This short note examines some time series evidence relating prices of exports and imports to the aggregate US wage over 34 years of falling tariffs starting in the mid 1960s. The cointegrated unit root series lead to error correction and vector autoregression models. The lost protection and changing traded prices lowered the US wage very slightly, by less than 1%. © 2007 Elsevier Inc. All right...

Vector autoregressions are widely used in macroeconomic forecasting since they became known in the 1970s. Extensions including vector error correction models, co-integration and dynamic factor models are all rooted in the framework of vector autoregression. The three important extensions are demonstrated to have formal equivalence between each other. Above all, they all emphasize the importance...

This paper investigates the effects of shocks to U.S. monetary policy on the dollar/yen exchange rate, using structural Vector Error Correction Model (VECM) methods. We compare our estimates of the impulse responses with those based on levels Vector Autoregression. We also compare results from short run and long run restrictions imposed on the structural VECM. We find evidence of overshooting b...

This paper examines empirically the tourism impact on the long-run economic growth of Greece by using the causality analysis among real gross domestic product, real effective exchange rate and international tourism earnings. A multivariate autoregressive VAR model is applied for the examined period 1960:Ι – 2000:IV. The results of cointegration analysis suggested that there is one cointegrated ...

Time-of-Flight (ToF) cameras, a technology which has developed rapidly in recent years, are 3D imaging sensors providing a depth image as well as an amplitude image with a high frame rate. As a ToF camera is limited by the imaging conditions and external environment, its captured data are always subject to certain errors. This paper analyzes the influence of typical external distractions includ...

Robustness of phoneme recognition to additive noise is investigated for PLP and acoustic waveform representations of speech using support vector machines (SVMs) combined via error-correcting code methods. While recognition in the PLP domain attains superb accuracy on clean data, it is significantly affected by mismatch between training and testing noise levels. The classification in the high-di...

This work is concerned with improving the robustness of phoneme classification to additive noise with hybrid features using support vector machines (SVMs). In particular, the cepstral features are combined with local energy features of acoustic waveform segments to form a hybrid representation. The local energy features are taken into account separately in the SVM kernel, and a simple subtracti...

In this paper, a reliable information hiding scheme based on support vector machine and error correcting codes is proposed. To extract the hidden information bits from a possibly tampered watermarked image with a lower error probability, information hiding is modeled as a digital communication problem, and both the good generalization ability of support vector machine and the error correction c...

in this paper, nonlinear adjustments and price transmission mechanism between the two levels of wholesale and retail for the egg market has been examined under the threshold vector error correction model (tvecm) framework using hansen and seo (2002)’s two-regimes). the unit root test showed that both wholesale and retail egg price series were integrated of order one . the johansen co-integratio...