Imran Hussain Shah

Making the most of high inflation

This article examines the relationship between the real effects of inflation and its level in countries with frequent episodes of high inflation. The real effects are computed as asymmetric impulse responses of output to inflation separately in the regimes with different signs of the differences between the expected inflation and the predicted output-neutral inflation. It is found that, with the increase in inflation, such effects increase in the regime with the positive sign, relatively to the effects in the regime with the negative sign. It is also shown that this finding is valid for most countries with high inflation episodes, where inflation is greater than 4.8% for at least 25% of quarterly observations. This leads to a simple policy prescription that, in economies with frequent high inflation episodes, anti-inflationary monetary decisions are least damaging for output if undertaken in the periods when the difference between the expected and output-neutral inflation is negative.

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

Seeking price and macroeconomic stabilisation in the euro area: the role of house prices and stock prices

We propose an Economic Stability Index (ESI) incorporating house prices and stock prices as components of the measure of the inflation rate in order to allow the European Central Bank (ECB) to achieve both price and macroeconomic stability. We use an optimisation approach to estimate target weights for different sectoral prices in the broader price index, which depend on sectoral parameters other than those used to compute the Harmonised Index of Consumer Prices applied by the ECB to gauge price stability in the euro area (EA). Our results suggest that if the ECB had targeted the ESI, it would have implemented a different monetary policy which would had increased stability in the EA’s economic activity and would have helped to create adequate preconditions for sustainable economic growth and job creation.