTP essentially captures the relationship between prices received by farmers and prices paid by farmers and is therefore highly sensitive to price changes. Consequently, NTP does not fully capture the broader dimensions of farmer welfare and cannot, by itself, serve as a comprehensive benchmark for assessing the impacts of government policies in the agricultural sector.

In response to the continuing debate and input from various stakeholders, BPS conducted a study in 2022 to improve the NTP methodology and develop alternative indicators for measuring the welfare of farmers and fishers. In the following year, BPS implemented the statistical business process required to produce NTP using the revised methodology and to develop farmer welfare indicators, while maintaining the existing NTP time series based on the previous methodology through 2024.

Since 2022, BPS has conducted studies on various indicators for assessing the welfare of farmers and fishers. The indicators selected for this purpose refer to the Rural Multidimensional Poverty Index (R-MPI), consistent with the framework promoted by the Food and Agriculture Organization of the United Nations (FAO). The selection of these indicators was intended to provide a broader assessment of the welfare conditions of farmers and fishers. The R-MPI framework developed by BPS comprises six dimensions and 20 indicators (BPS, 2024). The development of the revised NTP methodology and farmer welfare indicators, involving relevant ministries and government institutions, was undertaken alongside the reconciliation of NTP data for 2023.

The Multidimensional Poverty Index (MPI) was introduced in 2010 to provide a more comprehensive representation of poverty conditions. A multidimensional approach to poverty measurement offers a broader perspective because poverty is not assessed solely in terms of a single dimension, such as consumption or income, but also encompasses education, health, living standards, employment, and other aspects of human well-being. Within the National Sustainable Development Goals (SDGs) framework, the MPI comprises three major dimensions and 14 indicators. The health dimension includes basic immunization, nutrition, and morbidity; the education dimension includes years of schooling and school participation; while the living standards dimension includes access to safe drinking water, adequate sanitation, clean cooking fuel, adequate flooring, electricity, productive assets, birth certificates, employment, and internet access.

In developing the FWI, BPS (2024) has undertaken a broader assessment of farmer welfare using multiple indicators. In this framework, farmer welfare is conceptualized through several dimensions based on the Multidimensional Poverty Index (MPI) approach. A central concept in this approach is deprivation, which refers to the lack or inadequacy experienced by an individual or household in exercising or accessing basic rights, resources, services, or opportunities required to achieve an established standard of welfare.

Conversely, the concept of non-deprivation represents the absence of such deprivation and is used to measure the extent to which individuals or households achieve the established welfare standards. The development of the FWI adopts the dimensions used in the R-MPI framework (FAO, 2020), with the indicators adapted and operationalized using a non-deprivation approach. This approach shifts the analytical emphasis from measuring deficiencies or shortcomings to measuring the extent to which farmers and their households have achieved minimum welfare standards.

The dimensions and indicators used to assess farmer welfare through the Rural Multidimensional Poverty Index (R-MPI) include six major dimensions. (1) Food security and nutrition comprises adequate nutritional intake among children under five and household food security. (2) Education includes school participation and years of schooling. (3) Health includes health insurance coverage, access to basic health services, and basic immunization. (4) Living standards encompasses access to safe and clean cooking fuel, adequate sanitation, safe drinking water, electricity, housing structural resilience, and household assets. (5) Rural livelihoods and resources includes adequacy of agricultural assets, social protection, child labor, and access to agricultural extension services. (6) Risk mitigation includes access to credit financing, agricultural insurance, and exposure to economic or other shocks.

Accordingly, the FWI provides a multidimensional framework for assessing farmer welfare that extends beyond the purchasing-power perspective represented by NTP. While NTP primarily captures changes in the relative prices of agricultural products and the goods and services purchased by farmers, the FWI incorporates broader dimensions of welfare, including food and nutrition security, education, health, living standards, rural livelihoods and productive resources, and risk mitigation. The formulation of the Farmer Welfare Index based on the MPI non-deprivation approach is presented in Figure 5.

 

 

Figure 5. Measurement of Farmer Welfare Using the MPI Non-Deprivation Approach

Furthermore, BPS (2024) states that the measurement of the Farmer Welfare Index (FWI/IKP) using the MPI non-deprivation approach involves 12 stages: (1) defining the unit of analysis as agricultural households; (2) determining the dimensions based on the R-MPI framework; (3) determining the indicators; (4) assigning weights to the dimensions and indicators; (5) defining the non-deprivation category for each indicator; (6) applying the non-deprivation criteria to each indicator; (7) calculating the number of non-deprived units of analysis for each indicator; (8) calculating the dimension score for each unit of analysis using the indicator weights; (9) calculating the overall score using the dimension weights; (10) classifying a household as non-deprived/well-off when its total score exceeds 2/3; (11) calculating the headcount ratio (H); and (12) calculating the intensity and overall FWI score.

BPS (2024) conducted a simulation of farmer welfare measurement using data from the March 2021 and March 2022 National Socioeconomic Survey (SUSENAS), based on data availability and the indicators that had been previously defined and agreed upon. The simulation employed a non-deprived household approach, in which households were assessed based on the extent to which they had achieved the established welfare standards rather than solely on the absence of deprivation.

The results of the simulation are presented in Table 3. In this simulation, equal weights were assigned to each dimension and to each indicator within the respective dimensions. However, not all dimensions and indicators were included because of limitations in data availability.

3.3 Comparative Analysis of NTP and FWI in Measuring Farmer Welfare

3.3.1 Strengths and Limitations of NTP

The Farmer Terms of Trade (NTP) is widely used as a benchmark for assessing farmers’ purchasing power by comparing the prices of agricultural products received by farmers with the prices of goods and services purchased by them. However, NTP does not necessarily provide a comprehensive representation of farmer welfare. Several limitations should therefore be considered when interpreting NTP as a welfare indicator.

1. Limited Measurement of Prices and Inconsistent Price Fluctuations

NTP focuses primarily on the relative movement of prices between agricultural products sold by farmers and the goods and services they purchase. It does not directly account for changes in the quality of goods and services or broader changes in living standards. Farmer welfare is also influenced by non-economic dimensions, including quality of life, education, and health, none of which are directly reflected in NTP. Moreover, agricultural output prices and the prices of goods and services purchased by farmers may fluctuate substantially over time and across regions. Such short-term fluctuations do not necessarily represent farmers’ long-term economic conditions or structural welfare.

2. Limited Consideration of Production Costs and Technological Change

NTP does not directly measure all costs incurred by farmers during the production process. Although production-related expenditures are represented within the price index paid by farmers, the NTP framework does not directly measure the complete cost structure of individual farming enterprises or its effects on farm profitability. Input costs such as fertilizer, seeds, labor, machinery, and other production inputs may change differently from the aggregate price index. Furthermore, NTP does not directly capture the effects of technological change on farm profitability or changes in Total Factor Productivity (TFP). Consequently, an improvement in NTP does not necessarily imply an equivalent improvement in farm productivity or profitability.

3. Base-Year Bias and Regional Data Limitations

NTP is calculated using a fixed base year, which is generally updated periodically. The current NTP series uses 2018 as the base year, even though substantial changes in agricultural productivity, commodity structures, consumption patterns, input use, and prices may occur over time. As the observation period moves further away from the base year, the representativeness of the original weighting structure may gradually decline. In addition, NTP can vary substantially across regions because of differences in living costs, local market conditions, agricultural structures, infrastructure, and commodity composition. Consequently, aggregate or regional NTP values may not accurately represent the economic conditions of individual farmer groups in specific locations.

4. Welfare Is Not Equivalent to Purchasing Power and NTP Is Primarily Relevant to Net Producers

Farmer welfare involves considerably more than purchasing power. Access to health services, education, infrastructure, social protection, housing, and other basic services also plays an important role in determining household welfare. Furthermore, NTP implicitly assumes that agricultural production generates a marketable surplus and that agricultural output is sold in the market. This makes NTP more directly relevant to net agricultural producers than to net buyers of agricultural products. Farmers who consume a substantial proportion of their own production or purchase agricultural commodities from the market may experience welfare changes that are not fully captured by NTP.

5. Influence of Subsidies and Government Policies

Agricultural subsidies and government interventions can affect market prices and, consequently, influence NTP. However, changes in NTP resulting from policy interventions do not necessarily correspond directly to improvements in farmers’ overall welfare. For example, a policy may reduce input prices and thereby improve the price ratio without substantially increasing household income, employment opportunities, access to health services, or other dimensions of welfare. Therefore, NTP should be interpreted together with information on the actual transmission and distributional effects of agricultural policies.

6. Limited Ability to Capture Income Dynamics, Comprehensive Expenditures, Employment, and Multiple Sources of Income

In agricultural production, farm income is determined by the quantity of output produced and the price received for the commodity. NTP, however, primarily captures price changes, while production quantities are represented through the weighting structure associated with the base period. At the same time, the Index of Prices Paid by Farmers incorporates household consumption, capital goods, and agricultural production expenditures, whereas the Index of Prices Received is derived from agricultural products sold by farmers.

In reality, Indonesian farmers are not necessarily engaged exclusively in farming. Many agricultural households combine farming with agricultural wage labor, non-farm employment, small businesses, seasonal work, and other supplementary income-generating activities. These employment and income sources are not adequately captured by NTP. NTP also does not provide direct information on the number and quality of employment opportunities available to farmers or on their total household income from all economic activities. Consequently, changes in NTP should not be interpreted automatically as equivalent to changes in household income or overall welfare.

Overall, although NTP provides useful information on farmers’ relative purchasing power in relation to prices received and prices paid, it does not encompass all dimensions of farmer welfare. This finding challenges the interpretation advanced by several studies, including Suhartini and Rusastra (2013), Setiawan and Zulfanita (2015), Keumala and Zainuddin (2018), and Muis and Marlin (2023), which suggest a strong relationship between NTP and farmer welfare and support its use as a welfare indicator. Rather than completely rejecting NTP, the findings suggest that NTP should be interpreted as a partial economic indicator of farmers’ purchasing power, rather than as a comprehensive measure of welfare. A more complete assessment of farmer welfare therefore requires NTP to be combined with other indicators and household-level data covering the broader socioeconomic dimensions of farmers’ lives.

3.3.2 Strengths of NTP

Despite these limitations, NTP has several important advantages that make it a useful instrument for agricultural economic analysis.

1. Monthly Availability

An important characteristic of a useful indicator is the availability of the underlying data on a regular and consistent basis. NTP is based on price data collected periodically, allowing the indicator to be calculated and published on a monthly basis. This high-frequency availability makes NTP particularly useful for monitoring short-term developments in agricultural markets and farmers’ purchasing power.

2. Measurement of Farmers’ Purchasing Power and Terms of Trade

NTP provides a direct measure of the relative purchasing power or terms of trade faced by farmers by comparing the prices received for agricultural products with the prices of goods and services purchased by farmers. This contributes to an understanding of the extent to which changes in agricultural prices affect farmers’ capacity to obtain goods and services required for household consumption and agricultural activities.

3. Agricultural Policy Evaluation

NTP can be used as one of the indicators for evaluating the potential effects of government policies and agricultural subsidies on farmers’ purchasing power. Changes in NTP can help policymakers identify whether price-related interventions, input subsidies, or other agricultural policies are associated with improvements or deteriorations in farmers’ relative economic conditions.

4. Regional Comparability

NTP enables comparisons across provinces and regions, providing information on differences in agricultural price conditions and relative purchasing power. Such comparisons can support regional planning, identification of areas experiencing greater economic pressure, and more effective allocation of agricultural development resources.

5. Monitoring Economic Fluctuations

Because NTP is available at relatively high frequency, it can be used to monitor short-term fluctuations in agricultural markets and identify emerging trends that may affect farmers’ purchasing power. This information can support agricultural planning, market monitoring, and policy responses to changes in commodity and input prices.

3.3.3 Strengths of the Farmer Welfare Index (FWI)

The Farmer Welfare Index (FWI/IKP) is designed to provide a more comprehensive assessment of farmer welfare. Unlike NTP, which focuses primarily on relative purchasing power, the FWI incorporates multiple socioeconomic dimensions of household welfare. Based on the framework introduced by BPS (2024), several potential advantages can be identified.

1. Multidimensional Measurement

FWI measures several dimensions of welfare, including food and nutrition security, education, health, living standards, rural livelihoods and resources, and risk mitigation. This provides a more holistic representation of farmer welfare than an indicator based primarily on purchasing power.

2. Incorporation of Farmer Income and Expenditure Information

The FWI measurement process is preceded by a survey designed to collect household-level socioeconomic information. The FWI survey questionnaire can include information on farmers’ income by agricultural subsector and their household expenditures. Such information provides a more direct basis for analyzing changes in household economic welfare than an indicator based exclusively on relative prices.

3. Coverage of Social Welfare Dimensions

The FWI incorporates not only economic aspects but also social dimensions of welfare, including access to basic services, health, education, living conditions, and social protection. This broader coverage facilitates a more comprehensive understanding of farmers’ living conditions beyond monetary or price-related factors.

4. Assessment of Quality of Life

By incorporating multiple indicators, the FWI can provide information on the overall quality of life of agricultural households. These indicators include health conditions, educational attainment, living standards, household resources, and social conditions that collectively influence welfare.

5. Guidance for Policy Design and Intervention

Information generated through the FWI can assist policymakers in designing more targeted and effective agricultural and rural development programs. Because the index identifies multiple dimensions of welfare, policy interventions can be directed toward specific deficiencies, such as inadequate health services, low educational attainment, insufficient productive assets, food insecurity, or limited access to risk-management instruments.

6. Program Monitoring and Evaluation

The FWI can be used to monitor and evaluate agricultural development programs, social assistance, and other interventions. Changes in the index and its constituent dimensions can provide information on whether particular programs have contributed to improvements in farmers’ welfare.

7. Identification of Welfare Gaps

The multidimensional structure of the FWI makes it possible to identify disparities in welfare among different farmer groups and geographical areas. Such information can support more targeted interventions to address regional and socioeconomic inequalities.

8. Interregional Comparison

The FWI enables more comprehensive comparisons among regions because it incorporates several dimensions of household welfare. Such comparisons can support regional development planning and the allocation of resources based on the specific welfare conditions of different farmer populations.

9. Integrated Data

By integrating multiple indicators into a single analytical framework, the FWI provides more comprehensive information about farmers’ welfare. Such integrated information can facilitate data-driven analysis, policy formulation, program targeting, and evaluation. By covering multiple dimensions of farmers’ lives, the FWI offers a broader and deeper representation of welfare than an indicator based solely on purchasing power. Consequently, it has considerable potential as an instrument for agricultural and rural development planning, policy formulation, and program evaluation.

3.3.4 Limitations of the Farmer Welfare Index (FWI)

Despite providing a more comprehensive perspective on farmer welfare, the FWI also has several methodological and operational limitations that need to be considered.

1. Complexity of Data Collection

The collection of data required to calculate a multidimensional welfare index can be complex and resource-intensive. The FWI requires information covering multiple dimensions, including income, food security, health, education, living standards, productive resources, social protection, and risk mitigation. Collecting such information accurately and consistently across regions requires comprehensive survey instruments, trained enumerators, adequate sample sizes, and strong institutional coordination. Differences in respondents’ understanding, recall accuracy, and reporting behavior may also affect data quality.

The complexity of data collection may therefore affect the frequency with which the FWI can be produced. Unlike NTP, which can be calculated monthly from routinely collected price data, a multidimensional welfare index generally requires household-level surveys or integrated administrative data. Consequently, the FWI may be more suitable for medium- and long-term welfare assessment, while NTP remains particularly useful for short-term monitoring of farmers’ purchasing power and agricultural price dynamics.

2. Annual Measurement Frequency

The availability of data required for calculating the FWI is not uniform across indicators. Some variables are available monthly, others are collected seasonally, and some are available only annually. Consequently, the FWI survey can generally be conducted only on an annual basis. This relatively low measurement frequency may limit the ability of policymakers to respond rapidly to emerging changes in farmers’ welfare and may result in delays in the implementation of government interventions.

3. Data Variability

The quality and availability of data may vary across regions and indicators, potentially affecting the accuracy, reliability, and consistency of the index. Incomplete, inconsistent, or inaccurate data in particular geographical areas may result in welfare estimates that are less representative or potentially unreliable. Differences in survey coverage, data collection procedures, and administrative data systems may further contribute to variations in data quality.

4. Difficulty in Assigning Weights

Determining appropriate weights for the various dimensions and indicators included in a composite welfare index can be challenging and potentially subjective. Different weighting schemes may produce different index values and rankings. Moreover, a uniform weighting structure may not fully reflect the different priorities, vulnerabilities, or welfare needs of farmers across subsectors and geographical contexts. Therefore, the selection and justification of weights constitute an important methodological consideration in the construction of the FWI.

5. Limitations in Assessing Quality

Although the FWI can incorporate a broad range of welfare dimensions, quantitatively assessing the quality of services and outcomes within each dimension remains challenging. For example, measuring access to education does not necessarily capture the quality of education received, just as access to health services does not necessarily reflect the quality, affordability, timeliness, or effectiveness of those services. Consequently, an index based primarily on access or availability indicators may not fully capture the qualitative aspects of farmer welfare.

6. Challenges in Integrating Multiple Dimensions

Integrating multiple dimensions of welfare into a single composite index presents a methodological challenge. Each dimension may have different characteristics, measurement scales, and levels of importance. Combining these heterogeneous dimensions into a single numerical value can simplify the interpretation of welfare conditions but may also result in the loss of important information about individual dimensions. A relatively high overall FWI score, for example, may conceal substantial deprivation or vulnerability in a particular dimension.

Overall, although the Farmer Welfare Index (FWI) provides a broader perspective on farmer welfare by incorporating multiple socioeconomic dimensions, its limitations need to be carefully recognized when interpreting the results. The FWI should therefore not be considered a stand-alone measure of farmer welfare. Combining the FWI with other indicators, including NTP, household income and expenditure data, agricultural productivity, employment indicators, and other socioeconomic measures, can provide a more comprehensive and reliable assessment of farmers’ welfare conditions.

In summary, the strengths and limitations of NTP and FWI identified above are presented comparatively in Table 4.

 

Table 4. Comparative Analysis of the Strengths and Limitations of NTP and FWI

 

 

CONCLUSIONS AND POLICY IMPLICATIONS

Conclusions

The Farmer Terms of Trade (NTP) is calculated as the ratio between the Index of Prices Received by Farmers (It) and the Index of Prices Paid by Farmers (Ib), expressed as a percentage. NTP therefore provides an indication of farmers’ relative purchasing power in meeting household consumption and agricultural production needs. A higher NTP indicates a relatively greater purchasing power or terms-of-trade position for farmers. At present, NTP remains a useful instrument for rapidly assessing farmers’ economic conditions, particularly over the short term, under the assumption that production volumes remain relatively comparable over time. For medium- and long-term assessments, however, NTP would be more appropriately interpreted in conjunction with indicators of agricultural production volume and other sources of household income.

During 2020–2024, NTP increased at an average rate of approximately 3.3% per year. Furthermore, the average NTP for January–September 2024 increased by 7.17% compared with the corresponding period in 2023. This development indicates that the prices received by farmers for agricultural commodities generally improved relative to the prices of goods and services purchased by them. When analyzed by subsector, the increase in aggregate NTP was predominantly supported by the plantation and horticultural subsectors.

In assessing farmer welfare, NTP and the Farmer Welfare Index (FWI/IKP) each have distinct strengths and limitations. NTP has several advantages, including its relatively simple measurement, suitability for assessing farmers’ purchasing power or terms of trade, ability to monitor price fluctuations, usefulness for regional comparisons, and potential application in policy evaluation. However, its limitations include its inability to directly capture household income, its strong sensitivity to price fluctuations, its narrow focus on relative prices, and its limited ability to capture changes in technology, productivity, and the broader effects of policy interventions. Additional limitations include regional data constraints, its greater relevance to net agricultural producers than net buyers, and dependence on the selected base year.

Meanwhile, the FWI, which is currently being developed and gradually implemented, offers several advantages, including its multidimensional structure, its ability to incorporate information on household income and expenditure, and its capacity to assess welfare across multiple dimensions. This multidimensional structure allows policy recommendations to be formulated in a more comprehensive and targeted manner. Nevertheless, the new approach also presents several challenges, including the availability and complexity of data collection, difficulties in determining appropriate weights, inconsistencies among some variables, limitations in assessing the quality of services and outcomes, and methodological challenges in integrating different welfare dimensions into a single composite index.

Overall, considering the respective strengths and limitations of NTP and FWI, both instruments remain relevant and should be maintained and utilized according to their original measurement objectives. NTP remains relevant as an indicator of farmers’ relative purchasing power and terms of trade, whereas the FWI survey, which is currently being refined, is more appropriate for assessing farmer welfare from a broader multidimensional perspective. Rather than replacing one indicator with the other, the two should be regarded as complementary instruments within a broader agricultural welfare monitoring framework.

Policy Implications

NTP and FWI are two measurement instruments that should be maintained and utilized according to their respective objectives. However, to improve the quality and relevance of NTP, BPS should continue refining its methodology, including consideration of incorporating production-volume information and/or updating the current base year from 2018 to 2023. Such methodological improvements would help ensure that the weighting structure remains representative of contemporary agricultural production and consumption patterns. To implement these improvements effectively, the government should provide adequate budgetary support to ensure the availability of high-quality, timely, and representative agricultural data.

The FWI measurement developed by BPS through simulation studies using the March 2021 and March 2022 SUSENAS Core (SUSENAS KOR) should be continued and further refined through the implementation of the FWI survey in 2024 and subsequent years. Continued development is important to evaluate the robustness of the indicators, weighting system, data-collection procedures, and multidimensional aggregation method. Therefore, BPS, Bappenas, the Ministry of Finance, and other relevant stakeholders should maintain close coordination to ensure that the FWI survey can be implemented with adequate financial and institutional resources. Continuous stakeholder involvement is also necessary to improve the comprehensiveness, reliability, policy relevance, and sustainability of the FWI as an official instrument for monitoring farmer welfare.

From a policy perspective, the most appropriate strategy is therefore not to replace NTP with FWI, but to establish a complementary measurement framework. NTP can provide high-frequency information on short-term changes in farmers’ purchasing power and agricultural terms of trade, while FWI can provide a broader assessment of medium- and long-term welfare conditions. Integrating the two indicators with agricultural production, household income, employment, productivity, poverty, social protection, health, education, and rural infrastructure data would provide policymakers with a more comprehensive evidence base for designing, monitoring, and evaluating agricultural and rural development policies.

 

REFERENCES

 

Afifah, N., Nalurita L. (2022). Analisis Determinan Nilai Tukar Petani Tanaman Pangan Di Indonesia. NUSANTARA : Jurnal Ilmu Pengetahuan Sosial. 9(1). https://doi.org/DOI: https://doi.org/10.20961/agritexts.v45i2.57364.

 

Agustian, A., Sunarsih, S., Wahyudi, W. (2022). Analisis Kebijakan Penguatan Cadangan Pangan Pemerintah Daerah Di Kabupaten Cianjur Jawa Barat. Prosiding Seminar Nasional Hasil Penelitian Agribisnis. 6(1).

 

Agustina Mutia., Muhammad Orinaldi., M Hasan. (2023). Analisis Peningkatan Kesejahteraan Masyarakat Melalui Usaha Mikro Kecil Dan Menengah Di Kecamatan Pengabuan Kabupaten Tanjung Jabung Barat. Jurnal Publikasi Manajemen Informatika. 2(3). https://doi.org/10.55606/jupumi.v2i3.2078

 

Bappenas/Kementerian PPN. (2019). Rancangan Teknokratik: RPJMN 2020-2024. Rancangan Teknokratik RPJMN 2020-2024.

 

BPS. (2024). Indikator Kesejahteraan Petani. Badan Pusat Statistik. Jakarta.

 

BPS Jabar. (2022). Statistik Nilai Tukar Petani Provinsi Jawa Barat 2022. Jakarta: Badan Pusat Statistik Jawa Barat.

 

BPS. (2017). Statistik Nilai Tukar Petani. Badan Pusat Statistik. Jakarta.

 

Budy Kusnandar, V. (2022). Kesejahteraan Petani Kembali Meningkat pada Oktober 2022. databoks.katadata.

 

Darwanto, D. (2005). Ketahanan Pangan Berbasis Produksi dan Kesejahteraan Petani. Journal of Ilmu Pertanian [Internet]. [accessed 2024 Oct 17] 12(2):152–164. https://doi.org/https://doi.org/10.22146/ipas.58575

 

Darwis, V., Maulana, M., Rachmawati, RR.(2020). Dampak Pandemi Covid-19 terhadap Nilai Tukar Petani dan Nilai Tukar Usaha Pertanian. In: Dampak Pandemi Covid-19: Perspektif Adaptasi dan Resiliensi Sosial Ekonomi Pertanian. Vol. 7.

 

Dauda, A. (2019). Faktor yang Mempengaruhi Nilai Tukar Petani Sektor Tanaman Pangan di Provinsi Sulawesi Tengah. Bomba: Jurnal Pembangunan Daerah. 1(2).

 

Ervianti, Y. (2022). Strategi Peningkatan Nilai Tukar Petani Terhadap Kesejahterahan Petani Padi Di Jawa Timur. Repository UVN Jatim. 11(2). https://doi.org/http://repository.upnjatim.ac.id/id/eprint/4791

 

Fatimah, N H IM., Asmara, K. (2021). Analisis Daya Saing Ekspor Komoditi Kopi (Hs 090111) Indonesia Di Pasar Amerika Serikat : Pendekatan RSCA dan CMS. JIA (Jurnal Ilmiah Agribisnis) : Jurnal Agribisnis dan Ilmu Sosial Ekonomi Pertanian. 6(3). https://doi.org/10.37149/jia.v6i3.18078

 

Fausy, Ar I., Meiyani, E., Amin, S. (2023). Tingkat kesejahteraan kasyarakat dan usaha Sarang Burung Walet di Desa Belopa Kabupaten Luwu. Journal Socius Education (JSE). 1(2). https://doi.org/DOI: https://doi.org/10.0505/jse.v1i1.416

 

Firmansyah, U., Junaidi, J., Achmad, E. (2022). Pengaruh nilai tukar petani, indeks pembangunan manusia dan PDRB sektor pertanian terhadap ketimpangan distribusi pendapatan Provinsi di Wilayah Sumatera. e-Jurnal Perspektif Ekonomi dan Pembangunan Daerah. 11(1). https://doi.org/10.22437/pdpd.v11i1.16777

 

Guritno, DER., Wibowo, BA., Boesono, H. (2014). Analisis Tingkat Kesejahteraan Nelayan Pancing Ulur (Hand Line) di Pelabuhan Perikanan Nusantara (PPN) Palabuhanratu Sukabumi Jawa Barat. Journal of Fisheries Resources Utilization Management and Technology. 3 (3) (2012).

 

Ilahi, R., Agustin, B. (2022). Peramalan Nilai Tukar Petani Di Bangka Belitung Dengan Metode Holt-Winters. Fraction: Jurnal Teori dan Terapan Matematika. 2(2). https://doi.org/10.33019/fraction.v2i2.34

 

Keumala, CM., Zainuddin, Z. (2018). Indikator Kesejahteraan Petani melalui Nilai Tukar Petani (NTP) dan Pembiayaan Syariah sebagai Solusi. Economica: Jurnal Ekonomi Islam. 9(1). https://doi.org/10.21580/economica.2018.9.1.2108

 

Kurniawan, J. (2022). Nilai Tukar Petani sebagai Indikator Kesejahteraan Petani Kedelai di Kecamatan Pulokulon Kabupaten Grobogan. Journal of Integrated Agricultural Socio-Economics and Entrepreneurial Research (JIASEE). 1(1). https://doi.org/10.26714/jiasee.1.1.2022.21-32

 

Lewis JN. (1958). Trends in agriculture's terms of exchange. Australian Journal of Agricultural and Resource Economics 2(1):57-66.

 

Muis, M., Marlin, S. (2023). Analisis Tingkat Kesejahteraan Petani Kedelai Dengan Menggunakan Pendekatan Nilai Tukar Petani (Ntp) Dan Nilai Tukar Pendapatan Rumah Tangga Petani (NTPRP). Jurnal Agrisistem: Seri Sosek dan Penyuluhan. 19(2). https://doi.org/10.52625/j-agr-sosekpenyuluhan.v19i2.299

 

Mulyawan, Y. (2022). Pengaruh Inflasi Terhadap Nilai Tukar Petani Di Indonesia. Jurnal Ilmiah Mahasiswa Ekonomi Pembangunan (JIM EKP) Fakultas Ekonomi dan Bisnis Universitas Syiah Kuala. 7(1). https://doi.org/DOI: https://doi.org/10.24815/jimekp.v7i1.20497

 

Pratama, PRY., Budhi, MKS. (2023). Analisis Pengaruh Harga, Nilai Tukar Rupiah Dan Produksi Terhadap Volume Ekspor Kopi Indonesia. E-Jurnal Ekonomi Pembangunan Universitas Udayana. 12(1). https://doi.org/10.24843/eep.2023.v12.i01.p02

 

Rachmat, M. (2013). Nilai Tukar Petani : Konsep, Pengukuran dan Relevansinya sebagai Indikator Kesejahteraan Petani. Forum penelitian Agro Ekonomi. 31:111. https://doi.org/10.21082/fae.v31n2.2013.111-122

 

Razi, F., Wahyuni, S. (2022). Analisis Faktor-Faktor Yang Mempengaruhi Kesejahteraan Petani Padi Di Indonesia Tahun 2008–2012. Jurnal Agro Nusantara. 2(2).

 

Rizal, J., Rizaly, EN., Djabbar, A. (2021). Hubungan Tingkat Partisipasi dengan Tingkat Kesejahteraan Masyarakat dalam Pengembangan Wisata Pesisir. Jurnal Penelitian dan Pengabdian Masyarakat Bidang Pariwisata. 1(1):1–7.

 

Ruslan, K. (2022). Telaah Kritis Pengukuran Kesejahteraan Petani. Jakarta.

 

Sari, N. P. (2021). Analisis Komparatif Strategi Pemasaran Online Dan Offline Pada UMKM Rengginang Umi Tegal (Doctoral dissertation, Politeknik Harapan Bersama Tegal).

 

Setiawan, RAP., Noor, TI., Sulistyowati, L., Setiawan, I. (2019). Analisis Tingkat Kesejahteraan Petani Kedelai Dengan Menggunakan Pendekatan Nilai Tukar Petani (Ntp) Dan Nilai Tukar Pendapatan Rumah Tangga Petani (Ntprp). JURNAL AGRIBISNIS TERPADU. 12(2). https://doi.org/10.33512/jat.v12i2.6779

 

Setiawan., Zulfanita. (2015). Pengembangan Desa Wisata Jatimalang Berbasis Industri Kreatif (Development Jatimalang Village Tourism Based Creative Industries). Agrokreatif. 1(2):101–109. https://doi.org/DOI: https://doi.org/10.15294/abdimas.v19i1.4695

 

Simatupang, P. (1992). Pertumbuhan Ekonomi dan Nilai Tukar Barter Sektor Pertanian. Jurnal Agroekonomi: 11(1): 37-50. Pusat Penelitian Sosial Ekonomi Pertanian. Badan Penelitian dan Pengembangan Pertanian. Departemen Pertanian.

 

Sinaga, MA., Wardhana, MY., Usman, M. (2022). Analisis Faktor-faktor yang Mempengaruhi Nilai Tukar Petani Komoditas Nilam di Provinsi Aceh. Jurnal Ilmiah Mahasiswa Pertanian. 7(2). https://doi.org/10.17969/jimfp.v7i2.20018

 

Sitorus, EAG. (2022). Pengaruh Covid-19 terhadap Harga Beras, Nilai Tukar Petani dan Kemiskinan di Wilayah Perdesaan. Jurnal Ekonomi Pertanian dan Agribisnis. 6(3). https://doi.org/10.21776/ub.jepa.2022.006.03.9

 

Smith, A. (1776). An inquiry into the wealth of nations. Strahan and Cadell, London.

 

Suhartini, SH., Rusastra, IW. (2013). Dinamika nilai tukar petani: perubahan 2003 – 2013. Jurnal Rekonstruksi Agenda Peningkatan Kesejahteraan Petani.

 

Sukirno, S. 2018. Ekonomi Pembangunan: Proses, Masalah, dan Dasar Kebijakan. e-conversion - Proposal for a Cluster of Excellence.

 

Todaro. M. P. (2011). Pembangunan Ekonomi di Dunia Ketiga Edisi Kesebelas. Jakarta: Erlangga.

 

Wahyudi. (2024). Analysis of Increasing Farmer’s Exchange Rate and Efforts to Control [Internet]. SouthJakarta; [accessed 2024 Oct 15]. https://doi.org/10.13140/RG.2.2.35792.32005

 

Yacoub, Y., Mutiaradina, H. (2020). Analisis Kesejahteraan Petani dan Kemiskinan Perdesaan di Indonesia.Prosiding Seminar Akademik Tahunan Ilmu Ekonomi dan Studi Pembangunan.(2017).

 

Yulhendri, Y., Susanti, N. (2017). Analisis Konfirmatory Faktor Pengukuran Indikator Kesejahteraan Rumah Tangga. Econosains Jurnal Online Ekonomi dan Pendidikan. 15(2). https://doi.org/10.21009/econosains.0152.02

 

RESOURCE:

Jurnal Perencanaan Pembangunan Pertanian (JP3). 1 (1): 44-60, Juli 2025.

 

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