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Research
Publications:
“Measuring Synchronisation and Convergence of Business
Cycles” (with Koopman, S.J.),
Abstract: This paper investigates business
cycle relations among different economies in the Euro area. Cyclical dynamics
are explicitly modelled as part of a time series model. We introduce mechanisms
that allow for increasing or diminishing phase shifts and for time-varying
association patterns in different cycles. Standard Kalman
filter techniques are used to estimate the parameters simultaneously by maximum
likelihood. The empirical illustrations are based on gross domestic product
(GDP) series of seven European countries which are compared with the GDP series
of the Euro Area and that of the
“Tracking the Business Cycle of the Euro Area: a
Multivariate Model-based Band-pass Filter” (with Koopman,
S.J. and Rua, A.),
Journal of Business and Economic
Statistics, Vol. 24(3), July 2006,
pp.278-290
Abstract: This article proposes a multivariate bandpass
filter based on the trend plus cycle decomposition model. The underlying
multivariate dynamic factor model relies on specific formulations for trend and
cycle components and produces smooth business cycle indicators with bandpass filter properties. Furthermore, cycle shifts for
individual time series are incorporated as part of the multivariate model and
estimated simultaneously with the remaining parameters. The inclusion of
leading, coincident, and lagging variables for the measurement of the business
cycle is therefore possible without a prior analysis of lead–lag relationships
between economic variables. This method also permits the inclusion of time
series recorded with mixed frequencies. For example, quarterly and monthly time
series can be considered simultaneously without ad hoc interpolations. The
multivariate approach leads to a business cycle indicator that is less subject
to revisions than those produced by univariate
filters. The reduction of revisions is a key feature in real-time assessment of
the economy. Finally, the proposed method computes a growth indicator as a byproduct. The new approach of tracking business cycle and
growth indicators is illustrated in detail for the Euro area. The analysis is
based on nine key economic time series. (Link)
Working papers:
“A Multivariate Band-Pass Filter”, October 2007 (submitted)
Abstract: We develop a multivariate filter
which is an optimal (in the mean squared error sense) approximation to the ideal
filter that isolates a specified range of fluctuations in a time series, e.g.,
business cycle fluctuations in macroeconomic time series. This requires
knowledge of the true second-order moments of the data. Otherwise these can be
estimated and we show empirically that the method still leads to relevant
improvements of the extracted signal, especially in the endpoints of the
sample. Our filter is an extension of the univariate
filter developed by Christiano and Fitzgerald (2003).
Specifically, we allow an arbitrary number of covariates to be employed in the
estimation of the signal. We illustrate the application of the filter by
constructing a business cycle indicator for the
“Interpretation of the Effects of Filtering Integrated
Time Series”, September 2007 (submitted)
Abstract: We resort to a rigorous definition of
spectrum of an integrated time series in order to characterise the implications
of appying linear filters to such series. We conclude
that in the presence of integrated series the transfer function of the filters
has exactly the same interpretation as in the covariance stationary case,
contrary to what many authors suggest. This disagreement leads to different
conclusions regarding the link of the original fluctuations with the
transformed fluctuations in the time series data, embodied in various
unjustified criticisms to the application of detrending
filters. Despite this, and given the frequency domain characteristics of
filtered macroeconomic integrated series, we acknowledge that the choice of a
particular detrending filter is far from being a
neutral task. (PDF)
“Exact Limit of the Expected Periodogram
in the Unit-Root case”, September 2007 (submitted)
Abstract: We derive the limit of the expected periodogram in the unit-root case under general conditions.
This function is seen to be independent of time, thus sharing a fundamental
property with the stationary case equivalent. We discuss the consequences of
this result to the frequency domain interpretation of filtered integrated time
series. (PDF)
"Political Control and Monopolies in the Rise and
Fall of the First Portuguese Empire", March 2006 (under revision)
Abstract: We analyse the rise and fall of the
Portuguese commercial empire in Africa and in the Eastern World during the XV
and XVI centuries, taking into account two major forces shaping the evolution
of the events: The rent extraction mechanism used to maintain what was for a
long time a public enterprise and its role in the maintenance of political
control while favouring power centralisation. We interpret economic and social
tensions partly as a result of this institutional arrangement, and analyse the
policies used to alleviate those tensions. The causes for the rapid fall of the
empire seem to emerge clearly.
"Cycle Co-movement Within the
European Union in the Period 1960-1999. A Frequency Domain Approach", Working paper no. 5-2002, Banco de
Portugal (PDF)
Work in Progress:
"Retraining and Unemployment in
Turbulent Times"
Motivation
and Summary: Following decades of low unemployment, several (but not
all) European countries have faced persistent high unemployment. The typical
“rigidity of the labour market” explanations fail to account for the observed
differences. We explore a dynamic search model that incorporates the option of
retraining. We show how differences in the effectiveness and availability of
retraining can explain the heterogeneity of the experiences observed across