Econometrics and economic statistics

This study, first published in 1979, examines and contrasts two concepts of credit rationing.

This book answers some challenging questions in monetary growth theory within a compact theoretical framework.

This book demonstrates how mathematical models constructed in system dynamics modelling platforms, such as Vensim, can be used for long-term management of environmental change.

It is commonly believed that macroeconomic models are not useful for policy analysis because they do not take proper account of agents' expectations.

This book is the fifth annual project of the Asia Competitiveness Institute studying competitiveness at the sub-national level of Greater China.

This advanced textbook is an essential guide to discovering new and more illuminating ways to analyse the econometric modelling of experimental data.

This volume of Advances in Econometrics focuses on recent developments in the use of structural econometric models in empirical economics.

Arthur Vogt has devoted a great deal of his scientific efforts to both person and work of Irving Fisher.

Thoroughly classroom tested, this introductory text covers all the statistical topics that constitute a foundation for basic econometrics, with concise explanations of technical material.

Encompasses the main concepts and approaches of quantitative impact evaluations, used to consider the effectiveness of programmes, policies, projects or interventions.

This is the first book that examines the diverse range of experimental methods currently being used in the social sciences, gathering contributions by working economists engaged in experimentation, as well as by a political scientist, psychologists and philosophers of the social sciences.

There is a dearth of good books on accounting in China, East Asia and Southeast Asia.

Globalization and information and communications technology (ICT) have played a pivotal role in revolutionizing value creation through the development of human capital formation.

Barrier options are a class of highly path-dependent exotic options which present particular challenges to practitioners in all areas of the financial industry.

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First published in 1984.

Focusing on recent developments in the field, American-Style Derivatives provides an extensive treatment of option pricing with emphasis on the valuation of American options on dividend-paying assets.

Introduces first-year social science undergraduates to the practical aspects of simple regression analysis, without adopting an esoteric, mathematical approach.

Big data is presenting challenges to cybersecurity.

Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved.

For courses in introductory econometrics.

The most authoritative and comprehensive synthesis of modern econometrics availableEconometrics provides first-year graduate students with a thoroughly modern introduction to the subject, covering all the standard material necessary for understanding the principal techniques of econometrics, from ordinary least squares through cointegration.

This conference proceedings volume presents advanced methods in time series estimation models that are applicable various areas of applied economic research such as international economics, macroeconomics, microeconomics, finance economics and agricultural economics.

The optimisation of economic systems over time, and in an uncertain environment, is central to the study of economic behaviour.

This book expands the explanatory scope of econophysics to the real economy.

A noted economist challenges the fundamental economic assumptions that cast economic growth as the objective and markets as the universally applicable means of achieving it.

The British Economy After Oil (1988) examines the future paths for the British economy as North Sea oil runs out.

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation.

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data.

Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods.

A collection in honour of G.

Provides statistical tools and techniques needed to understand today's financial markets The Second Edition of this critically acclaimed text provides a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data.

On May 27-31, 1985, a series of symposia was held at The University of Western Ontario, London, Canada, to celebrate the 70th birthday of Pro- fessor V.

The UK energy system has experienced radical reform in past decade - privatisation, liberalisation, re-structuring and re-regulation for gas/electricity supply and coal, plus rapid technological change and flexible fiscal policy in offshore oil/gas.

This book provides an introduction to index numbers for statisticians, economists and numerate members of the public.

Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice.

This concise textbook presents students with all they need for advancing in mathematical economics.

An examination of collusive behavior: what it is, why it is profitable, how it is implemented, and how it might be detected.

Computable General Equilibrium (CGE) modelling is a relatively new field in economics, however, it is rapidly becoming one of the most useful tools for policy evaluation.

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist.

A First Course in Machine Learning covers the core mathematical and statistical techniques needed to understand some of the most popular machine learning algorithms.

An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.