Validity of Okun’s Law in a spatially dependent and cyclical asymmetric context

The current article analyzes the validity of Okun?s Law and sizable distortions that can occur in the estimation when spatial dependence and cyclical asymmetric impacts are not considered, which is a concern commonly ignored by the existing literature. Primarily spatial panel regressions (SDM, SAR, and SEM) and nonparametric regressions along with specification tests are adopted in terms of the methodology (such as panel unit root tests, panel cointegration, Moran?s I and Geary?s C tests of global spatial dependence, spatial LM, and Hausman tests). Additionally, spatial heterogeneity and cross-regional variation in Okun?s Law are investigated by adopting geographically weighted regression, LISA (local indicators for spatial association), and local Geary?s C analysis. A panel of 26 Turkish NUTS-2 regions from 2004 to 2018 was analyzed. The results clearly revealed that failing to incorporate spatial proximity and asymmetric cycle impacts leads to the biased estimation of Okun?s coefficient, such that during the downswing years of the national economy, Okun?s Law holds robustly: unemployment increases quickly in response to a decline in output. In contrast, during upswing years, the size of Okun?s coefficient is relatively much lower. Moreover, spatial dependence and heterogeneity are sizably evident. Okun?s coefficient is demonstrated to vary significantly across regions that have different industrial and labor market characteristics. As a policy implication, it has been understood that the reduction of unemployment is more difficult than initially understood, as economic growth itself does not provide a solution during upswing periods. The necessary special and region-specific policies are discussed throughout the text.

ASSESSMENT EXPERIMENTS ON FATIGUE RESISTANCE OF STRUCTURAL MATERIALS AND MACHINERY

A part of any complexity may be presented as a combination of smooth elements and those with design concentrators of mechanical stresses. As a consequence to a first approximation it is possible to investigate smooth samples for the assessment of material fatigue properties. An optimum formation of experiments on the assessment of fatigue strength, reliability and resource of the machine under design is a complex and significant problem. To carry out experiments for fatigue there are used testing machines of different kinds. A type of a testing machine is defined reasoning from the purpose of the work and possibilities of an experimentalist. Subject to the process of changes in time of stresses in a sample one differs fatigue tests at harmonic loading (symmetric, asymmetric cycle), biharmonic (application of two and more harmonics), program (change of stress amplitudes according to a certain program) and random at different types stochastic processes. The problem of machine reliability increase at the expense of destruction elimination in consequence of structural material fatigue is urgent in most of branches mechanical engineering. A topicality is particularly urgent in branches where accidents and breakdowns owing to the destruction of significant parts result in disastrous effects (power engineering, cosmonautics, aircraft, transport of all kinds and so on). For correct assessment of reliability and resource of significant parts subjected to time loads the test conditions approach to operation conditions. The purpose of this work is improvement of design- experimental methods for the assessment of machine reliability at the expense of test conditions approximation to operation loads.

The Asymmetric Cycling of U.S. Soybeans and Brazilian Coffee Prices: An Opportunity for Improved Forecasting and Understanding of Price Behavior

The behavior of agricultural commodity markets can arguably result in markedly asymmetric price cycles, that is, downward cycles of substantially different length and breadth than upward cycles. This study assesses whether asymmetric-cycle models can enhance the understanding of the dynamics and provide for a better forecasting of U.S. soybeans and Brazilian coffee prices. The forecasts from asymmetric cycle models are found to be substantially mode precise than those obtained from standard autoregressive models. The asymmetric cycle models also provide useful insights on the markedly different dynamics of the upward vs. the downward cycles exhibited by the prices of these two commodities.