On the Response of Economic Aggregates to Monetary Policy Shocks

This study empirically investigates how shocks to monetary policy measures (short-term nominal interest rate and broad money supply) affect economic aggregates: output growth, price levels and nominal exchange rate. The study is carried out for Pakistan using quarterly data covering the period from 1980 to 2009. In doing this, Johansen’s (1988) co integration technique and vector error correction model are applied to explore the long-run relationship among the variables. We find significant evidence on the existence of a long-run stable relationship between our monetary measures and economic aggregates. The impulse response functions (IRFs) are computed to examine the response of each macroeconomic variable to a standard deviation shock to monetary measures. The IRF graphs reveal a price puzzle in closed as well as in open economy model. However, an initial appreciation of exchange rate is observed, indicating the overshooting hypothesis phenomenon for Pakistan.Monetary Policy, Economic Aggregates, VECM, Impulse Response Function.

On the value of life

The national budget affects life and death via its allocations in areas such as traffic safety, flood control, public health and the like. When the cost-effectiveness of an intervention is evaluated, common effect measures are the number of lives extended (saved) and the expected lifeyears gained. The latter are usually adjusted for quality of life, giving QALYs, and discounted. In models that support decision making on the national aggregates, the subjects can be reduced to representative agents that are scored only on these dimensions. The lives extended measure is impartial to age and sex. The lifeyears measures deals better with the relative impact but is biased in age and sex, since young people have a higher life expectancy than the old and women have a higher life expectancy than men, and policy advice might reflect that bias. It seems advisable to devise a measure that is more impartial and fair with respect to the age groups and the sexes. An alternative is to value a single life at 100%, and to measure the lifeyears gain with respect to that 100%. In addition, rather than fine-tune policy with interpersonal utility comparisons, one could choose a utility norm for the representative agent. A possible norm for time preference and diminishing marginal utility of life is the square root. The square root is easier to communicate than logarithmic utility or some rate of discount, but has comparable effect. A life of 100 years then has value 10, a life of 25 years has value 5, so that by age 25 half of life is passed. The considerations of both 100% range and square root utility lead to the following age & sex adjusted gain measure. When a person has age a, experiences an event (accident, disease) with a life expectancy of d years, but might have an intervention such that the life expectancy could become e, then the current effect measures are the single life saved and the absolute lifeyears gain x = e - d, but the proposed compromise gain measure is g[x | a, d] = Sqrt[x / (a + d + x)]. The square root gives the utility of the representative agent, g gives the impact for interpersonal comparison, and aggregate utility is found by summing the a over the individuals i. For example, saving (from acute death, d = 0) a baby (a = 0) has the same value, namely 1, whether it is a boy (life expectancy at birth, x = 75.94) or girl (x = 80.71) (data Statistics Netherlands 2002). As another example, let the unit share s = x / (a + e) be 25% for one person and 81% for another person so that the last person would weigh more than three times as much in this respect. For above gain measure, g = Sqrt[s] and the weight ratio becomes 50% / 90%, so that the last person now weighs less than half so that there is more equality. The paper compares various gain measures within the context of social welfare maximization.

Quantifying the desired degree of supply chain flexibility

The dynamic nature of today\u27s market drives the need for flexibility in supply chains. The ever-growing need for and importance of flexibility in supply chains has motivated researchers to develop frameworks to achieve supply chain flexibility. Much of the research on supply chain flexibility focuses on drivers of the need for flexibility and classification of supply chain flexibility. Existing frameworks for determining the desired degree of flexibility in supply chains give an overview methodology; however, a comprehensive framework is absent. This research proposes a comprehensive framework to quantify the desired degree of flexibility in supply chains and accordingly determine its associated configuration --Abstract, page iii

Measurement of the reaction to stress and meditation using brain wave coherence and heart rate variability

Measurement of physiological parameters associated with the stress response and the relaxation response caused by various forms of meditation can provide valuable information about the reaction of the body to the mind and to the external environment. This study used two different techniques to evaluate physiological parameters. The first part examined the meditation response by recording the EEG and calculating the coherence between brain waves originating from different parts of the brain. It was found that high levels of coherence in the alpha portion of the EEG frequency band coincided with a restful state associated with the relaxation response. In an effort to measure the autonomic nervous system reaction to relaxation using heart rate variability analysis, it was found necessary to separate sympathetic from parasympathetic influences. This led to measuring the stress reaction in order to find the sympathetic contribution. The stress reaction was measured by acquiring skin temperature data and heart rate data, and comparing the changes in skin temperature to changes in heart rate variability calculated using time frequency analysis. Skin temperature was found to react gradually to sympathetic changes. A strong mental component was found to influence the stress reaction that was being measured

Measurement of the electroencephalogram (EEG) coherence, atmospheric noise, and Schumann resonances in group meditation

Electrical activity in the human body was investigated using EEG and ECG measurements while subjects remained with eyes open, eyes closed and in a meditation state. During these measurements, additional antennas were attached to the equipment to record atmospheric noise and signal activity simultaneously. The obtained data was analyzed and various observations were made. Processed data based on antenna signals clearly showed the presence of man-made signals, having narrow spectral widths that could be treated as atmospheric noise in the frequency range up to 50 Hz. In addition, signals clustered around 7.8, 14.1, 20.3, 26.4, and 32.5 Hz were observed as Schumann resonances of the earth-ionosphere waveguide. Careful analysis of the noise in the EEG and ECG signals showed the noise activity to be identical to the signals detected by the antennas. Hence, it was possible to differentiate the physiological brain and heart activity from the noise, which is now clearly identified as man-made signals and Schumann resonances up to 50 Hz. The presence of coherence in dual EEG channels is a good measure to quantify the meditation state. The performed measurements showed high coherence around 10 Hz in single subjects while meditating. When these measurements extended to two subjects, with the goal to study group meditation, it was observed that coherence spectra spread significantly to other frequencies

Polynomial function intervals for floating-point software verification

The focus of our work is the verification of tight functional properties of numerical programs, such as showing that a floating-point implementation of Riemann integration computes a close approximation of the exact integral. Programmers and engineers writing such programs will benefit from verification tools that support an expressive specification language and that are highly automated. Our work provides a new method for verification of numerical software, supporting a substantially more expressive language for specifications than other publicly available automated tools. The additional expressivity in the specification language is provided by two constructs. First, the specification can feature inclusions between interval arithmetic expressions. Second, the integral operator from classical analysis can be used in the specifications, where the integration bounds can be arbitrary expressions over real variables. To support our claim of expressivity, we outline the verification of four example programs, including the integration example mentioned earlier. A key component of our method is an algorithm for proving numerical theorems. This algorithm is based on automatic polynomial approximation of non-linear real and real-interval functions defined by expressions. The PolyPaver tool is our implementation of the algorithm and its source code is publicly available. In this paper we report on experiments using PolyPaver that indicate that the additional expressivity does not come at a performance cost when comparing with other publicly available state-of-the-art provers. We also include a scalability study that explores the limits of PolyPaver in proving tight functional specifications of progressively larger randomly generated programs