A new way to interpret the DIRAC equation in a non-Riemannian manifold

The idea of internal mass terms introduced in ref. (1), is shown not to be an appropriate hypothesis when it is placed in connection with the components of the generalized (matrix) vierbeins being proportional to the Riemannian (gravitational) vierbeins. It would result in an undesirable canceling of the Electromagnetic and the Yang-Mills components in the generalized metric. Another hypothesis is introduced where the wave function psi is Taylor expanded in a small parameter p

Intervention Analysis with Cointegrated Time Series: The Case of the Hawaii Hotel Room Tax

Tourism taxes have become an important source of revenue or many tourist destinations in the USA. Among the most widely used is the hotel room tax, levied by 47 states and many localities. Room taxes are touted by proponents as a way to shift the local tax burden to non-residents, while the travel industry claims the levies significantly harm their competitiveness. Previous studies of room tax impacts have relied on ex ante estimates of demand and supply elasticities. In this study, we analyse the effect on hotel revenues of the Hawaii room tax using time series intervention analysis. We specify a time series model of revenue behaviour that captures the long-run cointegrating relationships among revenues and important income and relative price variables, as well as other short-run dynamic influences. We estimate the effect on Hawaii hotel room revenues of the 5% Hawaii hotel room tax introduced in January 1987. We find no evidence of statistically significant tax impacts.

Chinese Saving Dynamics: The Impact of GDP Growth and the Dependent Share

China’s national saving rate rose rapidly in the 2000s after declining through the late 1990s. These dynamics are not explained by precautionary motives, the institutional distribution of income, or reform related processes in general. Rather, we find a compelling explanation lies with GDP growth fluctuations and movement in the dependent share in population. We estimate a vector autoregressive model for the period 1978-2008, then generate in-sample simulations that successfully replicate the 2000s runup in the saving rate. Our out of sample forecasts show the saving rate dropping in the 2010s as the dependency share falls and GDP growth moderates.

Financial Integration in the Pacific Basin Region: RIP by PANIC Attack?

We exploit advances in panel data econometrics to test whether real interest parity holds in the Pacific Basin region. We test for a unit root in the difference between either the US, Japanese or Euro area real interest rate and the real interest rates from a panel of eleven Pacific Basin economies. Unlike extant studies which test for RIP using panel data, we use Bai and Ng's (2004) PANIC test which allows for a very general model of cross-section dependence, including the possibility of cross-unit cointegration. Ignoring the possibility of cross-unit cointegration can lead to severe size distortions and to an over-rejection of the null hypothesis of a unit root. We overturn earlier findings based on first generation panel tests, and demonstrate that cross-unit cointegration lead to incorrect conclusions. We find that RIP holds in the Pacific region. Real interest rates converge to the US rate. We find no support for the hypothesis that Pacific Basin real interest rates converge to either the Japanese or Euro area rates.Real Interest Parity, Pacific-Basin Capital Market Integration, Panel Unit Root, PANIC.

The application of a computer data acquisition system for a new high temperature tribometer

The two data acquisition computer programs are described which were developed for a high temperature friction and wear test apparatus, a tribometer. The raw data produced by the tribometer and the methods used to sample that data are explained. In addition, the instrumentation and computer hardware and software are presented. Also shown is how computer data acquisition was applied to increase convenience and productivity on a high temperature tribometer

Specifying the Forecast Generating Process for Exchange Rate Survey Forecasts

This paper contributes to the literature on the modeling of survey forecasts using learning variables. We use individual industry data on yen-dollar exchange rate predictions at the two week, three month, and six month horizons supplied by the Japan Center for International Finance. Compared to earlier studies, our focus is not on testing a single type of learning model, whether univariate or mixed, but on searching over many types of learning models to determine if any are congruent. In addition to including the standard expectational variables (adaptive, extrapolative, and regressive), we also include a set of interactive variables which allow for lagged dependence of one industry’s forecast on the others. Our search produces a remarkably small number of congruent specifications-even when we allow for 1) a flexible lag specification, 2) endogenous break points and 3) an expansion of the initial list of regressors to include lagged dependent variables and use a General-to-Specific modeling strategy. We conclude that, regardless of forecasters’ ability to produce rational forecasts, they are not only “different,” but different in ways that cannot be adequately represented by learning models.Learning Models, Exchange Rate, Survey Forecasts

Modeling the supply and demand for tourism: a fully identified VECM approach

Cointegration analysis has gradually appeared in the empirical tourism literature. However, the focus has been exclusively on the demand side, neglecting potentially-important supply-side influences and risking endogeneity bias. One reason for this omission may be the difficulty identifying structural relationships in a system setting. We estimate a vector error correction model of the supply and demand for Hawaii tourism using a theory-directed sequential reduction method suggested by Hall et al. (2002). We compare forecasts for the selected model and for two competing models. Diebold and Mariano (1995) tests for forecast accuracy demonstrate the satisfactory performance of this approach.catastrophe, Cointegration, Vector error correction model, Identification, Tourism demand and supply analysis, Hawaii

The Impact of 9/11 and Other Terrible Global Events on Tourism in the U.S. and Hawaii

This paper reviews recent trends in travel and tourism in the U.S. and Hawaii to ascertain how the terrorist attacks of 9/11 and subsequent terrible global events affected their tourism flows and the manner and pace of their recovery. We note that tourism in the U.S. has not fully recovered from 9/11 and other international shocks; indeed recovery of international travel to the U.S. may be a long way off. By contrast, Hawaii tourism is enjoying robust growth in the aftermath of 9/11 as growth in tourist arrivals from the U.S. mainland has more than offset declines in Japanese and other international visitors. We suggest that Hawaii's current tourism boom is in part explained by the diversion of U.S. travel from foreign travel. The paper demonstrates the usefulness of vector error correction models to generate dynamic visitor forecasts which we use to ascertain whether tourism in Hawaii has fully recovered from 9/11 and other terrible international events. The paper considers policy options for facilitating the recovery of international tourism to the U.S.

Apollo extension system lsv studies. mission command and control

Steering system and control circuit for Lunar Surface Vehicle /LSV/ - Apollo projec

The Rationality and Heterogeneity of Survey Forecasts of the Yen-Dollar Exchange Rate: A Reexamination

This paper examines the rationality and diversity of industry-level forecasts of the yen-dollar exchange rate collected by the Japan Center for International Finance. In several ways we update and extend the seminal work by Ito (1990). We compare three specifications for testing rationality: the ”conventional” bivariate regression, the univariate regression of a forecast error on a constant and other information set variables, and an error correction model (ECM). We find that the bivariate specification, while producing consistent estimates, suffers from two defects: first, the conventional restrictions are suffcient but not necessary for unbiasedness; second, the test has low power. However, before we can apply the univariate specification, we must conduct pretests for the stationarity of the forecast error. We find a unit root in the six-month horizon forecast error for all groups, thereby rejecting unbiasedness and weak effciency at the pretest stage. For the other two horizons, we find much evidence in favor of unbiasedness but not weak effciency. Our ECM rejects unbiasedness for all forecasters at all horizons. We conjecture that these results, too, occur because the restrictions test suffciency, not necessity. In our systems estimation and micro- homogeneity testing, we use an innovative GMM technique (Bonham and Cohen (2001)) that allows for forecaster cross-correlation due to the existence of common shocks and/or herd e ects. Tests of micro-homogeneity uniformly reject the hypothesis that forecasters across the four industries exhibit similar rationality characteristics.Rational Expectations, Heterogeneity, Exchange Rate, Survey Forecast