Real Time Changes in Monetary Policy

This paper investigates potential changes in monetary policy over the last decades using a nonparametric vector autoregression model. In the proposed model, the conditional mean and variance are time-dependent and estimated using a nonparametric local linear method, which allows for different forms of nonlinearity, conditional heteroskedasticity, and non-normality. Our results suggest that there have been gradual and abrupt changes in the variances of shocks, in the monetary transmission mechanism, and in the Fed’s reaction function. The response of output was strongest during Volcker’s disinflationary period and has since been slowly decreasing over time. There have been some abrupt changes in the response of inflation, especially in the early 1980s, but we can not conclude that it is weaker now than in previous periods. Finally, we find significant evidence that policy was passive during some parts of Burn’s period, and active during Volcker’s disinflationary period and Greenspan’s period. However, we find that the uncovered behavior of the parameters is more complex than general conclusions suggest, since they display considerable nonlinearities over time. A particular appeal of the recursive estimation of the proposed VAR-ARCH is the detection of discrete local deviations as well as more gradual ones, without smoothing the timing or magnitude of the changes.Monetary Policy, Taylor Rule, Local Estimation, Nonlinearity, Nonparametric, Monetary Policy; Taylor Rule; Local Estimation; Nonlinearity; Nonparametric; Structural Vector Autoregression; Autoregressive Conditional Heteroskedasticity;

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the inferences’ policy relevance, which is particularly dramatic at the broadest (M3) level of aggregation. Indeed, as Belongia (1996) has observed in this regard, “measurement matters.”Measurement Error, Divisia Index, Aggregation, State Space, Markov Switching, Monetary Policy

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of simple sum monetary aggregates and the Divisia indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although the traditional comparison of the series may suggest that they share similar dynamics, there are important differences during certain times and around turning points that can not be evaluated by their average behavior. We use a factor model with regime switching that offers several ways in which these differences can be analyzed. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each one series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors represent exactly where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We also find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginning and end of economic recessions, and during some high interest rate phases.Measurement Error, Divisia Index, Aggregation, State Space, Markov Switching, Monetary Policy

Particular processing of pro-opiomelanocortin in Xenopus laevis intermediate pituitary Sequencing of α- and β-melanocyte-stimulating hormones

Abstractα- and β-melanocyte-stimulating hormones (α-MSH and β-MSH) have been isolated from Xenopus laevis neurointermediate pituitary and microsequenced. Intracellular α-MSH is not N-acetylated after proteolytic processing of pro-opiomelanocortin in contrast to mammalian α-MSHs. There is a high preservation of the melanotropic amino acid sequence common to all MSHs although in Xenopus β-MSH a histidine residue replaces the glutamic acid residue found in position 8 of mammalian β-MSHs

Neurohypophysial hormones of the 1-month-old bovine fetus: Absence of vasotocin during mammal development

AbstractThe neurohypophysial hormones of the 1-month-old bovine fetus have been identified by their positions in ion-exchange chromatography and their retention times in high-pressure reverse-phase partition chromatography. Arginine vasopressin and oxytocin have been recognized. The molar ratio vasopressin/oxytocin in neurohypophysis is about 6 in the 1-month-old fetus compared with 4 in the 3-month-old fetus, 2.7 in the 7-month-old fetus and 1 in the adult. Vasotocin is virtually absent even in the early fetus (less than 0.1% of arginine vasopressin). The occurrence of a vasotocin gene expressed in the fetus but silent in the adult appears unlikely

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the inferences’ policy relevance, which is particularly dramatic at the broadest (M3) level of aggregation. Indeed, as Belongia (1996) has observed in this regard, “measurement matters.”Measurement Error, Divisia Index, Aggregation, State Space, Markov Switching, Monetary Policy

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the policy relevance of the inferences. Indeed, as Belongia (1996) has observed in this regard, "measurement matters."Measurement error; monetary aggregation; Divisia index; aggregation; state space; Markov switching; monetary policy; index number theory; factor models

Evolutionary Stability of Ecological Hierarchy

A self-similar hierarchical solution that is both dynamically and evolutionarily stable is found to the multi dimensional Lotka-Volterra equation with a single chain of prey-predator relations. This gives a simple and natural explanation to the key features of hierarchical ecosystems, such as its ubiquity, pyramidal population distribution, and higher aggressiveness among higher trophic levels. pacs{87.23.Kg, 89.75.Da, 05.45.-a} keywords{Lotka-Volterra equation, Trophic pyramid, Self-similarity}Comment: 4 Pages RevTeX4, 1 Fig, 1 Table, shortened by publishers reques