Interpolation Vs Transition

Sometimes you read an academic article and the author fills in the data gaps with interpolation. That is, they assume some functional form of the data and then replace the missing values with the estimated ones. Often, lacking an informed opinion about functional form, authors will just linearly interpolate between the closest known values. Sometimes this method is OK. But sometimes we can do better.

Historical census data provides a good example because the frequency was only every ten years. Say that we want to know more about child migration patterns between 1850 and 1860. What happened in the intervening years? Who knows. Let’s look at the data.

Using data on individuals who have been linked across censuses allows us to fill in the gaps a little bit. For simplicity, let’s just look at whether a child migrant lived in an urban location and whether they lived on a farm. That means that there are 4 possible ways to describe their residence. Below is a summary of where children migrants lived at the age of zero in 1850 and where the same children lived a decade later at the age of ten in 1860 given that they moved counties.

When I’m the mean time did these children move from one place and to the other? We don’t know exactly. The popular answer is to say that they moved uniformly throughout the decade. That’s ‘fine’. But it assumes that the rate at which people departed places was rising and the rate at which they arrived places was falling. Maybe that’s true, but we don’t really know. Below-left is a graph that shows the linear interpolation.

The nice thing about linear interpolation is that everyone is accounted for at each point in time. The total number of people don’t rise or fall in the intervening interpolation period. But if we were to assume that children departed/arrived at each type of place at a constant rate (maybe a more reasonable assumption), then suddenly we lose track of people. That is, the sum of people dips below 100% as people depart faster than they arrive.

What’s the alternative to linear interpolation?

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Life Tables are Cool

Demography is cool generally, but life tables are really cool in their elegance. Don’t know what a life table is? Let me ‘splain.

A life table uses data from private or public death registers, or even genealogical records, to identify a variety of survival and death estimates. Briefly, the tables include for each age:

  • Probability of death in the next year
  • Probability of surviving to the age
  • The life expectancy

There is more in the tables, but these are the big items that people often want to know. All of the various table columns can be calculated from survival rates. The US government and the UN each has created many such tables for a variety of time, locations, and development details. For example, the earliest and most dependable one is from 1901 and includes separate tables by race, sex, migrant status, urbanity, and even for some specific states.

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Everyone Happy? Student Loan Repayment

I like a good lump sum tax. People *must* pay the tax without exception and the advantage over current progressive marginal income taxes is that the marginal wage received doesn’t fall with greater earnings. Employment rises and output rises. To the extent that college students fail to understand their student loans, the indebted graduates essentially pay a lump sum tax each period.

Of course, the exception is income based repayment (IBR) – especially with forgiveness after X years. IBR adjusts the incentives substantially. Under the standard system, your wages are garnished if you fail to make loan payments. Under IBR, lower earnings trigger lower monthly payments. Clearly, in contrast to the standard method, IBR incentivizes more leisure, less income, more black market activity, and higher loan balances. Indeed, all the more so if there is a forgiveness horizon. Someone just has to have low enough income for say 15 years, and their past debt is forgiven (with caveats & conditions).

My principal objection to IBR policy is the resulting malinvestment in human capital. Defaulting on loans is a sign that some investment was inadequately productive to repay the resources consumed by its endeavor. We call that a loss. Real resources of time, attention, and goods and services were consumed in order to produce capital that failed to serve others more than the opportunity cost of those resources.

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5 Game Theory Course Changes

I want to share some changes that I’ll make to my game theory course, just for the record. It’s an intense course for students. They complete homeworks, midterm exams, they present scholarly articles to the class, and they write and present a term paper that includes many parts. Students have the potential to learn a huge amount, including those more intangible communication skills for which firms pine.

There is a great deal of freedom in the course. Students model circumstances that they choose for the homeworks, and they write the paper on a topic that they choose. The 2nd half of the course is mathematically intensive. When I’ve got a great batch of students, they achieve amazing things. They build models, they ask questions, they work together. BUT, when the students are academically below average, the course much less fun (for them and me). We spend way more time on math and way less time on the theory and why the math works or on the applicable circumstances. All of that time spent and they still can’t perform on the mathematical assignments. To boot, their analytical production suffers because of all that low marginal product time invested in math. It’s a frustrating experience for them, for me, and for the students who are capable of more.

This year, I’m making a few changes that I want to share.

  1. Minimal Understanding Quizzes: All students must complete a weekly quiz for no credit and earn beyond a threshold score in order to proceed to the homework and exams. I’m hoping to stop the coasters from getting ‘too far’ in the course without getting the basics down well enough. The quizzes must strike the balance of being hard enough that students must know the content, and easy enough that they don’t resent the requirement.
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5 Easy Steps to Improve Your Course Evals.

Incentives matter. I’ve taught at both public and private universities, and students have given me both great course evaluations and less great student evaluations. The private university cared a lot more about them. Obviously, some parts of student evaluations of their instructors are beyond the instructor’s control. The instructor can’t control inalienables and may not be able to change their charisma. But what about the things that instructors can control? Regardless of your current evals, here are 5 policies that are guaranteed to improve your course evaluations.

1: Very Clear Expectations/Schedule

Have all deadlines determined by the time that the semester starts. Students are busy people and they appreciate the ability to optimally plan their time. Relatedly, students desire respect from their instructor. Having clear rubrics and deadlines helps students know your expectations and how to meet them – or at least understand how they failed to meet them. Students want to feel like they were told the rules of the game ahead of time. This means no arbitrary deductions or deadlines. The syllabus is a contract if you treat it like one.

2: Mid-Semester Evaluations

One of the absolute best ways to improve your evaluation is to ask your evaluators for a performance update. Make a copy of your end-of-semester course evaluation and issue it about halfway through the semester. Then, summarize the feedback and review it with your class. This achieves three goals. (1) It is an opportunity to clarify policy if there are misplaced complaints. You may also wish to explain why policy is what it is. Knowing a good reason makes students more amenable to policies that they otherwise don’t prefer.  (2) It provides voice to students who have things to say. Often, students want to be heard and acknowledged. It’s better that a student vents during the informal mid-semester survey than on the important one at the conclusion of the course. (3) If there are widespread issues with your course, then make changes. If you’re on the fence about something, then take a poll. And if you decide to make changes, then be graciously upfront about it. Unexplained or covert changes violate policy #1.

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Easy FRED Stata Data

Lot’s of economists use FRED – that’s Federal Reserve Economic Data for the uninitiated. It’s super easy to use for basic queries, data transformations, graphs, and even maps. Downloading a single data series or even the same series for multiple geographic locations is also easy. But downloading distinct data series can be a hassle.

I’ve written previously about how the Excel add-on makes getting data more convenient. One of the problems with the Excel add-on is that locating the appropriate series can be difficult – I recommend using the FRED website to query data and then use the Excel add-on to obtain it. One major flaw is how the data is formatted in excel. A separate column of dates is downloaded for each series and the same dates aren’t aligned with one another. Further, re-downloading the data with small changes is almost impossible.

Only recently have I realized that there is an alternative that is better still! Stata has access to the FRED API and can import data sets directly in to its memory. There are no redundant date variables and the observations are all aligned by date.

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Prohibition Reversals

We have all heard of the prohibition era. Popularly, it refers to the period from 1920-1933 during which it was illegal to sell, transport, and import alcohol in the US. National prohibition was enacted by the 18th amendment and repealed by the 21st amendment. That’s the basic picture.

But did you know that there were state alcohol prohibitions prior to the national one? In fact, there were 3 major waves of state alcohol prohibitions. The first was in the 1850s, the 2nd was in the 1880s, and then the 3rd preceded the 18th amendment. The image below illustrates the number of states that had statewide dry policies. You can see the first two waves and then the tsunami just prior to 1920.

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Gari Melchers

Who’s your favorite artist? Warhol? Picasso? Van Gogh? Maybe someone much earlier, such as Michelangelo or Titian? Of course, there is something about the style or subjects that you enjoy. But something about the artist’s personal life might also matter to you. Personally, I’m a fan of Hieronymus Bosch, about whom we know little, and William Blake, who had some social and political opinions that would still be considered liberal even today.

Picasso, Dalle, and Warhol were all eccentric. Picasso had multiple girlfriends who didn’t get along, Dalle enjoyed exemplifying surrealism in his dress and behavior, and Warhol was a reclusive hoarder. Their eccentricity increases their allure and fosters an aura of mystique that they are privy to some unknown truths.

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Basic Immigration Logic

Economists overwhelmingly favor looser immigration controls. Allowing people to immigrate would improve the allocation of scarce labor and capital and it is a far cheaper way to aid poorer families than sending direct payments or trying to develop an entire country. Let’s cover some static analysis basics for migrating workers and their dependents.

Workers, Labor Markets, & Output Markets

There are two markets to consider: The new home country and the old home country. If workers leave the old country in search of the higher wages in the new country, then world employment remains unchanged. Employment obviously rises in the new country and falls in the old country. With identical laborers (a terrible assumption that’s the least charitable to immigration), wages in the new country fall and wages in the old country rise. This logic illustrates the cheap aid of which economists are fond.

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Competition and Racial Exclusion

There is a narrative about US history that goes like this: “Historical racism was really bad and limited opportunities for blacks. Blacks were not allowed to participate in a set of occupations and other civic life. The absence of blacks from typically higher income occupations reduced the number of competitors in those sectors. Not only did blacks have fewereconomic opportunities, the whites who were insulated from competition earned monopoly rents. Therefore, if blacks were excluded, the whites who were in exclusive sectors earned profits at the expense of blacks.”

The logic is neat. Are there any holes in it?Let’s see.

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