Search results for "Econometria"

Regression with Imputed Covariates: A Generalized Missing Indicator Approach

2011

A common problem in applied regression analysis is that covariate values may be missing for some observations but imputed values may be available. This situation generates a trade-off between bias and precision: the complete cases are often disarmingly few, but replacing the missing observations with the imputed values to gain precision may lead to bias. In this paper we formalize this trade-off by showing that one can augment the regression model with a set of auxiliary variables so as to obtain, under weak assumptions about the imputations, the same unbiased estimator of the parameters of interest as complete-case analysis. Given this augmented model, the bias-precision trade-off may then…

Introduction - The "Rivista Internazionale di Scienze Sociali" in the Post-war Years (1945-1960)

2014

Testing for public debt sustainability using a time-scale decomposition analysis

2013

In this paper we estimate the response of primary surplus to lagged debt to test for debt sustainability within the 17 EMU countries by using a factor model. The analysis is split into two stages. In the first stage we retrieve the cyclical and long-run components of primary surplus and debt ratios of each EMU country using a wavelet decomposition for each fiscal covariate, based on the Maximal Overlapping Discrete Wavelet Transform. In the second stage, we use Full Information Maximum Likelihood for a factor decomposition of thecross covariance matrix of the wavelet coefficients of primary deficit and debt to GDP ratios in order to measure the short run and the long run reaction of the pri…

ESSAYS ON FINANCIAL STRESS: A MIXED FREQUENCY DATA ANALYSIS

Wavelet analysis of financial contagion

2011

The aim is to estimate a factor model fitted to financial returns to disentagle the role played by common shock and idiosincratic shocks in shaping the comovement between asset returns during periods of calm and financial turbulence. For this purpose, we use wavelet analysis and, in particular, the Maximum Overlapping Discrete Wavelet Transform, to decompose the covariance matrix of the asset returns on a scale by scale basis, where each scale is associated to a given frequency range. This decomposition will give enough moment conditions to identify the role played by common and idiosincratic shocks. A Montecarlo simulation experiment shows that our testing methodology has good size and power …

Testing for contagion: a time-scale decomposition

2011

The aim of the paper is to test for financial contagion by estimating a simultaneous equation model subject to structural breaks. For this purpose, we use the Maximum Overlapping Discrete Wavelet Transform, MODWT, to decompose four asset returns into different scale components (each associated with a given frequency range). The decomposition will enable us to obtain the moment conditions necessary to (over)identify a structural form model with a single dummy and the one with multiple dummies capturing shifts in the co-movement of asset returns occurring during periods of financial turmoil. A Montecarlo simulation exercise shows that test based on a single dummy structural form model has goo…

Volatility co-movements: a time scale decomposition analysis

2013

In this paper we investigate short-run co-movements before and after the Lehman Brothers’ collapse among the volatility series of US and a number of European countries. The series under investigation (implied and realized volatility) exhibit long-memory and, in order to avoid missspecification errors related to the parameterization of a long memory multivariate model, we rely on wavelet analysis. More specifically, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and we apply Maximum Likelihood for a factor decomposition of the short-run covariance matrix. The empirical evidence…

Volatility co-movements: a time scale decomposition analysis

2014

In this paper we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers’ collapse. The analysis, based on a factor decomposition of the covariance matrix of implied and realized volatilities, is carried for different sub-samples (identified as normal and crisis periods) and across different (high) frequency bands. In particular, the analysis is split in two stages. In the first stage, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and, in a second stage, we apply Maximum Likelihood for a factor de…

SAMPLING DESIGN IN SHARE WAVE 7

2019

This chapter documents the sampling design adopted in SHARE. Starting with a definition of the SHARE target population, we describe the protocol that is followed to harmonise and document the sampling procedure and present the sampling frames used by the countries that recruited a baseline or refreshment sample in Wave 7. We then discuss some important aspects of the SHARE sampling design, such as stratification, clustering, variation in selection probabilities and sample composition. Finally, we provide additional information about the sampling variables included in the released SHARE dataset.

Sample design and weighting strategies in SHARE Wave 5

2015

This chapter provides a description of the sampling design and weighting strategies adopted in the fifth wave of SHARE. We begin by defining the target population that SHARE aims to represent. Next, we describe the sampling design focusing on the basic principles guiding the construction of the SHARE sample, the role played by sampling frames for coverage of the target population, and other important aspects of sampling - such as stratification, clustering and variation in selection probabilities - that affect the efficiency of sample-based inference. The chapter concludes with a description of the weighting strategies adopted by SHARE to handle problems of unit nonresponse in the baseline …