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| introduction to quantitative macroeconomics using julia: Introduction to Quantitative Macroeconomics Using Julia Petre Caraiani, 2018-08-29 Introduction to Quantitative Macroeconomics Using Julia: From Basic to State-of-the-Art Computational Techniques facilitates access to fundamental techniques in computational and quantitative macroeconomics. It focuses on the recent and very promising software, Julia, which offers a MATLAB-like language at speeds comparable to C/Fortran, also discussing modeling challenges that make quantitative macroeconomics dynamic, a key feature that few books on the topic include for macroeconomists who need the basic tools to build, solve and simulate macroeconomic models. This book neatly fills the gap between intermediate macroeconomic books and modern DSGE models used in research. - Combines an introduction to Julia, with the specific needs of macroeconomic students who are interested in DSGE models and PhD students and researchers interested in building DSGE models - Teaches fundamental techniques in quantitative macroeconomics by introducing theoretical elements of key macroeconomic models and their potential algorithmic implementations - Exposes researchers working in macroeconomics to state-of-the-art computational techniques for simulating and solving DSGE models |
| introduction to quantitative macroeconomics using julia: A Gentle Introduction to Effective Computing in Quantitative Research Harry J. Paarsch, Konstantin Golyaev, 2016-05-13 A practical guide to using modern software effectively in quantitative research in the social and natural sciences. This book offers a practical guide to the computational methods at the heart of most modern quantitative research. It will be essential reading for research assistants needing hands-on experience; students entering PhD programs in business, economics, and other social or natural sciences; and those seeking quantitative jobs in industry. No background in computer science is assumed; a learner need only have a computer with access to the Internet. Using the example as its principal pedagogical device, the book offers tried-and-true prototypes that illustrate many important computational tasks required in quantitative research. The best way to use the book is to read it at the computer keyboard and learn by doing. The book begins by introducing basic skills: how to use the operating system, how to organize data, and how to complete simple programming tasks. For its demonstrations, the book uses a UNIX-based operating system and a set of free software tools: the scripting language Python for programming tasks; the database management system SQLite; and the freely available R for statistical computing and graphics. The book goes on to describe particular tasks: analyzing data, implementing commonly used numerical and simulation methods, and creating extensions to Python to reduce cycle time. Finally, the book describes the use of LaTeX, a document markup language and preparation system. |
| introduction to quantitative macroeconomics using julia: A Course in Modern Macroeconomics Pablo Kurlat, 2020-01-14 This book started as a collection of my teaching notes for the ECON 52 course that I taught at Stanford University. The objective of that course, and of this book, is to introduce students to the ideas and way of thinking of modern macroeconomics in a unified way that is accessible with a moderate amount of maths. Modern macroeconomics emphasizes explicit microeconomic foundations and general equilibrium analysis, combined with various kinds of constraints and market imperfections. When preparing the class I thought none of the existing textbooks conveyed this in a way that I liked, so I prepared my own notes, which then grew into this book. While mostly self-contained, the book is probably most useful to students who are familiar with the basics of multivariable calculus and have taken a calculus-based microeconomics class. |
| introduction to quantitative macroeconomics using julia: Statistics with Julia Yoni Nazarathy, Hayden Klok, 2021-09-04 This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia. |
| introduction to quantitative macroeconomics using julia: Good Economics for Hard Times Abhijit V. Banerjee, Esther Duflo, 2019-11-12 The winners of the Nobel Prize show how economics, when done right, can help us solve the thorniest social and political problems of our day. Figuring out how to deal with today's critical economic problems is perhaps the great challenge of our time. Much greater than space travel or perhaps even the next revolutionary medical breakthrough, what is at stake is the whole idea of the good life as we have known it. Immigration and inequality, globalization and technological disruption, slowing growth and accelerating climate change--these are sources of great anxiety across the world, from New Delhi and Dakar to Paris and Washington, DC. The resources to address these challenges are there--what we lack are ideas that will help us jump the wall of disagreement and distrust that divides us. If we succeed, history will remember our era with gratitude; if we fail, the potential losses are incalculable. In this revolutionary book, renowned MIT economists Abhijit V. Banerjee and Esther Duflo take on this challenge, building on cutting-edge research in economics explained with lucidity and grace. Original, provocative, and urgent, Good Economics for Hard Times makes a persuasive case for an intelligent interventionism and a society built on compassion and respect. It is an extraordinary achievement, one that shines a light to help us appreciate and understand our precariously balanced world. |
| introduction to quantitative macroeconomics using julia: Research Handbook on Economic Sanctions van Bergeijk, Peter A.G., 2021-12-10 Peter van Bergeijk brings together 40 leading experts from all continents to analyze state-of-the-art data covering the sharp increase in (smart) sanctions in the last decade. Original chapters provide detailed analyses on the determinants of sanction success and failure, complemented with research on the impact of sanctions. |
| introduction to quantitative macroeconomics using julia: An Introduction to Analysis of Financial Data with R Ruey S. Tsay, 2014-08-21 A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including: Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques. An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets. |
| introduction to quantitative macroeconomics using julia: Dynamic Economics Jerome Adda, Russell W. Cooper, 2003-08-29 An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers. This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics. In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation. The original contribution of Dynamic Economics: Quantitative Methods and Applications lies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation. |
| introduction to quantitative macroeconomics using julia: Advanced Mathematical Methods for Finance , 2011 The title of this volume 'Advanced Mathematical Methods for Finance, ' AMaMeF for short, originates from the European network of the European Science Foundation with the same name that started its activity in 2005. The goals of its program have been the development and the use of advanced mathematical tools for finance, from theory to practice. This book was born in the same spirit of the program. It presents innovations in the mathematical methods in various research areas representing the broad spectrum of AMaMeF itself. It covers the mathematical foundations of financial analysis, numerical methods, and the modeling of risk. The topics selected include measures of risk, credit contagion, insider trading, information in finance, stochastic control and its applications to portfolio choices and liquidation, models of liquidity, pricing, and hedging. The models presented are based on the use of Brownian motion, Lévy processes and jump diffusions. Moreover, fractional Brownian motion and ambit processes are also introduced at various levels. The chosen blending of topics gives a large view of the up-to-date frontiers of the mathematics for finance. This volume represents the joint work of European experts in the various fields and linked to the program AMaMeF.--Preface. |
| introduction to quantitative macroeconomics using julia: Monetary Theory and Policy Carl E. Walsh, 2003 An overview of recent theoretical and policy-related developments in monetary economics. |
| introduction to quantitative macroeconomics using julia: The Roman Market Economy Peter Temin, 2013 The quality of life for ordinary Roman citizens at the height of the Roman Empire probably was better than that of any other large group of people living before the Industrial Revolution. The Roman Market Economy uses the tools of modern economics to show how trade, markets, and the Pax Romana were critical to ancient Rome's prosperity.Peter Temin, one of the world's foremost economic historians, argues that markets dominated the Roman economy. He traces how the Pax Romana encouraged trade around the Mediterranean, and how Roman law promoted commerce and banking. Temin shows that a reasonably vibrant market for wheat extended throughout the empire, and suggests that the Antonine Plague may have been responsible for turning the stable prices of the early empire into the persistent inflation of the late. He vividly describes how various markets operated in Roman times, from commodities and slaves to the buying and selling of land. Applying modern methods for evaluating economic growth to data culled from historical sources, Temin argues that Roman Italy in the second century was as prosperous as the Dutch Republic in its golden age of the seventeenth century.The Roman Market Economy reveals how economics can help us understand how the Roman Empire could have ruled seventy million people and endured for centuries. |
| introduction to quantitative macroeconomics using julia: Global Waves of Debt M. Ayhan Kose, Peter Nagle, Franziska Ohnsorge, Naotaka Sugawara, 2021-03-04 The global economy has experienced four waves of rapid debt accumulation over the past 50 years. The first three debt waves ended with financial crises in many emerging market and developing economies. During the current wave, which started in 2010, the increase in debt in these economies has already been larger, faster, and broader-based than in the previous three waves. Current low interest rates mitigate some of the risks associated with high debt. However, emerging market and developing economies are also confronted by weak growth prospects, mounting vulnerabilities, and elevated global risks. A menu of policy options is available to reduce the likelihood that the current debt wave will end in crisis and, if crises do take place, will alleviate their impact. |
| introduction to quantitative macroeconomics using julia: Intermediate Macroeconomics Robert J. Barro, 2017 |
| introduction to quantitative macroeconomics using julia: Learning Julia Anshul Joshi, Rahul Lakhanpal, 2017-11-24 Learn Julia language for data science and data analytics About This Book Set up Julia's environment and start building simple programs Explore the technical aspects of Julia and its potential when it comes to speed and data processing Write efficient and high-quality code in Julia Who This Book Is For This book allows existing programmers, statisticians and data scientists to learn the Julia and take its advantage while building applications with complex numerical and scientific computations. Basic knowledge of mathematics is needed to understand the various methods that will be used or created in the book to exploit the capabilities for which Julia is made. What You Will Learn Understand Julia's ecosystem and create simple programs Master the type system and create your own types in Julia Understand Julia's type system, annotations, and conversions Define functions and understand meta-programming and multiple dispatch Create graphics and data visualizations using Julia Build programs capable of networking and parallel computation Develop real-world applications and use connections for RDBMS and NoSQL Learn to interact with other programming languages–C and Python—using Julia In Detail Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain. Style and approach This book demonstrates the basics of Julia along with some data structures and testing tools that will give you enough material to get started with the language from an application standpoint. |
| introduction to quantitative macroeconomics using julia: Recursive Macroeconomic Theory Thomas J. Sargent, 2016-09-15 Recursive methods offer a powerful approach for characterizing and solving complicated problems in dynamic macroeconomics. Recursive Macroeconomic Theory provides both an introduction to recursive methods and advanced material, mixing tools and sample applications. The second edition contains substantial revisions to about half the original material, and extensive additional coverage appears in seven chapters new to this edition. The updated and added material covers exciting new topics that further illustrate the power and pervasiveness of recursive methods.Significant improvements to original chapters include a better treatment of the existence of recursive equilibria, an enhanced account of the supermartingale convergence theorem, and an extended treatment of an optimal taxation problem in an economy in which there are incomplete markets. |
| introduction to quantitative macroeconomics using julia: Teaching Macroeconomics with Microsoft Excel® Humberto Barreto, 2016-05-23 Humberto Barreto shows professors how to teach macroeconomic models and incorporate data using Microsoft Excel® with free files and videos. |
| introduction to quantitative macroeconomics using julia: Quantitative Economic Policy Reinhard Neck, Christian Richter, Peter Mooslechner, 2010-11-22 Econometric techniques and models are still being extensively used in the business of forecasting and policy advice. This book presents recent advances in the theory and applications of quantitative economic policy, with particular emphasis on fiscal and monetary policies in a European and global context. The volume honors Andrew Hughes Hallett, a pioneer and major scientist in quantitative economic policy analysis, whose contributors are among his friends and former students. |
| introduction to quantitative macroeconomics using julia: Macroanalysis Matthew L. Jockers, 2013-04-15 In this volume, Matthew L. Jockers introduces readers to large-scale literary computing and the revolutionary potential of macroanalysis--a new approach to the study of the literary record designed for probing the digital-textual world as it exists today, in digital form and in large quantities. Using computational analysis to retrieve key words, phrases, and linguistic patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the close-reading of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections. |
| introduction to quantitative macroeconomics using julia: Policy and Choice William J. Congdon, Jeffrey R. Kling, Sendhil Mullainathan, 2011 Argues that public finance--the study of the government's role in economics--should incorporate principles from behavior economics and other branches of psychology. |
| introduction to quantitative macroeconomics using julia: The Analysis of Firms and Employees Stefan Bender, Julia Lane, Kathryn L. Shaw, Fredrik Andersson, Till von Wachter, 2009-05-15 The long-term impact of globalization, outsourcing, and technological change on workers is increasingly being studied by economists. At the nexus of labor economics, industry studies, and industrial organization, The Analysis of Firms and Employees presents new findings about these impacts by examining the interaction between the internal workings of businesses and outside influences from the market using data from countries around the globe. The result is enhanced insight into the dynamic interrelationship between firms and workers. A distinguished team of researchers here examines the relationships between human resource practices and productivity, changing ownership and production methods, and expanding trade patterns and firm competitiveness. With analyses of large-scale, nationwide datasets as well as focused, intensive observation of a few firms, The Analysis of Firms and Employees will challenge economists, policymakers, and scholars alike to rethink their assumptions about the workplace. |
| introduction to quantitative macroeconomics using julia: A Study in Monetary Macroeconomics Stefan Homburg, 2017 The financial crisis of 2007 and the following recession present a major challenge to macroeconomic theory. This text refines and improves mainstream approaches to contribute to a better understanding of the monetary and fiscal policies that have been complicated by low-interest rates and super-expansive monetary policies. |
| introduction to quantitative macroeconomics using julia: Principles of Economics in Context Neva Goodwin, Jonathan M. Harris, Julie A. Nelson, Brian Roach, Mariano Torras, 2015-03-04 Principles of Economics in Context lays out the principles of micro- and macroeconomics in a manner that is thorough, up to date, and relevant to students, attuned to the economic realities of the world around them. It offers engaging treatment of important current topics such as new thinking in behavioral economics, financial instability and market bubbles, debt and deficits, and policy responses to the problems of unemployment, inequality, and environmental sustainability. This new, affordable edition combines the just-released new editions of Microeconomics in Context and Macroeconomics in Context to provide an integrated full-year text covering all aspects of both micro and macro analysis and application, with many up-to-date examples and extensive supporting web resources for instructors and students. Key features include: An eye-opening statistical portrait of the United States; Clear explanation of basic concepts and analytical tools, with advanced models presented in optional chapter appendices; Presentation of policy issues in historical, institutional, social, political, and ethical context--an approach that fosters critical evaluation of the standard microeconomic models, such as welfare analysis, labor markets, and market competition; Issues of human well-being, both domestic and global, are given central importance, enriching the topics and analytical tools to which students are introduced; The theme of sustainability--financial, social, and ecological--is thoroughly integrated in the book, with chapters on alternatives to standard GDP measurement, the environment, common property, public goods, and growth and sustainability in the twenty-first century; Full complement of instructor and student support materials online, including test banks and grading through Canvas. |
| introduction to quantitative macroeconomics using julia: Information Rigidities Jonas Dovern, Mr.Ulrich Fritsche, Mr.Prakash Loungani, Ms.Natalia T. Tamirisa, 2014-02-12 We study forecasts for real GDP growth using a large panel of individual forecasts from 36 advanced and emerging economies during 1989–2010. We show that the degree of information rigidity in average forecasts is substantially higher than that in individual forecasts. Individual level forecasts are updated quite frequently, a behavior more in line “noisy” information models (Woodford, 2002; Sims, 2003) than with the assumptions of the sticky information model (Mankiw and Reis, 2002). While there are cross-country variations in information rigidity, there is no systematic difference between advanced and emerging economies. |
| introduction to quantitative macroeconomics using julia: The European Guilds Sheilagh Ogilvie, 2019-02-12 A comprehensive analysis of European craft guilds through eight centuries of economic history Guilds ruled many crafts and trades from the Middle Ages to the Industrial Revolution, and have always attracted debate and controversy. They were sometimes viewed as efficient institutions that guaranteed quality and skills. But they also excluded competitors, manipulated markets, and blocked innovations. Did the benefits of guilds outweigh their costs? Analyzing thousands of guilds that dominated European economies from 1000 to 1880, The European Guilds uses vivid examples and clear economic reasoning to answer that question. Sheilagh Ogilvie’s book features the voices of honourable guild masters, underpaid journeymen, exploited apprentices, shady officials, and outraged customers, and follows the stories of the “vile encroachers”—women, migrants, Jews, gypsies, bastards, and many others—desperate to work but hunted down by the guilds as illicit competitors. She investigates the benefits of guilds but also shines a light on their dark side. Guilds sometimes provided important services, but they also manipulated markets to profit their members. They regulated quality but prevented poor consumers from buying goods cheaply. They fostered work skills but denied apprenticeships to outsiders. They transmitted useful techniques but blocked innovations that posed a threat. Guilds existed widely not because they corrected market failures or served the common good but because they benefited two powerful groups—guild members and political elites. Exploring guilds’ inner workings across eight centuries, The European Guilds shows how privileged institutions and exclusive networks shape the wider economy—for good or ill. |
| introduction to quantitative macroeconomics using julia: Monetary Economics W. Godley, M. Lavoie, 2016-04-30 This book challenges the mainstream paradigm, based on the inter-temporal optimisation of welfare by individual agents. It introduces a methodology for studying how institutions create flows of income, expenditure and production together with stocks of assets and liabilities, thereby determining how whole economies evolve through time. |
| introduction to quantitative macroeconomics using julia: Handbook of Computable General Equilibrium Modeling Peter B. Dixon, Dale Jorgenson, 2013-11-14 In this collection of 17 articles, top scholars synthesize and analyze scholarship on this widely used tool of policy analysis, setting forth its accomplishments, difficulties, and means of implementation. Though CGE modeling does not play a prominent role in top US graduate schools, it is employed universally in the development of economic policy. This collection is particularly important because it presents a history of modeling applications and examines competing points of view. - Presents coherent summaries of CGE theories that inform major model types - Covers the construction of CGE databases, model solving, and computer-assisted interpretation of results - Shows how CGE modeling has made a contribution to economic policy |
| introduction to quantitative macroeconomics using julia: The Oxford Handbook of Economic Inequality Wiemer Salverda, Brian Nolan, Timothy M. Smeeding, 2009-02-19 Comprehensive analysis of economic inequality in developed countries. The contributors give their view on the state-of-the-art scientific research in their fields and add their own visions of future research. |
| introduction to quantitative macroeconomics using julia: Introduction to Econometrics, Student Value Edition James H. Stock, Mark W. Watson, 2018-11-06 Ensure students grasp the relevance of econometrics with Introduction to Econometrics -- the text that connects modern theory and practice with motivating, engaging applications. The 4th Edition maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. The text incorporates real-world questions and data, and methods that are immediately relevant to the applications. With very large data sets increasingly being used in economics and related fields, a new chapter dedicated to Big Data helps students learn about this growing and exciting area. This coverage and approach make the subject come alive for students and helps them to become sophisticated consumers of econometrics.-Publisher's description. |
| introduction to quantitative macroeconomics using julia: The Physics of Wall Street James Owen Weatherall, 2013-01-08 A look inside the world of “quants” and how science can (and can’t) predict financial markets: “Entertaining and enlightening” (The New York Times). After the economic meltdown of 2008, Warren Buffett famously warned, “beware of geeks bearing formulas.” But while many of the mathematicians and software engineers on Wall Street failed when their abstractions turned ugly in practice, a special breed of physicists has a much deeper history of revolutionizing finance. Taking us from fin-de-siècle Paris to Rat Pack–era Las Vegas, from wartime government labs to Yippie communes on the Pacific coast, James Owen Weatherall shows how physicists successfully brought their science to bear on some of the thorniest problems in economics, from options pricing to bubbles. The crisis was partly a failure of mathematical modeling. But even more, it was a failure of some very sophisticated financial institutions to think like physicists. Models—whether in science or finance—have limitations; they break down under certain conditions. And in 2008, sophisticated models fell into the hands of people who didn’t understand their purpose, and didn’t care. It was a catastrophic misuse of science. The solution, however, is not to give up on models; it’s to make them better. This book reveals the people and ideas on the cusp of a new era in finance, from a geophysicist using a model designed for earthquakes to predict a massive stock market crash to a physicist-run hedge fund earning 2,478.6% over the course of the 1990s. Weatherall shows how an obscure idea from quantum theory might soon be used to create a far more accurate Consumer Price Index. The Physics of Wall Street will change how we think about our economic future. “Fascinating history . . . Happily, the author has a gift for making complex concepts clear to lay readers.” —Booklist |
| introduction to quantitative macroeconomics using julia: A People's Guide to Capitalism Hadas Thier, 2018-06-02 A lively, accessible, and timely guide to Marxist economics for those who want to understand and dismantle the world of the 1%. Economists regularly promote Capitalism as the greatest system ever to grace the planet. With the same breath, they implore us to leave the job of understanding the magical powers of the market to the “experts.” Despite the efforts of these mainstream commentators to convince us otherwise, many of us have begun to question why this system has produced such vast inequality and wanton disregard for its own environmental destruction. This book offers answers to exactly these questions on their own terms: in the form of a radical economic theory. “Thier’s urgently needed book strips away jargon to make Marx’s essential work accessible to today’s diverse mass movements.” —Sarah Leonard, contributing editor to The Nation “A great book for proletarian chain-breaking.” —Rob Larson, author of Bit Tyrants: The Political Economy of Silicon Valley “Thier unpacks the mystery of capitalist inequality with lucid and accessible prose . . . . We will need books like A People’s Guide to help us make sense of the root causes of the financial crises that shape so many of our struggles today.” —Keeanga-Yamahtta Taylor, author of Race for Profit: How Banks and the Real Estate Industry Undermined Black Homeownership “Ranging from exploitation at work to the operations of modern finance, this book takes the reader through a fine-tuned introduction to Marx’s analysis of the modern economy . . . . Thier combines theoretical explanation with contemporary examples to illuminate the inner workings of capitalism . . . . Reminds us of the urgent need for alternatives to a crisis-ridden system.” —David McNally, author of Blood and Money |
| introduction to quantitative macroeconomics using julia: Economic Dynamics, second edition John Stachurski, 2022-08-16 The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems. This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field. New for the second edition: “Programming-language agnostic” presentation using pseudocode. New chapter 1 covering conceptual issues concerning Markov chains such as ergodicity and stability. New focus in chapter 2 on algorithms and techniques for program design and high-performance computing. New focus on household problems rather than optimal growth in material on dynamic programming. Solutions to many exercises, code, and other resources available on a supplementary website. |
| introduction to quantitative macroeconomics using julia: Julia High Performance Avik Sengupta, 2016-04-26 Design and develop high performing programs with Julia About This Book Learn to code high reliability and high performance programs Stand out from the crowd by developing code that runs faster than your peers' codes This book is intended for developers who are interested in high performance technical programming. Who This Book Is For This book is for beginner and intermediate Julia programmers who are interested in high performance technical computing. You will have a basic familiarity with Julia syntax, and have written some small programs in the language. What You Will Learn Discover the secrets behind Julia's speed Get a sense of the possibilities and limitations of Julia's performance Analyze the performance of Julia programs Measure the time and memory taken by Julia programs Create fast machine code using Julia's type information Define and call functions without compromising Julia's performance Understand number types in Julia Use Julia arrays to write high performance code Get an overview of Julia's distributed computing capabilities In Detail Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia. You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia's design makes them fast. The last chapter will give you a taste of Julia's distributed computing capabilities. Style and approach This is a hands-on manual that will give you good explanations about the important concepts related to Julia programming. |
| introduction to quantitative macroeconomics using julia: Approaches to Class Analysis Erik Olin Wright, 2005-07-01 Few themes have been as central to sociology as 'class' and yet class remains a perpetually contested idea. Sociologists disagree not only on how best to define the concept of class but on its general role in social theory and indeed on its continued relevance to the sociological analysis of contemporary society. Some people believe that classes have largely dissolved in contemporary societies; others believe class remains one of the fundamental forms of social inequality and social power. Some see class as a narrow economic phenomenon whilst others adopt an expansive conception that includes cultural dimensions as well as economic conditions. This 2005 book explores the theoretical foundations of six major perspectives of class with each chapter written by an expert in the field. It concludes with a conceptual map of these alternative approaches by posing the question: 'If class is the answer, what is the question?' |
| introduction to quantitative macroeconomics using julia: Julia Programming for Operations Research Changhyun Kwon, 2019-03-03 Last Updated: December 2020 Based on Julia v1.3+ and JuMP v0.21+ The main motivation of writing this book was to help the author himself. He is a professor in the field of operations research, and his daily activities involve building models of mathematical optimization, developing algorithms for solving the problems, implementing those algorithms using computer programming languages, experimenting with data, etc. Three languages are involved: human language, mathematical language, and computer language. His team of students need to go over three different languages, which requires translation among the three languages. As this book was written to teach his research group how to translate, this book will also be useful for anyone who needs to learn how to translate in a similar situation. The Julia Language is as fast as C, as convenient as MATLAB, and as general as Python with a flexible algebraic modeling language for mathematical optimization problems. With the great support from Julia developers, especially the developers of the JuMP—Julia for Mathematical Programming—package, Julia makes a perfect tool for students and professionals in operations research and related areas such as industrial engineering, management science, transportation engineering, economics, and regional science. For more information, visit: http://www.chkwon.net/julia |
| introduction to quantitative macroeconomics using julia: The Econometrics of Macroeconomic Modelling Gunnar Bårdsen, Øyvind Eitrheim, Eilev S. Jansen, 2005 This work describes how the discipline has adapted to changing demands by adopting new insights from economic theory and by taking advantage of the methodological and conceptual advances within time series econometrics. |
| introduction to quantitative macroeconomics using julia: Data Science with Julia Paul D. McNicholas, Peter Tait, 2019-01-02 This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist.- Professor Charles Bouveyron, INRIA Chair in Data Science, Université Côte d’Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist. Professor Charles Bouveyron INRIA Chair in Data Science Université Côte d’Azur, Nice, France |
| introduction to quantitative macroeconomics using julia: Global Economic History: A Very Short Introduction Robert C. Allen, 2011-09-15 Why are some countries rich and others poor? In 1500, the income differences were small, but they have grown dramatically since Columbus reached America. Since then, the interplay between geography, globalization, technological change, and economic policy has determined the wealth and poverty of nations. The industrial revolution was Britain's path breaking response to the challenge of globalization. Western Europe and North America joined Britain to form a club of rich nations by pursuing four polices-creating a national market by abolishing internal tariffs and investing in transportation, erecting an external tariff to protect their fledgling industries from British competition, banks to stabilize the currency and mobilize domestic savings for investment, and mass education to prepare people for industrial work. Together these countries pioneered new technologies that have made them ever richer. Before the Industrial Revolution, most of the world's manufacturing was done in Asia, but industries from Casablanca to Canton were destroyed by western competition in the nineteenth century, and Asia was transformed into 'underdeveloped countries' specializing in agriculture. The spread of economic development has been slow since modern technology was invented to fit the needs of rich countries and is ill adapted to the economic and geographical conditions of poor countries. A few countries - Japan, Soviet Russia, South Korea, Taiwan, and perhaps China - have, nonetheless, caught up with the West through creative responses to the technological challenge and with Big Push industrialization that has achieved rapid growth through investment coordination. Whether other countries can emulate the success of East Asia is a challenge for the future. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| introduction to quantitative macroeconomics using julia: Ageing and Health Scott L. Greer, Julia Lynch, Aaron Reeves, Michelle Falkenbach, Jane Gingrich, Jonathan Cylus, Clare Bambra, 2021-08-05 The mythical 'demographic timebomb' can be defused through policies that reduce inequalities between and within generations. |
| introduction to quantitative macroeconomics using julia: The Economic Impacts of Natural Disasters Debarati Guha-Sapir, Indhira Santos, Alexandre Borde, 2013-05-23 This work combines research and empirical evidence on the economic costs of disasters with theoretical approaches. It provides new insights on how to assess and manage the costs and impacts of disaster prevention, mitigation, recovery and adaption, and much more. |
| introduction to quantitative macroeconomics using julia: Ordinary Differential Equations Morris Tenenbaum, Harry Pollard, 1985-10-01 Skillfully organized introductory text examines origin of differential equations, then defines basic terms and outlines the general solution of a differential equation. Subsequent sections deal with integrating factors; dilution and accretion problems; linearization of first order systems; Laplace Transforms; Newton's Interpolation Formulas, more. |
INTRODUCTION Definition & Meaning - Merriam-Webster
The meaning of INTRODUCTION is something that introduces. How to use introduction in a sentence.
How to Write an Introduction, With Examples | Grammarly
Oct 20, 2022 · An introduction should include three things: a hook to interest the reader, some background on the topic so the reader can understand it, and a thesis statement that clearly …
INTRODUCTION | English meaning - Cambridge Dictionary
INTRODUCTION definition: 1. an occasion when something is put into use or brought to a place for the first time: 2. the act…. Learn more.
What Is an Introduction? Definition & 25+ Examples - Enlightio
Nov 5, 2023 · An introduction is the initial section of a piece of writing, speech, or presentation wherein the author presents the topic and purpose of the material. It serves as a gateway for …
Introduction - definition of introduction by The Free Dictionary
Something spoken, written, or otherwise presented in beginning or introducing something, especially: a. A preface, as to a book. b. Music A short preliminary passage in a larger …
INTRODUCTION Definition & Meaning - Merriam-Webster
The meaning of INTRODUCTION is something that introduces. How to use introduction in a sentence.
How to Write an Introduction, With Examples | Grammarly
Oct 20, 2022 · An introduction should include three things: a hook to interest the reader, some background on the topic so the reader can understand it, and a thesis statement that clearly …
INTRODUCTION | English meaning - Cambridge Dictionary
INTRODUCTION definition: 1. an occasion when something is put into use or brought to a place for the first time: 2. the act…. Learn more.
What Is an Introduction? Definition & 25+ Examples - Enlightio
Nov 5, 2023 · An introduction is the initial section of a piece of writing, speech, or presentation wherein the author presents the topic and purpose of the material. It serves as a gateway for …
Introduction - definition of introduction by The Free Dictionary
Something spoken, written, or otherwise presented in beginning or introducing something, especially: a. A preface, as to a book. b. Music A short preliminary passage in a larger …
