19,603 research outputs found
Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics
Economies are instances of complex socio-technical systems that are shaped by
the interactions of large numbers of individuals. The individual behavior and
decision-making of consumer agents is determined by complex psychological
dynamics that include their own assessment of present and future economic
conditions as well as those of others, potentially leading to feedback loops
that affect the macroscopic state of the economic system. We propose that the
large-scale interactions of a nation's citizens with its online resources can
reveal the complex dynamics of their collective psychology, including their
assessment of future system states. Here we introduce a behavioral index of
Chinese Consumer Confidence (C3I) that computationally relates large-scale
online search behavior recorded by Google Trends data to the macroscopic
variable of consumer confidence. Our results indicate that such computational
indices may reveal the components and complex dynamics of consumer psychology
as a collective socio-economic phenomenon, potentially leading to improved and
more refined economic forecasting.Comment: 21 pages, 6 figures, 13 table
Thirty Years of Spatial Econometrics
In this paper, I give a personal view on the development of the field of spatial econometrics during the past thirty years. I argue that it has moved from the margins to the mainstream of applied econometrics and social science methodology. I distinguish three broad phases in the development, which I refer to as preconditions, takeoff and maturity. For each of these phases I describe the main methodological focus and list major contributions. I conclude with some speculations about future directions.
Rough Set Theory for Real Estate Appraisal: An Application to Directional District of Naples
This paper proposes an application of Rough Set Theory (RST) to the real estate field, in order to highlight its operational potentialities for mass appraisal purposes. RST allows one to solve the appraisal of real estate units regardless of the deterministic relationship between characteristics that contribute to the formation of the property market price and the same real estate prices. RST was applied to a real estate sample (office units located in Directional District of Naples) and was also integrated with a functional extension so-called Valued Tolerance Relation (VTR) in order to improve its flexibility. A multiple regression analysis (MRA) was developed on the same real estate sample with the aim to compare RST and MRA results. The case study is followed by a brief discussion on basic theoretical connotations of this methodology
Fuzzy investment decision support for brownfield redevelopment
Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.This dissertation focuses on decision making, investing and brownfield redevelopment. Especially on the analysis, evaluation and selection of previously used real estates suitable for commercial use. The objective of this dissertation is to design a method that facilitates the decision making process with many possible alternatives and large number of relevant parameters influencing the decision. The proposed method is based on the use of fuzzy logic, modeling, statistic analysis, cluster analysis, graph theory and sophisticated methods of information collection and processing. New method allows decision makers to process much larger amount of information and evaluate possible investment alternatives efficiently.
A General Framework for Complex Network Applications
Complex network theory has been applied to solving practical problems from
different domains. In this paper, we present a general framework for complex
network applications. The keys of a successful application are a thorough
understanding of the real system and a correct mapping of complex network
theory to practical problems in the system. Despite of certain limitations
discussed in this paper, complex network theory provides a foundation on which
to develop powerful tools in analyzing and optimizing large interconnected
systems.Comment: 8 page
Identifying Key Sectors in the Regional Economy: A Network Analysis Approach Using Input-Output Data
By applying network analysis techniques to large input-output system, we
identify key sectors in the local/regional economy. We overcome the limitations
of traditional measures of centrality by using random-walk based measures, as
an extension of Blochl et al. (2011). These are more appropriate to analyze
very dense networks, i.e. those in which most nodes are connected to all other
nodes. These measures also allow for the presence of recursive ties (loops),
since these are common in economic systems (depending to the level of
aggregation, most firms buy from and sell to other firms in the same industrial
sector). The centrality measures we present are well suited for capturing
sectoral effects missing from the usual output and employment multipliers. We
also develop an R package (xtranat) for the processing of data from IMPLAN(R)
models and for computing the newly developed measures
Contextualized property market models vs. Generalized mass appraisals: An innovative approach
The present research takes into account the current and widespread need for rational valuation methodologies, able to correctly interpret the available market data. An innovative automated valuation model has been simultaneously implemented to three Italian study samples, each one constituted by two-hundred residential units sold in the years 2016-2017. The ability to generate a "unique" functional form for the three different territorial contexts considered, in which the relationships between the influencing factors and the selling prices are specified by different multiplicative coefficients that appropriately represent the market phenomena of each case study analyzed, is the main contribution of the proposed methodology. The method can provide support for private operators in the assessment of the territorial investment conveniences and for the public entities in the decisional phases regarding future tax and urban planning policies
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