Based on a more realistic assumption, we modify the Taylor regression. The modified Taylor regression gives an explanation of why the (standard) Taylor regression is spurious (in the econometric sense, i.e. no stable relationship among the variables of interest) and, at the same time, a solution as to how central bank monetary policy can still be described by the Taylor rule. An empirical examp...

this article is a comparative study of estimation power of artificial neural networks and autoregressive time series models in inflation forecasting. using 37 years iran’s inflation data, neural networks performs better on average for short horizons than autoregressive models. this study shows usefulness of early stopping technique in learning stage of neural networks for estimating time series...

Based on monthly observations, I specify an econometric model capturing the driving forces behind the crude oil price series in recent years. A large set of covariates, such as supply and demand variables as well as futures market variables, is used to test the impact on the crude oil price. Current price movements are a result of scarce refining capacity and speculators betting on higher price...

The paper suggests a CUSUM-type test for time-varying parameters in a recently proposed spatial autoregressive model for stock returns and derives its asymptotic null distribution as well as local power properties. As can be seen from Euro Stoxx 50 returns, a combination of spatial modelling and change point tests allows for superior risk forecasts in portfolio management. JEL Classification: C...

Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: -mdrawsfor deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function -mvnp()for calc...

We perform a series of Monte Carlo experiments in order to evaluate the impact of data transformation on forecasting models, and ̄nd that vector error-corrections dominate di®erenced data vector autoregressions when the correct data transformation is used, but not when data are incorrectly tansformed, even if the true model contains cointegrating restrictions. We argue that one reason for this ...

This paper considers an application of the Markov switching vector error correction model to analysis long-run and short-run dependence Russian real GDP exchange on oil prices. An algorithm for estimation with a priori information state hidden chain in some periods time is provided. It shown that period 1999–2018 two different regimes are well defined: slow adjustment rate sharp reaction respon...

Tumor hypoxia and the hypoxia-inducible factors (HIFs) play a central role in the development of cancer. To study the relationship between tumor growth, tumor hypoxia, the stabilization of HIF-1alpha, and HIF transcriptional activity, we have established an in vivo imaging tool that allows longitudinal and noninvasive monitoring of these processes in a mouse C51 allograft tumor model. We used p...

GroES is an indispensable chaperonin virtually found throughout all life forms. Consequently, mutations of this protein must be critically scrutinized by natural selection. Nevertheless, the homolog from a potentially virulent gastric pathogen, Helicobacter pylori, strikingly features a histidine/cysteine-rich C terminus that shares no significant homology with other family members. Additionall...