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.

Forecasting milk production in Bangladesh toward achieving self-sufficiency

Bangladesh dairy has been emerging as a transformation from livelihood-oriented dairy toward enterprise-driven dairy while it can still be seen as a key source of income and livelihoods for millions of people. There is an increasing emphasis by the government for achieving self-sufficiency. However, there have been challenges as the lack in authentic milk production data availability which counteract in estimating the self-sufficiency. There is a growing demand for milk along with the increasing consumer's preferences on high-quality milk. The objective of this study was to forecast Bangladesh milk production to analyze the possible timeframe for achieving the self-sufficiency. This study applies Autoregressive Integrated Moving Average (ARIMA) model and compares with the classical Trend Analysis Model (TAM) with three scenarios (i) Exponential growth, (ii) Compounding Average Growth Rate (CAGR), (iii) Simple Average Growth Rate (SAGR), built in MS Excel using time series milk data (2006 to 2019) obtained from the Department of Livestock Services (DLS), Integrated Dairy Research Network (IDRN) Sector database and International Farm Comparison Network (IFCN) Sector database. The results revealed the superiority of ARIMA model over the trend analysis. The maximum milk production of Bangladesh in 2025 and 2030 will be 10.24 and 13.65 million tons, respectively (according to IDRN data) while that will be 16.32 and 17.13 million ton, respectively according to DLS. Considering the only population as demand factor (deterministic approach), taking the results from the ARIMA model, Bangladesh will be self-sufficient in 2029 according to DLS data and according to IDRN data, Bangladesh will achieve 71% self-sufficient in 2029. The forecasting was calculated only with normal year with some mild shock in the milk production. However, the impact of severe shock-like Coronavirus in 2020 has not been possible to integrate due to anecdotal in data, which implies that including such shock in future this forecasting might lead to the different pace of the self-sufficiency achievement. The results of ARIMA model using DLS data was substantially different than IDRN data which might need to take into account to identify why those data were different and might revise the data backwards to increase the degree of precision for estimating the future milk production data. From this study, it is evident that under normal condition, Bangladesh could reach to the self-sufficiency in 2029 but the year like 2020 (with pandemic coronavirus) need to be observed in the future and might need strategic decision to continue the current growth rate. The precise documentation of the milk production data would lead to the right path toward self-sufficiency. The future study might focus on the stochastic demand and supply factor for self-sufficiency analysis.