Most dynamic CGE models work with periods of 1 year. This limits their applicability for analysing the effects of shocks that operate over a short period or with different intensities through a year. It is relatively easy to convert an annual CGE model to shorter periodicity, for example a quarter, if we ignore seasonal differences in the pattern of economic activity, but this is not acceptable for agriculture. This paper introduces seasonal factors to the agricultural specification in a detailed quarterly CGE model of the United States. The model is then applied to analyse the effects of the COVID pandemic on U.S. farm industries. Taking account of the general features of the pandemic such as the reduction in household spending, we find that these effects are mild relative to the effects on most other industries. However, agriculture is subject to potential supply-chain disruptions. We apply our quarterly model to analyse two such possibilities: loss of labour at harvest time in Fruit & nut farms, and temporary closure of meat-processing plants. We find that these disruptions are unlikely to cause noticeable reductions in the supply of food products to U.S. households.

This paper provides an empirical case study of impacts of COVID-19 on Australia's wine sector. Wine exports were subject to disruptions and, like domestic wine sales, were adversely affected not only by temporary declines in consumers' expected incomes but also by the social distancing measures and self-isolation that led to closure of restaurants, bars, cafes and clubs plus declines in international travel and tourism. Partly offsetting this has been a boost to off-premise and direct e-commerce sales. We first estimate those impacts and their expected partial recovery in 2021 using a new model of global beverage markets. Then, we add results on regional effects, including through domestic wine tourism, using a new economy-wide model with sub-national regions. The paper concludes by drawing lessons on how this sector's resilience to future global shocks could be strengthened.

We simulate the economic impacts of the COVID-19 pandemic on the Australian economy using VURM, a detailed computable general equilibrium model for Australia. We identify five sources of economic perturbations: changes to productivity due to changing work practices, changes in household demand imposed by voluntary and mandated social distancing behaviour, changes in international trade due to a weakened world economy and severe curtailment of international travel, reduced population growth due to lower net migration and large debt-financed fiscal stimulus. Variants of these shocks and associated recovery paths are simulated in VURM, with three scenarios describing potential recovery arcs. The macroeconomic and industry impacts are reported for each scenario. Ultimately, our focus is on the impact on output and employment in the agriculture and mining sectors, and on their likely recovery prospects. At the peak of economic impacts, output in these sectors declines by about 6 per cent relative to a no-COVID baseline. Compared to the economy-wide average, the decline in agriculture and mining output is small. This can be explained by relatively minor impacts on work practices, relatively low negative impacts on demand for intensive agriculture (helped by fiscal supports for households) and relatively low disruption to export demand.

The COVID-19 pandemic and associated public health and social distancing mandates caused unprecedented shifts and disruptions for local and regional food systems (LRFS). The pandemic also brought new and heightened attention to the structure and resiliency of US food systems, and LRFS appeared to be positioned to significantly increase the scope and scale of their market reach as a result. Researchers from three universities collaborated with staff from the U.S. Department of Agriculture's Agricultural Marketing Service to recruit leaders from sixteen key coalitions within the U.S. LRFS sector to frame an adaptive, community-driven set of applied research activities to understand important themes, learn from effective responses and gain insights into how local and regional supply chains may change post-pandemic. In this paper, we summarise urgent and emergent strategies and innovations from LRFS captured in a fall 2020 consumer survey, with additional insights on how the survey was framed and interpreted, considering synthesis of collaborative discussions and project team interactions. We conclude the article with a set of research, policy and technical assistance priorities that were identified and validated by this LRFS network.

In this paper, we draw on insights from economic theory on urban growth, large shocks and spatial dynamics to assess COVID-19 flow-on effects and potential disruptive legacy in urban-regional dynamics. Urban dynamics in Australia are assessed at national, regional and intra-urban scales. Long-term and short-term urban dynamics are analysed against random growth, locational fundamentals and increasing returns theories of urban growth and adjustment. A focus in Australia and elsewhere is the potential effect of COVID-19 on where people want to live, enabled in part by technological connectivity that releases some workers from proximity to work constraints when choosing a home. Our results suggest that urbanisation trends and adjustments to shocks differ for capital cities and noncapital cities. At the inter-regional migration level, Australia's largest urban system, Sydney, is characterised by a cointegration relationship between outmigration and Sydney property prices relative to other housing markets. At finer spatial scales, COVID-19 had a negative impact on house prices within Sydney and may, for some micro-geographies and/or towns and regional centres, lead to significant change. However, typically this effect on houses (not units) began to dissipate in the period June-November 2020, when also controlling for housing policy pre- and post-COVID-19.

The present study investigates the price (co)volatility of four dairy commodities-skim milk powder, whole milk powder, butter, and cheddar cheese-in three major dairy markets. It uses a multivariate factor stochastic volatility model for estimating the time-varying covariance and correlation matrices by imposing a low-dimensional latent dynamic factor structure. The empirical results support four factors representing the European Union and Oceania dairy sectors as well as the milk powder markets. Factor volatilities and marginal posterior volatilities of each dairy commodity increase after the 2006/07 global (food) crisis, which also coincides with the free trade agreements enacted from 2007 onward and EU and US liberalization policy changes. The model-implied correlation matrices show increasing dependence during the second half of 2006, throughout the first half of 2007, as well as during 2008 and 2014, which can be attributed to various regional agricultural dairy policies. Furthermore, in-sample value at risk measures (VaRs and CoVaRs) are provided for each dairy commodity under consideration.

In rainfed production systems throughout India, agricultural activities are dependent upon the summer monsoon, and any aberration in monsoon rainfall patterns can have severe consequences for rice production. There is considerable policy interest in designing programs to lower small-scale farmers' exposure to these types of risk given the regularity with which adverse monsoon events occur. This paper introduces a field experiment conducted with two risk management options in the state of Odisha: a drought-tolerant rice cultivar; and a weather index insurance product designed to complement the performance of the cultivar. Uptake rates for the cultivar itself and for the joint product are compared across two years alongside an analysis of factors that predict uptake. Results indicate high levels of demand for both the products, albeit with a significant degree of price sensitivity. But this sensitivity is agnostic to the of price reductions, suggesting that public investments that lower the costs of risk management may be sufficient to encourage broad uptake, without necessarily relying upon distortionary subsidies as is so often done. Sustained demand between years one and two is primarily explained where individuals were indemnified in year one and had a large number of peers also purchasing the product.