169,822 research outputs found
New proposals for the quantification of qualitative survey data
No full textHASH(0x1009bfd18)spectral envelope , non‐Gaussian state space models , cumulative logit model ,
Revisions in official data and forecasting
No full textThis paper deals with the topic of revisions in macroeconomic Italian data with the aim of investigating whether consecutive vintages published by the National Statistical Institute contain useful information for economic analysis and forecasting. The rationality of the revisions process is tested considering the complete history of data and an application to show the usefulness of revisions for improving the precision of forecasts is proposed. The results on Italian GDP show that embedding the revision process in a dynamic factor model helps to reduce the forecast error in the short term
New proposals for the quantification of qualitative survey data
No full textIn this paper we deal with several issues related to the quantification of business
surveys. In particular, we propose and compare new ways of scoring the ordinal
responses concerning the qualitative assessment of the state of the economy, such
as the spectral envelope and cumulative logit unobserved components models, and
investigate the nature of seasonality in the series. We conclude with an evaluation of
the type of business cycle fluctuations that is captured by the qualitative surveys
Survey data as coincident or leading indicators
No full textIn this paper we propose a monthly measure for the euro area gross domestic product (GDP) based on a small-scale factor model for mixed-frequency data, featuring two factors: the first is driven by hard data, whereas the second captures the contribution of survey variables as coincident indicators. Within this framework we evaluate both the in-sample contribution of the second survey-based factor, and the short-term forecasting performance of the model in a pseudo-real-time experiment. We find that the survey-based factor plays a significant role for two components of GDP: industrial value added and exports. Moreover, the two-factor model outperforms in terms of out-of-sample forecasting accuracy the traditional autoregressive distributed lags (ADL) specifications and the single-factor model, with few exceptions. Copyright © 2009 John Wiley & Sons, Ltd.
EUROMIND: A monthly indicator of the euro area economic conditions
No full textContinuous monitoring of the evolution of the economy is fundamental for the decisions of public and private decision makers. The paper proposes EUROMIND, which is a new monthly indicator of the euro area economic conditions, based on tracking real gross domestic product monthly, relying on information provided in the Eurostat Euro-IND database. EUROMIND has several original economic and statistical features. First, it considers both the output and the expenditure sides of the economy, as it provides a monthly estimate of the value added of the six branches of economic activity and of the main gross domestic product components by type of expenditure (final consumption, gross capital formation and net exports), and combines the estimates with optimal weights reflecting their relative precision. Second, the indicator is based on information at both the monthly and the quarterly level, modelled with a dynamic factor specification cast in state space form. Third, since estimation of the multivariate dynamic factor model with mixed frequency data can be numerically complex, computational efficiency is achieved by implementing univariate filtering and smoothing procedures. Finally, special attention is paid to chain linking and its implications, via a multistep procedure that exploits the additivity of the volume measures expressed at the prices of the previous year
EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries
No full textThe paper deals with the estimation of monthly indicators of economic activity for the Euro area and
its largest member countries that possess the following attributes: relevance, representativeness and
timeliness. Relevance is determined by comparing our monthly indicators to the gross domestic product
at chained volumes, as the most important measure of the level of economic activity. Representativeness
is achieved by considering a very large number of (timely) time series of monthly indicators relating to
the level of economic activity, providing a more or less complete coverage. The indicators are modelled
using a large-scale parametric factor model. We discuss its specification and provide details of the
statistical treatment. Computational efficiency is crucial for the estimation of large-scale parametric
factor models of the dimension used in our application (considering about 170 series). To achieve it,
we apply state-of-the-art state space methods that can handle temporal aggregation, and any pattern of
missing values
A Systemic Approach to Estimating the Output Gap for the Italian Economy
No full textEstimating potential output and the corresponding output gap plays a key role, not only for inflation forecasting and the assessment of the economic cycle, but also for the fiscal governance of the European Union (EU). Potential output is, however, an unobservable and extremely uncertain variable. Empirical measurements differ considerably depending on the econometric approach adopted, the specification of the data generating process and the dataset used. The method adopted at the EU level, which was agreed within the Output Gap Working Group, has been subject to considerable debate. The fiscal councils of the various Member States contribute to the discussion over the output gap modelling. This paper aims at estimating the potential output of the Italian economy, using a combination of five different models proposed by the relevant literature. More specifically, in addition to a statistical filter, we use unobserved components models based on the Phillips curve, the Okun law and the production function. The approach adopted allows to reconcile the parsimony of the econometric specification with the economic interpretation of the results. Estimates of the output gap obtained with the five selected models present important properties: low pro-cyclicity, stability with respect to the preliminary data and consistency with the economic theory. The use of multiple models also enables the construction of confidence bands for the output gap estimates, which are helpful for policy analysis. In the empirical application for Italy, estimates and forecasts of the output gap recently produced by relevant organisations tend to fall within the confidence interval calculated on the basis of the five selected models
Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?
No full textThis paper explores the potential of Business Survey data for the estimation and disaggregation of macroeconomic variables at higher frequency. We propose a multivariate approach which is an extension of the Stock and Watson (1991) dynamic factor model, considering more than one common factor and low-frequency cycles. The multivariate model is cast in State Space Form and the temporal aggregation constraint is converted into a problem of missing values. An application in real time for the value added of the Industry sector in the Euro area is presented.Temporal Disaggregation. Multivariate State Space Models. Dynamic factor
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Mitomycin C in highly myopic eyes - Author reply
No full textOphthalmology. 2005 Feb;112(2):208-18; discussion 219.
Mitomycin C modulation of corneal wound healing after photorefractive keratectomy in highly myopic eyes.
Gambato C, Ghirlando A, Moretto E, Busato F, Midena E.
SourceRefractive Surgery Service and Antimetabolite Therapy Research Unit, Department of Ophthalmology, University of Padova, Padova, Italy.
Abstract
PURPOSE: To evaluate the role of topical mitomycin C in corneal wound healing (CWH) after photorefractive keratectomy (PRK) in highly myopic eyes.
DESIGN: Prospective, double-masked, randomized clinical trial.
PARTICIPANTS: Seventy-two eyes of 36 patients affected by high (>7 diopters) myopia.
METHODS: In each patient, one eye was randomly assigned to PRK with intraoperative topical 0.02% mitomycin C application, and the fellow eye was treated with a placebo. Postoperatively, mitomycin C-treated eyes received artificial tears (3 times daily, tapered in 3 months), whereas the fellow eye was treated with fluorometholone sodium 2% and artificial tears (3 times daily, tapered in 3 months).
MAIN OUTCOME MEASURES: Uncorrected visual acuity (UCVA) and best-corrected visual acuity (BCVA), contrast sensitivity, manifest refraction, and biomicroscopy. Contrast sensitivity was determined using the Pelli-Robson chart. Corneal confocal microscopy documented CWH.
RESULTS: Mean follow-up was 18 months (range, 12-36). No side effects or toxic effects were documented. At 12-month follow-up examination, UCVAs (logarithm of the minimum angle of resolution) were 0.4+/-0.48 and 0.5+/-0.53 (P = .03) in mitomycin C-treated eyes and corticosteroid-treated eyes, respectively. At 1 year, corneal haze developed in 20% of corticosteroid-treated eyes, versus 0% of mitomycin C-treated eyes. At 12, 24, and 36 months, corneal confocal microscopy showed activated keratocytes and extracellular matrix significantly more evident in untreated eyes (Ps = 0.004, 0.024, and 0.046, respectively).
CONCLUSION: Topical intraoperative application of 0.02% mitomycin C can reduce haze formation in highly myopic eyes undergoing PRK.
Comment in
Ophthalmology. 2006 Feb;113(2):357; author reply 357-8
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