Methods for inference in large multiple-equation Markov-switching models

The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of free parameters in the transition matrix to grow as the square of the number of states but also without losing a convenient form for the posterior distribution of the transition matrix. Calculation of marginal data densities for assessing model fit is often difficult in high-dimensional models and seems particularly difficult in these models. This paper gives a detailed explanation of methods we have found to work to overcome these difficulties. It also makes suggestions for maximizing posterior density and initiating Markov chain Monte Carlo simulations that provide some robustness against the complex shape of the likelihood in these models. These difficulties and remedies are likely to be useful generally for Bayesian inference in large time-series models. The paper includes some discussion of model specification issues that apply particularly to structural vector autoregressions with a Markov-switching structure.

Indeterminacy in a Forward Looking Regime Switching Model

This paper is about the properties of Markov switching rational expectations (MSRE) models. We present a simple monetary policy model that switches between two regimes with known transition probabilities. The first regime, treated in isolation, has a unique determinate rational expectations equilibrium and the second contains a set of indeterminate sunspot equilibria. We show that the Markov switching model, which randomizes between these two regimes, may contain a continuum of indeterminate equilibria. We provide examples of stationary sunspot equilibria and bounded sunspot equilibria which exist even when the MSRE model satisfies a 'generalized Taylor principle'. Our result suggests that it may be more difficult to rule out non-fundamental equilibria in MRSE models than in the single regime case where the Taylor principle is known to guarantee local uniqueness.

Transparency, expectations, and forecasts

In 1994, the Federal Open Market Committee (FOMC) began to release statements after each meeting. This paper investigates whether the public’s views about the current path of the economy and of future policy have been affected by changes in the Federal Reserve’s communications policy as reflected in private sector’s forecasts of future economic conditions and policy moves. In particular, has the ability of private agents to predict where the economy is going improved since 1994? If so, on which dimensions has the ability to forecast improved? We find evidence that the individuals’ forecasts have been more synchronized since 1994, implying the possible effects of the FOMC’s transparency. On the other hand, we find little evidence that the common forecast errors, which are the driving force of overall forecast errors, have become smaller since 1994.

Methods for inference in large multiple-equation Markov-switching models

The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of free parameters in the transition matrix to grow as the square of the number of states but also without losing a convenient form for the posterior distribution of the transition matrix. Calculation of marginal data densities for assessing model fit is often difficult in high-dimensional models and seems particularly difficult in these models. This paper gives a detailed explanation of methods we have found to work to overcome these difficulties. It also makes suggestions for maximizing posterior density and initiating Markov chain Monte Carlo simulations that provide some robustness against the complex shape of the likelihood in these models. These difficulties and remedies are likely to be useful generally for Bayesian inference in large time-series models. The paper includes some discussion of model specification issues that apply particularly to structural vector autoregressions with a Markov-switching structure

Understanding the New Keynesian model when monetary policy switches regimes

This paper studies a New Keynesian model in which monetary policy may switch between regimes. We derive sufficient conditions for indeterminacy that are easy to implement and we show that the necessary and sufficient condition for determinacy, provided by Davig and Leeper, is necessary but not sufficient. More importantly, we use a two-regime model to show that indeterminacy in a passive regime may spill over to an active regime no matter how active the latter regime is. As a result, a passive monetary policy is more damaging than has been previously thought. Our results imply that the propagation of shocks in an active regime, such as that of the Federal Reserve in the post-1982 period, may be substantially affected by the possibility of a return to a passive regime of the kind that was followed in the 1960s and 1970s

An Activity-Based Nanosensor for Traumatic Brain Injury.

Currently, traumatic brain injury (TBI) is detected by medical imaging; however, medical imaging requires expensive capital equipment, is time- and resource-intensive, and is poor at predicting patient prognosis. To date, direct measurement of elevated protease activity has yet to be utilized to detect TBI. In this work, we engineered an activity-based nanosensor for TBI (TBI-ABN) that responds to increased protease activity initiated after brain injury. We establish that a calcium-sensitive protease, calpain-1, is active in the injured brain hours within injury. We then optimize the molecular weight of a nanoscale polymeric carrier to infiltrate into the injured brain tissue with minimal renal filtration. A calpain-1 substrate that generates a fluorescent signal upon cleavage was attached to this nanoscale polymeric carrier to generate an engineered TBI-ABN. When applied intravenously to a mouse model of TBI, our engineered sensor is observed to locally activate in the injured brain tissue. This TBI-ABN is the first demonstration of a sensor that responds to protease activity to detect TBI

Comparison of automated nucleic acid extraction methods for the detection of cytomegalovirus DNA in fluids and tissues

Testing for cytomegalovirus (CMV) DNA is increasingly being used for specimen types other than plasma or whole blood. However, few studies have investigated the performance of different nucleic acid extraction protocols in such specimens. In this study, CMV extraction using the Cell-free 1000 and Pathogen Complex 400 protocols on the QIAsymphony Sample Processing (SP) system were compared using bronchoalveolar lavage fluid (BAL), tissue samples, and urine. The QIAsymphonyAssay Set-up (AS) system was used to assemble reactions using artus CMV PCR reagents and amplification was carried out on the Rotor-Gene Q. Samples from 93 patients previously tested for CMV DNA and negative samples spiked with CMV AD-169 were used to evaluate assay performance. The Pathogen Complex 400 protocol yielded the following results: BAL, sensitivity 100% (33/33), specificity 87% (20/23); tissue, sensitivity 100% (25/25), specificity 100% (20/20); urine, sensitivity 100% (21/21), specificity 100% (20/20). Cell-free 1000 extraction gave comparable results for BAL and tissue, however, for urine, the sensitivity was 86% (18/21) and specimen quantitation was inaccurate. Comparative studies of different extraction protocols and DNA detection methods in body fluids and tissues are needed, as assays optimized for blood or plasma will not necessarily perform well on other specimen types

PROFITABILITY OF ESTABLISHING BASIN WILDRYE FOR WINTER GRAZING

This study examined the economic viability of establishing basin wildrye for winter grazing. Mixed integer-programming models were developed that minimized cow feed costs. Estimated basin wildrye establishment costs were $154 per acre. Break-even basin wildrye yields were approximately 2.6 and 2.3 AUMs/acre for March and May calving scenarios, respectively.Livestock Production/Industries,

OPTIMAL FEED COST STRATEGIES ASSOCIATED WITH EARLY AND LATE CALVING SEASONS

Integer programming models were used to examine optimal monthly feeding strategies and costs for March and May calving alternatives. Body condition scores were allowed to fluctuate throughout the year except for calving and breeding periods. The May calving strategy decreased annual feeding costs by $20 per cow.Livestock Production/Industries, Research Methods/ Statistical Methods,