45 resultados para Smart Panel


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We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.

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This paper examines factors explaining subcontracting decisions in the construction industry. Rather than the more common cross-sectional analyses, we use panel data to evaluate the influence of all relevant variables. We design and use a new index of the closeness to small numbers situations to estimate the extent of hold-up problems. Results show that as specificity grows, firms tend to subcontract less. The opposite happens when output heterogeneity and the use of intangible assets and capabilities increase. Neither temporary shortage of capacity nor geographical dispersion of activities seem to affect the extent of subcontracting. Finally, proxies for uncertainty do not show any clear effect.

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This paper demonstrates that, unlike what the conventional wisdom says, measurement error biases in panel data estimation of convergence using OLS with fixed effects are huge, not trivial. It does so by way of the "skipping estimation"': taking data from every m years of the sample (where m is an integer greater than or equal to 2), as opposed to every single year. It is shown that the estimated speed of convergence from the OLS with fixed effects is biased upwards by as much as 7 to 15%.

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Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

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This paper tests hysteresis effects in unemployment using panel data for 19 OECD countries covering the period 1956-2001. The tests exploit the cross-section variations of the series, and additionally, allow for a diferent number of endogenous breakpoints in the unemployment series. The critical values are simulated based on our specific panel sizes and time periods. The findings stress the importance of accounting for exogenous shocks in the series and give support to the natural-rate hypothesis of unemployment for the majority of the countries analyzed

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The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

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This paper tests for real interest parity (RIRP) among the nineteen major OECD countries over the period 1978:Q2-1998:Q4. The econometric methods applied consist of combining the use of several unit root or stationarity tests designed for panels valid under cross-section dependence and presence of multiple structural breaks. Our results strongly support the fulfilment of the weak version of the RIRP for the studied period once dependence and structural breaks are accounted for.

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The advances of the semiconductor industry enable microelectromechanical systems sensors, signal conditioning logic and network access to be integrated into a smart sensor node. In this framework, a mixed-mode interface circuit for monolithically integrated gas sensor arrays was developed with high-level design techniques. This interface system includes analog electronics for inspection of up to four sensor arrays and digital logic for smart control and data communication. Although different design methodologies were used in the conception of the complete circuit, high-level synthesis tools and methodologies were crucial in speeding up the whole design cycle, enhancing reusability for future applications and producing a flexible and robust component.

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The aim of this brief is to present an original design methodology that permits implementing latch-up-free smart power circuits on a very simple, cost-effective technology. The basic concept used for this purpose is letting float the wells of the MOS transistors most susceptible to initiate latch-up.

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This paper tests hysteresis effects in unemployment using panel data for 19 OECD countries covering the period 1956-2001. The tests exploit the cross-section variations of the series, and additionally, allow for a diferent number of endogenous breakpoints in the unemployment series. The critical values are simulated based on our specific panel sizes and time periods. The findings stress the importance of accounting for exogenous shocks in the series and give support to the natural-rate hypothesis of unemployment for the majority of the countries analyzed

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The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

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This paper tests for real interest parity (RIRP) among the nineteen major OECD countries over the period 1978:Q2-1998:Q4. The econometric methods applied consist of combining the use of several unit root or stationarity tests designed for panels valid under cross-section dependence and presence of multiple structural breaks. Our results strongly support the fulfilment of the weak version of the RIRP for the studied period once dependence and structural breaks are accounted for.

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Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

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Abordamos el Informe del Grupo de Alto Nivel sobre la Coherencia en todo el Sistema de las Naciones Unidas («Informe del Grupo») y el proceso de reforma de las Naciones Unidas del que forma parte como grupos de la sociedad civil que tienen una larga experiencia por lo que se refiere a propugnar reformas del sistema de las Naciones Unidas.

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The application of adaptive antenna techniques to fixed-architecture base stations has been shown to offer wide-ranging benefits, including interference rejection capabilities or increased coverage and spectral efficiency.Unfortunately, the actual implementation ofthese techniques to mobile communication scenarios has traditionally been set back by two fundamental reasons. On one hand, the lack of flexibility of current transceiver architectures does not allow for the introduction of advanced add-on functionalities. On the other hand, theoften oversimplified models for the spatiotemporal characteristics of the radio communications channel generally give rise toperformance predictions that are, in practice, too optimistic. The advent of software radio architectures represents a big step toward theintroduction of advanced receive/transmitcapabilities. Thanks to their inherent flexibilityand robustness, software radio architecturesare the appropriate enabling technology for theimplementation of array processing techniques.Moreover, given the exponential progression ofcommunication standards in coexistence andtheir constant evolution, software reconfigurabilitywill probably soon become the only costefficientalternative for the transceiverupgrade. This article analyzes the requirementsfor the introduction of software radio techniquesand array processing architectures inmultistandard scenarios. It basically summarizesthe conclusions and results obtained withinthe ACTS project SUNBEAM,1 proposingalgorithms and analyzing the feasibility ofimplementation of innovative and softwarereconfigurablearray processing architectures inmultistandard settings.