Calidad de vida de los cafeticultores en las Altas Montañas de Veracruz, México

Introduction: The High Mountain Region (RHM) is the most productive and socioeconomic region for the coffee cultivation in the state of Veracruz, Mexico, and one of the most representative of the sector at the national level. Background: To determine the quality of life (QL) from the objective and subjective point of view of the small coffee producers (SP) in RHM, Mexico. Materials and methods: One hundred and fifty semi-structured interviews were applied to producers in eleven municipalities located in: Comapa, Coscomatepec, Huatusco, Ixhuatl..n del caf.., Sochiapa, Tenampa, Tomatl..n, Totutla, Tlaltetela, Tlacotepec, and Zentla, during 2020. Descriptive statistics and trend measurements were obtained. Results: At objective level the QL was found to be low, but at the farmers' subjective level, it was determined to be acceptable. In the objective assessment, it was identified that the SP have minimal education (primary), the income is not adequate (they require activities outside the farm with an average net annual income of US $ 416 to US $ 1115), the cost of health has increased (due to the COVID-19 pandemic), and proper nutrition is lacking (19 to 25 meals per month). In the subjective assessment there is insecurity and distrust with the government authorities, however, the producers have adapted to living in adverse socioeconomic contexts, since they value community life, intra-family relationships and their environment (coffee growing), which could be influenced by their own worldview. Conclusion: With or without knowledge of the concept of quality, producers have developed a learned or acquired capacity, both individually and collectively to adapt to the environment. Objectively, the quality of life is considered low, however, the interviewees had a perception of satisfaction both individually and collectively.

COVID-19, living income differential and decline in income of cocoa producers in C..te d'Ivoire. (Agriculture et syst..mes alimentaires face .. la Covid-19.) [French]

Cocoa farmers in C..te d'Ivoire are mostly below the poverty line. In September 2019, the Ivorian and Ghanaian governments imposed the Living Income Differential (LID) on private companies, an additional $ 400 per ton compared to the international market price, passed on to the producer price (farm gate price). At the beginning of 2020, the Covid-19 arose. In this dual context, how did prices change? Has the hope of increased income been achieved? Three approaches are used: (a) monitoring of the selling price of cocoa beans and monitoring of the price of purchased cocoa farming inputs and basic necessities for households;(b) monthly monitoring of farm gate cocoa price in 2020-2021;(c) an analysis of national production data from C..te d'Ivoire and Ghana, the world price, variations in the demand for beans by the grinding industry, and the price paid to producers, over 20 years. The first result is a very temporary and limited rise in the farm gate price of cocoa at the end of 2020, then its fall in 2021 as the price of inputs and basic necessities soar. The 2021-2022 campaign is even more harmful with a tightening of the price scissor. It is therefore the failure of the LID, but the role of Covid-19 in this failure is very nuanced with regard to the declarations of the State and the multinationals. The drop in prices and the loss of income for cocoa farmers in 2020-2022 rather fits into the economic theory of games. Without control of their supply, an agreement between two companies or countries cannot work. The failure is part of a largely endogenous structural change: demographic growth, policies to encourage migration and deforestation, opacity of the sector and finally continued growth of the supply of cocoa from C..te d'Ivoire on the international market.

Italian farms during the COVID-19 pandemic: main problems and future perspectives. A direct analysis through the italian FADN

The spread of the COVID-19 virus in Italy during the first phasis of the pandemic (February-May 2020) has caused a large-scale crisis, with an almost immediate decrease of industrial production and a consequent contraction in domestic consumption and external trade. However, the issue of food security was immediately recognized as one of the most sensitive, so that the Government has decreed the priority role of the food system, which has been included among those considered fundamental services and economically essential, allowing the related activities to be carried out during the lockdown. Agricultural production activities transformation, and commercialization remained fully operative during the lockdown;nevertheless, the sector has faced many difficulties related to the contraction of some of the marketing channels (restaurants, on farm sales, agritourism, problems with the logistics and many other ones). To better understand the effects of the initial phasis of the pandemic on the Italian agricultural sector and provide useful information to the government and decision makers, a survey was carried out with a CAWI (Computer Assisted Web Interviewing) sent to over 10,000 farmers belonging to the sample of the Farm Accountancy Data Network (FADN). The number of respondents has been of 733 farms, which represents around 7% of the Italian FADN sample. The results of the questionnaire have been matched with FADN data on the structure and the economic performance of farms, allowing a more precise evaluation of the condition and effects of the pandemic. The results highlight a relevant effect of the COVID-19 pandemic emergency on the agricultural sector: 37% of the interviewed farmers declared a significant liquidity crisis, while 60% predicted a contraction in turnover. These effects are more relevant for the wine, olives, and horticulture types of farming and more frequent in medium/large farms. A better situation has been found for farms which usually outsource processing and/or marketing/sale of the products.

2020 Annual report of the Southwest Minnesota Farm Business Management Association

The average net farm income for the 108 farms included in the 2020 annual report of the Southwest Minnesota Farm Business Management Association was $322,402, up more than 100% from the preceding year. Much of this increased profitability resulted from improved crop prices in the third and fourth quarters of 2020 as well as improved profitability for livestock producers. Government payments related to the impacts of the COVID pandemic were also a big factor. Profits for association members were at their highest levels since 2012. Crop producers saw higher earnings based on above average yields, higher harvest season prices, and increased government payments. Livestock markets were severely impacted by the pandemic especially in the second quarter of the year. Earnings for all types of livestock operations were up primarily because of COVID related government payments. Without those payments, many livestock producers would have suffered severe losses.

Household Level Determinants of Food Insecurity in Rural Ethiopia

Introduction. Currently, Ethiopia, in particular, the rural areas of Ethiopia, faces high levels of food insecurity. In spite of the fact that there have been many studies on food security, most of them have been conducted in specific national settings. Hence, the determinants of food insecurity should be assessed at the national level. Therefore, this study was primarily aimed to identify the determinant factors of household food insecurity in rural Ethiopia. Method. A cross-sectional Ethiopian socioeconomic survey (ESS) data collected from September 2018 to August 2019 was utilized. A sample of 3115 households was selected from 316 clusters across rural Ethiopia using a two-stage probability sampling technique. To identify the determinants of food insecurity, logistic regression was applied. Results. Among 3,115 households, 50.05% of them were food insecure. Factors such as the household head being aged from 30 to 64 (AOR = 0.786, 95% CI: [0.635, 0.973]), widowed, divorced, or separated (AOR = 1.588, 95%CI: [1.001, 2.518]), literate (AOR = 0.702, 95%CI: [0.590, 0.834]), household aid (AOR = 1.339, 95%CI: [1.089, 1.648]), drought-affected (AOR = 0.640, 95%CI: [0.507, 0.808]), nonagricultural business (AOR = 0.655, 95%CI: [0.472, 0.908]), dependency ratio from 50 to 75% (AOR = 0.680, 95%CI: [0.534, 0.867]), having 6 to 10 livestock (AOR = 0.644, 95%CI: [0.496, 0.836]), and more than 10 livestock (AOR = 0.362, 95% CI: [0.284, 0.461]) were found to be significantly associated with the household’s food insecurity at 5% level of significance. Conclusion. The household head’s age from 30 to 64, being literate, drought-affected, having nonagricultural business, dependency ratio from 50 to 75%, and owning more than 10 livestock have been negatively affecting food insecurity. While supporting households, a “widowed, divorced, or separated” household head has had a positive effect on food insecurity in rural Ethiopia positively influencing food insecurity in rural Ethiopia. Policymakers need to pay special attention to very young and old-aged household heads, adult education, household self-help, livestock improvement, and entrepreneurship while implementing poverty reduction programs.

Soybean trade report: trend and risk analysis

This report presents organized and structured information on soybean trade indicators across geographical space and through time. The indicators considered are exports, imports and prices. These also are presented at the by-product level. The levels of aggregation are global, U.S. and North Dakota. The information of each indicator is presented in the form of trends and descriptive statistics. The former reveals the direction of the growth, while the latter reveals the magnitude of expectations. The descriptive statistics are represented by the mean, standard deviation, coefficient of variation and share contribution to the total. The report is presented in six sections: (I) global temporal soybean trade, (II) global spatial soybean export, (III) global spatial soybean import, (IV) U.S. temporal soybean export, (V) U.S. spatial soybean export and (VI) U.S. state level soybean export. At the global level, the trends of the indicators are presented in addition to the descriptive statistics of the top 15 exporting and importing countries. The trends and descriptive statistics for the top 15 exporting states also are provided at the U.S. level. This report is important because it serves as an informational guide on exports, our competitors for exports and potential markets for soybeans to our producers. In the current environment, the success (productivity and net farm income stability) of agricultural business depends on accurate prediction of potential demand for soybeans and their products to help producers in making decisions for domestic or foreign markets. Hence, having a comprehensive and accurate database on exports and imports at the global, national and state levels will enable producers in decisionmaking with confidence. To formulate trade policies related to the international market, the trends and the descriptive statistics are useful to producers in identifying variations in demand for soybeans and their products. For decision makers, this information is helpful in the development of risk management tools for potential export losses due to risky events such as politically driven tariffs and uncertain events such as COVID-19. Finally, in the years of decline, identifying sources of variation or risk in changing consumer preferences, genetically modified restrictive index, trade facilitation and prosperity indexes is important. The study reveals that: Global Trade * The soybean market has shifted to processed products. * Soybean grain, residue and crude oil are primary with an increase in flour. * Brazil, Argentina, Paraguay and Canada are the major competitors with the U.S. for soybean grains. * China, Japan, Netherlands, Spain and Germany are the major destinations for soybean grain. * Soybean grain prices have been on the decline in recent years. U.S. Trade vii * China, Mexico, Japan, Indonesia and Netherlands are the major destinations for U.S. soybean grains. * Turkey, Russia, Argentina and Italy are among the top 15 importers of soybean grains but not part of the top 15 U.S. export destinations. U.S. State Trade * Our state-level estimates of trade are consistent with U.S. Department of Agriculture (USDA) Economic Research Service (ERS) exports. In contrast, the USDA Foreign Agricultural Service (FAS) under- and overestimates state exports because they are based on the location of the port. * Our production-adjusted state export estimates suggest the major exporters of soybeans are Illinois, Iowa, Minnesota, Nebraska, Indiana, Ohio, Missouri, South Dakota, North Dakota and Kansas. North Dakota Trade * North Dakota soybean exports are underestimated by the USDA FAS. * For instance, the production adjusted export value predicts a value of $885,365,842 in 2018, while the ERS method predicted $887,896,380 for North Dakota. On the other hand, the FAS method presents a value of $62,543,314.

Selected impacts of the COVID-19 pandemic and responses on U.S. agriculture and agricultural product markets: FAPRI-MU Report #06-21

The following text examines some impacts of the COVID-19 pandemic on U.S. agricultural and agricultural product markets, producers, consumers, and related indicators. We outline reasons why reviewing events in isolation in 2020 might not give reliable estimates of the impacts of the COVID-19 pandemic and might result in misleading expectations about a future pandemic. Next, we explore the effects of three key aspects of the shock in the United States: (1) lockdown impacts that reduced liquid fuel use dramatically, (2) disruptions in the livestock-meat sector supply chain, and (3) changes in overall economic activity, household income, and total expenditures. For these experiments, we use the FAPRI-MU stochastic model to simulate the impacts of a hypothetical future pandemic. This is not a study of the entire COVID-19 pandemic. The full impacts of the COVID-19 pandemic are large and complex. Factors include effects on health and mortality, a broader economic shock with its employment and income effects, lockdowns and reduced socializing, supply chain disruptions, policy responses, and similar shocks to other countries. The negative effects were experienced differently by each country. We focus only on the U.S. experience. We draw some conclusions from this and related work. * Market outcomes in 2020 were driven by factors other than the pandemic, such as a surge in crop exports and weather disruptions, so year-over-year changes alone are probably not good indicators of how the pandemic affected the sector. * Three of the largest direct impacts of COVID-19 on the agriculture sector were on fuel markets, meat supply chains, and consumer demand patterns. Demands for fuels fell by 5-10% after taking into account price and income effects. Margins between meat retail prices and livestock prices widened after considering other factors. * The loss of economic activity as measured by the falling U.S. GDP could have been expected to cause weaker demand for agricultural goods, lower prices, and sharply lower farm income than what was observed in 2020. * U.S. policy responses included payments that increased disposable income, boosted consumer demand, and mitigated the impacts on farm income from the drop in the size of the national economy. Greater payments directly to farmers also help explain why farm income rose in 2020 relative to 2019. * The impact of COVID-19 is partly a story of policy responses, including sector-specific actions targeting agriculture, fiscal policy, monetary policy, and lockdowns. A future pandemic might be set in a context that limits or disallows some of these options, or a setting that has - perhaps by design - new options. * A future pandemic's impacts would differ from recent experiences because of disease characteristics and also new individual, firm, and policy responses. If one assumes that a future pandemic is an exact repeat of the 2020 pandemic, then that implicitly requires that the disease is equally contagious and harmful, individuals and firms respond to a new pandemic the same as they did in 2020, and policy responses repeat the responses to COVID-19.

Baseline update for Missouri farm income

An increase in farm commodity prices contributes to projected record farm cash receipts and net farm income in Missouri in 2021. A drop in government payments and rising production expenses could dampen the outlook for farm finances in 2022, but projected net farm income remains above the 2020 level for the next several years. The projections in this report update March 2021 estimates of Missouri agricultural markets and farm income. This report incorporates projections for US. agricultural markets included in the FAPRI-MU update published in early September 2021 FAPRI-MU Report 404-21, available at htips://www.faprimissouri.edu/publicationfaugast-2021-baseline-outlook-update/. The US. market update reflected information available in August 2021, including USDA production estimates of 2021 crop production and July 2021 macroeconomic forecasts from HIS Markit. Historical Missouri farm income data used in this report are from USDA's Economic Research Service, including estimates of 2020 Missouri farm income released on September 2, 2021. Key results of the projections for Missouri agricultural markets and farm income include: - Sharply higher prices for corn, soybeans, hogs and other farm commodities result in a $2.0 billion increase in Missouri crop cash receipts in 2021 and a $0.9 billion increase in livestock sector receipts. - Higher production expenses and reduced government payments offset part of the increase in cash receipts. Net farm income increases by $1.3 billion in 2021 over 2020, to a record $4.5 billion. - Projected Missouri crop acreage in 2022 is relatively stable. Crop receipts increase slightly in 2022 as farmers complete marketings of crops produced in 2021, but then fall back as prices for corn, soybeans and other crops moderate. - Livestock sector cash receipts dip in 2022, as projected declines in hog prices and receipts more than offset slightly higher cattle prices and receipts. In later years, modest projected increases in livestock sector production and higher cattle prices contribute to a slow increase in livestock sector cash receipts. - Direct government payments to Missouri farmers peaked at $1.5 billion in 2020, primarily because of temporary, ad hoc programs such as the Coronavirus Food Assistance Program (CFAP) and the Paycheck Protection Program (PPP). Projected payments decline in 2021, but remain large by historical standards. - This current-policy baseline does not assume any new ad hoc assistance programs beyond those announced by Au-gust 2021. In addition, higher commodity prices sharply reduce projected payments under the Agriculture Risk Coverage (ARC) and Price Loss Coverage (PLC) programs. As a result, projected direct government payments to Missouri farmers decline to $218 million in 2022. - Projected farm production expenses increase by almost $800 million in 2021, let by a sharp increase in purchased feed costs. Lower corn and soybean meal prices result in slightly lower feed costs in 2022, but increases in fertilizer expenses, machinery depreciation, and other cost categories result in a small net increase in Missouri farm production expenses next year. These projections should be considered a snapshot given information available in August and early September 2021. Final estimates of 2021 crop yields will differ from those in USDA's August crop report and farm output and input prices will change in response to shifting market conditions.

2021 U.S. agricultural market outlook: FAPRI-MU Report #01-21

The COVID-19 pandemic upended agricultural markets, contributing to a dismal outlook for the farm economy in the spring and summer of 2020. A series of emergency support programs provided record government payments to farmers, and prices for many commodities rebounded in the final months of the year, resulting in a large increase in 2020 net farm income. Looking ahead, the outlook is uncertain, but certainly more optimistic than it was a few months ago. These baseline projections for agricultural and biofuel markets were prepared using market information available in January 2021. Macroeconomic assumptions are based primarily on forecasts by IHS Markit, which suggest a recovery in the U.S. and global economies. The baseline reflects current policies, meaning it incorporates the various assistance programs that had been enacted prior to January 2021, but does not reflect any subsequent policy changes. Commodity markets will continue to be volatile. We use our models to develop a range of projected market outcomes that takes into account some major sources of uncertainty about future supply and demand conditions. In some of the resulting 500 outcomes, prices, quantities and values are much higher or much lower than the averages reported here. Some key results: * Major crop prices retreat from recent peaks, but remain above the prices of 2015-2019. For the crop to be harvested in the fall of 2021, projected corn prices average $4.06 per bushel and soybeans average $10.61 per bushel. * Increasing imports by China explain much of the recent strength in grain and oilseed markets. If China's purchases continue at the recent pace, U.S. exports and market prices could be higher than projected here, but there is downside risk as well. * Higher prices and assumed normal spring planting conditions allow 2021 total area planted to major crops to rebound to 2018 levels. That could allow planted acreage for corn, soybeans and wheat to all expand in the same year. Projected soybean acreage exceeds 90 million acres. * Average prices for livestock and poultry increase in 2021 as the sector returns to more normal operating conditions after the plant closures and other disruptions of 2020. * After the pandemic reduced driving and fuel use in 2020, projected ethanol production and use increase in 2021, but do not immediately rebound to pre-COVID levels. * Crop insurance and the price loss coverage (PLC) program account for most projected support to the farm sector. These programs provide far less support than the market facilitation program (MFP), the coronavirus food assistance program (CFAP) and the paycheck protection program (PPP) provided in 2020. * The final rounds of ad hoc assistance payments push total outlays on selected mandatory farm-related programs to a record $51 billion in fiscal year (FY) 2021. Without this additional assistance, the total drops back to an annual average of $23 billion between FY 2022 and FY 2030, only slightly above the FY 2015-FY 2019 average. * Net farm income increased to $121 billion in 2020, the highest level since 2013, primarily because of $46 billion in government payments. Net farm income drops to $112 billion in 2021, in spite of a $25 billion increase in crop and livestock receipts. Reduced government payments and higher production costs explain the drop in net farm income. * Higher levels of net farm income support an increase in land and farm asset values in 2021. The result is the first slight dip in the farm debt-to-asset ratio since 2012. In later years, declining real net farm income and an eventual increase in interest rates put pressure on asset values and cause the debt-to-asset ratio to resume its increase. * Consumer food price inflation increased to 3.4% in 2020, in part because of a wider gap between producer prices for livestock and consumer prices for meat. Food inflation moderates to 2.1% in 2021 as conditions normalize, and food inflation is similar to overall inflation in subsequent years.

Baseline update for U.S. farm income and government costs

Higher commodity prices contribute to a sharp increase in U.S. net farm income in 2021. Under current policies, farm income could drop again in 2022, as government payments decline and production expenses continue to rise. This report utilizes commodity supply, demand and price projections from the FAPRI-MU baseline update released in early September 2021 (FAPRI-MU Report #04-21, available at www.fapri.missouri.edu). Historical data are from USDA and include the revision to farm income accounts released by the Economic Research Service (ERS) on September 2, 2021. These baseline estimates reflect policies in place in late August 2021. It utilizes ERS estimates that farmers will receive about $18 billion in 2021 from pandemic-related programs such as the Coronavirus Food Assistance Program (CFAP), the Pandemic Assistance for Producers (PAP) initiative, and the Paycheck Protection Program (PPP). No further ad hoc assistance is assumed for 2022 and subsequent years, nor do these current-policy projections include any payments that might result from prospective legislation. Given the assumptions of the analysis, here are a few highlights of the results: * Projected 2021 net farm income reaches the highest level since 2013. Relative to 2020, a sharp increase in receipts from sales of crop and livestock products more than offsets the impact of higher production expenses and reduced government payments. * At $122 billion, projected 2021 net farm income exceeds that reported by ERS by several billion dollars. FAPRI-MU and ERS estimates of 2021 livestock sector receipts, government payments and production expenses are similar, but FAPRI-MU estimates higher receipts for corn, soybeans and other crops. * Total projected government spending on farm-related programs reaches a record $52 billion in fiscal year (FY) 2021. Spending on pandemic-related programs accounts for most of the outlays. Spending on 2018 farm bill commodity and crop insurance programs account for less than one-third of total expenditures on the selected programs in FY 2021. * Under current policies, government outlays drop to $22 billion in FY 2022, and government payments to farmers fall from $29 billion in calendar year 2021 to $6 billion in 2022. Conservation programs account for most 2022 government payments. * Projected market prices for several crops peak in the 2021/22 marketing year. As a result, feed grain and oilseed market receipts decline after 2021, but remain well above the levels of 2020. * In contrast, receipts for cattle, dairy and poultry all continue to increase each year. Hog receipts jump in 2021 with sharply higher barrow and gilt prices and then fall back in 2022 as prices moderate. * Higher costs for feed, purchased livestock, fertilizer and other farm inputs raise farm production expenses by $27 billion in 2021, and a smaller increase is projected for 2022. * In 2022, net farm income declines by $23 billion and net cash income falls even more sharply. Reduced government payments and higher production expenses explain the decline, as there is little net change in farm receipts. * In later years, projected net farm income remains fairly steady in nominal terms at just under $100 billion each year. After adjusting for inflation, real net farm income declines each year, and the projected value in 2026 is similar to that in 2019. * Rising asset values and slower growth in debt reduce the sector's debt-to-asset ratio in 2021 and 2022, temporarily reversing the trend of previous years. Lower projected farm income halts the rise in farm real estate values in 2023, and the debt-to-asset ratio again begins to increase. In contrast to the 2021 FAPRI baseline prepared earlier this year, these estimates do not consider market uncertainty. Small proportional changes in market receipts or production expenses can dramatically change the outlook for net income.

Assessment of farm constraints and income losses during COVID-19 lockdown in India

A telephonic survey was conducted during May 2020 among 675 farmers across 28 districts of 11 states of India to assess farm constraints and income losses of lockdown 1.0 and 2.0. The results indicate that labour availability and input accessibility were hurdles, but manageable to some extent. However, marketing constraints inflicted 48 and 19% losses in total expected income of perishable and non-perishable commodities and average loss per farm household was 0.93 lakh (28%). Although, income support was given through PM-KISAN, it was not adequate to compensate losses. Therefore, farm income support needs to be enhanced to cope with lockdown losses.

Study on the Agricultural Air Pollution Aggravated by the Rural Labor Migration

In recent years, air pollution has received serious concerns from researchers, media, and the public sectors, but air pollution from agricultural production activities has not received enough attention. This paper focuses on agricultural air pollution in central China, which is aggravated by the ongoing rural labor migration trend. With a set of panel data released from Hubei and Hunan provinces in China, we adopt the mediating effect model to explore the relationship between rural labor migration and air pollution caused by agricultural activity in China. First, we use the inventory analysis method and principal component analysis method to calculate the comprehensive index of the air pollution of agriculture in 152 counties and districts from Hubei and Hunan provinces, and we empirically test the impact of labor migration on air pollution with a mediating effect model as well as carry out regional heterogeneity analysis on the pollution effect of these two provinces mentioned above. The analysis above indicates that the increase of labor migration has intensified the comprehensive index of air pollution caused by agricultural activity by changing the supply of labor force in the agricultural sector, the budget line of rural residents, and the scale of agricultural production and crop planting structure, but there is a difference in the indirect total effect between the two provinces mentioned above according to our regional heterogeneity analysis. This study is a necessary extension to studies on alleviating and controlling air pollution in China.

Changes in household income, food consumption, and diet quality in urban and rural areas of Ghana during the COVID-19 crisis: results of 2020 phone surveys

This study provides an assessment of changes in household income, livelihood sources, food consumption, and diet quality during the first months of the COVID-19 crisis in a sample of households drawn from both urban and rural areas in Ghana. Phone surveys were conducted in June 2020 with 423 urban consumers in Accra and with 369 small-scale crop and fish farmers in rural areas in six regions in middle and southern Ghana. Data was disaggregated by asset quintiles for both the urban and the rural samples. Reduction in incomes were reported by 83 percent of urban households in Accra, mainly due to business closures and lower sales from their trading enterprises. Most households, however, are showing resilience in terms of food consumption, with a majority of urban consumers surveyed maintaining their pre-COVID-19 level of food consumption;only 9 percent of urban consumers reported reductions in food consumption to cope with income loss due to COVID-19. For the respondents in the rural areas in middle and southern Ghana, 76 percent reported income loss, and all reported that their livelihoods had been affected. Thirty-four percent of 2020 minor season crop farmers experienced difficulty in selling their produce, and 43 percent of all sample crop farmers anticipated difficulties in accessing inputs in the 2020 major season, mainly fertilizers and agrochemicals. Of those growing fish, 53 percent experienced difficulty in accessing inputs, mainly feeds;60 percent reported increased input prices;and 64 percent of those harvesting from March to June 2020 experienced difficulties in selling their fish because of lower demand, lower tilapia prices, and higher transportation costs. Despite farm and nonfarm income losses, a majority of households in the rural sample reported maintaining previous levels of diet diversity and food consumption - only 11 percent reported reducing their food consumption to cope with income loss. Several months into the COVID-19 crisis in Ghana, households in both rural and urban areas showed some resilience in terms of their agricultural production and food consumption. Regular monitoring is needed, however, especially if household savings start to dry up and coping mechanisms become more restrictive.

Application of the Farm Simulation Model approach on economic loss estimation due to Coronavirus (COVID-19) in Bangladesh dairy farms-strategies, options, and way forward.

The objective of this paper is to quantify the economic loss of the dairy farms due to the pandemic novel Coronavirus (COVID-19) infection by analyzing the real-time data of two typical farms (BD-2 and BD-14 cow) in Bangladesh and propose a strategic plan of action to make policy decisions in order to support the dairy industry. The International Farm Comparison Network (IFCN) Farm Simulation Approach and Technology Impact Policy Impact Calculations (TIPICAL) model was used considering with Corona (WC) and without Corona (WOC). The Integrated Dairy Research Network (IDRN) database (January 2019 to July 2020) was used for simulation of IFCN two typical farms. The milk price is decreased by 17% and feed price is increased by 3.7% due to COVID-19 in March which was used as the base for farm simulation. This resulted in a decrease in milk yield by 7.9% and 8.9% for small household and family farms, respectively. The cost of milk production increased by 19.10% and 10.9% for household and family farms, respectively. This has an overall negative impact on farm income which accounted for national economic loss from dairy farms in Bangladesh to 4.43 million USD/day (36.84 crore BDT). This loss has been fluctuated from April onward and was higher in June (3.83 million USD/day) due to a combination of COVID-19, flood, and seasonality effect on lowering milk production. At the same time, the farmers' response to the resilience capacity (liquidity, operating profit margin, and financial performance) to combat COVID-19-induced situation has been declined substantially. Based on this, we conclude that the government might take a strategy to support farmers by providing financial support for increasing the operating capital and decreasing the cost of milk production. The outcome of this study is expected to be beneficial for policymakers, farmers, and processors in Bangladesh and similar other countries elsewhere.