Since the 1990s, there have been rapid increases in concentration ratios in many industries in the U.S., Australia and, we suspect, in other countries. Despite this, applications of GTAP continue to be based on pure competition or Melitz-style Large-Group Monopolistic Competition (LGMC). In either case, all firms are small, there is free entry, and industries make zero pure profits. Markusen challenges modellers to move to Small-Group Monopolistic Competition (SGMC) in which industries have high levels of concentration and firms are aware of the likely behaviour of their rivals. By making two generalizations of Melitz-LGMC specifications, we create a version of GTAP in which some industries are modelled as SGMC. First, we treat the demand elasticities perceived by firms for their products as variables. In our SGMC specification, markups over marginal costs, which depend on perceived elasticities, rise when these elasticities are reduced (in absolute terms) by anti-competitive practices. Second, we allow for sticky adjustment of the number of firms in an industry and simulate situations in which entry is blocked or partially blocked, allowing incumbent firms to make positive pure profits. As illustrated in our simulations, the emergence of pure profits has the potential to suppress real wage rates.

Shock-intensive simulations can be used to: update computable general equilibrium (CGE) databases; estimate trends in industry technologies and the preferences of households, governments and importers; and generate baselines that incorporate forecasts from organizations specializing in different aspects of economies. We demonstrate the shock-intensive methodology by applying it to the Global Trade Analysis Project (GTAP) model. We update a 2014 GTAP database to 2019 with data-driven shocks to an array of macro and energy variables and describe the simulated shifts in technologies and preferences. Then, starting from the updated database, we conduct baseline simulations for 2019 to 2030, 2030 to 2040 and 2040 to 2050 in which macro and energy variables are driven by forecasts from the International Monetary Fund (IMF), International Institute for Applied Systems Analysis (IIASA) and International Energy Agency (IEA). The simulations connect disjoint years (e.g. 2019 and 2030) and use a smooth-growth assumption for savings in each region to jump over intermediate years. Investors are given forward-looking expectations so that their simulated decisions in 2030, for example, are realistic in light of prospects for 2030 to 2040. Considerable space in the paper is devoted to explaining closure swaps for facilitating shock-intensive simulations.

DSGE models incorporate attractive theoretical specifications of the behaviour of forward‐looking consumers facing an uncertain future. Central to these specifications is the idea that consuming agents decide their consumption level in year t by applying a function (policy rule) whose arguments represent information available in year t . Using the insight that, under certain conditions, the policy rule (but not the resulting policy) is invariant through time, DSGE modellers have developed the perturbation and other methods for quantitatively specifying policy rules. They have applied these methods in models with limited sectoral disaggregation. In this paper we adapt the perturbation method so that it can be used to specify a policy rule for consumption in a full‐scale CGE model. A novel feature of our method is the use of specially constructed CGE simulations to reveal key parameters used in deriving the policy rule. We apply our method in illustrative simulations of the effects of a technology shock in a 70‐sector version of the USAGE model of the US economy.

David Evans was an Australian who completed a path-breaking PhD thesis at Harvard in 1968 under the supervision of Wassily Leontief. The thesis set out Australia’s first computable general equilibrium (CGE) model, with an application to an analysis of Australia’s then policy of high tariffs. David returned to Australia in 1968 but left in 1973 and spent the rest of his career in the UK. Despite his relatively brief time working in Australia, David was a major contributor to Australian economics. In this paper, I start with a few personal reminiscences about David. Then I explain how the Evans model worked, and its limitations. This is followed by a description of what happened in Australian CGE research in the 1970s, post-Evans. Since then, Australia has become well known in this field. The international reach of Australian CGE modelling is described briefly in the final part of the paper.

China's household registration system—hukou system prevents rural workers from freely moving to the urban sectors. In this chapter, we introduced an innovative labor-market module to the CHINEGEM model to simulate the economic effects of relaxing the hukou system from 2008 to 2020. The extended CHINAGEM model allows us to model a gradual accumulation of workers in urban activities with a corresponding decumulation in agricultural activities in response to a dismantling of restrictions on rural-urban mobility. Our modelling results reveal that reducing the institutional restriction to rural labour movement will encourage rural workers to move into urban sectors. This enhanced labour movement will not only increase China's GDP and real consumption of households but also increase the real wages of agricultural and rural non-agricultural workers. Although the real wage of rural migrant workers will increase at a slightly lower rate than in the baseline scenario, rural migrant workers remain considerably better paid than agricultural and rural non-agricultural workers.

This chapter defines CGE modelling by explaining the meaning of the “C”, the “G” and the “E”. It then identifies Leif Johansen’s model of Norway, published in 1960, as the first CGE model, and outlines the subsequent evolution of the field. Since Johansen’s time, CGE models have become dynamic, multi-regional and multi-national. As illustrated in CHINAGEM, there has been an enormous increase in the quantity of policy-relevant detail embraced by CGE models. This has enabled them to become the go-to tool for policy analysis in trade, micro-economic reform, environment, labour and many other areas. People new to CGE modelling sometimes ask what it offers beyond I–O (input–output modelling). The chapter answers that question. Finally, the chapter provides a list of what readers can expect to learn from the rest of the book.

A major question in contemporary economic discussions is who wins and who loses from global supply chain (GSC) trade. In seeking an answer to this question, policy makers are not well-served by existing economic models. GSC models lack adequate representation of labour markets and other aspects of the economy outside the GSC sector. Global computable general equilibrium (CGE) models have an economy-wide perspective but lack essential GSC features. We integrate GSC with CGE. Results from the integrated model can differ sharply from standalone results. A stylized application of the integrated model shows that GSC trade can accelerate the transfer of labour in developing countries out of low-marginal-productivity agriculture into higher-marginal-productivity manufacturing. At the same time, GSC trade can leave high-income countries with a difficult structural-adjustment problem and little if any long-run gain.

Background Slowing climate change is crucial to the future wellbeing of human societies and the greater environment. Current beef production systems in the USA are a major source of negative environmental impacts and raise various animal welfare concerns. Nevertheless, beef production provides a food source high in protein and many nutrients as well as providing employment and income to millions of people. Cattle farming also contributes to individual and community identities and regional food cultures. Novel plant-based meat alternatives have been promoted as technologies that could transform the food system by reducing negative environmental, animal welfare, and health effects of meat production and consumption. Recent studies have conducted static analyses of shifts in diets globally and in the USA, but have not considered how the whole food system would respond to these changes, nor the ethical implications of these responses. We aimed to better explore these dynamics within the US food system and contribute a multiple perspective ethical assessment of plant-based alternatives to beef. Methods In this national modelling analysis, we explored multiple ethical perspectives and the implications of the adoption of plant-based alternatives to beef in the USA. We developed USAGE-Food, a modified version of USAGE (a detailed computable general equilibrium model of the US economy), by improving the representation of sector interactions and dependencies, and consumer behaviour to better reflect resource use across the food system and the substitutability of foods within households. We further extended USAGE, by linking estimates of the environmental footprint of US agriculture, to estimate how changes across the agriculture sector could alter the environmental impact of primary food production across the whole sector, not only the beef sector. Using USAGE-Food, we simulated four beef replacement scenarios against a baseline of current beef demand in the USA: BEEF10, in which beef expenditure is replaced by other foods and three scenarios wherein 10%, 30%, or 60% of beef expenditure is replaced by plant-based alternatives. Findings The adoption of plant-based beef alternatives is likely to reduce the carbon footprint of US food production by 2.5-135.%, by reducing the number of animals needed for beef production by 2-12 million. Impacts on other dimensions are more ambiguous, as the agricultural workforce and natural resources, such as water and cropland, are reallocated across the food system. The shifting allocation of resources should lead to a more efficient food system, but could facilitate the expansion of other animal value chains (eg, pork and poultry) and increased exports of agricultural products. In aggregate, these changes across the food system would have a small, potentially positive, impact on national gross domestic product. However, they would lead to substantial disruptions within the agricultural economy, with the cattle and beef processing sectors decreasing by 7-45%, challenging the livelihoods of the more than 1.5 million people currently employed in beef value chains (primary production and animal processing) in the USA. Interpretation Economic modelling suggests that the adoption of plant-based beef alternatives can contribute to reducing greenhouse gas emissions from the food system. Relocation of resources across the food system, simulated by our dynamic modelling approach, might mitigate gains across other environmental dimensions (ie, water or chemical use) and might facilitate the growth of other animal value chains. Although economic consequences at the country level are small, there would be concentrated losses within the beef value chain. Reduced carbon footprint and increased resource use efficiency of the food system are reasons for policy makers to encourage the continued development of these technologies. Despite this positive outcome, policy makers should recognise the ethical assessment of these transitions will be complex, and should remain vigilant to negative outcomes and be prepared to target policies to minimise the worst effects. Copyright (c) 2022 The Author(s). Published by Elsevier Ltd.

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It is possible that COVID will trigger permanent changes in work practices that increase costs in U.S. meat‐processing plants. These changes will be beneficial for the safety and economic welfare of meat‐processing workers. However, they will have economic costs. In assessing reform options, policymakers seek guidance from analyses based on models embracing micro detail and an economy‐wide perspective. In this paper, we use USAGE‐Food, a highly disaggregated computable general equilibrium (CGE) model of the United States, to work out how additional processing costs would be distributed between consumers of meat products and farmers. We also calculate industry and macroeconomic effects. Despite modelling farmers as owning fixed factors, principally their own labour, we find that the farmer share in extra processing costs is likely to be quite moderate. Throughout the paper, we support simulation results with back‐of‐the‐envelope calculations, diagrams and sensitivity analyses. These devices identify the mechanisms in the model and key data points that are responsible for the main results. In this way, we avoid the black‐box criticism that is sometimes levelled at CGE modelling.

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.

We add to the GTAP model a financial module built around an 18-region assetliability matrix. A financial agent in each region takes account of expected rates of return in allocating the region's financial budget between domestic capital and financial assets in each other region. Using the GTAP model with the financial module in place, we simulate financial decoupling between the U.S. and China. The results show that the U.S. would gain by limiting its financial flows to China, leading to a redirection of finance to the domestic economy. This would stimulate investment in the U.S. with favorable effects on employment, capital stocks, real GDP, wealth, and real wage rates. At the same time investment in China would decline with negative effects on the Chinese economy. Similarly, China would gain by limiting its financial flows to the U.S. and the U.S. would lose. In a tit-for-tat situation in which each country reduces its financial asset holding in the other country by x per cent, the winner would be China. We conduct additional simulations to compare the effects of trade decoupling with those of financial decoupling.

The general equilibrium method adopted here reveals several effects of agriculture-focused immigration policies that would not have emerged in partial equilibrium analysis applied to agriculture. Our general equilibrium model includes specifications of: inter-sectoral labor flows; the role of vacancies in determining occupational choices; and macroeconomic relationships. This enables us to show that agricultural guest-worker and legalization programs are likely to: have similar effects on the agricultural sector; cause a gradual welfare-enhancing transformation of the occupational mix of incumbent employment away from agriculture; have small (possibly negative) effects on farm income; and have positive effects on aggregate capital, employment and GDP.

With Covid, high-school students are having difficulty staying in school. We present a dynamic model of the effects of increased drop-out rates. The model accounts for labor productivity, crime costs and high-school savings. We simulate a 25 per cent increase in drop-out rates occurring in the two years starting September 2019, with a gradual return to pre-Covid rates in 2025. Our results show a loss of 597,000 high-school graduations from cohorts entering high-school in 2016-2024. The present-value cost is between $42 and $137 billion, depending on discount rates. These results support investment in high-school retention policies through the Covid crisis.

It is possible that Covid will produce permanent changes in work practices that increase costs in U.S. meat-processing plants. These changes may be beneficial for the safety of meat-processing workers and the health of the community more generally. However, they will have economic costs. In this paper we use USAGE-Food, a detailed computable general equilibrium (CGE) model of the U.S., to work out how those costs would be distributed between farmers and consumers of meat products. We also calculate industry and macroeconomic effects. Despite modelling the farmers as owning fixed factors, principally their own labour, we find that the farmer share in extra processing costs is likely to be quite moderate. Throughout the paper, we support simulation results by back-of-the-envelope calculations, diagrams and sensitivity analysis. These devices identify the mechanisms in the model and key data points that are responsible for the main results. In this way, we avoid the black-box criticism that is sometimes levelled at CGE modelling.

International financial institutions provide capital to a range of Indian financial intermediaries, and engage with these intermediaries in a range of ways that potentially improve the allocation of capital within India. We investigate the impact on the Indian economy of a hypothetical rise in foreign-supplied capital to local Indian financial institution investees, and the engagement activities that might be associated with it. We do this by modelling: (a) the effects on the Indian economy of the supply of additional $US 10 b. of financial capital phased in over five years, and (b) India benefiting from the capital efficiency enhancement effects arising from engagement with the providers of this capital. We undertake our investigation with a 150-sector dynamic computable general equilibrium model of the Indian economy (NCAER-VU-DYN, or NV-DYN) which builds on an existing comparative-static model (NCAER-VU). Compared with NCAER-VU, NV-DYN contains: (i) year-on-year dynamics, (ii) a treatment of the labour market that allows for temporary unemployment, (iii) a Lewis-style mechanism governing movement of unskilled labour between rural and urban activities, and (iv) a top-down facility for calculating employment impacts by gender.

Thousands of economists spread across almost every country use the GTAP model to analyse trade policies including trade wars and trade agreements. GTAP has an impressive regional coverage (140 countries), but the standard commodity coverage (57 commodities/industries) can cause frustration when tariffs on narrowly defined products are being negotiated. This article sets out a method for disaggregating commodities/industries in computable general equilibrium models such as GTAP and applies it to GTAP’s motor vehicle sector. The method makes use of readily available highly disaggregated trade data supplemented by detailed input–output data where available and data from a variety of other sources such as commercial market reports. JEL Codes: C68, F13, F14, F17

We add a financial module to the GTAP model, built around an 18-region asset-liability matrix. We simulate financial decoupling between the U.S. and China. We find that the U.S. would gain by limiting its capital flows to China, leading to a redirection of finance to the domestic economy. This would stimulate investment in the U.S. with favorable effects on employment, capital stocks, real GDP, wealth and real wage rates. At the same time investment in China would decline with negative effects on the Chinese economy. Similarly, China would gain by limiting its capital flows to the U.S. and the U.S. would lose. In a tit-for-tat situation in which each country reduces its financial-asset holding in the other country by x per cent, the winner would be China. We conduct additional simulations to compare the effects of trade decoupling with those of financial decoupling.

DSGE models incorporate attractive theoretical specifications of the behaviour of forward-looking households facing an uncertain future. Central to these specifications is the idea that households decide their consumption level in year t by applying a function (policy rule) whose arguments represent information available in year t. Using the insight that, under certain conditions, the policy rule (but not the resulting policy) is invariant through time, DSGE modellers have developed the perturbation and other methods for quantitatively specifying policy rules. They have applied these methods in small macro models. In this paper we adapt the perturbation method so that it can be used to specify a policy rule for household consumption in a full-scale CGE model. A novel feature of our method is the use of specially constructed CGE simulations to reveal key parameters used in deriving the policy rule. We apply our method in an illustrative simulation of the effects of a technology shock in a 70-sector version of the USAGE model of the U.S. economy.