Building a Country from Scratch

If I were building a country, and I wanted it to be successful, in the 19^th century and before, I would want to make sure it had natural resources – forests or coal or sheltered coastline.

Today, success is more about the institutions and the people that are in them.

As such, the first goal of a country should be to build human capital. This means that education is paramount. Early education needs to be funded, and the universities need to be strong.

You also need these people to be healthy. One thing to focus on would be infant mortality. A successful country will have a longer life span, but a lot of that is just cutting infant mortality. Possibly look at life expectancy at a certain age.

Also we need to make sure that infrastructure and physical capital are built out, but that is harder to quantify. The physical capital needs to go hand in hand with the human capital and the universities (and private R&D) to fund technical innovation. 

All this needs to theoretically take place where markets have low barriers to entry and are open and transparent and free – ie Economically free per the heritage foundation

Thing that gets me though, is the role of institutions. In “Why Nations Fail” Acemoglu and Robinson talk about the role of institutions in creating a successful country. The reason Mexico didn’t succeed with a lot of the starting points the U.S. did was the institutions that we had, like English Common Law.

Also, I would want an independent, rules-based central bank and to issue my own currency. 

And then we wait for Capitalism to fall from its inherent contradictions, and the rise of socialism and the eventual withering away of the state.

Ned Ludd Forever! Nicholas Carr's "The Glass Cage"

Nicholas Carr wrote “The Shallows,” which was a warning against the internets and the googles. Now he has another tome out, this time against warning us against technology.

The story goes like this: up to a point, technology allows us to be more productive. By not having to think about every little thing, we are able to outsource some of our cognitive load to machines/computers. The problem is that there are first diminishing returns and then offloading our brainpower diminishes our skills.

The example Carr uses is autopilot. Pilots in big jets are at the point where they only really have to be at the controls on take-off and landing. Or when there’s an emergency. And it is this emergency that matters. By not reinforcing the skills that the airmen need for every-day keeping the plane in the air, then when there’s an acute need to keep the plane in the air, they might not. There are a couple of recent examples of this, so it is not just scare-mongering.

Carr then extends this out to look at other current and future examples (Carr even looks at driverless cars). He even hits on the Asimov laws of robotics!

It’s interesting, but I’m not sure what to do with it.

You Will Know Too Much About Debt Collections: Jake Halperin's "Bad Paper"

I picked this off the shelf at my library after passing over it a couple of times. I was familiar with it because the New York Times ran a substantial excerpt from it in their Sunday Magazine. I didn’t pick it up the first time because I thought that the article was pretty in depth and that reading the book might not add that much.

I may have been right. In the book, Jake Halpern tells the story of debt collections from the bottom up, where the people who buy debt collect on it. They buy debt for pennies on the dollar and make their profits by collecting two pennies on the dollar and selling the rest of the debt onto another collection agency. This is not a well-regulated industry. The bulk of the book focuses on Buffalo New York, and the main enforcement body in Buffalo (apparently a collections hotspot) only has two full time staff.

The story is interesting, but where the story fails is that the author tries to take the overall idea of debt and turn it into a personalized narrative focused on a couple of interesting characters, and I was never sure if he was fully sure if he was writing about debt or those guys. He was trying to do the Michael Lewis Moneyball thing where the particular stands in for the general, but it is not 100% effective. However, it is an interesting fast read, and unless you worked at collections yourself, you will learn something. The main thing I learned is that I don’t want to be in the position where my debt is sold.

Dataclysm: Pop Science as it's Meant to be Done

I liked this book so much I stayed up until almost three o’clock reading it on the Friday after Thanksgiving.

When I was done, the next morning, I eagerly told my wife about all the cool things that were within the pages. I first showed her the graphs the author compiled from the OK Cupid dataset showing that women, in terms of what men say they find attractive, are pretty much over the hill when they’re 22.

 What I liked even better is a chapter called “Tall for an Asian,” where the author looks at the words that people use to describe themselves. They also look at the words that people don’t use to describe themselves, and then compare those to make a composite of the most [fill in the blank] words a certain ethnicity will use. For example, one of the most Asian things to say is that you are tall for an Asian. One of the least Asian things to say is “My name is Ashley”.

This book is full of cool little tidbits like that. It is also clearly written and the data is well visualized – the printers used more than black and white to visualize the charts. On top of all of that, how many books that are categorized as “Social Science – Statistics” will have blurbs from both Dan Ariely and Aziz Ansari? You have to read this book.

Three Cheers for the Minimum Wage

I’m taking an econ class for my MBA program right now, and we covered minimum wage. The intro econ view is that the labor market is like all efficient markets. There is a labor supply curve, and a labor demand curve, and there is an equilibrium price. 

There is also a wage floor, the minimum wage. I’m pretty left wing, and I know that some of my own peers are too, and they seem to have drunk the Kool Aide on the problem with the wage floor – that being it created structural unemployment.  This has distressed me.

So I was thinking about the problem with intro econ stuff, namely that it is a vast simplification and has a lot of normative biases towards conservative leanings. There’s a saying in econ circles to counter Colbert, that “Facts have a conservative bias.” That is true, but only at the level of simplification.

What econ as taught, at least in the intro econ classes I’ve had, doesn’t talk about enough is the simplifications that have taken place to illustrate the concept. The example here is the labor market.  The labor market supply and demand curve intersection graph assumes four big things that are not true. First is that all workers are the same. Second is that all jobs are the same. Third that there is no such thing as search and the markets clear.  Finally, they assume that there is no government to act as an agent of redistribution. 

That’s just not true.  There are many labor markets, and for most the equilibrium price is above the wage floor, so the wage floor only sets a standard. Those where the wage floor is above the clearing price, the jobs and the pay are horrible. A government should step in, as ours does to a limited extent, to make better the lives of those workers who work and those who are locked out of the labor market through structural unemployment. The problem is that a certain party has demonized those at the bottom of the wage scale, calling them takers are welfare queens. That means people want to work; there is a cultural and monetary advantage to working where there is not to just relying on benefits.

The other option is to look at the labor markets that do clear. Here I’m thinking of migrant farm workers. They are paid less than the minimum and have no guarantee of employment. When Alabama cracked down on undocumented workers, farmers couldn’t get people to harvest their fields because the national market price of farm labor was too low for people used to some labor protection. The jobs are that bad. That’s why I think a minimum wage is good, because it helps pull those shadow wages up, and there is less poverty overall with transfers even with structural employment.

Overall, the question should be about the appropriate level of the minimum wager, and stricter enforcement of wage and labor laws, not less.


Addendum, 12/7/2014

Another problem popped up in Facebook reply to a former student of mine: The other problem. The econ 101 view is also a market with perfect information. The employer has an information asymmetry in that area, in that it knows more about the labor market than the potential employee -- this is helped in some form by sites like Glassdoor, but it is imperfect. There is also the power gradient in that the employer can take someone down to the clearing price, but in some labor markets it is not possible to live at the clearing price for labor. Thus the government-mandated wage floor.

Data in Economics

Economic indicators are useful and reliable for predicting the future state of the economy as long as they have been collected long enough with the same methodology. At that point, it is possible for economists to look at the overall trend of the indicator and then to look at the pattern in the past. For example, Figure 4 is the four-week moving average for jobless claims.

Figure 4

There is a lot of useful information to be gleaned from figure four. Looking at the current state of the jobless claims, it looks as if the state of the economy is strong. People are not losing their jobs at a rate that existed in recent memory. The problem is that the past does not necessarily reflect the future. The current trend is down, which in isolation is good. However, looking at the graph shows that the current level is also near the lowest jobless claims have come since the early seventies. The question then is if the localized trend is the prevailing trend, and the jobless claims will keep going down, or is the larger cyclical trend the stronger part of the equation, where the current economy is at its localized peak. If the short-term trend prevails, then businesses can use that information and invest because the economy is only getting stronger. If the long-term trend prevails and the economy is at a natural low, then it is time to retrench because jobless claims will go up, then unemployment will increase, and then GDP will shrink.

            The jobless claims are just one indicator. By having more information, and having more indicators, then an economist can look at all of the information and discern the larger patterns and even fit the current information to which past economic situations were more like the current one. Total information awareness can only help professionals use this data and harness the predictive force of the economic indicators. Of course, even with all the information and all the historical examples, even the best-trained scientist can be wrong but overall tracking this various data has been smart for the country and has helped the government and the central bank make good decisions by moderating the business cycle. Modern macroeconomics was born of the great depression, and so far has prevented another one from happening. It would not have been possible without good data.