best economics books for phd students

Books to Study Before Going to Graduate School in Economics

Must Read Books for Pre-Ph.D Economics Students

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Q:  If I want to achieve a Ph.D. in economics what steps would you advise me to take and what books and courses would I need to study to gain the knowledge that is absolutely needed to be able to do and understand the research that is needed for a Ph.D.

A:  Thank you for your question. It's a question that I'm frequently asked, so it's about time that I created a page that I could point people toward.

It's really difficult to give you a general answer, because a lot of it depends on where you'd like to get your Ph.D. from. Ph.D programs in economics vary widely in both quality and scope of what is taught. The approach taken by European schools tends to be different than that of Canadian and American schools. The advice in this article will mainly apply to those who are interested in entering a Ph.D. program in the United States or Canada, but much of the advice should also apply to European programs as well. There are four key subject areas that you'll need to be very familiar with to succeed in a Ph.D. program in economics .

1. Microeconomics / Economic Theory

Even if you plan to study a subject which is closer to Macroeconomics or Econometrics , it is important to have a good grounding in Microeconomic Theory . A lot of work in subjects such as Political Economy and Public Finance are rooted in "micro foundations" so you'll help yourself immensely in these courses if you're already familiar with high level microeconomics. Most schools also require you to take at least two courses in microeconomics, and often these courses are the most difficult you'll encounter as a graduate student.

Microeconomics Material You Must Know as a Bare Minimum

I would recommend reviewing the book Intermediate Microeconomics: A Modern Approach by Hal R. Varian. The newest edition is the sixth one, bu if you can find an older used edition costing less you may want to do that.

Advanced Microeconomics Material that Would be Helpful to Know

Hal Varian has a more advanced book called simply Microeconomic Analysis . Most economics students are familiar with both books and refer to this book as simply "Varian" and the Intermediate book as "Baby Varian". A lot of the material in here is stuff you wouldn't be expected to know entering a program as it's often taught for the first time in Masters and Ph.D. programs. The more you can learn before you enter the Ph.D. program, the better you will do.

What Microeconomics Book You'll Use When You Get There

From what I can tell, Microeconomic Theory by Mas-Colell, Whinston, and Green is standard in many Ph.D. programs. It's what I used when I took Ph.D. courses in Microeconomics at both Queen's University at Kingston and the University of Rochester. It's an absolutely massive book, with hundreds and hundreds of practice questions. The book is quite difficult in parts so you'll want to have a good background in microeconomic theory before you tackle this one.

2. Macroeconomics

Giving advice on Macroeconomics books is a lot more difficult because Macroeconomics is taught so differently from school to school. Your best bet is to see what books are used in the school that you would like to attend. The books will be completely different depending on whether your school teaches more Keynesian style Macroeconomics or "Freshwater Macro" which is taught at places like "The Five Good Guys" which includes the University of Chicago, the University of Minnesota, Northwestern University, University of Rochester, and University of Pennsylvania.

The advice I'm going to give is for students who are going to a school that teaches more of a "Chicago" style approach.

Macroeconomics Material You Must Know as a Bare Minimum

I would recommend reviewing the book Advanced Macroeconomics by David Romer. Although it does have the word "Advanced" in the title, it's more suited for high level undergraduate study. It does have some Keynesian material as well. If you understand the material in this book, you should do well as a graduate student in Macroeconomics.

Advanced Macroeconomics Material that would be Helpful to Know

Instead of learning more Macroeconomics, it would be more helpful to learn more on dynamic optimization. See my section on Math Economics books for more detail.

What Macroeconomics Book You'll Use When You Get There

When I took Ph.D courses in Macroeconomics a few years ago we didn't really use any textbooks, instead we discussed journal articles. This is the case in most courses at the Ph.D. level. I was fortunate enough to have macroeconomics courses taught by Per Krusell and Jeremy Greenwood and you could spend an entire course or two just studying their work. One book that is used quite often is Recursive Methods in Economic Dynamics by Nancy L. Stokey and Robert E. Lucas Jr. Although the book is almost 15 years old, it's still quite useful for understanding the methodology behind many macroeconomics articles. I've also found Numerical Methods in Economics by Kenneth L. Judd to be quite helpful when you're trying to obtain estimates from a model which does not have a closed-form solution.

3. Econometrics Material You Must Know as a Bare Minimum

There's quite a few good undergraduate texts on Econometrics out there. When I taught tutorials in undergraduate Econometrics last year, we used Essentials of Econometrics by Damodar N. Gujarati. It's as useful as any other undergraduate text I've seen on Econometrics. You can usually pick up a good Econometrics text for very little money at a large second-hand book shop. A lot of undergraduate students can't seem to wait to discard their old econometrics materials.

Advanced Econometrics Material that would be Helpful to Know

I've found two books rather useful: Econometrics Analysis by William H. Greene and A Course in Econometrics by Arthur S. Goldberger. As in the Microeconomics section, these books cover a lot of material which is introduced for the first time at the graduate level. The more you know going in, though, the better chance you'll have of succeeding.

What Econometrics Book You'll Use When You Get There

Chances are you'll encounter the king of all Econometrics books Estimation and Inference in Econometrics by Russell Davidson and James G. MacKinnon. This is a terrific text, because it explains why things work like they do, and does not treat the matter as a "black box" like many econometrics books do. The book is quite advanced, though the material can be picked up fairly quickly if you have a basic knowledge of geometry.

4. Mathematics

Having a good understanding of mathematics is crucial to success in economics. Most undergraduate students, particularly those coming from North America, are often shocked by how mathematical graduate programs in economics are. The math goes beyond basic algebra and calculus, as it tends to be more proofs, such as "Let (x_n) be a Cauchy sequence. Show that if (X_n) has a convergent subsequence then the sequence is itself convergent". I've found that the most successful students in the first year of a Ph.D. program tend to be ones with mathematics backgrounds, not economics ones. That being said, there's no reason why someone with an economics background can not succeed.

Mathematical Economics Material You Must Know as a Bare Minimum

You'll certainly want to read a good undergraduate "Mathematics for Economists" type book. The best one that I've seen happens to be called Mathematics for Economists written by Carl P. Simon and Lawrence Blume. It has a quite diverse set of topics, all of which are useful tools for economic analysis.

If you're rusty on basic calculus, make sure you pick up a 1st year undergraduate calculus book. There are hundreds and hundreds of different ones available, so I'd suggest looking for one in a second hand shop. You may also want to review a good higher level calculus book such as Multivariable Calculus by James Stewart.

You should have at least a basic knowledge of differential equations, but you do not have to be an expert in them by any means. Reviewing the first few chapters of a book such as Elementary Differential Equations and Boundary Value Problems by William E. Boyce and Richard C. DiPrima would be quite useful. You do not need to have any knowledge of partial differential equations before entering graduate school, as they are generally only used in very specialized models.

If you're uncomfortable with proofs, you may want to pick up The Art and Craft of Problem Solving by Paul Zeitz. The material in the book has almost nothing to do with economics, but it will help you greatly when working on proofs. As an added bonus a lot of the problems in the book are surprisingly fun.

The more knowledge you have of pure mathematics subjects such as Real Analysis and Topology, the better. I would recommend working on as much of Introduction to Analysis by Maxwell Rosenlicht as you possibly can. The book costs less than $10 US but it is worth its weight in gold. There are other analysis books that are slightly better, but you cannot beat the price. You may also want to look at the Schaum's Outlines - Topology and Schaum's Outlines - Real Analysis . They're also quite inexpensive and have hundreds of useful problems. Complex analysis, while quite an interesting subject, will be of little use to a graduate student in economics, so you need not worry about it.

Advanced Mathematical Economics that would be Helpful to Know

The more real analysis you know, the better you will do. You may want to see one of the more canonical texts such as The Elements of Real Analysis by Robert G. Bartle. You may also want to look at the book I recommend in the next paragraph.

What Advanced Mathematical Economics Book You'll Use When You Get There

At the University of Rochester we used a book called A First Course in Optimization Theory by Rangarajan K. Sundaram, though I don't know how widely this is used. If you have a good understanding of real analysis, you will have no trouble with this book, and you'll do quite well in the obligatory Mathematical Economics course they have in most Ph.D. programs.

You do not need to study up on more esoteric topics such as Game Theory or International Trade before you enter a Ph.D. program, although it never hurts to do so. You are not usually required to have a background in those subject areas when you take a Ph.D. course in them. I will recommend a couple of books I greatly enjoy, as they may convince you to study these subjects. If you're at all interested in Public Choice Theory or Virginia style Political Economy, first you should read my article " The Logic of Collective Action ". After doing so, you may want to read the book Public Choice II by Dennis C. Mueller. It is very academic in nature, but it is probably the book that has influenced me most as an economist. If the movie A Beautiful Mind didn't make you frightened of the work of John Nash you may be interested in A Course in Game Theory by Martin Osborne and Ariel Rubinstein. It is an absolutely fabulous resource and, unlike most books in economics, it's well written.

If I haven't scared you off completely from studying economics , there's one last thing you'll want to look into. Most schools require you to take one or two tests as part of your application requirements. Here's a few resources on those tests:

Get familiar with the GRE General and GRE Economics Tests

The Graduate Record Examination or GRE General test is one of the application requirements at most North American schools. The GRE General test covers three areas: Verbal, Analytical, and Math. I've created a page called "Test aids for the GRE and GRE Economics" that has quite a few useful links on the GRE General Test. The Graduate School Guide also has some useful links on the GRE. I would suggest buying one of the books on taking the GRE. I can't really recommend any one of them as they all seem equally good.

It is absolutely vital that you score at least 750 (out of 800) on the math section of the GRE in order to get into a quality Ph.D. program. The analytical section is important as well, but the verbal not as much. A great GRE score will also help you get into schools if you have only a modest academic record.

There are a lot fewer online resources for the GRE Economics test. There are a couple of books that have practice questions that you may want to look at. I thought the book The Best Test Preparation for the GRE Economics was quite useful, but it's gotten absolutely horrid reviews. You may want to see if you can borrow it before committing to buying it. There is also a book called Practicing to Take the GRE Economics Test but I've never used it so I'm not sure how good it is. It is important to study for the test, as it may cover some material that you did not study as an undergraduate. The test is very heavily Keynesian, so if you did your undergraduate work at a school heavily influenced by the University of Chicago such as the University of Western Ontario, there will be quite a bit of "new" macroeconomics you'll need to learn.

Economics can be a great field in which to do your Ph.D., but you need to be properly prepared before you enter into a graduate program. I haven't even discussed all the great books available in subjects such as Public Finance and Industrial Organization.

• Choosing the Best Economics Graduate Program
• What Is Mathematical Economics?
• Why Get an Economics Ph.D?
• Real Analysis
• What You Should Know Before Applying to an Economics PhD Program
• Positive Versus Normative Analysis in Economics
• What Is International Economics?
• Ace Your Econometrics Test
• Biography of Adam Smith, Founding Father of Economics
• The Basic Assumptions of Economics
• Good Reasons to Study Economics
• What Is Behavioral Economics?
• What Are the Various Subfields of Economics?
• Economics for Beginners: Understanding the Basics
• Defining Managerial Entrenchment

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What are some good graduate-level econometrics books for someone with a strong mathematics background?

Related: Book recommendations on empirical methods in economic research and econometrics?

I would like to focus mainly on graduate texts in Econometrics . From the question above, I gather that Wooldridge's text is nice.

In terms of "strong math background," I did my undergrad in Statistics, consisting of two semesters each of linear algebra, real analysis, and abstract algebra, along with a measure-theoretic probability course.

What are some econometrics texts that you would recommend for me? I learned some intro econometrics in a course which taught from Studenmund but was extremely bored.

• econometrics
• reference-request

• 1 $\begingroup$ Are there particular areas that interest you, like causal inference, structural, time-series? $\endgroup$ –  dimitriy Commented Dec 5, 2014 at 22:30
• $\begingroup$ @DimitriyV.Masterov: I don't claim to know a ton about econometrics, but I definitely would be interested in casual inference and time-series. $\endgroup$ –  Clarinetist Commented Dec 5, 2014 at 22:31
• $\begingroup$ Can we again have one main reference per answer? That way people could vote single books. Was a suggestion in the other question and I feel it worked great. $\endgroup$ –  FooBar Commented Dec 5, 2014 at 23:09
• 1 $\begingroup$ An excellent treatment (published 1991) you may want to look into hup.harvard.edu/catalog.php?isbn=9780674175440 . I would also second: amazon.com/Primer-Econometric-Theory-MIT-Press/dp/0262034905 $\endgroup$ –  PatrickT Commented Mar 13, 2018 at 11:39

4 Answers 4

"Adult" Wooldridge is great intro to various microeconometrics topics.

For time series, Hamilton's Time Series and Lutkepohl's Introduction to Multiple Time Series Analysis are both nice, though Hamilton is a bit dated and Lutkepohl is more focused.

As far as more foundational, rigorous material, Herman Bierens has a short Introduction to the Mathematical and Statistical Foundations of Econometrics. Gourieroux and Monfort have a whole flock of graduate econometrics texts, but to quote an anonymous reviewer, they are "in the French tradition of excellent precision and terrible pedagogics," though they have their champions.

• 1 $\begingroup$ The Wooldridge book that @Dimitriy is talking about is "Econometric Analysis of Cross Section and Panel Data." "Baby" Wooldridge is "Introductory Econometrics: A Modern Approach." $\endgroup$ –  jmbejara Commented Dec 5, 2014 at 23:02
• 1 $\begingroup$ (+1) for also relaying the comment on Gourieroux and Monfort. $\endgroup$ –  Alecos Papadopoulos Commented Dec 5, 2014 at 23:06
• $\begingroup$ Thank you for telling me about Wooldridge. I have really enjoyed the text and it is right up my alley. :) $\endgroup$ –  Clarinetist Commented Jan 24, 2015 at 20:22

I repeat part of my answer in the question the OP already mentioned with some additional proposals:

Since you have a background in Statistics "Probability Theory and Statistical Inference: Econometric Modeling with Observational Data" 1999, by A. Spanos, provides the statistical foundations of econometrics in a way no other book does.

"Econometrics" by Hayasi , because, except of presenting a new synthesis focused around Extremum Estimators (i.e. Maximum Likelihood and Generalized Method of Moments), and of giving space to Time Series, Unit root econometrics and Co-integration, it has theoretical depth alongside very practical applications, a combination which is not usually found.

For Time-series, I don't believe you can ignore

Hamilton's Time Series Analysis" ,

" Lutkepohl's "Introduction to Multiple Time Series" which has gone into its 2nd ed. as "New Introduction to Multiple Time Series" (my experience is from the first edition).

• $\begingroup$ A book's "theoretical depth" is questionable when "measurability" appears exactly once in the book and is in quotes. $\endgroup$ –  Michael Commented Dec 6, 2014 at 14:41
• 3 $\begingroup$ @Michael And since when the concept of "measurability" and related, became the standard to measure theoretical depth? $\endgroup$ –  Alecos Papadopoulos Commented Dec 6, 2014 at 15:01

Can't forget "Econometric Analysis" by William Greene . It's in its 7th edition . It seems to get referenced lot. It sometimes skips over some detail but it does cover a broad range of topics. (Though I do like the pedagogical approach of something like Hayashi better, I think Greene might cover more ground.)

I am tempted to deviate from other answers and suggest that the best Econometrics textbook for someone with a strong enough mathematical background might not be a "mathematically-minded" econometrics textbook, but rather a textbook that focuses on "empirical methods and economics research", the best of which at the moment seems to remain:

Mostly Harmless Econometrics ( https://www.mostlyharmlesseconometrics.com/ )

Since you already have a strong mathematical background --- and unless you're specifically interested in the mathematical aspects of econometrics --- you are likely to learn much more (and find much more inspiration) from a book that starts and ends with a strong focus on causal inference and research design.

(This being said, by all means, do consult other answers in particular if you want to feed your interest in time-series analysis which is not covered much --- if at all --- in Mostly Harmless)

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• Must read books for economics students

If you’re curious about the world around us and want to know more about the production, distribution and consumption of wealth, you may be thinking about studying economics.

But before you enrol on an economics course to learn more, it’s a good idea to get a head start on your reading. Not only will this help you decide whether economics is a subject you really want to take, but if it is, you’ll have an advantage over your peers from day one.

From pocket-sized overviews to thousand-page tomes, there are countless books on economic theory and economic history to suit all academic abilities and curiosity levels. But if you’re struggling to know where to begin, this article on the best economics books might help.

What are the top books for economics students?

Some of the best books on economics include ‘The Armchair Economist’ by Steven E. Landsburg, Michael Lewis’ ‘The Big Short’ and ‘The Undercover Economist’ by Tim Harford.

Books like ‘Economics: A Very Short Introduction’ by Partha Dasgupta and Levitt and Dubner’s ‘Freakonomics’ are ideal for beginners, while one of the best-known economics books, ‘An Enquiry into the Nature and Causes of the Wealth of Nations’ by Adam Smith, delves into the subject in much more detail.

Read on for our full list of must-read books for people studying economics.

Ten of the best economics books for students

1. ‘an enquiry into the nature and causes of the wealth of nations’ by adam smith.

It may have been written way back in 1776, but Smith’s classic is still widely read and held in high regard today.

As the very first scientific argument for the principles of economics, his book paved the way for all subsequent economic theory – and it continues to be recommended by many economists, historians and entrepreneurs.

While it may not be the easiest read, it’s the go-to book for students who want to understand the early theories relating to the basic mechanics of economics.

By giving theories of capital accumulation, secular change and growth and breaking down the interactions among labour, stocks, commodities, trade and taxes, Smith provides insights into 18th-century economics that remain influential in modern economics.

2. ‘Economics: A Very Short Introduction’ by Partha Dasgupta

As the name suggests, this book is ideal for those who are just looking for a brief introduction to economics.

Much lighter than Smith’s ‘The Wealth of Nations’, Dasgupta’s book is more accessible, describing the lives of two children who live completely different lives in very different parts of the world – the American Midwest and Ethiopia.

Combining examples from everyday life with a global approach, he provides an accessible introduction to key economic concepts, such as national policies, individual choices, equity, sustainability, efficiency, development, markets, property rights and public goods.

This pocket-sized economics book forms part of an Oxford University Press series called ‘The Very Short Introductions’, which aims to make challenging, yet interesting topics highly readable. Some of the other ‘Very Short’ economics books you might find useful are: ‘Microeconomics’ by Avinash Dixit and Robert C. Allen’s ‘Global Economic History’.

3. ‘The Big Short: Inside the Doomsday Machine’ by Michael Lewis

You may have seen the film adaptation of this book, which was met with critical acclaim when it was released at the end of 2015. Starring Christian Bale, Ryan Gosling and Brad Pitt, the film won the Academy Award for Best Adapted Screenplay and was also nominated for the Academy Award for Best Picture.

This follows on from the success of the book, which spent 28 weeks on The New York Times Best Sellers list, was shortlisted for the 2010 Financial Times Business Book of the Year Award and received the 2011 Robert E. Kennedy Center for Justice and Human Rights Book Award.

‘The Big Short’ is about the build-up of the United States housing bubble during the 2000s. It describes how several individuals, who believed the housing bubble was going to burst, bet against the market and ended up profiting from the financial crisis of 2007-08, making millions when the market crashed.

4. ‘The Reckoning: Financial Accountability and the Rise and Fall of Nations’ by Jacob Soll

In this book, historian and winner of the MacArthur Foundation’s ‘Genius Grant’, Jacob Soll, charts the development of economics from the dawn of accountancy – with a focus on Western finance.

Rather than giving a technical historical account, it’s more about the social and political side of things, meaning it’s entertaining and accessible for casual readers, while still being of use to scholars and industry professionals.

He writes about the role accounting plays in global affairs, covering periods like the Italian Renaissance, the French Revolution and the financial crisis of 2007-08.

5. ‘Freakonomics: A Rogue Economist Explores the Hidden Side of Everything’ by Steven D. Levitt and Stephen J. Dubner

Another one to read if you’re still unsure as to whether economics is for you, ‘Freakonomics’ is amusing, while inspiring you to see the world through an economic lens.

A controversial New York Times Best Seller, it’s sold more than four million copies, making it one of the most popular economics books of all time.

It tells the stories of drug dealers, real estate agents, and covers issues such as abortion and parenting, exploring why people do what they do and how their actions have an impact on the world around them.

The authors’ intent is to encourage readers to consider the data below the surface and look beyond what they’ve been brought up to believe is true about the world around them.

Like ‘The Big Short’, it’s been made into a film, thanks to its relatability with data, human behaviour and lack of business terminology.

6. ‘The Undercover Economist’ by Tim Harford

If you’ve ever wondered why the gap between the rich and the poor is so great, then this book is for you. It reveals how instrumental economics is in our lives and will help you to understand the world around you slightly better.

Relatable and engaging, Harford highlights the relevancy of economics in everyday life, from buying a cup of coffee to sitting in a traffic jam. He exposes coffee shops, supermarkets and airlines from all over the world for the ways in which they convince us to part with our money.

Covering a wide range of economic concepts, such as limited resources, market power, market failure and inside information, this book sheds light on how what’s going on in different industries can shape our everyday lives – without us even realising it.

7. ‘The Armchair Economist: Economics and Everyday Life’ by Steven E. Landsburg

Again, this book explains the economics of everyday life in a relatable and amusing way, making it another one of the must-reads for those who want to study economics.

It goes further into the reasoning why certain things are happening in our day-to-day lives, yet manages to remain easily digestible.

Landsburg highlights the laws of human behaviour, explaining why corporations give failed executives huge pensions and why concert promoters increase ticket prices even when they know the gig will sell out months in advance.

Some of the other issues he covers include why cinema popcorn is so expensive and why drivers of safer cars have more crashes. The average person may find this fact surprising, but he explains how airbags cause accidents because drivers who believe they have safer cars take more risks. Economists understand that this is because people respond to incentives.

8. ‘Doughnut Economics: Seven Ways to Think Like a 21st Century Economist’ by Kate Raworth

If you feel despairing about the world and how economics has failed to play its part, then Oxford academic Raworth might help you to feel a bit more optimistic.

While she acknowledges that mainstream economics, and its outdated theories, have permitted a world in which the rich get richer while the poor get poorer, she sets out a roadmap for how things can be rectified.

Breaking down what really makes human-beings tick, Raworth highlights the far-reaching implications of ignoring the role of energy and nature’s resources.

Ambitious and radical, this book reframes what economics could be to a new generation of learners.

9. ‘Good Economics for Hard Times’ by Abhijit V. Banerjee and Esther Duflo

Imploring readers to end polarisation and make informed decisions based on data in order to combat the challenges faced by the world we live in, Nobel Prize-winning economists Banerjee and Duflo upend many traditionally-held thoughts, covering subjects like inequality, immigration, climate change and slowing growth.

As well as covering economic efficiency, some of the other topics they tackle include bigotry, extreme political rhetoric and the fluidity and logic of diverse preferences.

The authors demonstrate how we could have the answers to the problems we so often ignore due to our ideologies. They encourage readers to think from a new perspective, which considers the needs of the individual as well as the good of the whole, in appropriate proportions.

Building on cutting-edge research in economics and years of exploring solutions for how to alleviate extreme poverty, their book makes a convincing case for a society built on respect and compassion.

10. ‘23 Things They Don’t Tell You About Capitalism’ by Ha-Joon Chang

Chang’s revelatory book identifies some of the biggest myths in society today and turns them on their head, showing us an alternative view of the world.

Some of the concepts he puts forward are that there’s no such thing as a “free” market, poor countries are more entrepreneurial than rich ones, globalisation isn’t making the world richer and higher-paid managers don’t produce better results. He also explains how we don’t live in a digital world, because the washing machine has changed lives more than the internet.

Note that this isn’t an anti-capitalist text, though, with Chang himself stating at the beginning of the book that he believes “capitalism is still the best economic system that humanity has invented.”

Whether you want to dip your toes into the subject before you decide to enrol on a course, or you’ve always known you wanted to be an economics student, there are countless books on economic theories to choose from.

From brief introductions to in-depth volumes, you might feel overwhelmed by the amount of reading material available, but we hope our list of top ten books on economic thought provides you with a good starting point.

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Graduate Economics Books

This page provides a listing, broken down by field, of the most popular graduate-level economics books.

Microeconomics

• Microeconomic Theory (Andreu Mas-Colell, Michael D. Whinston, Jerry R. Green)
• Microeconomic Analysis (Hal R. Varian)
• Advanced Microeconomic Theory (Geoffrey A. Jehle, Philip J. Reny)
• A Course in Microeconomic Theory (David M. Kreps)
• Microeconomic Foundations I: Choice and Competitive Markets (David M. Kreps)

Macroeconomics

• Recursive Macroeconomic Theory (Lars Ljungqvist, Thomas J. Sargent)
• Dynamic Economics: Quantitative Methods and Applications (Jerome Adda, Russell W. Cooper), Kindle edition
• Advanced Macroeconomics (David Romer), Kindle edition
• Introduction to Modern Economic Growth (Daron Acemoglu), Kindle edition
• Economic Growth (Robert J. Barro, Xavier Sala-i-Martin), Kindle edition
• Recursive Methods in Economic Dynamics (Nancy L. Stokey, Robert E. Lucas Jr.) ( solutions manual )
• Lectures on Macroeconomics (Olivier Jean Blanchard, Stanley Fischer)

Econometrics

• Mostly Harmless Econometrics (Joshua D. Angrist, Jorn-Steffen Pischke), Kindle edition
• A Guide to Econometrics (Peter Kennedy)
• Econometric Analysis of Cross Section and Panel Data (Jeffrey M. Wooldridge) ( solutions manual ), Kindle edition
• Econometrics (Fumio Hayashi), Kindle edition
• Microeconometrics: Methods and Applications (A. Colin Cameron, Pravin K. Trivedi)
• Time Series Analysis (James D. Hamilton)
• Econometric Analysis (William H. Greene), Kindle edition
• Statistical Inference (George Casella, Roger L. Berger)

International Economics

• Foundations of International Macroeconomics (Maurice Obstfeld, Kenneth S. Rogoff)
• Advanced International Trade: Theory and Evidence (Robert C. Feenstra), Kindle edition

Game Theory, Auction Theory, Industrial Organization

• Social and Economic Networks (Matthew O. Jackson), Kindle edition
• Game Theory for Applied Economists (Robert Gibbons), Kindle edition
• Contract Theory (Patrick Bolton, Mathias Dewatripont) ( solutions manual ), Kindle edition
• Game Theory: Analysis of Conflict (Roger B. Myerson)
• Game Theory (Drew Fudenberg, Jean Tirole)
• Auction Theory (Vijay Krishna), Kindle edition
• A Course in Game Theory (Martin J. Osborne, Ariel Rubinstein)
• The Theory of Industrial Organization (Jean Tirole), Kindle edition

Mathematical and Numerical Methods

• Mathematics for Economists (Carl P. Simon, Lawrence E. Blume)
• A First Course in Optimization Theory (Rangarajan K. Sundaram)
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• An Introduction to Mathematical Analysis for Economic Theory and Econometrics (Dean Corbae, Maxwell B. Stinchcombe, Juraj Zeman), Kindle edition
• Infinite Dimensional Analysis: A Hitchhiker's Guide (Charalambos D. Aliprantis, Kim C. Border)
• Fundamental Methods of Mathematical Economics (Kevin Wainwright, Alpha Chiang)

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7 books to read if you’re an economics student

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Table of contents

• Introduction

Freakonomics by Steven D. Levitt and Stephen J. Dubner

Thinking, fast and slow by daniel kahneman and amos tversky, the undercover economist by tim harford, 23 things they don’t tell you about capitalism by ha-joon chang, animal spirits by akerlof and shiller, the armchair economist by steven e. landsburg, the black swan: the impact of the highly improbable by nissim nocholas taleb.

If you’re already an economics student, or are about to start an economics course at university, you probably don’t want to sit through more drab, dull economics textbooks. ‘Why isn’t there a fun way to learn this stuff?’ you think. Fear not! We have selected seven of the most entertaining books out there (which just so happen to be about economics…) Read on, and before you know it, you’ll have tons of interesting economics knowledge, without even realizing you’ve learnt it.

Freakonomics has often been described as one of the most popular economics books of all time – and there is a reason for this! If you’ve ever wondered why drug dealers tend to live with their mothers, what real estate agents and the KKK have in common, and which is more dangerous: a gun or a swimming pool, then this is the book for you. Freakonomics answers the questions that no one thought to ask – because they were just too absurd! The first of its kind, this novel manages to both amuse you, and make you start seeing the world from an economics perspective – perfect for an economics student!

Written by Nobel Prize winner, Daniel Kahneman, and mathematical psychologist, Amos Tversky, this is an incredibly insightful book, which challenges the classical economic assumption that people always act rationally. For example, this book explains why it is that we are more likely to believe something written in bold type, and why we are more likely to believe that attractive people are more competent. It’s a novel that helps us understand both the decisions we make ourselves, as well as the decisions made by those around us. Not only does reading this help you make better decisions, but it gives an excellent insight into behavioral economics, which will definitely help you on your economics course at some point.

This book has to be one of my personal favorites on this list. Mainly because it opens by explaining why the Starbucks in a London train station charges so much for coffee, and continues to talk through similar real life, relatable scenarios.  This is a book which shows you that economics plays a massive part in every section of your life, and how knowing about the economics behind these everyday things can help you understand the world slightly better.

This book takes the biggest myths in society today and turns them upside down and inside out. For example, it explains why the washing machine has changed lives more than the internet. Chang explains at the start of the novel that despite the name, the book is by no means anti-capitalist and aims not to take sides but to explain the realities, although he does say “despite its problems and limitations, I believe that capitalism is still the best economic system that humanity has invented.” This one will have you questioning everything you know.

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Animal Spirits makes for slightly heavier reading than some of the books on this list, but it’s also one of the most important ones. The book discusses the role played by emotions in economic decision making, which is really interesting, and at the same time gives an excellent overview of basic Keynesian ideas, which is extremely useful if you’re either going into an economics degree course, or currently studying one. Also, this book is loved by lecturers, so you’ll get major brownie points by saying you’ve read it.

The Armchair Economist is a lot like Freakanomics and The Undercover Economist in the way it explains the economics of everyday life, in an amusing and relatable way. The author recognizes this in the intro and explains “Freakonomics is out to dazzle you with facts; The Armchair Economist is out to dazzle you with logic.” You should read The Armchair Economist if you want answers to questions such as ‘Why is it that the safer a car gets, the more crashes the driver has?’ and ‘How much would the average person risk their life for a Starbucks mocha frappachino?’ Don’t act like you don’t want to know!

This one was on my suggested reading list for my economics course, and although it can be quite dense in parts, the general idea is really cool! The central idea in the book is that even if an event is extremely improbable, such as a black swan existing when no one had ever seen one, it doesn’t mean the event is impossible (as black swans do exist). The book goes on to explain how a significant unexpected event can have massive consequences. This one is also liked by economic lecturers, just in case you were wondering, and is a good one to bring up in class.

Hopefully there will have been something on that list that takes your fancy. Each of the books on the list will give you a good insight into at least one economic theory, and you will be able to reference them in essays etc. whilst at uni, so they are definitely worth a read.

Happy reading!

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As Content Editor for TopUniversities.com and TopMBA.com, Chloe creates and publishes a wide range of articles for universities and business schools across the world. Chloe has a Bachelor’s degree in Economics from the University of Reading and grew up in Leicestershire, UK. 

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Introductions to Economics

• Freakonomics , Steven D. Levitt and Stephen J. Dubner In Freakonomics , authors Steven D. Levitt and Stephen J. Dubner unpack how people respond to incentives by investigating seemingly non-economic subjects like how parents pick names for their children and even how the legalization of abortion could be responsible for a drop in crime. Provocative and entertaining, Freakonomics is a crash course in the populist application of economics.
• The Armchair Economist: Economics and Everyday Life , Steven E. Landsburg Steven Landsburg argues that economics can be boiled down to four words: people respond to incentives. The book gives readers a layman's introduction to economics through incentives and their implications, good and bad, and how all aspects of our life are influenced by them. The Armchair Economist is also a good introduction to the so-called “Chicago school” of economics, of which Landsburg is himself a member.
• Naked Economics: Undressing the Dismal Science , Charles Wheelan If you are looking for a refresher in economics or an introduction to the broad strokes of the subject, Naked Economics is for you. Charles Wheelan starts with one basic premise, that people seek to maximize their utility, and expands into a larger exploration of free market theory and its implications.
• Misbehaving: The Making of Behavioral Economics , Richard H. Thaler In Misbehaving , Richard Thaler examines how the “rational actor” assumption often used in economic theory misunderstands how humans think and act. The book focuses on how human misbehavior has consequences that appear no matter how large or small a decision appears to be. Misbehaving is an impressive account of the major development in behavioral economics over the last half-century.

Fundamental Economics Texts

• Capitalism and Freedom , Milton Friedman Milton Friedman's iconic work argues that economic freedom is essential to a free and liberal society. Published in 1962, many of Friedman's theories presented in Capitalism and Freedom have since been adopted worldwide. Friedman’s work ranks among the top 100 non-fiction books written in English in the last century, according to Time Magazine.
• The Wealth of Nations , Adam Smith One of the most essential economics texts, The Wealth of Nations forms the underpinning of much of modern economic theory. For many students of economics, Wealth of Nations is the first book assigned in class, but rereading this fundamental text can provide a deeper understanding of both the foundations of economics and its transformation over the last 300 years.
• The Affluent Society , John Kenneth Galbraith Affluent Society offers a contradictory view of the “conventional wisdom” underpinning modern economic theories and principles. John Galbraith argues in his iconic work the conventional wisdom of economics is fundamentally flawed because the theory of economics came into being in the late eighteenth and early nineteenth centuries and is poorly suited to explain the mechanisms of the affluent post-WW2 U.S. economy.

Field-Specific Economics Books

• The Bottom Billion: Why the Poorest Countries are Failing and What Can Be Done About It , Paul Collier If your interest is working as an economist in international development or with international aid agencies, The Bottom Billion is a must read. Paul Collier challenges the notion that the best way to help the poor in struggling economies is with a cash infusion. Rather, Collier argues, a more hands-on approach is the solution.
• The Travels of a T-Shirt in a Global Economy , Pietra Rivoli For a look at how globalization and free trade impact the cost of goods, look no further than The Travels of a T-Shirt in a Global Economy . Pietra Rivoli's book provides a way to see globalization, a deeply complicated issue, through the production of a single t-shirt. For economics students interested in working in the fields of international trade or monetary policy, Travels of a T-Shirt is a must-read.
• Plunder and Blunder: The Rise and Fall of the Bubble Economy , Dean Baker Plunder and Blunder offers a look at the causes of the housing bubble that precipitated the 2001 and 2007 market crashes. Dean Baker analyzes the causes and effects of the crash, why people ignored the signs of an oncoming economic disaster and what can be done to prevent future financial bubbles.

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Advanced Macroeconomics

An easy guide, filipe campante , affiliation: johns hopkins university, us close federico sturzenegger , affiliation: universidad de san andrés, ar close andrés velasco affiliation: london school of economics and political science, gb profiles: id close.

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Macroeconomic policy is one of the most important policy domains, and the tools of macroeconomics are among the most valuable for policy makers. Yet there has been, up to now, a wide gulf between the level at which macroeconomics is taught at the undergraduate level and the level at which it is practiced. At the same time, doctoral-level textbooks are usually not targeted at a policy audience, making advanced macroeconomics less accessible to current and aspiring practitioners.

This book, born out of the Masters course the authors taught for many years at the Harvard Kennedy School, fills this gap. It introduces the tools of dynamic optimization in the context of economic growth, and then applies them to a wide range of policy questions – ranging from pensions, consumption, investment and finance, to the most recent developments in fiscal and monetary policy. It does so with the requisite rigor, but also with a light touch, and an unyielding focus on their application to policy-making, as befits the authors’ own practical experience.

Advanced Macroeconomics: An Easy Guide is bound to become a great resource for graduate and advanced undergraduate students, and practitioners alike.

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“ This terrifically useful text fills the considerable gap between standard intermediate macroeconomics texts and the more technical text aimed at PhD economics courses. The authors cover the core models of modern macroeconomics with clarity and elegance, filling in details that PhD texts too often leave out. At the same time, the authors draw on their own extensive policy experience to provide thoughtful policy motivation and historical context throughout. Advanced undergraduates, public policy students and indeed many economics PhD students will find it a pleasure to read, and a valuable long-term resource .” — Kenneth Rogoff (Thomas D. Cabot Professor of Public Policy and Professor of Economics at Harvard University, former Chief Economist and Director of Research at the IMF)

“ This is an excellent and highly rigorous yet accessible guide to fundamental macroeconomic frameworks that underpin research and policy making in the world. The content reflects the unique perspective of authors who have worked at the highest levels of both government and academia. This makes the book essential reading for serious practitioners, students, and researchers .” — Gita Gopinath (John Zwaanstra Professor of International Studies and of Economics at Harvard University, Chief Economist and Director of Research at the IMF)

“ The words Advanced and Easy rarely belong together, but this book gets as close as possible. It covers macroeconomics from the classic fundamentals to the fancy and creative innovations necessary to anyone interested in keeping up with both the policy and the academic worlds. ” — Arminio Fraga (former president, Central Bank of Brazil)

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Part 1: growth theory, growth theory preliminaries, the neoclassical growth model, an application: the small open economy, endogenous growth models i: escaping diminishing returns, endogenous growth models ii: technological change, proximate and fundamental causes of growth, part 2: overlapping generations models, overlapping generations models, an application: pension systems and transitions, unified growth theory, part 3: consumption and investment, consumption, consumption under uncertainty and macro finance, part 4: short term fluctuations, real business cycles, (new) keynesian theories of fluctuations: a primer, unemployment, part 5: monetary and fiscal policy, fiscal policy i: public debt and the effectiveness of fiscal policy, fiscal policy ii: the long-run determinants of fiscal policy, monetary policy: an introduction, rules vs discretion, recent debates in monetary policy, new developments in monetary and fiscal policy, appendix a: very brief mathematical appendix, appendix b: simulating an rbc model, appendix c: simulating a dsge model, disciplines:, view wikipedia concepts, hide wikipedia concepts, book reviews (1):, review from 08 feb 2022: international review of economics education, advanced macroeconomics: an easy guide, f. campante, f. sturzenegger, a. velasco , lse press, london (2021), p. 421, isbn (pdf): 9781909890695.

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Econometrics is the quantitative language of economic theory, analysis, and empirical work, and it has become a cornerstone of graduate economics programs. Econometrics provides graduate and PhD students with an essential introduction to this foundational subject in economics and serves as an invaluable reference for researchers and practitioners. This comprehensive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of econometrics.

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• 1.1 What Is Econometrics?
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• 4.24 Technical Proofs*
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• 5.1 Introduction
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• 6.1 Introduction
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• 7.4 Joint Distribution
• 7.5 Consistency of Error Variance Estimators
• 7.6 Homoskedastic Covariance Matrix Estimation
• 7.7 Heteroskedastic Covariance Matrix Estimation
• 7.8 Summary of Covariance Matrix Notation
• 7.9 Alternative Covariance Matrix Estimators*
• 7.10 Functions of Parameters
• 7.11 Asymptotic Standard Errors
• 7.12 t-Statistic
• 7.13 Confidence Intervals
• 7.14 Regression Intervals
• 7.15 Forecast Intervals
• 7.16 Wald Statistic
• 7.17 Homoskedastic Wald Statistic
• 7.18 Confidence Regions
• 7.19 Edgeworth Expansion*
• 7.20 Uniformly Consistent Residuals*
• 7.21 Asymptotic Leverage*
• 7.22 Exercises
• 8.1 Introduction
• 8.2 Constrained Least Squares
• 8.3 Exclusion Restriction
• 8.4 Finite Sample Properties
• 8.5 Minimum Distance
• 8.6 Asymptotic Distribution
• 8.7 Variance Estimation and Standard Errors
• 8.8 Efficient Minimum Distance Estimator
• 8.9 Exclusion Restriction Revisited
• 8.10 Variance and Standard Error Estimation
• 8.11 Hausman Equality
• 8.12 Example: Mankiw, Romer, and Weil (1992)
• 8.13 Misspecification
• 8.14 Nonlinear Constraints
• 8.15 Inequality Restrictions
• 8.16 Technical Proofs*
• 8.17 Exercises
• 9.1 Introduction
• 9.2 Hypotheses
• 9.3 Acceptance and Rejection
• 9.4 Type I Error
• 9.5 T-Tests
• 9.6 Type II Error and Power
• 9.7 Statistical Significance
• 9.8 p-Values
• 9.9 t-Ratios and the Abuse of Testing
• 9.10 Wald Tests
• 9.11 Homoskedastic Wald Tests
• 9.12 Criterion-Based Tests
• 9.13 Minimum Distance Tests
• 9.14 Minimum Distance Tests under Homoskedasticity
• 9.15 F Tests
• 9.16 Hausman Tests
• 9.17 Score Tests
• 9.18 Problems with Tests of Nonlinear Hypotheses
• 9.19 Monte Carlo Simulation
• 9.20 Confidence Intervals by Test Inversion
• 9.21 Multiple Tests and Bonferroni Corrections
• 9.22 Power and Test Consistency
• 9.23 Asymptotic Local Power
• 9.24 Asymptotic Local Power, Vector Case
• 9.25 Exercises
• 10.1 Introduction
• 10.2 Example
• 10.3 Jackknife Estimation of Variance
• 10.4 Example
• 10.5 Jackknife for Clustered Observations
• 10.6 The Bootstrap Algorithm
• 10.7 Bootstrap Variance and Standard Errors
• 10.8 Percentile Interval
• 10.9 The Bootstrap Distribution
• 10.10 The Distribution of the Bootstrap Observations
• 10.11 The Distribution of the Bootstrap Sample Mean
• 10.12 Bootstrap Asymptotics
• 10.13 Consistency of the Bootstrap Estimate of Variance
• 10.14 Trimmed Estimator of Bootstrap Variance
• 10.15 Unreliability of Untrimmed Bootstrap Standard Errors
• 10.16 Consistency of the Percentile Interval
• 10.17 Bias-Corrected Percentile Interval
• 10.18 BCa Percentile Interval
• 10.19 Percentile-t Interval
• 10.20 Percentile-t Asymptotic Refinement
• 10.21 Bootstrap Hypothesis Tests
• 10.22 Wald-Type Bootstrap Tests
• 10.23 Criterion-Based Bootstrap Tests
• 10.24 Parametric Bootstrap
• 10.25 How Many Bootstrap Replications?
• 10.26 Setting the Bootstrap Seed
• 10.27 Bootstrap Regression
• 10.28 Bootstrap Regression Asymptotic Theory
• 10.29 Wild Bootstrap
• 10.30 Bootstrap for Clustered Observations
• 10.31 Technical Proofs*
• 10.32 Exercises
• 11.1 Introduction
• 11.2 Regression Systems
• 11.3 Least Squares Estimator
• 11.4 Expectation and Variance of Systems Least Squares
• 11.5 Asymptotic Distribution
• 11.6 Covariance Matrix Estimation
• 11.7 Seemingly Unrelated Regression
• 11.8 Equivalence of SUR and Least Squares
• 11.9 Maximum Likelihood Estimator
• 11.10 Restricted Estimation
• 11.11 Reduced Rank Regression
• 11.12 Principal Component Analysis
• 11.13 Factor Models
• 11.14 Approximate Factor Models
• 11.15 Factor Models with Additional Regressors
• 11.16 Factor-Augmented Regression
• 11.17 Multivariate Normal*
• 11.18 Exercises
• 12.1 Introduction
• 12.2 Overview
• 12.3 Examples
• 12.4 Endogenous Regressors
• 12.5 Instruments
• 12.6 Example: College Proximity
• 12.7 Reduced Form
• 12.8 Identification
• 12.9 Instrumental Variables Estimator
• 12.10 Demeaned Representation
• 12.11 Wald Estimator
• 12.12 Two-Stage Least Squares
• 12.13 Limited Information Maximum Likelihood
• 12.14 Split-Sample IV and JIVE
• 12.15 Consistency of 2SLS
• 12.16 Asymptotic Distribution of 2SLS
• 12.17 Determinants of 2SLS Variance
• 12.18 Covariance Matrix Estimation
• 12.19 LIML Asymptotic Distribution
• 12.20 Functions of Parameters
• 12.21 Hypothesis Tests
• 12.22 Finite Sample Theory
• 12.23 Bootstrap for 2SLS
• 12.24 The Peril of Bootstrap 2SLS Standard Errors
• 12.25 Clustered Dependence
• 12.26 Generated Regressors
• 12.27 Regression with Expectation Errors
• 12.28 Control Function Regression
• 12.29 Endogeneity Tests
• 12.30 Subset Endogeneity Tests
• 12.31 Overidentification Tests
• 12.32 Subset Overidentification Tests
• 12.33 Bootstrap Overidentification Tests
• 12.34 Local Average Treatment Effects
• 12.35 Identification Failure
• 12.36 Weak Instruments
• 12.37 Many Instruments
• 12.38 Testing for Weak Instruments
• 12.39 Weak Instruments with k2 > 1
• 12.40 Example: Acemoglu, Johnson, and Robinson (2001)
• 12.41 Example: Angrist and Krueger (1991)
• 12.42 Programming
• 12.43 Exercises
• 13.1 Introduction
• 13.2 Moment Equation Models
• 13.3 Method of Moments Estimators
• 13.4 Overidentified Moment Equations
• 13.5 Linear Moment Models
• 13.6 GMM Estimator
• 13.7 Distribution of GMM Estimator
• 13.8 Efficient GMM
• 13.9 Efficient GMM versus 2SLS
• 13.10 Estimation of the Efficient Weight Matrix
• 13.11 Iterated GMM
• 13.12 Covariance Matrix Estimation
• 13.13 Clustered Dependence
• 13.14 Wald Test
• 13.15 Restricted GMM
• 13.16 Nonlinear Restricted GMM
• 13.17 Constrained Regression
• 13.18 Multivariate Regression
• 13.19 Distance Test
• 13.20 Continuously Updated GMM
• 13.21 Overidentification Test
• 13.22 Subset Overidentification Tests
• 13.23 Endogeneity Test
• 13.24 Subset Endogeneity Test
• 13.25 Nonlinear GMM
• 13.26 Bootstrap for GMM
• 13.27 Conditional Moment Equation Models
• 13.28 Technical Proofs*
• 13.29 Exercises
• 14.1 Introduction
• 14.2 Examples
• 14.3 Differences and Growth Rates
• 14.4 Stationarity
• 14.5 Transformations of Stationary Processes
• 14.6 Convergent Series
• 14.7 Ergodicity
• 14.8 Ergodic Theorem
• 14.9 Conditioning on Information Sets
• 14.10 Martingale Difference Sequences
• 14.11 CLT for Martingale Differences
• 14.12 Mixing
• 14.13 CLT for Correlated Observations
• 14.14 Linear Projection
• 14.15 White Noise
• 14.16 The Wold Decomposition
• 14.17 Lag Operator
• 14.18 Autoregressive Wold Representation
• 14.19 Linear Models
• 14.20 Moving Average Process
• 14.21 Infinite-Order Moving Average Process
• 14.22 First-Order Autoregressive Process
• 14.23 Unit Root and Explosive AR(1) Processes
• 14.24 Second-Order Autoregressive Process
• 14.25 AR(p) Process
• 14.26 Impulse Response Function
• 14.27 ARMA and ARIMA Processes
• 14.28 Mixing Properties of Linear Processes
• 14.29 Identification
• 14.30 Estimation of Autoregressive Models
• 14.31 Asymptotic Distribution of Least Squares Estimator
• 14.32 Distribution under Homoskedasticity
• 14.33 Asymptotic Distribution under General Dependence
• 14.34 Covariance Matrix Estimation
• 14.35 Covariance Matrix Estimation under General Dependence
• 14.36 Testing the Hypothesis of No Serial Correlation
• 14.37 Testing for Omitted Serial Correlation
• 14.38 Model Selection
• 14.39 Illustrations
• 14.40 Time Series Regression Models
• 14.41 Static, Distributed Lag, and Autoregressive Distributed Lag Models
• 14.42 Time Trends
• 14.43 Illustration
• 14.44 Granger Causality
• 14.45 Testing for Serial Correlation in Regression Models
• 14.46 Bootstrap for Time Series
• 14.47 Technical Proofs*
• 14.48 Exercises
• 15.1 Introduction
• 15.2 Multiple Equation Time Series Models
• 15.3 Linear Projection
• 15.4 Multivariate Wold Decomposition
• 15.5 Impulse Response
• 15.6 VAR(1) Model
• 15.7 VAR(p) Model
• 15.8 Regression Notation
• 15.9 Estimation
• 15.10 Asymptotic Distribution
• 15.11 Covariance Matrix Estimation
• 15.12 Selection of Lag Length in a VAR
• 15.13 Illustration
• 15.14 Predictive Regressions
• 15.15 Impulse Response Estimation
• 15.16 Local Projection Estimator
• 15.17 Regression on Residuals
• 15.18 Orthogonalized Shocks
• 15.19 Orthogonalized Impulse Response Function
• 15.20 Orthogonalized Impulse Response Estimation
• 15.21 Illustration
• 15.22 Forecast Error Decomposition
• 15.23 Identification of Recursive VARs
• 15.24 Oil Price Shocks
• 15.25 Structural VARs
• 15.26 Identification of Structural VARs
• 15.27 Long-Run Restrictions
• 15.28 Blanchard and Quah (1989) Illustration
• 15.29 External Instruments
• 15.30 Dynamic Factor Models
• 15.31 Technical Proofs*
• 15.32 Exercises
• 16.1 Introduction
• 16.2 Partial Sum Process and Functional Convergence
• 16.3 Beveridge-Nelson Decomposition
• 16.4 Functional CLT
• 16.5 Orders of Integration
• 16.6 Means, Local Means, and Trends
• 16.7 Demeaning and Detrending
• 16.8 Stochastic Integrals
• 16.9 Estimation of an AR(1)
• 16.10 AR(1) Estimation with an Intercept
• 16.11 Sample Covariances of Integrated and Stationary Processes
• 16.12 AR(p) Models with a Unit Root
• 16.13 Testing for a Unit Root
• 16.14 KPSS Stationarity Test
• 16.15 Spurious Regression
• 16.16 Nonstationary VARs
• 16.17 Cointegration
• 16.18 Role of Intercept and Trend
• 16.19 Cointegrating Regression
• 16.20 VECM Estimation
• 16.21 Testing for Cointegration in a VECM
• 16.22 Technical Proofs*
• 16.23 Exercises
• 17.1 Introduction
• 17.2 Time Indexing and Unbalanced Panels
• 17.3 Notation
• 17.4 Pooled Regression
• 17.5 One-Way Error Component Model
• 17.6 Random Effects
• 17.7 Fixed Effects Model
• 17.8 Within Transformation
• 17.9 Fixed Effects Estimator
• 17.10 Differenced Estimator
• 17.11 Dummy Variables Regression
• 17.12 Fixed Effects Covariance Matrix Estimation
• 17.13 Fixed Effects Estimation in Stata
• 17.14 Between Estimator
• 17.15 Feasible GLS
• 17.16 Intercept in Fixed Effects Regression
• 17.17 Estimation of Fixed Effects
• 17.18 GMM Interpretation of Fixed Effects
• 17.19 Identification in the Fixed Effects Model
• 17.20 Asymptotic Distribution of Fixed Effects Estimator
• 17.21 Asymptotic Distribution for Unbalanced Panels
• 17.22 Heteroskedasticity-Robust Covariance Matrix Estimation
• 17.23 Heteroskedasticity-Robust Estimation—Unbalanced Case
• 17.24 Hausman Test for Random vs. Fixed Effects
• 17.25 Random Effects or Fixed Effects?
• 17.26 Time Trends
• 17.27 Two-Way Error Components
• 17.28 Instrumental Variables
• 17.29 Identification with Instrumental Variables
• 17.30 Asymptotic Distribution of Fixed Effects 2SLS Estimator
• 17.31 Linear GMM
• 17.32 Estimation with Time-Invariant Regressors
• 17.33 Hausman-Taylor Model
• 17.34 Jackknife Covariance Matrix Estimation
• 17.35 Panel Bootstrap
• 17.36 Dynamic Panel Models
• 17.37 The Bias of Fixed Effects Estimation
• 17.38 Anderson-Hsiao Estimator
• 17.39 Arellano-Bond Estimator
• 17.40 Weak Instruments
• 17.41 Dynamic Panels with Predetermined Regressors
• 17.42 Blundell-Bond Estimator
• 17.43 Forward Orthogonal Transformation
• 17.44 Empirical Illustration
• 17.45 Exercises
• 18.1 Introduction
• 18.2 Minimum Wage in New Jersey
• 18.3 Identification
• 18.4 Multiple Units
• 18.5 Do Police Reduce Crime?
• 18.6 Trend Specification
• 18.7 Do Blue Laws Affect Liquor Sales?
• 18.8 Check Your Code: Does Abortion Impact Crime?
• 18.9 Inference
• 18.10 Exercises
• 19.1 Introduction
• 19.2 Binned Means Estimator
• 19.3 Kernel Regression
• 19.4 Local Linear Estimator
• 19.5 Local Polynomial Estimator
• 19.6 Asymptotic Bias
• 19.7 Asymptotic Variance
• 19.9 Reference Bandwidth
• 19.10 Estimation at a Boundary
• 19.11 Nonparametric Residuals and Prediction Errors
• 19.12 Cross-Validation Bandwidth Selection
• 19.13 Asymptotic Distribution
• 19.14 Undersmoothing
• 19.15 Conditional Variance Estimation
• 19.16 Variance Estimation and Standard Errors
• 19.17 Confidence Bands
• 19.18 The Local Nature of Kernel Regression
• 19.19 Application to Wage Regression
• 19.20 Clustered Observations
• 19.21 Application to Test Scores
• 19.22 Multiple Regressors
• 19.23 Curse of Dimensionality
• 19.24 Partially Linear Regression
• 19.25 Computation
• 19.26 Technical Proofs*
• 19.27 Exercises
• 20.1 Introduction
• 20.2 Polynomial Regression
• 20.3 Illustrating Polynomial Regression
• 20.4 Orthogonal Polynomials
• 20.5 Splines
• 20.6 Illustrating Spline Regression
• 20.7 The Global/Local Nature of Series Regression
• 20.8 Stone-Weierstrass and Jackson Approximation Theory
• 20.9 Regressor Bounds
• 20.10 Matrix Convergence
• 20.11 Consistent Estimation
• 20.12 Convergence Rate
• 20.13 Asymptotic Normality
• 20.14 Regression Estimation
• 20.15 Undersmoothing
• 20.16 Residuals and Regression Fit
• 20.17 Cross-Validation Model Selection
• 20.18 Variance and Standard Error Estimation
• 20.19 Clustered Observations
• 20.20 Confidence Bands
• 20.21 Uniform Approximations
• 20.22 Partially Linear Model
• 20.23 Panel Fixed Effects
• 20.24 Multiple Regressors
• 20.25 Additively Separable Models
• 20.26 Nonparametric Instrumental Variables Regression
• 20.27 NPIV Identification
• 20.28 NPIV Convergence Rate
• 20.29 Nonparametric vs. Parametric Identification
• 20.30 Example: Angrist and Lavy (1999)
• 20.31 Technical Proofs*
• 20.32 Exercises
• 21.1 Introduction
• 21.2 Sharp Regression Discontinuity
• 21.3 Identification
• 21.4 Estimation
• 21.5 Inference
• 21.6 Bandwidth Selection
• 21.7 RDD with Covariates
• 21.8 A Simple RDD Estimator
• 21.9 Density Discontinuity Test
• 21.10 Fuzzy Regression Discontinuity
• 21.11 Estimation of FRD
• 21.12 Exercises
• 22.1 Introduction
• 22.2 Examples
• 22.3 Identification and Estimation
• 22.4 Consistency
• 22.5 Uniform Law of Large Numbers
• 22.6 Asymptotic Distribution
• 22.7 Asymptotic Distribution under Broader Conditions*
• 22.8 Covariance Matrix Estimation
• 22.9 Technical Proofs*
• 22.10 Exercises
• 23.1 Introduction
• 23.2 Identification
• 23.3 Estimation
• 23.4 Asymptotic Distribution
• 23.5 Covariance Matrix Estimation
• 23.6 Panel Data
• 23.7 Threshold Models
• 23.8 Testing for Nonlinear Components
• 23.9 Computation
• 23.10 Technical Proofs*
• 23.11 Exercises
• 24.1 Introduction
• 24.2 Median Regression
• 24.3 Least Absolute Deviations
• 24.4 Quantile Regression
• 24.5 Example Quantile Shapes
• 24.6 Estimation
• 24.7 Asymptotic Distribution
• 24.8 Covariance Matrix Estimation
• 24.9 Clustered Dependence
• 24.10 Quantile Crossings
• 24.11 Quantile Causal Effects
• 24.12 Random Coefficient Representation
• 24.13 Nonparametric Quantile Regression
• 24.14 Panel Data
• 24.15 IV Quantile Regression
• 24.16 Technical Proofs*
• 24.17 Exercises
• 25.1 Introduction
• 25.2 Binary Choice Models
• 25.3 Models for the Response Probability
• 25.4 Latent Variable Interpretation
• 25.5 Likelihood
• 25.6 Pseudo-True Values
• 25.7 Asymptotic Distribution
• 25.8 Covariance Matrix Estimation
• 25.9 Marginal Effects
• 25.10 Application
• 25.11 Semiparametric Binary Choice
• 25.12 IV Probit
• 25.13 Binary Panel Data
• 25.14 Technical Proofs*
• 25.15 Exercises
• 26.1 Introduction
• 26.2 Multinomial Response
• 26.3 Multinomial Logit
• 26.4 Conditional Logit
• 26.5 Independence of Irrelevant Alternatives
• 26.6 Nested Logit
• 26.7 Mixed Logit
• 26.8 Simple Multinomial Probit
• 26.9 General Multinomial Probit
• 26.10 Ordered Response
• 26.11 Count Data
• 26.12 BLP Demand Model
• 26.13 Technical Proofs*
• 26.14 Exercises
• 27.1 Introduction
• 27.2 Censoring
• 27.3 Censored Regression Functions
• 27.4 The Bias of Least Squares Estimation
• 27.5 Tobit Estimator
• 27.6 Identification in Tobit Regression
• 27.7 CLAD and CQR Estimators
• 27.8 Illustrating Censored Regression
• 27.9 Sample Selection Bias
• 27.10 Heckman’s Model
• 27.11 Nonparametric Selection
• 27.12 Panel Data
• 27.13 Exercises
• 28.1 Introduction
• 28.2 Model Selection
• 28.3 Bayesian Information Criterion
• 28.4 Akaike Information Criterion for Regression
• 28.5 Akaike Information Criterion for Likelihood
• 28.6 Mallows Criterion
• 28.7 Hold-Out Criterion
• 28.8 Cross-Validation Criterion
• 28.9 K-Fold Cross-Validation
• 28.10 Many Selection Criteria Are Similar
• 28.11 Relation with Likelihood Ratio Testing
• 28.12 Consistent Selection
• 28.13 Asymptotic Selection Optimality
• 28.14 Focused Information Criterion
• 28.15 Best Subset and Stepwise Regression
• 28.16 The MSE of Model Selection Estimators
• 28.17 Inference after Model Selection
• 28.18 Empirical Illustration
• 28.19 Shrinkage Methods
• 28.20 James-Stein Shrinkage Estimator
• 28.21 Interpretation of the Stein Effect
• 28.22 Positive Part Estimator
• 28.23 Shrinkage Toward Restrictions
• 28.24 Group James-Stein
• 28.25 Empirical Illustrations
• 28.26 Model Averaging
• 28.27 Smoothed BIC and AIC
• 28.28 Mallows Model Averaging
• 28.29 Jackknife (CV) Model Averaging
• 28.30 Granger-Ramanathan Averaging
• 28.31 Empirical Illustration
• 28.32 Technical Proofs*
• 28.33 Exercises
• 29.1 Introduction
• 29.2 Big Data, High Dimensionality, and Machine Learning
• 29.3 High-Dimensional Regression
• 29.4 p-norms
• 29.5 Ridge Regression
• 29.6 Statistical Properties of Ridge Regression
• 29.7 Illustrating Ridge Regression
• 29.9 Lasso Penalty Selection
• 29.10 Lasso Computation
• 29.11 Asymptotic Theory for the Lasso
• 29.12 Approximate Sparsity
• 29.13 Elastic Net
• 29.14 Post-Lasso
• 29.15 Regression Trees
• 29.16 Bagging
• 29.17 Random Forests
• 29.18 Ensembling
• 29.19 Lasso IV
• 29.20 Double Selection Lasso
• 29.21 Post-Regularization Lasso
• 29.22 Double/Debiased Machine Learning
• 29.23 Technical Proofs*
• 29.24 Exercises
• A.1 Notation
• A.2 Complex Matrices
• A.3 Matrix Addition
• A.4 Matrix Multiplication
• A.6 Rank and Inverse
• A.7 Orthogonal and Orthonormal Matrices
• A.8 Determinant
• A.9 Eigenvalues
• A.10 Positive Definite Matrices
• A.11 Idempotent Matrices
• A.12 Singular Values
• A.13 Matrix Decompositions
• A.14 Generalized Eigenvalues
• A.15 Extrema of Quadratic Forms
• A.16 Cholesky Decomposition
• A.17 QR Decomposition
• A.18 Solving Linear Systems
• A.19 Algorithmic Matrix Inversion
• A.20 Matrix Calculus
• A.21 Kronecker Products and the Vec Operator
• A.22 Vector Norms
• A.23 Matrix Norms
• B.1-Inequalities for Real Numbers
• B.2-Inequalities for Vectors
• B.3-Inequalities for Matrices
• B.4-Probability Inequalities
• B.5-Proofs*

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Nonfiction Books » Economics Books » Economics Textbooks

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Economics Textbooks

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Last updated: July 31, 2023

Core Economics

By core economics team.

Which is the best introductory economics textbook? When we asked Cambridge professor Diane Coyle for her opinion a while back, she recommended Core Economics . Not only does it cover issues, like inequality, that people really care about, but, even better, you can download the ebook for free . You can use the materials to start teaching yourself economics and see if it's the subject for you.

The Core project is led by UCL economics professor Wendy Carlin .

Read expert recommendations

Macroeconomics

By greg mankiw.

Introductory Macroeconomic Textbook

“Greg Mankiw is very good for entry-level type textbooks, whether they’re called ‘introduction’ to macroeconomics or ‘intermediate’ macroeconomics. They all suit, more or less, an entry-level knowledge of economics. Some have more, some have less analytical detail. This one is probably the most general in terms of its title, it’s just called Macroeconomics and, in my opinion, it’s the one that can reach the widest audience. That’s why I chose this one. He’s a great writer. It’s a classic and generation after generation of economists have gone through it. You cannot list five books on economics for undergraduates and not include this book. It would be like listing the five top guitarists from the 1960s and not including Jimi Hendrix.” Read more...

The Best Macroeconomics Textbooks

Raffaele Rossi , Economist

The Cartoon Introduction to Economics: Microeconomics

By yoram bauman and grady klein.

“This is by Yoram Bauman, who is perhaps better known as the stand-up economist. He sprang to fame because of this lecture – you can see it on YouTube – which was a stand-up comedy routine, based on a parody of one of the most famous economics textbooks, Greg Mankiw’s Principles of Economics . Bauman has a PhD in economics, so he knows a lot of economics, and there’s actually quite a lot of wisdom woven into the comedy routine, but he just lays into economics. Then he decided that the next thing he wanted to do was write this cartoon introduction to economics. And, just to be clear, this is a textbook. It’s not a comic book with some economic messages, it’s a textbook in the form of a cartoon. But it’s quite sophisticated and it’s very nicely done…For anybody who is genuinely interested in economics, who really wants to learn the jargon, or anyone who is starting out studying an economics course, this is just a brilliant source. It really is rigorous, but it’s also a lot of fun to read.” Read more...

Unexpected Economics Books

Tim Harford , Economist

Corporate Finance

By jonathan berk & peter demarzo.

Corporate Finance Textbook

Corporate Finance by Jonathan Berk and Peter DeMarzo (both professors at Stanford's Graduate School of Business) is an excellent corporate finance textbook, which explains everything you need to know clearly and well. If you've thought about business and have some basic maths, you should have no problem following it. Corporate finance is about the capital structure and financing side of a business: how to raise money and what instruments to use. Clearly, you need to adapt your financing to what kind of business it is. For example, if you work for a risky startup with no cashflow, issuing a lot of debt is not a good idea. Corporate finance is also about valuation, and whether a project or deal will add or subtract from shareholder value. Risk management (e.g. of changes in interest or exchange rates) is also essential and one of the many topics covered in this very nicely done book.

Analysis for Financial Management

By robert higgins, contract theory, by patrick bolton, recursive macroeconomic theory, by lars ljungqvist & thomas j. sargent.

“This is the textbook I use in my PhD macro courses. In fact, it’s used in almost all of the major PhD programmes in the US right now – any respectable programme most likely uses this book. It’s a book of tools and techniques to solve what are called recursive macroeconomic models. Modern macroeconomics uses DSGE models – dynamic stochastic general equilibrium models. That’s a bit of a mouthful, but all dynamic means is that it’s a model which explains how things move through time. So it explains what GDP will be today, tomorrow, the next day and the day after that, and how it might change if the government does different things or if certain things happen in the economy. It’s really a model of how the economy transitions from one point to the next – how it goes into recessions et cetera. Those models are extraordinarily difficult to solve. What this book shows us – and this is the recursive part in the title – is a way of breaking down this really hard problem into little tiny pieces. You can actually solve a much simpler problem when you only have to look at how the economy moves from today to tomorrow. I don’t have to look at how it moves from tomorrow to the next day and all the way out as far as I can see. We can break down these really hard problems into a recursion between today and tomorrow.” Read more...

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Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework and its Applications

By jordi gali.

“This is a book that I would suggest mostly for people starting a PhD. It’s very technical. It talks about monetary economics and inflation in a very technical way, but of the books of that kind it’s the easiest and gives you an overview of the vision of the so-called New Keynesian model. Jordi is an amazing writer. There is a lot of intuition, despite the use of a lot of maths. It helps you to understand, first of all, how inflation is created in a mathematical model but, most importantly, why we care about it. Jordi says that, in some sense, we care about inflation because of this feedback effect on output—employment and inflation are strictly linked together. A key element of the model economy in the book is price rigidity, firms do not immediately adjust prices. Now, if firms do not adjust prices, if they experience an increase or a decrease in the overall price level, then they need to adjust production in the short run. So if you have higher inflation, then you’re going to have some effect on the output through this mechanism. The book describes this mechanism, and then it describes the optimal monetary policy. The book discusses the connection between inflation and the real side of the economy, and why the central bank should care about inflation. Jordi also explains the conditions under which stabilizing inflation and stabilizing output and employment, in the short run, is exactly the same. This result is known as the ‘divine coincidence.'” Read more...

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Advanced Macroeconomics

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by Stephen Williamson

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Macroeconomics by greg mankiw, macroeconomics by stephen williamson, advanced macroeconomics by david romer, monetary policy, inflation, and the business cycle: an introduction to the new keynesian framework and its applications by jordi gali, recursive macroeconomic theory by lars ljungqvist & thomas j. sargent.

In its study of the broader economy, macroeconomics is a vital tool for understanding the world around us, offering insights into issues that affect us all, like inflation and unemployment. Which textbooks to read to learn more about it? Here, Raffaele Rossi , Senior Lecturer at the University of Manchester, recommends his top macroeconomics textbooks, starting with entry-level books aimed at undergraduates all the way through to the tough tomes you'll need to plough through if you're doing a doctorate and want to work at the frontier of the discipline.

In its study of the broader economy, macroeconomics is a vital tool for understanding the world around us, offering insights into issues that affect us all, like inflation and unemployment. Which textbooks to read to learn more about it? Here, Raffaele Rossi, Senior Lecturer at the University of Manchester, recommends his top macroeconomics textbooks, starting with entry-level books aimed at undergraduates all the way through to the tough tomes you’ll need to plough through if you’re doing a doctorate and want to work at the frontier of the discipline.

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Getting a PhD in Economics

Considering a graduate degree in economics? Good choice: the twenty-first-century financial crisis and recession have underscored the relevance of experts who know how the economy works, should work, and could work. However, Ph.D. programs in economics are extremely competitive, with a high rate of attrition and a median time of seven years to completion. Also, economic professions come in many shapes and sizes, and while a doctoral degree is crucial training for some, it is less beneficial for others. How do you know whether a Ph.D. in economics is for you? How do you choose the right program—and how do you get the right program to choose you? And once you've survived years of rigorous and specialized training, how do you turn your degree into a lifelong career and meaningful vocation? Getting a Ph.D. in Economics is the first manual designed to meet the specific needs of aspiring and matriculating graduate students of economics. With the perspective of a veteran, Stuart J. Hillmon walks the reader though the entire experience—from the Ph.D. admissions process to arduous first-year coursework and qualifying exams to armoring up for the volatile job market. Hillmon identifies the pitfalls at each stage and offers no-holds-barred advice on how to navigate them. Honest, hard-hitting, and at times hilarious, this insider insight will equip students and prospective students with the tools to make the most of their graduate experience and to give them an edge in an increasingly competitive field.

• ISBN-10 0812222881
• ISBN-13 978-0812222883
• Publisher University of Pennsylvania Press
• Publication date February 13, 2014
• Language English
• Dimensions 5.75 x 0.75 x 8.75 inches
• Print length 152 pages
• See all details

Editorial Reviews

Book description, about the author, excerpt. © reprinted by permission. all rights reserved..

Chapter 1 Preliminaries: The Lowdown on Academic Economics and Ph.D. Programs So you're thinking of going to graduate school in economics. I applaud your good taste and discernment. Now is the right time to study economics. Thanks to Freakonomics and blog- and op-ed-wielding economists, we Ph.D. economists seem almost cool; not only can we analyze the stock market, we know something about sumo wrestling. And more of us economists are wanted and needed. The financial crisis of 2008 and the Great Recession have made it abundantly clear how important it is to have people around who know and understand what's going on in the economy. But there are many misconceptions about economics and about graduate economics training. The purpose of this book is to introduce you to the world of academic economics by way of a guide through a Ph.D. program in economics. My goal is to have you come out with a clear-eyed view of what is required to become an academic (research) economist, and to equip you with the required tools. But before we get started on your graduate school adventure, we need to take a step back: we need to double-check your sanity. By this I mean we need to make sure you are clear on the (real) purpose of a Ph.D. program in economics and on what exactly it is that this program is meant to do. Graduate school is not all rainbows and unicorns, but it has a chance of coming pretty close if you understand why you're there. The (Real) Purpose of a Ph.D. Program in Economics To start with the obvious, Ph.D. programs are unlike any other graduate program. In particular, a distinction is always made between Ph.D. programs and "professional" graduate programs like law school, medical school, or business school. These professional programs are intended to train you in a profession—namely, law, medicine, and business. Ph.D. programs, in contrast, are all about the life of the mind and scholarship and thinking heavy thoughts, and indeed, a good Ph.D. program includes all of these things. But Ph.D. programs, even if they aren't so-named, are also professional programs. You should never forget that the purpose of a Ph.D. program in economics is to train you in the profession of economic research. Put differently, a Ph.D. program in economics is meant to train you to become a research professor in economics. It is not meant to train you to be a quant jock on Wall Street or a policy maker in Washington. That's right, the purpose of Ph.D. programs in economics is to produce research professors in economics; there is no other purpose. Of course, many students who graduate with Ph.D.s in economics go on to do other interesting and important things like working on Wall Street or making public policy, but few programs and even fewer faculty would say that these other things are what economics programs are designed to train students to do. Many students who enter Ph.D. programs are largely unaware of this primary purpose. Yet, if you come into these programs without having adopted this very purpose for yourself, you may well be surprised if not downright miserable. Here's an example that is more concrete. Suppose you decided to go to law school, not because you wanted to be a lawyer, but because you thought that law school might be useful for, say, starting your own car repair shop. Repair shop owners occasionally get sued, so it would be useful for a car repair shop owner to know something about law. What would your experience of law school be like? You would be unhappy with professors who were teaching you constitutional law and criminal procedure, which have nothing to do with your interests. You would be unhappy with fellow students who talked about case this and precedent that all the time. You would be crying over the boring cases you were forced to study. By and large, you would be miserable and would find the curriculum, faculty, and students intolerably narrow. While you might find a course or two useful for the car repair business, law school is primarily meant to train lawyers, not entrepreneurial auto mechanics. Likewise, if you go into a Ph.D. program in economics to do something other than to become a research professor in economics, you will be deeply unhappy. If you are, however, clear from the start about what the real purpose of this program is, there is some chance that you will benefit a great deal from the program and even enjoy it. What Academic Economists Do Let's make a distinction between what Ph.D. economists do and what academic or research Ph.D. economists—i.e., economists with Ph.D.s sitting in universities or research institutes—do. You may see economists with Ph.D. degrees doing lots of interesting things. They advise presidents; they consult for firms, banks, and investment companies; they study economic trends; they analyze public policy and make policy recommendations; they teach undergraduate and graduate students. Academic economists do fewer interesting things. They can act as advisors and consultants, but that is not their primary job. They may be expected to teach and advise students but in many places that is not their main job either. The main job of an academic economist is to write research articles and publish them. Writing and publishing articles is not easy. It requires understanding the existing academic economics literature, contributing in original ways to it, and convincing other academic economists that you've just done something interesting. This summary is a highly abbreviated version of academic economics but it is pretty accurate. A crucial missing piece of information, though, is this mysterious thing called "the academic economics literature" that economists are supposed to know and contribute to. These days, this literature is highly mathematical and can be very abstract. Much of the literature has relevance to the real world, but the applications may not be obvious to those unfamiliar with the current jargon and methods of academic economics. This is where the Ph.D. program comes in. The first two years of a Ph.D. program in economics are designed to teach you what the profession considers to be the most important aspects of the current economics literature. The rest of the program is designed to train you to be able to contribute to this literature. Bad and Good Reasons for Doing a Ph.D. in Economics There are perhaps two good reasons to study for a Ph.D. in economics and about 3,007 bad reasons. Here are the top four bad yet unnervingly common reasons that students enter Ph.D. programs in economics: You're generally smart and did well in school but you don't know what to do next with your life. You can't find a job, and it's a good holding pattern until you can get one (plus, you can get a master's degree in economics, which is as good as an M.B.A.). You want to make lots of money. You want to work in public policy and save the world. Let's unpack each of these and see why they won't work so well. 1. You're generally smart and did well in school but you don't know what to do next with your life. While professors in the academy are all for having smart graduate students who did well in school, Ph.D. programs are a terrible place to be if you aren't quite sure what to do next. The main reason for this is because Ph.D. programs are narrower in their focus than almost any other graduate program that you might consider. You will surely get an immersion baptism in graduate economics, but this turns out to be much, much narrower than you might think based on your undergraduate economics classes. If you are unsure of what you want to do next, a brutal first year (and all economics programs are brutal in their first year) in a specialized field will surely not help you explore or find things you want to do. In fact, a bad first year can jeopardize your chances of ever doing economics again, should you want to pick it up later, because fewer programs will take a chance on you. So if you don't know what to do, going to a Ph.D. program in economics will definitely not help you know where to go and it might even close off future prospects. 2. You can't find a job, and it's a good holding pattern until you can get one (plus, you can get a master's degree in economics, which is as good as an M.B.A.). Unless you have very screwy preferences, it is not clear that being forced to study a difficult, technical, narrow subject is better than being unemployed. You will get paid beans during grad school (if you're lucky), and you will certainly not have time to sleep, much less go job-hunting, while you're in grad school. And we should dispense here and now with this fallacy that a master's degree in economics is as good as an M.B.A. While there is practical utility to be gained from M.B.A. coursework, much of the benefit of an M.B.A. program is in getting to know your classmates—working professionals who may be helpful in your business career—and in the career services offered to M.B.A. students. So, if you get a master's in economics, not only will you be forced to take courses that are much more technically demanding, time consuming, and less relevant for the business world, you will also extract none of the most important benefits of an M.B.A. program. And the average business employer is much more interested in hiring an M.B.A. graduate—a quantity she knows—than a master's in economics graduate. 3. You want to make lots of money. Snort. Not sure this deserves comment. Obviously, if you want to make lots of money, you should get an M.B.A. instead of a Ph.D. in economics; this fact has been empirically confirmed many times over. 4. You want to work in public policy and save the world. While this is more feasible than reason number 3, getting a Ph.D. in economics is an awful lot of work to prepare for a job in public policy. Much policy work that has any real-world relevance requires very little of the abstruse mathematical juggling that is the bread and butter of economics programs. Further, economics programs won't teach you anything about saving the world, and you probably won't save the world either. Although many economists do act as policy advisors, getting a Ph.D. in economics is a more difficult path than alternative paths that can also lead to working in policy and saving the world. Those are four bad reasons for wanting to do a Ph.D. in economics. Now here are two good reasons: You want to do economic research, you have questions you're interested in answering, and you have ideas about how to answer them. You want to teach economics at the university level. Some people might even argue that reason number 1 is the only good reason for doing a Ph.D. in economics. I include teaching as reason number 2 because: (1) it is an empirical reality that many colleges and universities will only hire Ph.D. graduates for their teaching positions; and (2) almost all academic economics positions require you to both teach and do research, even if the pay and promotion incentives are based on your research. To the extent that you think you might enjoy teaching economics at the university level as well as conducting economic research, these are the two best reasons to get a Ph.D. in economics. Going to Grad School Now Suppose this all sounds good to you, but you're not quite sure if now is the right time. Perhaps you did blindingly well in college, but you're feeling a little burnt out and need a break. Or you are tired of being poor and you would like to spend a couple of years making some serious money. In general, if you have other things that you want to do with your life right now (make money, travel the world, play in a band), you should go and do them. Grad school will still be here. Once you start on the econ grad school track, it will be all-consuming and you should be intellectually and personally prepared for the challenge. It's not easy to take a break during grad school and get back on track. If you're not 100 percent sure that you're ready right now, the time away from school will scratch that (non-economic) itch and might make you even more keen to come back. Indeed, many students who jump into grad school without giving much thought to other things they might want to do regret not having pursued these other options before grad school. Now, you may be concerned that if you don't go to grad school right now, your skills will deteriorate. It is true if you spend time away from doing economics and math, you will be a little creaky when you come back. As long as your time away is not more than two or three years, though, it will not take too long for you to recall the things you learned and get up to speed, so this should not be a particular worry. The most important thing is that you have taken the time to fulfill any other ambitions you might have. Grad school is like marriage, a long-term relationship requiring a serious commitment; it's probably a good idea to date around a little before you get married. Economics Versus Friends of Economics Students often wonder if they really want to be in a Ph.D. program in economics, as opposed to a program in a closely related field. These days, you can get a Ph.D. in public policy, finance, business economics, political economy, or health economics. Why not one of those? A Ph.D. program in economics is not the right choice for everyone, but before deciding whether to devote yourself to economics or to a field friendly to economics (hereafter referred to as FOE, friend of economics), you should know that economics and FOE degrees are not easily substitutable. There are obvious differences in curriculum, and related to that and perhaps more important, there are differences in job opportunities. While economics Ph.D. graduates can and do find employment in economics departments, business schools, political science departments, and health policy departments in medical schools, Ph.D. graduates of these FOE programs are typically employable only in FOE departments even if they are working on exactly the same topic that an economics graduate is . Unfair but true. What's more, in certain FOE departments, economics graduates may still have an advantage over FOE graduates; that is, an economics graduate may have a better chance of being employed at some public policy schools than a public policy graduate. Thus, economics graduates generally have a wider range of employment opportunities than FOE graduates. If you are unsure of your area of interest within economics or if you are keen to have the broader training afforded by economics, an econ program would be a better option for you. If you are very sure of your research interests and don't want to waste your time taking courses not related to them, a FOE program is a better choice. In some programs, the courses and qualifying exams you take are identical to those required of economics students, but you take fewer of them. For example, business economics students may be required to take the same microeconomics and econometrics courses as the economics students, but are excused from macroeconomics courses. You should also know that, not only do FOE programs have a narrower focus, they also tend to have a more applied focus, and this is reflected in the content of the courses and in faculty research interests. Having noted the differences between the two types of programs, I should of course mention that despite these differences, the advice in this book is helpful for Ph.D. FOE students as well as econ students. Notwithstanding the curricular and labor market differences, the structure of FOE programs is very similar to that of economics programs, and FOE students and economics students face many of the same academic and professional issues. Master's Degrees If you are interested in a Ph.D. program in economics, should you get a master's degree first? Perhaps you're unsure of whether you really would like to commit to a Ph.D. program and just want to dip your toes in the water. Or your undergraduate degree was not in economics and you're thinking about doing a Ph.D. in economics. In the United States, the master's degree is usually conferred as doctoral students progress through the program; there are few terminal master's programs in economics. This is changing somewhat as more mid-level departments are offering the master's degree option; in addition, a few respected economics departments have in recent years begun offering terminal master's degrees (for example, Boston University, Duke, and New York University). There are also good master's degree programs overseas. Many top universities in Europe (e.g., Cambridge, London School of Economics, Oxford, and Universitat Pompeu Fabra in Spain) offer terminal master's programs and confer degrees that are well-respected in the United States. Bear in mind that these programs will be demanding and technical. They consist of the first year of coursework in a Ph.D. program and cover perhaps the least fun part of any graduate program. If you want to dip your toes in the graduate economics water, a master's program is not a bad idea. It will help you get your skill set together, help you find out if you enjoy graduate study in economics, and show others that you are serious about economics. If you do go on for your Ph.D., your experience during the first year of your Ph.D. will be much more pleasant because you will have seen a lot of the same material in your master's program. There are some downsides, however. In many master's programs, and especially the overseas master's programs, there is very little funding so you will have to fund yourself. Second, in many European programs, exams take place only once a year. American students have difficulty knowing how to study for these kinds of exams and good students can do poorly on them; a whole year's worth of work and tuition, and your Ph.D. admission prospects, may go down the tubes if you have a bad day or two so it's a bit of a risk. By the way, you should also know that a master's degree in economics has little professional value beyond getting you into a better Ph.D. economics program than you would have otherwise gotten into (although of course it has intellectual value). As I mentioned above, it is a poor substitute for an M.B.A. or, say, a master's in public policy. So if you decide to go for your master's degree, do it with the understanding that its only value will be to help you prepare for your Ph.D. A Few Factoids About Economics Ph.D. Programs So much for the highly opinionated part of this chapter. Now for a few facts. You may be curious to know some general statistics about economics Ph.D. programs. I should note that, here and throughout the book, I will focus primarily on economics training in the United States. Although the economics profession has become much more globalized in recent decades and there are many excellent economists and doctoral economics programs overseas, most advanced economics training still occurs in U.S. programs. (There is also more heterogeneity in the structure of non-U.S. training programs compared to U.S. programs.) My U.S. focus should be interpreted simply as reflecting the system I know best and as an attempt at addressing the needs of the majority of economics students, rather than as a dismissal of non-U.S. alternatives. According to the American Economic Association (AEA), there are 136 Ph.D. programs in economics in the United States. There are no official estimates of the total number of students in these programs, but several back-of-the-envelope calculations suggest the number is around 10,000. The top fifteen programs tend to have more students than the lower-ranked programs; an estimate from the 1980s suggests that program enrollment in the top fifteen programs averages around 130 students, whereas enrollment in lower-ranked program averages around 50-70 students (Hansen 1991). Since the 1970s, there have been steady increases in the percentage of doctorates in economics awarded to women. In 1977, about 9 percent of economics doctorates were awarded to women; in 1987, this proportion was 19 percent; and in 2001, it was 28 percent (Siegfried and Stock 2004). There have also been increases in the percentage of economics doctorates awarded to non-U.S. citizens. In 1977, about 33 percent of economics doctorates were awarded to non-U.S. citizens; by 2001, this percentage had increased to 62 percent (Siegfried and Stock 2004). And finally one last statistic: how long will take you to finish? Had you had the foresight and fetal know-how to graduate in 1977, the median time to completion would have been 5.7 years. Time to completion has been steadily increasing, and in 2001, the median time to Ph.D. was 7 years (Siegfried and Stock 2004). If these and other fun cocktail-party facts interest you, you can find more in the papers listed in the American Economic Association's extensive bibliography of studies on graduate economics education (URL below). For now, I'm presenting you with a few facts about economics Ph.D. programs because it's always good to know about the institution to which you are committing yourself. But overall statistics can only say so much. Mostly my job is to inform you about the experience of being a graduate student. Still here? Consider yourself briefed on economics Ph.D. programs and their real purpose (to produce professors). If after reading this chapter, you are still keen and are ready to make a serious commitment to such a program, read on.

Product details

• Publisher ‏ : ‎ University of Pennsylvania Press (February 13, 2014)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 152 pages
• ISBN-10 ‏ : ‎ 0812222881
• ISBN-13 ‏ : ‎ 978-0812222883
• Item Weight ‏ : ‎ 7.6 ounces
• Dimensions ‏ : ‎ 5.75 x 0.75 x 8.75 inches
• #785 in Academic Development Counseling
• #5,166 in Economics (Books)
• #9,609 in Motivational Management & Leadership

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• Getting a PhD in Economics

In this Book

• Stuart J. Hillmon
• Published by: University of Pennsylvania Press
• View Citation

Considering a graduate degree in economics? Good choice: the twenty-first-century financial crisis and recession have underscored the relevance of experts who know how the economy works, should work, and could work. However, Ph.D. programs in economics are extremely competitive, with a high rate of attrition and a median time of seven years to completion. Also, economic professions come in many shapes and sizes, and while a doctoral degree is crucial training for some, it is less beneficial for others. How do you know whether a Ph.D. in economics is for you? How do you choose the right program—and how do you get the right program to choose you? And once you've survived years of rigorous and specialized training, how do you turn your degree into a lifelong career and meaningful vocation? Getting a Ph.D. in Economics is the first manual designed to meet the specific needs of aspiring and matriculating graduate students of economics. With the perspective of a veteran, Stuart J. Hillmon walks the reader though the entire experience—from the Ph.D. admissions process to arduous first-year coursework and qualifying exams to armoring up for the volatile job market. Hillmon identifies the pitfalls at each stage and offers no-holds-barred advice on how to navigate them. Honest, hard-hitting, and at times hilarious, this insider insight will equip students and prospective students with the tools to make the most of their graduate experience and to give them an edge in an increasingly competitive field.

Table of Contents

• Title Page, Copyright Page
• 1: Preliminaries: The Lowdown on Academic Economics and Ph.D. Programs
• 2 :Applying to Ph.D. Programs: It's Both What You Know and Who You Know
• 3 Getting Through First Year: Welcome to Boot Camp
• 4: Acing Second Year: Getting On with Graduate Life
• 5: Finding a Topic and an Advisor: Like Getting Married … to a Polygamist
• 6: Getting Distracted: TAing, RAing, and the Meaning of Life
• 7: Thrown In with the Sharks: Women and International Students
• 8: Getting a Job: Taking Your Show on the Road
• pp. 114-136
• 9: Conclusion: The Ph.D. Economist-at-Large
• pp. 137-142
• pp. 143-146

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Macroeconomics is the most exciting new economics textbook in a generation. Charles Jones distills modern macroeconomics as it is currently practiced — ”producing the first text to cover modern growth theory at the undergraduate level. The author’s unique abilities as a teacher and writer render this modern treatment of economic theory an easy read for students new to the field. Together with a distinctive focus on problem solving, this clearly written text brilliantly matches accessibility with cutting-edge theory (source: W.W. Norton & Co.).

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PhD in Economics Programme: Books

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Introduction

These are titles that may be relevant to the corresponding courses. Click on the titles to find out more details about the individual books. 

To retrieve other titles, use the Library Search .

References for ECON 601 - Microeconomics

References for ECON 602 - Macroeconomics I

References for ECON 611 - Econometrics I

References for ECON 712 - Labour Economics

Journal Article References for ECON 712 - Labour Economics

• Keane, M.P. (2011): Labour supply and taxes: a survey.
• Keane, M.P. and R. Rogerson. (2012): Micro and macro labour elasticities: a reassessment of conventional wisdom.

References for ECON 713 - Nonparametric Econometrics

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Ph.D. Program

Make an impact: The intellectual rigor from researchers associated with Yale Economics drives innovations in domestic and international policy.

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Yale's Department of Economics offers a challenging and rigorous academic program, a distinguished and accessible faculty, and a friendly, supportive environment for study.

Our core teaching faculty of 66 is supported by a diverse group of visiting professors and graduate student teaching assistants, making it one of the largest economics departments in the United States with one of the highest teacher/student ratios for the 130 Ph.D. students in residence.

The Department of Economics also has close ties with professional schools in related fields, such as the Yale School of Management, the Yale School of the Environment, and the Yale School of Public Health, where many of its secondary faculty members teach. It also works with affiliated centers, including the Cowles Foundation for Research in Economics, the Economic Growth Center, and the newly created Tobin Center for Economic Policy . 

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Our Program

Yale's economics faculty embraces a broad range of research and teaching interests. Courses and seminars span a wide spectrum of economics, from dynamic structural models to field experiments. Our students apply econometric and data analytic methods to a variety of subjects in macroeconomics, labor economics and finance. Our courses examine critical economic policy issues, including antitrust and environmental regulation. Our focus is global, spanning the United States and developed economies to the developing nations of Latin America, Asia and Africa. Whatever your interest, our faculty is ready to guide you through a wide offering of more than a hundred regular courses, seminars or workshops, combined with individually tailored reading and research courses to best prepare you for your Ph.D. research and dissertation.

Our faculty is eclectic in methodologies and views of economics. There is no Yale dogma or school. You will acquire a critical perspective on the full range of approaches to macroeconomics. You will be well trained in neoclassical theory and in the theory of public choice, externalities and market failures. You will master the skills of sophisticated modern econometrics and understand pitfalls in its applications. You will gain respect for the power of contemporary mathematical models and also for history and for the insights of the great economists of the past.  

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The Ph.D. Program in the Department of Economics at Harvard is addressed to students of high promise who wish to prepare themselves in teaching and research in academia or for responsible positions in government, research organizations, or business enterprises. Students are expected to devote themselves full-time to their programs of study.

The program prepares students for productive and stimulating careers as economists. Courses and seminars offered by the department foster an intellectually active and stimulating environment. Each week, the department sponsors more than 15 different seminars on such topics as environmental economics, economic growth and development, monetary and fiscal policy, international economics, industrial organization, law and economics, behavioral economics, labor economics, and economic history. Top scholars from both domestic and international communities are often invited speakers at the seminars.  The Harvard community outside of the department functions as a strong and diverse resource. Students in the department are free to pursue research interests with scholars throughout the University. Faculty of the Harvard Law School, Kennedy School of Government, and Harvard Business School, for example, are available to students for consultation, instruction, and research guidance. As a member of the Harvard community, students in the department can register for courses in the various schools and have access to the enormous library resources available through the University. There are over 90 separate library units at Harvard, with the total collections of books and pamphlets numbering over 13 million.  Both the department and the wider University draw some of the brightest students from around the world, which makes for a student body that is culturally diverse and likely unequaled in the range of intellectual interests of its members. These factors combine to add an important dimension to the educational process. Students are able to learn from one another, collaborate on research projects and publications, and form bonds that are not broken by distance once the degree is completed and professional responsibilities lead them in different directions.

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