Non-parametric methods such as artificial neural nets can successfully model prices of financial options, out-performing the Black–Scholes analytic model (Eur. Phys. J. B 27 (2002) 219). However, the accuracy of such approaches is usually expressed only by a global fitting/error measure. This...

Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the...

This paper argues that the sometimes-conflicting results of a modern revisionist literature on data mining in econometrics reflect different approaches to solving the central problem of model uncertainty in a science of non-experimental data. The literature has entered an exciting phase with...

Modern statistical data analysis is predominantly model-driven, seeking to decompose an observed data distribution in terms of major underlying descriptive features modified by some stochastic variation. A large part of data mining is also concerned with this exercise. However, another...

For effective Customer Relationship Management (CRM), it is important to gather information on customer value. Segmentation is the method of knowing the customers and partitioning a population of customers into smaller groups. This paper develops a novel country segmentation methodology based on...

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper we propose...

In the last twenty years in real estate appraisal there has been a growing interest for new and reliable assessment techniques essentially through the introduction of pluriparametric estimate, in particular of linear regression. However, also these techniques seem having not a great deal of...

The development of infrastructure contributes to the social and economic improvement of a country, and generally requires huge and immediate investments. To decide on appropriate infrastructure projects, many countries use preliminary feasibility studies (PFS). However, a preliminary feasibility...

Boosting, or boosted regression, is a recent data-mining technique that has shown considerable success in predictive accuracy. This article gives an overview of boosting and introduces a new Stata command, boost, that im- plements the boosting algorithm described in Hastie, Tibshirani, and...

This article revisits the validity of the Environmental Kuznets Curve hypothesis. Based on data for seven pollutants in 29 Chinese provinces from 1995 to 2010, we conducted statistical tests on the coefficients of the critical variables (polynomial income-related terms) by following the logic of...