Business Investment in the 1970s: A Comparison of Models

macroeconomics, business investment, business models

Revisions in Investment Anticipations

macroeconomics, investment anticipations

A Test of Fischer's Theory of Monetary Misperceptions and the Business Cycle in the Presence of Long-Term Contracts

This article uses multi-period ex ante anticipations of money supply growth to estimate the parameters of a model, suggested by Stanley Fischer, in which money affects real variables only through multi-period errors in anticipations. This model is tested against an alternative, first evaluated empirically by Robert Barro, in which money affects real variables only through single period errors in anticipations. The two models are compared using the "P" test procedure for non-nested models suggested by Davidson and MacKinnon. The small sample properties of the test are unknown. Random experiments are performed to approximate these properties. On the basis of estimated small scale distributions, the Fischer model rejects the Barro model at conventional levels, but is not rejected by it.Business Cycles; Cycle; Monetary; Money; Supply

Tax Policy and Business Fixed Investment During the Regan Era

We examine the impact of major tax legislation on business capital investment during the 1980-88 period. We detail the tax changes and imbed them into a neoclassical rental price of capital goods. We then use this rental price in two popular models of business fixed investment, a standard and a modified neo-classical model. We estimate these two models along with an accelerator model of capital investment. The models, in general, exhibit parameter instability regardless of fit. We then develop a model incorporating expected delivery lags for new capital goods and embed a forecasted output and the rental price of capital services. Again, parameter instability and fit are examined. Finally we conduct simulations of tax, price and output shocks. We conclude that the new model has parameter stability, and that the net effect of Reagan's tax policies was small

Essential Nutrients for Bone Health and a Review of their Availability in the Average North American Diet

Osteoporosis and low bone mineral density affect millions of Americans. The majority of adults in North America have insufficient intake of vitamin D and calcium along with inadequate exercise. Physicians are aware that vitamin D, calcium and exercise are essential for maintenance of bone health. Physicians are less likely to be aware that dietary insufficiencies of magnesium, silicon, Vitamin K, and boron are also widely prevalent, and each of these essential nutrients is an important contributor to bone health. In addition, specific nutritional factors may improve calcium metabolism and bone formation. It is the authors’ opinion that nutritional supplements should attempt to provide ample, but not excessive, amounts of factors that are frequently insufficient in the typical American diet

Clinical implications of a possible role of vitamin D in multiple sclerosis

Hypovitaminosis D is currently one of the most studied environmental risk factors for multiple sclerosis (MS) and is potentially the most promising in terms of new clinical implications. These practical consequences, which could be applied to MS patients without further delay, constitute the main purpose of this review. Vitamin D is involved in a number of important general actions, which were not even suspected until quite recently. In particular, this vitamin could play an immunomodulatory role in the central nervous system. Many and varied arguments support a significant role for vitamin D in MS. In animal studies, vitamin D prevents and improves experimental autoimmune encephalomyelitis. Epidemiologically, latitude, past exposure to sun and the serum level of vitamin D influence the risk of MS, with, furthermore, significant links existing between these different factors. Clinically, most MS patients have low serum levels of vitamin D and are in a state of insufficiency or even deficiency compared to the international norm, which has been established on a metabolic basis. Large therapeutic trials using vitamin D are still lacking but the first results of phase I/II studies are promising. In the meantime, while awaiting the results of future therapeutic trials, it can no longer be ignored that many MS patients have a lack of vitamin D, which could be detected by a serum titration and corrected using an appropriate vitamin D supplementation in order to restore their serum level to within the normal range. From a purely medical point of view, vitamin D supplementation appears in this light to be unavoidable in order to improve the general state of these patients. Furthermore, it cannot currently be ruled out that this supplementation could also be neurologically beneficial

Data assimilation in a system with two scales-combining two initialization techniques

11 pages, 11 figures, 1 tableFull-text version available Open Access at: http://clivar.iim.csic.es/?q=es/node/319An ensemble Kalman filter (EnKF) is used to assimilate data onto a non-linear chaotic model, coupling two kinds of variables. The first kind of variables of the system is characterized as large amplitude, slow, large scale, distributed in eight equally spaced locations around a circle. The second kind of variables are small amplitude, fast, and short scale, distributed in 256 equally spaced locations. Synthetic observations are obtained from the model and the observational error is proportional to their respective amplitudes. The performance of the EnKF is affected by differences in the spatial correlation scales of the variables being assimilated. This method allows the simultaneous assimilation of all the variables. The ensemble filter also allows assimilating only the large-scale variables, letting the small-scale variables to freely evolve. Assimilation of the large-scale variables together with a few small-scale variables significantly degrades the filter. These results are explained by the spurious correlations that arise from the sampled ensemble covariances. An alternative approach is to combine two different initialization techniques for the slow and fast variables. Here, the fast variables are initialized by restraining the evolution of the ensemble members, using a Newtonian relaxation toward the observed fast variables. Then, the usual ensemble analysis is used to assimilate the large-scale observationsThis study is supported by the Spanish National Science Program under contracts ESP2005–06823-C05 and ESP2007–65667-C04Peer reviewe