Suchergebnisse

We use real-time annual data on the fiscal balance, government current spending, current revenues and net capital outlays as published at a half yearly frequency in the OECD Economic Outlook for 25 OECD countries. For each fiscal year t we have a number of forecasts, a first release, and subsequent revisions. It turns out that revisions in the fiscal balance data are not affected by elections. However, we do find that governments spend more than reported before an election which provides support for moral-hazard type of political budget cycle (PBC) models: through hidden efforts the incumbent tries to enhance his perceived competence. We also find that governments had higher current receipts than reported before an election, which is in line with adverse-selection type of PBC models in which incumbents signal competence through expansionary fiscal policy before the elections.

We start from the assertion that a useful monetary policy design should be founded on more realistic assumptions about what policymakers can know at the time when policy decisions have to be made. Since the Taylor rule - if used as an operational device - implies a forward looking behaviour, we analyze the reliability of the input information. We investigate the forecasting performance of OECD projections for GDP growth rates and inflation. We diagnose a much better forecasting record for inflation rates compared to GDP growth rates, which for most countries are almost uninformative at the time a Taylor rule should sensibly be applied. Using this data set, we find significant differences between Taylor rules estimated over revised data compared to real-time data. There is evidence that monetary policy seems to react more actively in real time than rules estimated over revised data suggest. Given the evidence of systematic errors in OECD forecasts, in a next step we attempt to correct for these forecast biases and check to which extent this can lower the errors in interest rate policy setting. An ex-ante simulation for the years 1991 to 2001 supports the proposal that correcting for forecast errors and biases based on an error model can lower the resulting policy error in interest rate setting for most countries under consideration. In addition we investigate to what extent structural changes in the policy reaction behaviour can be handled with moving instead of expanding samples. Our results point out that the information set available needs a careful examination when applied to instrument rules like those of the Taylor type. Limited forecast quality and significant data revisions recommend a more sophisticated handling of the dated information, for which we present an operational procedure that has the potential of reducing the risk of severe policy errors.

This paper surveys the empirical research on fiscal policy analysis based on real-time data. This literature can be broadly divided in three groups that focus on: (1) the statistical properties of revisions in fiscal data; (2) the political and institutional determinants of projection errors by governments and (3) the reaction of fiscal policies to the business cycle. It emerges that, first, fiscal data revisions are large and initial releases are biased estimates of final values. Second, the presence of strong fiscal rules and institutions leads to relatively more accurate releases of fiscal data and small deviations of fiscal outcomes from government plans. Third, the cyclical stance of fiscal policies is estimated to be more 'counter-cyclical' when real-time data are used instead of ex-post data. Finally, more work is needed for the development of real-time datasets for fiscal policy analysis. In particular, a comprehensive real-time dataset including fiscal variables for industrialized (and possibly developing) countries, published and maintained by central banks or other institutions, is still missing.

International audience ; Accidents of pedestrians sometimes take lives, in Bucara-manga since 2012 pedestrian died by accidents are 179, and 2873 hurt, In a city as Bucaramanga, this means each day at least one pedestrian is involved in a accident. Therefore is necessary to know the causes of accidents in the way to decrease the accidents. One of many reasons to know the causes is with system dynamics, simulating the events of the Pedestrian behavior when accidents occur in risen cities. The implementation simulation joint with technology and research looking for saving lives, reducing the accidental rate, and to implementing or suggesting new policies from the government. This project is looking for the implementation of technology in video records and Deep Learning analysis for the service of the citizens, where a simulation model will be revealing the main variables which intervene in the pedestrian's behavior. As initials results, shows the methodology here implemented, can reach data which was insufficient before thanks to the cameras and software of objects detection , those are the data input for the simulation model, which after to implement a change in a particular spot of Bucaramanga is possible decrease the accident rate in 80% where pedestrians could be involved.

International audience ; Accidents of pedestrians sometimes take lives, in Bucara-manga since 2012 pedestrian died by accidents are 179, and 2873 hurt, In a city as Bucaramanga, this means each day at least one pedestrian is involved in a accident. Therefore is necessary to know the causes of accidents in the way to decrease the accidents. One of many reasons to know the causes is with system dynamics, simulating the events of the Pedestrian behavior when accidents occur in risen cities. The implementation simulation joint with technology and research looking for saving lives, reducing the accidental rate, and to implementing or suggesting new policies from the government. This project is looking for the implementation of technology in video records and Deep Learning analysis for the service of the citizens, where a simulation model will be revealing the main variables which intervene in the pedestrian's behavior. As initials results, shows the methodology here implemented, can reach data which was insufficient before thanks to the cameras and software of objects detection , those are the data input for the simulation model, which after to implement a change in a particular spot of Bucaramanga is possible decrease the accident rate in 80% where pedestrians could be involved.

Supply chains play today a crucial role in the success of a company's logistics. In the last years, multiple investigations focus on incorporating new technologies to the supply chains, being Internet of Things (IoT) and blockchain two of the most recent and popular technologies applied. However, their usage has currently considerable challenges, such as transactions performance, scalability, and near real-time contract verification. In this paper we propose a model for continuous verification of contracts in supply chains using the benefits of blockchain technology and real-time data acquisition from IoT devices for early decision-making. We propose two platform independent optimization techniques (atomic transactions and grouped validation) that enhances data transactions protocol and the data storage procedure and a method for continuous verification of contracts, which allows to take corrective actions to reduce ¿ ; This work has been partially supported by the project "CABAHLA-CM: Convergencia Big data-Hpc: de los sensores a las Aplicaciones" S2018/TCS-4423 from Madrid Regional Government and by the Spanish Ministry of Science and Innovation Project "New Data Intensive Computing Methods for High-End and Edge Computing Platforms (DECIDE)". Ref. PID2019-107858GB-I00.