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AbstractEconomic consequence analysis is one of many inputs to terrorism contingency planning. Computable general equilibrium (CGE) models are being used more frequently in these analyses, in part because of their capacity to accommodate high levels of event‐specific detail. In modeling the potential economic effects of a hypothetical terrorist event, two broad sets of shocks are required: (1) physical impacts on observable variables (e.g., asset damage); (2) behavioral impacts on unobservable variables (e.g., investor uncertainty). Assembling shocks describing the physical impacts of a terrorist incident is relatively straightforward, since estimates are either readily available or plausibly inferred. However, assembling shocks describing behavioral impacts is more difficult. Values for behavioral variables (e.g., required rates of return) are typically inferred or estimated by indirect means. Generally, this has been achieved via reference to extraneous literature or ex ante surveys. This article explores a new method. We elucidate the magnitude of CGE‐relevant structural shifts implicit in econometric evidence on terrorist incidents, with a view to informing future ex ante event assessments. Ex post econometric studies of terrorism by Blomberg et al. yield macro econometric equations that describe the response of observable economic variables (e.g., GDP growth) to terrorist incidents. We use these equations to determine estimates for relevant (unobservable) structural and policy variables impacted by terrorist incidents, using a CGE model of the United States. This allows us to: (i) compare values for these shifts with input assumptions in earlier ex ante CGE studies; and (ii) discuss how future ex ante studies can be informed by our analysis.

In 1995 all Australian state and territory governments entered into an agreement with the federal government to introduce a comprehensive program of national competition policy (NCP) reforms. A number of studies have attempted to assess the benefits of these reforms by (i) estimating, via data envelopment analysis or similar techniques, the productivity gap between Australian industries affected by the reforms and their foreign counterparts, and (ii) then modelling the long-run effects of bringing the relevant Australian industries to world-best-practice levels of efficiency. These studies have been criticised for having severely overestimated the efficiency gains from NCP, and for ignoring the associated labour market adjustments. In this paper we take advantage of FEDERAL-F's historical modelling and forecasting capabilities to take a new approach to the problem. First, to measure the efficiency gains from NCP, we use the observed changes in efficiency in one of the sectors subject to NCP reforms (utilities) immediately after the introduction of NCP (rather than following the earlier approach of making a comparison between actual and best-practice levels of productivity). The changes in the utilities sector's primary factor productivity pre- and post- the introduction of NCP are calculated during historical simulations with FEDERAL-F. We investigate the impacts that the changes in observed productivity improvements have had on regional indicators of aggregate economic activity, with particular attention to indices of regional labour market adjustment costs. The changes in these indices provide measures of the value of labour inputs that are lost as implementation of the NCP alters the flow of people between different labour market categories.

On accession to the EU, Poland, one of the most agricultural countries in the region, became eligible for the Common Agricultural Policy (CAP), which it perceived as a chance to develop its rural economy. However, in constructing its 2007-2013 Rural Development Programme, Poland directed the largest funding share to Less Favoured Areas (LFA) -- a controversial measure accused of poor targeting and ineffectiveness. In this paper, we analyse the spatial economic consequences of LFA support for all 16 NUTS2 regions in Poland using a regional computable general equilibrium model called POLTERM. We show that LFA support did help to increase farmers' incomes, but harmed export-oriented sectors and hindered structural change in the Polish economy.

The Common Agricultural Policy (CAP) is one of the most complex and also the most costly of all EU policies. It comprises over 40 financing streams, including Pillar I and Pillar II measures which are highly regulated. In the case of Poland, these are directed to all 16 NUTS2 regions. We are modelling here the regional and thus national consequences of the CAP's most costly Pillar II measure in Poland, so called Less Favoured Areas support (LFA). It is complex, when we recognise the multipurpose of this measure and significant amount of funds directed at a large number of regions. To handle the regional complexity of this problem, we require a multi-regional model. Such a model must be detailed in its disaggregation of industries, commodities and households if it is to be capable of reflecting the complexity of this measure. As such, we use a large-scale multi-regional CGE model. The model is tailored to reflect the complexity of the rural development policy (Pillar II), of which LFA is the largest part in Poland. Of the 82 region-specific sectors in the model, over 20 is related to agricultural production. The model distinguishes rural and urban households in each region and is based on the most recent IO tables of 2005. We propose a framework for mapping the individual financing stream of the LFA to the specific structural variables relating to specific type of land (LFA and nonLFA) in each region. As to our best knowledge such an approach was never conducted before with respect not only of LFA but also Pillar II measures in general.

In response to oil price rises and carbon emission concerns, policies promoting increased ethanol usage in gasoline blends are being implemented by many countries, including major energy users such as USA, EU and Japan. As a result, Brazil, as the largest ethanol producer and exporter in the world, can expect growing foreign demand for ethanol exports. Also, the introduction of flex-fuel vehicles in Brazil is causing domestic sales of ethanol to increase steadily. In this paper, we investigate the regional and industrial economic consequences of rapid growth in Brazilian ethanol consumption and exports. For this, we use a disaggregated multi-regional computable general equilibrium (CGE) model with energy industry detail. Our modelling emphasises a number of features of ethanol production in Brazil which we expect to be important in determining the adjustment of its regional economies to a substantial expansion in ethanol production. These include regional differences in ethanol and sugar production technologies, sugarcane harvesting methods and the elasticity of land supply to sugarcane production.

Many studies, both of Australia and of comparable developed economies, have found that the economic benefits from investment in urban infrastructure are substantial. However the nature of this infrastructure is often such that it is under-provided by the private sector. In Australia, much of the responsibility for the provision of urban infrastructure rests with state and local government. However throughout the 1990's many of Australia's state governments embarked on a period of fiscal restraint, seeking to improve financial positions weakened by exposure to failed state government enterprises in the early 1990's. Perhaps because of the deferred consequences of reducing spending on infrastructure, a large proportion of this fiscal adjustment appears to have been borne by spending on public infrastructure. Today, policy attention at the state government level is again focussing on public infrastructure. However in spite of the now robust fiscal positions of Australia's state governments, there remains a reluctance on their part to finance public infrastructure through debt, and raising taxes is perceived as politically unpopular. Instead, governments are exploring alternative financing instruments, such as developer charges and public-private partnerships. This paper uses a dynamic multi-regional CGE model (MMRF) to evaluate the regional macro economic consequences of four alternative methods of financing an expansion in state government spending on public infrastructure. The four methods are developer charges, payroll tax, government debt, and residential rates. The paper confirms that the services provided by public infrastructure can have significant impacts on the regional macro economy. More importantly however, the paper demonstrates that the total gains from urban infrastructure are quite sensitive to the means chosen by government to finance infrastructure investment. In contrast to up-front financing methods (such as developer charges, payroll tax, and residential rates), the paper finds that the gains from urban infrastructure are greatest when the chosen financing method provides a closer match between the timing of the burden of financing the infrastructure and the timing of the benefits provided by the infrastructure. This can be achieved by instruments such as debt, public-private partnerships, and user charges. On this basis the paper finds that a greater reliance by regional government son debt financing might be warranted, and that the gains from infrastructure expenditure are least when that expenditure is financed by developer charges.

Many studies have found that the economic benefits from investment in urban infrastructure are substantial. In Australia, much of the responsibility for the provision of urban infrastructure rests with regional governments. Throughout the1990's many of these governments embarked on a program of fiscal restraint, seeking to restore financial positions weakened by exposure to failed government enterprises. A large proportion of this fiscal adjustment appears to have been borne by spending on public infrastructure. Today, regional government policy attention is again focussing on public infrastructure. In spite of the now robust fiscal positions of Australia's regional governments, they remain reluctant to finance infrastructure through debt, and raising the rates of existing taxes is perceived as politically unpopular. Instead, governments are exploring alternative financing instruments, such as developer charges and public-private partnerships. This paper uses a dynamic multi-regional CGE model (MMRF) to evaluate the regional macroeconomic consequences of four methods of financing a program of regional government infrastructure provision. The methods are developer charges, debt, payroll tax and residential rates. We demonstrate that the net gains from a program of urban infrastructure development are quite sensitive to the chosen financing means. The net gains tend to be greatest under rates and debt financing, and least under developer charges.

MMRF is a dynamic CGE model of Australia's six State and two Territory economies. MMRF is used extensively in contract research. Several features of MMRF make it an ideal tool for policy analysis, including: dynamics, a highly disaggregated regional and sectoral database, a national labour market, and detailed modelling of government financial statistics.