Intro to Econ: First Lecture – People pursue Goals

Much of economic theory is developed with one very simple guiding principle: People pursue goals. They may do so consciously or unconsciously. I think the following (thought) experiment demonstrates that human behavior is not entirely unpredictable, that in some cases there are some very simple principles that can explain a fair amount of behavior, and at the same time demonstrates why economic theory will almost never provide perfect predictions.

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Intro to Econ: First Lecture – What is Economics?

It is not easy to specify exactly what does and what does not constitute an economic problem. Some people like to say that “economics is what economists do”, which tells you only that it is not completely clear what the boundaries of economics are. A traditional definition is that “economics is about the allocation of scarce resources that have alternative uses” or that “economics is concerned with human behavior in the ordinary business of life and the societal implications of such behavior”. I find all of these useful but still somewhat unsatisfying.

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A New Keynesian toy model

I’ve been keeping a collection of “toy models” on my computer. I do this for two reasons. First, building them is a lot of fun and useful as a kind of intellectual work-out to develop the “model-building” regions of my brain. Second, I think they help clarify my own thinking about economic issues.

I’d like to share one of my favorite toy models with you. I learnt it from Cedric Tille when I was at the IfW Kiel. The purpose of this model is to show the basic intuition behind a strand of literature called “New Keynesian” macroeconomics. The NK approach can be thought of as a combination of the techniques of the “Real Business Cycle”  literature (rational expectations, continuous market clearing, dynamically optimizing agents) with “old” Keynesian economics (monetary policy has real effects, government spending has a multiplier effect, etc.). The model is simple enough to be taught to first-year econ students and at the same time rich enough to provide a basis for discussion of the effects of monetary policy, technology shocks, fiscal policy, the distinction between expected and unexpected shocks and more. It is also much closer to current macroeconomic research than the usual AS-AD model contained in most textbooks. The model has a natural extension to an open economy setting, which is contained in this paper by Corset & Pesenti.

Here goes.

Technology. An economy’s output (Y) is produced by labor (L) alone. The aggregate production function is

Y = A*L,                           (1)

where A is the technology parameter (labor productivity).

Households. Households consume output and supply labor. They trade off the marginal utility from consumption against the marginal disutility of working. Under usual assumptions about the shape of utility functions, consumption will be an increasing function of the real wage. Denoting the nominal wage by W and the price level by P, let household consumption (C) be given by

C = k*(W/P),                 (2)

where k is a positive parameter. The basic intuition behind this consumption function is that a higher real wage induces people to substitute consumption for leisure (substitution effect) and raises their real income (income effect). Both effects act to increase consumption, while the effect on labor supply is ambiguous.*

In order to purchase goods, households must hold money. Money demand (M) is a function of nominal consumption spending:

M = (1/v)*P*C,             (3)

where v is the (exogenous) velocity of money. Note that this is just a versions of the quantity theory of money. The money supply is set by the central bank and exogenous to the model. We will think of M as describing the stance of monetary policy.

Firms. Firms compete in a monopolistic way, i.e. each firm has a monopoly over the specific kind of consumption good it produces, but there is a large number of close substitutes. It can be shown that under this kind of competition, the aggregate price level will be set as a mark-up over marginal costs of production. Nominal marginal costs are equal to W/A — it takes 1/A hours to produce one unit of output and each hour costs W euros.

Crucially, firms must set prices before learning the labor productivity and the monetary policy stance. Hence, they must form expectations about nominal marginal costs. Let z be the mark-up, which indicates the market power of firms (which in turn depends on how “tough’’ competition is in the goods market). Then the price level is given by

P = z*E(W/A),               (4)

where E() denotes the expected value conditional on information available to firms when they set prices.

Closing the model. The model is closed by the goods market clearing condition:

Y = C.                              (5)

This is a model with five endogenous variables (Y, C, L, W, and P) and two exogenous variables (M and A). Let’s find the general equilibrium of this economy. First, combine (2) and (3) to get
W = (v/k)*M.                (6)
Taking expectations and inserting into (4) yields
P = (z*v/k)*E(M/A).               (7)
Next, combine (3), (5) and (6) to get
Y = (k/z)*M/E(M/A).              (8)
Re-inserting this into (1) yields
L = (k/z)*[M/A]/[E(M/A)].   (9)

Equilibrium. Suppose that, in the long run, expected values equal actual values, i.e. E(M/A)=M/A. This is just the rational expectations assumption which in this context means that firms don’t make persistent, systematic mistakes in forming expectations about productivity and monetary policy. With this assumption, (8) reduces to

Yn = (k/z)*A,

which we can call the natural rate of output or full-employment output. It increases in productivity and decreases in the degree of monopolistic distortions. The long-run (“natural”) level of employment is given via (9) by

Ln = k/z.

Using these results in (8) yields

Y/Yn = [M/A]/[E(M/A)].

This equation relates the ratio of actual to natural output (the output gap) to the monetary stance and the state of technology. What exactly does this mean?

  • An unexpected increase in money supply raises output over its natural level. The reason is that an increase in M while P is fixed makes households spend more which raises output and employment.
  • An unexpected increase in labor productivity reduces the output below its natural level. The reason is that a higher A increases potential output, but does nothing to stimulate household spending. Hence output stays the same while labor demand (and therefore employment) falls. So a positive technology shock produces underemployment in the short run.
  • Expected changes in monetary policy or technology have no effect on the output gap. In the long run, money is completely neutral with respect to Y and L.
  • If the central bank has a way of knowing A in advance (for instance, because they employ competent economists who can forecast A perfectly), they could set M in such a way as to completely stabilize the economy at the natural output level. They “simply” have to set M=b*A.

Fiscal policy. How do we get fiscal policy into the model? Easy. Just add government spending into the goods market clearing condition:

Y = C + G                                     (5*)

and assume for simplicity that the government makes spending proportional to total output G=g*Y. (You also must assume that the government finances its expenditure by lump-sum taxes on households only so that firms’ pricing decisions and households’ labor supply are not distorted.) In this case natural output becomes

Yn =(k/z)*A/(1-g),

which increases in g. Government spending doesn’t affect the output gap, though, because it moves actual and potential output by the same amount.

 

*) A utility function which gives rise to such a consumption function is U(C,L) = log(C) — (1/k)*L.

Rationales Entscheiden bei Radikaler Unsicherheit

Für diejenigen, die es verpasst haben oder es noch einmal sehen wollen! Hier ist ein Video meiner Antrittsvorlesung an der Universität Graz, vom 19. Oktober 2016:
Rationales Entscheiden bei Radikaler Unsicherheit“. Der Vortrag beruht auf meiner Arbeit “Abraham Wald’s Complete Class Theorem and Knightian Uncertainty“.

Einkommenseffekte der Flüchtlingskrise: Eine Pi-mal-Daumen-Rechnung

Im Jahr 2015 erreichte die Immigration nach Österreich einen Höchststand. Der Nettozuzug betrug ca. 113.000 Menschen, fast doppelt so viele Menschen wie im Jahr davor. Davon kamen 75.650 Menschen aus sogenannten Drittstaaten, der Rest aus der EU und assoziierten Saaten wie der Schweiz. Hauptgrund dieses Anstiegs war natürlich die Flüchtlingskrise, die riesige politische und mediale Aufmerksamkeit bekam. Zu den vielen heißen Themen in diesem Zusammenhang gehört die Frage nach den wirtschaftlichen Auswirkungen der Immigration. Weil ich im kommenden Semester eine Vorlesung in internationaler Ökonomik halten werde, dachte ich es wäre nützlich sich einmal anzusehen was das Lehrbuch zu dieser Frage beizutragen hat.  Also habe ich folgende vom Lehrbuch inspirierte Pi-mal-Daumen-Kalkulation aufgestellt.

Das Bruttoinlandsprodukt Österreichs im Jahre 2015 betrug 339.896 Mio. Euro und die Zahl der Erwerbstätigen 4.148.400. Die Lohnquote betrug 69 Prozent. Unterstellen wir, dass Österreich eine Cobb-Douglas-Produktionsfunktion mit einer Arbeitselastizität von 0,69 aufweist. Des weiteren gehen wir in üblicher Lehrbuchmanier davon aus, dass alle Immigranten in den Arbeitsmarkt integriert werden und vollkommener Wettbewerb herrscht.

Konzentrieren wir uns auf die 75.650 Einwanderer aus Drittländern. Diese Menschen kommen zum überwiegenden Teil aus armen Ländern, sind relativ jung und bringen daher wenig Kapital mit. Wir behandeln daher diesen Zustrom als reine Verschiebung des Arbeitsangebots — und zwar von 1,82 Prozent der Erwerbstätigen.

Gegeben unsere unterstellte Produktionsfunktion würde das zu einem Anstieg des BIPs von 4.265 Mio. Euro bzw. 1,25 Prozent (= 0,69 x 1,82) führen. Das ist schon mal keine Kleinigkeit! Nur zum Vergleich: Der Effekt des Handelsabkommens TTIP aufs BIP wird auf 0.5 Prozent geschätzt.

Wie verteilt sich dieser Gewinn auf verschiedene Bevölkerungsgruppen?

Zusätzliche Arbeitskräfte führen zu einem niedrigeren Grenzprodukt der Arbeit und daher zu sinkenden Löhnen. Unter meinen Annahmen sinkt der Lohnsatz um 0,56 Prozent (= (1-0.69) x 1.82). Das geht primär zulasten der heimischen (also nicht zuwandernden) Arbeiter, deren Gesamteinkommen somit um 1.310 Mio. Euro sinkt (= -0,0056 x 0,69 x 339.896 Mio.). Die Gewinner sind die heimischen Bezieher von Kapitaleinkommen und anderen Einkommensarten außer Löhnen. Ihr Gewinn ergibt sich zum einen daraus, dass sie die heimischen Arbeiter billiger beschäftigen können, zum anderen (kleineren) Teil aus der Möglichkeit, die zugewanderten Arbeitskräfte gewinnbringend zu beschäftigen. Insgesamt entsteht ihnen so ein Einkommenszuwachs von um 1.322 Mio. Euro (=0,31 x 4.265 Mio.). Das ist ein durchaus beträchtlicher Einkommenstransfer innerhalb der heimischen Bevölkerung — so als würde jeder österreichische Arbeiter mit einer Steuererhöhung von 300 Euro pro Jahr belastet, deren Ertrag zur Gänze an Kapitalbesitzer fließt.

Unterm Strich bringt die Zuwanderung der heimischen Bevölkerung also ein kleines Einkommensplus von 12 Mio. Euro (= 1.322 – 1.310 Mio.), sodass der der Großteil des BIP-Zuwachses (4.243 Mio. Euro) an die Zuwanderer selbst fließt. Das ist natürlich eine direkte Folge der Annahme vollständiger Konkurrenz am Arbeitsmarkt, die impliziert, dass jeder ungefähr das verdient, was er zum BIP beiträgt.

Also fassen wir zusammen: Die Eingliederung der Immigranten in den Arbeitsmarkt bewirkt einerseits einen spürbaren Anstieg des BIPs, andererseits eine Umverteilung von heimischen Beziehern von Arbeitseinkommen hin zu heimischen Kapitaleinkommen. Diese Rechnung ist selbstverständlich nur als erster Anhaltspunkt zu verstehen und soll nur dazu dienen einmal die Größenordnungen abschätzen zu können. Aller Vereinfachungen zum Trotz glaube ich, dass die grobe Richtung, in die diese Kalkulation deutet, richtig ist.

How to make students honest in exams

One of my favorite economists, David Friedman, suggests an economic solution to a problem that every teacher has probably faced.

In most exams, students have an incentive to respond to a question even if they do not know the answer. If they do not respond at all, they will get zero points with certainty. If they write something – anything – there is some probability that they will get at least a few points, maybe because they guessed the correct answer or because the teacher reads what he or she wants to read.

Pretending to know the answer when you don’t is an economically wasteful activity. It is a waste of time for the student as well as for the teacher who has to grade the exam. It is also, at least potentially, a distortion of the signal embodied in exam grades, because students who pretend to know might do as well on the exam as students who really know.

Friedman’s solution: Award 20 percent of the points for the response “I don’t know”. Students who know less than 20 percent or are less than 20 percent sure that they know the right answer will respond, rationally and honestly, “I don’t know”. Students who know more or are more certain of their knowledge will give their answer.

Now behavioral economists might object that students may be overconfident, i.e. they overestimate their true abilities and give an answer not because they pretend to know, but rather because they truly believe they know. However, even overconfident students – those who, for instance, put the probability that they know the right answer at 50 percent when in fact they don’t know it – might still prefer to answer “I don’t know”, because that guarantees them a certain outcome of 20 percent of the points whereas writing an response they are unsure about means risking losing all the points on the question.

Anyway, I love the solution. I think I will try it in my course. It is also a good example of how simple economics – thinking through the implications of rational behavior – helps solving a non-economic problem.