Between May and July 2018, the International Food Policy Research Institute (IFPRI) implemented a household-level survey in four areas of PNG: the Autonomous Region of Bougainville (South Bougainville near Buin), Madang (Middle Ramu near Kwanga Station), East Sepik (near Maprik) and West Sepik (near Nuku). The survey investigated the food systems of rural households and how they assure sufficient food to meet the nutritional needs of their household members. The household questionnaire for the survey focused on agricultural production systems and health outcomes and included modules on: production; consumption and expenditure; labor activities (farm and non-farm); nutritional status; and the experience of the survey households with recent agricultural production or other shocks that impacted their livelihoods. This report provides descriptive results from the survey and discusses key indicators and actions to improve agricultural systems and nutrition in PNG.
From May to December 2023, the International Food Policy Research Institute (IFPRI) implemented a rural household survey that collected detailed data on rural household food consumption and expenditures, agricultural production practices, employment profiles, child and mother 24-hour diet recall, and child anthropometry measurements in Papua New Guinea (PNG). The research team carried out the survey, which used location-based sampling, across five agroecological study areas, of which four of the areas were defined using elevation and rainfall variation. The five agroecological survey areas were seasonal highlands, nonseasonal highlands, seasonal lowlands, nonseasonal lowlands, and islands (the islands survey sample was not disaggregated by elevation or precipitation patterns). In identifying seasonal and nonseasonal survey areas, we adapted the rainfall seasonality categories established by Bourke and Harwood (2009), who evaluated the relative difference in rainfall between the wet and the dry season using resource mapping units defined by the PNG Resource Information System (PNGRIS). The areas of the country that experience large seasonal variation in rainfall (heavy to light, depending on the season) are classified as seasonal, whereas the areas that experience moderate to continuously heavy rainfall throughout the year are classified as nonseasonal (see Figure A1.1 in the appendix for the survey seasonality classification by area). In nonseasonal areas, agricultural growing conditions remain similar year-round, whereas seasonal rainfall areas have agricultural conditions that necessitate a variety of production strategies. Lowland and highland areas were defined using elevation data; areas 1,000 meters or more above sea level were classified as highlands, and those below 1,000 meters were classified as lowlands. The survey collected data from 270 communities across 14 provinces, from a total of 2,699 households. It is important to note that the survey is not nationally representative. Rather, we chose a purposive sample using criteria that would enable analysts of the data to understand the key factors that interact within rural households and communities to create more resilient local food systems, more diversified employment profiles, and improved well-being. Generalizable relationships between variables that affect socioeconomic and other development outcomes in rural PNG communities should be seen consistently in both representative and unrepresentative survey samples.
If smallholder farming households in Papua New Guinea achieve higher crop productivity levels, progress will be made along several dimensions of the development vision for PNG – increasing GDP for the agricultural sector and the overall economy; driving growth, diversification, and transformation of local rural economies; improving food consumption; and reducing poverty. In this paper, we examine recent data on yields for the most important crops grown in PNG, assess what yields might be achieved based on productivity data from areas of Indonesia with similar growing conditions, and sketch where policy reforms could provide incentives and access to technologies to achieve higher crop yields by all farmers across PNG.
The onset of the COVID-19 pandemic has presented a unique challenge to governments across the globe, reinforcing the need to improve understanding of domestic and international trade trends to provide more informed options for policy response. During the last several months, IFPRI has been analyzing a variety of Papua New Guinea (PNG) national and global datasets with the goal of expanding analytical tools to evaluate potential production shortfalls and food price shocks, and their associated impacts on household food security and livelihoods. This research note focuses on agri-food import and export trends during the last two decades to better evaluate potential changes in related import demand and export potential in PNG. In doing so, this research note informs an upcoming economy-wide multi market model analysis that will model a variety of potential shocks to household welfare to identify policies to manage potential ensuing food security threats. PNG’s growth in international agri-food trade (both export and import) will continue to be important to overall food security outcomes among rural and urban households. Rural households that produce key export cash-crops (e.g., coffee, cocoa, palm oil) depend on the cash economy to supplement overall food consumption, while urban households depend on rice and other agri-food imports (as well as domestic goods) for consumption. Agri-food imports are also contributing to important increases in the availability of protein-dense foods, with the value of poultry imports growing, on average, 30 percent per capita per year from 2001 – 2016. Although PNG’s agri-food import data suggest a greater demand for higher value food items such as animal-sourced foods, the total import value of ultra-processed foods, such as sugary drinks, are also increasing rapidly within PNG. The profitability and growth of agricultural exports and imports are driven by several factors, including levels of public investment in infrastructure, weather and climate shocks, security and political stability, and conditions in the world market. Government economic policies, including exchange rate, trade and price policies, also heavily influence agricultural trade. Policy to promote and facilitate domestic movement of goods, as well as macro-economic policies that influence the relative price of tradable to non-tradable goods (the real exchange rate) should be managed appropriately to support and incentivize greater agri-food production and trade. These policies could also be paired with an expanded set of education programs that integrate nutrition-sensitive information to address current increases in demand and consumption of high-saturated and sugary processed goods, of which total import values are rapidly increasing in PNG. Finally, a greater portfolio of organized databases, analytical tools and policy resources are warranted to facilitate real-time policy analysis that can inform key development investments and initiatives.
Papua New Guinea continues to encourage a policy focus on food and nutrition security. The PNG National Nutrition Policy (2016-2026) and Nutrition Strategic Action Plan (2018-2022) (NSAP) set a path to improve coordination, secure sufficient funding, and improve technical capacity of nutrition-focused pro gram implementation. As policy prioritizes improved nutrition outcomes, it is important to understand the cost that households face of securing a higher level of nutrition. Ensuring a healthy diet that meets nutrition standards is relatively expensive in PNG. The analysis presented in this paper, which uses detailed household food and non-food consumption data suggests that 4/5 of households in the survey sample live below the healthy diet poverty line (which sets a calorie threshold and defines healthy diet nutrition targets). That is, these households do not have the income available (or do not consume sufficient food and non-food goods) to meet their basic needs which includes securing a nutritious diet that meets food based die tary guidelines.
Understanding how the Papua New Guinea (PNG) agricultural economy and associated household consumption is affected by climate, market and other shocks requires attention to linkages and substitution effects across various products and the markets in which they are traded. In this study, we use a multi-market simulation model of the PNG food economy that explicitly includes production, consumption, external trade and prices of key agricultural commodities to quantify the likely impacts of a set of potential shocks on household welfare and food security in PNG. In this study, we use a multi-market simulation model of the PNG food economy that explicitly includes production, consumption, external trade and prices of key agricultural commodities to quantify the likely impacts of a set of potential shocks on household welfare and food security in PNG. We have built the model to be flexible in order to explore different potential scenarios and then identify where and how households are most affected by an unexpected shock. The model is designed using region and country-level data sources that inform the structure of the PNG food economy, allowing for a data-driven evaluation of potential impacts on agricultural production, food prices, and food consumption. Thus, as PNG confronts different unexpected challenges within its agricultural economy, the model presented in this paper can be adapted to evaluate the potential impact and necessary response by geographic region of an unexpected economic shock on the food economy of the country. We present ten simulations modeling the effects of various shocks on PNG’s economy. The first group of scenarios consider the effects of shocks to production of specific agricultural commodities including: 1) a decrease on maize and sorghum output due to Fall Armyworm; 2) reduction in pig production due to a potential outbreak of African Swine Fever; 3) decline in sweet potato production similar to the 2015/16 El Niño Southern Oscillation (ENSO) climate shock; and 4) a decline in poultry production due to COVID-19 restrictions on domestic mobility and trade. A synopsis of this report, which focuses on the COVID-19 related shocks on the PNG economy is also available online (Diao et al., 2020).1 The second group of simulations focus on COVID-19-related changes in international prices, increased marketing costs in international and domestic trade, and reductions in urban incomes. We simulate a 1) 30 percent increase in the price of imported rice, 2) a 30 percent decrease in world prices for major PNG agricultural exports, 3) higher trade transaction costs due to restrictions on the movement of people (traders) and goods given social distancing measures of COVID-19, and 4) potential economic recession causing urban household income to fall by 10 percent. Finally, the last simulation considers the combined effect of all COVID-19 related shocks combining the above scenarios into a single simulation. A key result of the analysis is that urban households, especially the urban poor, are particularly vulnerable to shocks related to the Covid-19 pandemic. Lower economic activity in urban areas (assumed to reduce urban non-agricultural incomes by 10 percent), increases in marketing costs due to domestic trade disruptions, and 30 percent higher imported rice prices combine to lower urban incomes by almost 15 percent for both poor and non-poor urban households. Urban poor households, however, suffer the largest drop in calorie consumption - 19.8 percent, compared to a 15.8 percent decline for urban non-poor households. Rural households are much less affected by the Covid-19 related shocks modeled in these simulations. Rural household incomes, affected mainly by reduced urban demand and market disruptions, fall by only about four percent. Nonetheless, calorie consumption for the rural poor and non-poor falls by 5.5 and 4.2 percent, respectively.
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This research note provides a description of the survey sample and implementation and reports on initial findings from analysis of the survey data. Our aim is to use this research and evidence to spur a policy dialogue on promoting increased agricultural productivity, enhanced food security, and improved nutrition policies in PNG. Initial survey results show that most of the food consumed by rural households in the sample is produced from households’ own farms, indicating that consumption is closely linked with overall agricultural productivity. Classifying the survey sample by poor and non-poor households, we find that the poor households are not consuming the recommended daily calorie levels, considered necessary for a healthy and productive life. The survey data also suggest that child stunting (29 percent) and wasting (7 percent) are relatively high in the surveyed areas.
Despite poultry being lauded as a relatively affordable source of protein and micronutrients in many lower-income countries, chicken meat is twice as expensive in PNG compared to nearby Southeast Asian countries. Recent rural household consumption data collected by the International Food Policy Research Institute (IFPRI) suggests that an important share of households do not eat enough protein to meet healthy dietary guidelines (Schmidt et al., 2024). Poultry, along with fish and pork, are the three most important animal-source protein foods in the country, yet these products remain financially prohibitive to a large share of the population. This paper explores the unique challenges and opportunities within PNG’s poultry sector using a "growth diagnostic" approach (pioneered by Rodrik, 2010). Through interviews with key stakeholders across the poultry value chain, we found that while high feed costs persist as a significant challenge, poultry farmers have yet to adopt additional cost-reduction strategies, such as establishing small-scale regional feed mills, utilizing local feed ingredients, and diversifying feed and input imports. An intriguing puzzle of PNG’s poultry sector is the limited number of small-scale producers successfully transitioning to medium-scale operations. This primarily stems from high transport costs and restricted access to input and sales markets. The challenges of marketing chicken in PNG have received less attention than production. Drawing on the experiences of successful models in other countries and considering the specific situation of PNG's poultry sector, fostering poultry production and processing clusters (e.g., in Lae suburban areas) emerges as a potential strategy to address production, transportation, and marketing constraints. By concentrating production, value chain clustering can enhance access to essential services (e.g. slaughtering and cold storage), improve market access, and reduce overall costs. While clustering holds promise for PNG’s poultry value chain, its success hinges upon joint action between the public and private sectors, as well as NGOs operating within the value chain.
