Originally published in 1978. This book is designed to enable students on main courses in economics to comprehend literature which employs econometric techniques as a method of analysis, to use econometric techniques themselves to test hypotheses about economic relationships and to understand some of the difficulties involved in interpreting results. While the book is mainly aimed at second-year undergraduates undertaking courses in applied economics, its scope is sufficiently wide to take in students at postgraduate level who have no background in econometrics - it integrates fully the mathematical and statistical techniques used in econometrics with micro- and macroeconomic case studies.

This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.

"This book provides a comprehensive overview of the fruitful achievement of China's Quantitative Economics during the past 30 years, assembling pioneering contributions of prominent quantitative economists in China. It chronicles significant events and the detailed evolution of Quantitative Economics in China. This well-organized book is a must-have for scholars to get a full picture of the status quo, and identify possible research gaps."--

Advanced Lectures in Quantitative Economics summarizes some of the efforts of a second-phase program for first-rate candidates with a Master's degree in economics who wish to continue with a doctoral degree in quantitative economics. This book is organized into three main topics—macroeconomics, microeconomics, and econometrics. This text specifically discusses the Neo-Keynesian macroeconomics in an open economy, international coordination of monetary policies under alternative exchange-rate regimes, and prospects for global trade imbalances. The post-war developments in labor economics, introduction to overlapping generation models, and measurement of expectations and direct tests of the REH are also elaborated. This monograph likewise covers the dynamic econometric modeling of decisions under uncertainty and fundamental bordered matrix of linear estimation. This publication is a good reference for students and specialists interested in quantitative economics.

The aim of this book is to bring students of economics and finance who have only an introductory background in mathematics up to a quite advanced level in the subject, thus preparing them for the core mathematical demands of econometrics, economic theory, quantitative finance and mathematical economics, which they are likely to encounter in their final-year courses and beyond. The level of the book will also be useful for those embarking on the first year of their graduate studies in Business, Economics or Finance. The book also serves as an introduction to quantitative economics and finance for mathematics students at undergraduate level and above. In recent years, mathematics graduates have been increasingly expected to have skills in practical subjects such as economics and finance, just as economics graduates have been expected to have an increasingly strong grounding in mathematics. The authors avoid the pitfalls of many texts that become too theoretical. The use of mathematical methods in the real world is never lost sight of and quantitative analysis is brought to bear on a variety of topics including foreign exchange rates and other macro level issues.

This collection of essays by twenty-one distinguished American historians reflects on a peculiarly American way of imagining the past. At a time when history-writing has changed dramatically, the authors discuss the birth and evolution of historiography in this country, from its origins in the late nineteenth century through its present, more cosmopolitan character. In the book's first part, concerning recent historiography, are chapters on exceptionalism, gender, economic history, social theory, race, and immigration and multiculturalism. Authors are Daniel Rodgers, Linda Kerber, Naomi Lamoreaux, Dorothy Ross, Thomas Holt, and Philip Gleason. The three American centuries are discussed in the second part, with chapters by Gordon Wood, George Fredrickson, and James Patterson. The third part is a chronological survey of non-American histories, including that of Western civilization, ancient history, the middle ages, early modern and modern Europe, Russia, and Asia. Contributors are Eugen Weber, Richard Saller, Gabrielle Spiegel, Anthony Molho, Philip Benedict, Richard Kagan, Keith Baker, Joseph Zizak, Volker Berghahn, Charles Maier, Martin Malia, and Carol Gluck. Together, these scholars reveal the unique perspective American historians have brought to the past of their own nation as well as that of the world. Formerly writing from a conviction that America had a singular destiny, American historians have gradually come to share viewpoints of historians in other countries about which they write. The result is the virtual disappearance of what was a distinctive American voice. That voice is the subject of this book.

This book provides a contemporary treatment of quantitative economics, with a focus on data science. The book introduces the reader to R and RStudio, and uses expert Hadley Wickham’s tidyverse package for different parts of the data analysis workflow. After a gentle introduction to R code, the reader’s R skills are gradually honed, with the help of “your turn” exercises. At the heart of data science is data, and the book equips the reader to import and wrangle data, (including network data). Very early on, the reader will begin using the popular ggplot2 package for visualizing data, even making basic maps. The use of R in understanding functions, simulating difference equations, and carrying out matrix operations is also covered. The book uses Monte Carlo simulation to understand probability and statistical inference, and the bootstrap is introduced. Causal inference is illuminated using simulation, data graphs, and R code for applications with real economic examples, covering experiments, matching, regression discontinuity, difference-in-difference, and instrumental variables. The interplay of growth related data and models is presented, before the book introduces the reader to time series data analysis with graphs, simulation, and examples. Lastly, two computationally intensive methods—generalized additive models and random forests (an important and versatile machine learning method)—are introduced intuitively with applications. The book will be of great interest to economists—students, teachers, and researchers alike—who want to learn R. It will help economics students gain an intuitive appreciation of applied economics and enjoy engaging with the material actively, while also equipping them with key data science skills.

This volume presents advanced quantitative methods and applications in economics with special interest in macroeconomics, microeconomics, financial economics, international economics, agricultural economics, and marketing and management. Featuring selected contributions from the 2021 International Conference of Applied Economics (ICOAE 2021) held in Heraklion Crete, Greece, this book provides country specific studies with potential applications in economic policy.

Economic Theory, Econometrics, and Mathematical Economics: Quantitative Economics and Development: Essays in Memory of Ta-Chung Liu focuses on the advancements in the methodologies and processes in the field of quantitative economics. The selection first offers information on society, politics, and economic development, global stability of stochastic economic processes, and the design of mechanisms for the efficient allocation of public goods. Discussions focus on the design of individually incentive compatible mechanisms in an abstract setting, design problem under coalition formation, stability results for the economic models, invariant measures for diffusions, and disjoint principal-components method. The text then takes a look at critical observations on the labor theory of value and Sraffa's Standard Commodity and a generalization of Hotelling's solution. The manuscript examines an exploratory policy-oriented econometric model of a metropolitan area and the effect of simple specification error on the coefficients of "unaffected" variables, including distinctive features of the model and individual sectoral models. Temporal aggregation and econometric models; uniqueness of the representation of commodity-augmenting technical change; and technological change and growth performance in Taiwan agriculture are also discussed. The selection is a valuable source of data for economists and readers interested in quantitative economics.