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The Exchange Rate: What’s in It for Prices?*
BY GEORGE ALESSANDRIA AND JARCY ZEE

arge movements in the exchange rate are
quite common, and they substantially alter
one’s purchasing power when traveling
abroad. Yet these exchange rate movements
tend to have a smaller impact on the price of foreign
goods that are imported. Following an appreciation of the
euro against the dollar, European firms selling products
to American firms for import do not raise their prices
by nearly as much as the prices they charge consumers
in the European market. Similarly, American firms sell
their products at higher prices in Europe than at home.
This incomplete, or partial, pass-through of exchange
rate movements to domestic import prices is important
for inflation, American purchasing power, and the
pattern of trade between countries. In this article, George
Alessandria and Jarcy Zee discuss some of the reasons
why changes in the exchange rate may not be fully passed
through to import prices.

In the summer of 2008, traveling
to Europe was quite expensive for
Americans, while traveling to the
U.S. was a bargain for Europeans. For
George
Alessandria is an
economic advisor
and economist in
the Philadelphia
Fed’s Research
Department.
This article is
available free of
charge at www.
philadelphiafed.org/research-and-data/
publications/.
www.philadelphiafed.org

instance, on average, a Big Mac1 was
almost 50 percent more expensive
in Europe than in the U.S. ($5.31 in
Europe and only $3.57 in the U.S.).
Just five years earlier, the gap was
much smaller: Big Macs in Europe cost
only about 15 percent more than Big

Big Mac™ is a registered trademark of the
McDonald’s Corporation.

*The views expressed here are those of the
authors and do not necessarily represent
the views of the Federal Reserve Bank of
Philadelphia or the Federal Reserve System.

Macs in the U.S. ($3.05 in Europe and
$2.65 in the U.S.). 2 A key component
of the 35 percent increase in the price
of European Big Macs relative to U.S.
Big Macs was a nearly 50 percent
depreciation of the U.S. dollar relative
to the euro: from $1.06 per euro in
January 2003 to $1.58 per euro in
July 2008. As the dollar depreciated,
McDonald’s raised both the Big Mac’s
dollar price in the U.S. and the euro
price in Europe, but the price increase
in the U.S. was not large enough to
offset the effect of a weaker dollar,
making European Big Macs relatively
more expensive.
The increase in the relative price
of European Big Macs was typical for
a broad range of goods. Over this
same period, the broad basket of goods
making up the European consumer
price index3 (CPI) became 45 percent
more expensive relative to the broad

2
Based on Big Mac prices as of July 24, 2008,
and January 16, 2003. The Big Mac index is
published periodically by The Economist and is
a useful way of comparing the price of goods in
different countries. For more information about
the Big Mac index, go to http://www.economist.
com/markets/bigmac/.
3
The consumer price index measures the price
of a basket of goods that the typical consumer
in a country purchases. The CPI is one of the
main indicators measuring inflation.

Jarcy Zee is a
research analyst in
the Philadelphia
Fed’s Research
Department.

Business Review Q3 2009 1

basket of goods making up the U.S.
CPI. Just as with the Big Mac, the
main source of the increase in the
price of European goods in Europe
relative to U.S. goods in the U.S. was
the 50 percent depreciation of the U.S.
dollar against the euro.4 Only a small
part of this exchange rate movement
was offset by U.S. prices rising slightly
faster than European prices in euros
(18 percent rise in the U.S. vs. 13
percent rise in Europe).
These movements in the exchange
rate have made buying all goods in the
U.S. relatively inexpensive compared
with buying goods in Europe, even if
these goods were produced in Europe.5
For instance, while the sticker price
of an Audi A4 sold in the U.S. but
produced in Germany rose 13 percent
in dollars from 2003 to 2007, its sticker
price in Germany when converted to
dollars rose 28.5 percent as the dollar
depreciated.6 Across a broad range
of imported goods, we find similar
price changes in that European firms
selling products to American firms
for import have not raised their prices
by nearly as much as the price they
charge Europeans to buy their products
in Europe. Similarly, American firms

are selling their products to Europe
for more than they sell their products
at home. These pricing policies imply
that U.S. consumers purchasing
imports have been partially insulated
from the effect of a weaker dollar.
The incomplete, or partial, passthrough of exchange rate movements
to domestic import prices is important
for inflation, American purchasing
power, and the pattern of trade
between countries. In this article,
we present some evidence on the
pass-through of the changes in the
exchange rate to import prices in the
U.S. and abroad, and we discuss some
reasons why changes in the exchange
rate may not fully pass through to
import prices.
BEHAVIOR OF EXCHANGE
RATES AND CONCEPT
OF PASS-THROUGH
The nominal exchange rate,
which measures the rate at which one

country’s currency can be exchanged
for another country’s currency, tends
to experience large and sustained
changes. As seen in Figure 1, the
U.S. nominal exchange rate relative
to the currency of its trading partners
(the dashed line) fell substantially
from 1996 to 2002, so that it took 29
percent fewer U.S. dollars to buy one
unit of foreign currency in 2002 than
in 1996. This period of U.S. dollar
appreciation was followed by a period,
from 2002 to 2008, when the nominal
exchange rate increased 29 percent,
indicating a depreciation of the U.S.
dollar.
These changes in the nominal
exchange rate are not offset by
movements in the local prices or
production costs of goods, so that there
are also large and sustained changes
in the relative cost of producing goods
or buying goods in different countries.
The real exchange rate, which
measures the cost of goods sold in the

FIGURE 1
U.S. Nominal and Real Exchange Rates
Percentage Change (measured as log difference) from 2002Q1

The relative change in price, 'q, is calculated
by 'q = 'e + 'p – 'p*, where 'e is the change
in the nominal exchange rate, 'p is the change
in the U.S. price level, and 'p* is the change in
the European price level.
4

Nominal, Broad Series

Since the first quarter of 2003, nominal
European manufacturing costs have risen 14.5
percent in euros, while U.S. manufacturing
costs have risen only 12.1 percent, measured in
dollars.

These price changes are based on sticker
prices in the U.S. from annual issues of Ward
Automotive’s Car Specifications and Prices and
pre-tax sticker prices in Germany from the
European Commission’s biannual car price
reports in May 2003 and May 2007. In 2003,
the U.S. model was an Audi A4 1.8T FrontTrak
(1.8L, 170 hp), and the German model was an
Audi A4 1.9 TDI (1.9L, 130 hp). In 2007, the
model priced in each country was an Audi A4
2.0 TDI. Exchange rate conversions were $1.13/
euro in 2003 and $1.37/euro in 2007.

2 Q3 2009 Business Review

Real, Broad Series

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U.S. relative to the rest of the world,
is calculated as a ratio of foreign and
domestic consumer prices measured
in a common currency. Because most
goods consumed are domestically
produced, the real exchange rate
provides a good proxy for how the
relative cost of producing goods in
different countries changes over time.
Figure 1 demonstrates that the real
exchange rate (solid line) and nominal
exchange rate (dashed line) tend to
move together, indicating that relative
production costs are highly correlated
with the nominal exchange rate.
These fluctuations in the cost of
producing goods in the U.S. relative to
overseas markets also affect the cost
of producing the goods that the U.S.
imports (and exports). In response
to the movements in relative costs,
foreign firms alter the price they
charge for their goods in the U.S.
and at home. Figure 2 shows both
how the relative cost of American
goods fluctuates (the real exchange
rate indicated by the solid green line)
and how the price of imported goods
relative to the price of goods produced
in the U.S. changes. The two lines
have a similar pattern. As the cost of
producing goods overseas fell relative
to the U.S. from 1996 to 2002, so did
the price of goods imported to the
U.S. Similarly, as the cost of producing
goods overseas rose from 2002 to the
present, so did the price of imported
goods. The magnitudes are quite
different, though. From 1996 to 2002,
relative to the cost of producing and
selling U.S. goods, the cost of foreign
goods fell 24 percent, while the price at
which Americans could import these
goods fell about 13 percent. Similarly,
since 2002, producing goods overseas
has become about 27 percent more
expensive than producing in the U.S.,
yet the price at which these goods
are imported into the U.S. has risen
only about 15 percent. Thus, import

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price movements tend to be smaller
than movements in relative costs or
exchange rates.
The extent of pass-through can
be measured as the ratio of the change
in the import price to the change in
relative production costs. A passthrough value of 100 percent denotes
complete pass-through and indicates
that a 10 percent change in foreign
cost results in a 10 percent change
in the import price. Pass-through
less than 100 percent, denoted as
incomplete or partial pass-through,
implies that prices are less responsive
to movements in relative production
costs. To measure pass-through, we
could just use the nominal exchange
rate as a measure of the relative
change in costs. However, because
the exchange rate movement may be
associated with changes in the costs of
producing the good, the approach we
take will be conditioned on changes in
costs. To control for these changes in

costs, for import prices, it is common
to use a measure of costs or prices in
the source market. For our baseline, we
take the change in price in the source
country market measured in nominal
terms using the destination market’s
currency as a measure of the change in
costs and then estimate pass-through
using the change in price in the
destination market.
For example, suppose the ABC
car company charges $10 for a car
in its home market of Europe when
converted to U.S. dollars and $10
for the same car in the U.S. If the
company raises its price to $20 in
Europe and $17 in the U.S., passthrough is 70 percent. However, the
price change in Europe relative to the
U.S. may result from either a change
in the euro to dollar nominal exchange
rate or from the cost of producing the
good. Suppose initially that $1 can
be exchanged for 1 euro and the car
sells for 10 euros in Europe and $10

FIGURE 2
Import Prices Relative to Producer Prices
Percentage Change (measured as log difference) from 2002Q1
30

RER (Broad)

5
Core Import Price/Core PPI

0
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Business Review Q3 2009 3

in the U.S. In the next year, suppose
the U.S. dollar depreciates, so now
$2 are needed to buy 1 euro. If ABC
keeps its car price in Europe at 10
euros, or $20 when converted to U.S.
currency at the new exchange rate, but
raises its price in the U.S. to $17, we
find pass-through to be 70 percent.7
Alternatively, suppose the nominal
exchange rate does not change but
that the price of steel, an important
input for producing cars, increases.
If ABC decides to double its price
in Europe to 20 euros, or $20 at a
constant $1 per euro exchange rate,
and raise its price to only $17 in the
U.S., we will also find pass-through to
be 70 percent.8
EVIDENCE OF INCOMPLETE
PASS-THROUGH
Many studies measure passthrough in different countries,
industries, and time periods. These
studies also distinguish between passthrough to import prices and passthrough to the consumer price index.
The focus here is on pass-through
to import prices in the long run.
Empirical Estimates of Exchange Rate
Pass-Through explains the empirical
framework of some of these studies.
Pinelopi Goldberg and Michael
Knetter survey these studies and find
that pass-through to import prices is
about one-half. Thus, if foreign costs
rise 10 percent, the import price of
foreign goods is expected to rise 5
percent. Pass-through is nearly the
7

ERPT =

ecent research has focused on understanding how pass-through
has changed over time and how it differs across countries. A
study by Mario Marazzi and co-authors uses disaggregated data
to document a decline in exchange rate pass-through since the
1980s and to attribute it to the decrease in industry-specific
changes. José Campa and Linda Goldberg study trade between the U.S. and a
broader sample of countries to observe pass-through across time.
The two studies use a similar empirical framework, running a regression
of changes in import prices on changes in the exchange rate and foreign costs
using quarterly data:
4

i 0

'ptj

i 0

0.7
'p
=
=0.7,
'e + 'p*
0+1

4 Q3 2009 Business Review

i 0

where for country j, pt is the import price, e is the exchange rate, wtj is
foreign cost, gdpt is real GDP and p tcom is a measure of commodity prices. The
regressions in the two papers differ slightly. Campa and Goldberg run their
regression using quarterly data from the first quarter of 1976 to the first quarter
of 2004 for 16 countries and drop the term controlling for commodity prices.
Marazzi and co-authors focus on just the U.S. from the fourth quarter of 1972
to the fourth quarter of 2004, exclude the term of real GDP, and constrain the
term on foreign costs measured using foreign price levels to be the same as that
on the exchange rate.
Short-run pass-through is represented by the coefficient a0j and long-run
4
pass-through is represented by the sum of coefficients¦ aij. Campa and Goldberg
i 0
find that long-run pass-through of exchange rates into manufacturing import
prices is about 44 percent for the U.S. using this regression. Their micro
estimates from the broad range of countries show an average exchange rate
pass-through into manufacturing import prices of about 60 percent.
Marazzi and co-authors find that pass-through to import prices in the
1980s was roughly 50 percent, but it has declined to about 20 percent in the
mid-1990s. Campa and Goldberg, however, find less evidence of the decline in a
broader sample of countries.
j

0.7
'p
=
=0.7,
'e + 'p*
1+0

where 'p is the percent change in price, 'e is
the percent change in the nominal exchange
rate, and 'p* is the percent change in the
foreign price.

E j ¦ aij 'etji ¦ bi j 'wtji ¦ cij 'ptcom ¦ di j 'gdptji vitj
i

same following either an increase or a
decrease in foreign costs.9
Pass-through also tends to vary by
industry: It’s relatively high for raw materials and energy and relatively low for

where 'p is the percent change in price, 'e is
the percent change in the nominal exchange
rate, and 'p* is the percent change in the
foreign price.
8

Empirical Estimates of Exchange Rate
Pass-Through

In a study of exchange rate pass-through to
U.S. import prices, Giovanni Olivei finds that
pass-through does not depend on the direction
of the exchange rate movement in 32 out of 34
industries.

j
t

manufactured goods. José Campa and
Linda Goldberg estimate pass-through
from a broad sample of countries in the
energy industry to be about 77 percent,
on average. Giovanni Olivei estimates
pass-through for nonenergy industries
and finds pass-through of about 39
percent for the automobile industry, in
the long run.
We next turn to the recent
evidence of pass-through to import

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prices for manufactured goods between
the U.S. and two of its major trading
partners, Canada and the European
Union. Together, Europe and Canada
account for about 30 percent of U.S.
international trade over the period
2000 to 2007. We focus on these
countries not only because they are
major trading partners of the U.S. but
also because we have fairly accurate
measures of both their production
costs and U.S. import prices. There
have also been some fairly large and
sustained exchange rate movements
that allow us to measure pass-through
over long intervals.10
Pass-through on European
goods to prices in the U.S. has
been approximately 25 percent.
Figure 3 presents the relative cost
of manufactured goods produced
in Europe to manufactured goods
produced in the U.S. (solid line). As
before, we split the period evenly
between a large appreciation of
the dollar from 1996 through the
first quarter of 2002 and a large
depreciation since then. In the first
half of the sample, European goods
became 38 percent less expensive to
produce, yet the import price (the
dashed line) fell only by about 10
percent, indicating that pass-through
was just under 25 percent. In the
second half of the sample, producing
European goods became just over 60
percent more expensive, yet import
prices rose only about 14.5 percent.
Again pass-through was only about 25
percent.
At about 50 percent, pass-through
on Canadian goods has been somewhat

higher than for European goods. Figure
4 presents the cost of manufactured
goods produced in Canada relative
to the cost of goods manufactured in
the U.S., again divided into a period
of dollar appreciation followed by a
period of depreciation. In the first
half of the sample, Canadian goods
became about 13 percent cheaper to
produce than American goods, and
this translated into a drop in the price
of Canadian imports of just under
7 percent, for pass-through of about
52 percent. In the latter half of the
sample, the situation reversed, with
relative costs rising 29 percent and
import prices rising about 15.5 percent.
Again, pass-through was just over 50
percent.

the same good in different countries11
and that, over time, they are changing
prices in each market by different
amounts. We now discuss some of the
common reasons why firms may elect
to change their prices by different
amounts in different countries
following a change in their costs.
One common reason for
incomplete pass-through, suggested
by Rudiger Dornbusch, is that firms
face different competitors in each
market, and therefore, exchange rate
movements affect the competitive
environment differently across
countries. For instance, most cars
available in the U.S. are produced in
the U.S., while most cars available
in Europe are produced in Europe.

WHY IS PASS-THROUGH
INCOMPLETE?
Fundamentally, incomplete
pass-through suggests that firms are
sometimes charging different prices for

11
The Business Review article by George
Alessandria and Joseph Kaboski presents
evidence that some of the long-run differences
in prices across countries are related to
differences in income.

FIGURE 3
Europe’s Real Exchange Rate and Import Prices
Percentage Change (measured as log difference) from 2002Q1

40
PPI-based RER

20
EU Import Prices/US PPI
10

While we focus on pass-through of relative
cost movements that occurred along with
changes in nominal exchange rates, it is also
possible to measure pass-through of relative
costs when the exchange rate does not change,
such as when a country follows a fixed exchange
rate regime.

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Business Review Q3 2009 5

FIGURE 4
Canada’s Real Exchange Rate and Import Prices
Percentage Change (measured as log difference) from 2002Q1
35
30
25
PPI-based RER

20
15
10
5
0

CAN Import Price/US PPI (adjusted for oil)

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But, of course, you can find European
cars in the U.S. and U.S. cars in
Europe. When the euro appreciates,
or becomes more valuable compared
to the dollar, European carmakers
will face higher relative costs. In the
U.S., European carmakers may find
it difficult to raise their prices, since
there are many relatively low-cost U.S.
cars available. In Europe, however,
there are fewer relatively low-cost U.S.
cars available, so European carmakers
can raise their prices by more, or at
least they do not have to lower prices
to avoid losing customers.
Firms exporting their goods to
the U.S. may also decide not to raise
their prices following a depreciation
of the dollar because doing so would
have a negative impact on its future
profits. For instance, an automaker
that sells a car today also expects to
sell repair services for that car in the

6 Q3 2009 Business Review

future and increases the likelihood
that the same customer will buy
another car in the future. Thus, if that
automaker raises its prices a lot today
and sells fewer cars, it will have fewer
customers (and sales and profits) in the
future. A study by George Alessandria
shows that firms carefully consider the
effects of their price changes on both
today’s profits and future profits. It
turns out that maximizing the sum of
current and future profits may imply
a relatively smaller price adjustment
today in order to prevent losing
customers and future sales and service.
Local inputs to production of
foreign goods can also cause import prices to move by less than the
exchange rate. In a 2002 article, José
Campa and Linda Goldberg find that
increases in the amount of imported
inputs that originate from the home
market, used in goods that are eventu-

ally re-exported to the home country,
are associated with lower pass-through
into import prices. For instance, the
cost of an Airbus airplane imported to
the U.S. from Europe would be expected to rise with an appreciation of the
euro. However, if the airplane’s engines
are produced by GE in the U.S. with a
relatively constant cost in dollars, the
cost to Airbus of producing the airplane will not have risen by the same
amount as the exchange rate. Thus,
Airbus may raise its price by less than
the exchange rate has appreciated. In
our estimates of pass-through, these
effects of inputs on prices are captured
by the foreign cost, so it only shows
up in an estimate of pass-through that
uses the nominal exchange rate to
measure costs.
Incomplete pass-through to
import prices may also arise if local
inputs are bundled to make final sales.
For instance, a European car sold in
the U.S. is bundled with some U.S.
services, mainly the wholesale services
in getting the car from the port of
entry in the U.S. to the dealership
and then the dealer’s retail services.
In another article (2006a), Campa
and Goldberg show that these local
components mostly matter for the
price that the final purchaser pays.
(See Pass-Through to Consumer Prices
from Exchange Rates for more details.)
However, these downstream costs
can also affect import prices and
pass-through. Again, consider the
case of a European car manufacturer
following an appreciation of the euro.
In addition to raising the cost of
producing European cars relative to
U.S. cars, the appreciation increases
the downstream costs of selling cars
in Europe relative to the U.S. These
differences in downstream costs imply
that the price at which the carmaker
sells to the dealer will be relatively
more important for the final sales
price, and hence sales, to consumers in

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Pass-Through to Consumer Prices from
Exchange Rates

he consumer price index (CPI) is a weighted average of the
prices of goods, based on a standard basket of consumer goods.
It is used to measure inflation. Movements in exchange rates
are not only passed through to import prices; they can also
be passed through to consumer prices. Thus, pass-through to
consumer prices measures the sensitivity of consumer prices to changes in the
exchange rate.
José Campa and Linda Goldberg study exchange rate pass-through to
import and consumer prices for 21 countries. On average, pass-through to
import prices is 64 percent, while pass-through to consumer prices is about
17 percent for these countries. For the U.S., consumer price pass-through is
close to zero. However, consumer price pass-through is higher in more open
economies, such as the Netherlands (38 percent) and Spain (36 percent). In all
cases, though, consumer price pass-through is lower than import price passthrough, indicating that exchange rate movements have a smaller effect on
domestic price levels than on import prices.
Consumer price pass-through tends to be lower than import price passthrough because the consumer price index includes only a small share of
imported goods. Thus, holding import price pass-through constant across
countries, consumer price pass-through tends to be higher in countries that
purchase a high share of goods from abroad, since a larger fraction of the
consumption bundle in these countries is affected by the exchange rate.
However, it is also possible to measure pass-through to consumer prices of
individual imported goods. For instance, in a case study of beer, Rebecca
Hellerstein finds that pass-through to retail prices on imported beer is only
about 11 percent. She attributes this incomplete pass-through to retail
prices to three things: incomplete pass-through of import prices by the beer
manufacturers; incomplete pass-through by retailers of the price charged by the
beer manufacturer; and the presence of wholesale and retail distribution costs
that do not change with the exchange rate.

the U.S. than to consumers in Europe.
Thus, the carmaker has an incentive
to raise its price by less in the U.S.
than in Europe.
An alternative, less conventional
view is that incomplete pass-through
results primarily from difficulties in
measuring prices accurately. In this
view, the composition of imports
may change systematically with the
exchange rate. In a third article
(2006b), Campa and Goldberg observe

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that these composition shifts can
change measures of pass-through
on aggregate import prices. Shifting
imports toward industries with lower
pass-through will cause aggregate
import pass-through to decline.
Likewise, a shift of imports toward
industries with higher pass-through
will increase pass-through of aggregate
prices. Alternatively, a depreciation of
the dollar may cause high-price foreign
firms exporting to the U.S. to exit,

or buyers may shift their purchases
toward lower quality imported goods.
For instance, consumers may prefer
imported cars with smaller engines or
cloth seats rather than leather ones.
Measurement of pass-through does not
adjust for these changes in the goods
being imported to the U.S.
Another possibility is that
companies are not accurately reporting
the price of international transactions.
This is thought to be particularly
relevant for those international
transactions that occur within
divisions of a multinational company,
such as when a car manufacturer ships
an engine or chassis from a plant in
one country to an assembly plant in
the U.S. This trade between related
parties is very common, accounting for
about 50 percent of all imports to the
U.S. These transactions are supposed
to be booked at market prices, the
prices at which unrelated companies
would carry out transactions. However,
since these prices do not affect trade
flows, multinational firms may not
be vigilantly updating these prices
with the exchange rate or even be
aware of market prices. Alternatively,
multinationals may choose the price of
the transactions to shift profits within
the company toward divisions that
are in countries with relatively low
taxes. In this case, tax considerations
matter more for pricing than exchange
rate movements do. Indeed, Kimberly
Clausing’s findings are consistent with
this tax-shifting story; she finds that
related-party transactions involving
U.S. imports are carried out at
relatively high prices when the goods
are imported from countries with
relatively low taxes.
Research has found that each
of the reasons described above
generates incomplete pass-through.
However, since the relevance of these
explanations differs across industries
and even time periods, the relative

Business Review Q3 2009 7

importance of each reason relative to
the others remains a question.
WHY PASS-THROUGH
MATTERS
To each of us, pass-through
clearly matters because it affects our
purchasing power at home and when
we travel overseas. At the aggregate
level, pass-through matters for the
conduct of monetary policy and the
propagation of business cycles across
countries.
Monetary policymakers concerned
with the inflationary impact of
exchange rate movements focus on
pass-through to import prices and
subsequently to consumer prices.12
The importance of pass-through for
inflation differs across countries. For
instance, in a country that consumes
a lot of imported goods, such as
New Zealand, where imports make
up nearly 40 percent of GDP, passthrough is very important for gauging
the inflationary impact of exchange
rate movements.13 In the U.S., which
imports only about 15 percent of
GDP and has relatively low passthrough, the influence of exchange
rate movements on inflation is smaller.
With better measures and models of
pass-through, policymakers can better
forecast the inflationary impact of
exchange rate movements and adjust

monetary policy accordingly.14
Pass-through is also important
for understanding the relationship
between economic activity and the
exchange rate. When pass-through
is high, changes in the exchange rate
can have a relatively large effect on

To each of us, pass-through clearly matters
because it affects our purchasing power
at home and when we travel overseas.
trade flows and thus the trade balance,
which is the difference between
what a country exports and what it
imports. An increase in import prices
decreases imports and therefore raises
net exports. This movement shifts
production to domestic firms, raising
demand for workers in the U.S. and
lowering it for workers overseas.
When pass-through is low, the effect
of exchange rate movements on trade
flows is much more muted.
Theoretical research, such as that
of George Alessandria and that of
Caroline Betts and Michael Devereux,
finds that incomplete pass-through
may actually contribute to larger
fluctuations in international relative
prices, such as the real exchange
rate, over the business cycle. Suppose
that the U.S. economy is booming

See the speech by former Federal Reserve
Governor Frederic S. Mishkin at the Norges
Bank Conference on Monetary Policy.

Import ratios are from the Organization for
Economic Cooperation and Development’s
(OECD) Country Statistical Profiles.

8 Q3 2009 Business Review

and producing a lot of goods. To
get consumers to purchase the
abundantly available U.S. goods, the
U.S. goods must sell for relatively
low prices; so there is a tendency for
the real exchange rate to depreciate.
However, if pass-through is low, within

14
Joseph Gagnon and Jane Ihrig also present
evidence that pass-through tends to be lower
for countries with more stable inflation and
hence central banks more determined to fight
inflation.

countries, the price of U.S. goods
will fall relatively little compared to
foreign goods, and hence, purchases of
domestic goods will not rise by much,
requiring a much larger movement in
the real exchange rate.
SUMMARY
Movements in the exchange
rate substantially alter the relative
cost of producing goods in different
countries. However, consumers in
different countries are partly insulated
from these movements by the pricing
behavior of producers.
Recently, the large depreciation
of the dollar has made producing
goods outside the U.S. relatively more
expensive. This has contributed to
rising prices of imported manufactured
goods in the U.S. However, the price
of imported manufactured goods has
risen by substantially less than the cost
of producing these goods and the price
at which they are sold in the country
where they are produced, making these
goods a bargain in the U.S. BR

www.philadelphiafed.org

REFERENCES

Alessandria, George. “Consumer Search,
Price Dispersion, and International
Relative Price Fluctuations,” International
Economic Review, 50:3 (August 2009), pp.
803-29.

Campa, José Manuel, and Linda S.
Goldberg. “Pass Through of Exchange
Rates to Consumption Prices: What Has
Changed and Why?,” NBER Working
Paper 12547 (2006b).

Hellerstein, Rebecca. “Who Bears the
Cost of a Change in the Exchange Rate?
Pass-Through Accounting for the Case of
Beer,” Journal of International Economics
76:1 (2008), pp. 14-32.

Alessandria, George, and Joseph Kaboski.
“Why Are Goods So Cheap in Some
Countries?,” Federal Reserve Bank of
Philadelphia Business Review (Second
Quarter 2008).

Clausing, Kimberly A. “The Behavior
of Intra-firm Trade Prices in U.S.
International Price Data,” BLS Working
Paper 333 (2001).

Marazzi, Mario, Nathan Sheets, Robert
Vigfusson, Jon Faust, Joseph Gagnon,
Jaime Marquez, Robert Martin, Trevor
Reeve, and John Rogers. “Exchange Rate
Pass-Through to U.S. Import Prices: Some
New Evidence,” Board of Governors of
the Federal Reserve System, International
Finance Discussion Papers Number 833
(2005).

Betts, Caroline, and Michael Devereux.
“Exchange Rate Dynamics in a Model of
Pricing-to-Market,” Journal of International
Economics, 50 (2000), pp. 215-44.
Campa, José Manuel, and Linda S.
Goldberg. “Exchange Rate Pass-Through
into Import Prices: A Macro or Micro
Phenomenon?,” NBER Working Paper
8934 (2002).
Campa, José Manuel, and Linda S.
Goldberg. “Distribution Margins, Imported
Inputs, and the Sensitivity of the CPI to
Exchange Rates,” NBER Working Paper
12121 (2006a).

www.philadelphiafed.org

Dornbusch, Rudiger. “Exchange Rates and
Prices,” American Economic Review, 77:1
(1987), pp. 93-106.
Gagnon, Joseph, and Jane Ihrig. “Monetary
Policy and Exchange Rate Pass-Through,”
International Journal of Finance and
Economics, 9 (2004), pp. 315-38.
Goldberg, Pinelopi, and Michael Knetter.
“Goods Prices and Exchange Rates: What
Have We Learned?,” Journal of Economic
Literature, 35:3 (1997), pp. 1243-72.

Mishkin, Frederic S. “Exchange Rate PassThrough and Monetary Policy,” Norges
Bank Conference on Monetary Policy,
Oslo, Norway (March 2008).
Olivei, Giovanni P. “Exchange Rates and
the Prices of Manufacturing Products
Imported into the United States,” New
England Economic Review (First Quarter
2002), pp. 3-18.

Business Review Q3 2009 9

Beautiful City*
BY GERALD CARLINO

roponents of the City Beautiful movement
advocated for sizable public investments in
monumental spaces, street beautification,
and classical architecture. Today, economists
and policymakers see the provision of consumer leisure
amenities as a way to attract people and jobs to cities.
But past studies have provided only indirect evidence of
the importance of leisure amenities for urban growth and
development. In this article, Jerry Carlino uses a new
data set on the number of leisure tourist visits to
metropolitan areas to examine the correlation between
leisure consumption opportunities and population and
employment growth in metropolitan areas during the
1990s. His study suggests that leisure amenities are
important for an area’s growth, even after controlling for
other characteristics, such as climate or proximity
to a coast.

The City Beautiful movement
of the late 19th and early 20th
centuries advocated city beautification
as a way to improve the living
conditions and civic virtues of
urban dwellers. Proponents of the

Jerry Carlino is a
senior economic
advisor and
economist in
the Research
Department of
the Philadelphia
Fed. This article
is available free
of charge at www.
philadelphiafed.
org/research-and-data/publications/.
10 Q3 2009 Business Review

movement advocated for sizable
public investments in monumental
public spaces, street beautification,
and classical architecture, with an
emphasis on aesthetic and recreational
values. The Benjamin Franklin
Parkway in Philadelphia with its
many public buildings (for example,
the Philadelphia Museum of Art, the
main branch of the Free Library of
Philadelphia, the Franklin Institute,

and the Rodin Museum) exemplifies
this movement.
Today, economists and
policymakers see the provision of
consumer leisure amenities as a way
to attract people and jobs to cities.
But most amenities, such as pleasant
weather or scenic views, are not
standard goods that are traded in
visible markets, making it difficult to
quantify the contribution of a city’s
quality of life to its growth. Past
studies have provided only indirect
evidence of the importance of leisure
amenities for urban growth and
development.
My 2008 study with Albert Saiz
makes the point that since leisure
tourists are attracted by an area’s
special traits (such as proximity to
the ocean, scenic views, historic
districts, architectural beauty, and
variety in cultural and recreational
opportunities), the number of leisure
tourist visits to a city can serve as
a fairly comprehensive proxy for
the quality of life the city offers.
Put differently, some of the very
characteristics that attract tourists to
cities also attract households to cities
when they choose these places as their
permanent homes.1
Using a new data set on the
number of leisure tourist visits to
metropolitan areas, Albert Saiz and
I looked at the correlation between

*The views expressed here are those of the
author and do not necessarily represent
the views of the Federal Reserve Bank of
Philadelphia or the Federal Reserve System.

“City” and “metropolitan area” are used
here to designate a metropolitan statistical
area (MSA). In general, MSAs are statistical
constructs used to represent integrated labor
market areas. They typically are geographic
areas combining a large population nucleus with
adjacent communities that have a high degree
of economic integration with the nucleus.

www.philadelphiafed.org

leisure consumption opportunities and
population and employment growth in
metropolitan areas during the 1990s.
We found that, all else equal, during
the 1990s, population growth was
about 2.2 percentage points higher and
employment growth 2.6 percentage
points higher in a city with twice as
many leisure tourists as another city.
The extra growth associated with
leisure amenities is not trivial when
one takes into account that during the
1990s, population grew 12 percent in
the typical metropolitan area in our
sample, while employment grew 20
percent. Over a long period of time,
even relatively small differences in
growth rates translate into relatively
large differences in population and
employment growth. Among the forces
Saiz and I considered in our study, our
leisure measure was the third most
important predictor of population
growth in the 1990s.
Cities around the world (such
as Barcelona and Bilbao; Glasgow;
and Oklahoma City, Camden, and
San Antonio) have used public
investments in leisure spaces and
city beautification in an attempt to
spur economic development. My
study with Saiz suggests that leisure
amenities are important for an area’s
growth, even after controlling for an
area’s proximity to a coast and for its
climate. This is an important finding,
since if people are largely attracted
by an area’s natural advantages, such
as coastlines or nice weather, these
types of amenities are not something
local policymakers can reproduce.
Instead, my study with Saiz provides
policymakers with evidence that
spending public funds to provide
public goods that are oriented toward
leisure activity (such as museums,
waterfront parks, and open-air
shopping centers) yields a return on
the investment in terms of a city’s
economic growth. The association

www.philadelphiafed.org

between leisure amenities and growth
may occur because such amenities
disproportionately attract more
productive workers.
WHY ARE PEOPLE AND JOBS
CONCENTRATED IN CITIES?
Although metropolitan areas
account for less than 20 percent
of the overall territory of the U.S.,
they contain about 80 percent of the
nation’s population and almost 85
percent of its jobs. Why are people
and jobs so spatially concentrated?
Economists have developed the notion
of agglomeration economies — that is,
the benefits that firms and households
receive from locating near one another

firms are too small to have a full-time
chief financial officer but big enough
to have some of the same problems
that confront larger companies.
However, by locating in a large city,
a small firm will be able to find a
local business that provides financial
managers who spend part of each week
doing what CFOs are supposed to do:
prepare budgets, project sales, and
negotiate with banks. A similar story
applies to other types of specialized
business services, such as access to
legal services and advertising agencies.
Consumer Agglomeration
Economies. Cities also offer numerous
leisure consumption opportunities to
households, and the larger the city,

Cities also offer numerous leisure consumption
opportunities to households, and the larger
the city, the greater the opportunities.
— to explain this concentration.
The two main types of agglomeration
economies are described below.
Business Agglomeration
Economies. Cities offer numerous
advantages to business firms, and
often, the larger the city, the greater
the advantages. Agglomeration
economies constitute an important
source of a firm’s productivity.
Increases in productivity due to
agglomeration economies depend not
on the size of the firm itself (internal
economies of scale) but rather on the
size of a firm’s industry in a particular
city or on the size of the city itself. For
example, firms in large cities are better
able to find workers who possess the
specific skills the firms require than
if they were in much smaller places.
Also, firms can reduce their costs by
locating in large cities and sharing
specialized inputs. For example, many

the greater the opportunities. Large
concentrations of population can
provide consumers with a greater
variety of goods and services. Our
largest cities can support professional
sports teams, theater, opera, and a
symphony orchestra. If consumers
prefer a large variety of goods and
services and there are substantial
economies of scale in providing them,
economic welfare will depend on the
size of the local market. For example,
studies by Joel Waldfogel and by
Waldfogel and Lisa George have shown
that larger cities have more and better
newspapers and more and better radio
and television stations.
From a social point of view, larger
cities make it easier for people to make
wider social contacts and to have a
more diverse set of friends. Along
these lines, larger cities appeal to
younger, more highly educated workers

Business Review Q3 2009 11

because large cities better facilitate
development of professional and social
connections. Dora Costa and Matthew
Kahn note that power couples (both
partners have bachelor’s degrees) are
increasingly locating in larger cities
because they offer better labor-market
outcomes for working couples.
It’s important to recognize that an
area’s quality of life depends on more
than the variety of goods and services
that increase with city population size.
People are also attracted by an area’s
“natural” amenities, such as its historic
character, architectural variety, natural
scenic beauty, nearness to the ocean,
or climate. Richard Florida has also
pointed out that people are paying
increasing attention to the provision of
public goods that are oriented toward
leisure activities, such as museums,
waterfront parks, open-air shopping
centers, and other public spaces
enjoyed by families and individuals.
But increased urbanization brings
not only greater productive efficiency
and greater variety of cultural and
leisure activities but also costs, such
as congestion, that take the form
of long-distance commuting and
higher housing prices. These costs
eventually balance the gains from the
various amenities. The higher cost of
housing as cities get congested reduces
households’ purchasing power and
limits the inflow of people.2
WHAT’S THE EVIDENCE?
Until recently, the vast majority of
studies have looked at the relationship
between business agglomeration
economies and city growth. As I’ve
pointed out in previous articles,
technical improvements, especially
in transportation, mean that, today,
businesses are freer to locate wherever

they want, and, unlike before, their
choice of location will depend on
where their workers choose to live.3
This means that an area’s special
features, such as its quality of life, will
be an important determinant of where
households and, ultimately, firms
locate.
Comparisons of the quality of
life across cities have generated a
fair amount of interest from workers,
the media, and local policymakers.

Beginning in the late 1970s, economists
introduced a methodology for determining the
value of an area’s special characteristics by
observing what people are willing to pay to live
there in terms of higher rents and lower wages.
Since 1981, David Savageau has
compiled the Places Rated Almanac.
A “places rated” index is used to
produce a ranking of cities. The
index is based on nine categories
of amenities: cost of living (mostly
housing costs); the economy (e.g.,
the risk of unemployment); climate;
education; health care (physicians
and hospitals); transportation (e.g.,
airline connections); safety; recreation;
and location (e.g., scenic beauty).
In constructing the index, David
Savageau uses his own judgment in
three ways. First, he uses his own
preferences to determine which items
to include in each of these categories.
Second, Savageau assigns points to
each of the nine categories. Finally, he
applies equal weights to the rankings
in each of the nine categories to
compute an index number reflecting

See my 2005 Business Review article for
further discussion of consumer agglomeration
economies.

12 Q3 2009 Business Review

the amenities offered in each city
(the places rated index). As Glenn
Blomquist has pointed out, “This
equal weighting means that a oneposition difference in climate is equally
important as a one-position difference
in the crime ranking.” Obviously, the
rankings of cities will be quite sensitive
to weights assigned to the various
characteristics. For example, I might
put more weight on the cost of living
in a city and much less weight on a

See my 2005 Business Review article.

city’s economy. This would almost
certainly result in a different ranking
of cities than one produced by equally
weighting the various categories of
quality of life.
Beginning in the late 1970s,
economists introduced a methodology
for determining the value of an area’s
special characteristics by observing
what people are willing to pay to
live there in terms of higher rents
and lower wages.4 Individuals who
choose to live in areas with a high
quality of life are willing to move to
these locations despite facing some
combination of higher housing prices
(or rents) and lower wages. This
combination of higher housing costs

See, for example, the articles by Jennifer
Roback; Glenn Blomquist, Mark Berger, and
John Hoehn; Joseph Gyourko and Joseph Tracy;
and David Albouy. See Glenn Blomquist’s 2007
article for an accessible review of the quality-oflife literature.

www.philadelphiafed.org

and lower wages is the premium, or
implicit price, that people must pay to
live in places with a high quality of life.
A comparison across metropolitan
areas is achieved using a quality-oflife index, or QOLI. The index is
constructed by first weighting each
amenity an area offers by its implicit
price. Next, the final index is produced
by summing all amenities. Finally, the
QOLI is used to rank cities by quality
of life. Notice that the weights for each
amenity in the index are based on
preferences as expressed by thousands
of consumers in local housing markets
and thousands of workers in local labor
markets and not on the preferences of
the person constructing the index, as is
the case for the Places Rated Almanac.
Many QOLIs have been constructed
for metropolitan areas in the United
States, and they show that quality of
life matters. There appear to be sizable
differences in the quality of life across
locations, and residents “pay” for these
differences through some combination
of higher rents and lower wages.
There are important shortcomings
with the calculations of what households are willing to pay for quality
of life and the associated rankings.
According to the quality-of-life view,
relatively higher wages are one way to
compensate workers for a lack of local
amenities (such as unpleasant weather,
relatively high crime rates, and pollution). One advantage of the qualityof-life approach is that it uses data
on individual workers and individual
households (called micro data). It is
easy to account for observable worker
characteristics, such as education, job
experience, occupation, and industry.
However, an important shortcoming
of this approach is that it is largely
impossible to account for the many intangible characteristics of workers (motivation, dedication, creativity, and so
on) that can make some workers more
productive even when they are com-

www.philadelphiafed.org

pared with other, very similar workers.
If these high-productivity workers are
disproportionately attracted to highamenity cities, the higher wages reflect
the relatively higher productivity of
these workers and not compensation
for a lack of amenities. Thus, the omission of the many intangible worker
characteristics may introduce a serious
bias when calculating quality-of-life

concern in that it ranks San Jose 88th
and San Francisco 105th out of the 185
cities they considered.
An additional limitation of the
quality-of-life approach is that it is
virtually impossible to include in
any study the vast variety of private
(such as restaurants) and public
leisure-oriented goods (pleasant
weather) that draw people to cities.

An additional limitation of the quality-of-life
approach is that it is virtually impossible
to include in any study the vast variety
of private and public leisure-oriented
goods that draw people to cities.
rankings. For example, suppose that
the hardest working and most creative
software engineers are attracted to
Silicon Valley in California because
they are more productive there, and
this greater productivity translates
into higher wages. In the qualityof-life calculations, these relatively
higher wages for otherwise similar
software engineers give San Jose and
San Francisco lower QOLIs than they
probably deserve.5 The ranking of
cities reported in the article by Glenn
Blomquist and co-authors supports this

In the article by Jordan Rappaport and the
one by David Albouy both authors point out
that ranking cities based on the QOLI often
produces rankings that are counter-intuitive.
For example, in the ranking of 185 U.S. cities in
the study by Glenn Blomquist and co-authors,
Pueblo, Colorado, ranks first, while San
Francisco ranks 105th and New York City ranks
216th. Recall that these indexes are calculated
using only local wages and local rents. David
Albouy goes a step further and also accounts for
federal taxes paid by local residents, nonhousing
costs, and nonlabor income to produce a QOLI
and finds that his city rankings are much closer
to people’s intuitive rankings.

Typically, researchers have chosen
the types of amenities (usually limited
to environmental amenities such as
weather) to include in their studies.
In addition to being subjective, the
set of amenities chosen will not be
comprehensive.
Measuring Quality of Life
Based on Leisure Tourism. Given
the shortcomings of the quality-of-life
approach, in our study, Albert Saiz and
I suggest a more encompassing measure
of the demand for urban amenities
that stems from a revealed preference
for these amenities as represented by
the number of leisure tourists who visit
a metropolitan area. Leisure tourists
are attracted by an area’s special traits,
such as its restaurants and its theater
but also by its unique ambiance,
architectural variety, pleasant public
spaces, or natural scenic beauty. We
point out that the special traits that
attract tourists to an area are some of
the very characteristics that attract
households to cities when they choose
these places as their permanent homes.
Since households are attracted to cities

Business Review Q3 2009 13

by many of the same traits that attract
tourists, the number of leisure tourists
can serve as a comprehensive measure,
or proxy, for consumer amenities
offered in cities. In our research, we
find a positive correlation between the
number of leisure tourist visits to cities
and subsequent economic growth.
But why should leisure-related
amenity levels be associated with
economic growth? Jesse Shapiro
has shown that “beautiful cities”
are especially attractive to highskill workers, who can stimulate
employment and population growth.
The idea is that high-skilled (highly
educated) individuals are not only
highly productive workers, but they
also enhance the productivity of other
workers they come into contact with.
Along these lines, Sanghoon Lee
notes that the demand for variety may
increase more than proportionately
with income and as high-skill
individuals account for a larger share
of the workforce in large cities.6
In our study, Saiz and I use
a new data set on leisure tourist
trips provided by D.K. Shifflet and
Associates, a firm specializing in
consulting and market research for
the travel industry. The Shifflet data
provide the destinations for individuals
who traveled for leisure purposes.7 The

6
Of course, highly educated workers might
move to relatively faster growing cities rather
than directly affecting city growth. Studies have
offered evidence that this is not the case (see,
for example, the study by Jesse Shapiro).
7
Shifflet defines travel as any overnight trip
or any day trip greater than 50 miles one way.
Households were asked to report on travel
destinations during the last three months.
Questionnaires were mailed to 180,000
households in 1992 (the year we use in our
study). Returned samples were demographically
re-balanced on five key measures (state
of origin, age, gender, household size, and
household income) to ensure that they are
representative of the U.S. population. Shifflet
provided leisure travel data for the top 200
tourist destinations for 1992.

14 Q3 2009 Business Review

table shows the 1992 destinations of
leisure tourists for selected cities. The
average cities drew almost 4.5 million
leisure tourists in 1992. Orlando and
Las Vegas are at the top of the list,
drawing 22.3 million and 18 million
tourists, respectively. In our study,
we excluded these two cities, since
tourism in these locations is related to
recreational resorts (Orlando) or the
gaming industry (Las Vegas), and these
activities are, at best, only weakly

Philadelphia ranked
20th overall, having
almost twice as many
tourists in 1992 as
did a typical city.

related to urban amenities that draw
residents.8 Many of the cities typically
thought to be high-amenity locations
(such as New York, San Diego, San
Francisco, and Los Angeles) rank in
the top 10 in terms of leisure tourist
visits in 1992. Philadelphia ranked
20th overall, having almost twice as
many tourists in 1992 as did a typical
city. At the other extreme, Oakland,
California, and Newark, New Jersey,
had the fewest leisure tourists (under
100,000 in 1992).
Since Saiz and I use leisure tourist
visits as a proxy for the quality of
life offered in cities, it’s important to
demonstrate that leisure tourist visits
are, in fact, positively correlated with

8
Albert Saiz and I show that our findings are
not sensitive to the inclusion or exclusion of the
Orlando and Las Vegas metropolitan areas from
our sample.

many variables thought to influence
the quality of life. We show that this
turns out to be the case. For example,
we find that leisure tourists tend to be
attracted to sunnier metro areas with
more colleges; lower poverty rates;
lower manufacturing employment;
greater average distances to hazardous
sites; accessibility to the ocean, parks,
and golf courses; and more historic
buildings.
Next, we look at the association
between leisure consumption
opportunities, proxied by the number
of leisure tourists, and population and
employment growth in metropolitan
areas during the 1990s. There is
indeed a positive correlation between
population growth in the 1990s and
the number of leisure tourist visits to
metropolitan areas in 1992 (see the
figure). Of course, many other things
could potentially account for this
positive correlation. For example, New
York City would be expected to have
more tourists than, say, Philadelphia,
since New York City has a much larger
population base to begin with; thus,
we control for city size. Since many
people are attracted to coastal cities
and to cities with pleasant weather,
we also control for whether a city is
within about 30 miles of an ocean or
a Great Lake, and we also account for
a city’s average January temperature
and for its relative humidity in July.
After controlling for a city’s coastal/
Great Lakes proximity, its climate, and
a variety of other factors that might
account for the positive correlation
between leisure visitors and growth
(such as the previous share of the
adult population with a college degree,
previous average income, and so forth),
Saiz and I find that population growth
during the 1990s was 2.2 percentage
points and employment growth was
2.6 percentage points higher in a
metropolitan area with twice as many
leisure visits as another metropolitan

www.philadelphiafed.org

TABLE
Tourist Destinations in 1992 for Selected Cities

Top 20 Destinations
Metropolitan Area
Orlando, FL

Bottom 20 Destinations
Number of
Visits in 1992
(millions)
22.3

Number of
Visits in 1992
(millions)

Metropolitan Area
Miami, FL

3.15

Las Vegas, NV-AZ

17.95

San Jose, CA

3.05

New York, NY

15.99

Charleston-North Charleston, SC

2.97

San Diego, CA

14.05

Toledo, OH

2.86

Los Angeles-Long Beach, CA

13.41

Fort Lauderdale, FL

2.72

Atlanta, GA

13.22

Chicago, IL

11.6

Wilmington-Newark, DE-MD

2.43

Grand Rapids-Muskegon-Holland, MI

2.39

Washington, DC-MD-VA-WV

11.32

Bakersfield, CA

2.13

San Francisco, CA

11.17

Allentown-Bethlehem-Easton, PA

2.08

Knoxville, TN

10.83

Baton Rouge, LA

2.06

Tampa-St. Petersburg-Clearwater, FL

10.56

Fort Worth-Arlington, TX

2.06

St. Louis, MO-IL

10.17

Fresno, CA

2.02

Houston, TX

9.58

Greenville-Spartanburg-Anderson, SC

1.55

Columbus, OH

9.42

Hartford, CT

1.52

Nashville, TN

9.42

Akron, OH

1.44

Norfolk-Virginia Beach-Newport
News, VA-NC

9.36

West Palm Beach-Boca Raton, FL

1.32

Tacoma, WA

1.14

San Antonio, TX

9.15

El Paso, TX

1.11

Dallas, TX

8.49

Oakland, CA

0.96

Indianapolis, IN

8.27

Newark, NJ

0.66

Philadelphia, PA-NJ

8.02
AVERAGE

4.42

Source: D.K. Shifflet and Associates

www.philadelphiafed.org

Business Review Q3 2009 15

have believed that consumption
amenities, especially those geared
to the enjoyment of leisure, were
becoming more important in
explaining urbanization and the
location of individuals. Until now,
urban economists were not able to
provide an estimate of the importance
of consumption amenities for city
growth. The main benefit of my study
with Albert Saiz is to provide such
an estimate. Using the number of
tourist visits to cities as a proxy for
the amenities offered in these cities,
Saiz and I found the predicted decadal
population growth rate would be
2.2 percentage points higher and its

FIGURE
Population Growth Increases with Tourism
Population Growth, 1990-2000
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-2.6

-1.6

-0.6

0.4

1.4

2.4

3.4

Log of Leisure Visits, 1992
Population Growth, 1990-2000

area.9 Among the things we considered
in our study, our leisure tourist
measure was the third most important
predictor of population growth in the
1990s. (The most important factor
for growth is prior immigration, and
the second most important factor is
previous changes in local tax revenue.)
As we have seen, economists
believe that more educated workers
tend to be disproportionately drawn
to cities offering a relatively high
quality of life. Saiz and I investigate
this point and find that growth in
the share of highly educated workers
is positively related to greater leisure
tourism in cities. We also find
evidence of acceleration in houseprice appreciation and rent growth in
metropolitan areas with more leisure
tourists. Specifically, we find that a
city with twice as many leisure tourists
as another city has a 0.3-percentagepoint increase in the growth rate of
the share of the population with at

16 Q3 2009 Business Review

Fitted Values

least a college education. Similarly,
a city with twice the level of leisure
tourists as another city has about a
2-percentage-point higher house-price
appreciation and a 1.3-percentagepoint higher rent growth. During the
1990s, the share of the population
with a college degree grew 4 percent
in the typical metropolitan area in our
sample, while house values grew 42
percent and rents, 31 percent. Based
on these estimates, in a city with twice
the previous level of leisure tourists
as another city, the share of the adult
population with a college education
would have increased 4.3 percent
instead of 4 percent during the 1990s,
while housing prices would have
appreciated 44 percent rather than 42
percent and rents would have grown
almost 32.3 percent as opposed to 31
percent.
CONCLUSION
For some time urban economists

9
No doubt tourism leads to growth, but to some
extent, growth (perhaps due to agglomeration
economies in production) helps finance cultural
and recreational amenities and the growth
of these amenities draws leisure tourists.
The difficulty lies in trying to differentiate
the extent to which tourism causes growth
or growth causes tourism. Saiz and I use an
approach (instrumental variables) that attempts
to break the reverse causality of growth on
tourism. We argue that historic places (such
as Independence Hall in Philadelphia) cause
tourism today, but tourism today is unlikely
to have caused historic places. Similarly, the
coastal share within a 10-km. radius (about six
miles) of an MSA’s boundary will cause tourism,
but not vice versa. That is, historic places
and access to the coast are highly correlated
with tourism (and therefore serve as good
instruments for tourism), but these instruments
are not caused by urban growth during the
period 1990-2000 we considered. We find
that reverse causation does not appear to be a
problem in interpreting our findings.
Another concern is that a metropolitan
area that is geographically close to other
population centers may disproportionately
draw leisure visitors relative to the amenities
they offer. For example, Philadelphia may
draw relatively more leisure tourists because
the city is somewhat close to New York City
and to Washington, D.C. People who visit New
York City or Washington, D.C. might also visit
Philadelphia, even though they might not have
if Philadelphia were not close to these other
cities. In our research, Saiz and I controlled for
the population potential of each city in our data
set, where the population potential of a city
measures how near people in all cities are to any
given city. We found essentially identical results
after controlling for the population potential of
cities compared with the results when we did
not control for population potential.

www.philadelphiafed.org

predicted decadal employment would
be 2.6 percentage points higher in
a city with twice the level of leisure
tourists as another city.
My study with Saiz provides
important implications for
policymakers who want to stimulate
local economic growth. First, we
find that consumer leisure amenities
do appear to positively enhance city
population and employment growth,
even after controlling for a city’s
natural advantages, such as its distance
to a coast and its climate. This is an
important finding because if people
were largely attracted by an area’s
natural advantages, these types of
amenities are not something local
policymakers can reproduce. However,
we find an association between growth
and amenities that policymakers can
affect.
Second, as policymakers think
about ways to stimulate local economic
growth, spending public funds on

leisure and cultural activities may
prove to be an avenue worth exploring.
This may explain why policymakers
and private investors are paying
increasing attention to providing
public goods oriented toward leisure,
such as museums, waterfront parks,
open-air shopping centers, and other
public spaces enjoyed by families
and individuals. Cities around the
world (such as Barcelona and Bilbao;
Glasgow; and Oklahoma City,
Camden, and San Antonio) have used
public investments in leisure spaces
and city beautification as a way to spur
economic growth.
An important issue is whether
some types of amenities are better at
stimulating growth than are other
types of amenities. While using the
number of tourist visits is a useful way
to summarize in a single number the
vast array of consumption amenities
offered by cities, it does not help in
addressing the question of which types

of leisure amenities stimulate growth
the most or if they even stimulate
growth at all. That is, my research
with Saiz does not allow us to tell the
extent to which having, say, clean
and safe streets affects city growth
as opposed to the effect on growth
of a city offering, say, waterfront
parks, open-air shopping centers,
and other public spaces. The answer
to the question about which types
of amenities affect growth the most
awaits future research. An additional
caveat is that the finding that leisure
amenities are associated with higher
local growth is not the same thing as
recommending that cities immediately
decide to fund activities that attract
tourists/residents if only because the
opportunity cost of appropriating
such funds is the elimination of other,
possibly more worthy, programs, such
as building new schools. BR

Costa, Dora L., and Matthew E. Kahn.
“Power Couples,” Quarterly Journal of
Economics, 115 (2000), pp. 1287-1315.

Savageau, David (with Ralph D’Agostino).
Places Rated Almanac. Foster City, CA:
IDG Books, 2000.

Florida, Richard. The Rise of the Creative
Class. Basic Books: New York, 2002.

Shapiro, Jesse M. “Smart Cities: Quality of
Life, Productivity, and the Growth Effects
of Human Capital,” Review of Economics
and Statistics, 88, 2006, pp. 324-35.

REFERENCES
Albouy, David. “Are Big Cities Really Bad
Places to Live? Improving Quality-of-life
Estimates across Cities,” University of
Michigan, mimeo, 2008.
Blomquist, Glenn, Mark Berger, and John
Hoehn. “New Estimates of the Quality of
Life in Urban Areas,” American Economic
Review, 78 (1988), pp. 89-107.
Blomquist, Glenn. “Measuring Quality
of Life,” in Richard Arnott and Daniel
McMillen, eds., A Companion to Urban
Economics, Oxford: Blackwell-Synergy
(2007), pp. 483-501.
Carlino, Gerald A., and Albert Saiz.
“City Beautiful,” Federal Reserve Bank
of Philadelphia, Working Paper 08-22
(September 2008).
Carlino, Gerald A. “The Economic Role
of Cities in the 21st Century,” Federal
Reserve Bank of Philadelphia Business
Review (Third Quarter 2005), pp. 9-15.
www.philadelphiafed.org

Gyourko, Joseph, and Joseph Tracy. “The
Structure of Local Public Finance and
the Quality of Life,” Journal of Political
Economy, 99 (1991), pp. 774-806.
Lee, Sanghoon. “Ability Sorting and
Consumer City,” unpublished manuscript,
University of Minnesota and Federal
Reserve Bank of Minneapolis (2004).

Waldfogel, Joel. “Who Benefits Whom
in Local Television Markets?” BrookingsWharton Papers on Urban Affairs (2003).
Waldfogel, Joel, and Lisa George. “Who
Affects Whom in Daily Newspaper
Markets?” Journal of Political Economy 111:4
(August 2003), pp. 765-84.

Rappaport, Jordan. “Consumption
Amenities and City Population Density,”
Regional Science and Urban Economics, 38
(2008), pp. 533-552.
Roback, Jennifer. “Wages, Rents and
the Quality of Life,” Journal of Political
Economy, 90 (1982), pp. 1257-78.
Business Review Q3 2009 17

Convertible Securities and
Venture Capital Finance*
BY YARON LEITNER

enture capital financing relies heavily on
convertible securities; the most common
type is convertible preferred stock. Venture
capital contracts also specify control rights
that describe who gets to make the firm’s decisions.
The recent literature has provided some theoretical
explanations for the use of these two features. Underlying
these explanations is the idea that individuals can take
actions that affect the firm’s performance but that these
actions cannot be specified in a contract. In this article,
Yaron Leitner focuses on venture capital contracts, but
the ideas presented can be applied to other contracting
problems in which individuals must be given incentives to
take appropriate actions.

Venture capital is a type of private
equity capital typically provided to
early-stage, high-potential-growth
companies that are not publicly traded.
By providing funds, the venture
capitalist hopes to eventually generate
a return through an event such as
an initial public offering (IPO) or
sale to another company. A contract
between a venture capitalist and an

entrepreneur has many special features;
for example, a venture capitalist
typically provides capital in stages and
can abandon the venture at any time.
The venture capitalist provides not
only capital but also advice on how to
manage the venture.1
Unlike debt, which characterizes
most bank financing, venture capital

Yaron Leitner
is a senior
economist in
the Research
Department of
the Philadelphia
Fed. This article
is available
free of charge
at www.
philadelphiafed.
org/research-and-data/publications/.

18 Q3 2009 Business Review

financing relies on equity-like and
convertible securities that provide
the venture capitalist with a share
of the profits (the upside). The most
commonly used security is convertible
preferred stock.2 Convertible preferred
stocks were used in 204 of the 213
real-world venture capital investment
contracts analyzed by Steven Kaplan
and Per Strömberg.3 Sometimes the
convertible preferred stock was used
in combination with other securities,
but in 170 financing rounds (almost 80
percent), convertible preferred stock
was the only security used.
Real-world venture capital
contracts also specify control rights
that clearly describe who gets to make
the firm’s decisions. These control
rights often depend on the firm’s
performance. The recent literature
has provided some theoretical
explanations for the extensive use of
convertible preferred stocks in venture
capital contracts and for the use of
contingent control rights. Underlying
these explanations is the idea that
individuals (the entrepreneur and the
venture capitalist) can take actions
that affect the firm’s performance but
that these actions cannot be specified
explicitly in a contract.
This article focuses on venture

An excellent, accessible account of what
venture capitalists do can be found in the
Business Review article by Mitchell Berlin. An
account of the history of venture capital can be
found in the introduction to the book by Paul
Gompers and Josh Lerner.

2
The government is now using this type of
security to recapitalize banks under the Capital
Assistance Program. For more details, see the
regulatory agencies’ joint press release from
February 23, 2009 at http://www.federalreserve.
gov/newsevents/press/bcreg/20090223a.htm.

*The views expressed here are those of the
author and do not necessarily represent
the views of the Federal Reserve Bank of
Philadelphia or the Federal Reserve System.

3
Their sample largely reflects financing rounds
completed between 1996 and early 1999
(166 cases). Of the remaining cases, 34 were
completed between 1992 and 1995 and 13 were
completed before 1992.

www.philadelphiafed.org

capital contracts, but the ideas
presented here can be applied to
other contracting problems in which
individuals must be given incentives to
take appropriate actions.
After explaining what a convertible preferred stock is, we will describe
some of the theoretical explanations
and some empirical facts.
WHAT IS A CONVERTIBLE
SECURITY?
In exchange for putting money
into a firm, a venture capitalist
usually receives convertible preferred
stocks. Because these are complicated
securities, I will first explain what
preferred stock is and then explain what
convertible preferred stock is.
Preferred stock has some features
that resemble debt, but legally, it is
an equity security. As with a debt
contract, the company needs to
make fixed payments (dividends) to
the holder of the preferred security.
But unlike with debt, the company
can choose not to pay the dividends
without being considered in default of
the contract.4 Preferred stock is called
preferred because the company cannot
pay dividends on its common stock
unless it has paid them to preferred
stockholders. Debt holders, however,
must be paid before any preferred
stockholder gets paid. Unlike preferred
stockholders in many other settings,
venture capitalists who hold preferred
stock usually have voting rights. In
addition, venture capitalists usually
have a right of redemption, which
means that they can cash out their
shares at some predetermined price
whenever they want to.
Convertible preferred stocks are
preferred stocks that give the holder

In addition, dividends received from preferred
stock have different tax implications from
interest collected on debt.

www.philadelphiafed.org

the right (or option) to convert his or
her shares into a pre-specified number
of shares of common stock. Venture
capitalists who hold convertible stock
will exercise this option only if they
expect to receive more money by doing
so, for example, if the stock price is
very high relative to the conversion
price. Thus, convertible preferred stock
provides venture capitalists with some
protection if the business does not

use “effort” to describe actions or
decisions that involve time and work
but that increase the probability
of higher profits. For example,
in a biotechnology start-up, the
entrepreneur, who has scientific skills,
puts effort into developing a new drug
by reading scientific material and
conducting laboratory experiments,
while the venture capitalist, who has
managerial skills, puts effort into

Preferred stock has some features that
resemble debt, but legally, it is an
equity security.
do well (in this case, the fact that it
is preferred allows venture capitalists
to take priority over common
stockholders in payments) while the
conversion feature allows them to
share the upside.
A convertible bond is another
example of a convertible security.
This is a bond that can be converted
into shares of common stock. While
convertible bonds are sometimes
used by other firms, they are not very
common in venture capital finance.5
(See Who Issues Convertible Securities?)
CONVERTIBLE SECURITIES
CAN ALIGN INCENTIVES
Venture capitalists are usually
very active in managing and providing
advice to the firms they finance.
The firm’s success depends on the
venture capitalist’s effort as well as
on the entrepreneur’s. Economists

Convertible debt was used in only one out
of the 213 cases that Kaplan and Strömberg
analyzed. Convertible zero-coupon debt was
used in eight cases. A zero-coupon debt is a
bond that does not make periodic interest
payments. It pays only the principal at the
expiration date. A convertible zero-coupon debt
is a zero-coupon debt that can be converted into
shares of common stock.

marketing the drug by conducting
market research to find out who is
likely to use it. Clearly, earnings and
profits depend not only on effort but
also on some other factors that are
beyond the firm’s control, such as
overall economic conditions or what
a competitor does. Nevertheless, the
underlying assumption is that when
one exerts more effort, the firm is more
likely to generate more profits. The
firm may still end up with low profits,
but the chances for low profits are
reduced when more effort is exerted.
Since exerting effort is costly, the
entrepreneur and venture capitalist
will do so only if they are provided
with the right incentives. Ideally, this
could be done via a contract that
specifies the level of effort that each
one should make and the punishment
for shirking. For example, someone
who does not exert the appropriate
amount of effort should be paid less (or
not be paid at all).
The problem with such a contract
is that it is often impossible to observe
or measure precisely how much effort
someone exerts. For example, it may
be hard to determine whether the
scientist has used intelligence and
creativity in developing the drug or

Business Review Q3 2009 19

conducted the “right” experiments.
Thus, a court may not be able to
enforce the ideal contract described
above. However, a court may be able
to enforce a contract that depends
on some observable outcomes, such
as earnings before interest and tax
(EBIT). A contract between an
entrepreneur and venture capitalist
can therefore depend on EBIT, but it
cannot depend on effort directly.
The issue then is how to share
the project’s earnings between
the entrepreneur and the venture
capitalist so that each one will have
the incentive to put the appropriate
amount of effort into the project.
Intuitively, one will exert more effort
when one has more at stake. If you are
the sole owner of the firm and do not
need to share the profits with anyone,
you will exert as much effort as you
can, up to the point at which the extra
effort no longer increases profits (net
of the cost of exerting effort). However,
if you need to share the profits with
someone else, you will be less willing to
exert effort, and you will do so only up
to the point at which the extra effort
increases your share of the profits.
The optimal split of profits
between the entrepreneur and the
venture capitalist is the one that
induces efforts that generate the
highest total profits (net of the cost
of putting forth effort). Suppose, for
example, that the optimal split is 5050; that is, the entrepreneur and the
venture capitalist each have 50 percent
of common stock, giving each a claim
on 50 percent of the firm’s profits. This
is how the entrepreneur and venture
capitalist would split the profits if
there were no other issues involved.
In other words, if providing incentives
to exert effort is the only concern, we
can induce the optimal level of effort
by giving the entrepreneur and the
venture capitalist shares of common
stock according to the optimal split.

20 Q3 2009 Business Review

Who Issues Convertible Securities?

homas Noddings, Susan Christoph, and John Noddings
analyzed U.S. convertible bonds and U.S. convertible preferred
stocks trading in January 2000.a Their data do not include
firms that rely on venture capital financing, since those firms
are not publicly traded.
They found that companies that issue convertible bonds span a broad
market spectrum from very small-cap to very large-cap firms, but the majority
of issues represented micro-sized to small-sized growth companies with
ratings below investment grade. A total of 311 companies had actively traded
convertible bonds. Of these companies, 26 percent were in what the authors
defined as the micro-cap category (market capitalization below $225 million),
32 percent were in the small-cap category (market capitalization between $225
million and $1.25 billion), 27 percent were in the medium-cap category (market
capitalization ranging from $1.25 billion to $10.5 billion), and the remaining 15
percent were large-cap companies (market capitalization above $10.5 billion).b
Only 21 percent of the firms had a Standard & Poor’s bond rating of BBB and
above. Noddings, Christoph, and Noddings note that the 230 small-cap and
larger companies (i.e., the small, medium, and large) were among the 3,000
largest U.S. firms, and that while there was a slight overlap with the largest
3,000 firms, most of the 81 micro-cap companies came from the 1,000 firms
just below the top 3,000. This gives us some idea of the fraction of public firms
with actively traded convertible bonds (roughly 8 percent).
Like convertible bonds, most convertible preferred stocks were issued by
small to mid-sized companies. Out of the 117 companies with actively traded
convertible preferred stocks, 15 percent were in the micro-cap category (defined
above), 32 percent were small cap, 39 percent were medium cap, and 14 percent
were large cap. Only 13 percent had a Standard & Poor’s preferred stock rating
of BBB and above.

a
The first edition of their book covers January 1998. Even though the numbers are not identical
in both editions, the results are essentially the same.
b

There are no precise definitions for small, medium, and large market cap. In addition, these
definitions can change over time. I use the definitions in Noddings, Christoph, and Noddings’
study.

Another issue, however, is
that venture capitalists need to be
compensated not only for the effort
they exert but also for the money
they invest in the venture. Venture
capitalists will agree to invest in the
firm only if they expect to make a
profit; more precisely, the expected

return on the investment, adjusted
for risk, needs to be at least as high
as what the venture capitalists could
obtain by investing their money
elsewhere. If the investment is
very large relative to the size of the
company, a venture capitalist may
insist on a split of, say, 60-40, where he

www.philadelphiafed.org

or she gets 60 percent of equity instead
of only 50 percent. However, compared
with the optimal split of 50-50
assumed above, a 60-40 split distorts
incentives, inducing the entrepreneur
to exert too little effort. The use of
convertible securities can help ensure
that a venture capitalist gets enough
cash to cover the initial investment
while at the same time maintaining
incentives.
The idea is as follows: Suppose
that profits can be either $100 million
(good state) or $40 million (bad state),
and the entrepreneur can either exert
effort or not. The entrepreneur’s
effort increases the likelihood of the
good state and reduces the likelihood
of the bad state. The entrepreneur
will exert effort only if the payoff he
receives in the good state is large
enough compared to what he gets in
the bad state. With a 50-50 split, the
entrepreneur obtains $50 million in
the good state and $20 million in the
bad state, and as assumed here, this
induces him to exert effort. However,
we can also induce effort by giving
the entrepreneur less in both states; for
example, we can give the entrepreneur
$30 million in the good state and
nothing in the bad state. In this case,
more is left to the venture capitalist,
and the venture capitalist can cover
his investment. This profit allocation
can be implemented by giving the
entrepreneur shares of common stock
and by giving the venture capitalist
shares of convertible preferred stock.
The preferred stock ensures that
the venture capitalist has priority
in payment in the bad state (in our
example, he receives everything), and
the convertibility option allows the
venture capitalist to share the upside.
For more details, see An Example of
Venture Capital Financing on pages 22
and 23, as well as the table on page 24.
The detailed numerical example
illustrates two more things: First,

www.philadelphiafed.org

the need for convertible preferred
stock arises only when the required
investment from the venture capitalist
is large. Otherwise, the two objectives
(inducing effort and allowing the
venture capitalist to cover his
investment) can be achieved by simply
giving the venture capitalist shares of
common stock, which is equivalent
to simply sharing the profits of the
firm. This seems consistent with the
observation that “angel investors,” who
invest smaller amounts than venture

CONVERTIBLE PREFERRED
STOCK CAN PREVENT
WINDOW DRESSING
A striking feature of venture
capital finance is that the venture
capitalist typically infuses capital in
stages, which are usually related to
significant milestones in the development process. Such stages, for example,
might be completion of the design, the
pilot production, the first date the firm
makes a profit, or the introduction
of a second product. At each stage,

A striking feature of venture capital
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milestones in the development process.
capitalists, are more likely to obtain
common stock. See, for example, the
paper by Andrew Wong.6 Second, in
some cases (for example, when the
required investment is very large and
the entrepreneur has no funds of his
own), we may not achieve the two
objectives above even with convertible
preferred stock. In this case, it might
not be possible to finance the venture
at all, or the entrepreneur might need
to wait until he has amassed enough
capital of his own.7

6
An angel investor is a high-net-worth
individual who typically invests in small private
firms, on his own account. (In contrast, venture
capitalists invest funds received from other
individuals.) Formally, angel investors are
“accredited investors,” according to the SEC.
The SEC rule 501 of Regulation D states that
an accredited investor is an individual who
has a net worth that exceeds $1 million or an
expected yearly income of more than $200,000
($300,000 including spouse).
7
For more detailed models, read the paper by
Catherine Casamatta and the paper by Rafael
Repullo and Javier Suarez.

the firm is given just enough cash to
reach the next stage, and the venture
capitalist retains the option to abandon the venture if performance is not
satisfactory.
The threat to abandon the venture may induce the entrepreneur to
put more effort into making the venture a success. This is good, of course,
but it also introduces the potential for
“window dressing.” The entrepreneur
might manipulate short-term performance signals upward to fool the
venture capitalist into continuing to
finance the project. For example, the
entrepreneur might engage in activities that boost short-term earnings but
reduce long-term earnings. Or the entrepreneur might produce a prototype
that looks functional (and so meets the
requirements of the current stage) but
is in fact too costly to put into mass
production. Window dressing reduces
the benefit of stage financing because
the venture capitalist bases decisions
on “noisy” or incorrect information

Business Review Q3 2009 21

An Example of Venture Capital Financing

exter, a young genius, has finally
decided to have his own start-up. He
has an idea about how to develop a
drug that allows cartoon characters to
become humans and vice versa. Dexter
has no cash of his own, and he hopes to raise the required investment of $45 million from his old neighbor,
Mandark, who now has his own venture capital firm.
Assume that there are two states: A good state,
where profits are $100 million, and a bad state, where
profits are $40 million. Dexter and Mandark can either
exert effort or not. Exerting effort raises the probability
of the good state and lowers the probability of the bad
state: If both Dexter and Mandark exert effort, the
probability of each state is 50 percent. If either of them
does not exert effort, the probability of the good state
falls to 25 percent, and the probability of the bad state
rises to 75 percent.
But Dexter and Mandark bear a cost for exerting
effort. Think of this as profits each forgoes by putting
effort into the venture rather than into other projects.
Assume that the cost of exerting effort (per individual)
is $7.5 million.
Let’s suppose that Dexter and Mandark share
profits between them. The question is how to design a
contract between Dexter (the entrepreneur) and Mandark (the venture capitalist) so that (i) each will have
the incentive to exert effort (more precisely, we want to
make sure that if one exerts effort, the other one cannot gain by not exerting effort);a and (ii) Mandark (who

supplies the funds) will at least break even.
Consider first an even split; that is, Dexter and
Mandark write a contract according to which they split
the profits equally, so that each one gets $20 million in
the bad state and $50 million in the good state. Is this
enough to induce effort? Yes. If Dexter exerts effort,
Mandark cannot gain by not exerting effort. To see
this, note that Mandark’s expected return from exerting effort equals (0.50×20)+ (0.50×50) - 7.5=27.5,
and his return from not exerting effort is the same
((0.75×20)+(0.25×50)=27.5). Similarly, if Mandark
exerts effort, Dexter cannot gain by not exerting effort.
The problem with this split is that Mandark does
not receive enough to cover his initial investment of
$45 million. Knowing this, Mandark will not invest to
begin with.
We might think that the solution is to give Mandark a larger share of the project’s profits, so that he
can cover his initial investment. The problem is that by
reducing Dexter’s share, we eliminate his incentives to
exert effort. For example, if Mandark gets 75 percent
of the profits and Dexter gets 25 percent, Dexter ends
up with $10 million in the bad state and $25 million in
the good state, so he has no incentive to exert effort.
(If he exerts effort, he obtains (0.50×10)+ (0.50×25)
- 7.5=10; if he does not exert effort, he obtains
(0.75×10)+ (0.25×25)=13.75.)
Instead, one solution is a contract that gives
Dexter nothing in the bad state and $30 million in the
good state, while giving Mandark $40 million in the

This is what economists refer to as a Nash equilibrium.

rather than on correct information. In
extreme cases, the possibility of window dressing may cause the venture
capitalist to decide not to finance the
venture to begin with.
In their article, Francesca Cornelli
and Oved Yosha show that properly
designed convertible preferred equity
can overcome window dressing. How
can such a security resolve the problem? Cornelli and Yosha show that the

22 Q3 2009 Business Review

convertibility option is the answer.
Cornelli and Yosha assume that
the venture capitalist must choose
whether to convert his preferred stock
to common stock after he sees the
results of the first financing stage
but before he sees final profits. This
means that the decision to convert
must be based on the venture’s interim
performance. The venture capitalist
will choose to exercise the conversion

options only if profits are likely to be
high, based on the venture’s interim
performance. Window dressing,
because it makes interim performance
look better, increases the likelihood
that the venture capitalist will convert
his or her preferred stock to common
stock. But conversion is a very undesirable outcome for the entrepreneur. In
particular, if the conversion price is
set low, the venture capitalist obtains

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An Example of Venture Capital Financing...continued
bad state and $70 million in the good state.b This is
feasible because Mandark expects to get $55 million,
on average, which is more than his initial investment
plus his effort cost.c It also induces both Dexter and
Mandark to exert effort (as shown in possibility 3 in the
table).
This last contract is more than pure profit sharing, since Dexter receives a positive share of the profits
in the good state, but nothing in the bad state, even
though the project generates $40 million. Such a
contract can be implemented by giving Dexter shares
of common stock and by giving Mandark shares of
convertible preferred stock. Specifically, Dexter gets 30
shares of common stock, and Mandark gets 70 shares
of convertible preferred stock that has a total promised
payment of $40 million (if not converted) and that can
be converted into 70 shares of common stock. If the
bad state happens, Mandark will not exercise the option to convert and will obtain the promised payment

of $40 million, which is everything the firm has. If
instead Mandark chose to convert the preferred shares,
he would obtain only 70 percent of the profits (because
he has 70 shares and Dexter has 30), which is less than
$40 million. In contrast, if the good state happens,
Mandark will exercise the conversion option and, by
doing so, obtain $70 million (since he will then own 70
percent of the firm’s shares, and the firm is worth $100
million as a whole). This is clearly better than not converting and receiving $40 million instead. (The table
provides a summary.)
Finally, note that if Mandark needs to invest $27.5
million or less, the two objectives (inducing effort
and allowing Mandark to cover his investment) can
be achieved even with an equal share (first possibility
in the table). In contrast, if Mandark needs to invest
more than $47.5 million, even the use of convertible
preferred stock (third possibility in the table) does not
achieve the two goals.

b
This is not the only possibility. For example, giving Dexter $1 million in the low state and $31 million in the high state, while giving Mandark $39
million and $69 million, can also work.
c

To simplify, I assumed here that the discount rate (i.e., the expected return Mandark can obtain by investing his money in other ventures with
similar risk) is 0 percent. With a positive discount rate, Mandark would need to get more. For example, if the discount rate is 5 percent, Mandark
would require an expected payoff of $54.75 million (= (45×1.05) + 7.5). The solution presented in this example still works in this case.

many shares of stock by choosing to
convert preferred stock to common
stock, and the entrepreneur ends up
owning a substantially smaller portion
of the venture. To prevent this from
happening, the entrepreneur will not
engage in window dressing in the first
place.
Putting it differently, the
entrepreneur faces a tradeoff: Window
dressing increases the probability
that the venture will continue to
be financed but also increases the
probability that the venture capitalist
will use the conversion option to
acquire a substantial portion of the
firm’s equity. Setting the conversion
price low makes the second scenario,

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in which the venture capitalist uses the
conversion option, very undesirable for
the entrepreneur, and this induces the
entrepreneur to refrain from window
dressing in the first place.8
8
The assumption that the venture capitalist
must decide whether to exercise the conversion
option after seeing the results of the first stage
but before seeing the final results (i.e., before
learning about the long-term performance of
the venture) is crucial. Otherwise, the venture
capitalist will not convert upon seeing a good
interim signal and instead will wait to obtain
more precise information. This is a drawback
of the model because in reality convertible
preferred stock typically does not have such
a pre-specified deadline for conversion. The
venture capitalist usually converts only upon
exiting the investment, i.e., when the venture
is sold to an acquirer or when the venture goes
public in an initial public offering.

CONVERTIBLE SECURITIES
AND EXIT DECISIONS
Now let’s consider the exit
decision and the contract between
the venture capitalist and the
entrepreneur. The exit decision refers
to the terms on which the venture
capitalist can cash out his or her
investment, pay the investors, and
move on to the next prospect. A
moderately successful investment
usually leads to a sale to another firm,
while an exceptionally successful
investment leads to an initial public
offering (IPO), in which the firm
issues common stock to the general
public. For example, Apple, Google,
Intel, Microsoft, and Yahoo, which are

Business Review Q3 2009 23

TABLE
An Example of Venture Capital Financing
Possibility 1

Total profits
Dexter’s payoff
Mandark’s payoff

Good
state
100

Bad
state
40

50
50

20
20

Possibility 2
On
average*
70
35
35

Possibility 3

Good
state
100

Bad
state
40

On
average*
70

Good
state
100

25
75

10
30

17.5
52.5

30
70

Bad
state
40

On
average*
70

0
40

15
55

On average, does
Mandark cover his initial
investment plus the cost
of effort?*

No
(35 < 45 +7.5)

Yes
(52.5 = 45 +7.5)

Yes
(55 > 45 + 7.5)

If Mandark exerts effort,
can Dexter gain by not
exerting effort?

No
If Dexter exerts effort, he
receives 35-7.5 = 27.5.
Otherwise, he receives
(0.25×50) + (0.75×20)
=27.5.

Yes
If Dexter exerts effort, he
receives 17.5-7.5 = 10.
Otherwise, he receives
(0.25×25) + (0.75×10)
=13.75.

No
If Dexter exerts effort, he
receives 15-7.5 = 7.5.
Otherwise, he receives
(0.25×30) + (0.75×0) =7.5.

If Dexter exerts effort,
can Mandark gain by not
exerting effort?

No
If Mandark exerts effort, he
receives 35-7.5 = 27.5.
Otherwise, he receives
(0.25×50) + (0.75×20)
=27.5.

No
If Mandark exerts effort, he
receives 52.5-7.5 = 45
Otherwise, he receives
(0.25×75) + (0.75×30)
=41.25.

No
If Mandark exerts effort, he
receives 55-7.5 = 47.5.
Otherwise, he receives
(0.25×70) + (0.75×40)
=47.5.

Implementation

Dexter and Mandark each
get 50 shares of common
stock.

Dexter gets 25 shares
of common stock, and
Mandark gets 75 shares of
common stock.

Dexter gets 30 shares
of common stock, and
Mandark gets 70 shares of
convertible preferred stock,
which can be converted into
70 shares of common stock,
and which have a total
promised payment of $40
million.

*If both Dexter and Mandark exert effort
The table illustrates three ways to split profits between Dexter (the entrepreneur) and Mandark (the venture capitalist). Total profits are either $100
million (good state) or $40 million (bad state). If both Dexter and Mandark exert effort, the probability of each state is 50 percent. If either of them
does not exert effort, the probability of the good state falls to 25 percent and the probability of the bad state rises to 75 percent. The cost of effort
is $7.5 million per individual. Mandark needs to cover his initial investment of $45 million plus the cost of effort. In addition, both Mandark and
Dexter must be induced to exert effort. For simplicity, the discount rate is assumed to be 0 percent. The table shows that possibility 3 achieves the
two goals, but possibilities 1 and 2 violate one of them. All numbers represent millions of dollars.

24 Q3 2009 Business Review

www.philadelphiafed.org

now publicly traded, initially received
venture capital.
The two types of exit decisions
create new contracting opportunities for the venture capitalist and the
entrepreneur: They can now allocate
profits differently, depending on
whether the firm is sold to another
firm or goes public. This additional
flexibility can make it easier to achieve
the two objectives: providing incentives to exert effort and making sure
that the venture capitalist breaks
even. Indeed, real world contracts
often incorporate the exit decision. In
many cases, the convertible preferred
stock automatically converts to common stock in an IPO, but it does not
automatically convert when the firm
is purchased by another firm; Kaplan
and Strömberg show that an automatic
conversion provision was present in 95
percent of the financing rounds they
studied. In almost all cases, automatic
conversion was related to an IPO.9
Thomas Hellmann provides a
model that explains this automatic
conversion clause. In his model, the
entrepreneur and the venture capitalist learn about the potential profitability of the venture. Then they need
to make an exit decision. They can
either sell the venture to an acquirer
or remain independent, hoping to go
public (in an IPO) later. Remaining
independent is risky: The venture can
succeed and obtain a high IPO price
(the IPO value for existing shareholders could be $1 billion), but it can also
fail and yield no profits.10 In contrast,

9
The convertible preferred shares currently
being used to recapitalize banks also have a
mandatory conversion feature.

if the venture is sold, say, at $600
million, the venture capitalist and the
entrepreneur end up with a guaranteed
payoff that is high but not as high as
what they would get if they remained
independent and the venture turned
out to be a huge success.
The two types of exit decisions
have very different implications for
continuing effort by the venture
capitalist and the entrepreneur
(i.e., the effort they need to exert
after learning about the potential
profitability of the venture and making
an exit decision). If the venture

A moderately successful investment usually
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exceptionally successful investment leads to
CP KPKVKCN RWDNKE QHHGTKPI
+21 KP YJKEJ VJG ſTO
issues common stock to the general public.
remains independent, the entrepreneur
and the venture capitalist need to
exert effort in order to increase the
probability of a success before going
public. However, if the venture is sold,
their efforts are no longer needed.
Thus, a contract must provide the
entrepreneur and venture capitalist
with incentives to exert effort only if
the venture remains independent but
not if it is acquired by another firm.11
Remember that the contract also
needs to make sure that the venture
capitalist is compensated for his or
her initial investment. In the example
above, we showed that this can be
done by giving the venture capitalist
convertible preferred stock. But we

In the survey by William Sahlman, 34.5
percent of the capital invested resulted in a loss
(11.5 percent resulted in total loss, and 23.0
percent resulted in partial loss). The data he
used covered investments by 13 venture-capital
partnerships in 383 companies from 1969 to
1985.

www.philadelphiafed.org

also showed that when the required
investment by the venture capitalist
is very large, we could not achieve
the two objectives simultaneously.
(The problem was that if we gave the
venture capitalist a big enough share
of the profits to cover his investment,
we hurt the entrepreneur’s incentives
to exert effort.) Contracting on the
exit decision can help us achieve the
two objectives. In particular, we can
give the venture capitalist a higher
share of profits only if the firm is sold
to another firm (in which case the
entrepreneur’s effort is not important),

Note that we are dealing here only with
the efforts that must be exerted after the
exit decision has been made. In his article,
Hellmann also deals with the effort that
must be made in the first stage before the exit
decision is made.

while maintaining the optimal split of
profits (inducing both to exert effort) if
the venture remains independent. For
example, if the firm is sold to another
firm, the venture capitalist can obtain
everything ($600 million), whereas
if the firm remains independent, the
venture capitalist and the entrepreneur
can split profits equally to induce
optimal effort levels.12
Note that in the profit allocation
above, the venture capitalist receives
more if the value is realized through
an acquisition rather than an IPO.

In the first numerical example in this article,
there was more than one way to induce optimal
levels of efforts because we could decide how
to split profits in the high state as well as in
the low state. Here if the venture remains
independent there are also two states (failure,
success), but because there are no profits if the
venture fails, we can only split profits if the
venture has an IPO. The only way to do it and
maintain the optimal level of effort is equal
shares.

Business Review Q3 2009 25

He or she obtains $600 million in
the first case but only $500 million
(which is half of the IPO value) in the
second case. This is done to increase
the amount of money that the venture
capitalist obtains as much as possible
(so that he or she is willing to put out
more money upfront) while at the
same time inducing the entrepreneur
and venture capitalist to exert the
optimal level of effort needed for a
successful IPO.13 This allocation of
profits can be achieved by giving the
entrepreneur 50 shares of stock and
giving the venture capitalist 50 shares
of convertible preferred stock that
have a total promised payment of $600
million and that can be converted into
50 shares of common stock. For this to
work the convertible preferred stock
must have an automatic conversion
clause. Otherwise, the venture
capitalist will not convert the preferred
stock voluntarily when the firm makes
an IPO.14
CONTROL RIGHTS
The discussion so far has been
about cash flow rights: i.e., who has
the right to obtain the venture’s
profits? Hellmann’s model provides
insights not only about cash flow rights
but also about control rights; i.e., who

13
The fact that the venture capitalist receives
more in an acquisition compared to an IPO is
counterfactual. However, it is not necessary
for the main idea to hold. To see why, consider
the case in which we don’t know exactly at
what price the firm will be sold, and we want
the venture capitalist to obtain $300 million
plus 50 percent of the remaining sale profits
(so the entrepreneur gets the other half of the
remaining profits). For example, if the firm is
sold for $600 million, the venture capitalist gets
$450 million, and the entrepreneur gets $150
million. This can be implemented by giving
participating preferred stock to the venture
capitalist (as explained in the next footnote)
that automatically converts to common stock
in an IPO. Automatic conversion is necessary
because without it, the venture capitalist
would get $300 million plus 50 percent of the
remaining $700 million, which is more than
$500 million, so he will not want to convert.

26 Q3 2009 Business Review

gets to make the venture’s decisions?
In particular, Hellmann focuses on the
exit decision, showing that the firm’s
performance determines who gets to
make the exit decision. According to
his model, the entrepreneur should
obtain control when the potential

Control rights are
important because
the entrepreneur and
the venture capitalist,
who hold different
securities, may have
different preferences
regarding the exit
decision to be made.
profitability of the venture is high,
and the venture capitalist should
obtain control otherwise. This is
consistent with the empirical evidence
presented in the article by Kaplan

If the venture capitalist converts preferred
stock to common stock, he or she ends up with
$500 million because the venture capitalist
and the entrepreneur each have 50 shares of
stock. If the venture capitalist does not convert
preferred stock to common stock, he or she
ends up with $600 million, but this does not
implement the profit allocation wanted. In the
real world, there is an extensive use of a variant
of convertible preferred stock called participating
preferred. This type of security was used in 38.5
percent of the cases in the sample of Kaplan
and Strömberg. Participating preferred stock
can be thought of as a position of two securities:
preferred stock and straight common stock.
Upon exit, the holder of the participating
preferred stock (the venture capitalist) obtains
the promised dividend (just like preferred
equity) but also obtains dividends as if the
security had been converted to common stock.
The venture capitalist will never want to
convert his or her security to common stock;
a venture capitalist who does so gives up the
preferred stock and ends up with only common
stock. Automatic conversion is therefore
necessary.

and Strömberg. For example, they
show that the venture capitalist may
contractually obtain control from the
entrepreneur when EBIT falls below a
mutually agreed upon amount.15
Control rights are important
because the entrepreneur and the
venture capitalist, who hold different
securities, may have different
perferences regarding the exit decision
to be made. We have already seen
that given the profit allocation in the
previous section, the venture capitalist
always prefers to sell the firm rather
than have an IPO. However, this may
not be the right decision from the
firm’s point of view (it may not be the
decision that maximizes total profits).
For example, if the probability of a
successful IPO is 70 percent, it is better
to remain independent and attempt
a successful IPO because 0.7 × $1
billion is greater than $600 million.
The entrepreneur will be happy with
this decision (as he or she receives
nothing if the firm is sold, but $500
million if the IPO is successful), but
the venture capitalist will not.
But this does not mean that
we should give the entrepreneur
full control. In particular, suppose
the entrepreneur and the venture
capitalist learn that the probability of
a successful IPO is only 50 percent.
The right decision in this case is to
sell the firm because $600 million >
0.5×$1 billion. The venture capitalist
gets paid $600 million and so will be
happy with this decision. However,
the entrepreneur will prefer to take

15
They also showed that a state-contingent
board provision (i.e., the venture capitalist
gets control of the board in the bad state)
was present in 18 percent of the cases in their
sample and that state-contingent voting rights
(i.e., the percentage of votes that investors and
management have to affect corporate decisions)
were present in 18 percent of all financing
rounds and 25 percent of first financing rounds.

www.philadelphiafed.org

the risk of remaining independent. If
they sell the firm, the entrepreneur
gets nothing, whereas if they remain
independent and the venture succeeds,
he or she can get $500 million.
So how can we make sure that the
right decision is made? In the example
above, the entrepreneur should
obtain control if the probability of a
successful IPO is high (70 percent),
and the venture capitalist should
obtain control if the probability of a
successful IPO is low (50 percent).
More generally,the entrepreneur
should obtain control if the expected
proceeds from an IPO are high (either
because of a high probability of success
or because of a high IPO price), and
the venture capitalist should obtain

control if the expected proceeds from
an IPO are low. In the real world,
such contingent control rights can be
implemented, for example, by stating
in the contract that the venture
capitalist obtains control if EBIT falls
below some pre-specified level, which
might indicate a low probability of a
successful IPO.
SUMMARY
Convertible securities (in
particular, convertible preferred stock)
are widely used in venture capital
financing. Convertible securities can
help align incentives so that both
the entrepreneur and the venture
capitalist exert the appropriate levels of
effort to ensure the business’ssuccess.

Convertible securities can also prevent
window dressing, so that the venture
capitalist can provide financing in
stages based on performance without
worrying that the entrepreneur will try
to make things look better than they
really are.
The convertible securities used
in venture capital financing have
many unique features. For example,
an automatic conversion when the
firm makes an IPO can increase the
amount of money the entrepreneur
can raise from the venture
capitalist without compromising the
incentives necessary to put effort
into the venture. We also saw that
appropriately designed control rights
can ensure optimal exit decisions. BR

Berlin, Mitchell. “That Thing Venture
Capitalists Do,” Federal Reserve Bank of
Philadelphia Business
Review
(January/
February 1998), pp. 15-26.

Hellmann, Thomas. “IPOs, Acquisitions,
and the Use of Convertible Securities
in Venture Capital,” Journal Financial
of
Economics, (2006), pp. 649-79.
81

Repullo, Rafael, and Javier Suarez.
“Venture Capital Finance: A Security
Design Approach,” Review Finance8
of
,
(2004), pp. 75-108.

Casamatta, Catherine. “Financing and
Advising: Optimal Financial Contracts
with Venture Capitalists,” Journal
of
Finance58 (2003), pp. 2059-85.
,

Kaplan, Steven N., and Per Strömberg.
“Financial Contracting Theory Meets
the Real World: An Empirical Analysis
of Venture Capital Contracts,” Review
of
Economic
Studies70 (2003), pp. 281-315.
,

Sahlman, William A. “The Structure
and Governance of Venture-Capital
Organizations,” Journal Financial
of
Economics, (1990), pp. 473-521.
27

REFERENCES

Cornelli, Francesca, and Oved Yosha.
“Stage Financing and the Role of
Convertible Securities,” Review Economic
of
Studies70 (2003), pp. 1-32.
,
Gompers, Paul, and Josh Lerner. The
Venture
CapitalCycle Second Edition.
,
Cambridge: MIT Press, 2004.

www.philadelphiafed.org

Noddings, Thomas C., Susan C.
Christoph, and John G. Noddings. The
International
Handbook Convertible
of
Securities: GlobalGuideto theConvertible
A
Market,Second Edition . Chicago: The
Glenlake Publishing Company, 2001.

Wong, Andrew. “Angel Financing,”
Working Paper, University of Chicago
(2001).

BusinessReview Q3 2009 27

Changes in the Use of
Electronic Means of Payment: 1995-2007*
BY LORETTA J. MESTER

his article updates the tables originally
published in an article by Loretta Mester
in the March/April 2000 Business Review
and subsequently updated in the Second
Quarter 2006 issue.

In “The Changing Nature of the
Payments System: Should New Players
Mean New Rules?” (Business Review,
Federal Reserve Bank of Philadelphia,
March/April 2000), I presented some
data from the 1995 Federal Reserve
Survey of Consumer Finances on the
use of electronic banking. This survey
of more than 4,000 households, which
is designed to be representative of all
households in the U.S., is redone every
three years. Attached are updates of
the statistics indicating how the usages
of various means of electronic payment
have changed between 1995 and 2007.
As seen in Exhibit 1 and in
the accompanying charts, usage of
electronic forms of payment, including ATMs, debit cards, automatic bill
paying, and smart cards, has risen from
about 78 percent of households in 1995
to almost 92 percent of households
in 2007. Debit card use, which about
doubled between 1995 and 1998, has

Loretta J. Mester
is a senior vice
president and
director of
research at the
Federal Reserve
Bank of
Philadelphia. This
article is available
free of charge at www.philadelphiafed.org/
research-and-data/publications/.
www.philadelphiafed.org

been steadily increasing (although at a
slower pace) since then and now stands
at nearly 67 percent of all households.
Increases were seen in all categories by
age, income, and education. Use of direct deposit increased except for those
over age 60. Automatic bill paying fell
across all categories, but the percentage of households now using it remains
double what it was in 1995. Nearly 80
percent of households have an ATM
card, with the largest growth seen in
those over age 60. There was little
change in the percentage of households that use some type of computer
software to manage their money: The
percentage stood at about 19 percent
in 2007. Respondents under 60 years
old, those with higher income, and
those with college degrees are more
likely to use a computer for money
management.
As seen in Exhibit 2 and the accompanying charts, households that
do business with at least one financial
institution continued to increase usage
of automated methods of conducting
this business. However, there was also
an increase in the fraction of house* The views expressed here are those of
the author and do not necessarily represent
the views of the Federal Reserve Bank of
Philadelphia or the Federal Reserve System.
Forthcoming as exhibit 1 in The Statistical
Abstract of the United States, 2010.

holds, to almost 85 percent, reporting
that one of the main ways they deal
with at least one of their financial
institutions is in person. There was
a sizable increase in the percentage
of households that use the telephone
as one of the main ways of conducting business. This might reflect cell
phone usage, but both voice and
touchtone usage increased. Overall
use of electronic means of doing business — either ATM, phone, fax, direct
deposit and payment, other electronic
transfer, and/or computer — continued
to increase between 2004 and 2007.
In 2007, about 93 percent of households used an electronic method as
one of their main ways of conducting
business, and differences by income,
education, and age have become less
pronounced. Differences in the popularity of ATM/debit card usage across
age groups remain: Almost 86 percent
of those under 30 years old use ATM/
debit cards as one of their main ways of
conducting business, while around 50
percent of those over 60 years old use
them. Still, the usage by those over 60
has more than tripled since 1995.
The largest increase between 2004
and 2007 was seen in the percentage
of households that use a computer,
the Internet, or an online service to
do business. In 2007, over 50 percent
of households used these methods, up
from 34 percent in 2004 and less than
4 percent in 1995. Youth, high income,
and a college degree continue to be
associated with a higher incidence of
computer banking. While the computer remains a less popular means of
doing business with financial institutions compared with other methods,
its popularity is catching up to that of
using mail or the phone. BR

Business Review Q3 2009 29

30 Q3 2009 Business Review

EXHIBIT 1, PART 1
Percent of U.S. Households That Use Each Instrument: 1995, 1998, 2001, 2004, and 2007a
ATMb

Debit Card

Smart Cardb

1995

1998

2001

2004

2007

1995

1998

2001

2004

2007

1995

1998

2001

62.5%

67.4%

69.8%

74.4%

79.7%

17.6%

33.8%

47.0%

59.3%

67.0%

1.2%

1.9%

2.9%

72.3%

75.6%

78.1%

83.0%

84.8%

24.4%

45.0%

60.6%

74.4%

78.3%

1.8%

2.6%

Between 30 and 60 years old 68.6%

76.1%

76.8%

82.3%

85.9%

19.7%

38.6%

53.4%

67.6%

74.9%

1.5%

2.3%

3.3%

Over 60 years old

44.2%

41.9%

48.9%

51.6%

63.5%

9.6%

16.0%

24.6%

32.5%

43.9%

0.3%

0.5%

2.1%

Low income

38.5%

45.9%

46.8%

53.0%

58.8%

7.0%

19.7%

29.2%

41.2%

48.1%

0.7%

1.5%

1.9%

Moderate income

61.5%

64.4%

67.4%

73.4%

78.5%

16.0%

31.6%

46.3%

57.4%

68.0%

0.6%

3.1%

3.0%

Middle income

70.9%

72.0%

75.2%

78.3%

87.5%

20.5%

36.6%

50.0%

64.3%

75.0%

1.3%

2.0%

2.4%

Upper income

77.2%

82.3%

83.7%

86.5%

91.0%

25.1%

43.8%

57.8%

69.3%

75.8%

1.8%

1.7%

3.7%

No college degree

54.7%

60.1%

63.7%

67.4%

74.0%

14.3%

29.2%

42.3%

54.9%

63.7%

0.8%

1.8%

2.4%

College degree

80.4%

82.1%

81.6%

86.4%

90.3%

25.2%

43.1%

56.2%

67.0%

72.9%

2.1%

2.0%

3.8%

All Households
By Age:
Under 30 years old

By Income :
c

By Education

www.philadelphiafed.org

b
The questions on ATMs and smart cards asked whether any member of the household had an ATM card or a smart card, not whether the member used it. The other questions asked about usage. The
question on smart cards was dropped after the 2001 survey.
c

Low income is defined as less than 50 percent of the median household income; moderate income is 50 to 80 percent of the median; middle income is 80 to 120 percent of the median; and upper income
is greater than 120 percent of the median. Each survey refers to income in the previous year. Median income in current dollars was $32,264 in 1994; $37,005 in 1997; $41,990 in 2000; $43,318 in 2003; and
$48,201 in 2006.
Source: 1995, 1998, 2001, 2004, 2007 Survey of Consumer Finances data as of March 3, 2009, Federal Reserve System, and author’s calculations.

www.philadelphiafed.org

EXHIBIT 1, PART 2
Percent of U.S. Households That Use Each Instrument: 1995, 1998, 2001, 2004, and 2007a

Direct Deposit
1995
All Households

Automatic Bill Paying
1998

Any of the Methods: ATM, Debit Card,
Smart Card, Direct Deposit, Automatic
Bill Paying, or Software

Softwareb

1998

2001

2004

2007

1995

2001

2004

2007

2001

2004

2007

1995

1998

2001

2004

2007

46.7% 60.5%

67.3%

71.2%

74.9%

21.8% 36.0% 40.3%

47.4%

45.5% 18.0%

19.3%

19.1%

77.7%

85.5% 88.9%

90.7%

91.8%

36.5%

35.7%

17.0%

20.4%

21.4%

76.3% 80.2% 83.8%

21.9%

21.6%

78.7%

87.5%

89.9% 90.9%

92.4%

9.0% 12.8%

12.3%

76.1%

83.7%

89.4% 92.0%

92.1%

74.3% 78.0%

79.7%

By Age:
Under 30 years old

31.0%

45.2% 48.8% 54.0%

61.3%

17.7%

Between 30 and 60 years old

42.8% 58.0% 64.8% 68.2%

72.6%

24.4% 38.6%

44.1% 50.3% 48.8% 22.0%

Over 60 years old

63.3%

86.4%

18.2%

33.0%

35.9% 46.5%

74.8%

83.2%

87.0%

30.5%

32.1%

42.9%

87.6% 88.6%

By Income :
c

Low income

32.5% 44.3%

51.9% 54.8% 60.5%

9.7%

17.1%

18.2%

24.6% 23.8%

6.1%

6.8%

7.7%

56.7%

69.3%

Moderate income

42.9% 58.8%

63.1% 64.0% 68.5%

17.5%

30.5%

35.1% 40.5%

37.8%

10.7%

11.1%

10.7%

78.4%

87.2% 88.6%

88.7%

91.1%

Middle income

48.3%

66.1%

65.7%

73.2% 76.8%

23.4% 42.8%

45.1% 52.8% 50.2%

16.3%

17.8%

18.8%

85.1%

89.4%

92.5%

95.5%

96.4%

Upper income

58.3%

70.4% 80.2%

83.6% 86.6%

32.1%

49.3%

55.2%

62.4%

61.6%

29.9%

31.4%

30.5%

89.6%

94.9%

97.1%

97.5%

98.4%

No college degree

40.3%

54.4%

18.1% 30.2%

33.7%

39.5% 38.0%

10.9%

12.4%

11.9%

71.4%

80.7%

85.1% 86.6%

88.4%

College degree

61.0%

72.6% 78.0%

30.1%

53.2%

61.1%

31.8%

31.3%

32.2%

91.8%

95.1%

96.4% 98.0% 98.2%

By Education
61.8% 64.3% 68.9%
83.2%

85.9%

47.7%

59.3%

Business Review Q3 2009 31

The question on software asked whether the respondent or spouse/partner uses any type of computer software to help in managing their money.

Low income is defined as less than 50 percent of the median household income; moderate income is 50 to 80 percent of the median; middle income is 80 to 120 percent of the median; and upper income
is greater than 120 percent of the median. Each survey refers to income in the previous year. Median income in current dollars was $32,264 in 1994; $37,005 in 1997; $41,990 in 2000; $43,318 in 2003;
and $48,201 in 2006.
Source: 1995, 1998, 2001, 2004, 2007 Survey of Consumer Finances data as of March 3, 2009, Federal Reserve System, and author’s calculations.

32 Q3 2009 Business Review

EXHIBIT 2, PART 1
Percent of U.S. Households with at Least One Financial Institution Using Each Method Among the Main
Ways of Conducting Business with at Least One of Their Financial Institutionsa
In Person
1995
All Households

1998

2001

Mail
2004

2007

1995

1998

ATM/Debit Cardb

2001

2004

2007

1995

1998

2001

2004

2007

85.5%

79.5%

77.2%

77.4%

84.9%

56.5%

54.1%

50.4%

50.5%

58.9%

33.8%

52.6%

56.7%

64.4%

73.6%

Under 30 years old

77.0%

73.7%

71.5%

72.9%

79.3%

58.2%

51.9%

50.5%

44.5%

52.4%

53.0%

68.8%

72.6%

79.3%

86.2%

Between 30 and 60 years old

86.8%

81.8%

78.6%

77.3%

84.8%

62.1%

60.4%

56.6%

56.8%

62.7%

37.7%

61.5%

65.0%

72.0%

82.2%

Over 60 years old

86.7%

77.2%

76.8%

79.6%

87.7%

44.0%

39.9%

36.0%

39.2%

53.5%

16.2%

22.3%

29.8%

39.9%

49.5%

Low income

81.2%

70.3%

68.2%

71.2%

80.9%

32.8%

33.4%

24.7%

28.9%

40.4%

19.6%

34.7%

35.6%

46.6%

53.9%

Moderate income

85.9%

80.4%

76.9%

75.0%

83.0%

48.5%

46.9%

42.0%

42.8%

52.5%

29.6%

47.8%

50.5%

62.3%

71.4%

Middle income

85.7%

81.4%

78.6%

77.8%

86.4%

56.9%

56.4%

58.4%

56.4%

63.0%

37.7%

54.1%

60.7%

65.9%

80.5%

Upper income

87.7%

84.1%

81.8%

81.5%

87.4%

74.3%

69.1%

64.9%

63.0%

70.9%

42.3%

65.2%

69.6%

74.4%

83.3%

No college degree

85.8%

79.2%

75.1%

76.9%

84.0%

49.4%

48.2%

43.5%

44.3%

53.8%

27.4%

45.1%

50.1%

59.2%

69.0%

College degree

84.8%

80.2%

81.1%

78.0%

86.5%

71.2%

65.2%

63.0%

60.6%

67.7%

46.7%

66.7%

68.8%

72.9%

81.7%

By Age:

By Income

By Education

www.philadelphiafed.org

The percentages reported are based on the population-weighted figures using the revised Kennickell-Woodburn consistent weights for each year. (For further discussion see the Survey of Consumer
Finances codebooks at www.federalreserve.gov/pubs/oss/oss2/scfindex.html.) Referring to each financial institution with which the household does business, the survey asked: “How do you mainly do
business with this institution?” Respondents could list multiple methods, with the main method listed first. This exhibit reports for all households with at least one financial institution all of the methods
a respondent listed for each of the household’s financial institutions. Note, the percentages do not add up to 100 percent across columns, since households could list more than one method and more than
one financial institution. Previous versions of this chart prior to 2006 reported for 1998 and 2001 on the main ways respondents did business with their depository financial institutions (i.e., commercial
banks, trust companies, thrifts, and credit unions) rather than with any of their financial institutions.

In 1995, the question did not include debit cards

Low income is defined as less than 50 percent of the median household income; moderate income is 50 to 80 percent of the median; middle income is 80 to 120 percent of the median; and upper income
is greater than 120 percent of the median. Each survey refers to income in the previous year. Median income in current dollars was $32,264 in 1994; $37,005 in 1997; $41,990 in 2000; $43,318 in 2003;
and $48,201 in 2006.
Source: 1995, 1998, 2001, 2004, 2007 Survey of Consumer Finances data as of March 3, 2009, Federal Reserve System, and author’s calculations.

www.philadelphiafed.org

EXHIBIT 2, PART 2
Percent of U.S. Households with at Least One Financial Institution Using Each Method Among the Main
Ways of Conducting Business with at Least One of Their Financial Institutionsa
Phone
1995
All Households

1998

Computer

2001

2004

2007

1995

1998

2001

Electronicb
2004

2007

1995

1998

2001

2004

2007

25.7%

49.7%

48.9%

49.0%

61.8%

3.7%

6.2%

19.6%

33.7%

51.5%

56.2%

81.7%

87.0%

89.2%

93.3%

Under 30 years old

20.8%

45.4%

45.9%

43.2%

52.9%

5.2%

8.3%

22.9%

42.2%

61.7%

66.7%

81.0%

85.2%

89.2%

94.6%

Between 30 and 60 years old

28.1%

54.3%

52.4%

51.5%

64.8%

4.5%

7.6%

24.2%

39.9%

60.5%

59.9%

85.1%

89.4%

90.9%

95.1%

Over 60 years old

23.0%

40.6%

42.4%

46.0%

59.3%

1.2%

1.6%

7.3%

15.4%

27.4%

43.4%

73.9%

82.4%

85.4%

88.7%

Low income

13.5%

28.8%

29.2%

30.0%

46.8%

1.3%

1.5%

4.8%

14.0%

23.9%

35.3%

65.4%

73.8%

78.7%

83.7%

Moderate income

18.6%

42.5%

42.8%

44.8%

59.6%

1.8%

2.7%

11.2%

22.5%

38.1%

48.5%

80.1%

84.2%

84.8%

92.1%

Middle income

22.6%

51.7%

50.7%

62.8%

4.0%

4.3%

17.8%

32.5%

53.0%

59.2%

85.2%

89.7%

92.1%

96.6%

Upper income

37.9%

64.9%

61.4%

60.4%

71.2%

5.9%

11.5%

32.5%

49.5%

72.9%

70.8%

91.0%

94.5%

95.6%

98.1%

No college degree

19.7%

41.9%

41.7%

43.4%

58.1%

2.8%

2.7%

11.3%

24.0%

39.8%

47.8%

76.5%

83.2%

85.7%

90.3%

College degree

38.1%

64.3%

61.9%

58.0%

68.2%

5.6%

12.8%

34.8%

49.4%

71.8%

73.5%

91.4%

94.0%

94.9%

98.4%

By Age:

By Income :
c

By Education

The percentages reported are based on the population-weighted figures using the revised Kennickell-Woodburn consistent weights for each year. (For further discussion see the Survey of Consumer
Finances codebooks at www.federalreserve.gov/pubs/oss/oss2/scfindex.html.) Referring to each financial institution with which the household does business, the survey asked: “How do you mainly do
business with this institution?” Respondents could list multiple methods, with the main method listed first. This exhibit reports for all households with at least one financial institution all the methods a
respondent listed for each of the household’s financial institutions. Note, the percentages do not add up to 100 percent across columns, since households could list more than one method and more than
one financial institution. Previous versions of this chart prior to 2006 reported for 1998 and 2001 on the main ways respondents did business with their depository financial institutions (i.e., commercial
banks, trust companies, thrifts, and credit unions) rather than with any of their financial institutions.

Business Review Q3 2009 33

b
In 1995, electronic refers to ATM, phone, payroll deduction and direct deposit, electronic transfer, or computer. In 1998, 2001, 2004, and 2007, electronic refers to ATM, phone (via voice or touchtone),
direct deposit, direct withdrawal/payment, other electronic transfer, computer/Internet/online service, or fax machine.
c

Low income is defined as less than 50 percent of the median household income; moderate income is 50 to 80 percent of the median; middle income is 80 to 120 percent of the median; and upper income
is greater than 120 percent of the median. Each survey refers to income in the previous year. Median income in current dollars was $32,264 in 1994; $37,005 in 1997; $41,990 in 2000; $43,318 in 2003;
and $48,201 in 2006.
Source: 1995, 1998, 2001, 2004, 2007 Survey of Consumer Finances data as of March 3, 2009, Federal Reserve System, and author’s calculations.

FIGURES
Figure 1.1 Exhibit 1 ATM
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

2004

2007

Figure 1.2 Exhibit 1 Debit Card
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

2004

2007

Figure 1.3 Exhibit 1 Direct Deposit
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

all hhs
30-60 yrs old
low income
middle income
no college degree

34 Q3 2009 Business Review

2001

2004

2007

under 30 years old
over 60 yrs old
moderate income
upper income
college degree

www.philadelphiafed.org

FIGURES
Figure 1.4 Exhibit 1 Automatic Bill Paying
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

2004

2007

Figure 1.5 Exhibit 1 Software
Percent
40

0
2001

2007

2004

Figure 1.6 Exhibit 1 Any of the Methods
ATM, Debit Card, Smart Card, Direct Deposit, Automatic Bill Paying, or Software
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

all hhs
30-60 yrs old
low income
middle income
no college degree

www.philadelphiafed.org

2001

2004

2007

under 30 years old
over 60 yrs old
moderate income
upper income
college degree

Business Review Q3 2009 35

FIGURES
Figure 2.1 Exhibit 2 In Person
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

2004

2007

2004

2007

Figure 2.2 Exhibit 2 Mail
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

Figure 2.3 Exhibit 2 ATM/Debit
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

all hhs
30-60 yrs old
low income
middle income
no college degree

36 Q3 2009 Business Review

2001

2004

2007

under 30 years old
over 60 yrs old
moderate income
upper income
college degree

www.philadelphiafed.org

FIGURES
Figure 2.4 Exhibit 2 Phone
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

2004

2007

Figure 2.5 Exhibit 2 Computer
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

2001

2004

2007

Figure 2.6 Exhibit 2 Electronic
Percent
100
90
80
70
60
50
40
30
20
10
0
1995

1998

all hhs
30-60 yrs old
low income
middle income
no college degree

www.philadelphiafed.org

2001

2004

2007

under 30 years old
over 60 yrs old
moderate income
upper income
college degree

Business Review Q3 2009 37

Full text of Business Review (Federal Reserve Bank of Philadelphia) : Third Quarter 2009

FRASER