42,310 research outputs found
The Power-law Tail Exponent of Income Distributions
In this paper we tackle the problem of estimating the power-law tail exponent
of income distributions by using the Hill's estimator. A subsample
semi-parametric bootstrap procedure minimising the mean squared error is used
to choose the power-law cutoff value optimally. This technique is applied to
personal income data for Australia and Italy.Comment: Latex2e v1.6; 8 pages with 3 figures; in press (Physica A
Reflections on Modern Macroeconomics: Can We Travel Along a Safer Road?
In this paper we sketch some reflections on the pitfalls and inconsistencies
of the research program - currently dominant among the profession - aimed at
providing microfoundations to macroeconomics along a Walrasian perspective. We
argue that such a methodological approach constitutes an unsatisfactory answer
to a well-posed research question, and that alternative promising routes have
been long mapped out but only recently explored. In particular, we discuss a
recent agent-based, truly non-Walrasian macroeconomic model, and we use it to
envisage new challenges for future research.Comment: Latex2e v1.6; 17 pages with 4 figures; for inclusion in the APFA5
Proceeding
Am I Done? Predicting Action Progress in Videos
In this paper we deal with the problem of predicting action progress in
videos. We argue that this is an extremely important task since it can be
valuable for a wide range of interaction applications. To this end we introduce
a novel approach, named ProgressNet, capable of predicting when an action takes
place in a video, where it is located within the frames, and how far it has
progressed during its execution. To provide a general definition of action
progress, we ground our work in the linguistics literature, borrowing terms and
concepts to understand which actions can be the subject of progress estimation.
As a result, we define a categorization of actions and their phases. Motivated
by the recent success obtained from the interaction of Convolutional and
Recurrent Neural Networks, our model is based on a combination of the Faster
R-CNN framework, to make frame-wise predictions, and LSTM networks, to estimate
action progress through time. After introducing two evaluation protocols for
the task at hand, we demonstrate the capability of our model to effectively
predict action progress on the UCF-101 and J-HMDB datasets
Market-Driven Management and Intangible Assets in Global Television Set Manufacturers
The television set industry is a global sector where the most competitive companies are market-driven. Their competitive advantage is based not only on their ability to innovate products but also on their capability to develop and strengthen intangible assets, such as corporate culture, brand image and relationships between organisations.Television set industry, Market Driven Management, Competitiveness, Intangible Assets DOI:http://dx.doi.org/10.4468/2010.2.07silvestrelli
Impacts of air pollution on human and ecosystem health, and implications for the National Emission Ceilings Directive. Insights from Italy
Across the 28 EU member states there were nearly half a million premature deaths in 2015 as a result of exposure to PM2.5, O3 and NO2. To set the target for air quality levels and avoid negative impacts for human and ecosystems health, the National Emission Ceilings Directive (NECD, 2016/2284/EU) sets objectives for emission reduction for SO2, NOx, NMVOCs, NH3 and PM2.5 for each Member State as percentages of reduction to be reached in 2020 and 2030 compared to the emission levels into 2005. One of the innovations of NECD is Article 9, that mentions the issue of âmonitoring air pollution impactsâ on ecosystems. We provide a clear picture of what is available in term of monitoring network for air pollution impacts on Italian ecosystems, summarizing what has been done to control air pollution and its effects on different ecosystems in Italy. We provide an overview of the impacts of air pollution on health of the Italian population and evaluate opportunities and implementation of Article 9 in the Italian context, as a case study beneficial for all Member States. The results showed that SO42â deposition strongly decreased in all monitoring sites in Italy over the period 1999â2017, while NO3â and NH4+ decreased more slightly. As a consequence, most of the acid-sensitive sites which underwent acidification in the 1980s partially recovered. The O3 concentration at forest sites showed a decreasing trend. Consequently, AOT40 (the metric identified to protect vegetation from ozone pollution) showed a decrease, even if values were still above the limit for forest protection (5000 ppb hâ1), while PODy (flux-based metric under discussion as new European legislative standard for forest protection) showed an increase. National scale studies pointed out that PM10 and NO2 induced about 58,000 premature deaths (year 2005), due to cardiovascular and respiratory diseases. The network identified for Italy contains a good number of monitoring sites (6 for terrestrial ecosystem monitoring, 4 for water bodies monitoring and 11 for ozone impact monitoring) distributed over the territory and will produce a high number of monitored parameters for the implementation of the NECD
Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data
We develop a Bayesian approach for selecting the model which is the most
supported by the data within a class of marginal models for categorical
variables formulated through equality and/or inequality constraints on
generalised logits (local, global, continuation or reverse continuation),
generalised log-odds ratios and similar higher-order interactions. For each
constrained model, the prior distribution of the model parameters is formulated
following the encompassing prior approach. Then, model selection is performed
by using Bayes factors which are estimated by an importance sampling method.
The approach is illustrated through three applications involving some datasets,
which also include explanatory variables. In connection with one of these
examples, a sensitivity analysis to the prior specification is also considered
A new measure for community structures through indirect social connections
Based on an expert systems approach, the issue of community detection can be
conceptualized as a clustering model for networks. Building upon this further,
community structure can be measured through a clustering coefficient, which is
generated from the number of existing triangles around the nodes over the
number of triangles that can be hypothetically constructed. This paper provides
a new definition of the clustering coefficient for weighted networks under a
generalized definition of triangles. Specifically, a novel concept of triangles
is introduced, based on the assumption that, should the aggregate weight of two
arcs be strong enough, a link between the uncommon nodes can be induced. Beyond
the intuitive meaning of such generalized triangles in the social context, we
also explore the usefulness of them for gaining insights into the topological
structure of the underlying network. Empirical experiments on the standard
networks of 500 commercial US airports and on the nervous system of the
Caenorhabditis elegans support the theoretical framework and allow a comparison
between our proposal and the standard definition of clustering coefficient
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Lowering the pirate flag: a TPB study of the factors influencing the intention to pay for movie streaming services
The launch of several movie streaming services has raised new questions about how online consumers deal with both legal and illegal options to obtain their desired products. This paper investigates the factors influencing consumersâ intentions to subscribe to online movie streaming services. These services have challenged the dramatic growth in their illegal counterpart in recent years. Taking the theory of planned behavior as a starting point, we extended existing models in the literature by incorporating factors that are specific to consumer behavior in this particular field. A quantitative survey was conducted for the Italian market, and structural equation modeling was used for data analysis. Attitudes, involvement with products, moral judgement and frequency of past behavior were found to be the most important factors in explaining the intention to pay for movie streaming services. The paper provides insights for policy makers and industry managers on the marketing communication strategies needed to minimize the risk of digital piracy
Religion-based Urbanization Process in Italy: Statistical Evidence from Demographic and Economic Data
This paper analyzes some economic and demographic features of Italians living
in cities containing a Saint name in their appellation (hagiotoponyms).
Demographic data come from the surveys done in the 15th (2011) Italian Census,
while the economic wealth of such cities is explored through their recent
[2007-2011] aggregated tax income (ATI). This cultural problem is treated from
various points of view. First, the exact list of hagiotoponyms is obtained
through linguistic and religiosity criteria. Next, it is examined how such
cities are distributed in the Italian regions. Demographic and economic
perspectives are also offered at the Saint level, i.e. calculating the
cumulated values of the number of inhabitants and the ATI, "per Saint", as well
as the corresponding relative values taking into account the Saint popularity.
On one hand, frequency-size plots and cumulative distribution function plots,
and on the other hand, scatter plots and rank-size plots between the various
quantities are shown and discussed in order to find the importance of
correlations between the variables. It is concluded that rank-rank correlations
point to a strong Saint effect, which explains what actually Saint-based
toponyms imply in terms of comparing economic and demographic data.Comment: 55 pages, 70 refs., 21 figures, 15 tables; prepared for and to be
published in Quantity & Qualit
Financial Fragility in the Current European crisis
The paper argues that the European financial system in the years following the great financial crisis started in 2007 has become increasingly fragile. Minskyâs notion of fragility, on which it is based, is related to history, policy and institutions. In the current European environment, fragility depends on the rise of shadow banksâ assets, the expansion of derivatives and the changes in financial regulation. All these elements have jointly triggered several feedback loops. In Minskyâs opinion, policies should have the scope of thwarting self-enforcing feedback loops. Yet the policies that have been implemented so far seem to have produced the opposite effects. They have created new feedback loops that nurture fragility again. This outcome, however, is not surprising for policies may change initial conditions and have unintended consequences, as Minsky has taught us since a long time
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