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Should Potential Employers have Access to Credit Scores ?

Robert Waldmann

Oh good, Kevin Drum and Matthew Yglesias disagree. This is bound to be interesting.

Drum remembers the good old days when liberals had less respect for the standard results of simple neoclassical economic models.

The specific issue is that firms are using credit scores to decide who to hire. This can trap some people as they can’t improve their credit score without a job and can’t get a job with their current credit score. Kevin Drum thinks the practice should be banned. Matthew Yglesias isn’t sure.

Yglesias wrote

But at the same time I try to adhere to the principle I outlined here and resist the urge to call for regulating the business practices of private firms when the issue isn’t pollution or some other case where the externalities are clear. After all, it seems like either this credit check business is a sound business practice (in which case allowing it is making the economy more efficient and ultimately building a more prosperous tomorrow) or else it’s an unsound business practice (in which case competition should drive it out).

That is actually a pretty radical position. I wonder what clear externality the 64 civil rights act addressed. I’m quite sure Yglesias doesn’t think what he seemed to assert, but I want to figure out what he had in mind.

Drum responds “More important is the fact that we liberals shouldn’t view the relationship between businesses and individuals as solely economic transactions” and gives an example

Here’s an example. Back in 1968, Congress passed the Truth in Lending Act. Among other things, it made credit card companies liable for charges on stolen credit cards over $50. In a purely economic sense, there’s really no excuse for this.

Ah how naïve. There is always an excuse based on economic theory (with the assumption of full rationality) for any policy. I view any assertion to the contrary as a personal challenge. This one is easy. Drum argues that the regulation creates a moral hazard problem as we are more careless with our wallets. I see his moral hazard and raise him an adverse selection (Hint: adverse selection is a great tool for justifying regulations as market outcomes are inefficient if there is adverse selection).

So let’s say everyone is better off with the regulation so the most wallet guarding yet not risk averse person is willing to pay extra to the bank in exchange for this protection. That doesn’t mean that this will be the market outcome. Let’s say a credit card company introduces a new card with the $50 limit. It will attract all the people who can’t keep track of their wallets. It will also attract people who commit a rare kind of fraud giving their card to an accomplice, having the accomplice buy stuff and then reporting it lost. There aren’t many of those, but there are enough that the extra interest (or other fees) that the company would have to charge would drive away everyone but the fraudsters and the most absent minded yet risk averse (I raise my hand). So the new product would enter the adverse selection death spiral.

The only solution is to force everyone to buy the protection which everyone wants if the fee is the actuarially fair fee for 100% coverage. Oh look, that’s the current law. That was easy. No sweat, no equations.

I mean Kevin you consider the health care reform debate and recall how forcing people to buy insurance, whether they want it or not, can be Pareto improving in a standard economic model.

Now on the original topic, I side with Drum. I think there is an externality. If people are rendered unemployable, maybe because of their fecklessness maybe because of their unluckiness there are externalities. For one thing the standard argument for laissez faire assumes we are totally selfish and absolutely needs that assumption to get the result. If desperate unemployable people cause others pain, then there is an externality. Another simpler externality is crime. People who are excluding from employment have little to lose from turning to crime. That’s an externality.

I’m pretty sure Yglesias’s idea is that both of these are arguments for redistribution from rich to poor and that such redistribution is more efficiently obtained by taxing and transferring. First, self esteem can’t be transferred. Good examples for the children can’t be transferred either. More importantly, there is no way that the feckless poor are getting much in the USA. You make policy with the electorate you have not the electorate you want. US voters are very willing to regulate business. They are totally unwilling to transfer money to people who firms don’t want to employ, because they seem to be irresponsible.

Assuming a social planner who taxes and transfers optimally is like assuming regulators can’t be captured or assuming that CO2 doesn’t cause global warming. That’s not the world we live it. I think we have to transfer however we can and that includes hiding information from potential employers. The loss in efficiency is a social loss only if one assumes that income distribution doesn’t matter (or assumes that there are optimal lump sum taxes and transfers which is an oxymoron). The link clicking reader will notice that my arguments are pretty much orthogonal to Drum’s.

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How to Build an Economic Model

Let us see if we can translate my previous post on job selection into an economic model.  Start with a basic formula:

(1) AcceptOffer = a(1) + a(2)*w + a(3)*b + a(4)*oa + a(5)*t

where a is a constant, w is wages, b is benefits, oa is “opportunity for advancement” and t is treatment received in the workplace.

The first observation we make is that several of these variables are difficult to quantify—and even more difficult to objectify. So let’s start with the easy ones.

w is very identifiable: reported (on a per capita aggregate basis), subject to enforcement penalties (e.g., minimum wage laws), and used in “downstream applications” (e.g., tax filings) and therefore relatively verifiable.

b is (1) known to be non-negative and (2) often variable within, let alone between, organizations. (Vacation time, sick days, insurances offered and costs to the employee all may vary depending on level, time of service, location of office, etc.)

This could present a problem, but here we can use standard economic theory to our advantage. We do not know the amount of b, but we can assume that the employer is rational, and is offering a total compensation to the worker that s/he expects will be less than or equal to the marginal product of that person’s labor. We therefore can reasonably assume that b is related to w. If we then review the available aggregate data we can approximate that benefits offered will be approximately a certain percentage of w—and that workers will assume that assumption (and, in most cases, verify that assumption within a margin of error) before accepting the job.

We then restate the equation as

(2a) AcceptOffer = a(1) + a(2’)*w’ + a(4)*oa + a(5)*t

where w’ is the weighted combination of w and b above, and a(2’) is the restated coefficient.

If we then assume that all parties have full information of the ratio of wages to benefits, then a(2’) = a(2)=a(3), so we simplify to:

(2b) AcceptOffer = a(1) + a(2)*w’ + a(4)*oa + a(5)*t

We now have to consider opportunities for advancement and treatment. Here, we have two problems that are difficult, possibly insurmountable, for modeling.

The first is a lack of measurability. There are no public records for “didn’t get promoted.” Nor, except in extreme cases, is there a way to measure treatment by supervisors. The data that might be available&mdassh;lawsuits, official complaints, even Human Resources files (for which there are significant privacy considerations)—is all negative and, accordingly, skewed (biased). This is because (a) ninety percent or so of all workers and/or bosses will never have a complaint filed against them and (b) the ability to file a complaint may be present because the general work atmosphere is more amenable to filing one than not, so the presence of a complaint is not in itself a good or bad thing for the overall measure.

The second is that tolerances vary by person. To use an absurd example, people who use “Every Breath You Take” for their wedding may be more likely to tolerate attentions that others view as harassment. Similarly, forcing people to clock out for a “smoke break” will be viewed differently depending upon whether one is a smoker or not. General policies are just that—general.

So, if we are building an economic model, we must come up with a reasonable approximation of these last two variables. The most direct way to do this is the standard method: assume each individual has their own Utility Curve, and “prices” accordingly.

Based on their preferences and options, then, we map the compensation required to offset negative consequences from oa and t. While the variables still are not directly observable, we can make a simplifying assumption:

Assume that the compensation required to do the work is a factor of w’.

Have to work in the sewer system? Change w’ to compensate. Need to work the night shift and/or weekends? Same type of adjustment. Boss clearly favors buxom blondes and you’re a petite redhead? Adjust current salary requirements to compensate for lowered opportunity for advancement/promotion. You’re a b.b. who will have trouble getting work done because the boss will harass you? Adjust accordingly.

We assume—due to the constraint: a lack of available data—that we can reduce “a(4)*oa + a(5)*t” to some proportion of w that will compensate the worker for the environment into which they are being placed. If we further assume that the worker has complete information as to hisser preferences, the worker will not accept a job that does not offer that level of compensation.

So we can restate equation 2(b) using the Utility Curve assumption. Assume

(3a) a(6)*w” =a(4)*oa + a(5)*t

such that w” also proportionate to w(and therefore w’ as well) and a(6) is the coefficient selected by the individual that makes the offered wage compensatory to the opportunities for advancement and expected treatment on a Present Value basis.

We can then reduce equation (2b) to

(3b) AcceptOffer = a(1) + a(2)*w’ + a(6)*w”

or, given that (a) w” is proportionate to w and w’ and (b) that the multiplier in most cases is 1, and (c) the constant (e.g., signing bonus) can be assumed without loss of generality to be 0,

(3b) AcceptOffer = clip_image002[10]

to indicate that the value varies with individuals.

To concretize the example, assume that a redhead and a blonde, as above, are both offered a job. Assume further that the redhead’s compensation requirement—lower-but-still-positive opportunity for advancement—is lower than the blonde’s for will-be-harassed-and-work-will-be-impeded. That is

clip_image002(r) < clip_image002[4](b)

There are four possibilities:

  1. The offered wage will be belowclip_image002[12](r), in which case neither will accept the job
  2. The offered wage will be below clip_image002[14](b) but above clip_image002[16](r), in which case one of the two positions will be filled
  3. The offered wage will be above clip_image002[18](b), in which case both will accept the offer and the company will have offered a higher wage than was required to fill both positions. (That the offer is what the company believes will be the employees’ s marginal product of labor [MPL] is a collateral issue.), or
  4. The company will negotiate with each, offering the redhead clip_image002[20](r) and the blonde clip_image002[22](b), and everyone will be happy—so long as initial expectations were accurate (or, if you prefer, the new employees both had full information).

Note also that there is a learning process for both the applicant and the employer. Offers and demands will be adjusted based on historic data (if both decline the offer, the next candidates of similar background will be offered more, and perceptions of growth (improvements in experience and/or education by the worker).

If we generalize this, we note that there is a distribution of clip_image002[24] (due to Individual Preferences). If we further make simplifying assumptions—e.g., a normal distribution of clip_image002[26] among the population—we come to the conceit of the “reservation wage,” and all the economic literature that is attendant upon it.

So that is how you build an economic model.  The question then becomes: how do you use it? A relatively short (though it does incorporate a micro model) discussion of that continues below the fold.

The problem—if it is one (I’m inclined to argue it is; YMMV)—is that, having built a model in which all the proxying assumptions are “simplified” into a single variable, we lose some granularity, having made a trade-off for the sake of measurement.

Accordingly, a change in the “reservation wage” may not in itself tell us whether the real wage has gone up or the work environment has become, on balance, more or less acceptable.

Again, an example, one that will be familiar to students of microeconomics. You are given two choices: (1) you can receive $100 right here and now or (2) you can travel a known distance (say, five miles)—with a finite chance of death or injury—and receive $1,000,000 on completion.

Surroundings, at this point, matter. If the five miles traveled is as an American soldier in full uniform walking outside of the Green Zone, you might well choose $100. Even when you are native to the area, the choice may vary: walking five miles through one gang’s territory is a different option than traveling that distance through different territories. Or even a pure environmental matter may have an effect: Walking five miles through a desert with no canteen, or having to swim five miles from shore in a dangerous waters, is not the same risk as walking five miles down an unpaved dirt road in the middle of the day. Even if you would be required “only” to walk down a heavily-used interstate highway with no shoulder or sidewalks, discretion may be the better part of valor.

Over time, through the “learning process” (op cit. Arrow, 1962, as all good op cits must), the dollars offered will be adjusted so that the payouts balance on a risk-adjusted basis. (Collaterally, there may be other reasons for the greater payouts; signaling by any other name.)

Now suppose the landscape changes. There is a canteen every half-mile in the desert. A gang is run out of its territory, or takes over another’s territory. The Green Zone becomes larger.

The balance has changed; the risk is different. The job is demonstrably different, and therefore requires lower (higher) compensation. But the difference has nothing directly to do with the base salary/benefits requirement and everything to do with the overall attractiveness and/or treatment received.

If we were to forget that, we would conclude that there is more demand for the job itself, and therefore people are willing to take a lower salary. If, on the other hand, we keep in mind that there are more factors to the reservation wage than just the salary itself, we realize that producing a more pleasant work atmosphere is beneficial to our firm, as it enables us both to present a good face to clients and to reduce our cost of labor.

The first type of economist probably should be avoided, as he adds very little value to the discussion of how to use the model.

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Vague Thoughts on The Theory of the Firm, the Business Cycle and Kurt Vonnegut

Robert Waldmann

Don’t say you weren’t warned. I am trying to understand the effects of the switch from mechanically controlled machine tools to electronically controlled machine tools and then to digitally controlled machine tools. I don’t really know much about machine tools, but, then again, I don’t know much about firms or the business cycle either. My thoughts after the jump.

update: spelling checked

I warn again, don’t trust any claims of fact in this post.

The reference to Kurt Vonnegut is a reference to “player piano” a dystopian vision of mass unemployment due to industrial robots. It seems that Mr Vonnegut never checked how many people are actually employed in manufacturing, since he asserted that there would be massive unemployment even if people demanded services from other people. So I am not going to predict massive unemployment.

I am partly stimulated by the Nobel Memorial Prize committee which gave the prize to Oliver Williamson for new contributions to the old theory of the firm — that is for trying to figure out the optimal amount of vertical integration. In very brief Williamson argued that vertical integration is efficient when intermediate goods are made with inflexible capital.

IIRC They key example is stamps for bashing metal which shape metal into one form. He noted that arms length market transactions don’t work in this case. Once the parts supplier has sunk money into the specific capital, the final goods manufacture can pay a price equal to marginal cost giving it 0 return on the sunk cost. Thus only a fool will sink money in capital which produces a good for only one possible customer without any guarantees. A long term contract promising to by a fixed amount of the part for a fixed price can make the transaction possible. Similarly things work out fine if the parts are made by the same firm which makes the final product, since the firm has no incentive to take advantage of itself.

(a bit of jargon here. To pay marginal cost to a supplier who has paid a fix cost of building specialized capital is called “to seize the quasi-rent produced by the capital.” I will strikestick with “take advantage of” below.)

Note the example depends on the inflexibility of capital. Once it applied to grinding and assembling as well as stamping. That is, I am changing the subject to equipment which grinds, assembles, welds etc. The specific example of metal stamps still works, but many other productive processes have evolved in a way that protects a parts supplier from ruthless bargaining by their customer, the final goods producer.

Once upon a time, machines which ground and welded and so forth were controlled by the hands of skilled artisans. Also parts were put together by human hands. Then it was noted that a machine could do that on its own with its active bits (drill bits for example) guided by metal guides, by oddly shaped metal parts through which other metal parts slid or by oddly shaped gears.

This made it possible to substitute pieces of metal for people and the pieces of metal demanded no wages. The problem is that the machine could do only one thing. To make the mechanically controlled machine tool do something else, new metal parts had to be designed and made and the mechanically controlled machine tool and to be disassembled and reassembled. This process is called “re-tooling”.

Then technology shifted to analog electronically controlled machine tools (as described by Kurt Vonnegut). The movements were controlled by electronic signals read off a magnetic tape. The machine tool could be, in effect, retooled by leading it through the new motions once. I don’t know how this was done, but I assume that a manual control (like a joystick or something) was plugged in and the tape recorder was set to record. Then someone could try to make the machine tool perform a new task and keep trying and recording over the tape till the controller did it well (via the joystick). Probably frustrating, but quicker than designing, casting disassembling and reassembling.

Then they went digital. Now the motions are described with equations and the new instructions are typed on a keyboard. No one with skilled hands was needed (I mean the equations could be typed in by hunt and peck if necessary). The tragic irrelevance of the artisan in the digital age was made by David Noble (who was allegedly denied tenure at MIT, because he noted that technology is not everyone’s friend).

This made manufacturing much more flexible. This reduced the optimal degree of vertical integration. If suppliers just have to reprogram their machine tools when their current customer tries to take advantage of them, then they don’t neeed to be a long term contracts nor is efficiency enhanced if they merge with their customer.

Why low and behold, large firms are outsourcing more and more in the age of digitally operated machine tools. I’m sure Prof. Williamson has noted this fact which supports his analysis.

I am interested in something else — the business cycle. I think that increased flexibility helps us understand the late great moderation (near absence of the business cycle form 1982 through 2007), the reduction in temporary layoff unemployment, the unprecedented current average duration of unemployment, and the joblessness of recent recoveries.

The point is that it used to be that a rule of manufacturing is that when demand is slack one shuts down and retools. Producing new products and improving efficiency required a fairly long period without production — the period during which the machine tools were disassembled. Relatively few people were employed disassembling, and reassembling the mechanically controlled machine tools. Thus temporary layoffs were a necessary part of innovation. Given that, firms decided to schedule them at a time when demand was slack. If all firms have the same policy, recessions can happen due to a sunspot. In practice they had something to do with monetary policy and/or oil shocks, but the instability of the system made frequent severe recessions possible.

If it takes minutes not weeks or months to digitally retool, then there is no technological need for temporary layoffs. It might be better to deal with slack demand by cutting prices rather than production. Sometimes firms will choose to shut down a factory permanently, but they will have less reason to shut it down for weeks or months but not forever.

In fact, there has been a massive reduction in temporary layoff unemployment, and, in particular, in temporary layoff unemployment during recessions. This implies weaker recoveries — permanently laid off workers need to find new jobs and expanding firms need to find workers. In particular, this implies a less rapid increase in employment in recoveries. Finally it obviously implies longer average spells of unemployment for the same unemployment rate.

Many stylized facts about the changes in the business cycle can be explained by increased flexibility of capital, including, in particular, digitally operated machine tools.

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The Measured Version of My Screaming

John Quiggin finally makes explicit What Everyone Knows: that the clusterfuck that has been made of Macroeconomics is due largely to an attempt to leverage (insufficiently robust) Microeconomic Theory:

the search for a macroeconomic theory founded on (roughly) neoclassical micro, which has been the main direction of macro research for 40 years or so, was a wrong turning, forcing us to retrace our steps and look for another route.

Think Lucas and Prescott as Mirror-Moses, leading gullible Macroites further and further from the Promised Land, themselves evermore unable to ask for directions.* Couldn’t have said it better, or with so few expletives, myself. But then, that’s why he has a book contract.

Read the Whole Thing.

UPDATE:*Or, probably more accurately, think the years Christ spends between “I have thirst” and realizing that his long, happy peaceful life was The Last Temptation, as per the movie and novel of that name.

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The Problem with Macro is Micro

John Quiggin makes the broad case (link fixed).

If you are then stuck with trying to present a Grand Unified Field Theory, you will inevitably lose (or, at best, reduce) the importance of all the agglomerations that follow from the presumption that the Rational Actor is the mean performer—ignoring that no one, including the economists themselves, believes that to be true in their own lives, let alone the lives of others.

Micromotives and Macro Behavior indeed. But no molecular biologist (or even biologists) would try to build on the Phlogiston Theory.

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