Search results for "C51"
showing 10 items of 13 documents
Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis
2009
Abstract In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events affecting a number of East Asian countries during the 1997–1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performance.
The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?
2002
International audience; The authors show that spatial dependence and spatial heterogeneity matter in the estimation of the ß-convergence process among 138 European regions over the 1980 to 1995 period. Using spatial econometrics tools, the authors detect both spatial dependence and spatial heterogeneity in the form of structural instability across spatial convergence clubs. The estimation of the appropriate spatial regimes spatial error model shows that the convergence process is different across regimes. The authors also estimate a strongly significant spatial spillover effect: the average growth rate of per capita GDP of a given region is positively affected by the average growth rate of …
Hétérogénéité spatiale : principes et méthodes
2004
Spatial Heterogeneity : Principles and Methods This article has a dual purpose . First , it describes the main econometric specifications which can be used to represent spatial heterogeneity , reflected in an instability of parameters in space and / or a heteroscedasticity of error terms . Only the specifications valid in cross-section are examined . Second , it explains the links between spatial heterogeneity and autocorrelation , the other major feature of localised data , defined by the absence of independence between geographical observations . In particular , we look at the extent to which traditional tests of heteroscedasticity or instability need to be amended to take account of spat…
Faktoru modeļu priekšrocības ekonomiskās aktivitātes īstermiņa prognozēšanā
2014
Promocijas darba anotācija Pēdējā desmitgadē Latvijas tautsaimniecības attīstība bijusi īpaši svārstīga, kas sarežģīja ekonomiskās politikas lēmumu pieņemšanu ekonomiskās situācijas stabilizēšanai. Lai atvieglotu lēmumu pieņemšanu, ekonomisko aktivitāti īstermiņā var prognozēt ar ekonometriskiem modeļiem. Promocijas darba mērķis ir novērtēt faktoru modeļu priekšrocības ekonomiskās aktivitātes prognozēšanas kontekstā un noteikt Latvijas gadījumā nepieciešamo instrumentu un metožu klāstu īstermiņa prognozēšanai. Promocijas darbā tiek sniegtas atbildes uz faktoru modeļu lietošanas problēmjautājumiem īstermiņa prognozēšanā, kā arī novērtēti daži faktoru modeļu lietošanas aspekti. Faktoru modeļu…
Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options
2010
Weather derivatives have become very popular tools in weather risk management in recent years. One of the elements supporting their diffusion has been the increase in volatility observed on many energy markets. Among the several available contracts, Quanto options are now becoming very popular for a simple reason: they take into account the strong correlation between energy consumption and certain weather conditions, so enabling price and weather risk to be controlled at the same time. These products are more efficient and, in many cases, significantly cheaper than simpler plain vanilla options. Unfortunately, the specific features of energy and weather time series do not enable the use of …
Weak versus strong dominance of shrinkage estimators
2021
We consider the estimation of the mean of a multivariate normal distribution with known variance. Most studies consider the risk of competing estimators, that is the trace of the mean squared error matrix. In contrast we consider the whole mean squared error matrix, in particular its eigenvalues. We prove that there are only two distinct eigenvalues and apply our findings to the James–Stein and the Thompson class of estimators. It turns out that the famous Stein paradox is no longer a paradox when we consider the whole mean squared error matrix rather than only its trace.
Spain in the euro: a general equilibrium analysis
2010
Bayesian dynamic stochastic general equilibrium (DSGE) models combine microeconomic behavioural foundations with a full-system Bayesian likelihood estimation approach using key macro-economic variables. Because of the usefulness of this class ofmodels for addressing questions regarding the impact and consequences of alternative monetary policies they are nowadays widely used for forecasting and policy analysis at central banks and other institutions. In this paper we provide a brief description of the two main aggregate euro area models at the ECB. Both models share a common core but their detailed specification differs reflecting their specific focus and use. The New Area Wide Model (NAWM)…
Estimation des effets de proximité dans le processus de convergence régionale : une approche par l'économétrie spatiale sur 92 régions européennes (1…
2002
L'objectif de cet article est d'examiner les conséquences de la dépendance spatiale sur la croissance régionale et le processus de convergence. Sur un échantillon de 92 régions européennes sur la période 1980-1995, nous montrons que le modèle de b-convergence absolue doit être re-spécifié en raison de la présence d'auto-corrélation spatiale. Les méthodes de l'économétrie spatiale nous orientent vers une spécification avec erreurs spatialement auto-corrélées qui nous permet de mettre en évidence un effet de débordement géographique. Nous montrons ainsi que le taux de croissance d'une région est influencé positivement par les taux de croissance des régions contiguës.
On the Ambiguous Consequences of Omitting Variables
2015
This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.
Clubs de convergence et effets de débordements géographiques : une analyse spatiale sur données régionales européennes, 1980-1995
2007
Our article offers an econometric model of spatial interactions for the empirical analysis of growth in European regions over the period 1980-1995. The model detects spatial spillover effects and makes it possible to take account of the European economy’s strong polarization. More specifically, by factoring in both spatial autocorrelation and spatial heterogeneity, we characterize the economic polarization pattern in European regions, identify convergence clubs, and model them as spatial regimes. We estimate a two-regime model with spatially autocorrelated errors and show that the convergence process differs between the two regimes. We find a strongly significant spatial spillover effect : …