20,137 research outputs found

    Can a simple DSGE model outperform Professional Forecasters?

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    DSGE models have recently become one of the most frequently used tools in policy analysis. Nevertheless, their forecasting proprieties are still unexplored. In this article we address this problem by examining the quality of forecasts from a small size DSGE model, a trivariate VAR model and the Philadelphia Fed Survey of Professional Forecasters. The forecast performance of these methods is analysed for the key U.S. economic variables: the three month Treasury bill yield, the GDP growth rate and the GDP price index inflation. We evaluate the ex post forecast errors on the basis of the data from the period of 1994–2006. We apply the Philadelphia Fed “Real-Time Data Set for Macroeconomists,” described by Croushore and Stark (2001a), to ensure that the information available to the SPF was exactly the same as the data used to estimate the DSGE and VAR models. Overall, the results are mixed. It appears that when comparing the root mean squared errors for some forecast horizons the DSGE model seems to outperform the SPF in forecasting the GDP growth rate. However, this characteristic turned out to be not statistically significant. In principle most forecasts of the GDP price index inflation and the short term interest rate by the SPF are significantly better than those from the DSGE model. The forecast quality of the VAR model turned out to be the worst one.forecasting, real-time data, Survey of Professional Forecasters, DSGE, VAR

    Synchronization of multihop wireless sensor networks at the application layer

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    Time synchronization is a key issue in wireless sensor networks; timestamping collected data, tasks scheduling, and efficient communications are just some applications. From all the existing techniques to achieve synchronization, those based on precisely time-stamping sync messages are the most accurate. However, working with standard protocols such as Bluetooth or ZigBee usually prevents the user from accessing lower layers and consequently reduces accuracy. A receiver-to-receiver schema improves timestamping performance because it eliminates the largest non-deterministic error at the sender’s side: the medium access time. Nevertheless, utilization of existing methods in multihop networks is not feasible since the amount of extra traffic required is excessive. In this article, we present a method that allows accurate synchronization of large multihop networks, working at the application layer while keeping the message exchange to a minimum. Through an extensive experimental study, we evaluate the protocol’s performance and discuss the factors that influence synchronization accuracy the most.Ministerio de Ciencia y Tecnología TIN2006-15617-C0

    Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

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    Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

    Ultrasonic Doppler measurement of renal artery blood flow

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    An extensive evaluation of the practical and theoretical limitations encountered in the use of totally implantable CW Doppler flowmeters is provided. Theoretical analyses, computer models, in-vitro and in-vivo calibration studies describe the sources and magnitudes of potential errors in the measurement of blood flow through the renal artery, as well as larger vessels in the circulatory system. The evaluation of new flowmeter/transducer systems and their use in physiological investigations is reported

    Snapshots of the EYES project

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    The EYES project (IST-2001-34734) is a three years European research project on self-organizing and collaborative energy-efficient sensor networks. It addresses the convergence of distributed information processing, wireless communications, and mobile computing. The goal of the project is to develop the architecture and the technology which enables the creation of a new generation of sensors that can effectively network together so as to provide a flexible platform for the support of a large variety of mobile sensor network applications. This paper provides a broad overview of the EYES project and highlights some approaches and results of the architecture

    Why we measure period fertility

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    Four reasons for measuring period fertility are distinguished: to explain fertility time trends, to anticipate future fertility, to construct theoretical models and to communicate with non-specialist audiences. The paper argues that not all measures are suitable for each purpose, and that tempo adjustment may be appropriate for some objectives but not others. In particular, it is argued that genuine timing effects do not bias or distort measures of period fertility as dependent variable. Several different concepts of bias or distortion are identified in relation to period fertility measures. Synthetic cohort indicators are a source of confusion since they conflate measurement and forecasting. Anticipating future fertility is more akin to forecasting than to measurement. Greater clarity about concepts and measures in the fertility arena could be achieved by a stronger emphasis on validation. Period incidence and occurrence-exposure rates have a straightforward interpretation. More complex period fertility measures are meaningful only if a direct or indirect criterion can be specified against which to evaluate them. Their performance against that criterion is what establishes them as valid or useful

    Large Angle Satellite Attitude Maneuvers

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    Two methods are proposed for performing large angle reorientation maneuvers. The first method is based upon Euler's rotation theorem; an arbitrary reorientation is ideally accomplished by rotating the spacecraft about a line which is fixed in both the body and in space. This scheme has been found to be best suited for the case in which the initial and desired attitude states have small angular velocities. The second scheme is more general in that a general class of transition trajectories is introduced which, in principle, allows transfer between arbitrary orientation and angular velocity states. The method generates transition maneuvers in which the uncontrolled (free) initial and final states are matched in orientation and angular velocity. The forced transition trajectory is obtained by using a weighted average of the unforced forward integration of the initial state and the unforced backward integration of the desired state. The current effort is centered around practical validation of this second class of maneuvers. Of particular concern is enforcement of given control system constraints and methods for suboptimization by proper selection of maneuver initiation and termination times. Analogous reorientation strategies which force smooth transition in angular momentum and/or rotational energy are under consideration

    Simple Estimators for Binary Choice Models with Endogenous Regressors

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    This paper provides simple estimators for binary choice models with endogenous or mismeasured regressors. Unlike control function methods, which are generally only valid when endogenous regressors are continuous, the estimators proposed here can be used with limited, censored, continuous, or discrete endogenous regressors, and they also allow for latent errors having heteroskedasticity of unknown form, including random coefficients. The variants of special regressor based estimators we provide are numerically trivial to implement. We illustrate these methods with an empirical application estimating migration probabilities within the US.Binary choice; Binomial response; Endogeneity; Measurement error; Heteroskedasticity; Discrete endogenous regressor; Censored regressor; Random coefficients; Identification; Latent variable model
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