The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems—and financial markets in particular—that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, “physics envy” has also created a false sense of mathematic...

A GIS multi-component module was developed within the ArcView GIS environment for processing and analysing weather radar precipitation data. The module is capable of: (a) reading geo-reference radar data and comparing it with rain-gauge network data, (b) estimating the kinematics of rainfall patterns, such as the storm speed and direction, and (c) accumulating radar-derived rainfall depths. By ...

Stock market prediction has been a classical yet challenging problem, with the attention from both economists and computer scientists. With purpose of building an effective model, linear machine learning tools have explored for past couple decades. Lately, deep models introduced as new frontiers this topic rapid development is too fast to catch up. Hence, our motivation survey give latest revie...

Focused on the emerging conditions of industrial capitalism in Britain in their own time, the classical economists were able to provide an account of the broad forces that influence economic growth and of the mechanisms underlying the growth process. Accumulation and productive investment of a part of the social surplus in the form of profits were seen as the main driving force. Hence, changes ...

Modern development economics emerged with the realization that poverty changes the set of options available to individuals. Poverty thus affects behavior, even if the decision maker is “neo-classical”: unboundedly rational, forward-looking, and internally consistent. The “homo economicus” at the core of neo-classical economics (“calculating, unemotional maximizer”, (Mullainathan and Thaler, 200...