Factor proportions and international business cycles

Positive investment comovements across OECD economies as observed in the data are difficult to replicate in open-economy real business cycle models, but also vary substantially in degree for individual country-pairs. This paper shows that a two-country stochastic growth model that distinguishes sectors by factor intensity (capital-intensive vs. labor-intensive) gives rise to an endogenous channel of the international transmission of shocks that first, can substantially ameliorate the “quantity anomalies” that mark large open-economy models, and second, generate a cross-sectional prediction that is strongly supported by the data: investment correlations tend to be stronger for country-pairs that exhibit greater disparity in the factor-intensity of trade. In addition, three new pieces of evidence support the central mechanism: (1) the production composition of capital versus labor-intensive sectors changes over the business cycle; (2) the prices of capital-intensive goods and labor-intensive goods are respectively, procyclical and countercyclical; (3) a positive productivity shock in the U.S. tilts the composition of production towards capital-intensive sectors in other countries

Factor Proportions and International Business Cycles

Positive investment comovements across OECD economies as observed in the data are difficult to replicate in open-economy real business cycle models, but also vary substantially in degree for individual country-pairs. This paper shows that a two-country stochastic growth model that distinguishes sectors by factor intensity (capital-intensive vs. labor-intensive) gives rise to an endogenous channel of the international transmission of shocks that first, can substantially ameliorate the "quantity anomalies" that mark large open-economy models, and second, generate a cross-sectional prediction that is strongly supported by the data: investment correlations tend to be stronger for country-pairs that exhibit greater disparity in the factor-intensity of trade. In addition, three new pieces of evidence support the central mechanism: (1) the production composition of capital versus labor-intensive sectors changes over the business cycle; (2) the prices of capital-intensive goods and labor-intensive goods are respectively, procyclical and countercyclical; (3) a positive productivity shock in the U.S. tilts the composition of production towards capital-intensive sectors in other countries.International business cycles, international comovement, composition effects

The Use of a Cell Filter for State Estimation in Closed-Loop NMPC of Low Dimensional Systems

Combining variants of the Kalman filter and moving horizon estimation (MHE) with nonlinear MPC has been studied before. The MHE is appealing due to its ability to impose constraints and demonstrated superiority over extended Kalman filter. However, nonlinear MPC based on MHE requires solutions to two back to back nonlinear programs. In this paper we propose to use the cell filter (CF) to provide state feedback to the MPC regulator. The cell filter is a piecewise constant approximation of the conditional probability density of the states, whose temporal evolution is modeled by an aggregate Markov chain. Since the CF is based on discretized state, input and output spaces, the curse of dimensionality limits its application to low dimensional and constrained systems. In this paper we present simulation examples of closed-loop MPC for a nonlinear reactor and agricultural pest control based on state feedback from both CF and MHE

Minimum Initial Marking Estimation in Labeled Petri Nets With Unobservable Transitions

In the literature, researchers have been studying the minimum initial marking (MIM) estimation problem in the labeled Petri nets with observable transitions. This paper extends the results to labeled Petri nets with unobservable transitions (with certain special structure) and proposes algorithms for the MIM estimation (MIM-UT). In particular, we assume that the Petri net structure is given and the unobservable transitions in the net are contact-free. Based on the observation of a sequence of labels, our objective is to find the set of MIM(s) that is(are) able to produce this sequence and has(have) the smallest total number of tokens. An algorithm is developed to find the set of MIM(s) with polynomial complexity in the length of the observed label sequence. Two heuristic algorithms are also proposed to reduce the computational complexity. An illustrative example is also provided to demonstrate the proposed algorithms and compare their performance

An Embedding-based Approach to Inconsistency-tolerant Reasoning with Inconsistent Ontologies

Inconsistency handling is an important issue in knowledge management. Especially in ontology engineering, logical inconsistencies may occur during ontology construction. A natural way to reason with an inconsistent ontology is to utilize the maximal consistent subsets of the ontology. However, previous studies on selecting maximum consistent subsets have rarely considered the semantics of the axioms, which may result in irrational inference. In this paper, we propose a novel approach to reasoning with inconsistent ontologies in description logics based on the embeddings of axioms. We first give a method for turning axioms into distributed semantic vectors to compute the semantic connections between the axioms. We then define an embedding-based method for selecting the maximum consistent subsets and use it to define an inconsistency-tolerant inference relation. We show the rationality of our inference relation by considering some logical properties. Finally, we conduct experiments on several ontologies to evaluate the reasoning power of our inference relation. The experimental results show that our embedding-based method can outperform existing inconsistency-tolerant reasoning methods based on maximal consistent subsets.Comment: 9 pages,1 figur