Synopsis Assessing The Economywide Impacts Of Covid 19 On Rwandas Economy Agri Food System And Poverty A Social Accounting Matrix Sam Multiplier Approach

Rwanda’s policy response to COVID-19 has been widely praised for its rapid, systematic, and comprehensive approach to containing the pandemic. Although the economic consequences of the actions taken are unavoidable, the country expects to return its economy to its high-growth trajectory as the pandemic subsides. We used economic modeling tools designed to estimate the short-term economywide impacts of the unanticipated, rapid-onset economic shocks of COVID-19 on Rwanda. In this brief, we present a synopsis of the results of this analysis. • During the six-week lockdown that began in March 2020, we estimate Rwanda’s GDP fell 39.1 percent (RWF 435 billion; USD 484 million) when compared to a no-COVID situation. • Rwanda’s GDP in 2020 will be between 12 and 16 percent lower than a predicted no-COVID GDP, depending on the pace of economic recovery. The losses in annual GDP are between RWF 1.0 and 1.5 trillion (USD 1.1 to 1.6 billion). • While GDP for the industrial and services sectors were estimated to have fallen during the lockdown period by 57 and 48 percent, respectively, exemptions of COVID-19 restrictions for the agricultural sector limited the decline in agricultural GDP to 7 percent compared to a no-COVID situation. • During the lockdown period, the national poverty rate is estimated to have increased by 10.9 percentage points as 1.3 million people, mostly in rural areas, fell into temporary poverty. Poverty rates are expected to stabilize by the end of 2020, increasing only by between 0.4 and 1.1 percentage points over the pre-COVID situation. While these figures are encouraging, they mask the impacts on poor households of the sharp poverty spike during the lockdown and the inherent complexity of poverty dynamics post-lockdown. Looking forward, the speed and success of Rwanda’s economic recovery will depend critically on expanding Rwanda’s social protection programs, supporting enterprises of all sizes, providing broad assistance to the agri-food system, and restoring international trade.

Rwanda’s policy response to COVID-19 has been widely praised for its rapid, systematic, and comprehensive approach to containing the pandemic. Although the economic consequences are unavoidable, the country expects to return its economy to its high-growth trajectory as the pandemic subsides. We use economic modeling tools designed to estimate the short-term economywide impacts of the unanticipated, rapid-onset economic shocks of COVID-19 on Rwanda. - Results show that during the six-week lockdown that began in March, Rwanda’s GDP fell 39.1 percent (RWF 435 billion; USD 484 million) when compared to a no-COVID situation in the same period. - Results further show that Rwanda’s GDP in 2020 will be between 12 and 16 percent lower than a predicted no-COVID GDP, depending on the pace of the recovery. The losses in annual GDP are between RWF 1.0 and 1.5 trillion (USD 1.1–1.6 billion). - While GDP for the industrial and services sectors were estimated to have fallen during the lockdown period by 57 and 48 percent, respectively, exemptions of COVID-19 restrictions for the agricultural sector limited the decline in agricultural GDP to 7 percent compared to a noCOVID situation. - During the lockdown period, the national poverty rate is estimated to have increased by 10.9 percentage points as 1.3 million people, mostly in rural areas, fell into temporary poverty. Poverty rates are expected to stabilize by the end of 2020, increasing only by between 0.4 and 1.1 percentage points. While these figures may be encouraging, they mask the impacts on poor households of the sharp poverty spike during the lockdown and the inherent complexity of poverty dynamics post-lockdown. Looking forward, the speed and success of Rwanda’s recovery will depend critically on the expansion of Rwanda’s social protection programs, boosting enterprises of all sizes, support to the agri-food system, and restoration of international trade.

In Rwanda, as elsewhere, different types of households experienced the economic effects of COVID-19 differently. We use a microsimulation approach to show the importance of these differences to better understand COVID-19’s impacts on their income and poverty status. Main results: Nationally, during the lockdown period between March and May 2020, the simulation results estimate declines in household income by 33 percent on average. The urban population experienced the largest declines, averaging 40 percent during this period. Unlike patterns seen with other shocks, middle-income households experienced the sharpest declines in income during the lockdown of an estimated 33 to 35 percent. The share of individuals falling into poverty was highest among those in urban, middle income (Ubudehe 2) households (27 percent). However, the greatest absolute number of individuals in poverty remained concentrated in rural areas during the lockdown. Poor individuals in the lowest expenditure quintile remain in the most severe poverty, with average expenditures during the lockdown estimated at 54 percent below the poverty line. Under both the fast and slow post-COVID economic recovery scenarios used in the simulations, household incomes nearly return to pre-COVID levels for all household categories by the end of 2020. However, these results do not capture the potential longterm impacts of the substantial shocks of the pandemic to incomes, assets, and individual wellbeing. These modeling results suggest that targeting should be a central component of the design and implementation of social protection programs and economic recovery policies to support a diverse set of beneficiaries. These beneficiaries include rural farming households and poor households, as well as nonagricultural household, and households in the middle expenditure quintiles.

In Rwanda, as in other countries, different types of households will experience the economic effects of the COVID-19 pandemic differently. We use a microsimulation approach to highlight the importance of these differences and to draw attention to the diversified livelihood strategies of Rwandan households in order to fully understand COVID-19’s impacts on their income and poverty status. Our approach complements macro-level assessments of COVID-19’s economic impacts, focusing on the contribution of the income sources, asset holdings, and location (urban/rural) of households to understanding these differential effects.

The COVID-19 pandemic has had far-reaching impacts in every part of the world, including on vulnerable populations in rural areas of low- and middle-income countries. This report explores the ways in which men and women in rural areas of four countries in sub-Saharan Africa (SSA)—Kenya, Niger, Rwanda, and Uganda—experienced the COVID-19 pandemic and associated income losses, as well as their responses to the crisis. To identify and monitor the differential effects of the COVID-19 pandemic on women and men in rural households, IFPRI conducted phone surveys in selected regions of the four focal countries, with financial and technical support from the Food and Agriculture Organization of the United Nations (FAO). The surveys traced gender differences in responses to the pandemic and associated restrictions, such as choice of coping strategies, access to public assistance, and changes in the care burden for men and women.

As COVID-19 spread across the globe in early 2020, governments had to make difficult policy choices to balance the socioeconomic costs of social distancing and lockdown measures, on the one hand, and the human costs of increased morbidity and mortality of an unchecked pandemic, on the other. The challenge was particularly daunting for developing countries with their often illequipped and underfunded health systems coupled with general skepticism about the effectiveness of economic restrictions to curb viral spread, especially in densely populated informal urban communities (The Economist 2020). Poorer developing country populations also tend to be less resilient to income shocks, while the social protection measures needed to mitigate against income losses are costly. With developing country governments already heavily indebted before the pandemic (Onyekwena and Ekeruche 2019), and with further anticipated losses in tax revenues due to COVID-related economic restrictions, their ability to finance palliative measures without sacrificing much-needed, longer-term public investments has remained a major concern.

Global food, fuel, and fertilizer prices have risen rapidly in recent months, driven in large part by the fallout from the ongoing war in Ukraine and the sanctions imposed on Russia. Other factors have contributed to the crisis, such as export bans and continued supply chain disruptions from the COVID-19 pandemic. For example, between June 2021 and April 2022, the global prices of palm oil and wheat increased by 56 and 100 percent in real terms, respectively. At the same time, the price of fertilizer doubled, while crude oil and natural gas prices have also risen substantially. However, wide variation also exists across commodities, with real maize prices increasing by only 11 percent, and rice prices declining by 13 percent (Figure 1).

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.

Rwanda’s impressive economic growth over the past two decades has been accompanied by significant structural change in the broad economy and the agrifood system in particular. This note summarizes key results from a recent diagnostic of Rwanda’s agrifood system transformation, examining the effectiveness of productivity-led growth in different agricultural value chains for promoting development outcomes related to poverty, growth, employment, diet quality, and hunger. The findings show that value chains differ in their effectiveness in promoting these different development outcomes. The wheat and sorghum value chain, for example, has strong anti-poverty effects and is effective at reducing hunger, but is less effective at increasing jobs. Trade-offs will emerge as no single value chain is most effective at achieving every desired outcome; therefore, promoting a few value chains jointly will diversify agrifood system growth and help achieve multiple development outcomes simultaneously.

As Rwanda is expected to return to its rapid growth trajectory following the COVID-19 pandemic, agriculture will continue to play a central role in the structural transformation of the entire economy. To this end, the Government of Rwanda continues to invest in the agricultural sector by building on Strategic Plans for the Transformation of Agriculture (PSTAs) that began in the early 2000s. The challenging question is how to prioritize public expenditures across a broad portfolio of policies and programs. Ambitious plans, whether in the short or long term, require difficult decisions. The prioritization of public investment becomes even more complex as Rwanda’s structural transformation advances and as new investments—beyond the farm—become critically important for the agricultural sector. The structural transformation process itself means that as agriculture becomes more integrated with the rest of the economy, public resource allocations need to address a wider range of issues across the entire food system; these include nutrition-sensitive food production systems, inclusive value chain development, nonfarm rural enterprise development, and climate-resilient sustainable intensification of both crops and livestock. This study provides evidence that is designed to assist the Government of Rwanda in its selection of agricultural policy, investment, and expenditure portfolios that reflect the country’s broad focus on its food system and structural transformation. This process of prioritization will need to incorporate multiple public investments targeting multiple development outcomes and will need to be grounded in the costeffective use of public resources in a largely market-led transformation process. This data-driven and evidence-based approach must critically underpin an informed investment prioritization process that helps achieve ambitious targets in an environment constrained by limited public resources. The study uses the Rural Investment and Policy Analysis (RIAPA) economywide model developed by the International Food Policy Research Institute (IFPRI), with contributions from colleagues at the Ministry of Agriculture and Animal Resources (MINAGRI), the Ministry of Finance and Economic Planning (MINECOFIN) and the National Institute of Statistics of Rwanda (NISR). The study draws on data from multiple sources as well as expert insights to inform the application of RIAPA’s Agricultural Investment for Data Analyzer (AIDA) module as a tool to measure the impacts of alternative public expenditure options on multiple development outcomes. Using this integrated modeling framework, the study links agricultural and rural development spending to four specific outcomes: economic growth, job creation, poverty reduction, and diet quality improvement; at the same time, it considers the synergies and tradeoffs associated with the different investment options in the transformation process. The paper first assesses the contribution of public expenditures to agricultural and rural development under the fourth Strategic Plan for Agriculture Transformation (PSTA 4) that extends between 2018 and 2024. These findings are important, given the fact that since the beginning of PSTA 4, the budget allocated to MINAGRI (measured in constant prices) has stagnated. Our results suggest that increased spending on agriculture is well justified and that such spending is essential if the Government of Rwanda is to achieve its long-term development goals.