A Polynomial Translation of pi-calculus FCPs to Safe Petri Nets

We develop a polynomial translation from finite control pi-calculus processes to safe low-level Petri nets. To our knowledge, this is the first such translation. It is natural in that there is a close correspondence between the control flows, enjoys a bisimulation result, and is suitable for practical model checking.Comment: To appear in special issue on best papers of CONCUR'12 of Logical Methods in Computer Scienc

Too Much to Lose, or More to Gain? Should Sweden Join the Euro?

This paper considers the costs and benefits of Sweden joining the European Economic and Monetary Union (EMU). We pay particular attention to the costs of abandoning the krona in terms of a loss of monetary policy independence. For this purpose, we apply a cointegrated VAR framework to examine the degree of monetary independence that the Sveriges Riksbank enjoys. Our results suggest that Sweden has in fact relatively little to lose from joining EMU, at least in terms of monetary independence. We complement our analysis by looking into other criteria affecting the cost-benefit calculus of monetary integration, which, by and large, support our positive assessment of Swedish EMU membership

Bayesian Updating, Model Class Selection and Robust Stochastic Predictions of Structural Response

A fundamental issue when predicting structural response by using mathematical models is how to treat both modeling and excitation uncertainty. A general framework for this is presented which uses probability as a multi-valued conditional logic for quantitative plausible reasoning in the presence of uncertainty due to incomplete information. The fundamental probability models that represent the structure’s uncertain behavior are specified by the choice of a stochastic system model class: a set of input-output probability models for the structure and a prior probability distribution over this set that quantifies the relative plausibility of each model. A model class can be constructed from a parameterized deterministic structural model by stochastic embedding utilizing Jaynes’ Principle of Maximum Information Entropy. Robust predictive analyses use the entire model class with the probabilistic predictions of each model being weighted by its prior probability, or if structural response data is available, by its posterior probability from Bayes’ Theorem for the model class. Additional robustness to modeling uncertainty comes from combining the robust predictions of each model class in a set of competing candidates weighted by the prior or posterior probability of the model class, the latter being computed from Bayes’ Theorem. This higherlevel application of Bayes’ Theorem automatically applies a quantitative Ockham razor that penalizes the data-fit of more complex model classes that extract more information from the data. Robust predictive analyses involve integrals over highdimensional spaces that usually must be evaluated numerically. Published applications have used Laplace's method of asymptotic approximation or Markov Chain Monte Carlo algorithms

Price, inventories, and volatility in the global wheat market

The study estimates a conditional mean model for international wheat prices and inventories. Endogenous price volatility and exogenous shocks in the price and inventory series are controlled for in estimation. Redressing the empirical linkage between volatility, prices, and inventories is important because volatility increases returns to inventories, which in turn may imply prices. The problem is also important from the regulator perspective, because publicly funded inventory programs have been traditional measures in stabilizing prices and improving food security by providing a buffer against adverse yield shocks and stock-outs. The structural model underlying the estimating equations is based on a dynamic inventory optimization problem. The data suggest that the price of both wheat and wheat inventories is nonstationary and that they are significantly linked to each other in the short run but do not exhibit a stationary long-run equilibrium relationship. Price volatility is an important determinant in the short-run conditional mean processes for both the price and inventories. The pairwise causal relationships have only one direction each. Inventories imply price volatility, price volatility implies price, and price implies inventories, but not vice versa. The parameter estimates suggest that when inventories decrease, price volatility increases. Thus, low inventories have likely been among the necessary conditions, but have not been a sufficient condition by themselves, for the price surge observed in 2008. The price and inventory movements have a significant negative relationship in the very short run, but it is leveled off over time. A decreasing price implies either inventory build-ups or postponement of inventory withdrawals. Overall, the current and past inventory and price movements are not very valuable in predicting the future price movements, and it is likely that the inventory information announced each month is already in the prices.international price, inventories, volatility, Wheat,

A first-order purely frame-formulation of General Relativity

In the gauge natural bundle framework a new space is introduced and a first-order purely frame-formulation of General Relativity is obtained.Comment: 9 Pages, Submitted to Classical and Quantum Gravit

Macroeconomic Volatility Trade-off and Monetary Policy Regime in the Euro Area

This research uncovers a well-defined monetary policy regime starting in 1986 in the aggregate Euro Area. Both alternative solution-estimation methods employed - optimal control cum GMM, and dynamic programming cum FIML - identify a regime of strict inflation targeting with interest rate smoothing. The unemployment gap, properly estimated as quasi real-time information, is a relevant element in the information set of the monetary authority, despite not being included in its preferences. The emergence of the regime relates to the improvement of the volatility trade-off between inflation and unemployment gap since the mid-80s. Additional improving factors have been milder supply shocks and better ability of policymakers to set the interest rate closer to optimum.Monetary Policy Regime, Euro Area, Optimal Control, Dynamic Programming, GMM, FIML.

INTERNAL CONSISTENCY IN MODELS OF OPTIMAL RESOURCE USE UNDER UNCERTAINTY

For several decades, economists have been concerned with the problem of optimal resource use under uncertainty. In many studies, researchers assume that prices evolve according to an exogenous stochastic process and solve the corresponding dynamic optimization problem to yield an optimal decision rule for exploitation of the resource. This study is motivated by our attempt to understand the relationship between efficiency in resource markets and optimal harvest decisions in which price is an exogenous state variable. The literature on optimal commodity storage finds that in a rational expectations equilibrium commodity prices are stationary and serially correlated. Yet recent papers on optimal timber harvesting that assume exogenous stationary prices generate harvest rules inconsistent with the price processes on which they are based. In this study, we investigate the appropriate form of the stochastic process governing prices of renewable resources. We develop a model in which timber is supplied by profit-maximizing managers with rational expectations and aggregate timber demand is subject to independent exogenous shocks. In contrast to earlier studies, prices are endogenously determined. Managers know the structure of the timber market and form expectations of future market equilibria in making optimal harvesting decisions. We show under general conditions that efficient timber prices are stationary and serially correlated. Stationarity and serial correlation are shown to arise from two sources: the occurrence of stock-outs (i.e., depletion of the inventory) and stock-dependent growth of the resource. Further, we show that prices retain these properties even in the absence of stock-outs. Simulations are used to further illustrate the analytical results. Our findings have implications for a large number of economic analyses of optimal resource use. First, our results reveal why extraction rules for renewable resources based on exogenous price specifications are internally inconsistent, even when the specification conforms to the stochastic behavior of prices generated by an efficient market. These prices arise in a particular structural environment, and if large numbers of resource managers adopt the harvesting rule, the underlying structural environment would change, and the price process would deviate from that used to derive the harvesting rule. Second, we show that there can be no gains from exploiting the stochasticity of resource prices in a rational expectations world, a finding that challenges the prescriptive policies for resource use found in many studies, including those on option values. Third, our results show that time-series analyses designed to test for the efficiency of renewable resource markets cannot distinguish prices generated in an efficient market from those generated in an inefficient market. Finally, we extend the literature on optimal storage. Previous models of commodity storage models are shown to be a special case of our model involving age-independent depreciation of the inventory.Resource /Energy Economics and Policy,