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 the narrator, Francisco Louca discusses both the keys events - the establishment of the Econometric Society, the Cowles Commission and the journal Econometrica – and the major players - economists like Wesley Mitchell, mathematicians like John von Neumann and statisticians like Karl Pearson - in history that shaped the development of econometrics. He discusses the evolution of their thought, detailing the debates, the quarrels and the interrogations that crystallized their work and even offers a conclusion of sorts, suggesting that some of the more influential thinkers abandoned econometrics or became critical of its development. International in scope and appeal, The Years of High Econometrics is an excellent accompaniment for students taking courses on probability, econometric methods and the history of economic thought.

Reformation of Econometrics is a sequel to The Formation of Econometrics: A Historical Perspective (1993, OUP) which traces the formation of econometric theory during the period 1930-1960. This book provides an account of the advances in the field of econometrics since the 1970s. Based on original research, it focuses on the reformists' movement and schools of thought and practices that attempted a paradigm shift in econometrics in the 1970s and 1980s. It describes the formation and consolidation of the Cowles Commission (CC) paradigm and traces and analyses the three major methodological attempts to resolve problems involved in model choice and specification of the CC paradigm. These attempts have reoriented the focus of econometric research from internal questions (how to optimally estimate a priori given structural parameters) to external questions (how to choose, design, and specify models). It also examines various modelling issues and problems through two case studies - modelling the Phillips curve and business cycles. The third part of the book delves into the development of three key aspects of model specification in detail - structural parameters, error terms, and model selection and design procedures. The final chapter uses citation analyses to study the impact of the CC paradigm over the span of three and half decades (1970-2005). The citation statistics show that the impact has remained extensive and relatively strong in spite of certain weakening signs. It implies that the reformative attempts have fallen short of causing a paradigm shift.

In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.

A book on nonlinear economic relations that involve time. It covers specification testing of linear versus non-linear models, model specification testing, estimation of smooth transition models, volatility modelling using non-linear model specification, analysis of high dimensional data set, and forecasting.

The economic crisis of 2008 led to an unprecedented focus on the world of high finance—and revealed it to be far more arcane and influential than most people could ever have imagined. Any hope of avoiding future crises, it’s clear, rest on understanding finance itself. To understand finance, however, we have to learn its history, and this book fills that need. Kevin R. Brine, an industry veteran, and Mary Poovey, an acclaimed historian, show that finance as we know it today emerged gradually in the late nineteenth century and only coalesced after World War II, becoming ever more complicated—and ever more central to the American economy. The authors explain the models, regulations, and institutions at the heart of modern finance and uncover the complex and sometimes surprising origins of its critical features, such as corporate accounting standards, the Federal Reserve System, risk management practices, and American Keynesian and New Classic monetary economics. This book sees finance through its highs and lows, from pre-Depression to post-Recession, exploring the myriad ways in which the practices of finance and the realities of the economy influenced one another through the years. A masterwork of collaboration, Finance in America lays bare the theories and practices that constitute finance, opening up the discussion of its role and risks to a broad range of scholars and citizens.

Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally. Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study the behavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.

Shedding light on some of the most pressing open questions in the analysis of high frequency data, this volume presents cutting-edge developments in high frequency financial econometrics. Coverage spans a diverse range of topics, including market microstructure, tick-by-tick data, bond and foreign exchange markets, and large dimensional volatility modeling. The volume is of interest to graduate students, researchers, and industry professionals.

Modern economies are full of uncertainties and risk. Economics studies resource allocations in an uncertain market environment. As a generally applicable quantitative analytic tool for uncertain events, probability and statistics have been playing an important role in economic research. Econometrics is statistical analysis of economic and financial data. In the past four decades or so, economics has witnessed a so-called 'empirical revolution' in its research paradigm, and as the main methodology in empirical studies in economics, econometrics has been playing an important role. It has become an indispensable part of training in modern economics, business and management.This book develops a coherent set of econometric theory, methods and tools for economic models. It is written as a textbook for graduate students in economics, business, management, statistics, applied mathematics, and related fields. It can also be used as a reference book on econometric theory by scholars who may be interested in both theoretical and applied econometrics.

The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.

This publication contains a substantial amount of detail about the broad history of the development of econometric software based on the personal recollections of many people. For economists, the computer has increasingly become the primary applied research tool, and it is software that makes the computer work.