LABOUR MARKET BEHAVIOR IN MACROECONOMICS:
Dynamics and Cycles
Jeremiah Allen
©2004
There are two separate issues in macro-level Labour Market behavior: one I call “dynamics”, the
other I call “cycles”. The first is about how labour market behavior interacts with other
macroeconomic variables in both the Short-Run and the Medium-Run. In particular, here we are
interested in what produces labour market dynamics, and how those dynamics can affect the level of
Yn and, therefore, un. The second issue is about how the labour “market” behaves over the business
cycle. Here the cyclical effects are exogenous. Labour market variables react to changes in output.
The issue is which important variables are pro-cyclical, which are counter-cyclical, and why? That
is, what type of labour market behavior drives the labour market cycles we see? In all cases the
labour market behavior is observed at a macro-level, but it is derived from micro-level theory. Here I
concentrate on the macro-level observations. If you want to see a derivation from micro-level theory,
see my RRS paper in your package.
I summarized the empirical observations of Phillips and the theory of Phelps, which led to the
DAD/DSAS model, in my “Output/Inflation Dynamics” notes. Here I first explain and summarize
the theory of Lipsey, which produces some interesting dynamics. I haven’t yet integrated these with
the DAD/DSAS model. Then I give a short description of the “flows approach” to labour market
behavior over the business cycle. This provides the link between labour market cycles and the
DAD/DSAS model. Last I summarize the empirical observations of the cyclical behavior of a
number of labour market variables, and discuss how these relate to two different types of macroeconomic theory.
Note on symbols: I continue to use italicized UPPER CASE ROMAN letters for variables which
are determined by numbers: eg, Ht, Jt . Rates, like unemployment rate, ut, are lower case, as are
parameters.
I. LABOUR MARKET BEHAVIOR: LOOPS, and the “TIME VARYING NAIRU” or
“HYSTERESIS”
A. Loops, Lipsey and Labour Market Behavior
All supply-side models also have difficulty with the loops, and with “hysteresis” or “TimeVarying NAIRU”. (This latter phenomenon is described in Gordon.) The New-Keynesian model,
because it’s based on a correct model of labour market behavior, has no difficulty with these.
There are four strands to the reasoning here, which weave together to produce a coherent picture.
The first strand is empirical. Labour economists observed what they labeled “hysteresis”. Hysteresis
is the fact that the NAIRU, un, the level of unemployment associated with Yn, isn’t a constant. It isn’t
just that it moves around, it moves around systematically. If unemployment stays low for some
period of time, the NAIRU falls, and if unemployment stays high for some period of time, the
NAIRU rises. This is described in Gordon, but it was known well before he wrote that paper. It was
observed in most OECD countries during the eighties, when unemployment rates were high for a
contracted period.
The second strand is Phillips’s finding of the counter-clockwise loops around his eponymous
curve. The third strand is Lipsey’s explanation for those loops. The fourth and final strand is also
empirical – it is the actual labour market behavior over the business cycle. You can read Gordon. I
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summarize Lipsey below. Here, for simplicity, I treat inflationary expectations, et , as zero, so I can
ignore them.
Phillips found counter-clockwise loops in the dynamics of his curve, as shown in Figure 1 below:
Figure 1
Wt
3
2
4
1
5
0,6
ut
un
Figure 1 shows the dynamics of unemployment and W during a typical seven period cycle (0 – 6) of
output from trough to trough. Lipsey proposed an explanation for these loops based on the geometry
of the curve and how that affects the aggregation.
First, he noted that the shape was a generalization of a basic Supply and Demand model for
labour. The horizontal axis can be read as: (S–D)/S, where S and D are quantity of labour Supplied
and quantity Demanded in a market. The point where S = D is un, the point where the curve crosses
the horizontal axis. This is shown in Figure 2 below. (You can see more details of Lipsey’s
theoretical derivation in Bruce.)
Wt
Figure 2
(St – Dt)/St
0
Lipsey then transformed the straight line into the curve for two reasons. First, u cannot be less
than zero, so the curve must asymptotic to some vertical line as it moves left – that is, as (St–Dt)
becomes increasingly negative. This is the dotted line on Figure 2, where ut = 0. Second, observing
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that money wages are sticky downwards, the curve must become asymptotic to some horizontal line
as it moves right – that is, as (St–Dt) becomes large and positive. (Here I use Wt = 0 as the
asymptote; it’s probably a bit lower.) This produces a smooth curve, which is the Phillips curve.
The Phillips curve is an aggregate – a curve for the economy as a whole. But Lipsey noted that
the basic Supply and Demand model applies at all levels of the economy: sectors, geographic regions,
and even individual firms. At each of these levels it would have the shape found by Phillips.
However, when aggregating these lower level curves, something interesting happens. [Note, I will
label these sectoral curves as “p-curves”, while maintain the label of the aggregate as the Phillips
curve.]
Consider an aggregate economy consisting of three lower level labour sectors, labeled A, B, and
C. These could be regions, industrial sectors, or occupations, or any combination of these. For
simplicity, I’m going to condense the upswing of a business cycle – that part of the cycle from trough
to peak – to just three time periods. The trough is period 0, the peak is period 2, and period 1 is the
middle of the upswing. The three periods for each of the three sectors is shown below. For each
sector the horizontal axis is (st–dt)/st , where st is quantity of labour Supplied (number of workers
searching) in that sector, and dt is quantity Demanded (number of job vacancies) in that sector. The
p-curve for each sector crosses the horizontal axis where this equals zero – that is, where st = dt . (Or,
in a labour market model, where the number of Unemployed equals the number of Job Vacancies.)
The vertical axis is rate of change of money wages: Wt = (Wt – Wt-1)/Wt-1 .
What Lipsey noticed was that, if all three sectors weren’t at exactly the same point on their pcurves at the same time, when the three points were aggregated one would observe a point that was to
the right of the true Phillips curve! Furthermore, as the difference between the points being
aggregated becomes greater, the distance of the observed point to the right of the true curve becomes
greater! What causes this is the curvature. As one moves a given horizontal distance to the left
twice, the second time one moves up vertically by more than one did the first time.
This is shown on the three graphs of Figure 3 below. The difference on the horizontal axis
between 0 and 1 for sector A is twice the distance between 0 and 1 for sector B, and in sector C the
distance between 0 and 1 is zero. Set the horizontal distance between 0 and 1 in sector B as X. To
aggregate, first add A + B + C = (2X + 1X + 0) = 3X. Then divide by 3; you get 1X. So aggregating
the horizontal distances gives a horizontal distance between 0 and 1 that is the distance in sector B.
Figure 3
A
B
C
1
2
1-agg
2
2
1
1
0
0
0
Now repeat that process for the vertical distance. You can see that the vertical distance from the
horizontal axis to point 1 in sector A is nearly four times the distance from the horizontal axis to point
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1 in sector B, and it is zero in sector C. Set the vertical distance between 0 and 1 in sector B as Z. To
aggregate, first add A + B + C = (4Z + 1Z + 0) = 5Z. Then divide by 3; you get (5/3)Z. So
aggregating the vertical distances gives a vertical distance between 0 and 1 of around 2/3 greater
than the distance in sector B. This shown on the sector B graph as point “1-agg”. Note that if you do
this same aggregation exercise for points 0 and 2, you will find that the aggregate point is on the
sector B curve.
Here I use the sector B curve of Figure 3 two ways: one is the sector B p-curve, the other is as a
proxy for the aggregate Phillips curve. Using the sector B curve both ways, you can see, traced out
on the graph of sector B, that the aggregate Phillips curve will go from point 0 to point 1-agg, to
point 2 as the economy expands. If the sectors contract together, the aggregate Phillips curve will go
from point 2 to point 1 to point 0. That is, over the course of a full business cycle, from trough to
trough, the observed aggregate Phillips curve will trace out a counter-clockwise loop. This is what
Lipsey proved.
Thus, Lipsey’s explanation of the loops begins by noting that the economy is made up of a large
number of smaller sectors. He then argued, and the evidence showed, that during an expansion – the
move from point 0 to point 2 on the sector p-curves shown above – individual sectors don’t all
expand at the same rate. In the example with three sectors above, sector A expands relatively
quickly, sector B expands at the average rate, and sector C expands relatively slowly. During
expansion, then, the sectors are at different places on their individual p-curves. Aggregating them
when they are at different points gives points to the right of the “true” Phillips curve.
Lipsey then argued that after a period or two at the peak of the expansion all markets will begin to
converge. They will start to approach the same point on their individual p-curves. Aggregating will
give a point that has moved to the left, close to the “true” Phillips curve. Since the observed points
remain to the left during contraction, the evidence suggests that contraction affects the individual
sectors more evenly than does expansion.
This is a brilliant piece of reasoning. Chris Archibald, among others, tested Lipsey’s conjecture
by using regional labour markets as the “individual markets” of Lipsey’s theory. His findings
supported Lipsey’s conjecture.
But Lipsey (and Archibald) missed one point, one that reinforces Lipsey’s reasoning. That is that
quits-to-search, and all other observed labour market mobility including migration (except return
migration), is pro-cyclical. Thus, as expansion takes place, not only do some markets expand more
quickly than do others, but labour mobility increases substantially. This causes the points in the
individual sectors to “converge” to be close to the same in each sector. Rather than draw the full
graphs, I’ll just write out how this works.
Look again at the three sectors in Figure 3 above. After one period, wages in sector A have risen
substantially; wages in sector B have risen a bit, and wages in sector C haven’t risen at all. Saying
the same thing, st < dt in sector A, st = dt in sector B, and st > dt in sector C. Labour economic
theory has workers moving from lower wage, excess supply sectors to higher wage, excess demand
sectors. Virtually all empirical studies bear out this strong theoretical result. So, as the economy
expands, workers become more mobile. The mobility is from the slower growing or stagnant sectors,
like sector C above, to the faster growing sectors which will have higher wage growth in order to
attract mobile workers, like sector A above. Thus this explanation is completely consistent with both
micro-level labour economic theory and the macro-level observed facts of labour mobility.
The mobility will cause the convergence that is shown on points 2 on the three graphs of Figure 3
above. Workers move from C to A. The increased supply of workers in sector A reduces excess
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demand there, causing a movement to the right along its p-curve. This also reduces the rate of
growth of money wages in A. The reduced supply of workers in sector C reduces excess supply of
labour there, causing a movement to the left along its p-curve. This also increases the rate of growth
of money wages in C. Both of these continue as long as there are wage and employment differentials
between A and C, and the economy stays at high output/low unemployment. And both of these cause
the points in sectors A and C to converge. As they do, the aggregated point shifts to the left.
B. Time Varying NAIRU or Hysteresis: shifts in un and Yn and Labour Market Behavior:
My explanation for the “time-varying” NAIRU, or what is often called “hysteresis” in labour
economics literature, uses Lipsey’s idea, but enlarges on it by recognizing the role that labour
mobility plays in causing convergence in individual markets. Lipsey ignored the economic behavior
that would cause individual labour markets to converge. Here I add this behavior, which reinforces
Lipsey’s conjecture.
There are two implications of Lipsey’s geometric/aggregation argument that are extremely
important. The first is that, since individual sectors will never fully converge (until “we’re all dead”),
the observed Phillips curve is always to the right of the true Phillips curve. The second implication
is even more interesting and important. This implication, combined with observed labour market
behavior, provides a full explanation of so-called hysteresis or “time-varying NAIRU”.
The observed Phillips curve is always to the right of the “true” Phillips curve. But the observed
points move closer to the true Phillips curve as the individual labour markets making up the
aggregate market converge. Since labour mobility, which causes the convergence, is pro-cyclical, the
observed Phillips curve moves closer to the true Phillips curve the longer the economy remains at
low levels of unemployment. That is, the observed Phillips curve shifts left as the economy remains
at low levels of unemployment. As it shifts left, the point where it crosses the horizontal axis, un, also
shifts left. Voila, the “time-varying NAIRU”!
Both the US and Canadian economies expanded during the decade of the 1990s, beginning around
1992. This was the longest period of sustained expansion – that is, the longest period of continuous
increases in Y – ever seen. Yet inflation rates were remarkable stable, varying within a band of
t0.5%. And during this expansion u dropped from over 7.5% in the US in 1992 to 4.0% in
2000. This shows a substantial leftward shift in un. Studies have also shown that, in fact, regional
labour markets have converged in the US – unemployment differences between regions dropped
steadily during the 1990s. Gordon describes the first half of this expansion; the Chart below
describes the entire period from 1990 to 2000. That Chart shows that the leftward shift continued
over the entire decade of the 1990s in the US.
[You can reproduce this argument for yourselves to have un shift right. Normal random
differences in productivity increase cause individual labour markets to pull apart. If the economy is
contracting and unemployment is rising, labour mobility falls. So the mechanism, mobility, that
would bring the individual markets together is disabled. As higher levels of unemployment continue,
the markets pull farther and farther apart from the random disturbances. The farther apart the
individual markets, the farther to the right is the observed Phillips curve from the true Phillips
curve, and the farther to the right is the point where it crosses the horizontal axis, un. The “timevarying NAIRU” shifts to the right.]
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time-varying NAIRU -- US 1990 - 2000
7.00
1990
6.00
Inflation
5.00
4.00
1996
time-varying NAIRU
3.00
2000
1992
1994
2.00
1998
1.00
0.00
0
1
2
3
4
5
6
7
8
Unemployment Rate
You can see that this analysis uses “supply-side” effects. And it uses a lot of micro-economic
underpinnings. Yet the analysis is a purely Keynesian analysis: labour reacts to changes in output,
but the initial changes in output that drive the changes in labour are caused by changes in Aggregate
Demand. The model here builds on known micro-economic facts and uses them to explain known
macro-economic facts. In short, it is good science.
II. “NEW” LABOUR ECONOMICS
A. Variables:
The so-called “new” labour economics focuses attention on flows rather than stocks. It goes by
two names: “job-matching” and “flows approach”; I’ll use the latter. (I say “so-called new” because
most of it isn’t really new. The facts that it has “discovered” were well known by labour economists
when I was in graduate school. I read these when surveying the literature for my PhD dissertation.
The first good description of the flows approach, and a good technique for dealing with it, was
published by Curtis Eaton in 1970. Both he and I used it in our PhD dissertations – his finished in
1968, mine in 1969.)
A “flows approach” requires that we use a new concept: “stasis”. Stasis is when the size of a
stock, which has flows into and out of it every period, doesn’t change in a period. Consider a pond
with a stream flowing in and a stream flowing out. It is in “stasis” when the sizes of the two streams
are equal, so the pond is getting neither larger nor smaller. Note that this isn’t the same as the pond
being “constant”, although its size is constant. The water is flowing in and out; it’s the size that’s
constant, not the water. If no water were flowing in and out it would be a different type of pond. In
this example the flows are continuous. We use discrete periods in this course, so here’s an example
using those.
Consider a population of organisms. Some are born each period, some die each period. Stasis in
this population, during a period, is when births during the period equal deaths during the period, so
the size of the population at the end of the period is the same as at the beginning. Note that I avoid
using the word “constant” here. A constant does not change. The size of this stock can change, but if
labour market behavior
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it does not change during a time period, it is in stasis (not “is constant”). Stasis is similar to dynamic
equilibrium, but subtly different. Dynamic equilibrium in a variable, Y, is when Yt = Yt-1 . When this
happens Y may be either constant or in stasis.
For the flows approach analysis, we begin (and, here, end) with a constant labour force. This is
too simple, but is a good starting point. [For now, I will not expand the analysis to deal with a
changing labour force size.] The two key variables are numbers of Unemployed, Ut and Job
Vacancies, Vt . Note that Ut is the number of unemployed, not the Unemployment Rate, which is ut .
With a constant labour force, neither Employment nor Unemployment can change because of a
change in the size of the labour force.
The variable that defines the potential supply of new workers for jobs is Unemployment. Flows
out of Unemployment in a period are hires, Ht . Flows into Unemployment in a period are voluntary
quits-to-search, Qt , plus involuntary “quits” or “layoffs”, Lt . Here “layoffs” also includes jobs lost
when a firm goes out of business; layoffs are “created” exogenously by decreases in Aggregate
Demand. A critical difference between voluntary quits and layoffs is that voluntary quits always
create Job Vacancies. So:
Ut = Ut – Ut-1 = (Qt + Lt ) – Ht .
(1)
Unemployment is in stasis when Ut = 0, or:
Ut = Ut-1  (Qt + Lt) = Ht .
(2)
If (Qt + Lt) > Ht , Unemployment is increasing:Ut > 0 and Ut > Ut-1 . If (Qt + Lt) < Ht,
Unemployment is decreasing: Ut < 0 and Ut < Ut-1 . In these two cases Unemployment is not in
stasis. [Note that, because we’re holding the size of the labour force constant, if Unemployment is in
stasis, Employment must also be in stasis. But either can be in stasis at a higher or lower level.]
The variable that defines firms’ potential demand for new workers is Job Vacancies, Vt. Flows out
of Job Vacancies are hires, Ht, which fill a Vacancy. Flows into Job Vacancies in a period are (Qt +
Jt), where Jt is Jobs “created” exogenously by increases in Aggregate Demand. So:
Vt = Vt – Vt-1 = (Qt + Jt) – Ht .
(3)
On the demand side, Vacancies are in stasis when Vt = 0, or:
Vt = Vt-1  (Qt + Jt) = Ht .
(4)
If (Qt + Jt) > Ht, Job Vacancies are increasing:Vt > 0 and Vt > Vt-1 . If (Qt + Jt) < Ht, Job Vacancies
are decreasing: Vt < 0 and Vt < Vt-1 . In these two cases, Job Vacancies are not in stasis.
B. Equilibria and dynamics in the different “runs”:
Quantity Demanded in the labour “market” equals Quantity Supplied when Vt = Ut , and both are
in stasis. This is a compelling definition of a dynamic equilibrium: stasis in the labour market, using
the flows approach. From equations (1) and (3), this equilibrium occurs only when (Qt + Lt) – Ht =
(Qt + Jt) – Ht , or when Lt = Jt . In equilibrium new jobs are being created in the same numbers as
workers being laid-off. [Note that dynamic equilibrium in the labour market can occur with higher or
lower levels of Vt = Ut . Note also that labour market stasis can occur without both Vt and Ut
stasis, when both are positive or negative if they are equal. But it is a stylized fact (see below) that
Vt and Ut are negatively correlated – that if one is positive the other is negative and vice-versa. So
this last case, while mathematically possible, is of no real world interest.]
This equilibrium is normally considered to be where ut = un, which is where Yt = Yn. So the labour
market is in dynamic equilibrium, stasis, when the macro-economy is in Medium-Run equilibrium –
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that is, when the macro-economy is at a point on the MAS curve. Again, note that this can occur
with higher or lower levels of Vt = Ut .
Movements away from dynamic equilibrium in the labour market to excess supply are caused by
reductions in Aggregate Demand which reduce output, Yt. In the labour market, this increases
Layoffs, and reduces Quits and Hires; these increase Unemployment: (Lt + Qt) > Ht → Ut >  .
Simultaneously this reduces Job creation; these reduce Job Vacancies: (Qt + Jt) < Ht → Vt < 0.
(From equation (1), Ut = (Qt + Lt ) – Ht , and from equation (3), Vt = (Qt + Jt) – Ht . Consider Ut
>
>
< Vt , which is (Qt + Lt ) – Ht < (Qt + Jt) – Ht. Since Qt and Ht are in both equations with the same
>
signs, this becomes: Lt < Jt . The simultaneous reduction of Aggregate Demand and Yt increases the
first and decreases the second. Since we began with equilibrium, we began with Lt = Jt ; increasing
the first and decreasing the second means Lt > Jt , so Ut > Vt unambiguously.)
As these movements occur in the labour market, simultaneous movements occur down and to the
left along the DSAS curve away from MAS and left from Yn, and down and to the right along the
Phillips curve.
Movements away from dynamic equilibrium in the labour market to excess demand are caused by
increases in Aggregate Demand which increase output, Yt. In the labour market, this decreases
Layoffs, and increases Quits and Hires; these reduce Unemployment: (Lt + Qt) < Ht → Ut <  .
Simultaneously this increases Job creation; these increase Job Vacancies: (Qt + Jt) < Ht < → Vt >0.
(From equation (1), Ut = (Qt + Lt ) – Ht , and from equation (3), Vt = (Qt + Jt) – Ht . Consider Ut
>
>
< Vt , which is (Qt + Lt ) – Ht < (Qt + Jt) – Ht. Since Qt and Ht are in both equations with the same
signs, this becomes: Lt >< Jt . The simultaneous increase of Aggregate Demand and Yt decreases the
first and increases the second. Since we began with equilibrium, we began with Lt = Jt ; decreasing
the first and increasing the second means Lt < Jt , so Ut < Vt unambiguously.)
As these movements occur in the labour market, simultaneous movements occur up and to the
right along the DSAS curve away from MAS and right from Yn, and up and to the left along the
Phillips curve.
During the “hysteresis” demonstrated in Part I above, the macro-economy is in a Medium-Run
equilibrium, so the labour market is in a dynamic equilibrium. But, for the shift of the NAIRU to the
left shown in Part I, as the labour market sits in that equilibrium, labour mobility causes Job
Vacancies to be matched to Unemployed workers. Both are reduced, and by equal amounts. The
labour market remains in stasis, with Vt = Ut , but the size of both gets smaller. That is, as the
economy sits in that equilibrium, Vt = Ut > 0, and the NAIRU shifts to the left.
A full Long-Run equilibrium in the labour market occurs only when all sectors have are in
equilibrium and none have either excess demand or excess supply – when Quantity Demanded equals
Quantity Supplied in every sector. Because the economy never sits still long enough for labour
mobility to make this happen, the labour market is never in Long-Run equilibrium. (This is sort-of
what Keynes had in mind when he famously said, “In the Long Run, we are all dead.”)
III. CYCLES AND LABOUR MARKET BEHAVIOR
There is a very large body of empirical studies of how labour market variables behave over the
business cycle. These were a staple of the “old” labour economics: there are studies going back to
the 1920s showing these cycles, and Lord Beveridge published his findings in the 1940s. They are
also a staple of the “new” labour economics. The studies listed in the bibliography by Blanchard and
Diamond, by Jackman with others, by Pissarides, and by all the authors in Padoa-Schippa, explicitly
labour market behavior
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put their empirical findings into the so-called “new” labour economics of “job-matching” or “flows
approach”. But all of these, both “old” and “new”, agree! Those findings include:
1) Vacancies are pro-cyclical: Vt increase with increases in Yt, and vice versa.
2) Unemployment is counter-cyclical: Ut decreases with increases in Yt and vice versa.
3) Thus, the Vt/Ut relation is strongly pro-cyclical; it increases with increases in Yt and vice versa.
When this is graphed with Ut and Vt on the axes, it is known as the Beveridge curve after Lord
Beveridge’s findings in the 1940s. Like the Phillips curve, this was considered to be stable.
With the changing make-up of the labour force in the 1970s through the 1990s, it shifted
around a bit but has become relatively stable once again. On the next page is a chart showing
a Beveridge curve that was published just two months ago in the leading economics journal,
the American Economic Review.
I also printed a chart from the same article which shows that “job finding” is pro-cyclical –
that is, that Ht , which is “job finding”, is pro-cyclical. Note how close the points are to both
curves in the two charts.
4)
5)
6)
7)
Quits-to-search is pro-cyclical: Qt increases with increases in Yt and vice versa.
Jt – exogenously created jobs – are non-zero (in the aggregate) and strongly pro-cyclical.
Lt – layoffs – are non-zero and strongly counter-cyclical.
Labour market mobility, in particular geographic mobility (labour market migration – moving
from one economic region to another) is pro-cyclical, with one exception:
8) Return migration – workers who moved from one region to another in the immediate past,
moving back to the first region – is counter-cyclical.
9) Changes in money wages, as Phillips showed, are pro-cyclical.
10) Changes in real wages show no particular cyclicality.
11) The loops in the Phillips curve are counter-clockwise; that is, the difference between a point
and the aggregated Phillips curve is pro-cyclical.
12) The NAIRU is “time varying”, falling as ut falls with a constant rate of inflation.
13) The rate of increase in labour productivity is pro-cyclical.
14) The elasticity of aggregate labour supply in the short-run is roughly zero. (Most studies have
actually found it to be slightly negative.)
These “stylized” facts create a major problem with all New Classical models. In fact, the true
statement is stronger than that. These facts, in the language of positive science, falsify New
Classical models.
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IV. MACROECONOMIC MODELS and how they fit the FACTS
A: New Classical
In New Classical models unemployment is always voluntary. All increases in Ut are caused by
quits. Layoffs don’t exist: Lt = 0. These are pure “supply side” models. There is no job creation or
destruction coming from changes in aggregate demand. The chain of causality is:
workers don’t take jobs  employment falls  output falls.
All reductions in output are caused by workers either not taking jobs because (perceived) wages
offered are too low, or workers leaving jobs because (perceived) real wages are falling.. Thus, all
reductions in output are caused by Ht falling and Qt rising. Moving along the production function,
fewer workers means less output. End of Story. So the “micro-economic foundations” of New
Classical Macroeconomics is looking at why wages change over the business cycle.
There are two broad types of these New Classical “micro-economic foundations”:
“Misperceptions”, or “Fooling”:
This has been attributed to Lucas, with his “island” model. But before Lucas it was called
“Friedman/Phelps” and there is a good description of it in Phelps. Here workers’ expectations lag
actual changes in inflation – the parameter “g” in the Adaptive Expectations equation is less than
one. The lag between expectations and changes in actual inflation leads to systematic
misperceptions by workers:
Real wage is money wage divided by Aggregate Prices. In a dynamic model, the change in real
wage, wt, equals the change in money wage, Wt divided by inflation, t. The expected real
wage from any offered money wage is that wage, W, divided by expected Aggregate Prices over
the period of the wage contract, which is current Prices, Pt, times (1+et).
When inflation is increasing, more workers accept offered jobs because they misperceive the
offered money wage as being a higher real wage than it really is. That is, since their et < t ,
their perceived increase in the money wage, Wt /et is greater than the true increase in the money
wage, Wt /t . They are “fooled” by their own misperceptions of actual inflation – they expect
inflation to be lower than it really will be – to accept jobs. Output goes up as more workers are
employed, and the economy moves up the Phillips curve.
When inflation is falling, fewer workers accept offered jobs because they misperceive the offered
money wage as being a lower real wage than it really is. That is, since their et > t , their
perceived increase in the money wage, Wt /et is less than the true increase in the money wage,
Wt /t . They are “fooled” by their own misperceptions of actual inflation – they expect it to be
higher than it really will be – to refuse jobs. Fewer take jobs, more quit, and fewer are
employed. Output goes down, and the economy moves down the Phillips curve.
A special problem with the misperception model is that it generates clock-wise loops in the
Phillips curve, in contradiction to the evidence.
“Real Business Cycles”:
This is a genuinely lunatic idea, but economists seem to have to talk about it anyway. Here the
economy is hit with random productivity shocks. Since real wages are roughly equal to marginal
product, and marginal and average product move together, when a productivity shock is negative
(never-you-mind that no-one knows what a negative productivity shock is), the real wages offered
new hires fall, and firms try to reduce real wages for existing workers. Fewer workers accept jobs
labour market behavior
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and more quit (Ht decreases and Qt increases), and output, Yt, falls. The model is symmetric;
everything works the same way but reversed with a positive productivity shock.
The RBC model doesn’t predict any loops in the Phillips curve. But it strictly implies that real
wages and output move together – that real wages are pro-cyclical – because it is decreases
(increases) in real wages that cause decreases (increases) in employment that cause decreases
(increases) in output. So a special problem exists with the RBC model because real wages don’t
have any cyclical relation.
The problem with all New Classical models – the problem, that is, with having output be entirely
determined by the behavior of labour – is that they either predict, or rely on, a large number of labour
market behaviors over the cycle that are precisely the opposite of what are observed Thus:
1) New Classical models strictly imply that Job Vacancies and Unemployment will move together –
that the Beveridge curve is positively sloped. This is how they get all the action in output. Since
Lt = Jt = 0, then Vt = Qt, Ut = Qt and Vt = Ut . Since unemployment is exclusively workers not
taking jobs plus workers quitting jobs in reaction to (sometimes illusory) too-low real wages, Vt
and Ut must be equal and both must be counter-cyclical; that is, both must go up when output
goes down.
But the fact is that, while Ut is strongly counter-cyclical, Vt is as strongly pro-cyclical, and Ut and
Vt move in opposite directions over the cycle. The Beveridge curve is negatively-sloped. The
reason is that Lt and Jt are not zero, and are rarely equal. Lt is strongly counter-cyclical and Jt is
strongly pro-cyclical. Furthermore, Qt is also strongly pro-cyclical, meaning that increases in Ut
are dominated by high values of Lt . The first Blanchard and Diamond paper cited below
discusses and shows (again) the true relations between, and cyclicality of, Vt and Ut .
2) New Classical models strongly imply – no, that’s too weak, they rely on – that Qt is countercyclical. It is workers not taking jobs or quitting when faced with too low money wages, that
causes reductions in output. But Qt is strongly pro-cyclical. Again, this has been well-known
since at least the mid-1950’s; three good papers which showed this empirically were published,
two in the American Economic Review, in the 1970’s, long before Real Business Cycles were
hypothesized. The second Blanchard and Diamond paper cited below discusses and shows the
true cyclicality of Qt .
3) New Classical models strongly imply that labour market mobility, including migration, will be
counter-cyclical. Unemployed workers will search, and some proportion of that search will
involve migrating to another region to search. But migration is, in fact, strongly pro-cyclical.
And, again, this has been well known since the 1930’s. Good papers re-establishing this fact
were published by Vanderkamp – cited below – in 1968 and 1972, again well before New
Classical models came into being. More than a dozen new papers showing this have been
published in the 1990s.
Further, return migration has been well established as being counter-cyclical, and this was known
as early as Vanderkamp’s 1968 paper. While this is not necessarily inconsistent with New
Classical theory, it is predicted by New-Keynesian, as shown in Allen, 2003.
4) There are no layoffs in New Classical models. All Unemployment is workers not taking jobs
because they don’t like the wages being offered. But there are layoffs, and these don’t involve
firms asking workers to accept lower wages and the workers refusing. Layoffs are strongly
counter-cyclical.
labour market behavior
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5) The misperceptions model predicts that the rate of increase in productivity will be countercyclical. As workers don’t take jobs, firm move up, to the left, along marginal and average
product curves. But the rate of increase in productivity is pro-cyclical.
6) In the early 1980’s, the Canadian unemployment rate rose from around 7% to around 11.5% in a
single year. The US, and a number of European countries, had similar experiences. In 1990, the
unemployment rate rose from about 6% to about 8% in the US, and from 7.5% to 12% in Canada.
To account for these observed changes by way of New Classical models, one would have to have:
either: i) extremely high and extremely inaccurate misperceptions of inflation by everyone,
combined with a very high short-run labour supply elasticity; or ii) an unbelievably large
“negative” shock to productivity – ie, have productivity suddenly decrease by more than 4.5% in
a single year – combined with a short-run labour supply elasticity of about unity.
Misperceptions of this order of magnitude are utterly implausible. What happened at just that
time to cause those misperceptions? Negative productivity shocks are hard to swallow – although
a plausible case could be made for the two OPEC incidents – but no events of anything like that
order occurred in the early 80s. Nor did any occur in Canada in the early 1990s. To swallow the
RBC model, one would have to have had a productivity shock in Canada that was more than
double that in the US. Nothing that could remotely account for this happened.
Finally, all micro-data studies of short-run labour supply elasticity find it to be essentially zero.
B: New-Keynesian
All of the known results are consistent with New-Keynesian models. I use “Keynesian” to mean
the conventional IS/LM model of aggregate demand, with an aggregate supply curve in the
conventional shape, subject to downwardly sticky Prices and Wages. I use “New-Keynesian” to
mean a Keynesian model that has been made dynamic, so that it deals with output and inflation. The
DAD curve is derived from static IS/LM, and fiscal or monetary policy shifts the DAD curve as in
the Keynesian model. The EA-DSAS curve is derived from the Phillips curve and Okun’s law, so it
is positively sloped, and it shifts up and down as inflationary expectations become higher or lower.
Underlying the New-Keynesian model is that Jt and Lt are determined by demand for output. Jt
increases as Aggregate Demand increases and vice-versa; Lt increases as Aggregate Demand falls and
vice-versa.
Microeconomics predicts that unemployed workers will engage in search when the expected return
from search is greater than the cost of search. When Ut is high and Vt is low, the expected return
from search is low and workers search less. Less search means fewer quits: a worker quits-to-search
only when s/he expects to find a better job (this is standard human capital theory). See Allen, 2003,
for a full model of this.
That Vt and Ut move in opposite directions reflects that changes in output are primarily the result
of changes in Aggregate Demand, that “New-Keynesian” models are correct. When Aggregate
Demand falls, Jt and Vt fall because firms are choosing to reduce output, while Ut rises as firms
reduce Ht and increase Lt. When Aggregate Demand rises, Jt and Vt rise because firms are choosing
to increase output, while Ut falls as firms increase Ht and reduce Lt. The cyclical behavior of Ut and
Vt are dominated by Lt and Jt , which are demand-driven. Lt is strongly and negatively related to
changes in Aggregate Demand, and Jt is strongly and positively related to changes in Aggregate
Demand.
In New-Keynesian models output is mainly determined by demand. Inflation is jointly determined
by the level of Aggregate Demand and inflationary expectations (as in the model you’re doing in the
EXCEL assignment). This model is consistent with all of the stylized facts about labour market
labour market behavior
page 14
dynamics described above, and actually predicts almost all of those facts. It is also consistent with
the observed variations in output, inflation and the exchange rate over the past two decades.
None of the New Classical models can make that claim. All of them are inconsistent with most of
the stylized facts about labour market dynamics, and some are inconsistent with all of the stylized
facts about labour market dynamics. In addition, all of them have difficulty with the observed
variations in output, inflation and the exchange rate over the past two decades. They have so much
difficulty with this that Robert Lucas, who won a Nobel prize for his work on New Classical macroeconomics, now says that New Classical models “didn’t work”. And presumably, “don’t work”.
In conclusion, New Classical models get almost everything wrong. New-Keynesian models get
almost everything right. If we follow standard rules of science, which model do we consider correct?
V.
A DYNAMIC MACRO MODEL WITH LABOUR MARKET EFFECTS
I don’t have time to write this up, and we’ve run out of class time to do it. You have enough
theory now to see its shape though. Good luck to you all as you finish this semester. To those of
you that go to graduate school, good luck there.
VI.
A SHORT BIBLIOGRAPHY
Here is a list of papers which show the labour market cycles and dynamics described above. After
each reference, I give numbers in parentheses of just which facts the paper shows. The references
below are only those that came quickly to me from my own research. It is incomplete.
Allen, Jeremiah. 2003. “The Time Patterns of Internal Migration: Human Capital meets Job
Matching”, Review of Regional Studies, 33, 3. (4,7,8)
2. Blanchard, Olivier and Peter Diamond. 1989. “The Beveridge Curve”, Brookings Papers on
Economic Activity (1), 1–60. (1,2,3,4)
3. Blanchard, Olivier and Peter Diamond. 1990. "The Cyclical Behavior of the Gross Flows of
U.S. Workers." Brookings Papers on Economic Activity, (2), 85-155. (1,2,3,4)
4. Blanchard, Olivier and Peter Diamond. 1992. "The Flow Approach to Labor Markets."
American Economic Review (May) 82(2) 354-359. (1,2,3,4)
5. Devine, Theresa and Nicholas Kiefer. 1990. Empirical Labor Economics: The Search
Approach, New York: Oxford University Press.
6. Eaton, B. Curtis. 1970. “Studying Mass Layoffs Through Markov Chains.” Industrial
Relations 9(4) 394-403.
7. Jackman, R., R. Layard, and S. Savouri. 1991. "Mismatch: a framework for thought." in PadoaSchioppa, 1991, 44-101. (1,2,3)
8. Mortensen, Dale T. 1986. “Models of Search in the Labor Market”, Handbook of Labor
Economics, Amsterdam: North-Holland.
9. Padoa-Schioppa, Fiorella (ed.).1991. Mismatch and Labour Mobility, Cambridge: Cambridge
University Press. (1,2,3,7)
10. Pissarides, C. and J. Wadsworth. 1989. "Unemployment and the Inter-Regional Mobility of
Labour." Economic Journal, 99, 739-755. (8)
11. Shimer, Robert. 2007. “Mismatch.” American Economic Review, 97: 1074-1101.
12. Vanderkamp, John. 1968. "Interregional Mobility in Canada: A Study of the Time Pattern of
Migration." Canadian Journal of Economics, I, 595-608. (7,8)
1.