Javier Salas nos ofrece una cuidada introduccion al mundo de la econometria, asi como una inteligente propuesta para aplicar sus modelos de analisis y planeacion a la economia de los paises del Tercer Mundo, tomando como base el caso concreto de Mexico. Una obra dirigida a los economistas y en general a los interesados en conocer las bases teoricas de la econometria.
Joseph A. Schumpeter (1883-1950) is one of the most celebrated authors on the economics and sociology of the twentieth century. Richard Swedberg's new biography provides an engaging and vivid account of Schumpeter's varied life, including his ventures into politics and private banking as well as his academic career. As a backdrop to these, Swedberg also discusses Schumpeter's tragic personal life. This book provides a thorough overview of Schumpeter's writings, and also introduces previously unpublished material based on his letters and interviews. Swedberg emphasizes that Schumpeter saw economics as a form of social investigation, consisting of four fields: economic theory, economic sociology, economic history and statistics. The author describes and analyses Schumpeter's theory of social classes and modern states as well as his more famous theory of the entrepreneur.
La tercera edición de este “Tesauro”, nacido en 1986, responde a la necesidad de actualizar su universo terminológico según los usos más implantados en la literatura económica más reciente. Tiene como notas diferenciales respecto a la anterior edición: la reestructuración del esquema organizativo general para acercarlo a la cosmovisión de la disciplina que generalmente tienen los economistas y hacerlo compatible con otros esquemas académicos; la reducción y sustitución de descriptores y la introducción de nuevos conceptos o la nueva formulación de otros ya existentes.
Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.
This book presents the latest knowledge on the still under-researched field of academic tourism, which over the past decade has gained in importance at local and national economic levels as a result of increasing international mobility of students and academic staff in higher education. A wide range of themes are explored from various perspectives, with the focus on Europe. Particular attention is paid to academic tourism demand, expenditure, and economic impact; the relationships between academic tourism and local and regional development, sustainable development, and environmental sustainability; and the importance of academic tourism for the internationalization of higher education and international cooperation and development. Further topics to be considered include the significance of academic tourism for the dynamics of tourism destinations and insights from experimental tourism research. In addition to theoretical chapters and state of the art reviews, readers will find insightful empirical and case studies. The book will be of interest to academics, researchers, students, and practitioners, including policy makers.
The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.
