Does the Phillips curve hold for consumer survey data?

EUROPEAN COMMISSION DIRECTORATE GENERAL

ECONOMIC AND FINANCIAL AFFAIRS Policy strategy and co-ordination

Economic situation, forecasts, business and consumer surveys

Does the Phillips curve hold for consumer survey data?1

Introduction

Expectations play an integral role in economic theory. Consumers usually form their expectations

about macroeconomic variables when they make decisions with long-term importance, for example,

when planning a major purchase (buying a house). Their expectations about future prices, incomes,

taxes, interest rates or other variables impact their choices, which eventually influence the overall

economic activity via the price mechanism. This is the reason why economists study consumers'

expectations. Consumer surveys are utilized to collect data about consumers' expectations for

monitoring, forecasting and research purposes. This data provide various opportunities for economic

research. It is sensible to study patterns between different consumers' expectations or to analyse

the relationships between relevant soft and hard data. One of the research opportunities is also to

check whether consumers' expectations reflect economic concepts.

Dräger, Lamla and Pfajfar (2013) evaluate whether US consumers form macroeconomic expectations

consistent with three different economic concepts: the Phillips curve, the Taylor Rule and the Income

Fisher Equation. Based on their analysis of the microdata of the Michigan Survey of Consumers, they

conclude that "consistency with economic concepts on average moves consumers' inflation forecasts

closer to professionals' estimates." Their research and findings provide the inspiration for this paper,

which attempts to reproduce a similar inquiry on European consumers' expectations, albeit focusing

on only one of the above-mentioned economic concepts.

The objective of this paper is to analyse European consumers' expectations about the future

developments of inflation and unemployment and check whether they are consistent with

the Phillips curve – a concept, which describes the relationship between the inflation rate and

the rate of unemployment as an inverse relationship.

The Phillips curve (PC) was proposed by A.W. Phillips (1958) in his research paper based on

the empirical observation and analysis of British data of wage inflation and the level of

unemployment in the period from 1861 to 1957. The PC has been a controversial macroeconomic

concept from its origin despite its initial success. Phelps (1967) and Friedman (1968) argued that

the PC is vertical in the long-run because the price changes do not impact the level of

unemployment, which in the long run equals the natural rate of unemployment. Monetarists started

to distinguish between the long-run and short-run PCs. The short-run curve, also called

the expectations-augmented PC, began to take account of workers' adaptive expectations of price

1 Prepared by Marek Doval and Roberta Friz (DG ECFIN). The views expressed in this study are those of the

authors and do not necessarily reflect those of the European Commission.

2

inflation. The stagflation of the 1970s confirmed the non-existence of a stable negative relationship

between the inflation rate and the rate of unemployment in the long-run. According to Gordon

(2011) research on the PC developed in two separate strands since 1975. The first is represented by

a classical model, which considers demand and supply factors as well as inflation expectations,

whereas the Keynesian PC, which takes into account only forward looking inflation expectations

either in its traditional or hybrid version, presents the other line of research.

The present note focusses on the consistency of consumers' inflation and unemployment

expectations in the European Commission's Harmonised Consumer Survey with the PC. Survey

questions 6 and 7 are relevant for this research.2 Question 6 (Q6) inquires consumers' expectations

about future consumer prices developments and question 7 (Q7) refers to consumers' expectations

about the future change in the number of unemployed people.3 To evaluate the theory-consistency

of consumers' expectations in the EU, the euro area and other selected major Member States,

correlation coefficients are calculated between the time series of the balance statistics of Q6 and the

Q7 using both the full sample and shorter periods, which are determined by business cycle phases.

Consistency of relevant hard data (i.e. statistical data on inflation and unemployment) with the PC is

also examined. In addition, the analysed data are presented in the form of PCs, the relationship

between the variables is charted in figures. Last but not least the theory-consistency of consumers is

evaluated by taking into account their gender, age, education and income.

The analysis confirms the presence of a negative relationship between price and unemployment

expectations of EU and euro-area consumers when the whole analysed period is considered.

However, consumers in the EU are not strictly theory-consistent (correlation coefficient rather weak),

while in the euro area correlation is somewhat stronger. Results for Member States are mixed. Only

German and Dutch consumers have theory-consistent expectations with negative correlation

coefficients, while the correlation coefficients of the rest of the observed consumers are closer to

zero. When shorter periods of expansions and recessions are considered, there are no systemic

changes observed in the theory-consistency of consumers related to the changes of the business

cycle. This contrasts with the findings by Dräger et al (2013) for the US. The findings for the soft data

are broadly in line with those for hard data. However, correlation coefficients obtained for the soft

data indicate somewhat better theory-consistency than for the hard data. The conclusions of the

consumers' categories analysis can be summarized into one sentence: a young rich man is more

theory-consistent than an elderly poor woman.

The paper is organised as follows: Section 1 introduces the employed data. The aim of section 2 is to

illustrate how the soft data relate to the respective hard data. Then in section 3 the theory-

consistency is examined on the hard data. The results provide a reference point for the evaluation of

theory-consistency in the soft data, which is carried out in section 4. Section 5 presents and describes

the PCs of the used data, based on both hard and soft data. Section 6, looks at different categories of

consumers and evaluates whether there are any systemic changes in theory-consistency of

consumers' expectations between these categories. The last section, section 7, concludes.

2 Also the question 4 of the consumer survey, which asks consumers on their expectations on development of

general economic situation, can be used to examine consumers' theory-consistency with the PC. Annex 1 contains a brief analysis using the questions 4 and 6. 3 Exact wording of the Q6 and the Q7 is provided in the Data description section.

3

1 Data description

The aggregate soft data of the European Commission's Harmonised Consumer Survey are employed

for the analysis. This monthly survey is conducted in all 28 European Union (EU) Member States (MS)

by national partner institutes as part of the Joint Harmonised EU Programme of Business and

Consumer Surveys. The nominal sample size for the EU is around 41 060 respondents and 26 440

respondents for the euro area (EA). The effective sample size is around 34 000 respondents for

the EU and 21 000 respondents for the euro area. The survey is designed to be representative at

national level. The respondents of the consumer survey are categorized according to six criteria:

income, occupation, working regime, education, age and gender.

The Harmonised Consumer Survey questionnaire contains altogether seventeen questions, only two

of them are quantitative, the rest is qualitative. The qualitative questions 6 and 7 are relevant for

the purpose of this paper. Q6 asks about consumers' expectations about future consumer prices

developments and Q7 refers to consumers' expectations about future changes in the number of

unemployed people.

Q6: By comparison with the past 12 months,

how do you expect that consumer prices will

develop in the next 12 months? They will…

++ increase more rapidly

+ increase at the same rate

= increase at a slower rate

- stay about the same

-- fall

N don't know.

Q7: How do you expect the number of people

unemployed in this country to change over

the next 12 months? The number will…

++ increase sharply

+ increase slightly

= remain the same

- fall slightly

-- fall sharply

N don't know.

Respondents' answers are presented as balance statistics. Aggregate balances are measured as

percentage points of total answers and are calculated for each question as the difference between

the percentages of positive and negative answers using the following formula:

B = (PP + ½P) – (½M + MM)

PP, P, E, M, MM denote the percentages of respondents who have chosen one option (++), (+), (=), (-)

or (--). N is the percentage of respondents who have selected the option "don't know". The middle

option E and "don't know" option N are attributed zero weights, whereas the moderate options P

and M are attributed half the weight of the extreme options PP and MM. The sum of

PP+P+E+M+MM+N equals 100 and the range of the balance statistic B is from -100 to +100.

Aggregate survey results for the EU and the euro area are based on weighted averages of

the individual country results. Balances per question at aggregate level (country, EU, euro area) are

seasonally adjusted. For the analysis, a subset of monthly consumer survey data is utilized.

The subset consists of aggregate survey results for Q6 and Q7 and covers the period from January

1999 to May 2015.

4

In addition to the total aggregate balances, the survey data are analysed at EU and euro-area level

along four respondents' categories (sex, age, education and income). None of the category data are

seasonally adjusted. Survey respondents are categorized into four age, three education and four

income categories:

Age Education Income

AG1: 16-29 years ED1: primary RE1: 1st Quartile

AG2: 30-49 years ED2: secondary RE2: 2nd Quartile

AG3: 50-64 years ED3: further RE3: 3rd Quartile

AG4: 65+ years RE4: 4th Quartile

The hard data come from Eurostat. The all-items HICP monthly data seasonally adjusted index (2005

= 100) is used to calculate annual inflation rates in the EU, the euro area and selected MS.4 For

the unemployment rate in the EU, the euro area and selected MS, the total seasonally adjusted

monthly average percentage unemployment rate data are utilized. The employed hard data cover

the period from January 1999 to May 2015. The unemployment rate data for the EU are available

only from January 2000. To allow a relevant comparison of soft and hard data, the rate of

unemployment is transformed into the annual change in the rate of unemployment.

The chronology of recessions and expansions established by the Centre for Economic Policy Research

(CEPR) Euro Area Business Cycle Dating Committee is applied to derive shorter time intervals from

the available full sample of soft and hard data. The CEPR chronology is adjusted and expanded by the

introduction of an additional recession period. This recession is defined by the Economic Sentiment

Indicator data and lasts from July 2000 to April 2003. The following are the periods of recessions and

expansions, which are applied for the analysis in this paper:

A. Recessions

a. July 2000 – April 2003

b. January 2008 – June 2009

c. June 2011 – June 20145

B. Expansions

a. May 2003 – December 2007

b. July 2009 – May 2011

4 The selected MS: Germany, France, Italy, Spain, Poland, the United Kingdom, and the Netherlands.

5 The committee members on the last meeting, which took place in June 2014, decided not to call an end of

the current recession amid observed weak economic growth in the EA. For the purpose of this paper, June 2014 is considered as the end of the recession. More information about the functioning of the Committee can be found on the CEPR's website (http://www.cepr.org/content/euro-area-business-cycle-dating-committee).

5

2 Comparison of soft and hard data

How well do the time series of consumers' expectations resemble the time series of

the corresponding hard data? In this section, the survey data are presented in the graphs alongside

their hard data counterparts. From the figures below it is apparent that the soft data are highly

correlated with the hard data. Figure 1 contrasts the time series of EU consumers' expectations

about future consumer prices (EU Q6) with the time series of the EU inflation rate as measured by

HICP. The correlation coefficient of these two series is 0.74, which demonstrates a strong positive

correlation.

Figure 1: EU Q6 and the EU inflation rate (January 1999 to May 2015)

Figure 2 illustrates the relationship of EU consumers' expectations about the change in unemploy-

ment (EU Q7) with the change in the EU rate of unemployment. The correlation coefficient of these

two time series is 0.88, which demonstrates an even stronger positive correlation.

Figure 2: EU Q7 and the change in the EU unemployment rate (January 2001 to May 2015)

-20

-10

0

10

20

30

40

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0% EU inflation rate

EU Q6 (rhs)r = 0.74

0

10

20

30

40

50

60

70

80

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5Change in the EUunemployment rate

EU Q7 (rhs)

r = 0.88

6

3 Theory-consistency of the hard data with the Phillips curve

Consistency of the hard data with the PC is assessed first, before the evaluation of soft data

consistency with the PC. This provides more insight into the analysis of consumers' expectations

theory-consistency. The firm link between the respective hard and soft data promises comparable

theory-consistency of the hard and soft data.

For the purposes of this paper hard data and consumers' expectations are considered as consistent

with the PC if a correlation is negative and strong. For simplicity, we describe as "strong"

a correlation coefficient from an interval of ǀ0.5ǀ to ǀ1.0ǀ. If a correlation coefficient belongs to the

interval -0.1 to 0.1, it is considered as zero or no correlation. Anything between strong and zero

correlation is considered as weak correlation.

Figure 3 illustrates the relationship between the EU inflation rate and the change in the EU rate of

unemployment. Visual inspection of the time series suggests that there is no strong inverse

relationship between the variables when the whole sample is considered. This is confirmed by

a weak correlation coefficient (-0.14) over the period January 2001 to March 2015. In spite of this,

there are shorter periods where a strong inverse relationship between the variables is apparent.

Figure 3: The EU inflation rate and the change in the EU rate of unemployment (January 2001 to May 2015)

Changes in the rate of unemployment in the EU were relatively small over the period from

the beginning of January 2002 until the end of 2005 when unemployment started to decrease until it

reached its minimum in the beginning of 2008. The development of the inflation rate in the EU was

broadly stable around 2% over the period from mid-2002 to mid-2007, just before the Great

Recession. Inflation soared between August 2007 and August 2008. Then it plunged and reached its

minimum around mid-2009. While inflation was rising between August 2007 and August 2008,

unemployment was still decreasing before it started to grow dramatically from September 2008. In

the second half of 2011, when the EU returned to recession, inflation began to decline gradually and

unemployment continued to grow until mid-2013 when it reached its maximum. Since then both

-1.5

-0.5

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%EU Inflation rate

EU Change inunemployment rate (rhs)

r = -0.14

7

unemployment and inflation were on a downward trend, which is not in line with the PC.6 However,

the latest inflation data indicate a bouncing back of the EU inflation rate.

Table 1 presents the correlation coefficients for the inflation rate and the change in the rate of

unemployment in the EU, euro area and seven selected MS, for the full sample as well as for

the shorter periods, which are defined by the business cycle. When the full sample is applied none of

the correlation coefficients calculated for the countries, the EU or the euro area confirm consistency

of the analysed hard data with the PC. The EU, the euro area, Germany, France and Spain show weak

negative correlation, whereas Italian and Dutch correlation coefficients are close to zero. Moreover,

Polish and British correlation coefficients are positive and close to the threshold of 0.50. Considering

the periods of recessions (orange) and expansions (blue), there is no systematic pattern in the values

of the correlation coefficients related to development of the business cycle. However, in the period

of the Great Recession (January 2008 to June 2009) and in the following expansion (July 2009 to May

2011) inflation and the change in unemployment show very strong, almost perfect negative

correlation in the EU and the euro area as well as in many of the selected MS. Among the selected

MS, Germany is the only country which records negative correlation coefficients in each of

the observed periods.

Table 1: Correlation coefficients for the inflation rate and the change in the rate of unemployment

Country

Period

1999:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU -0.14 -0.79 -0.19 -0.91 -0.95 0.64

EA -0.21 -0.29 -0.03 -0.94 -0.97 0.55

Germany -0.35 -0.52 -0.40 -0.90 -0.88 -0.75

France -0.38 0.09 0.50 -0.94 -0.90 0.15

Italy -0.03 0.30 0.39 0.03 -0.80 0.45

Spain -0.18 0.29 -0.26 -0.91 -0.95 0.79

Poland 0.54 0.61 0.07 -0.42 -0.11 0.55

United Kingdom 0.40 0.29 0.60 -0.21 -0.84 0.88

Netherlands -0.05 -0.48 0.07 -0.50 -0.88 0.02

Note: The full sample for the EU is shorter than for the euro area and the selected MS. The full sample for the EU in Table 1 and Figure 3 covers the period from January 2001 to May 2015.

6 Ed Dolan (2014) noticed a similar development in the US data (from mid-2011 to early 2014) in the aftermath

of the Great Recession and argues that the period of the US economy recovery from the Great Recession is not consistent with the shifting PC model (monetarists' short-run PC), which contrasts with the previous US recoveries. He concludes: "If the Phillips curve is not dead, we must at least declare it in a persistent vegetative state from which it will not awaken without some radical change in circumstances." (Dolan, 2014) His conclusion is based on the assumption of the shifting PC model, which says that a simultaneous decline in inflation and unemployment can only take place if inflation expectations are falling.

8

4 Theory-consistency of consumers' expectations with the Phillips curve

This section evaluates theory-consistency of consumers' inflation and unemployment expectations

with the PC.7 Figure 4 depicts the two EU consumers' expectations time series, which cover the

period from January 1999 to May 2015.

Figure 4: Consumers' expectations in the EU - Q6 and Q7 (January 1999 to May 2015)

Figure 4 reveals substantial information about the relationship of consumers' expectations on price

and unemployment changes. There are periods when the series move inversely, but also some

periods when they co-move. Co-movement of the series, which contradicts the PC, can be seen since

the beginning of 2001 until mid-2002, in the years before the Great Recession from mid-2006 to mid-

2008 and in the recent years since the beginning of 2012. On the other hand, there are also several

periods when the inverse relationship seems to be significant, especially, in the interval from mid-

2008 until mid-2011. Considering the full sample, the correlation coefficient for the EU (-0.44) is

negative.

Table 2 summarizes the theory-consistency of consumers' expectations. When the period from

January 1999 to May 2015 is considered, the EU (-0.44) and euro area (-0.53) correlation coefficients

are close to the threshold value of -0.50. As a result, euro-area consumers' expectations can be

considered as consistent with the PC when the whole sample is utilized. Also German and Dutch

consumers' expectations are theory-consistent. The rest of the observed MS shows correlation

coefficients closer to zero. French, Spanish and UK coefficients are roughly equal to zero. The Italian

correlation coefficient indicates weak negative correlation between consumers' expectations, while

Polish consumers' expectations show weak positive correlation. When shorter periods of recessions

(orange) and expansions (blue) are considered, the EU and euro area coefficients indicate very strong

or almost perfect inverse relationship between the variables in the interval from May 2003 to May

7 Compare with Annex 1 and Annex 2. Annex 1 evaluates consumers' theory-consistency with the PC using

consumers' expectations about future consumer prices developments (Q6) and expectations about development of general economic situation (Q4). Annex 2 replicates the analysis of section 3 and 4 by employing different variables. The change in the rate of unemployment is replaced by the rate of unemployment and a new variable question 7 cumulative is used instead of the original Q7.

-20

-10

0

10

20

30

40

50

60

70

80

EU Q6

EU Q7

r = -0.44

9

2011. Therefore, consumers' expectations are theory-consistent in the periods covered by this

interval, which encompasses two periods of expansion and one period of recession, the Great

Recession. By contrast, during the latest recession (June 2011 to June 2014) the correlation

coefficients are strongly positive, which conflicts with the PC.

Table 2: Correlation coefficients for consumers' expectations - Q6 and Q7

Country

Period

1999:1 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU -0.44 -0.46 -0.84 -0.93 -0.94 0.71

EA -0.53 -0.50 -0.85 -0.92 -0.92 0.51

Germany -0.53 -0.35 -0.65 -0.93 -0.85 0.28

France 0.02 0.06 -0.56 -0.89 -0.88 0.22

Italy -0.16 -0.51 0.09 -0.80 0.22 0.74

Spain 0.00 0.68 0.12 0.03 -0.76 0.68

Poland 0.14 N/A 0.14 -0.38 -0.09 0.37

United Kingdom -0.09 -0.45 0.53 -0.78 0.27 -0.07

Netherlands -0.57 -0.64 -0.88 -0.96 -0.96 -0.01

At MS level, the values of correlation coefficients are mixed when the periods of expansions and

recessions are considered. Similarly to the results using the hard data, there is no systematic pattern

based on business cycle phases. During the first recession (July 2000 – April 2003) and the first

expansion (May 2003 – December 2007) the results are rather mixed, with only a minority of

selected MS showing theory-consistent consumers' expectations. By contrast, a majority of the MS

shows significant theory-consistency in the period of the Great Recession (January 2008 to June

2009) and the following expansion (July 2009 to May 2011), whereas all correlation coefficients are

positive or equal to zero in the latest recession (June 2011 to June 2014). In this period, consumers'

expectations in none of the geographical areas indicate consistency with the PC. This period is

represented by the simultaneous decline in inflation and unemployment expectations of consumers.

All in all, within the selected MS, the Netherlands is the MS with the best theory-consistency of

consumers' expectations. The value of the Dutch correlation coefficient for the full sample is

the highest. Furthermore, all correlation coefficients except one are strongly negative when

the shorter periods are considered.

Comparing the theory-consistency of the hard data (Table 1, pp 7) and of consumers' expectations

(Table 2), the following differences and similarities have been observed. Contrasting the full sample

periods for the EU and the euro area, it is apparent that soft data indicate better theory-consistency

than hard data, since their correlation coefficients show stronger negative correlation.8 When looking

at correlation coefficients of the EU and the euro area for the periods of expansions and recessions,

consumers' expectations show better theory-consistency than the hard data, thanks to significantly

8 However, these results are slightly different when the rate of unemployment is used instead of the change in

the unemployment rate (see Annex 2).

10

stronger negative correlation in the periods July 2000 to April 2003 and May 2003 to December 2007.

The results in the other three periods are broadly the same.

At MS level, for the whole period, consumers' expectations show somewhat better consistency with

the PC than the hard data. None of the observed MS indicate theory-consistency using the hard data,

while German and Dutch consumers' expectations are consistent with the PC according to the criteria

used in this paper. When looking at periods of expansions and recessions, the difference between

theory-consistency of the hard and soft data at MS level is not as pronounced as the difference

observed at EU and euro-area level. Overall, strongly negative correlation coefficients are obtained in

around 41% of the cases using soft data, while for the hard data this happens in 35% of the cases.

Considering particular periods, the soft data indicate better theory-consistency for the first two

periods (July 2000 to April 2003 and May 2003 to December 2007), while theory-consistency of hard

data is slightly better in the last three analysed periods (January 2008 to June 2009, July 2009 to May

2011 and June 2011 to June 2014).

11

5 Phillips curves for the analysed soft and hard data

The objective of this section is to present the analysed hard and soft data in figures as Phillips curves.

The periods of the business cycle are highlighted in the figures as well. Figures 5 and 6 chart the PCs

for the hard and soft data.

Figure 5 shows the relationship between the change in the rate of unemployment and the inflation

rate (hard data) in the EU over the period from 2001 to 2014, plus the development in the first five

months of 2015. This figure is complementary to Table 1 (pp 8). The only period in which a very clear

and strong inverse relationship between the variables is visible is during the expansion of 2009 to

2011. The shape of the PC for the first two recessions (2001 to 2003 and 2007 to 2009) is equivocal

as it shows neither a clear inverse relationship nor a positive linear relationship. However, this result

can be attributable to the length of the analysed periods, which is rather short. Due to the very

stable inflation rate of 2% in the expansion period 2003 to 2007, the PC is flat. Moreover, the PC for

the latest recession (2011 to 2014) shows a positive linear relationship between the variables, which

conflicts with the concept of the PC. Finally, the PC for the first five months of 2015 is practically

vertical.

Figure 5: EU Phillips curve –inflation rate and change in the rate of unemployment (2001 – 2014, plus 2015 monthly data)

Note: Red colour indicates recessions, blue colour indicates expansions.

2001

2002

2003

2004

2005 2006 2007

2008

2009

2010

2011

2012

2013

2014

Jan Feb

Mar Apr

May

-1%

0%

1%

2%

3%

4%

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Infl

atio

n r

ate

Change in the rate of unemployment

2001 - 2003

2003 - 2007

2007 - 2009

2009 - 2011

2011 - 2014

2015

12

Figure 6 charts the data of EU consumers' expectations on inflation (Q6) and unemployment (Q7) for

the period from 2000 to 2014, plus the first six months of 2015. This figure is complementary to

Table 2 (pp 10). The PC in Figure 6 shows - with few exceptions - almost a perfect continuous inverse

relationship between consumers' expectations during the period from 2001 to 2012. On

the contrary, the end of the observed period (2012 to 2014) indicates a positive linear relationship

between the variables. However, the PC for the first six months of 2015 suggests again an inverse

relationship for the soft data.

Figure 6: EU Phillips curve – Q6 and Q7 (2000 – 2014, plus 2015 monthly data)

Note: Red colour indicates recessions and blue colour indicates expansions.

Comparing the PCs using hard or soft data (Figures 5 and 6), the most noticeable difference can be

seen in the period 2003 to 2007 when the inflation rate in the EU remained stable while EU

consumers' inflation expectations grew gradually throughout this period.

2000

2001

2002

2003

2004

2005

2006

2007 2008

2009

2010

2011

2012

2013

2014

Jan

Feb March

April

May June

-5

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60

Infl

atio

n e

xpe

ctat

ion

s (Q

6)

Unemployment expectations (Q7)

2000 - 2003

2003 - 2007

2007 - 2009

2009 - 2011

2011 - 2014

2015

13

6 Theory-consistency according to consumers' categories

The survey data provide the opportunity to evaluate consumers' expectations consistency with

the PC at the level of the following consumer categories: gender, age, education and income. This

section checks whether and how consumers' theory-consistency changes within the categories.

Table 3 shows the difference in theory-consistency between male and female consumers. When

the full sample is considered theory-consistency of men is somewhat better. On shorter periods,

men's expectations are more theory-consistent in periods of recession, while women's expectations

are as good as men's expectations or even slightly better during expansion periods.

Table 3: Correlation coefficients for consumers' expectations – gender categories

Region Category

Period

1999:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU Male -0.47 -0.48 -0.81 -0.94 -0.94 0.72

Female -0.41 -0.35 -0.82 -0.90 -0.95 0.76

EA Male -0.55 -0.49 -0.76 -0.93 -0.92 0.55

Female -0.49 -0.43 -0.77 -0.88 -0.95 0.60

Table 4 compares the differences in the correlation coefficients between four age groups of

consumers. On the full sample period, inflation and unemployment expectations of younger

respondents are noticeably more theory-consistent than expectations of older respondents:

the younger the consumer, the better the theory-consistency of his or her expectations with the PC.

This conclusion is valid for all shorter periods, except the Great Recession and the following

expansion, when theory-consistency of all age groups is virtually the same in the former case and

theory-consistency of the youngest age group is the worst in the latter case.

Table 4: Correlation coefficients for consumers' expectations – age categories

Region Category

Period

1999:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU

AG1 -0.53 -0.49 -0.80 -0.93 -0.88 0.66

AG2 -0.47 -0.43 -0.79 -0.93 -0.95 0.71

AG3 -0.39 -0.36 -0.78 -0.93 -0.95 0.72

AG4 -0.37 -0.33 -0.75 -0.92 -0.94 0.77

EA

AG1 -0.55 -0.49 -0.80 -0.94 -0.87 0.43

AG2 -0.54 -0.48 -0.80 -0.91 -0.94 0.51

AG3 -0.50 -0.44 -0.79 -0.90 -0.94 0.55

AG4 -0.47 -0.41 -0.79 -0.89 -0.93 0.66

14

Table 5 presents the correlation coefficients of three groups of consumers with different levels of

attained education. Consumers' theory-consistency does not change considerably with the level of

consumers' education. On average, expectations of consumers with higher education are only slightly

more theory-consistent, except during the period May 2003 to December 2007 where indeed

correlation improves with higher education levels. Moreover, in the case of euro-area consumers,

consumers with higher education score somewhat better than consumers with lower education.

Surprisingly, in the period July 2000 to April 2003, euro-area consumers with lower educational level

appear slightly more theory-consistent.

Table 5: Correlation coefficients for consumers' expectations – education categories

Region Category

Period

1999:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU

ED1 -0.41 -0.40 -0.72 -0.91 -0.94 0.74

ED2 -0.43 -0.42 -0.79 -0.93 -0.95 0.73

ED3 -0.44 -0.39 -0.82 -0.93 -0.95 0.70

EA

ED1 -0.50 -0.48 -0.75 -0.89 -0.93 0.61

ED2 -0.52 -0.47 -0.79 -0.91 -0.93 0.58

ED3 -0.50 -0.40 -0.82 -0.91 -0.93 0.50

Table 6 looks at the correlation coefficients of four income groups of consumers. Theory-consistency

of consumers' expectations is improving with rising income: the higher the income, the stronger

the negative correlation (or the weaker the positive correlation) between consumers' expectations.

This conclusion, however, does not hold for the expansion of July 2009 to May 2011 when

the correlation coefficients do not present any trend.

Table 6: Correlation coefficients for consumers' expectations – income categories

Region Category

Period

1999:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU

RE1 -0.40 -0.29 -0.74 -0.91 -0.94 0.75

RE2 -0.42 -0.38 -0.77 -0.90 -0.96 0.78

RE3 -0.44 -0.41 -0.75 -0.92 -0.93 0.72

RE4 -0.49 -0.47 -0.80 -0.95 -0.94 0.66

EA

RE1 -0.49 -0.39 -0.77 -0.89 -0.92 0.60

RE2 -0.51 -0.44 -0.79 -0.88 -0.96 0.61

RE3 -0.52 -0.47 -0.75 -0.91 -0.93 0.56

RE4 -0.55 -0.46 -0.81 -0.92 -0.93 0.50

15

7 Conclusion

The objective of this paper was to check whether European consumers' expectations about the future

developments of inflation and unemployment are consistent with the Phillips curve. For this purpose, the

Harmonised Consumer Survey questions Q6 and Q7 were used. The relationship between the two

variables was evaluated using correlation coefficients, which were calculated for the time series of the

aggregate soft data and eventually compared with the results for the respective hard data for the whole

analysed period as well as for shorter periods of expansions and recessions.

A first finding is that correlation coefficients obtained for the survey data indicate somewhat better

theory-consistency than is observable for the hard data.

For the whole analysed period, the analysis confirms the presence of an inverse relationship between

consumers' expectations for both the EU and the euro area. However, the correlation coefficients are not

always strong. At MS level, the results are mixed. German and Dutch consumers' expectations are clearly

theory-consistent, while the rest of the observed MS shows correlation coefficients closer to zero. Similar

results are observed at EU and euro-area level when consumers' expectations about the development of

the general economic situation (instead of unemployment expectations) is employed to evaluate

consumers' theory-consistency with the PC (Annex 1). Cumulating expectations of the change of the

unemployment rate to obtain a measure of unemployment level expectations considerably weakens the

results (Annex 2).

When sub-periods are considered, the strength of the correlation coefficients varies significantly. At EU

and euro-area level, an inverse relationship is present for all periods except one (June 2011 to June 2014

recession) when it changes into a strong positive linear relationship, which contradicts the PC. The

differences in the values of correlation coefficients do not indicate any systemic influence based on

development of the business cycle (changes in recession or expansion periods) on consumers' consistency

with the PC. Using expectations about the general economic development, better theory-consistency of

consumers is observed in the first and last analysed period. When Q7 cumulative is employed, the theory-

consistency of consumers is comparable to the results of the main analysis, with the exception of the last

two sub-periods where correlation coefficients for most of the countries have different signs compared to

the original analysis.

Finally, the paper checks how consumers' theory consistency changes across different consumers'

categories at EU and euro-area level. Generally, theory-consistency of men is better than theory-

consistency of women, younger generations are more theory-consistent than older generations, and

consumers' consistency with the PC gets better with rising income, whereas higher education leads only

to a marginal improvement in theory-consistency of consumers. In other words, a young rich man will, in

general, be more theory-consistent than an elderly poor woman.

Unlike Dräger, Lamla and Pfajfar (2013), which use microdata of the Michigan Survey of Consumers,

the conclusions of this exploratory and descriptive note are based on the analysis of aggregate survey

data. This does not allow checking what each individual replied to each question, but rather the average

consistency of the total or a sub-group of the population. Therefore, the evidence presented in this paper

is of a tentative nature and needs more research to be corroborated. In particular, an analysis

of microdata from the Harmonised Consumer Survey might produce further insights.

16

References

Dolan, Ed (2014): What Ever Happened to the Phillips Curve? Interpreting a Half Century of

Inflation and Unemployment. Blog. Available at

http://www.economonitor.com/dolanecon/2014/05/12/what-ever-happened-to-the-phillips-

curve-interpreting-a-half-century-of-inflation-and-unemployment/

Dräger, Lena, Lamla, Michael J. and Pfajfar, Damjan (2013): Are Consumer Expectations Theory-

Consistent? The Role of Macroeconomic Determinants and Central Bank Communication. KOF

Working Papers, No. 345.

European Commission (2014): The Joint Harmonised EU Programme of Business and Consumer

Surveys. User Guide. Available at

http://ec.europa.eu/economy_finance/db_indicators/surveys/documents/bcs_user_guide_en.pdf

Friedman, Milton (1968): The Role of Monetary Policy. In: American Economic Review, Vol. 58, No.

1, 1-17.

Gordon, Robert J. (2011): The History of the Phillips Curve: Consensus and Bifurcation. In:

Economica, Vol. 78, No. 309, 10-50.

Phelps, Edmund S. (1967): Phillips Curves, Expectations of Inflation and Optimal Employment over

Time. In: Economica, Vol. 34, No. 3, 254-281.

Phillips, A. W. (1958): The Relation between Unemployment and the Rate of Change of Money

Wage Rates in the United Kingdom, 1861-1957. In: Economica, Vol. 25, No. 100, 283-299.

17

Annex 1

Dräger, Lamla and Pfajfar (2013) in their analysis of consumers' expectations test also the relation-

ship between inflation and business conditions, which they take as a proxy for the output gap. This

approach is based on Okun's law and the New Keynesian PC. Okun's law is used to translate

the trade-off between inflation and unemployment into a positive correlation between inflation and

output, while the New Keynesian PC is defined as a function of expected inflation and the output

gap.9

The European Commission's Harmonised Consumer Survey contains the question 4 (Q4), which asks

consumers on their expectations on development of general economic situation in their country.10

Q4 can be applied together with question 6 (Q6) to test consumers' theory-consistency with the PC.

In this case, consumers are consistent with the PC when the relationship between their expectations

is characterized by a strong positive correlation.11 Since the Q6 time series is lagging behind the Q4

time series, a lag of three quarters of year has been introduced to the Q4 data and the original Q4

time series has been replaced by the new time series: Q4(t-3). Figure 1 illustrates the relationship

between the Q4(t-3) and Q6 from 1999 Q1 to 2015 Q1.

Figure 1: Consumers' expectations in the EU – Q4(t-3) and Q6 (quarterly data, Q1 1999 to Q1 2015)

Table 1 presents correlation coefficients, which were calculated for the full sample period (1999 Q1

to 2015 Q1). For the whole period, consumers in the EU are not strictly theory-consistent (positive

correlation of 0.47), whereas consumers in the euro area show theory-consistency with the PC

(positive correlation of 0.57). At MS level, most of the countries indicate a positive correlation but

only three countries (Germany, Poland and the Netherlands) show theory-consistency with the PC.

9 This approach is formally described by Dräger, Lamla and Pfajfar (2013: 6).

10 The exact formulation of the question 4 can be found in the survey user guide, which is available at

http://ec.europa.eu/economy_finance/db_indicators/surveys/documents/bcs_user_guide_en.pdf. 11

For this analysis quarterly survey data have been employed.

-45.0

-40.0

-35.0

-30.0

-25.0

-20.0

-15.0

-10.0

-5.0

0.0

5.0

-15.0

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

EU Q6

EU Q4 (t-3) (rhs) r = 0.47

18

When shorter periods are considered, EU and euro-area consumers are theory-consistent in all

recessions and expansions, except the latest recession of 2011-2014. In the recession of 2008-2009,

consumers' expectations show almost a perfect correlation. At MS level, the results are mixed but

negative correlation is present only in very few cases.

Table 1: Correlation coefficients for Q4(t-3) and Q6 (quarterly data)

Country

Period

1999:1 - 2015:1

2000:3 - 2003:1

2003:2 - 2007:4

2008:1 - 2009:2

2009:3 - 2011:2

2011:3 - 2014:2

EU 0.47 0.84 0.59 0.99 0.84 0.19

EA 0.57 0.86 0.67 0.98 0.83 0.39

Germany 0.63 0.93 0.65 0.98 0.82 0.54

France -0.07 0.62 0.28 0.99 0.64 0.48

Italy 0.26 0.04 0.42 0.59 0.44 -0.39

Spain 0.48 -0.79 0.09 0.92 0.82 0.47

Poland 0.61 N/A -0.23 -0.27 0.37 0.73

United Kingdom 0.25 0.24 -0.34 0.96 0.79 -0.17

Netherlands 0.56 0.70 0.92 0.95 0.83 0.32

19

Annex 2

Theory-consistency of hard data is different when the rate of unemployment is utilized instead of

the change in unemployment rate. The analysis, which uses the rate of unemployment is viable

because the PC describes the relationship between the rate of unemployment and the rate of

inflation. Therefore such an analysis matches the concept better. Figure 1 illustrates the relationship

between the EU inflation rate and the EU rate of unemployment for the period January 2000 to May

2015, where the correlation is negative but weak (-0.43).

Figure 1: The EU inflation rate and the EU rate of unemployment (January 2000 to May 2015)

Table 1 shows the correlation coefficients for the inflation rate and the rate of unemployment in

the EU, euro area and seven selected MS. When the full sample is applied the euro area, France,

Spain and the Netherlands indicate theory-consistency with the PC. The EU and Italy are very close to

the threshold correlation coefficient of -0.50. Germany shows no correlation, whereas Poland shows

a weak positive correlation and the UK shows even a strong positive correlation between inflation

and unemployment. The Netherlands is the country with the most theory-consistent data. In all three

recessions the Dutch correlation coefficients reached the level of strong negative correlation. The EU

and the euro area reached such a level of strong negative correlation only twice during recessions. All

the other countries, except the UK, recorded two shorter periods with a strong negative correlation.

The EU and the euro area values of correlation coefficients for the given periods are in several cases

very close but in other cases they differ significantly. During the expansions (May 2003 to December

2007 and July 2009 to May 2011), the hard data for the EU and the euro area do not show

consistency with the PC. The results are much more positive (theory-consistent) for the recession

periods (July 2000 to April 2003, January 2008 to June 2009, June 2011 to June 2014) when at least

one of the European regions indicates negative and strong correlation between the inflation rate and

the rate of unemployment. In those cases the hard data are consistent with the PC. In general,

correlation between inflation and unemployment tends to be stronger and negative in the periods of

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

11.0%

12.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

EU Inflation rate

EU Rate of unemployment (rhs)

r = -0.43

20

recession in comparison to the periods of expansion. This observation has to be considered carefully

because the examined period is rather short and might not be representative.

Table 1: Correlation coefficients for the inflation rate and the rate of unemployment

Country

Period

2000:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU -0.43 -0.79 -0.26 -0.94 0.49 -0.50

EA -0.52 -0.34 -0.04 -0.96 0.24 -0.67

Germany 0.09 -0.63 -0.17 -0.24 -0.96 0.87

France -0.58 0.07 0.22 -0.95 -0.39 -0.84

Italy -0.43 -0.15 0.57 -0.76 -0.16 -0.76

Spain -0.60 0.72 -0.16 -0.94 0.94 -0.30

Poland 0.11 -0.96 -0.02 0.20 -0.62 -0.05

United Kingdom 0.62 -0.32 0.69 -0.31 0.13 0.81

Netherlands -0.54 -0.79 -0.28 -0.62 0.12 -0.59

In addition to the original Q7, which does not comply with the concept of the PC completely, a new

variable question 7 cumulative is introduced. Indeed, the Q7 does not ask the consumers for their

expectations of the future level of unemployment, but the change in the number of unemployed

people, which is not exactly the same variable as the rate of unemployment. Therefore

a transformation of the original time series is carried out. First, the series is standardized and then

the standardized values are cumulated12. As a result of this transformation the new variable question

7 cumulative expresses the level of unemployment based on consumers' expectations. It is

comparable with the rate of unemployment.

Figure 2 depicts the question 7 cumulative for the EU data with the EU rate of unemployment. These

two time series are highly correlated (0.91). The transformed time series of the question 7 correlates

almost perfectly with the unemployment rate. From Figure 2, it is apparent that the series of

the question 7 cumulative lags behind the rate of unemployment.

12

More precisely, the cumulative Q7 series (Q7*) is calculated in the following way: 𝐷𝑀𝑄7𝑛 = 𝑄7𝑛 − 𝑙𝑜𝑛𝑔-𝑡𝑒𝑟𝑚 𝑎𝑣𝑒𝑟𝑎𝑔𝑒(𝑄7)

𝑄7𝑛∗ = 𝑄7𝑛−1

∗ + 𝐷𝑀𝑄7𝑛; where 𝑛 ∈ 𝑍+, 𝑄70∗ = 𝐷𝑀𝑄70.

21

Figure 2: EU Q7 cumulative and the EU unemployment rate (January 2000 to May 2015)

Figure 3 presents the time series of EU consumers' expectations on inflation (Q6) and cumulative

consumers' unemployment expectations (Q7 cumulative), which corresponds with the rate of

unemployment. For the whole period January 1999 to May 2015, the correlation between these two

variables is negative but weak (-0.13).

Figure 3: Consumers' expectations in the EU - Q6 and Q7 cumulative (January 1999 to May 2015)

Table 2 shows the correlation coefficients, which were calculated for the Q6 and the Q7 cumulative.

For the whole period, consumers' expectations are not theory-consistent. The correlation coefficient

for the EU is very weak (-0.13) and the correlation coefficient for the euro area is even weaker

(-0.09). For the full sample, at MS level, only Spain shows strong negative correlation and thus

theory-consistency. The rest of MS indicates rather weak correlation (France, Poland and the

Netherlands), no correlation (Germany) or even positive correlation (the UK, Italy).

-700.0

-500.0

-300.0

-100.0

100.0

300.0

6

7

8

9

10

11

12EU unemployment rate

EU Q7 cumulative (rhs)

r = 0.91

-800.0

-600.0

-400.0

-200.0

0.0

200.0

400.0

-20

-10

0

10

20

30

40

EU Q6EU Q7 cumulative (rhs) r = -0.13

22

Table 2: Correlation coefficients for consumers' expectations - Q6 and Q7 cumulative

Country

Period - soft data - Q7_cum

1999:01 - 2015:05

2000:07 - 2003:04

2003:05 - 2007:12

2008:01 - 2009:06

2009:07 - 2011:05

2011:06 - 2014:06

EU -0.13 0.32 -0.75 -0.90 0.86 -0.75

EA -0.09 0.33 -0.64 -0.84 0.65 -0.82

Germany -0.10 -0.34 0.22 -0.52 -0.24 0.71

France -0.27 -0.14 -0.66 -0.65 0.81 -0.54

Italy 0.54 0.81 -0.86 -0.58 0.94 -0.72

Spain -0.54 -0.70 -0.80 -0.86 0.86 -0.33

Poland -0.19 N/A 0.12 0.11 -0.43 -0.89

United Kingdom 0.11 0.36 0.68 -0.93 0.91 0.07

Netherlands -0.23 -0.55 -0.22 -0.79 0.79 -0.84

When the business cycle phases are considered, the results are mixed at all levels. Theory-

consistency of consumers' expectations is not systematically influenced by development of

the business cycle. EU and euro-area consumers' expectations are theory-consistent in three out of

five periods (May 2003 to December 2012, January 2008 to June 2009 and June 2011 to June 2014).

For the other two periods (July 2000 to April 2003 and July 2009 to May 2011) correlation

coefficients are positive. At MS level, four MS (France, Italy, Spain and the Netherlands) show theory-

consistency in three periods, whereas the other two MS (Germany and Poland) show only one period

of theory-consistency. The period July 2009 to May 2011 is dominated by very strong positive

correlation coefficients in most of the observed MS.

For a comparison on the whole period, consumers' theory-consistency in the EU and euro area is

substantially stronger when the original Q7 is employed. At MS level, the difference is not that

strong. When the periods of recessions and expansions are considered, the most significant

difference at all levels is present in the last two observed periods where the correlations go in

opposite directions.