Summer Before PhD, What to Read?

It's about a month until another group of fools young economists start math camp before their first year. One month after that, they are starting actual class. Oh what a joyous time!

In the meantime, students are frantically trying to prepare, turning a 9 month school year into 12. At least that's what my friends and I did.

After an article about what law students should read, Pete Boettke asked what should economists read?

Before spending months with your face in MWG (micro), SLP (macro) or maybe Greene (econometrics), take the summer to read other stuff. These are the books I'd read if I was just 12 months younger.

Books To Stay Excited About Economics

For me, the hardest part of first year is staying excited about economics. First year is a long slog (it's frickin' boring) and it's easy to forget why you decided to become an economist. Take the summer to build back up that excitement.

Books To Put First Year in Perspective

It's easy to get lost in all the Lagrangians and proofs. Take the summer to read some books about how to do economics beyond first year.

  • What Should Economists Do? by James Buchanan- I've reread the first five chapters at least four times. The whole book is worth a thorough read, but the beginning makes me think deeper about what it means to do economics than anything else I've read.
  • How to be Human *: * Though an Economist by Deirdre McCloskey- I love anything McCloskey writes on economic me. This is a great collection of essays.
  • Living Economics by Peter Boettke- For anyone sympathetic to Austrian economics, Boettke offers a fresh perspective on doing economics. This is the only book I'm aware of that is specifically geared toward incoming economics students. I read it before my masters and again before my PhD. It's worth it.

Books to Prep for First Year

Learning technical skills before first year will help. However, don't overestimate how much you will learn on your own. If you're like me, you'll learn more in a few weeks of class than through all of summer. But if you want to work on technical skills, I'd stay basic.

  • Book of Proof by Richard Hammack- For my first year, given my training, learning proofs was the biggest hurdle. This book brought me from 0 to okay in no time. I wish I had used it earlier in the year.
  • Economic Theory by Gary Becker- This book can teach an immense amount about price theory. While price theory is out of vogue in most schools, the material in here would have helped me greatly during consumer and producer theory.

I'd say don't pick up any books you are going to read during the year. You have 9 months to torture yourself with those book. Pick up something else.

All of these recommendations are biased toward the reasons I feel in love with economics (I'm weird) and what it took me to get through a year at Minnesota. But hey, that's all I know. Good luck!

What am I missing? What should be skipped?

Setting Up a EC2 Instance for Cloud Computing

This is a little outside of my normal posts, but I think it will be helpful for some people. If not, it will simply be notes for myself.

I will show you how to get started with cloud computing. You can follow my directions with no understanding of cloud computing. However, I recommend you're become comfortable using a terminal window, using commands like "pwd" or "cd". After this, you will be able to run IPython "on the cloud." Woohoo.

Things To Do Only Once

First you need to create an Amazon Web Services (AWS) account. Click here and follow the instructions. Simple enough. You've done this a billion times. You will need a phone number and a credit card. Don't worry about the credit card. Everything I will show is free and I will show you how to get AWS to email you if it starts charging for some reason.1_signin


After you have created an account, go to the AWS management console. In the top left of the screen, click on EC2, which stands for Elastic Cloud Compute. The "elastic" comes from the fact that you will be using some Amazon CPU when it becomes available.


Each Time You Create an Instance

Click "Launch Instance." An instance is just a virtual server that you will be using. Think of it as a virtual machine that you get to set up and customize.



Next you need to select the instance type. This tutorial is for Ubuntu 14.04. That is what I use, both on my local machine and on EC2. This means your virtual machine will run Ubuntu with all the Ubuntu commands.

Every tutorial I've seen is different, because Amazon keeps updating the process. Here are the steps on June 18th, 2015. Keep the "t2.micro" instance selected. It is the slowest type, but also free. Click "Next: Configure Instance Details"



Simply click through until Step 5, where you can add tags to this instance. Tags aren't vital, but nice if you're trying to use multiple instances.

Step 6 is the important step in all of this. It is where you create a security group for the instance. Multiple instances can have the same security. In the future, you can change this, but for now, select the source to be just "My IP" on the bottom right of the screen. This only allows your local IP address to get access to your instance.

Click "Review and Launch" and then "Launch."



You need to download the Key Pair. This is what allows you to use the instance. Save it on your local computer. If you lose this, you will need to copy your instance and create a new key pair. Download key pair and click launch instance.

For the key, I put it in a folder on my desktop called EC2.

Your instance is now launching. You will also get a notice about billing alerts. I recommend you set these up to make sure you don't accidentally leave a paid instance running.



Follow the instruction on Amazon.

After that, return to your AWS tab. Click the orange box in the top left and click on EC2 again. This will bring you to the screen that you will always use when accessing your instances.

The first time, you might see a status check on your instances saying "Initializing." Wait for that to finish.

Every Time You Use EC2

On the left bar, under "Network & Security," click on Security groups. Then click on the security group you just created and the "Inbound" tab. This sets what is allowed to use the instance. Click Edit to allow access from the computer you're using. (I have to do this each time I use the instance. If there is a way around, let me know.)11_security


Again, on the left bar, click on Instances. Then click the instance you want to use, likely the only one you have. On the bottom half of the page, you should see a Public DNS. Copy the Public DNS for later use.

Now, it is finally time to get into the instance.

On your local machine, open up a Terminal Window.  Change directories to the folder that has your .pem file that you just saved.

(Note: The first time you access your instance, you will have to type "chmod 600 name_of_your.pem".

Type ssh -X -i "the name of your pem file" ubuntu@ "your public DNS that you copied"


You are now in your very own instance. Congrats. You computing are on the cloud. Give yourself a pat on the back. That wasn't so hard.

To make sure, type "pwd" to make sure you aren't in your local directory. Type "ls" to see the instance is clear, nothing fancy going on.

One Time: Installing Software

Well, the instance is pretty worthless now. There is nothing on it. Installing programs is simple enough. I use the list below. I use EC2 for Python (and various packages connected to Python).

sudo apt-get update
sudo apt-get upgrade
sudo apt-get install xfce4
sudo apt-get install jockey-gtk
sudo apt-get install xdm
sudo apt-get install ipython
sudo apt-get install python-numpy
sudo apt-get install python-scipy
sudo apt-get install python-matplotlib
sudo apt-get install python-dev
sudo apt-get install git
sudo apt-get install python-sphinx
sudo apt-get install liblapack-dev
sudo apt-get install thunar
sudo apt-get install xfce4-terminal
sudo apt-get install gedit              # my favorite file editor
sudo apt-get install gitk               # to view git history
sudo apt-get install python-sympy       # symbolic python
sudo apt-get install imagemagick        # so you can "display plot.png"
sudo apt-get install python-setuptools  # so easy_install is available
sudo easy_install nose                  # unit testing framework
sudo easy_install StarCluster           # to help manage clusters on AWS

When it asks you if you want to continue, type Y and hit Return.

Now you have a operational instance on the cloud for computing using Python. If you want to use something else, like Fortran, just search do the same thing as above, but "sudo apt-get install gfortran". This is just an Ubuntu computer where you can do everything you could do on a local Ubuntu.

Running IPython

I use IPython and will show you how to get it running. There are two simple ways to start using IPython on your instance.

The simplest is to just type "ipython --pylab". The -- preloads IPython with the Pylab package. This opens up IPython to start playing around with. Enter "quit" to leave IPython.


This should pop up an image. It might take a long time. On the free instance, images are slow to load. But this should give you an understanding of how you can use EC2. It is just like a local Linux machine.

Your other option is to use the gedit package to write Python scripts. The options are endless.

To exit the EC2 Instance, simply type "exit".

I hope that convinces you that the cloud is easy and manageable, especially once you are comfortable on the command line. I'll post more about different ways that I use EC2. I learned most of what I do from a Coursera course page.

Comment below with any questions!


Behind First Year: The Numbers

(Update: I passed both exams on the first attempt. Hopefully that helps readers to judge the information below.)

Grad students constantly talk about how much they work. It's a badge of honor to explain how terrible life is. Even I have gotten a little mopey about things lately. I apologize.

This post attempts to put some numbers to the amount of work one specific PhD student did. My purpose is not to brag, neither about how much nor how little I worked, but simply explain how the time I put in. (If it turns out I failed my exams, I'll make a note on this post in the future.)

Instead of relying on my biased recollection, I used data. Of course, this has its own biases, but it is better than my memory.

Since about 2 years ago, I've used an app called Toggl to track my time. I highly recommend it. It pushes me to work more and stay focused. I always feel bad when I'm clocked into work and I'm actually checking Twitter, since I'm only fooling myself. That pushes me to get back to work.

A quick note on how I track my time: when I arrive at the office and start to actually work, I mean actually work and not just get ready for the day making tea, I begin clocking my time. I have the app on my phone, iPad, and on a browser. I am able to keep them synced reasonably well. When I take a break to eat, I switch the tag to "Personal." When people come into my office to chat, I do the same. I want to get a real estimate of my time doing each activity.

I originally tried to keep track of smaller categories of activities, but I've found my optimal tracking is with broad categories like Personal, Courses, Studying, and specific projects.

Categories I included as "work" time:

  • Courses: the actual course lectures
  • Coursework: studying, problem sets, related readings
  • Non-Coursework Econ: reading for my Adam Smith fellowship, fun economics readings like Hayek, programming, departmental lectures
  • Projects: I have three papers at various stages and I've tracked the time on them.
  • Blogging: This is the least like work, but I only tracked about 10 hours over the year. I likely missed a lot of blogging time or put it as personal.

The most obvious bias is from checking Twitter. If I just glanced quickly, say less 30 seconds, I wouldn't mark the time. If I got in a conversation, I would count that as personal time.

I tracked personal time to try to see how much time I was wasting at the office. If I wasn't working, I wanted to be home with my wife. My apologies to her for wasting the time I did at the office.

Categories I included as "personal" time:

  • Eating
  • Browsing the internet
  • Working out
  • Practicing Spanish

So here is my non-perfect data from September 1st to May 27th. Continue reading

Year 1 = Finished (Hopefully)

While I am not really done with first year until I have passed both exams, I'm going to act like the first year is done. At least, I'll do that for a few weeks.

This morning I finished my 2nd prelim, which was in macro. The first was in micro. I hope to write more reflections over the coming weeks about first year. I hope to get my thoughts down when I have a clear head, but also remember what first year is like. I don't want time to distort my perception.

Both exams were easier than I expected. While that doesn't mean I passed both, it is nice to come out and feel better than when you went in.

But it's hard to tell. As I said in a earlier post, the grading is a mystery. I'll have to wait until the pass/fail comes in to really know.

The 5 hours of the actual exam was a unique experience. While I'd taken long exams for my physics undergrad or for things like the GRE, these were more exhausting than I anticipated. Luckily, there was lots of candy (the food of champions I believe) to keep me fueled for the exam. It was mentally draining. I expect to crash in about an hour.

There was such a build up to micro that I crashed after that. The rest of that day and the next, I couldn't study for macro. I came to the office and tried to focus, but I was completely fried. That is something I did not schedule for, leaving me with 2 less days for macro than I expected.

Overall, the exams were fair.

I started studying in January, which made life easier for me at the end. It was still a rush over the past few weeks, but less so than for people who started in March.

My advice to anyone who has to take these exams, start early. This seems obvious, but not everyone does it. Maybe other strategies work for other people. It wouldn't have worked for me. Seeing stuff over several months allowed some things to stick by the end.

Maybe what I did wasn't enough. Maybe I should have started last September. I won't know whether my strategy worked until the end of June when we get the results.

But this year is now sunk. I did what I did. All I can do from here is maximize my utility going forward. In the immediate future that includes a BBQ with our department. Over the weekend that involves a bachelor party. Over the summer that involves more time with my wife and maybe some economics. Actually, there definitely will be lots of economics. I can't give it up. It's an addiction...

Prelim #1: Micro

This blog has turned into a diary of the first year of an econ PhD, instead about understanding the world using economics. That makes some sense, since I spend my days doing an econ PhD, not understanding the world.

Tomorrow is my first prelim, micro. I will blog after all the exams about my retrospective thoughts, but I wanted to get down my thoughts right before too.

I'm excited to finish one. It will feel like a huge hurdle. Two will feel even better. May 27th. That's what I'm looking toward. The beer after that macro prelim will taste SO good.

For the last few days, I have reached stage 5 of prelim prep, acceptance. At this point, I know what I know. Now I am just reviewing a few things and trying to relax. I don't see any value in going into the exam stressed. I never have seen that as a good strategy. Tonight I'll go for a run and have a nice dinner. Maybe I'll read some Austrian economics for fun. And I'll listen to B.B. King and have a scotch. Macallan. 12 years. Neat.

Now, whether I pass or not will depends on the specific exam questions. "Duh" say both readers.

Let me elaborate. Looking over past exams, there are many I believe I could pass today and many I would fail. I say "believe" since we are never given a real understanding of what it takes to pass. I'm relying on hearsay and gut feeling. It's the best we have. The exam has 4 questions and everyone says 2.5/4 is passing. What is a 2.5 vs a 2.0? Not sure. But that's my imaginary goal I've been shooting for over the last 9 months.

The nice part about Minnesota's prelims is that they don't matter a ton. I have around 5 attempts to pass. Given the only options are in May and August, that gives me another two years. So I don't have any fear of being kicked out if I don't pass. That doesn't mean they aren't stressful or important. It still will be nice to pass this time. (I shot myself in the foot when I idiotically scheduled a trip over the August prelims. That's made these exams more important for me than they should have been. Whoops.)

Passing on the first try would allow me to spend the summer doing things I actually want to do, things that would be a productive input into my research. That sounds better than studying more for an exam.

Studying for these prelims has been zero fun, sir.  I added the extra stress of putting together a paper to present over the summer. My advice to any future PhD students: don't agree to submit a paper the week before exams. You might see a pattern of my smart life decisions... If you want to read a draft of that paper and leave some comments, I'd appreciate it.

Studying for prelims is still better than milking cows (a job I did for a summer), but not as fun as actual economics. Compared to everything else I've done in economics, it's awful.  Granted, that's not saying a lot since I love studying economics.

But this studying is at a point where it is pure memorization of definitions and mathematical results. Applying the fact that demand curves slope downward or using opportunity cost reasoning? Understanding how an economy functions? Ha. Yeah right. That's not something you get in first year. Memorizing Topkis' Theorem or the proof of the First Welfare Theorem? Yep. Proof after proof? Oh yeah baby.

Luckily, because I studied I'll be ready for those times where someone comes up to me with a gun and asks me to recite the Maximum Theorem and I don't have a reference or computer around. When I do have a reference, I'll check the reference like an actual scholar would. There is some method to the madness, or so I'm told. At the moment, it seems irrelevant.

But that's one of the aspects of being a student. I have acknowledge that certain people, called professors, know more than me. In particular, I chose these professors at Minnesota to show me what I don't know. There are other schools I could have went to and not worried about the exams. Yet, I chose Minnesota knowing prelims awaited. Can I really be upset about something I willingly and knowingly chose?

That doesn't mean they have convinced me on every issue. I'm pretty sure they're wrong about prelims being a valuable part of econ PhDs. But in general, I'm taking their advice.

I'm sorry if this is an incoherent rambling. Forgive me. It's prelim time.

I'd be interested in what other economists felt around their prelims. Please let me know in the comments.



Prelims: T-Minus 12 Days

Blogging has been a little slow. There have been interesting conversations going on throughout the blogosphere, but nothing I could join in on. Things are just too busy. (Excuses, excuses...)

As I've said before, the first year of an econ PhD at Minnesota is a build up to prelims. Prelims are overwhelming at times, but the year is still good. I spend my days learning economics. That's awesome. Not ideal to do so much memorization, but economics is still better than anything else I'd do all day.

But everything has a cost. So I have limited my amount of blogging over the last few months. Hopefully this summer will lead to more. For now, prelims are center.

For people who haven't been through prelims (specifically Minnesota prelims), this structure might seem odd. Why all this build up for an exam that doesn't matter? Isn't a PhD about research? Good questions. I don't know. People act like there is a reason, but no one can articulate what it is. It's just something I have to do, like learn cursive or go through hazing in college.

In under two weeks, I have my first prelim exam. It's in microeconomics and will look something like this. I remember looking at the exams before class started and being completely overwhelmed. I didn't know how to do anything. That feeling has only slightly changed.

There are 4 sections, one for each of our quarters:

  1. Consumer and Producer Theory
  2. General Equilibrium
  3. Game Theory
  4. Mechanism Design

In each section, there are a range of topics. Some topics I understand, especially from 1st quarter since I've had time to study them. Some I am still clueless about (everything in mechanism design). From now until May 20th, I'm working to fill in the gaps.

After all the joy of studying micro, I will have another week to focus solely on macro. The exam for macro is longer (5 hours compared to 3 hours), but more structured. For macro, the courses build on each other more directly than for micro. Studying for one subject helps (at least a little) for the others. For micro, that is not the case. Each section is basically independent in micro.

That makes studying for macro less overwhelming. It doesn't seem so varied by topics, but has more depth on one topic. That one topic is the Dynamic Stochastic General Equilibrium model (DSGE). Sometimes we set up the problem in one way, sometimes in another. Sometimes there are taxes, sometimes not. Whatever.

While there has been much criticism of this type of macro, DSGE is still the main framework for modern macro. Therefore, DSGE = macro for first year UMN students. We can debate the issues with that later. For now, I must ignore those concerns.

DSGE and the micro topics above are what I have been focused on for months and hopefully will only have to focus on for a few more weeks. Ideally, I will pass both. But economists don't care too much about ideal worlds.

If I don't pass, summer means studying. We get a second shot at the exams in August. However, I'd rather spend my summer learning about things that interest me, like network theory or agent-based modeling, than studying for an exam. My reading list, and stacks of books I bought without reading properly, is embarrassingly long. I hope summer makes a dent in that.

Oh well. That all has to wait. Wish me luck.

The Five Stages of Econ Prelim Prep

Up to this point, I've written mostly positive thoughts on first year (like here, here, and here.) That's because overall this year is awesome. I'm finally getting paid to study economics, something I've done on my free time for years. Training to be an economist is a wonderful experience and I wanted to highlight that in earlier posts.

However, with my end of the year exams, aka prelims, only a month away, the mood has turned. All day, every day is focused on those prelims. I have one in micro on May 20th and one in macro on May 27th.

The hours have gotten longer and the subjects I'm studying are less interesting. I've finally noticed the 5 Stages of Econ Prelim Prep.

Stage 1: Denial

For me, this stage was roughly the first semester and the beginning of second. This was the happy time of the year, where I denied that the prelims will ever come.

I went about with my business, studying as I went along. I worked hard (still averaging around 60-70 dedicated work hours a week), but I was able to study things I wanted. I read lots of Austrian economics, books on agent-based modeling, network theory, and worked on programming. Everything (well almost everything) I studied was just because I wanted to do it and I thought it might help my future research.

I denied that prelims would ever come. The date was so distant that I could ignore them for a long period.

Stage 2: Anger

Then the anger stage hit. After starting to study and memorize as much as I could, I got bored quickly. That is a problem I have that will plague me through my whole PhD. It wasn't that I thought the material not worth knowing, but only that I hated the structure of the year and prelims. It is all about memorizing definitions and theorems for an exam that doesn't matter in the end.

Yes, we should be trying to actually learn the material, but everyone resorts to a lot of pure memorization. It is not enjoyable and results was a not-so-happy Brian. The level of cursing, especially directed at books and study notes, went from almost zero to a level I'm not proud of.

One aspect makes it especially bad. The topics that need the most time to study are exactly the topics that are confusing or boring. Exactly the stuff I don't want to study, that's what I end up studying. With a full year of material, everyone will have something they find extremely boring. It's just the nature of it.

Stage 3: Bargaining

Just when I think I was about to explode, I started to bargain with myself. The material load because too overwhelming and I started to believe there is some way out.

I bargained that "I only need to study these subjects in General Equilibrium" or "I will only study for micro and spend the summer studying for macro." Whatever little deals that I could think of, I considered.

Stage 4: Depression

I am on the verge on the depression stage. (This is all relative understand. I'm still a happy, upbeat person, just less than without prelims.) There appears to be no hope. I realize that all the bargaining is in vain. Every subject needs to be studied.

There are trade-offs, as in everything in life, but now there are mostly between work and "life." The hours spent with my wife are steadily decreasing. I will not see the 2 friends I have outside of the department for another month. It is a dark time in the first year. A shadow is cast over the economics department...

Expected Stage 5: Acceptance

I assume in the week or two before the prelims I will accept my fate. That fate will likely be a summer spent studying both prelims. Oh well. Wish me luck.

Critiquing Micro-Foundations, a Response to Mark Thoma

There has been a lot of talk on the blogosphere about so-called "micro-foundations" for years. It has especially picked up since David Levine's post on Keynesian economics.

So it should not surprise me to wake up and read two posts on the topic: one from Paul Krugman and another from Mark Thoma. After thinking about it more by myself and on Twitter, I am still left confused about what the critique is of micro-foundations. Thoma's article is more substantive and interesting, so I'll focus on his.

Macro, by definition, deals with aggregates, such as unemployment, GDP, and inflation. While individual actions determine GDP, economists study them as aggregates statistics. So first off, all macro is aggregation.

According to Thoma, there are two main ways to do macro. The newer version uses micro-foundations. These models start with standard micro-style consumers and producers. The other approach, older in origin, assumes some steady macro relationship, such as a constant relationship between aggregate consumption and aggregate output. This is the style of Keynes and Fisher.

Since the 1970's, macroeconomists have tended to use the micro-founded approach. But it's still an aggregate. Both are aggregates. Even Thoma recognizes this when he describes the modern approach which must ultimately "aggregate across household and firms to determine macroeconomic relationships." The most common way to do this is using a "representative agent." When Thoma draws a distinction between micro and aggregate models, I'm left confused. I might not be reading it right.

Leaving that aside, Thoma levels a reasonable critique of the representative household models:

Unfortunately, the representative agent approach is unsuited for studying behavior in financial markets. The problem is that there is no way for a single representative household to trade stocks and bonds with itself based upon different forecasts of future economic conditions (e.g. a person who thinks the price of a stock will fall in the future sells the stock to someone who believes the price will rise).

I agree. The representative agent model is not suited for financial markets. But the old Keynesian model of aggregates is suited for financial markets? How does the aggregate Y and aggregate C or IS/LM or whatever aspect of the Keynesian model explain financial markets? I don't see it. To explain financial markets, there must be two people who value a financial asset, e.g. a stock, differently.  I just don't see how the representative agent or the old Keynesian model can explain. Any critique of the micro-founded DSGE model in this respect also is a critique of the old models. So the score is 0-0.

There is one difference that I see. DSGE models have developed beyond the representative agent models and are working to model financial markets. Are the models perfect? No. Should the models have been more common before the Great Recession? Probably.

The only critique I understand of Thoma's,which he makes in a linked-to article, is that DSGE doesn't give clear policy advice the old Keynesian model does. Sure, but the model wasn't designed to manipulate the economy like an engineer. That's not the purpose of the DSGE model, at least not the purpose that I learned in class. It may have been the purpose of the Keynesian model. But as Thoma says in the linked-to article "when a model is applied to situations it was not designed to address, it is not the model that failed. The model has been misused."

I am left wondering what are the "simple, fast, and accurate answers to our questions" that the old Keynesian model provides. I would love to hear in the comments.

Thoma ends with

Thus, the approach to take depends critically on the question the researcher is asking. For some questions, the aggregate approach (sic) is best despite the criticism it has received in recent years from those using modern models, and we shouldn’t think of it as going backwards if we adopt this approach when it provides simple, fast, and accurate answers to our questions. The “correct” model to use is not an either/or decision, and macroeconomists should be open to both approaches as we try to improve our ability to understand the macro-economy, and provide policy advice when the economy experiences problems.

Here I am absolutely in agreement. As micro teaches us, there are trade-offs everywhere. Just as consumers don't buy only one type of good, economists should probably not use only one type of model. But Thoma has left me unconvinced that the old aggregate approach is the way to focus efforts on the margin.

I can't believe I wrote a post defending DSGE models. But if the critique is not compelling, it's not compelling. This is true regardless of what it is critiquing.

Models, Who Needs Them?

There are many books that I've read that continue to influence my thinking. An important book for me is "Philosophy: Who Needs It?" by Ayn Rand. This book was important, not because I became a Randian. I didn't after that book nor "Atlas Shrugged". Instead, it was the first book I read that urge me to think about philosophy.

Before Rand, I was like most people, scoffing at philosophy, dismissing argument as "just philosophical." I, in all my infinite wisdom, didn't need to think of the mumbo-jumbo philosophy.

Rand's main argument in the title essay is that the question isn't whether to have a philosophy or not. Every person must have a philosophy of how to live their lives. It's unavoidable.

The options are to follow the philosophy that we absorb through life or consciously choose our philosophy. If we do the first, our philosophy might come indirectly from parents, friends, teachers, or celebrities. It might be whatever we pick up through our day-to-day.

Or, as Rand argues we should know what our philosophy is and why it is our philosophy. We can think deeply about the way we want to live our lives and work to pursue that. Instead of passively floating down the river, we can direct our philosophical boat in the direction we want.

The answer to Rand's question "who needs it?" We all do.

Economic Models

The same is true for models of the world, although I have economic models in mind for this post. For this post, I'm using the word "model" to mean a systematic way of analyzing economic questions. We can debate elsewhere the difference between models, theories, frameworks, etc.

If you don't want to talk or think about economics, you don't need a model. That's fine. Economics is not as fundamental as philosophy.

But I haven't met anyone yet who doesn't talk about economic issues. Every time you blame those greedy oil companies for high gas prices, you're using a theory of economics that you probably picked up without knowing. As Rothbard reminds us,

[i]t is no crime to be ignorant of economics, which is, after all, a specialized discipline and one that most people consider to be a ‘dismal science.’ But it is totally irresponsible to have a loud and vociferous opinion on economic subjects while remaining in this state of ignorance.

After reading Rand, I realized I can passively pick up my economic analysis from newspaper or our humanities professors. Or I can pick the models I use and then do are best to understand how to apply them. Models push me to clarify my thinking. That's why economists love models and are insistent on being explicit about them.

Using models might seem odd to non-economists who aren't used to talking about or thinking about models explicitly. I know it was weird for me when I first studied economics.

Our love of models comes up in discussions with critical students, who usually invoke some heterodox economics. Complaints are levied against the common models, say standard consumer theory. "Individuals aren't rational" is one classic complaint. Sometimes Samuelsonian economists get annoyed at these complaints and ask "what's your model?" That is not because economists are evil jerks who want to crush any outside opinion. Every economist I've met is nice and willing to discuss models. We love that.

Instead, we are looking for what model the complainer has in mind. Only then can we judge whether it is a helpful way of looking at the world. If the model you use is "corporations are evil and cause all the bad in the world", fine. You should at least know that so you can decide for yourself whether that is a good model.

Models are just tools, nothing more, nothing less. The economist who insists on a model does so because he finds it easier to discuss a topic when it is clearer where people are coming from. Once a model is put forward, then we can talk about what are the costs and benefits of using it.

People cannot debate economics, nor any social science, without at least using implicit models. It's not only ill-advised, but impossible. One person asserts QE will cause inflation. He is using a model, probably not a good one. If a person says capitalism impoverishes Africa. He is probably invoking a poor model.

Since it's impossible to not use models, I want to know what model I am using. I hope the people I discuss economics with have the same goal. This is an idea I've been going on about all week on Twitter.

To be clear, the models don't need to be equations. A supply and demand graph is a model, and a damn good one. Sometimes equations help clarify a model. Sometimes they don't. Either way, I want to choose my models carefully to aid my understanding of the world.

Practical men, who believe themselves to be quite exempt from any intellectual influences, are usually slaves of some defunct economist.

My advice to other: Don't be the "practical men" who Keynes is talking about. Figure out which models you use and only use the ones you want.

There are many references that explore the nature and role of models, specifically how economists use them. Some that people recommended by Erik Angner and Beatrice Cherrier are here, here, and Mary Morgan's book The World in the Model: How Economists Work and Think. Morgan's book is by far the most thorough examination of models that I've seen.

Why Aren't There More Microeconomics Blogs?

That was the question I posed last night on Twitter. Maybe I better question would have been, why aren't micro blogs more popular?

Now I don't have any data on whether there are less microeconomics blogs or whether they get less traffic, but that is my impression. Most people agreed with me too. Of course there are counterexamples (Freakonomics, Marginal Revolution, Chris Blattman), depending on how one defines "microeconomics blog". There are blogs on every topic imaginable and every blog touches on micro topics. But the blogs that I see talked about on Twitter and from other blogs are almost always macro focused.

For the sake of argument, let's say it is true that micro has fewer/less popular blogs. Then the next question is, why?

Here were some of the suggestions

All these make sense to me. Yet, I'm not completely satisfied with any of the answers.

First, micro can be political too. Yes, pure micro theory is not political; nor is applied work concerned with identification political. But neither is macro. Solving an OLG or Neoclassical Growth model is not inherently political either. Yet, when macro gets applied, especially to monetary policy, people make it political. That adds a huge readership and drives macro blogging. It's fun to see Krugman and Cochrane go back and forth.

Micro can be the same way. It's political when it gets applied to policy. I'm not just thinking about minimum wage, but also topics like regulation and patent protection. Microeconomists analyze all  these and they are inherently political. Walter Williams and Thomas Sowell have made a living for a long time by writing popular pieces from a microeconomics point of view. There is no reason microeconomists couldn't debate taxation online. Yes, many macro bloggers have taken this up too.

Secondly, I don't see how micro is more specialized than macro. Research in both fields is highly specialized. Yet, most blogs are not about leading research. Instead, they are brought down to a more basic level that non-specialists can understand. I see no reason a microeconomist working on development couldn't blog about identification problems in IO. Trade economists blog about monetary policy.

I think the most compelling point was Claudia's. Macro has a natural readership of people involved in business and finance. Again, I see no reason these same people wouldn't read industry or policy analysis from a microeconomist. Explaining the state of some industry or the effects of some policy seem extremely beneficial to businesses. Businesses hire microeconomists to do this. (Maybe that is why people don't blog for free...) Of course, monetary policy affects all businesses, while micro policies are more, well, micro.

But I refuse to give up hope.

People suggested two options which I would love to see.

  1. A group on microeconomists that blog on different topics. One blogger writes about healthcare policy. One writes about regulation. This would avoid the specialization problem about microeconomics.
  2. A whole blog could be about industrial organization.

Until then, I hope to encourage a group of microeconomists to pick up blogging. That is my new crusade (after prelims, of course). I hope all my readers will join me in this fight.