Implications of Domestic Support Disciplines for Further Agricultural Trade Liberalization

This paper employs the GTAP computable general equilibrium model and dataset to analyse the implications of domestic support reductions in the context of agricultural trade liberalisation. Three specific issues are addressed: overhang in domestic support, the accurate distinction of the boxes in the GTAP dataset and the treatment of market price support in the amber box. An extensive domestic support database is used to calculate the change in applied domestic support rates from a specified cut in bound rates, and to identify the impact on the different domestic support boxes and the required reductions in each support category. The GTAP model is extended to incorporate an explicit representation of the market price support element of the AMS. The results from these extensions of the standard database and model support the view that the impact of an agreement to reduce domestic support will be limited and lower than conventionally estimated. Results of simulations combining domestic support cuts with market access and export competition disciplines show that the effect of import tariff reductions dominate the gains from domestic support cuts once full account is taken of the issues addressed in this paper.WTO agricultural negotiations, domestic support, agricultural protection, Aggregate Measure of Support

Combination interventions to prevent HCV transmission among people who inject drugs: modelling the impact of antiviral treatment, needle and syringe programs, and opiate substitution therapy

BackgroundInterventions such as opiate substitution therapy (OST) and high-coverage needle and syringe programs (HCNSP) cannot substantially reduce hepatitis C virus (HCV) prevalence among people who inject drugs (PWID). HCV antiviral treatment may prevent onward transmission. We project the impact of combining OST, HCNSP, and antiviral treatment on HCV prevalence/incidence among PWID.MethodsAn HCV transmission model among PWID was used to project the combinations of OST, HCNSP, and antiviral treatment required to achieve different prevalence and incidence reductions within 10 years for 3 chronic prevalence scenarios and the impact of HCV treatment if only delivered through OST programs. Multivariate and univariate sensitivity analyses were performed.ResultsLarge reductions (>45%) in HCV chronic prevalence over 10 years require HCV antiviral treatment. Scaling up OST and HCNSP substantially reduces the treatment rate required to achieve specific HCV prevalence reductions. If OST and HCNSP coverage were increased to 40% each (no coverage at baseline), then annually treating 10, 23, or 42 per 1000 PWID over 10 years would halve prevalence for 20%, 40%, or 60% baseline chronic HCV prevalences, respectively. Approximately 30% fewer treatments are necessary with new direct-acting antivirals. If coverage of OST and HCNSP is 50% at baseline, similar prevalence reductions require higher treatment rates for the same OST and HCNSP coverage.ConclusionsCombining antiviral treatment with OST with HCNSP is critical for achieving substantial reductions (>50%) in HCV chronic prevalence over 10 years. Empirical studies are required on how best to scale up antiviral treatment and combine treatment with other interventions

Integrating Porpoise and Cod Management: A Comparison of Days-at-sea, ITQs, and Closures

The purpose of this study is to determine if management measures based on effort reductions, in particular days-at-sea (DAS) controls, can approach a harbor porpoise individual transferable quotas (ITQ) program in terms of efficiency. The intent is to expand discussions of combining fishery-porpoise management actions. The New England sink gillnet fishery is examined by using a numerical bio-economic model. Year-round and seasonal surcharges in combinations with overall DAS reductions are investigated. Results indicate that several programs for marine mammal protection can achieve the same conservation outcome with modest differences in industry profits. At the industry level, the program selection decision may then rest on the goal of cod management, since reductions in cod landings are much greater under the DAS year-round (59–63%) versus seasonal (39–46%) programs. Significant differences in vessel profits, however, may make consensus on the appropriate program difficult.Fisheries management, individual transferable quotas, protected species, marine mammals, turtles, bycatch, Environmental Economics and Policy, Research Methods/ Statistical Methods, Q220, Q280, Q570, Q580,

Combining disaggregate forecasts or combining disaggregate information to forecast an aggregate

To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts of those disaggregates or forecasting by a univariate aggregate model. New analytical results show the effects of changing coefficients, mis-specification, estimation uncertainty and mis-measurement error. Forecastorigin shifts in parameters affect absolute, but not relative, forecast accuracies; mis-specification and estimation uncertainty induce forecast-error differences, which variable-selection procedures or dimension reductions can mitigate. In Monte Carlo simulations, different stochastic structures and interdependencies between disaggregates imply that including disaggregate information in the aggregate model improves forecast accuracy. Our theoretical predictions and simulations are corroborated when forecasting aggregate US inflation pre- and post 1984 using disaggregate sectoral data. JEL Classification: C51, C53, E31Aggregate forecasts, Disaggregate information, forecast combination, inflation

From average case complexity to improper learning complexity

The basic problem in the PAC model of computational learning theory is to determine which hypothesis classes are efficiently learnable. There is presently a dearth of results showing hardness of learning problems. Moreover, the existing lower bounds fall short of the best known algorithms. The biggest challenge in proving complexity results is to establish hardness of {\em improper learning} (a.k.a. representation independent learning).The difficulty in proving lower bounds for improper learning is that the standard reductions from $\mathbf{NP}$-hard problems do not seem to apply in this context. There is essentially only one known approach to proving lower bounds on improper learning. It was initiated in (Kearns and Valiant 89) and relies on cryptographic assumptions. We introduce a new technique for proving hardness of improper learning, based on reductions from problems that are hard on average. We put forward a (fairly strong) generalization of Feige's assumption (Feige 02) about the complexity of refuting random constraint satisfaction problems. Combining this assumption with our new technique yields far reaching implications. In particular, 1. Learning $\mathrm{DNF}$'s is hard. 2. Agnostically learning halfspaces with a constant approximation ratio is hard. 3. Learning an intersection of $\omega(1)$ halfspaces is hard.Comment: 34 page

Searching Market Equilibria under Uncertain Utilities

Our basic model is a noncooperative multi-player game in which the governments of neighboring counties trade emission reductions. We prove the existence of a market equilibrium (combining properties of Pareto and Nash equilibria) and study algorithms of searching a market equilibrium. The algorithms are interpreted as repeated auctions in which the auctioneer has no information on countries' costs and benefits and every government has no information on the costs and benefits of other countries. In each round of the auction, the auctioneer offers individual prices for emission reductions and observes countries' best replies. We consider several auctioneer's policies and provide conditions that guarantee approaching a market equilibrium. From a game-theoretical point of view, the repeated auction describes a process of learning in a noncooperative repeated game with incomplete information