New Low Price!
An Analysis of IKEA Pricing
Marianne Baxter
Boston University
andNational Bureau of Economic Research

November 2023

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"New Low Price!"

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Why Study Prices?

Some prices change continuously in response to economic news
Stock and bond prices
Commodity prices (oil; gold)

Most prices don’t change that frequently aside from temporarysales
Firms selling inputs on the wholesale market to other firms
Textbooks; college tuition

To understand how monetary policy will affect the economy, weneed to understand how prices will respond to a change in policy

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Previous Literature
Supermarket prices in the US (Nielsen scanner data): Midrigan(2011)
Goods used to calculate price indexes for consumer goods orimport/export price indexes, within one country: Nakamura andSteinsson (2008)
Cross-country comparison of a few similar but not identical goods:
Crucini et al. (2005)
Retail price differences across Japanese cities: Crucini, Shintani
and Tsuruga (2010)
Cross-section web scraped prices across countries: Cavallo et al.
(2014)
Single-country studies of wholesale price setting by manufacturingfirms: Schoenle (2017) for the US; Dedola et al. (2021) for
Denmark
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Problems with the Existing Studies

Product replacement: When a good disappears, it is usuallyreplaced with a similar but not identical good
Comparing goods across firms with the same industry: even if they
are all "chairs", they are not exactly the same
Most contributions study a single country: the existing
cross-country studies compare similar but not identical goods
Prices may be "posted" prices but not the "transactions prices"that customers actually pay (problem with unobserved discountprices)Marianne Baxter (BU)

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Why Study IKEA Prices?

Unique opportunity to observe one company setting prices forthousands of goods sold in many countries at once, and for many
years at a time
These are posted, consumer-currency transactions prices that are
set by the firm that produces and sells the good, which is often not
the case for prices used in other studies
Prices change infrequently, with only a few limited sales
IKEA prices are free of issues associated with product substitution
or missing data

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IKEA catalog prices
IKEA’s iconic catalog represented 70% of IKEA advertising budget;
over 200 million copies printed each year
The catalogs are released in the summer of each year; the 2014
catalog was mailed in June 2013
Catalog prices are listed in the purchaser’s currency, including VAT
in European countries
IKEA guaranteed the catalog prices until the next year’s catalog isreleased
Most catalog goods are available in all catalogs, allowing
cross-country price comparisons

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Overview

1

Dataset Construction

2

Facts about IKEA Prices

3

Coordination of Price Changes

4

Exchange-Rate Pass-Through5

Summary and Conclusion

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Overview

1

Dataset Construction

2

Facts about IKEA Prices

3

Coordination of Price Changes

4

Exchange-Rate Pass-Through5

Summary and Conclusion

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Constructing the dataset
Gathered physical copies of IKEA catalogs for
Ten years: 2005-2014
Seven countries: Germany, France, US, UK (4 largest markets)
plus Italy, Sweden, UK: 2/3 of worldwide sales

Professional double-keyed entry of all product information on every
product entry in the catalogs,
guaranteed 99% accuracy
2,000 items per catalog; over 140,000 individual items
Information includes item name, dimensions, numeric code, color,materials, and any other text in the catalog that describes the goodMarianne Baxter (BU)

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Page from Swedish Catalog for 2008
Two‐seat sofa with chaise longue 6390:‐ withremovable, washable cover in 92%cotton/8%
polyester. Width 244xDepth 93/158. Height80cm. SIVIK yellow. [Item number] 498.483.13.

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Classification of Products
Family: a product line identified by nameExample: POANG family of seating; BILLY bookcases

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Good: Different products within a family
Example: Goods in the POANG family include rocking chair,armchair, ottoman, and even children’s chairs

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Variety: Goods within a family that differ only in fabric,color, or wood finish
Example: Varieties of the POANG armchair may have different prices
because some fabrics are more expensive.

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Linking IKEA Products

Beginning in 2005 IKEA catalogs became much more standardized
across countries, with a much higher fraction of common goods
than previously.
Also beginning in 2005, IKEA assigned a unique key to some items;by 2007, nearly all items contained a key for at least one country.
The information in the dataset was used to join together goods
across countries and years to produce a new panel dataset
containing prices for each individual IKEA catalog good.

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Could The Data Have Been Scraped from theWeb?
Cavallo et al. (2014) has extensive research on web-scraped prices,
including IKEA prices
Each item identified by its item number
But the item number isDifferent for the same item in different countries and different years
Different for the same item but with a different color or fabric

There is no way to join together the same item across countries,
years, and varieties without using the other information like name,dimensions, etc.

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Gaps in the Price Line

Price-lines for individual products in a given country are sometimes
interrupted
When a product is missing in one country it is usually missing in all
countries for that year: similarity of catalogs across countries isprobably the reason
Fill the missing price with the last observed price (standard
approach; see Klenow and Willis (2007); Nakamura and Steinsson(2008)) so the price does not change until it is observed in a
catalog

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A Price Line

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"Charm Pricing"Marketing research has shown that customers are influenced byprices that end in the digit "9", believing that these prices areespecially low or attractive
IKEA used this form of "charm pricing" extensively in somecountries
The use of “9” as the last digit is most common in the US (75%)
and Canada (69%), and least common in the UK, Sweden andFrance (about 48% in each of these countries).
It is also common in Japan

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Types of Price Changes

Previous work distinguishes between "small" price changes, usually
because of a temporary sale, and "regular" price changes that are
not meant to be temporary.
IKEA did not have "sales", but IKEA did experiment extensively
with "charm pricing", where prices ending in the digit "9" wereused to entice buyers
Penny price change: A price change less than 1 currency unit,
mainly because of experiments with "charm pricing"
Regular price change: All other price changes

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Type of Price Changes

Country

Regular

Penny

Total

CanadaGermany
France
Italy
Sweden
UK
US

83%
72%
75%
64%
100%
71%
88%

17%
28%
25%
36%
0%
29%
12%

100%
100%
100%
100%
100%
100%
100%

Average

78%

22%

100%

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Overview

1

Dataset Construction

2

Facts about IKEA Prices

3

Coordination of Price Changes

4

Exchange-Rate Pass-Through5

Summary and Conclusion

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Price Setting Behavior
IKEA did not change prices every year, even though they print a
new catalog every year
About 70% of possible price changes (the good is in the
catalog two years in a row) are equal to zeroFirms don’t always change prices when they have the opportunity
to do so because of a "menu cost" or some other force that makeschanging prices costly to the firm
By observing how often prices change, under what circumstances
they change, and the size of the change, we can learn about thesize of these costs

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Price Changes Happen Infrequently

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Distribution of Regular Price Changes

Zero price change
Positive price change
Negative price change

Fraction

Size: Mean

Size: Median

70%
19%
12%

0%
17%
-19%

0%
11%
-17%

Price increases are more frequent and larger in absolute value thanprice decreases
But IKEA’s advertising draws attention to
Goods that have the same price as last year
Goods with lower prices than last year: "New Low Price!"

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Price Changes: Intensive and Extensive Margins
The literature on price stickiness and inflation has emphasized thedistinction between the extensive margin and intensive margin forprice changes.
Extensive margin: change in the fraction of goods having pricechanges
Intensive margin: the same fraction of goods experienced pricechanges, but the average size of the price change changes
Different models of price-setting have different implications for thepredicted importance of intensive vs. extensive margins
Klenow and Kryvtsov (2008) find that the variance of US CPI
inflation is due mainly to variation along the intensive margin
IKEA ’country level inflation’ is also mostly due to changes on theintensive margin but with a more significant covariance term
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Price change decomposition
Let πct denote the annual inflation rate of an IKEA price in country
c in year t (suppressing the subscript for the particular good).
Write πct as the product of the average size of the price change, szct
and the fraction of goods changing price, frct :πct = szct ·frct .
A second-order approximation yields
2var(πct ) = var(szct )frc + var(frct )sz2c + 2frc szc cov(frct , szct ) + Oct
where frc denotes the sample mean of frct , szc denotes the sample
mean of szct and Oct denotes higher-order terms.
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Price change decomposition, continued
Klenow and Kryvtsov (2008) define intensive margin (IM) andextensive margin (EM) components as follows:
IM = var(szct )frc

2

EM = var(frct )szc 2 + 2frc szc cov(frct , szct ) + Oct .
This decomposition allocates the covariance term to the extensive
margin component, which is unimportant in the Klenow and Kryvstov(2008) data where the covariance term is very small and the intensive
margin component accounts for over 90% of the variance of inflation.

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Intensive and Extensive Margins

Corr. w/IKEA inflation
Intensive
CanadaFranceGermany
Italy
SwedenUK
USMarianne Baxter (BU)

Extensive

0.94
0.96
0.94
0.95
0.96
0.96
0.98

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0.80
0.85
0.78
-0.20
0.75
0.71
0.83

Corr(IM,EM)
0.67
0.73
0.61
-0.02
0.58
0.61
0.80

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Variance Decomposition of IKEA Inflation

Share of inflation variance explained by
IM EM Corr(IM,EM)O
CanadaFranceGermany
Italy
SwedenUK
USMarianne Baxter (BU)

0.74
0.78
1.02
0.74
0.74
0.62
0.74

0.01
0.02
0.04
0.03
0.00
0.05
0.04

0.14
0.16
0.24
0.01
0.04
0.23
0.28

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0.11
0.04
-0.30
0.23
0.22
0.10
-0.06

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Intensive Margin: Non-Zero Regular Price Changes
Age of Price(years)
2
3
4
5
6
7
8
9
10

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Price Change
mean
s.d.

N

0.29% 11.39% 25,162
1.02% 12.42% 13,066
1.47% 12.80% 7,867
1.22% 12.40% 4,417
1.27% 15.41% 2,798
0.24% 14.67% 1,528
3.36% 24.35%
658
3.09% 22.49%347
2.15% 20.90%
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The Hazard Rate
The hazard rate–the probability of a price change conditional on theprice being unchanged for N years – appears to be independent of N.
Estimation results below show that the age of the price has a small
but significant effect on the probability of a price change.

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Summary: Facts About IKEA Prices

Facts about Prices

IKEA

Prior
Literature

Frequent price changes (every 7 months)
Large average absolute price changes (10%+)
Many small price changes
Price incr. smaller & more frequent than decr.
Variable price durations
Flat hazard rates
Size of price changes does not increase with duration
Intensive margin dominates the variance of inflation

NO
Yes
Yes
Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

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Overview

1

Dataset Construction

2

Facts about IKEA Prices

3

Coordination of Price Changes

4

Exchange-Rate Pass-Through5

Summary and Conclusion

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Coordination of Price Changes
We can learn about the costs of changing prices by observing
whether firms selling many products choose to change the prices ofmany goods at the same time. That is: are price changes
coordinated ?
If price changes are coordinated, and especially if there are manysmall price changes, this suggests the presence of economies ofscope in price setting: changing one price makes it less costly tochange other prices
Why would this be true? Information costs; attention costs; timeand effort to calculate the optimal level of a new priceMarianne Baxter (BU)

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Evidence on Economies of Scope

Several papers find evidence on economies of scope operating at thelevel of the firm: coordinated price changes within firms is muchhigher than coordination across firms. Two examples are:Midrigan (2011) suggests that economies of scope can explain thepresence of many small price changes in a US supermarket chain
Dedola et al. (2021) study individual product prices for
multi-product Danish firms. They find evidence of coordination ofprice changes within firms, but not across firms in the same
industry.

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Price Coordination for IKEA
Following Dedola et al. (2021), estimate a probit with dependent
variable = 1 if the good’s price increased (decreased) in a given
country, year, and family
Significant within-year coordination of price changes in a country
When adding family-level variables, within-country coordination issignificant at the family level, but the overall country variable
becomes insignificant
Rest-of-the-world (ROW) price changes at the country or familylevel are not significant
Results are consistent with the spirit of Dedola et al. (2021) who
found coordination of price changes within a firm but not acrossfirms in the same industry
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Probit: Coordination of Price Increases
(1)

(2)

(3)

Inflation (lagged)−0.39(0.32)−0.35(0.25)−0.68(0.53)

Age of price (years)

0.04∗∗∗(0.00)

0.04∗∗∗(0.00)

0.04∗∗∗(0.00)

Fraction incr. in c, y0.39∗∗∗(0.04)

0.06∗(0.03)

0.05∗(0.02)

0.36∗∗∗(0.01)

0.36∗∗∗(0.00)

Fraction incr. in family, c, y
Price increases in ROW, y

0.09(0.06)

Fraction incr. in family, ROW, y−0.01(0.01)

Observations

74113

63370

63178

Marginal effects evaluated at variables’ means.
Includes country dummies. SE’s in parentheses, clustered at country level.
∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
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Probit: Coordination of Price Decreases
(1)

(2)

(3)

Inflation (lagged)

0.17(0.11)−0.06(0.16)−0.05(0.16)

Age of price (years)

0.03∗∗∗(0.00)

0.03∗∗∗(0.00)

0.03∗∗∗(0.00)

Fraction decr. in c, y0.48∗∗∗(0.03)

0.10∗∗∗(0.02)

0.08∗(0.04)

0.26∗∗∗(0.00)

0.26∗∗∗(0.00)

Fraction decr. in family, c, y
Fraction decr. in ROW, y

0.04(0.08)

Fraction decr. in family, ROW, y−0.03∗∗(0.01)

Observations

74113

63370

63178

Marginal effects evaluated at variables’ means.
Includes country dummies. SE’s in parentheses, clustered at country level.
∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
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Overview

1

Dataset Construction

2

Facts about IKEA Prices

3

Coordination of Price Changes

4

Exchange-Rate Pass-Through5

Summary and Conclusion

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Do Exchange Rates Affect IKEA Prices?
IKEA goods are produced in several steps that can take place inseveral different countries
Workers at each stage of production must be paid in their homecountry currency
The cost of material inputs that cross borders can be affected bychanges in the exchange rate
The finished goods are shipped from the final production location
to stores around the world, where local "distribution services" areincurred in the local currency, and goods prices are set in the homecurrency of the customer
The exchange rate should affect the local currency price in thestore because the cost of the physical good was paid in in thecurrency of the production location
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Estimating Exchange-Rate Pass-ThroughThe IKEA store combines the goods with retail services and sells
the goods to the consumer
The cost of good i at the border (the price to the local IKEA storeof the good when it arrives in the country, but before being put
borderinto the store) at date t is denoted Pictand is measured in Euros
The country-c local currency price of this good at the border isborderthen Ect Pict
where Ect is the exchange rate expressed as local
currency units per Euro.
The share of retail services in the overall cost of delivering thegood is given by ρ
The local currency price of distribution services is Dct

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The Pricing Equation
The cost to IKEA of selling good i in country c at time t isborderCOSTict = Ect Pict(1−ρ)(Dct )ρ

IKEA may add a markup over cost equal to Γict , in order to earn someprofit from selling the good.
The in-store price of the good is:borderPict = Ect Pict(1−ρ)(Dct )ρ Γict

Notice that this becomes the Law of One Price if there are no
distribution services: ρ = 0, and if there is no markup.

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Estimating Exchange-Rate Pass-ThroughTo turn the price equation into a linear form that we can estimate
using regression methods, take the log difference of both sides:
retailretail)) − ln(Pic,(t−1)≡ ln(Pict
Δpretail
ict

Then we have:Δpretail= (1 − ρ) Δect + Δpborder+ ρΔdict + Δγict .
ict
ict

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Estimating Exchange-Rate Pass-ThroughWe have data on the retail price and the exchange rate, and the local
price level will be used as our measure of local distribution costs. We
do not observe the border price or the markup. Rearrange thepassthrough equation as follows:Δpretail= (1 − ρ)Δect + ρΔdict + (1 − ρ)Δpborder+ Δγict .
ict
ict
The change in the border price would be the same for all countries
except for the different costs of shipping to different countries, sinceeach good, with few exceptions, is made in the same location in theworld. So the change in the border price would be approximately thesame for all countries, except for changes in relative shipping costs.
Most of the variation in the last term will be coming from changes in
the markup.
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Estimating Exchange-Rate Pass-Through

The ERPT estimating equation includes country fixed effects, Ψi ,that capture each country’s average change in markup and shipping
costs.
Δpretail= Ψi + (1 − ρ)Δect + ρΔdict + uictict
The error term uict captures good-level changes in factory prices anddeviations from country-level average markups.

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Results from Pass-Through Regressions
Dependent variable: price change (t)Inflation (t-1)
1.025*** 0.990*** 0.951*** 0.955*** 0.954***(Std. Error)(0.06)(0.06)(0.06)(0.06)(0.06)
Depreciation (t-1) 0.078*** 0.071*** 0.076*** 0.077*** 0.077***(Std. Error)(0.01)(0.01)(0.01)(0.01)(0.01)
Fixed Effects
Country
Age
Price decile
Variety
Adjusted R2 (%)
Observations

Marianne Baxter (BU)

0.9
56,067

Y

Y
Y

Y
Y
Y

Y
Y
Y
Y

1.2
56,067

1.5
56,0671.7
56,0671.7
56,067

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Approximately Zero Exchange-Rate Pass-ThroughThe coefficient on the change in the exchange rate –the amount of
exchange-rate pass-through –was expected to be equal to ρ ≈ 0.33,
the share of the physical good in the total cost of providing thegood to the consumer. But the estimate is only about 0.07 − 0.08.
This result is consistent with many previous studies on
exchange-rate pass-throughFirms choose not to pass on changes in costs coming from theexchange rate to customers
Firms may be worried about keeping their prices in line withcompetitors, or may be worried about upsetting their customers

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Almost 100% Pass-Through of Local Inflation

The expected coefficient was ρ ≈ 0.67, but the estimates are all
close to 1.00, meaning that 100% of local inflation is passed
through into IKEA prices in that country
This is also consistent with many previous studies that find highpass-through of local inflation to prices, especially when local costs
are a substantial fraction of the overall cost of delivering the good
It can also reflect the firm’s focus on the costs of local competitors,
whose prices will probably change with the level of local inflation

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Anticipating VAT Changes
IKEA looks ahead two years and raises prices before the
VAT change so it can lower them later!
Three countries increased their Value-Added-Tax rates during thesample period
In each case, it was known at least two years in advance that the
VAT increase was coming.
IKEA raised prices in the two years ahead of the VAT increase, but
decreased prices in the year the VAT increase took place
This allowed IKEA to advertise lower VAT-inclusive prices when the
VAT rose!

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Value-Added Tax Rates
Country specific VAT across years
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014

FranceGermany

Italy

US

CanadaUK

Sweden

.196
.196
.196
.196
.196
.196
.196
.196
.196
.196

.16
.16
.16
.19
.19
.19
.19
.19
.19
.19

.20
.20
.20
.20
.20
.20
.20
.21
.21
.22

0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
0
0
0
0
0

.175
.175
.175
.175
.175
.175
.175
.200
.200
.200

.25
.25
.25
.25
.25
.25
.25
.25
.25
.25

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Pass-through with VAT Changes
Dependent Variable: Price Change (t)Inflation (t-1)
Depreciation (t-1)
VAT Change (t)

(1)

(2)

(3)

(4)

1.025
(0.06)
0.078(0.01)

1.028(0.06)
0.076-0.01-0.515(0.14)

0.992(0.06)
0.075(0.01)-0.496(0.14)
1.145(0.14)

1.144(0.08)
0.099(0.01)-0.572(0.20)
0.708(0.20)
1.340(0.19)

56,0670.009

56,067 56,067
0.009 0.011

30,9030.014

VAT Change (t-1)
VAT Change (t-2)
Observations
Adjusted R-squared
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Overview

1

Dataset Construction

2

Facts about IKEA Prices

3

Coordination of Price Changes

4

Exchange-Rate Pass-Through5

Summary and Conclusion

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Summary and Conclusion

The IKEA catalogs formed the foundation for a new data set
allowing the analysis of transactions prices for precisely defined
goods across countries and over time
The analysis shows that IKEA is truthful in advertising its
extraordinary commitment to unchanging prices
Prices last an average of half the lifetime of the product, comparedwith just a few months for prices analyzed in previous studies
IKEA advertises reductions in price but actually increases moreprices than it decreases, just by a smaller average amountMarianne Baxter (BU)

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Summary and Conclusion
Overall, the "price facts" for IKEA are similar to the facts for otherstudies of prices, except for the extremely long time that IKEA
prices remained unchanged
IKEA focuses its focus pricing strategy at the country level: there
is little cross-country coordination in price changes despite the factthat most IKEA goods are produced in a single location andshipped worldwide
Exchange-rate pass-through is approximately zero – much lower
than predicted, even with an important role for distribution
services.

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Review 95 (3), 724–738.
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extensive and intensive margin of price adjustment to cost shocks:
Evidence from Danish multiproduct firms.
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time-dependent pricing: Does it matter for recent US inflation?
The Quarterly Journal of Economics 123 (3), 863–904.
Klenow, P. J. and J. L. Willis (2007). Sticky information and sticky
prices. Journal of Monetary Economics 54, 79–99.
Midrigan, V. (2011). Menu costs, multiproduct firms, and aggregate
fluctuations. Econometrica 79 (4), 1139–1180.
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Nakamura, E. and J. Steinsson (2008). Five facts about prices: A
reevaluation of menu cost models. The Quarterly Journal of
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