Author: Zachary Bartsch

It Takes a Village

Zachary Bartsch3 Comments

Many households are now 2-income households. And that can make parenting a slog.

You go to work for 8-10 hours, you may or may not need to provide transportation for children to/from school, and child-care can eat a substantial portion of income. If the children are small, then the parents clean the floors, the dishes, and the clothes. Not to mention any home improvements or repairs. And food! Do you want to eat a home-cooked meal as a family? If both parents work typical hours, then prepare to eat no earlier than 6 PM, and maybe as late as 7:30.

Hey but there’s the weekend, right? NOPE! Someone has to do that big weekly shopping trip. How long is that going to take? The whole ordeal is enough to make someone think twice before having that 2nd kid. After all, if one kid getting sick throws a wrench in even a single day’s routine, then the whole week can be affected. How many sick kids before things stop getting done? Having a grandparent around to help would be a huge privilege and blessing.

At this point, I think that I can begin to call myself an experienced parent. I’ve got 4 kids who are ages 6 and younger. Plenty of modern conveniences make life easier. Many groceries can be purchased ahead of time for ‘order pick-up’ or online for delivery. Nice. Books are super cheap, and so are bubbles and drawing supplies. If I have to get some work/chores done while the kids are awake, then I can buy myself some time. But, like it or not, when the kids are asleep in the evening is when most chores will get done.

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Hand-in-Hand: Demand & Technology

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In standard microeconomics, the long-run demand is unimportant for the market price of a good. Firm competition, entry, and exit causes economic profits to be zero and the price to be equal to firms’ identical minimum average cost. This unreasonably assumes that they have constant technology. That is, they have a constant mix of productive inputs and practices.

Just so we’re clear: time is passing such that firms can enter, exit, and adjust the price – but no productive innovation occurs. For the modeling, we freeze time for technology, but not for other variables. The model ceases to reflect reality on the margin of scale-induced innovation. The standard model assumes an optimal quantity of production for each firm and the only way for total output to change is for there to be more or fewer firms. The model precludes adopting any different technology because firms are already producing at the minimum average cost – if they could produce more cheaply, then they would.

Enter Scale

One of my favorite details about production was taught to me by Robin Hanson.* Namely, that the scale of production isn’t merely with the aid of more raw materials, labor, and capital. There are perfectly well-known existing technologies and methods that reduce the average cost – if the firm could produce a large enough quantity. This helps to illustrate what counts are technology. A firm can achieve lower average costs without inventing anything, and merely by adopting a superficially different production method.

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Dysfunctional Virtue: A Tale of No Profits

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For-profit firms are well-oriented. The managers within firms may not make profit their only explicit priority, but it is pre-requisite to their other concerns. Without profits, firms eventually cease to exist. Non-profits are different. They might have revenues due to sales and operate much like a for-profit firm. But, they many times operate on revenue from donations and endowments. Because the success of non-profits is harder to measure, the signals of triumph and defeat do not orient the employees as clearly. The result can be that there is a lot of ruin in a non-profit. Plenty of tasks are done inefficiently, poorly, or not at all.

Mission-driven non-profits are able to attract enthusiastic, dedicated employees given the pay that they offer. But, supporting the mission of such an organization often acts as an implicit “belief test”, filtering out other would-be job applicants who self-select out of applying to open positions for which they are otherwise qualified. Indeed, part of the purpose of mission statements is to filter for the kind of employees that the organization managers or donors desire. While the employees may be enthusiastic and dedicated to the mission, that is mostly separate from whether they have the technical skills to flourish in their position and to effectively serve the organization.

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[Not] Choosing Rationally

Zachary Bartsch4 Comments

I’ve written previously on game theory, about the generality of Pure Strategy Nash Equilibria (PSNE), and the drawbacks of Sub-Game Perfect Nash Equilibria (SGPE). In this post I have another limitation for SGPE.


First, some definitions:
PSNE: “No player can change one of their strategies and improve their payoff, given the strategies of all other players.”
Subgame: “A subset of any extensive-form game that includes an initial node (which doesn’t share an information set with other nodes) and all its successor nodes.”
Subgame Equilibrium (SGE): “The PSNE of the Subgame”
SGPE: “The set of PSNE that are also SGE”


Clearly, there is nothing inconsistent about the above definitions. The reason that SGPE emerged was because some PSNE assert that a player would be willing to choose strategies that do not maximize conditional payoffs in subgames that are off of the equilibrium path. So, people often characterize the SGPE as a player ‘being rational each step of the way in each subgame’.

But, there is a problem. “Each step of the way” and “in each subgame” are not the same thing. Each step of the way implies that a player is rational at each decision – ie, at each information set. But, not every information set is a subgame! So, a SGPE can include rationality at each SGE while also permitting some irrationality at individual information sets. Since economists like to identify the bounds of their claims, let me emphasize the word can. In order to be correct, I need only identify one case in which the claim is true.


Here is that case:

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Interpolation Vs Transition

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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

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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

Zachary Bartsch3 Comments

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

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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.

Zachary Bartsch2 Comments

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

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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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