In Search of the Effects of Competition on Unemployment: Evidence from OECD Countries

doi:10.4236/jssm.2011.44051

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Journal of Service Science and Management, 2011, 4, 453-457

doi:10.4236/jssm.2011.44051 Published Online December 2011 (http://www.SciRP.org/journal/jssm)

453

In Search of the Effects of Competition on

Unemployment: Evidence from OECD Countries

Bo Zhao

School of International Trade and Economics, University of International Business and Economics, Beijing, China.

E-mail: [email protected]

Received September 13th, 2011; revised October 18th, 2011; accepted November 15th, 2011.

ABSTRACT

This paper explores the empirical relationship between unemployment rate and product market competition in eighteen

OECD countries through three sets of quantitative analyses. We find that the effect of competition on employment de-

pends on the existing competition intensity and the relationship between the unemployment and competition appears to

be inverted-N shape—in countries where existing competition intensity is either high or low, an increase in competition

tends to reduce unemployment rate significantly; but for countries where existing competition intensity is moderate,

intensified competition is more likely to increase unemployment rate significantly.

Keywords: Competition, Unemployment, Panel Data, SVAR

1. Introduction

Recent report from the International Labor Organization

indicates that global unemployment rate in 2009 soared to

an unprecedented height of approximately 6.6%. Espe-

cially, the unemployment rates in the Developed Econo-

mies and European Union region jumped to 8.4%. Mo-

reover, the overall unemployment rates in the next ten

years are expected to keep increasing [1]. Against such a

background, the importance of understanding the factors

that influence a country’s unemployment cannot be over-

stated. Labor market institutions and distortions are argua-

bly among the most significant factors. However, as ob-

served and argued by many economists, the labor market

institutions and distortions cannot fully explain the high

unemployment rates (see Nickell et al. [2] for example).

More attention, therefore, has been directed at the pro-

duct market imperfections and distortions, especially pro-

duct market power, as a possible reason for the increas-

ing unemployment rates. However, theoretical analyses

suggest that the relationship between competition and

unemployment may be ambiguous. Hence, it is necessary

to examine the empirical evidence on this relationship.

As far as we know, however, there is surprisingly little

empirical work on this subject. Therefore, the main ob-

jective of this paper is to search for the effects of product

market competition on unemployment by using data from

eighteen OECD countries.

The rest of this chapter is organized as follows. Sec-

tion 2 gives the list of estimation variables and discusses

the measures of competition. In section 3, quantitative a-

nalyses are conducted to explore the relationship bet-

ween unemployment and competition. Main conclusions

are summarized in section 4.

2. Variables, Database and Proxies

Our data sample mainly spans over 1970-2005 and cro-

sses eighteen OECD countries: Australia, Austria, Bel-

gium, Canada, Denmark, Finland, France, Greece, Ire-

land, Japan, Italy, Luxembourg, Netherlands, New Zea-

land, Norway, Sweden, the United Kingdom and the Uni-

ted States of America.

A complete list of variables and their proxies used in

our estimations is provided in Table 1. Specifically, pro-

duct market competition is a non-monetary concept whi-

ch makes it hard to measure. The Herfindahl Index (HHI)

and the Price Cost Margin (PCM) are the two theoretical

measures that are often used to identify the degree of

competition in the product market. In this paper, we use

PCM to measure the degree of competition because of

two advantages that it has over HHI: 1) PCM can be ap-

proximated by using the macro level data; and 2) PCM

can capture the competitions in both domestic and fo-

reign markets.

Although the robustness of PCM as a measure of com-

petition intensity has been questioned by many econo-

mists, there is no other practical measure for competition

intensity, especially at the macro level [3].

In Search of the Effects of Competition on Unemployment: Evidence from OECD Countries

454

Table 1. Variables and proxies.

u unemployment rate: ratio of unemployed to economically active

population

r interest rate: nominal annual interest rate

N total labor force: economically active population

s technical progress: productivity index

p price level: consumer price index

w labor compensation: total labor compensation divided by total

labor force

COM degree of product market competition: price cost margin

Using the macro data sets, the aggregate PCM can be

calculated via:



GOS CFCTS

PCM GVA



 (1)

where GVA is the Gross Value Added, GOS is the Gross

Operating Surplus, CFC is the Consumption of Fixed Capi-

tal, and (T − S) is the Taxes Less Subsidies on products.

Let be the proxy for the degree of

competition. Hence, a larger value of COM represents a

more intensive competition product market.

1COM PCM

3. Regressions

3.1. Panel-Data Regression with Lagged

Variables

Trying to find the general effect of competition on unem-

ployment, we start with a panel-data (time-series cross-

section) regression. Due to the observed stickiness of un-

employment and its delayed response to changes in eco-

nomic variables, we use a model with lagged indepen-

dent variables (i.e. a dynamic process) to describe and

explain the unemployment rate. Moreover, since there

are omitted variables, e.g. union density and education,

which probably have different gross effects across coun-

tries, we use a country-specific intercept to capture these

effects.

itikit kit









 



1, 2, 3,, 18i

1972, 1973, t

with

and (2)



, 2005

where ui,t is the observed unemployment rate at time t for

country i, xi,t is the observations for a vector of the ex-

planatory variables , βk is the slope

coefficient vector of kth lagged independent variables,

and αi is the cross-section fixed effect (country-specific

constant). Let , that is, one-period lag is applied.



,,,, ,pwsrNCom



Q

To see more clearly the impact of competition on un-

employment, we conduct two regressions: the first one

excludes the variable COM, while in the second regres-

sion, we add it in. Table 2 displays the regression results

with PCSE estimators.

It is interesting to find that product market competition

is indeed significantly related to the unemployment rates,

and the overall effect of competition on unemployment

appears to be positive. However, as noted, when COM is

added into the regression, some statistic measures of re-

gression are reduced. How could this happen? One pos-

sible reason is that the responses of the unemployment

rates to the changes in competition are more complex,

probably country-specific.

3.2. A Structural VAR Approach

The Structural Vector Autoregression (SVAR) is com-

monly used for estimating and forecasting systems of

interrelated time series and for analyzing the dynamic

impact of random disturbances on a system of variables,

and it sidesteps the need for structural modeling by trea-

ting every endogenous variable in the system as a func-

tion of the lagged values of all of the endogenous vari-

ables in the system. In comparison with the paneldata a-

nalysis in Section 3.1, a SVAR model allows us to search

and characterize the country-specific long-run effect of

competition on unemployment rate.

The identifying assumptions used in our model can be

summarized in the following contemporaneous relation-

ship:

4142 43 44 45 46

51 525355

61 62636566

7172 73 74 75 76 77

000000

0 00000

000000

000

s s

N N

r r

p p

w w

COM COM

u u

gggggg v

ggg gv

ggg gg v

ggggggg v





 



 



 



 



 





 



 



 



 



 



 

(3)

Table 2. Panel-data regression results.

Explanatory Variable#1 #2

pt –0.359156 * –0.362129 *

pt-1 0.396755 * 0.401480

log(wt) –14.01174 * –13.01221

log(wt-1) 16.35585 * 15.26283

st 0.023938 ** –0.004423

st-1 –0.078136 * –0.048781

rt 0.055446 * 0.046219

rt-1 0.222642 * 0.229598

log(Nt) –20.19961 * –18.90145

log(Nt-1) 10.65544 * 9.560489

COMt –2.220691

COMt-1 4.355663

In Search of the Effects of Competition on Unemployment: Evidence from OECD Countries

455

(a) Australia (b) Austria (c) Belgium

(d) Canada (e) Denmark (f) Finland

(g) France (h) Greece (i) Ireland

(j) Italy (k) Japan (l) Luxembourg

(m) Netherland (n) New Zealand (o) Norway

In Search of the Effects of Competition on Unemployment: Evidence from OECD Countries

456

(p) Sweden (q) UK (r) USA

Figure 1. Structural impulse response of unemployment to a positive shock of competition.

where ε is the structural disturbance, and ν is the residu-

als in the reduced form equations, representing unex-

pected movements of each variable.

Figure 1 shows the structural impulse responses (over

ten years) of the unemployment rates to a one-time one-

standard-deviation positive shock of product market com-

petition for each country. The solid curve shows the per-

centage deviations from an underlying growth path, and

the dashed curves plotted in each graph are one-standa-

rd-error bands. These diagrams demonstrate that the ef-

fect of competition on unemployment rate is significantly

distinct across countries, both directionally and quantita-

tively.

3.3. Grouped Panel-Data Analysis

According to their specific response of unemployment to

competition, the eighteen countries can be classified into

two groups, as displayed in Table 3. Then we conduct a

panel-data regression for each group. Just as expected,

for those countries in Group A, intensified competition

increases unemployment significantly; while for the

countries in Group B, there is an opposite effect.

Moreover, we find that the average competition inten-

sity of Group A is higher than that of Group B over

1970-2005. Therefore, the relationship between unem-

ployment and competition seems to be U-shaped, as il-

lustrated in Figure 2.

However, a closer examination of the ranking of com-

petition intensity across countries suggests that the rela-

tionship between unemployment and competition may be

more complex. As displayed in Table 4, most countries

in Group A have an intermediate intensity of competition,

Table 3. Grouping by impulse response.

Group Countries Common Character

Australia, Belgium, Canada France,

Greece, Japan New Zealand, Sweden,

UK, USA

COM u

Unemployment

Competition

Group B Group A

Figure 2. U-shaped relation between competition and unem-

ployment.

Table 4. Average intensity of competition.

Country GroupAverage Intensity of Competition (↑)

Greece A 0.509174357

LuxemburgB 0.735863454

Italy B 0.738866699

Ireland B 0.756146347

Japan A 0.772045048

New ZealandA 0.777843656

Canada A 0.827443469

USA A 0.836445117

NetherlandsB 0.841354966

Australia A 0.843551061

Belgium A 0.849021465

Norway B 0.857324047

France A 0.871354498

Austria B 0.884357567

Finland B 0.90062676

UK A 0.900998865

Sweden A 0.921480577

Denmark B 0.947884889



B Austria, Denmark, Finland Ireland, Italy,

Luxembourg Netherlands, Norway COM u

In Search of the Effects of Competition on Unemployment: Evidence from OECD Countries457

Table 5. Grouped panel-data regression results (Grouped

by Impulse Response).

Explanatory Variable Group C Group D

pt –0.164559 * –0.406813 *

pt-1 0.148068 * 0.426115

log(wt) –5.510587 * –13.53308

log(wt-1) 11.59782 * 15.24213

st –0.110827 * 0.024911

st-1 0.022537 –0.076128

rt –0.128123 * 0.062993

rt-1 0.110894 * 0.168190

log(Nt) –36.76861 * 3.007705

log(Nt-1) 25.85197 * 3.727524

COMt 0.451076 –3.155832

COMt-1 8.816740 * –1.221837



Unemploymen

Group C Group D

Group D

Competition

Figure 3. Inverted-N shaped relation between unemploy-

ment and competition.

while most countries in Group B have either the lowest or

the highest competition intensity. This finding suggests that

our conjecture—a U-shaped relation between unemploy-

ment and competition—is not accurate.

In light of Table 4, we regroup those eighteen coun-

tries according to the intensity of competition: one group

mediate intensity of competition; another group (D) in-

cludes the four countries that have the lowest competi-

tion intensity and the five countries with the highest in-

tensity of competition.

Table 5 reports the estimation results for these two

groups. This regression result shows that for those coun-

tries where competition intensity is medium (i.e. Group

C), increasing product market competition increases the

unemployment rates more likely; while for those coun-

tries whose competition intensity at either the high or the

low end (i.e. Group D), intensified competition in produ-

ct market tends to reduce the unemployment rates.

This finding implies that the effect of competition on

unemployment depends on the existing competition in-

tensity and the relation between unemployment and the

intensity of competition, as illustrated in Figure 3, is

more likely to be inverted-N shaped.

4. Conclusions

This paper, by using the macro data from eighteen OE-

CD countries, we have examined the relationship between

product market competition and unemployment. Our ana-

lysis suggests that the relationship between these two

variables is not simply monotonic. Rather, it appears to

be inverted-N shaped, with the effect of product market

competition on unemployment depending on the existing

competition intensity. Specifically, in countries where e-

xisting competition intensity is either high or low, increa-

sed competition in the product market tends to reduce

unemployment significantly, but for countries where exi-

sting competition is moderate, intensified competition mo-

re likely increases unemployment. Therefore, our findings

do not support the common belief among many econo-

mists that increased competition in the product market

always improves the level of employment.

REFERENCES

[1] “Global Employment Trends,” International Labor Or-

ganization, January 2010.

[2] S. Nickell, L. Nunziata and W. Ochel, “Unemployment in

the OECD Since the 1960s. What Do We Know?” Eco-

nomic Journal, Vol. 115, 2005, pp. 1-27.

doi:10.1111/j.1468-0297.2004.00958.x

[3] J. Boone, “Competition,” CEPR Discussion Papers, No.

2636, 2000.