Currently Assistant Professor (ricercatore) of Economic Statistics. Ph.D. in Statistics achieved at Università degli Studi di Milano in 2002. Visiting Ph.D. Student at Humboldt Universitaet zu Berlin (winter semester 2000/01). Italian University Degree in Statistics and Economics (Faculty of Political Sciences) achieved at Università degli Studi di Milano in 1997.
Abstract: In this paper we apply a model of optimal bidding behaviour to the Italian wholesale electricity
market under three hypotheses: i) costs of generation are private knowledge, ii) firms can be vertically integrated, and iii) firms can sell part of their production in advance with bilateral contracts. We first use optimal bid
functions and market data to retrieve time-varying marginal
cost functions, price-cost margins and Lerner Indexes of market
power for a sample of Italian companies.
Then, we use estimated costs and actual equilibrium prices to
evaluate the elasticity of these series to fuel price variations and
estimate a possible differential impact of the dynamics of input
expenditures (fuel price above all) on generation costs and final
electricity prices. Our estimates suggest that the elasticities of
costs and equilibrium prices with respect to oil price are
virtually the same and, therefore, that the auction mechanism
per se does not limit the extent to which cost increases are
transferred to prices.
Abstract: The use of state space models and their inference is illustrated using the package SsfPack for Ox. After a rather long introduction that explains the use of SsfPack and many of its functions, four case-studies illustrate the practical implementation of the software to real world problems through short sample programs. The first case consists in the analysis of the well-known (at least to time series analysis experts) Nile data with a local level model. The other case-studies deal with ARIMA and RegARIMA models applied to the (also well-known) Airline time series, structural time series models applied to the Italian industrial production index and stochastic volatility models applied to the FTSE100 index. In all applications inference on the model (hyper-) parameters is carried out by maximum likelihood, but in one case (stochastic volatility) also an MCMC-based approach is illustrated. Cubic splines are covered in a very short example as well.
Abstract: A coincident business cycle indicator for the Milan area is built on the basis of a monthly industrial survey carried out by Assolombarda, the largest territorial entrepreneurial association in Italy. The indicator is extracted from three time series concerning the production level and the domestic and foreign order book as declared by some 250 Assolombarda associates.
This indicator is potentially very valuable in itself, being the Milan area one of the most dynamic economic systems in Italy and Europe, but it becomes much more interesting when compared to the Italian business cycle as extracted from the Italian industrial production index. Indeed, notwithstanding the deep differences in the nature of the data, the indicator for Milan has an extremely high coherence with the Italian cycle and the former leads the latter by approximately 4-6 months. Furthermore there is a direct relation between the amplitude of the cycle and the leading time of the Milan indicator.
The ability of the Milan indicator to predict in real time the turning points of the Italian business cycle is tested through a simple forecasting exercise.
Abstract: This paper analyses the interdependencies existing in wholesale
electricity prices in six major European countries. The results of
a robust multivariate long run dynamic analysis reveal the
presence of four highly integrated central European markets
(France, Germany, the Netherlands and Austria). The trend shared
by these four electricity markets appears to be common also to gas
prices, but not to oil prices. The existence of a common long term dynamics
among electricity prices and between electricity prices and gas
prices can be explained by the similarity of the market design
across Europe and by the same marginal generation technology.
Since standard unit root and cointegration tests are not robust to
the peculiar characteristics of electricity prices time series, we
also develop a battery of robust inference procedures
that should assure the reliability of our results.
Abstract: The returns of many financial assets show significant skewness, but in the literature this issue
is only marginally dealt with. Our conjecture is that this distributional asymmetry may be due to
two different dynamics in positive and negative returns.
In this paper we propose a process that allows the simultaneous modelling of skewed conditional
returns and different dynamics in their conditional second moments. The main stochastic properties
of the model are analyzed and necessary and sufficient conditions for weak and strict stationarity
are derived.
An application to the daily returns on the principal index of the London Stock Exchange supports
our model when compared to other frequently used GARCH-type models, which are nested
into ours.
Abstract: The aim of this article was to evaluate the time course of paroxysmal positioning vertigo (PPV) and to investigate correlations with environmental and seasonal factors through a retrospective statistical analysis spanning 4 years (2001-2004). Applying rigorous diagnostic criteria, we selected 575 patients (429 women and 146 men; age range, 17-94 years; mean age, 55 years for men and 56 years for women). Statistical analysis included events per month and per year. We conducted a descriptive statistical analysis to investigate the correlation between vertigo events and main environmental factors: air pollution as expressed by daily concentration of nitric monoxide and ultrafine particles; air pressure; mean temperature and sun radiation; and humidity. We referred the environmental data, collected by Regione Lombardia (the regional government of Lombardy), to the greater Milan homogeneous area. We performed an analysis of variance test and observed that PPV is more frequent in middle-aged women (in or around their fifties) and on the right side. PPV is clearly negatively correlated with temperature, and frequency of attacks depends on temperature variations. The role of air pollution, especially particles, is suspected, but it is not yet clearly identified. Factors that link climate and otoconia metabolism require further investigation.
Abstract: Background: The primary objective of this study was to derive cost comparators
for the fourteen Anatomical Therapeutic Chemical (ATC) classes of drugs at
first level, based on age-sex related weightings. Our aim was to develop an
accurate analysis method of prescribing patterns in general practice and to be
able to explain individual variations in prescribing costs based on the age/sex
distribution of the population and individual clinical needs.
Methods: Individual cost data were collected for 3,175,691 subjects living in
three different Italian regions (Lombardy, situated in the North, Marche in the
Centre and Basilicata in the South). The observation period was 12 months
(September 2004 – August 2005).
Results: The analysis by ATC classes showed large variations in prescribing
costs for the different age groups in each of the ATC classes for both sexes,
and, in some instances, wide differences in prescribing costs by gender. The
largest cost difference between age groups, for both males and females, was
seen in drugs for the cardiovascular system. Antibiotics revealed a difference
from the general pattern with more prescriptions in the youngest age groups
compared to other ATC classes. Large differences between sexes were observed
in the older age groups in drugs used for the respiratory system. The ASSET
sample was a robust proxy of the actual public spending by ATC, while the
therapeutic group age/sex related weightings were unable to explain the large
individual variations in individual prescribing costs.
Conclusion: The outcomes of this study are apparently discordant with the
conclusions of the limited published literature on prescribing analysis in general
practice, suggesting that the ability to make more accurate comparisons of
prescribing rates, especially in individual therapeutic groups, should help to
provide a more sensitive measure when estimating prescribing costs. The
ASSET model confirmed the validity of demographic adjusted models to
quantify the impact of ageing population in terms of resources needed to
satisfy long term population prescribing needs. The ASSET age/sex weightings
of total prescribing costs should be used as a guide, not as the ultimate
determinant, for an equitable allocation of prescribing resources in conjunction
with historic utilisation and cost data.
Abstract: In this paper we analyze a time series of daily average prices in the Italian electricity market, which started to operate as a Pool in April 2004. Our objective is to model the high degree of autocorrelation and the multiple seasonalities in electricity prices. We use periodic time series models with GARCH disturbances and leptokurtic distributions and compare their performance with more classical ARMA-GARCH processes. The within-year seasonal variation is modelled using the low-frequency components of physical quantities, which are very regular throughout the sample. Our results reveal that much of the variability in the price series is explained by the interactions between deterministic multiple seasonalities. Periodic AR-GARCH models seem to perform quite well in mimicking the features of the stochastic part of the price process.
Abstract: BACKGROUND: The primary objective of this study was to make the first step in the modelling of pharmaceutical demand in Italy, by deriving a weighted capitation model to account for demographic differences among general practices. The experimental model was called ASSET (Age/Sex Standardised Estimates of Treatment). METHODS AND MAJOR FINDINGS: Individual prescription costs and demographic data referred to 3,175,691 Italian subjects and were collected directly from three Regional Health Authorities over the 12-month period between October 2004 and September 2005. The mean annual prescription cost per individual was similar for males (196.13 euro) and females (195.12 euro). After 65 years of age, the mean prescribing costs for males were significantly higher than females. On average, costs for a 75-year-old subject would be 12 times the costs for a 25-34 year-old subject if male, 8 times if female. Subjects over 65 years of age (22% of total population) accounted for 56% of total prescribing costs. The weightings explained approximately 90% of the evolution of total prescribing costs, in spite of the pricing and reimbursement turbulences affecting Italy in the 2000-2005 period. The ASSET weightings were able to explain only about 25% of the variation in prescribing costs among individuals. CONCLUSIONS: If mainly idiosyncratic prescribing by general practitioners causes the unexplained variations, the introduction of capitation-based budgets would gradually move practices with high prescribing costs towards the national average. It is also possible, though, that the unexplained individual variation in prescribing costs is the result of differences in the clinical characteristics or socio-economic conditions of practice populations. If this is the case, capitation-based budgets may lead to unfair distribution of resources. The ASSET age/sex weightings should be used as a guide, not as the ultimate determinant, for an equitable allocation of prescribing resources to regional authorities and general practices.
Abstract: The possible relationship between warm katabatic winds and human
health and behaviour is analyzed; notwithstanding popular belief which is very
positive about it, the connection has not been previously analyzed with the proper
methods. We use a statistical model to address this question and our data suggest
that the effects of warm katabatic winds in the Po Valley (Italy) can indeed be
detected in the increase of car accidents.
Abstract: The availability of scanner data from large-scale retailers makes the construction
of a continuously updated system of price indexes over space and time
for an important share of household consumption expenditures possible. However,
building a coherent (transitive) system of price indexes across space and time involves
issues that are irrelevant for bilateral price indexes or multilateral price indexes
only over space. Some of these issues were discussed by Hill (2004), but in my
opinion the most important has been ignored. Indeed, it is very likely that the same
commodity is differently priced across space, but in the long run the movements of
its prices will be similar (stable) in space. So it is quite natural to ask price indexes
for pairs of space situations not to diverge over time if the prices of each single
commodity in the basket remain approximatively pairwise proportional in the two
sites. In this work, we give a definition of the test of stability preservation, starting
from the stochastic properties that panels of price time series seem to obey to. Then,
many different approaches to the construction of the system of indexes are analysed
in order to identify those that pass the test. The selected systems are applied both to
simulated and to real-world data collected in four supermarkets located in the city
of Milan for a time span of 24 months.
Abstract: Duration dependent Markov-switching VAR (DDMS-VAR) models are time series
models with data generating process consisting in a mixture of two VAR processes.
The switching between the two VAR processes is governed by a two state Markov
chain with transition probabilities that depend on how long the chain has been in
a state. In the present paper we analyze the second order properties of such models
and propose a Markov chain Monte Carlo algorithm to carry out Bayesian inference
on the model’s unknowns. Furthermore, a freeware software written by the author
for the analysis of time series by means of DDMS-VAR models is illustrated. The
methodology and the software are applied to the analysis of the U.S. business cycle.
Abstract: In this paper we examine the bidding behaviour of firm competing in the Italian wholesale electricity market where generators submit hourly supply schedule to sell power. We describe the institutional characteristics of the Italian market and derive generators' equilibrium bidding functions. We also discuss the main empirical strategies followed by the recent econometrical literature to obtain estimates of (unobservable) optimal bids. Then, we use individual bid data, quantity volumes and other control variables to compare actual bidding behaviour to theoretical benchmarks of profit maximization. We obtain estimates of generators' costs to be used in conjunction with hourly market equilibrium prices to derive some measures of the extent of market power in the Italian electricity sector and of its exploitation by firms.
Abstract: In setting up the (quasi) maximum likelihood (QML) estimation of the unknown parameters
of a GARCH model the initial instances of the conditional variance process must be given values.
Many software packages use the sample variance as default while others use exponentially weighted
moving averages schemes. Many other alternatives are of course possible, but to the best of our knowledge
nobody has studied the performance of QML estimators under the different alternatives. This is
probably due to the fact that under rather weak conditions the choice of the initial values is asymptotically
irrelevant. Nevertheless, in finite samples different initialisation criteria do matter in particular
when highly persistent GARCH processes are considered. This work intends to fill this gap in the literature.
The precision of QML estimates under different choices of initialisation and sample dimension
is analysed, and the closeness of the actual (Monte Carlo) finite-sample distributions to the asymptotic
approximation is measured.
Abstract: In this paper we examine the bidding behaviour of firm competing in the Italian wholesale electricity market where generators submit hourly supply schedule to sell power. We describe the institutional characteristics of the Italian market and derive generators' equilibrium bidding functions. We also discuss the main empirical strategies followed by the recent econometrical literature to obtain estimates of (unobservable) optimal bids. Then, we use individual bid data, quantity volumes and other control variables to compare actual bidding behaviour to theoretical benchmarks of profit maximization. We obtain estimates of generators' costs to be used in conjunction with hourly market equilibrium prices to derive some measures of the extent of market power in the Italian electricity sector and of its exploitation by firms.
Abstract: This paper proposes a test of the null hypothesis of stationarity that is robust to the presence of fat-tailed errors. The test statistic is a modified version of the KPSS statistic, in which ranks substitute the original observations. The rank KPSS statistic has the same limiting distribution as the standard KPSS statistic under the null and diverges under I(1) alternatives. It features good power both under thin-tailed and fat-tailed distributions and it turns out to be a valid alternative to the original KPSS and the recently proposed Index KPSS (de Jong et al. 2007).
Abstract: This paper analyses the interdependencies existing in wholesale electricity prices in six major European countries. The results of our robust multivariate long run dynamic analysis reveal the presence of four highly integrated central European markets (France, Germany, the Netherlands and Austria). The trend shared by these four electricity markets appears to be common also to gas prices, but not to oil prices. The existence of long term dynamics among electricity prices and between electricity prices and gas prices may prove to be important for long term hedging operations to be conducted even in countries where well established and liquid electricity derivatives markets are not present. Since standard unit root and cointegration tests are not robust to the peculiar characteristics of electricity prices time series, we adapt and further develop a battery of robust inference procedures that should assure the reliability of our results.
Abstract: The returns of many financial assets show significant skewness, but in the literature this issue is only marginally dealt with. Our conjecture is that this distributional asymmetry may be due to two different dynamics in positive and negative returns. In this paper we propose a process that allows the simultaneous modelling of skewed conditional returns and different dynamics in their conditional second moments. The main stochastic properties of the model are analyzed and necessary and sufficient conditions for weak and strict stationarity are derived. An application to the daily returns on the principal index of the London Stock Exchange supports our model when compared to other frequently used GARCH-type models, which are nested into ours.
Abstract: This paper analyses the interdependencies existing in the European electricity prices. The results of a multivariate dynamic analysis of weekly median prices reveal the presence of strong integration (but not perfect integration) among the markets considered in the sample and the existence of a common trend among electricity prices and oil prices. This implies that there are no long-run arbitrage opportunities. The latter result appears to be relevant also in the context of the discussion of efficient hedging instruments to be used by medium-long term investors.
Abstract: The Dynamic Conditional Correlation (DCC) model of Engle has made
the estimation of multivariate GARCH models feasible for reasonably big
vectors of securities’ returns. In the present paper we show how Engle’s
multi-step estimation of the model can be easily extended to elliptical conditional
distributions and apply different leptokurtic DCC models to twenty
shares listed at the Milan Stock Exchange.
Abstract: A methodology based on the multivariate generalized Butterwoth filter for extracting the business cycles of the whole economy and of its productive sectors is developed. The method is then illustrated through an application to the Italian gross value added time series of the main economic sectors.
