Search Results (2)

Countries that achieve economic complexity in a holistic way are well-prepared to respond to external shocks through internal processes that may also improve their resilience. This article suggests that the Economic Complexity Index (ECI) can capture this ‘resilience dimension’ of complex economies and assesses their contribution to sustainable change through the amalgamation of export and import information. This novel methodological approach incorporates import information by applying amalgamation on a pre S-Level, which is based on the Lie-Trotter methodology, inducing a Random Walk on a Graph. In the empirical part, this procedure is examined. It shows that the ECI ranking may not always reflect the underlying internal economic complexity of a country, and with it, the country’s resilience and contribution to sustainable change. The novel approach is to some extent comparable with the degree of eligibility criteria of the original ECI and consistent with the organic evolutionary character of complex economies. After translating the ECI framework into its stochastic counterpart, the proofs of its interpretation in statistic and probabilistic terms, and its relationship to the Shannon Entropy are conducted. Coherency conditions of sustainability as further eligibility criteria are formulated and the degree of coherency of the ECI is investigated. In view of the challenges related to data preparation, we suggest applying the approach to a broader set of data including import information in order to gain additional insights in a country’s internal economic complexity and resilience. Full article

In this paper, we discuss iterative and noniterative splitting methods, in theory and application, to solve stochastic Burgers’ equations in an inviscid form. We present the noniterative splitting methods, which are given as Lie–Trotter and Strang-splitting methods, and we then extend them to deterministic–stochastic splitting approaches. We also discuss the iterative splitting methods, which are based on Picard’s iterative schemes in deterministic–stochastic versions. The numerical approaches are discussed with respect to decomping deterministic and stochastic behaviours, and we describe the underlying numerical analysis. We present numerical experiments based on the nonlinearity of Burgers’ equation, and we show the benefits of the iterative splitting approaches as efficient and accurate solver methods. Full article