Suchergebnisse

We examine the efficiency of multivariate macroeconomic forecasts by estimating a vector autoregressive model on the forecast revisions of four variables (GDP, inflation, unemployment and wages). Using a data set of professional forecasts for the G7 countries, we find evidence of cross‐series revision dynamics. Specifically, forecasts revisions are conditionally correlated to the lagged forecast revisions of other macroeconomic variables, and the sign of the correlation is as predicted by conventional economic theory. This indicates that forecasters are slow to incorporate news across variables. We show that this finding can be explained by forecast underreaction.

The Workshop on the Economics of Information Security (WEIS) is the leading forum for interdisciplinary research and scholarship on information security and privacy, combining ideas, techniques, and expertise from the fields of economics, social science, business, law, policy, and computer science. In 2009, WEIS was held in London, at UCL, a constituent college of the University of London. "Economics of Information Security and Privacy" includes chapters presented at WEIS 2009, having been carefully reviewed by a program committee composed of leading researchers. Topics covered inclu

We develop and simulate a basic mathematical model of the costly deployment of software patches in the presence of trade-offs between confidentiality and availability. The model incorporates representations of the key aspects of the system architecture, the managers' preferences, and the stochastic nature of the threat environment. Using the model, we compute the optimal frequencies for regular and irregular patching, for both networks and clients, for two example types of organization, military and financial. Such examples are characterized by their constellations of parameters. Military organizations, being relatively less cost-sensitive, tend to apply network patches upon their arrival. The relatively high cost of applying irregular client patches leads both types of organization to avoid deployment upon arrival.

This paper uses scanner data to generate estimates of quality‐adjusted price changes for video‐recorders. We use hedonic regressions to derive estimates of the changing worth of each quality component. These are then applied to weighted changes in the mix of quality attributes of products to derive estimates of quality‐adjusted price (QAP) changes. The data source used is electronic‐point‐of‐sale (EPOS) scanner data that are available for a wide range of goods. This study provides an example of how such methods can be more widely applied. The estimates of QAP changes correspond to constant‐utility, (hedonic) cost‐of‐living indexes defined in economic theory as the ratio of expenditure functions at constant utility allowing for changing prices and characteristics of goods. This method is proposed as an improvement on the existing direct method, which takes its estimates directly from the coefficients associated with 'time dummies' in a hedonic regression. We finally undertake a matching process, akin to that used by statistical offices, and compare the results. Direct comparisons with RPI estimates and these hedonic approaches are not easy since the approaches use quite different data sets. Our replication of a procedure akin to that used for the RPI on the scanner data set provides insights into sources of potential bias.

This paper uses scanner data to generate estimates of quality-adjusted price changes for videocassette recorders. We use hedonic regressions to derive estimates of the changing worth of each quality component. These are then applied to weighted changes in the mix of quality attributes of products to derive estimates of quality-adjusted price (QAP) changes. The data source used is electronic-point-of-sale (EPOS) scanner data that are available for a wide range of goods. The estimates of QAP changes correspond to constant-utility, "hedonic" cost-of-living indexes defined in economic theory as the ratio of expenditure functions at constant utility allowing for changing prices & characteristics of goods. This method is proposed as an improvement on the existing direct method, which takes its estimates directly from the coefficients associated with "time dummies" in a hedonic regression. We finally undertake a matching process, akin to that used by statistical offices, & compare the results. Direct comparisons with RPI estimates & these hedonic approaches are not easy since the approaches use quite different data sets. Our replication of a procedure akin to that used for the RPI on the scanner data set provides insights into sources of potential bias. 5 Tables, 48 References. Adapted from the source document.