Econometrics and economic statistics Books

Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: (1) Decision tree learning with uncertainty, (2) Clustering under uncertainty environment, (3) Active learning based on uncertainty criterion,...

Maurice Potron (1872-1942), a French Jesuit mathematician, constructed and analyzed a highly original, but virtually unknown economic model. This book presents translated versions of all his economic writings, preceded by a long introduction which...

Praise for the first edition:"[This book] succeeds singularly at providing a structured introduction to this active field of research. ... it is arguably the most accessible overview yet published of the mathematical ideas and principles that one needs...

This book provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II). Part I of the book brings several different tree algorithms into focus, both conventional and contemporary. 

This new edition covers some of the key topics relating to the latest version of MS Office through Excel 2019, including the creation of custom ribbons by injecting XML code into Excel Workbooks and how to link Excel VBA macros to customize ribbon...

This book presents post-estimation and predictions strategies for the host of useful statistical models with applications in data science. Combining statistical learning and machine learning techniques in a unique and optimal way, it will help...

R for College Mathematics and Statistics encourages the use of R in mathematics and statistics courses. Instructors are no longer limited to ``nice'' functions in calculus classes. They can require reports and homework with graphs. They can do...

This new book will be welcomed by econometricians and students of econometrics everywhere. Introducing discrete time modelling techniques and bridging the gap between economics and econometric literature, this ambitious book is sure to be an invaluable...

This research deals with the increasingly complex issues of waste generation, waste management and waste disposal that in less developed industrialised countries present diverse but critical concerns. It takes a socio-economic and policy-oriented...

This book unifies conventional statistical thinking and contemporary machine learning framework into a single overarching umbrella over data science. The book is designed to bridge the knowledge gap between conventional statistics and machine learning.

From the late 1990s, the spectacular growth of a secondary market for credit through derivatives has been matched by the emergence of mathematical modelling analysing the credit risk embedded in these contracts. This book aims to provide a broad and deep...

Praise for the first edition:[This book] reflects the extensive experience and significant contributions of the author to non-linear and non-Gaussian modeling. ... [It] is a valuable book, especially with its broad and accessible introduction of models...

An easy-to-understand guide to modelling productivity and efficiency using modern statistical tools. Introduces the fundamentals of stochastic frontier analysis (SFA) and the latest concepts and methods related to the use of copulas in SFA. A useful...

This text is designed to help students fully understand regression analysis, its components, and its uses. Taking into consideration current statistical technology, it focuses on the use and interpretation of software, while also demonstrating the logic,...

Little known to many, R works just as well with JavaScript-this book delves into the various ways both languages can work together. The ultimate aim of this work is to put the reader at ease with inviting JavaScript in their data science workflow. In...

There is no book currently available that gives a comprehensive treatment of the design, construction, and use of index numbers. However, there is a pressing need for one in view of the increasing and more sophisticated employment of index numbers in the...

Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and...

Identifying and assessing the ways in which changes in the marketing mix affect consumer behavior is key to a successful marketing strategy.The Essentials of Marketing Research guides the student in designing, conducting and interpreting marketing...

This new text provides a state-of the-art introduction to educational and psychological testing and measurement theory that reflects many intellectual developments of the past two decades. The book introduces psychometric theory using a latent variable...

This book provides an introduction and overview to seven applied financial studies on the theme of labour. The studies cover a wide range of topics, from the individual effects of becoming disabled on key aspects of labour market outcomes in Germany, to...

This book addresses one of the most important research activities in empirical macroeconomics. It provides a course of advanced but intuitive methods and tools enabling the spatial and temporal disaggregation of basic macroeconomic variables and the...

This edited volume seeks to provide a critical and technical look at international political economy indices (PEIs). It examines measurement issues, relates PEIs to economic theory, and suggests better measures than those currently used.

In recent years it has become apparent that the pattern of population growth is consistent with the predictions of the Malthusian model. Studies on the pre-industrial epoch in a wide range of countries show positive income elasticities of mortality and a...

The proliferation ofthe internethas often been referred to as the fourth technological revolution. This book explores the diffusion of radical new communication technologies, and the subsequent transformation not only of products, but also of the...

This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and...

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in...

This book enables us to analyze statistically brain imaging data. It is meant for a wide range of researchers interested in biostatistics, data science, and neuroscience. It is useful to understand the background theory of standard software for...

This book covers both conceptual and procedural aspects of cutting-edge data mining methods, and the path for transitioning from classical statistics and modern data science. Readers will learn how various open source and commercial software modules can...

Knowledge Guided Machine Learning provides an introduction to this rapidly growing field by discussing some of the common themes of research in SGML, using illustrative examples and case studies from diverse application domains and research...

Notes on the Contributors - Introduction ; E.Quinet & R.Vickerman - A Disaggregate Box-Cox Logit Choice Model of Intercity Passenger Travel in Germany; M.Gaudry, B.Mandel & W.Rothengatter - Measuring the Contribution of Road Infrastructure to...

The GUHA is a method of mechanizing hypothesis formation. The input of the GUHA procedure consists of analysed data and several parameters defining a large set of relevant patterns. The output is a representation of a set of all relevant patterns...

This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare.

The first number of our earlier series, A Programme for Growth, carried a notice of forthcoming papers. Five were announced but eventually only four were published. The fifth, which was intended to deal with consumption...

Providing researchers in economics, finance, and statistics with an up-to-date introduction to applying Bayesian techniques to empirical studies, this book covers the full range of the new numerical techniques which have been...

How SAS Works is a textbook designed to span the gap between the SAS Institute's "Introductory Guide", which is a very basic introduction to the SAS system, and the "User's Guide", which is a reference tool for those already...

In a relatively short period of time, data envelopment analysis (DEA) has grown into a powerful analytical tool for measuring and evaluating performance. DEA is computational at its core and this book is one of several Springer...

A fascinating and comprehensive history, this book explores the most important transformation in twentieth century economics: the creation of econometrics. Containing fresh archival material that has not been published before and taking Ragnar Frisch as...

Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive...