Directions For questions 1-80, choose the best answer from the c.docx

Directions: For questions 1-80, choose the best answer from the
choices provided. Each question is worth 1 point. You may
mark your answers on this document and send it back to me, or
record them on a separate sheet.
1. The label on a bottle of shampoo lists many ingredients, such
as water, sodium laureth sulfate, lauramide DEA, sodium
chloride, etc… From this information, shampoo is best
classified as a(n),
a. |_| substance.
b. |_| element.
c. |_| compound.
d. |_| mixture.
2. Which of the following represents an element?
a. |_| CO
b. |_| He
c. |_| HF
d. |_| NO
3. The ability to recycle aluminum (glass or plastic) is
ultimately an illustration of,
a. |_| the Law of Conservation of Mass.
b. |_| the Law of Definite Proportions.
c. |_| the Ideal Gas Laws.
d. |_| none of the above.
4. True/False - A molecule is a group of atoms that are
chemically bonded together.
5. The most abundant component of air is,
a. |_| Oxygen
b. |_| Nitrogen
c. |_| Carbon dioxide

d. |_| Water vapor
e. |_| Argon
6. In the periodic table the elements are organized,
a. |_| always by increasing atomic number.
b. |_| always by increasing atomic weight.
c. |_| alphabetically by name.
d. |_| by the number of electrons.
7. Refined white table sugar is usually derived from either sugar
cane or sugar beets. Irrespective of the source of table sugar,
after refining it always has the same composition of carbon,
hydrogen and oxygen. Sugar is best classified as which one of
the following?
a. |_| Element
b. |_| Compound
c. |_| Mixture
d. |_| State
8. This air pollutant is emitted from motor vehicles, has no
color, taste, or smell, and can cause death.
a. |_| CO
b. |_| Ozone
c. |_| SO2
d. |_| NO2
e. |_| Particulate matter, PM
9. The electrons in the outer unfilled shell are called,
a. |_| core electrons.
b. |_| valence electrons.
c. |_| electronegativity.
d. |_| noble gases.

10. Avogadro's number represents,
a. |_| one mole.
b. |_| the number of atoms in one mole of a substance.
c. |_| the number of atoms with the same mass, in grams, as the
atomic mass of an element.
d. |_| 6.02 x 1023
e. |_| all of the above.
11. The element tin (Sn) occurs naturally as ten isotopes. With
each of these isotopes,
a. |_| the number of protons is variable.
b. |_| the number of neutrons is variable.
c. |_| the number of electrons cannot vary.
d. |_| all of the above are true.
12. Relative to the size of the nucleus, the size of the area taken
up by the electrons is,
a. |_| always much smaller.
b. |_| always much larger.
c. |_| essentially the same.
d. |_| positively charged.
13. Chlorofluorocarbons, CFCs,
a. |_| are very stable molecules consisting of carbon, fluorine
and chlorine.
b. |_| have been commercially used as refrigerant gases.
c. |_| can react with UV-C light to release chlorine free radicals.
d. |_| have been shown to destroy ozone in the troposphere.
e. |_| all of the above are true
14. Which of the following statements about the
electromagnetic spectrum are TRUE?
a. |_| As the wavelength increases in the electromagnetic
spectrum, the energy of the radiation also increases.
b. |_| All electromagnetic radiation is dangerous.

c. |_| Ultraviolet radiation (UV) is not part of the
electromagnetic spectrum.
d. |_| Most of the dangerous UV radiation is screened out by
oxygen and ozone in the troposphere.
e. |_| The entire electromagnetic spectrum is visible as different
colors of light.
15. The number of neutrons in a Potassium, K-39, atom,
a. |_| is always 19
b. |_| is always 20
c. |_| is always 39
d. |_| variable
e. |_| cannot be determined
16.
If X can represent the chemical symbol of any element in the
periodic table, then represents an isotope of,
a. |_| Calcium.
b. |_| Lead.
c. |_| Uranium.
d. |_| Niobium.
17. True/False – In a free radical all the electrons are
paired.
18. A chemical bond where electrons are shared between 2
atoms is a(n),
a. |_| ionic bond.
b. |_| covalent bond.
c. |_| intermolecular force.
d. |_| none of the above are correct.
19. Use the octet rule to determine the Lewis diagram for N2.

What best describes the bonds between nitrogen molecules?
a. |_| ionic bond
b. |_| single covalent bond
c. |_| double covalent bond
d. |_| triple covalent bond
20. The number of protons in any Beryllium, Be, atom is,
a. |_| 4.
b. |_| 5.
c. |_| 9.
d. |_| cannot be determined as isotopes of Beryllium exist.
21. Carbon capture,
a. |_| requires separating CO2 from other atmospheric gases.
b. |_| involves storing carbon rather than releasing it into the
atmosphere.
c. |_| is currently limited by cost factors.
d. |_| All of the above are true statements.
22. True/False – Methane, carbon dioxide, nitrogen
molecules and oxygen molecules in the troposphere are all
greenhouse gases.
23. The identity of an element is determined by the _________
in the atom.
a. |_| number of protons
b. |_| number of neutrons
c. |_| number of electrons
d. |_| mass number
e. |_| charge
24. How many grams are in a mole of octane, C8H18?
a. |_| 6.02 x 1023
b. |_| 18g
c. |_| 25g
d. |_| 114g

25. Elements in the same group have,
a. |_| the same atomic number.
b. |_| the same number and configuration of neutrons.
c. |_| the same number and configuration of all of their
electrons.
d. |_| the same number and configuration of valence electrons
only.
26. The following reaction is important in the removal of sulfur
dioxide, a major source of acid rain, from the smokestacks of
coal burning power plants. When the equation below is
balanced, the coefficient of calcium sulfate (CaSO4, commonly
called gypsum) is:
CaO + SO2 + O2 CaSO4
a. |_| 1
b. |_| 2
c. |_| 3
d. |_| 4
27. Reactions in a vehicle’s catalytic converter act to remove
nitrogen oxide emissions in the following reaction. This
reaction shows how nitrogen oxide is combined with carbon
monoxide to produce harmless nitrogen gas and carbon dioxide.
You will need to balance the equation. Once balanced, how
many molecules of nitrogen oxide, NO, are removed for each
molecule of nitrogen gas, N2, produced?
NO (g) + CO (g) N2 (g) + CO2 (g)
a. |_| 1
b. |_| 2
c. |_| 3
d. |_| 4
28. In this reaction (shown here unbalanced), what is or are the

products?
NO (g) + CO (g) N2 (g) + CO2 (g)
a |_| NO only
b. |_| NO and CO
c. |_| N2 and CO2
d. |_| CO2 only
29. The most commonly used abrasive in toothpaste is calcium
carbonate, CaCO3. What is the mass of a mole of calcium
carbonate molecules?
a |_| 100 g
b. |_| 100 amu
c. |_| 68 g
d. |_| impossible to determine
30. Which component of the atmosphere is predicted to continue
to rise in the foreseeable future due to human activity?
a. |_| argon
b. |_| carbon dioxide
c. |_| nitrogen
d. |_| oxygen
31. A protective layer of ozone is found in which layer of the
atmosphere?
a. |_| mesosphere.
b. |_| stratosphere.
c. |_| thermosphere.
d. |_| troposphere.
32. True/False - The concentration of air pollutants is
never higher indoors than outdoors.
33. A chloride ion, Cl-(charge of minus 1), has the same
electron configuration as a(n),
a. |_| sodium atom.

b. |_| chlorine atom.
c. |_| neon atom.
d. |_| argon atom
34. A chloride ion, Cl-, is a(n),
a. |_| solvent.
b. |_| cation.
c. |_| anion.
d. |_| acqueous solution.
35. When magnesium reacts with chlorine, magnesium ions,
Mg2+, and chloride ions, Cl-, are formed. In this reaction,
chlorine atoms,
a. |_| lose electrons.
b. |_| gain electrons.
c. |_| lose protons.
d. |_| gain protons.
36. The measure of the attraction of an atom for electrons is
called its,
a. |_| nonpolarity.
b. |_| electronegativity.
c. |_| valence.
d. |_| covalence.
37. Which is the correct Lewis electron dot structure of an
atom of the element oxygen?
a. |_|
b.|_|
c. |_|
d. |_|
38. Group VIIIA, the noble gases, does not usually participate

in chemical reactions because of,
a. |_| the unique structure of their nuclei.
b. |_| the special number of protons and neutrons.
c. |_| the bonds that they form with other protons.
d. |_| the number and arrangement of their electrons.
39. True/False - The volume of water increases as it
freezes.
40. ppm and ppb are,
a. |_| toxic chemicals.
b. |_| chlorinated hydrocarbons.
c. |_| wastewater treatment strategies.
d. |_| concentration units.
41. Water’s unique properties, including its high heat
capacity, high density, and ability to act as a solvent can be
attributed to,
a. |_| its ionic bonding.
b. |_| the radioactive nature of hydrogen isotopes.
c. |_| the polarity of the molecule and the subsequent hydrogen
bonding between molecules.
d. |_| all of the above
42. A charged atom is called a(n),
a. |_| isotope.
b. |_| radioactive nuclei.
c. |_| cathode ray.
d. |_| ion.
43. A solute that conducts electricity is called a(n),
a. |_| electrolyte.
b. |_| nonelectrolyte.
c. |_| solvent.
d. |_| electronegativity.

44. A water –soluble vitamin,
a. |_| is a non-polar compound.
b. |_| is a polar compound.
c. |_| cannot form an aqueous solution.
d. |_| accumulates in the fatty tissues of the body.
45. In what group of the periodic table would elements that
form ions with a positive charge of 1, +1, be found?
a. |_| 1A, the Alkali Metals
b. |_| 2A, the Alkali Earth Metals
c. |_| 7A, the Halogens
d. |_| 8A, the Noble Gases
46. True/False – Desalination plants, where salt water is
made potable, are found in various locations around the world.
47. Many of the ancient marble statues in Athens, Greece have
become eroded during the last generation due to the action of
H2SO4 as shown in the reaction below. In this reaction H2SO4
is acting as a(n),
CaCO3 (s) + H2SO4 (aq) CaSO4 (aq) + H20 + CO2 (g)
a. |_| salt
b. |_| acid
c. |_| base
d. |_| neutralizing agent
48. Which is NOT a characteristic of bases?
a. |_| taste bitter
b. |_| turn litmus blue
c. |_| react with acids to form bases
d. |_| feel slippery on the skin
49. Which substance has the highest pH?
a. |_| hydrochloric acid
b. |_| lemon juice
c. |_| unpolluted rainwater

d. |_| a concentrated solution of NaOH, sodium hydroxide
50. If the hydrogen ion concentration of a dilute solution of
nitric acid is 0.00001M, what is the pH of that solution?
e. |_| 7
f. |_| 14
g. |_| 4
h. |_| 5
51. Acids are,
i. |_| neutron donors.
j. |_| neutron acceptors.
k. |_| proton donors.
l. |_| proton acceptors.
52. Which of the following correctly shows what happens
during the neutralization of magnesium hydroxide, Mg(OH)2, a
strong base, with hydrochloric acid, HCl, a strong acid?
a. |_| Mg(OH)2 + 2HCl MgCl2 + 2H2O
b. |_| Mg(OH) 2 + 2H2O MgCl2 + HCl
c. |_| Mg(OH) 2 2HCl + MgCl2 + 2H2O
d. |_| MgCl2 + H2O 2HCl + Ba(OH) 2
53 Alka-selzer, NaHCO3, is an efficient antacid because it is
a(n),
a. |_| acid.
b. |_| base.
c. |_| neutral.
d. |_| salt.
54. Which of the following is the correct balanced equation of
the ionization in water of NaOH, a strong base?
a. |_| NaOH H+ + O- + Na+

b. |_| NaOH H2O + Na+
c. |_| NaOH Na+ + OH-
d. |_| Na+ + OH- NaOH
55. A weak acid in water,
a. |_| produces no hydronium ions.
b. |_| produces only a relatively small fraction of the maximum
number of possible hydronium ions.
c. |_| produces a relatively small fraction of the maximum
number of possible hydroxide ions.
d. |_|produces 100% of the maximum number of possible
hydronium ions.
56. Hydoxide ions are,
a. |_| OH-
b. |_| OH+
c. |_| H3O+
d. |_| H2O-
57. True/False - The majority of the average human’s
exposure to radioactivity comes from medical diagnosis.
58. True/False - The United States currently has an
adequate amount of permanent disposal sites for high-level
radioactive waste, HLW.
59. A piece of cloth is dated using carbon-14. The cloth is
determined to be 1400 years old. The half-life of C-14 is
5730 years. The C-14 radioactivity in the cloth will be ______
than the radioactivity in the new cloth.
a. |_| greater
b. |_| the same
c. |_| less than
d. |_| the amount of radioactivity cannot be predicted
60. Ionizing radiation is,

a. |_| radiation of sufficient energy to remove neutrons.
b. |_| radiation of sufficient energy to remove protons.
c. |_| radiation of sufficient energy to remove electrons.
d. |_| none of the above.
61. Which of the following is NOT a common type of
radiation?
62. After 2 half-lives, what fraction of the original radioactive
isotope remains in a sample?
a. |_| none
b. |_| ½
c. |_| ¼
d. |_| 1/8
63. Nuclear fission is a process by which the nucleus of an
atom,
a. |_| splits into two or more fragments.
b. |_| loses an electron with the release of a large amount of
energy.
c. |_| combines with another nucleus to produce a larger
nucleus.
d. |_| loses a cosmic ray with the release of a large amount of
energy.
64. Which type of radioactivity has a negative charge?
c. |_|
d. |_| Visible light

65. True or False - Radiation is most lethal to rapidly
reproducing cells, hence its use in fighting cancer.
66. An alpha particle is the same as a(n),
a. |_| helium-4 nucleus.
b. |_| hydrogen-2 nucleus.
c. |_| electron.
d. |_| proton.
67. True or False – Batteries produce a flow of electrons
due to reduction/oxidation reactions.
68. True or False – Iron, Fe, is oxidized in the following
reaction: Fe Fe2+ + 2e-
69. Which of the following statements are TRUE concerning
common alkaline cells?
a. |_| The voltage from an AA alkaline cell is the same as the
voltage from a D alkaline cell.
b. |_| An AA alkaline cell will sustain the flow of electrons for
longer than a D alkaline cell.
c. |_| The voltage in AA and D alkaline cell batteries is variable.
d. |_| All of the above statements are true.
70. In reduction chemical reactions,
a. |_| an electron is gained.
b. |_| an electron is lost.
c. |_| an electron is either gained or lost.
d. |_| a proton is transferred.
71. Which of the following is the best definition of voltage?
a. |_| rate of electron flow
b. |_| site of oxidation in a galvanic cell
c. |_| source of electrons in a galvanic cell
d. |_| difference in electrochemical potential between two

electrodes
72. An anode,
a. |_| is not where a reduction or oxidation reaction take place in
a galvanic cell.
b. |_| is the source of electrons in a galvanic cell.
c. |_| is a measure of the rate of electron flow.
d. |_| is a measure of the difference in electrochemical potential
between two electrodes.
73. Carbohydrates are polymers of,
a. |_| amino acids.
b. |_| saccharides such as glucose.
c. |_| cellulose.
d. |_| lipids.
74. Saturated fats have,
a. |_| only C-C single bonds.
b. |_| a large proportion of C=C double bonds.
c. |_| an odd number of carbon atoms.
d. |_| an even number of carbon atoms.
75. Amino acids that are not synthesized by the human body
and must be obtained in food sources are called,
a. |_| nucleic acids.
b. |_| carboxylic acids.
c. |_| essential amino acids.
d. |_| vitamins.
76. Most dietary fats are,
a. |_| trans fats.
b. |_| cholesterol.
c. |_| triglycerides
d. |_| glycerol

77. True or False – Trans fats are a type of fat commonly
found in plant and animal foods.
78. Fat soluble vitamins,
a. |_| are inorganic compounds that are required for proper
nutrition.
b. |_| are less important than water soluble vitamins.
c. |_| can be taken in large doses as they are rapidly decomposed
in the body and excreted daily.
d. |_| can be stored in the body in fatty tissue.
79. True or False – Someone who is obese cannot suffer
from malnutrition.
80. Which of the following statements concerning lipids is
FALSE.
a. |_| Fats, oils, steroids and waxes are all lipids.
b. |_| Lipids are nonpolar molecules and so are not soluble in
water.
c. |_| Lipids have the highest calorie per mass value of the
different types of foods.
d. |_| The lipid, triglyceride, consists of three amino acid
structures and a glycerol.
Directions: For questions 81-88, answer each of the following
questions in the text box or on a separate sheet of paper. Be
sure to answer the entire question. Each is worth 4-6 points as
noted.
81. (6pts) Choose ONE of the following air pollutants: VOCs,
sulfur dioxide, particulate matter, radon. Describe the
pollutant. What are the natural and man-made sources of the

pollutant? Describe how it is toxic to humans?
82. (6pts) What is the chemical formula for the oxygen
molecule? What is the chemical formula for the ozone
molecule? How is ozone naturally generated in the atmosphere?
What are some effects of ozone in the air around you here in the
troposphere? What is the beneficial action of ozone in the
stratosphere?
83. (4pts) What a balanced equation for the combustion of
propane, C3H8, in the presence of oxygen, O2, to yield carbon
and water.
84. (6pts) Describe how the greenhouse effect naturally
influences the earth’s temperature. Then, describe what is
meant by the enhanced greenhouse effect. List two greenhouse
gases.
85. (5pts) Define solubility. What types of molecules are
soluble in water? What types of molecules are not soluble in
water? Relate this to hydrogen bonding.
86. (6pts) Define and describe acid rain. Choose either sulfur
or nitrogen oxides. How does this contribute to acid rain? What
are the main sources of these emissions?
87. (6pts) Briefly describe how nuclear reactors produce
electricity.
88. (6pts) Define and describe ONE of the following: galvanic

cell, fuel cell, photovoltaic cell.
238
92
X
The Pipeline to the Top:
Women and Men in the Top Executive Ranks of U.S.
Corporations
by Constance E. Helfat, Dawn Harris, and Paul J. Wolfson
Executive Overview
People often ask about the pipeline of women in line for the top
position in major U.S. corporations.
Despite persistent interest in this issue, we do not yet have good
answers to the question of how long it will
take until more than a token number of women hold the CEO
position. This study provides numerical
estimates that help to answer this question, and also provides
new information regarding the job
responsibilities and positions in the executive hierarchy of
women and men below the rank of CEO. This
article presents the results of an extensive data collection effort
that has yielded a comprehensive census
of top executives in U.S. Fortune 1000 firms as of the year
2000. With regard to the pipeline to the CEO
position, our data suggest that we should expect to see a slow
increase in the percentage of CEOs that are
women in the next five to ten years. Nevertheless, the
percentage of CEOs that are women is likely to
remain relatively low. As a result, our estimates suggest that if
current trends continue, perhaps 6 percent
of CEOs in the Fortune 1000 will be women by 2016. We also

document the little known fact that almost
50 percent of the firms in the Fortune 1000 had no women as
top executives as recently as the year 2000.
Moreover, even firms with women executives generally had
only 1 or 2 per firm.
T
he business press frequently bemoans the
dearth of women at the top ranks of business.
Academic research has documented this scar-
city as well. And virtually everyone wants to know
what the pipeline of women in line for CEO
positions looks like. We continually hear people
ask a question that so far has lacked an answer:
How long will it be until we see more than a token
number of women as CEOs in major U.S. corpo-
rations? In answer to this question, we provide
numerical estimates of the percentage of CEOs
that are likely to be women in 2010 and 2016.
Based on comprehensive new data, we also ana-
lyze how women below the rank of CEO compare
with male top executives in terms of functional
area job responsibility, position in the executive
hierarchy, age, company tenure, and tenure in
current position. This analysis provides the basis
for an assessment of the future prospects for the
representation of women in top management, and
for recommendations for improvement.
To date, statistical analyses have contained rel-
atively little direct comparison of the characteris-
tics of women and men at the executive level
(with notable exceptions such as Cappelli and
Hamori 2004). But without a baseline for com-
parison–namely, male executives who comprise

the overwhelming majority of top management–it
is difficult to fully assess the position of women in
the top executive ranks. In order to provide a
comprehensive picture of the status of and pros-
pects for women in top executive ranks, we re-
quire a large, well designed data set that will
enable us to draw reasonably precise, robust con-
clusions. This article presents the results of an
extensive data collection effort that has yielded a
comprehensive census of top executives in U.S.
Fortune 1000 firms as of the year 2000. Based on
this data set of nearly 10,000 individuals, we have
performed a detailed analysis of the characteristics
of women and men of executive rank in the U.S.
* Constance E. Helfat ([email protected]) is the J. Brian Quinn
Professor of Technology and Strategy at the Tuck School
of Business at Dartmouth.
Dawn Harris ([email protected]) is an Associate Professor in the
Graduate School of Business at Loyola University, Chicago.
Paul J. Wolfson ([email protected]) is a Statistical Research
Associate at the Tuck School of Business at Dartmouth.
42 NovemberAcademy of Management Perspectives
These data provide a benchmark from which to
gauge current and future progress.
Our analysis contains three main findings.
First, we find that almost 50 percent of the firms
in our sample had no women as top executives.
Second, in firms that had women among their
executives, we find evidence consistent with “to-
ken” status of women on the top executive team.

Third, partly as a consequence of the first two
findings, the pipeline of women in line for the
CEO position, although growing, remains small.
Despite these sobering findings, we also have pos-
itive data to report. Contrary to popular percep-
tion, the women in our sample are not underrep-
resented in certain important functional areas
such as accounting and legal, relative to the over-
all percentage of women in the top executive
ranks. In addition, the women do not cluster at
the very lowest levels of the hierarchy, but instead
tend to hold positions one or two levels below the
second-in-command executive. Finally, our results
suggest that many of the firms that have women in
top management have actively recruited and pro-
moted them to executive rank.
In what follows, we first elaborate on the mo-
tivation for our study. Then we explain our data
collection and coding. We present the results of
the study and provide an analysis of the pipeline
to the CEO position. We also analyze factors that
differentiate firms in terms of the representation of
women among top executives.
Why Study Women Executives?
T
here is a broad literature on the career ad-
vancement of women in business. Topics of
research have included gender differences in
career success (e.g., Kirchmeyer 1998) and career
mobility (e.g., Valcour & Tolbert 2003). Research
also has focused specifically on the “glass ceiling”
(for a review, see Powell 1999). This term, coined

by Hymowitz and Schelhardt of the Wall Street
Journal in 1986, denotes an invisible barrier to the
upward movement of women and minorities in
management. Morrison and Von Glinow (1990)
pointed to systematic barriers to advancement of
women in management, including lack of oppor-
tunities, power, mentors, and role models. Good-
man, Fields, and Blum (2003) investigated
whether greater career opportunities for women
within organizations mitigated the glass ceiling
effect in a sample of medium-to-large size work
establishments in the state of Georgia in the early
1990s. They found that greater opportunity for
women due to higher management turnover and
emphasis on internal promotion and develop-
ment, as well as a larger pool of female non-
management employees (as a percentage of all
such employees), was associated with a greater
likelihood of women in top management.
Prior research has advanced three general types
of explanations for generally low percentages of
women in management: person-centered; situa-
tion-centered; and social-system-centered (Powell
1999). Person-centered explanations refer to indi-
vidual-level factors that cause women and men to
make different career decisions and to perform job
tasks differently. Situation-centered explanations
refer to group and organizational-level factors that
affect the differential hiring and promotion of
women and men. Social-system-centered explana-
tions refer to factors in society (political, social,
governmental, and economic) that affect the dif-
ferential hiring and promotion of women and
men.

Our study focuses on the situation-centered, or
organizational, level of analysis. Within that level
of analysis, we focus on top management. The
leader of an organization plays an important role
in directing strategy and operations, and as a sym-
bol to the outside world (Hambrick & Mason
1984; Hayward, Rindova, & Pollack 2004). Re-
search has demonstrated the impact of CEO hu-
man capital on firm performance (e.g., Bailey &
Helfat, 2003, 2005; Harris & Helfat 1997, 1998;
Hitt, et al. 2001). For these reasons, both the
business press and organizations dedicated to in-
creasing the overall representation of women in
business have focused special attention on the
CEO position.
Yet in order to understand decision making at
the top of the organization, we must also look
beyond the CEO. What has come to be called the
“top management team” (TMT) is the set of in-
dividuals at the top of the organization responsible
for the strategic and organizational decisions that
affect the direction, operations, and performance
2006 43Helfat, Harris, and Wolfson
of the company as a whole. Studies have shown
that TMTs, as well as CEOs, have an important
influence on firm strategy and performance (for a
review, see Finkelstein & Hambrick 1996).
A key issue regarding the effectiveness of deci-
sion making in teams, including TMTs, has to do

with the diversity of the team. Diversity within
organizational teams leads to greater search for
information, range of perspectives, and generation
of alternative solutions (e.g., Dutton & Duncan
1987; Watson, Kumar, & Michaelsen 1993).
Greater heterogeneity, however, may also lead to
offsetting negative effects such as greater conflict
and communication difficulties among top team
members (Miller, Burke, & Glick 1998). Based on
a review of the evidence, Finkelstein and Ham-
brick (1996) conclude that on balance, the ben-
efits of diversity in experience and background
among top managers outweigh any negative im-
pact.
Should we include gender when considering
the benefits of diversity in top management?
Some prominent business people have answered
strongly in the affirmative. For example, the
former CEO of Newell-Rubbermaid, a major con-
sumer products company, has argued that the
company must promote managers who can best
understand its customers—including women and
minorities.1 James Preston, CEO of Avon, and
Larry Johnston, CEO of Albertson’s grocery
chain, have made the same argument with regard
to including women on boards of directors (Daily,
et al. 1999). Women control 88 percent of all
purchases in the U.S. (Kanner 2004). If women in
management have additional insight (beyond that
of men) into the purchasing decisions of other
women, then companies should benefit from in-
cluding women in the top management team.2
In addition to the diversity argument, compa-
nies routinely state how important it is to obtain

the best possible managers. Logically, if talent is at
a premium, then firms should benefit from having
as large a pool of potentially qualified individuals
to draw upon as possible. Today women make up
over half the managerial and professional work-
force, including much lower levels of management
than those examined here (Bureau of Labor Sta-
tistics 2003). Unless women inherently have less
top management potential than men, the sheer
increase in the size of the labor pool that comes
from including women should benefit companies.
The importance of drawing from the largest
possible talent pool, and the potential benefits to
TMT decision making, constitute the crux of the
“business case” for including women in the top
executive ranks of corporations. Yet we still have
an incomplete picture of the population of women
in top management. In addition, we know rela-
tively little about how this population of women
compares with the population of men in top man-
agement, particularly below the level of the CEO.
In what follows, we elaborate on the need for
additional data, before explaining our data collec-
tion process and coding.
Women in Top Management: What We Know Thus
Far
Perhaps the most widely quoted source of data on
women in executive rank is the Catalyst bi-annual
Census of Women Corporate Officers and Top
Earners. Catalyst collects data on women who are
corporate officers in the Fortune 500 companies
from publicly available company reports to the

Securities and Exchange Commission (SEC) and
to stockholders, and then asks each company to
verify these data. As part of the verification pro-
cess, companies can add female corporate officers
that do not appear in official company filings or
annual reports to stockholders.3 Catalyst also asks
the companies to verify the functional area re-
sponsibilities of the executives. Based on these
data, Catalyst reports the number and percentage
of officers who are women.4
1 In February 2004, Joe Galli, CEO of Newell-Rubbermaid at
the time,
made this statement in a speech at the Tuck School of Business
at
Dartmouth.
2 A study by Richard, et al. (2004) suggests that under some
conditions
gender diversity within the top team is positively associated
with firm
productivity, but the study did not investigate the impact of
gender diver-
sity on the decision making process of TMTs.
3 This information is based on a conversation between one of
the
authors of this article and the person at Catalyst responsible for
directing
the research for the Catalyst Census of Women Corporate
Officers and Top
Earners in 2000.
4 It is difficult to know what the percentages represent, since it
is
unclear if the companies also add the names of male executives

to their lists
Academic studies also have examined the rep-
resentation of women in top management, often
focusing on Fortune 500 companies (for a review,
see Powell 1999). The data in the Catalyst reports
and other studies show a growing proportion of
women in top management in recent years. Most
estimates of women in top management in the
1970s through 1990 ranged from zero to 3 percent
(Powell 1999). The percentages reported by Cat-
alyst for the Fortune 500 companies in the second
half of the 1990s were much higher: 8.8 percent in
1995, 11.2 percent in 1998, 12.5 percent in 2000,
and 15.7 percent in 2002 (Catalyst 1998, 2002).
Hillman, et al. (2005) also found that 7.34 per-
cent of top executives in the largest 1,000 com-
panies during the period 1990-2003 were women.
Finally, Cappelli and Hamori (2004) found that
11 percent of top executives in the Fortune 100 in
2001 were women.
Despite this upward trend, the data show less
representation of women among executives most
directly in line to be CEO. Catalyst reports that in
2002 women held 9.9 percent of line (profit-and-
loss responsibility) officer positions and comprised
5.2 percent of the top five most highly compen-
sated corporate officials, up from 7.3 percent and
4.1 percent respectively in 2000. Bertrand and
Hallock (2001) found that previously, during the
period 1992-1997, 2.4 percent of the top five

highest paid executives per firm in the Standard
and Poor’s (S&P) ExecuComp data base (cover-
ing firms in the S&P 500, S&P Midcap 400, and
S&P SmallCap 600) were women. Moreover, Dai-
ley, et al. (1999) found that in the Fortune 500
only eight inside directors in 1996 were women
(down from 11 in 1987), amounting to 0.006 of
the total number of inside directors in the sample.
Since these are the women most directly in line to
become CEO (Zelechowski & Bilimoria 2003),
this very low figure essentially predicts that the
percent of CEOs who are women would be small
in the near to medium term. Current data bear
this out. As of March 2005, 1.8 percent of CEOs
(9 individuals) in the Fortune 500 were women.
This is a relatively small change from the 1.2
percent of CEOs (6 individuals) in the Fortune
500 that were women in 2002.
Our Data
The foregoing studies provide a useful starting
point for assessing the representation of women in
top management. In order to provide a fuller pic-
ture, we collected data with several goals in mind.
First, in order to gain information about a larger
segment of the U.S. economy, we included all
companies in the Fortune 1000, rather than only
the Fortune 500 companies examined in most
prior studies. Second, we coded data for both men
and women. This enabled us to make explicit
comparisons between them. Third, in order to
prevent potential over-reporting by firms of the
number of women executives, we included only
executives that companies listed in their official

filings and reports. Although companies differed
in the number of executives they reported, we
have accounted for these differences in the statis-
tical analysis. We did not restrict our analysis to a
subset of the executives listed per firm, such as the
five most highly compensated executive officers
that all companies must report. This approach
would have excluded a large proportion of top
executives that are women.
Our data collection began with the list of For-
tune 1000 companies from the year 2000.5 We
coded information from the short biographies of
every individual in the List of Executive Officers
reported by each company in their annual 10-K
reports to the Securities and Exchange Commis-
sion or in proxy statements. We developed a de-
tailed coding protocol, which we relied on to
pre-code every biography by hand. Research assis-
tants then entered the data into an Excel spread-
sheet. Other research assistants proofread the
spreadsheet entries. The final database consisted
of 942 firms and 9,950 individuals. A number of
firms on the Fortune 1000 list did not file 10-K
reports in 2000 due to mergers, acquisitions, bank-
for Catalyst. The Catalyst reports also include the percentage of
women
who are among the top five most highly compensated
individuals of their
companies, are “line” officers, and have selected job titles
below the rank of
CEO. In addition, the reports contain a breakdown of the
number and
percentage of female officers by industry. Finally, the reports
list the titles

held by female officers in each company, but do not list the
titles held by
male officers for purposes of comparison.
5 We started collecting data in the summer of 2000, and used
the most
recent Fortune 1000 list available.
ruptcies, or private ownership, which reduced the
sample size. In addition, some companies did not
list information for all of the data items that we
coded. We therefore have small amounts of miss-
ing data for most of the variables in our data base
(other than gender).
In order to compare the jobs and career pat-
terns of women versus men, we coded several
variables. First, we coded more fine-grained dis-
tinctions between functional area responsibilities
than in prior studies of women in top manage-
ment. Although prior studies have distinguished
between line (profit-and-loss responsibility) and
staff (non-line) positions (see e.g., Catalyst 2000,
2002), they have not examined gender differences
in staff positions. Since some types of staff posi-
tions (e.g., finance) are often perceived as more
influential than others, we sought to understand
whether women and men differed in their staff as
well as their line job responsibilities. The Appen-
dix explains how we coded the functional area job
classifications.

In order to further gauge the relative authority
and status of women within the top management
of each firm, we coded the relative rank of each
executive, female and male, within each top exec-
utive hierarchy. Although studies have examined
the representation of women among executives
holding particular executive titles (e.g., Catalyst
2000, 2002; Powell 1999), prior research has not
analyzed within-company executive hierarchies.
Corporate titles mean different things in different
companies. For example, some companies use the
Senior Executive Vice President title and others
do not. The title that an individual holds does not
necessarily tell us where that person falls within
the top management hierarchy of each company.
The Appendix explains the algorithm that we
used to assign a within-company hierarchical rank
to each executive.
We also coded the number of years that each
executive had held his or her current position, and
the number of years that the executive had
worked for the company. These data can help us
to understand whether firms used early promotion
and outside hiring more often for women than for
men. Currently, we do not know whether firms
use these approaches to increase the representa-
tion of women in top management. We recorded
several other data items as well: age of the exec-
utive, industry, number of corporate officers re-
ported by each company, and total revenues (a
measure of firm size) and profits of each compa-
ny.6
Our data base comprises what to our knowledge

is the most comprehensive set of information on
the characteristics of women and men of execu-
tive rank in the United States. What emerged
after a time-consuming data collection effort is a
baseline from the year 2000 that can be used to
assess the progress of women in the recent past.
These data also can inform us about the future.
For example, our data include women at lower
levels of the executive hierarchy not directly in
line for promotion to CEO in 2000. Since it can
take many years to be promoted through the ranks
of the executive hierarchy, our data can help to
predict the extent to which we should expect to
see a significant number of women who are CEOs
in the next 5 to 10 years.
In what follows, we compare women and men
at the executive level using the data just de-
scribed. Then we provide estimates of the percent
of women in the Fortune 1000 who are likely to
reach the CEO position in 2010 and 2016. Fi-
nally, we report the results of statistical analyses
that assess differences between companies in the
representation of women among top executives.
A Comparison of Women and Men in Top
Management
O
f the 942 firms in our sample, 8.25 percent
(821 executives) of the total of 9,950 execu-
tives in those firms were women. As reported
in Table 1, almost one-half of the companies in
our sample (48 percent) had no women as exec-
utives. Twenty-nine percent of the companies had

just one woman of executive rank and only 23
percent had more than one woman. Thus, the
overall figure of approximately 8 percent women
6 We also recorded the educational background of each
executive
where available, but since the majority of the biographies did
not provide
this information, we did not analyze these data. We had
originally hoped to
analyze the job histories of the executives as well, but this
information was
spotty and often not comparable between companies.
in top management masks the fact that almost half
of the companies had no executives who were women.
Table 1 indicates that the Fortune 1000 com-
panies had between zero and 8 women of execu-
tive rank per firm. Few firms, however, had more
than 3 women at the top level. The variation
across firms was much greater for the percentage of
executives per firm that were women, ranging
from a low of zero to a high of 60 percent. To
quantify the dispersion across firms in the percent-
age of executives that were women, we can use the
coefficient of variation (the ratio of the standard
deviation to the mean). This ratio is 1.20, com-
pared with a ratio of 0.10 for the percentage of
executives per firm who were men. These figures
tell us that there were far greater differences be-
tween firms in the percentage of executives who

were women than in the percentage who were
men.
In order to obtain additional information about
the representation of women in top management,
we next compared the ages of female and male
executives. We also examined how long the
women and men had worked for their current
employers, and how long they had held their
current positions. Table 2 reports these data.
With regard to age, we found that on average
women were approximately 5 1/2 years younger
than the men (statistically significant at the
0.0001 level).7 Women had an average age of
46.7, whereas men had an average age of 51.1.
Cappelli and Hamori (2004) found almost identi-
cal results for executives in the Fortune 100 in
2001: an average age of 47 for women and 52 for
men. Figure 1 provides further information regard-
ing the age distribution of women and men at
executive levels. As the figure shows, close to half
the women— 42 percent—were age 45 or less,
compared with only 24 percent of the men.
Clearly, the women were substantially younger
than the men.
We also found that on average women had
worked for their current employers for approxi-
mately 2.5 years less than the men: 8.1 years for
women versus 10.7 years for men, a statistically
significant difference at the 0.0001 level. Figure 2
compares the distribution of company tenure for
7 For all t-tests reported here, we tested for equality of the

variances in
the two sub-samples. If the variances were unequal, we
performed a t-test
under the assumption of unequal variances and report that result
here.
Table 1
Number of Executives per Firm
Number of
Women Per Firm
Number of
Firms
Percent of Firms in
the Sample
0 450 47.77
1 276 29.30
2 148 15.71
3 44 4.67
4 12 1.27
5 6 0.64
6 4 0.42
7 1 0.11
8 1 0.11
Minimum
Value
Maximum
Value
Number of Female
Executives Per

Firm
0 8
Number of Male
Executives Per
Firm
2 50
Total Number of
Executives Per
Firm
3 54
Lowest Level in the
Hierarchy
Reported
3 7
Table 2
Executive Age, Company Tenure, and Tenure in
Current Position
Women Mean
Standard
Deviation
Minimum
Value
Maximum
Value

Age 46.70 6.11 29.00 78.00
Years of Company
Tenure
8.08 7.13 0 46.00
Years in Current
Position
2.62 2.55 0 17.00
Men Mean
Standard
Deviation
Minimum
Value
Maximum
Value
Age 51.07 7.46 28.00 91.00
Years of Company
Tenure
10.70 9.60 0 72.00
Years in Current
Position
3.45 3.98 0 53.00

women and men. This figure shows that 47 per-
cent of the women had worked for their compa-
nies for 5 years or less, compared with 38 percent
of the men. Companies appear to have been more
willing to hire high-level women than men from
outside the firm, perhaps in order to seed the pool
of women in top management.
Additionally, women on average had approxi-
mately one less year of tenure in their current
executive positions than men: 2.6 years for
women compared with 3.5 years for men, a statis-
tically significant difference at the 0.0001 level.
Figure 3 compares the distribution of tenure in
current position (defined as the period for which
an individual had no change in job titles) for
women and men. Sixty-four percent of the women
had held their current position for two years or
less, versus 56 percent of the men. This disparity
further suggests noticeable efforts by some firms to
promote women to executive rank.
In sum, these data indicate that whereas nearly
half of the Fortune 1000 firms had no women
executives, the other half of the firms were ac-
tively recruiting and promoting women to the top
executive ranks. Relative to the men, the women
were younger, and had worked for their companies
and held their current positions for shorter periods
of time.
Job Positions of Women and Men at the Executive
Level
Although the analysis thus far suggests that a

subset of the Fortune 1000 companies were ac-
tively promoting women to executive rank,
women in management are sometimes perceived
to hold less influential positions than men. We
investigated three ways in which women might or
might not hold less powerful positions at the ex-
ecutive level. First, we analyzed where women
ranked in the top executive hierarchy relative to
men. Second, we analyzed the job responsibilities
of women and men in order to ascertain whether
women were more likely than men to hold non-
operational “staff” positions. Executives who hold
staff positions generally have less say in decision
making than those that hold “line” responsibility
Figure 1
Age of Executives
for business operations. Third, within staff posi-
tions, some are perceived as more influential than
others. For example, finance is often viewed as a
relatively important “staff” position. Indeed, the
position of chief financial officer has become a
more common route to the CEO position than in
the past. We therefore analyzed the representation
of women versus men in different functional
“staff” areas.
Table 3 reports the total number of executives
and the number of women and men at each level
in the executive hierarchy. The highest possible
within-company level in the hierarchy was a rank

of 1 and the lowest reported level was a rank of 7.
Few executives had a rank of 6 or 7, reflecting the
fact that most firms reported only very high level
executives. At Level 1, the very top of the hier-
archy, only 0.62 percent (7 out of 1,119) of exec-
utives were women. (A number of companies had
more than one executive at Level 1 in the hier-
archy.) At Level 2 (second-in-command execu-
tives), only 1.7 percent of executives (7 out of
424) were women. The representation of women
increased sharply below Level 2, rising to 6.4
percent at Level 3, 10.4 percent at Level 4, and
12.8 percent at Levels 5, 6, and 7 combined.
A majority of the women held positions just
below the top two rungs of the executive hierar-
chy. Table 3 indicates that 66 percent of the
women had attained either Level 3 or Level 4 in
the hierarchy. Figure 4 and table 3 show how each
gender was distributed across different levels in
the hierarchy. Levels 1 and 2 combined contained
only 1.7 percent of the total number of women,
compared with 16.7 percent of men. The disparity
largely disappears in Levels 3 and 4, which to-
gether contained 66 percent of the women and
63.5 percent of the men. Although a smaller per-
centage of the women (23 percent) were in Level
3 than the men (30.3 percent), relative to their
overall numbers, women were well-represented in
the two combined levels just below the second-
in-command position.
We next investigated differences between
women and men in line versus staff positions and
in functional area responsibilities. By definition,

Figure 2
Company Tenure
the top two levels in the hierarchy are line posi-
tions, with direct profit-and-loss responsibility.
Positions such as CEO, President, and Chief Op-
erating Officer have direct responsibility for the
operations of the entire company. Therefore, we
coded a position as having “line” responsibility if:
an individual was in Level 1 or 2 in the hierarchy;
the title indicated that the individual was head of
an operational subsidiary; or at least one of the
individual’s functional area responsibilities in-
cluded operations, marketing, or sales. We in-
cluded marketing and sales as line positions since
these positions often come with profit-and-loss
responsibility in many companies, such as those in
consumer products, retailing, and financial ser-
vices.
In order to compare the representation of men
and women in line positions, we compared the
percentage of women who held line positions with
the percentage of men who held line positions.
The percentage of women in line positions (25.3
percent) was approximately half that of men (52.5
Figure 3
Tenure in Current Position

Table 3
Level in the Executive Hierarchy
Level in the
Hierarchy
Total Number
of Executives
Per Level
Number of
Men
Per Level
Number of
Women
Per Level
Women as
percent of
Total
Executives
Per Level
Women as
percent of
# Total
Female
Executives
in Full

Sample
Men as percent
of Total # Male
Executives in
Full Sample
1 1119 1112 7 0.63 0.85 12.18
2 424 417 7 1.65 0.85 4.57
3 2955 2766 189 6.40 23.02 30.30
4 3385 3032 353 10.43 43.00 33.21
5 1719 1499 220 12.80 26.80 16.42
6 326 287 39 11.96 4.75 3.14
7 22 16 6 27.27 0.73 0.18
percent). Since the remainder of the executives
held staff positions of some type, these data indi-
cate a corresponding overrepresentation of
women in staff positions. To further investigate
this finding, we excluded executives in Levels 1
and 2 of the hierarchy from the analysis. Because
very few women held these high-level line posi-
tions, including the Level 1 and 2 positions could
overstate line/staff differences between men and
women. When we excluded Levels 1 and 2, the
percentage of men in line positions dropped by 10
percentage points to 42 percent, while the per-
centage of women in line positions dropped only
slightly to 24 percent. The gap between women
and men, however, remained substantial.

Next we compared the representation of
women and men in each of the individual func-
tional areas. Since many executives had more
than one functional area responsibility, we as-
signed each job responsibility (rather than each
individual) in the database to a functional area.
Hence, the number of job responsibilities exceeds
the number of executives. Then for each func-
tional area, we computed the ratio of the number
of job responsibilities held by women in that func-
tional area relative to the total number of job
responsibilities held by women in all functional
areas together, and converted this to a percentage.
We performed the corresponding calculations for
men. Although these data depend on the number
of job responsibilities and titles (which often re-
flect job responsibilities) reported per person, they
provide a sense of whether or not women and men
clustered in different functional areas.
Figure 5 enables us to discern functional areas
in which women and men were under- or over-
represented relative to their overall representation
among top executives. The data reveal large dis-
parities in the following areas: operations, finance,
accounting, secretary, legal, public relations, and
human relations. Men were much more heavily
represented in the first two areas, especially oper-
ations, and women were much more heavily rep-
resented in the latter areas. Some of these findings
accord with popular perception, particularly with
regard to operations, finance, and public and hu-
man relations. Other findings, however, do not
necessarily fit popular perceptions. Women were

Figure 4
Level in the Executive Hierarchy
more heavily represented in accounting and legal
positions than men. Furthermore, we do not see
wide disparities in areas such as strategy, opera-
tions support, and information technology, which
might generally be perceived as positions held by
men rather than women.
Women and men had fewer disparities in job
responsibilities than a popular reading of the
situation might suggest. Although underrepre-
sented relative to their total numbers in line
and finance positions, women were overrepre-
sented in some functional areas, notably ac-
counting and legal, and held their own in in-
formation technology and strategy. Women
were underrepresented at the very highest levels
of the hierarchy, but two-thirds of them at-
tained ranks in the hierarchy just below the top
two rungs. This suggests that eventually we may
see greater numbers of women at the very top of
the hierarchy. We next use our data to provide
some rough estimates of what we might expect
to see and how soon.
The Pipeline Question
I
n order to estimate how many women may move
up in the executive hierarchy and how soon, we

need to account for several factors. First, we
must account for the fact that not all executives at
each level of the hierarchy are promoted to the
next higher level in the hierarchy. Second, we
must account for the speed at which individuals
who are promoted move up in the hierarchy.
Third, because line positions, and more recently
the CFO position, are often a route to the top, we
need to know the representation of women in line
plus CFO positions in relevant levels of the hier-
archy. To assess the pipeline to the CEO position,
we start with a base case scenario that accounts for
the foregoing factors, and then suggest some alter-
natives to the base case estimates. Table 4 reports
the range of estimates discussed below.
For the base case, we assume that average CEO
tenure is 5 years. This is probably on the low side,
but it ensures that our estimates of the rate at
which women may become CEO will not suffer
Figure 5
Functional Areas of Responsibility
from undue pessimism. In accordance with this
assumption about average CEO tenure, we assume
that other promotions from one level to the next
within the executive hierarchy occur on average
every five years as well. Additionally, we assume
that women will be promoted to the next higher
level in the hierarchy in accordance with their

representation at their current level of the hierar-
chy. Thus, if women were to comprise 10 percent
of all Level 4 executives in 2005, we would expect
that after promotion, on average they would com-
prise the same 10 percent of all Level 3 executives
in 2010.
Using these (perhaps optimistic) base case
assumptions regarding the speed and rate of
promotion, our data enable us to make rough
predictions regarding the pipeline to the CEO
position in the near to medium term, meaning
in the next five to ten years. Since our data
come from the year 2000, an average CEO ten-
ure of five years implies that by 2005 the aver-
age CEO position would have turned over. Of-
ten, new CEOs come from the ranks of second-
in-command executives at the same or another
firm. Thus, in 2005, the executives most likely
to reach the top two rungs by 2010 and 2015
would have been at Levels 3 and 4, respectively,
of the executive hierarchy in the year 2000.
To begin, we take the most optimistic scenario
and assume that all executives, not just those in
line or CFO positions, are potential candidates for
CEO. In the year 2000, 6.4 percent of all execu-
tives at Level 3 in the hierarchy were women.
This would imply that by 2010, with an average
five-year tenure in each level of the hierarchy, this
same 6.4 percent of CEOs would be women. Sim-
ilar reasoning suggests that since 10.4 percent of
all executives in Level 4 in 2000 were women, by
2015 we might expect to see this same percentage
of executives reach Level 1 in the hierarchy. We

emphasize that these are only estimates, and that
we certainly cannot forecast actions by companies
that might alter these estimates. Furthermore, our
estimates are based on averages, and things may
Table 4
Pipeline Estimates
Average Years of Tenure Per Level in
the Executive Hierarchy Year
Estimated Percent of CEOs
That May be Women
Base case:
5 Years
(All Executives Eligible for CEO Position)
2010 6.4
5 Years
(Only Line and CFO Executives Eligible)
2010 4.9
8 Years
(All Executives Eligible)
2010
(reach CEO in 2008)
1.7*
8 Years

2010
(reach CEO in 2008)
1.7*
4 Years
2010
(reach CEO in 2008)
6.4
Base case:
5 Years
2015 (and 2016) 10.4
5 Years
2015 (and 2016) 6.2
8 Years (All Executives Eligible) 2016 6.4
8 Years
2016 4.9
4 Years (All Executives Eligible) 2016 12.8
*These estimates are based on the percentage of women in
Level 2 in 2000, which by definition is a line position. Hence,
the two
estimates with asterisks are the same.

move more slowly or more quickly than averages
would predict.
The base case does not account for the fact that
executives in line and CFO positions generally
have a greater likelihood of promotion to the top
position. We next refine the base case estimates
under the assumption that only CFOs or execu-
tives in line positions are eligible for promotion to
higher levels in the hierarchy. This approach
yields the following train of logic. In 2000, 4.9
percent of all executives in Level 3 in line or CFO
positions were women. An average five-year ten-
ure in each level of the hierarchy implies that by
2010 this same 4.9 percent of CEOs or chairmen
of the board would be women. Similar logic sug-
gests that since 6.2 percent of all executives in
Level 4 in line or CFO positions in 2000 were
women, by 2015 we might expect to see this same
percent of executives reach Level 1 in the hierar-
chy.8
These estimates are sensitive to assumptions
about the number of years of tenure in each level
of the hierarchy. If executives have a longer av-
erage tenure of eight years in each level in the
hierarchy for both women and men, executives in
Level 2 (a line position) in 2000 would be pro-
moted to the CEO position in 2008, and execu-
tives in Level 3 in the hierarchy in 2000 would be
in line for the CEO position in 2016. In this case,

1.7 percent of all executives would be women in
2008 (and therefore in 2010). Between 4.9 and
6.4 percent of CEOs would be women in 2016. If
we assume a shorter average tenure of four years in
each level in the hierarchy, the base case esti-
mates given earlier for 2010 do not change, al-
though women would reach these percentages two
years earlier in 2008. The estimates for one year
beyond 2015, however, do change from the base
case. Executives at Level 5 in the hierarchy in
2000 would reach the CEO position in 2016. In
this case, up to 12.8 percent (the proportion of all
executives at Level 5 in 2000) of CEOs would be
women in 2016.9
The foregoing estimates suggest that between
1.7 percent (based only on line and CFO execu-
tives in 2000) and 6.4 percent (including all ex-
ecutive positions) of CEOs and Chairmen of the
Board may be women by 2010. Between 4.9 and
12.8 percent may be women by 2016. This broader
range in the more distant future reflects the fact
that there were more women lower down in the
hierarchy in 2000. Companies therefore will have
a greater pool of women from which to draw for
the CEO position.
Whether one sees the pipeline picture as rosy
or dreary depends on which estimates seem most
realistic. We favor the estimates where only line
and CFO executives are candidates for promotion
to the top. Our base case estimates for this pool
suggest that 4.9 percent of CEOs could be women
by 2010 and 6.2 percent of CEOs could be women
by 2015 (and 2016). These estimates may slightly

underestimate the full pool of CEO candidates,
since firms occasionally promote executives in
other functional areas such as legal or audit to the
CEO position. The speed at which women reach
the top could also be somewhat faster than we
have estimated, particularly if firms promote large
numbers of women from Level 3 positions directly
to the CEO position or if firms promote women
through the executive ranks more quickly than
men.10
Our analysis nevertheless strongly suggests that
while we should expect to see more women at the
top of Fortune 1000 firms, progress will be slow.
The facts simply do not support statements such as
that by James Preston, former CEO of Avon, that
“women are in the pipeline in droves” (Himel-
stein & Forest 1997:64). Indeed, it is difficult to
have a full pipeline of women in line for promo-
tion to CEO when as recently as the year 2000,
8 Having a line or CFO position is probably particularly
important for
promotion from Level 3 to Level 2, since the second-in-
command position
entails line responsibility. Unless women in Level 4 who lack
line or CFO
positions obtain them when they move to Level 3, the
percentage estimates
given in the text for female candidates for Level 1 positions
would not
change.
9 Since Level 5 is relatively low in the hierarchy of top
executives, and
since there are fewer CFO positions at this level, we do not

attempt to
refine the estimates to reflect only line and CFO women at
Level 5 in 2000.
10 The pipeline estimates become complicated if men and
women
move up at a different pace. Differential promotion rates imply
that during
the periods of time when women have been promoted before the
men catch
up, either the total number of executives at each level must
change or the
number (and percentage) of men must decrease to keep the total
number of
executives at each level the same.
almost half of the companies in the Fortune 1000
had no women as top executives at all.
What (If Anything) Explains Differences Between
Firms?
The fact that almost half of the companies had no
women as top executives raises the question: what,
if anything, explains differences between firms in
the representation of women? We considered
three possible explanations that our data enabled
us to examine. First, we assessed whether firms of
different sizes had systematically different repre-
sentation of women. Some prior reports and re-
search have analyzed larger firms that comprise a
subset of our sample, such as the Fortune 100

(Cappelli & Hamori 2004) or the Fortune 500
companies (e.g., the Catalyst reports). We com-
pared these sets of companies with the remainder
of the firms in our larger sample. Second, we
examined differences between industries. Prior re-
search has found that companies in services in-
dustries tend to have greater representation of
women in top management (Cappelli & Hamori
2004; Hillman, et al. 2005; Goodman, Fields, &
Blum 2003). In addition, some CEOs have stated
that companies need women executives in order
to gain the best possible understanding of their
customers. We therefore investigated whether
consumer products companies had greater repre-
sentation of women than other firms. Finally, we
examined whether the total number of executives
reported per firm had a bearing on the reported
representation of women in top management.
Companies differed in the total number of exec-
utives that they reported in the List of Executive
Officers in their 10-K reports and proxy state-
ments. Generally, companies that reported a
greater number of executives also reported more
executives lower down in the executive hierarchy.
Since women tended to cluster at somewhat lower
levels in the executive hierarchy than men, we
investigated whether companies that reported
larger numbers of corporate officers in total also
reported greater representation of women.
With regard to differences in firm size, we
found almost no disparity in the representation of
women between the top and the lower portions of
the Fortune 1000 companies. Women comprised
7.8 percent of executives in the Fortune 100, 8.3

percent in the Fortune 500, and 8.2 percent in the
Fortune 501-1000 companies. These percentages
did not differ significantly statistically between
the companies in the Fortune 500 and those in the
Fortune 501-1000, or between the Fortune 100 and
the Fortune 501-1000.
Unlike the results for firm size, we found large
differences between industries (as classified by
Fortune) in the representation of women. To mea-
sure the extent of these differences, for each in-
dustry we computed the average percentage of
executives per firm that were women and the
average percentage of men. We then calculated
the coefficient of variation (the ratio of the stan-
dard deviation to the mean) across industries for
each of these percentage measures. That coeffi-
cient of variation is 0.46 for women and 0.04 for
men. The difference in these ratios underscores
the large differences between industries in the
representation of women, compared with the min-
imal differences between industries in the repre-
sentation of men. Table 5 reports the ten indus-
tries with the highest mean percentages of women
executives per firm and the ten industries with the
lowest mean percentages. Some of these industries
might accord with general preconceptions of
where women are well or poorly represented, such
as a low representation of women in trucking and
a relatively high representation in soaps and cos-
metics. But we find a few surprises as well. Com-
puter software and transportation equipment are
in the top two industries and furniture is in the
bottom ten.
We also examined whether the representation

of women differed between service industries, con-
sumer products industries, and the remainder of
the industries in the Fortune 1000. The percentage
of executives in each sector who were women was:
9.6 percent in service companies, 8.2 percent in
consumer products companies, and 7.2 percent in
the other industries. An F-test revealed that these
percentages differed significantly statistically at
the 0.001 level. Subsequent t-tests revealed that
the difference between service and all other com-
panies drove these results (significant at the 0.001
level); consumer products companies did not dif-
fer significantly statistically from either the service
or the other industry companies. These results add
further confirmation to the findings of Cappelli
and Hamori (2004), Hillman, et al. (2005), and
Goodman, Fields, and Blum (2003), who also
found greater representation of women in service
industries. Goodman, et al. (2003) proposed that
this finding may reflect the greater value placed
on women’s interpersonal skills in non-manufac-
turing industries.
Next we examined whether companies that
reported having more executives in total also re-
ported greater representation of women in their
executive ranks. Figure 6 displays a plot of the
number of women executives per company against
the total number of executives per company. The
number of women executives per firm appears to

increase modestly as the number of executives per
firm increases. In particular, the figure suggests
that as the number of executives reported per firm
increases, so does the likelihood that the total
includes at least one woman.
Figure 7 displays a plot of the percentage of
executives per firm that were women against the
number of total executives per firm. Notably, the
percentage of women executives decreases as the
number of executives per firm increases. The fact
that the proportion of women falls as the total
number of executives rises suggests the possibility
of “tokenism” with regard to the representation of
women. We know from the raw data that 29
percent of the firms had one woman of executive
rank and only 23 percent of the firms had more
than one woman. Of the latter set, few firms had
more than two women. As Figure 7 demonstrates,
even in the firms with women at the executive
level, the number of women does not increase in
proportion to the total number of executives per
firm. This evidence of tokenism of women in top
management echoes that of Farrell and Hersch
(2005), who found strong evidence of tokenism
on boards of directors. They found that boards
added women when they had low or zero repre-
sentation of women, and sought to attract a new
female board member when a woman left the
board.
Thus far, we have seen that the percentage of
executives who were women differed by industry
of operation and that firms that reported more
women also reported more executives in total. But
how important were these factors relative to one

another, and relative to other factors that might
differentiate firms with regard to the representa-
tion of women? To answer this question, we next
turn to regression analysis, which enables us to
incorporate multiple potential explanatory factors
simultaneously.
Regression Analysis
To measure the representation of women among
top executives, we used two different dependent
variables: the number of executives per firm that
Table 5
Industry Percentages of Executives Who Are
Women
10 Industries with the Highest Percentage of Executives
Who Are Women
Industry
Percentage of
Women
Publishing, Printing 15.8
Transportation Equipment 15.7
Securities 14.8
Health Care 14.6
Temporary Help 14.5
Airlines 13.8
Food Services 13.6
Computer Software 13.4
Soaps & Cosmetics 13.1
Pharmaceuticals 12.5
10 Industries with the Lowest Percentage of Executives

Who Are Women
Industry
Percentage of
Women
Semiconductors 1.3
Energy 2.8
Waste Management 3.6
Trucking 3.8
Aerospace 3.8
Mail, Package, & Freight
Delivery
3.8
Pipelines 3.9
Motor Vehicles & Parts 3.9
Furniture 4.2
Electronics, Electrical
Equipment
4.3
were women and the percentage of executives per
firm that were women. The implication contained
in Figure 7, namely, that the number of women
may be an artifact of company reporting policies,
makes it especially important that we examine the
percentage of executives per firm that were
women. If one of the key ways that firms show
that they have more women among their execu-

tives is by reporting a larger executive team, ana-
lyzing the number rather than the percentage of
executives that are women may be misleading.
We report two sets of regressions, one set per
dependent variable.11 The explanatory variables
include firm-level characteristics as well as vari-
ables that reflect characteristics of the executives
in each firm. Since the regressions use the firm as
the unit of observation, the variables that reflect
executive characteristics are firm-level averages.
The Appendix describes the explanatory variables
and the rationale for their inclusion in the regres-
sions. As a caveat, we do not attribute causation
to the explanatory variables, since our cross-sec-
tional data do not permit us to preclude potential
endogeneity of some of the variables.
Table 6 reports the regression results. The re-
gressions show that an important factor associated
with differences between firms in both the num-
ber and percentage of women is industry of oper-
ation. The industry dummy variables are signifi-
cant as a group: some industries, and therefore the
firms in them, have greater representation of
women than others. This result is consistent with
our earlier analysis that showed substantial differ-
ences in the representation of women across in-
dustries. In the regression for the percentage of
executives that were women, none of the variables
other than industry of operation were significant.
11 For the regression for the number of women per firm, we use
Poisson
maximum likelihood estimation. Poisson estimation is

appropriate when
the dependent variable consists of integers (termed “count
data”), often of
low values (including zeros). We also tested for overdispersion
of the
variance relative to the mean, a potential problem in Poisson
regression,
but found no evidence of such in the regressions reported here.
For the
regression for the percentage of women per firm, we use Tobit
maximum
likelihood estimation. Tobit estimation is appropriate when a
variable is
censored at a lower threshold such as zero, as well as when a
variable also
has an upper threshold, such as for a percentage variable. We
used STATA
to estimate all of the regressions.
Figure 6
Number of Women vs. Total Number of Executives
In the regression for the number of executives who
were women, only three variables were significant
at the .10 level or less (two-tailed test): number of
(male) executives reported, lowest level in the
executive hierarchy reported, and profitability.
As a sensitivity analysis, we assessed whether
firms that had a woman in the top position were
more likely to have greater representation of
women in the remainder of the top executive

team. To conduct this analysis, we excluded
women in Level 1 from the dependent variables
and added an explanatory dummy variable indi-
cating whether or not the firm had any women in
Level 1. The dummy variable for a woman in the
top position was not significant and the other
results did not change.
The regression analysis confirms the results of
the two scatter plots presented earlier in Figures 6
and 7. In the regressions, a greater number of male
executives per firm is associated with an increased
likelihood that we observe a greater number but
not a greater percentage of executives per firm who
were women. Consistent with this result regarding
company reporting policies, the regressions also
show that firms that reported executives lower
down in the hierarchy reported a greater number
but not a greater percentage of executives who
were women. The fact that the total number of
reported executives and the lowest reported level
in the hierarchy is positively associated with a
greater number but not a greater percentage of
women executives per firm again suggests a degree
of “tokenism.” Furthermore, although we find that
greater profitability is associated with a greater
number of women per firm,12 this result does not
hold for the percentage of women per firm. Over-
all, the regressions indicate that when we analyze
the percentage rather than the number of execu-
tives per firm who are women, the significance of
12 Catalyst and Adler (1999) found similar results for the
relationship
between profitability and the number of women executives per

firm using
simple correlations, as did Hillman, et al. (2005) using
regression analysis.
These authors did not analyze the percentage of women
executives per firm.
Figure 7
Percent of Executives Who Are Women vs. Total Number of
Executives
variables other than industry of operation disap-
pears. For this reason, we recommend that future
research on the representation of women pay par-
ticular attention to the percentage rather than the
number of executives per firm who are women.
The regressions further show that characteristics
that differentiated women from men in the Fortune
1000 companies – age, company tenure, and tenure
in current position – did not differentiate firms in
terms of either the number or percentage of execu-
tives who were women. Although the women were
younger and had less company tenure and tenure in
their current positions than the men, this did not
occur because firms with more women had younger
executives, relied more heavily on outside hiring, or
promoted executives more quickly. Instead, the rep-
resentation of women in top management appears to
reflect aggressive promotion and hiring of women
specifically.
Discussion and Conclusion

W
e began this study by asking about the pipe-
line of women to the CEO position. Based
on an extensive data collection effort, we
have provided quantitative estimates of the per-
centage of CEOs that may be women in 2010 and
2016. We estimate that in 2016, between 4.9 and
12.8 percent of CEOs may be women. Within this
range, we believe that a particularly likely esti-
mate is 6.2 percent, because it includes only line
and CFO executives as candidates for the CEO
position. Although low, this estimate is substan-
tially greater than the 1.8 percent of CEOs in the
Fortune 500 who were women in 2005.
We found other promising signs as well. In
companies with women executives, the women
were younger, had less company tenure, and less
tenure in their current positions than the men.
These factors suggest that many companies were
aggressively hiring and promoting women into the
top executive ranks. Moreover, although women
clustered lower down in the executive hierarchy
than men, two-thirds of the women executives
held positions in the two levels just below the
second-in-command. Once women are in the ex-
ecutive hierarchy, they do well in terms of rank.
In order for women to continue to make and
accelerate the sort of progress that our data indi-
cate, they need to reach executive rank in the first
place. Therefore, getting more qualified women

Table 6
Firm-Level Regressions
Dependent Variable Number of Women Per Firma Percentage of
Women Per Firmb
Constant Term �1.055 (0.717) �0.107 (11.007)
Average Age of Male Executives �0.015 (0.013) �0.242
(0.207)
CEO Age 0.006 (0.006) 0.032 (0.092)
Average Years of Company
Tenure of Male Executives
�0.009 (0.008) �0.077 (0.116)
Average Years in Current
Position of Male Executives
�0.025 (0.015) �0.221 (0.248)
Number of Male Executives 0.048 (0.070)*** �0.070 (0.134)
Lowest Level in Executive Hierarchy of
Male Executives
0.093 (0.048)* 0.694 (0.72)
Ratio of Line to Total Positions
of Male Executives
0.056 (0.223) 0.843 (3.326)
Profitability (Return on Sales) 0.007 (0.003)** 0.065 (0.059)
Revenues (logarithm) 0.018 (0.046) 0.862 (0.678)
Industry Dummy Variables Included Included
N�900

Standard errors are in parentheses.
Two-tailed significance levels: *** � � 0.001, ** � � 0.05, *
� � 0.10
aPoisson estimation
bTobit maximum likelihood estimation
into the executive hierarchy is critical. This first
and foremost requires a change in the almost 50
percent of firms in the Fortune 1000 that had no
women at the executive level. These companies
can draw lessons from those companies that have
made advances in this area. Our findings suggest
that companies achieved greater representation of
women in the top executive ranks through aggres-
sive promotion and hiring, policies that compa-
nies lacking women executives could emulate.
Moreover, even companies that had women ex-
ecutives could benefit from additional efforts of
this sort, in light of our findings suggestive of
“tokenism.”
Aggressive promotion and hiring of women
into top management requires a pool of available
talent. Companies cannot simply recruit talented
women from other firms, since eventually this
approach will leave some firms short of talented
women. Companies must further develop and in-
crease the overall pool of talent from which to
draw female executives. This has particular import
for the still low proportions of women in line
positions, which are an important route to the top
of the executive hierarchy. Unless firms find ways

to move women into line positions and retain
them, the route to the top will remain much more
difficult for women than for men.
The extant literature contains many useful
suggestions for developing the pool of women
with top management potential. For example,
providing developmental experience for lower-
level female managers can increase the propor-
tion of women in top management (Powell
1999). Specific approaches that companies can
take to develop the careers of women include:
mentoring (formal and informal); developing
and utilizing women’s networks inside and out-
side of the organization; and creating and im-
plementing leadership development programs
for women (Society for Human Resource Man-
agement 2004). A good deal of research has
documented the importance of mentoring and
networking to the career success of women (e.g.,
Metz & Tharenou 2001), as well as differences
in networking success for men and women (e.g.,
Lyness & Thompson 2000; van Emmerik, Eu-
wema, Geschiere, & Schouten 2006).
A structured hiring and promotion process that
holds decision makers accountable also has less
room for personal biases to affect hiring and pro-
motion decisions (Powell & Butterfield 1994).
This in turn can help to increase the percentage of
top executives who are women (Powell 1999).
Companies therefore can benefit by reviewing hu-
man resources policies and practices to insure that
they are fair and inclusive (Society for Human
Resource Management 2004).

In addition to the indirect steps just men-
tioned, companies can seek to directly increase
the proportion of women who are candidates for
top (and other) management jobs, which is par-
ticularly important when most job incumbents
and applicants are men (Powell 1999). Specific
hiring and promotion policies and processes in-
clude: incorporating the advancement of women
into performance goals for line management;
training line management to raise awareness and
understanding of barriers to the advancement of
women; identifying best practices that support the
advancement of women; tracking the advance-
ment of women in the organization; and develop-
ing a list of women for succession planning (So-
ciety for Human Resource Management 2004).
Representation of women in top manage-
ment is also sensitive to the interest of women
in holding these jobs and in remaining in the
organization if faced with limited career oppor-
tunities (Powell 1999). Support for women with
families, such as flexible work schedules, child
and elder care assistance, and temporary leaves
of absence for family reasons, can increase the
interest of women in holding top management
jobs and in remaining with the organization
(Powell 1999). Having more women in top
management positions also may lead to less
turnover of women at lower levels of the orga-
nization, in part by influencing the perceptions
of women that the organization provides oppor-
tunities for career advancement (Powell 1999;
Cohen & Elvira 1997).
The observation that having women in top

management may lead to more women with
potential for promotion to top management
brings us back to a key conclusion of our anal-
ysis: getting more qualified women into the
executive hierarchy remains a critical priority.
Achieving this goal requires leadership and
commitment from the most senior executives of
business organizations.
APPENDIX
Functional Area and Executive Rank in Hierarchy
Variables
Functional area job responsibilities: One author of
the study assigned each of the job titles and job
responsibilities in the data base to a narrow func-
tional area classification. Many of the executive
biographies contained short descriptions of job
responsibilities, which aided in this coding. A
second author checked these functional area as-
signments for accuracy and differences were re-
solved through discussion. Some executives had
more than one title or job responsibility. Each
title and job responsibility was assigned a func-
tional area, and some executives had responsibil-
ity for more than one functional area within the
firm. In all, we assigned 572 different titles plus
thousands of job descriptions in the database to 18
functional area classifications. In making these
assignments, we relied on our own knowledge
gained from prior research on top executives (Har-

ris & Helfat 1997, 1998; Bailey & Helfat 2003,
2005). Additionally, we consulted several experts
in the various functional areas and in the study of
top management teams to ensure the correct as-
signments of titles and job responsibilities to func-
tional areas. The functional area classifications
that we used are: operations; marketing; sales;
information technology; research and develop-
ment (including new product development); op-
erations support (including engineering and qual-
ity control); legal (including regulatory and
government affairs); secretary; finance; account-
ing; miscellaneous staff (including corporate and
shared services); administration; real estate; sup-
ply chain; customer service; public relations; hu-
man resources; and strategy.
Rank within the Executive Hierarchy per Firm:
After the raw data from the biographies were
entered into the database, we wrote a computer
algorithm to assign ranks within the top exec-
utive hierarchy for each company. We first
ranked all of the 572 distinct titles in the data
base as though every company had every title. A
title of CEO or Chairman was assigned a hier-
archical Level of 1 for the highest ranking of-
ficers. A title of President or COO (Chief Op-
erating Officer) was assigned a Level 2.
President and COO in particular are considered
second-in-command titles (Hambrick & Can-
nella 2004). We consulted with preeminent
scholars of top management teams in assigning
these and other titles to ranks within the exec-
utive hierarchy. A full description of the rank
assigned to each of the titles in the data base is

available from the authors on request.
Next we assigned a preliminary hierarchical
level to each individual in the database, based
on the full ranking of titles. If an individual had
more than one title, the person was assigned the
level for their highest ranking title. We then
sorted the preliminary hierarchical levels by
company. For the individuals that had prelimi-
nary Levels of 1 or 2, in the final within-com-
pany ranking the highest ranking individual(s)
in the company received a Level 1, even if they
did not hold the title of CEO or Chairman,
since not all companies used these titles for
their top ranked executives. (All companies in
our sample had at least one executive with a
title of CEO, Chair, or President, however.)
Some firms did not have a second-in-command
executive. Notably, most of the executives at
Level 1 held multiple titles, often including a
second-in-command title of President or COO.
Some firms leave the second-in-command posi-
tion unfilled and give the title to the top rank-
ing executive, particularly during the early years
of a CEO’s tenure. Later in the top executive’s
tenure, these companies may transfer the sec-
ond-in-command title to a potential successor
to the CEO, who then holds the number 2
position in the company. Because firms some-
times purposely leave the second-in-command
position unfilled, in the final within-company
rankings, we retained the Level 2, even though
some companies had no executives in this po-
sition. Then, beginning with the preliminary
Levels of 3 and greater (meaning lower levels in
the executive hierarchy), we closed up any gaps

in the levels within companies, and re-ranked
titles within companies from Level 3 up to and
including the lowest within-company hierarchy
level reported, which was a Level 7.
Explanatory Variables in the Regressions
The firm-level explanatory variables are: aver-
age age of all male executives, average years of
company tenure of male executives, average years
of tenure in their current positions of male exec-
utives, the ratio of the number of line positions to
the total number of positions held by male exec-
utives, the total number of male executives, the
lowest level in the executive hierarchy held by
men, and dummy variables reflecting industry of
operation (based on a total of 61 Fortune industry
classifications). The rationale for including each
of the explanatory variables is as follows.
Earlier we identified some key differences be-
tween men and women at the executive level. On
average, the women were younger than the men,
had fewer years of tenure within the company and
within their current positions, held lower posi-
tions in the executive hierarchy, and were more
likely to hold staff than line positions. We inves-
tigated whether differences between companies
on these dimensions were correlated with differ-
ences in the representation of women per com-
pany. For example, were women at the executive

level younger than their male counterparts be-
cause companies with greater representation of
women also had younger executives overall? Since
we also found that companies with more women
reported a larger number of executives, and since
the representation of women differed substantially
by industry, we included these factors in our anal-
ysis as well.
Because our dependent variables measure the
representation of women executives at each firm,
we avoided using explanatory variables that would
be influenced by the characteristics of the women
in the executive ranks of each company. This is
particularly important because some of the vari-
ables differed substantially by gender. For exam-
ple, as reported earlier, the ratio of line to total
positions for men is twice that for women. Includ-
ing women in the ratio of line to total positions
per firm causes the ratio to drop substantially
relative to a variable that only includes the men.
If we were to include the women in this explan-
atory variable, we would be regressing the repre-
sentation of women on a variable that reflects the
representation of women– creating endogeneity of
the explanatory variables. To avoid creating this
sort of problem, we expressed the explanatory
variables that reflected the characteristics of ex-
ecutives only in terms of the characteristics of
male executives.13 Since the executive teams in
most companies consist largely of men, these vari-
ables reflect the most common executive charac-
teristics per firm.
In addition to the foregoing variables, we in-

cluded revenues as a control for size of company.
Larger companies may have a larger pool of em-
ployees to draw from, which in turn could influ-
ence the representation of women in top execu-
tive ranks. We included profitability as well,
measured as return on sales (calculated as profits
divided by revenues, using data reported in the
Fortune 2000 survey). Prior research has found
that profitability is positively correlated with the
number of executives who are women (e.g., Adler
1999), although the reasons for this prior finding
and the direction of causation are unclear. Finally,
to account for the possibility that the CEO may
play a key role in determining the representation
of women in his or her top executive team, we
included a variable associated with individual
CEOs. We used the age of the CEO on the theory
that younger CEOs might be more used to work-
ing with women and perhaps more likely to pro-
mote women to the top executive ranks.14 Table
A1 provides descriptive statistics for all of the
variables in the regressions. Since we have missing
observations for some variables, the means re-
ported in Table A1 for the number and percentage
of women per firm differ slightly from those re-
ported earlier for the full sample.
13 A sensitivity analysis that included both female and male
executives
in these variables revealed noticeable changes in some of the
regression
coefficients, in a direction consistent with endogeneity. This
further con-
firmed our decision to exclude female executives from the
explanatory
variables in the regressions.

14 If a firm had more than one executive in Level 1, we used
the
average age of the Level 1 executives in the firm.
Acknowledgements
We received very helpful comments on an earlier draft of
this paper from Peter Cappelli and an anonymous reviewer.
We are also grateful to our many research assistants: Ashley
Nowygrod, Igor Fuks, Marcella Gift, Patrick Jou, Jesse
Kiefer, Raina Kim, Stanley Kim, Jennifer Lee, Seungyeon
Lee, Veronica Mendez, Pierre Nguyen, Mark Permann, and
Marcia Sajewicz.
References
Adler, R. D. 1999. Women in the Executive Suite Correlate
to High Profits. Pepperdine, CA: Evergreen Project on
Equal Pay.
Bailey, E. E. & Helfat, C. E. 2003. External management
succession, human capital, and firm performance: An
integrative analysis. Managerial and Decision Economics,
24: 347–369.
Bailey, E. E. & Helfat, C. E. 2005. External succession and
disruptive change: Heirs-apparent, forced turnover and
firm performance. Strategic Organization, 3(1): 47– 83.
Bertrand. M. & Hallock, K. F. 2001. The gender gap in top
corporate jobs. Industrial and Labor Relations Review,
55(1): 3–12.

Bureau of Labor Statistics. 2003. Current Population Sur-
vey. Washington, DC: U.S. Government Printing Of-
fice.
Cappelli, P. & Hamori, M. 2004. The path to the top:
Changes in the attributes and careers of corporate exec-
utives, 1980-2001. Working Paper 10507: National Bu-
reau of Economic Research.
Catalyst. 1998. Catalyst census of women corporate officers and
top earners of the Fortune 500. New York: Catalyst.
Cohen, L. & Elvira, M. 1997. The effects of organizational
sex composition on the turnover of men and women: Is
leaving just the same? Presented at the annual meeting
of the Academy of Management, Boston.
Daily, C. M., Certo, S. T., & Dalton, D. D. 1999. A decade
of corporate women: Some progress in the boardroom,
none in the executive suite. Strategic Management Jour-
nal, 20(1): 93–99.
Dutton, J. E. & Duncan, R. B. 1987. The creation of
momentum for change through the process of strategic
issue diagnosis. Strategic Management Journal, 8: 270 –
295.
Farrell, K. A. & Hersch, P. A. 2005. Additions to corporate
boards: The effect of gender. Journal of Corporate Fi-

nance, 11: 85–106.
Finkelstein S. & Hambrick, D. C. 1996. Strategic
leadership: Top executives and their effects on organi-
zations. Minneapolis/St. Paul: West Publishing Com-
pany.
Goodman, J. S., Fields, D. I, & Blum, T. C. 2003. Cracks in
the glass ceiling: In what kinds of organizations do
women make it to the top? Group & Organization Man-
agement, 28: 475–501.
Hambrick, D. C. & Cannella, A. A. 2004. CEOs who have
COOs: Contingency analysis of an unexplored structural
form. Strategic Management Journal, 25(10): 959 –979.
Table A1
Descriptive Statistics for Regression Variables
Variable Name Mean
Standard
Deviation Minimum Maximum
Number of Female Executives Per Firm 0.872 1.093 0.0 7.0
Percentage of Female Executives Per Firm 7.927 9.570 0.0 60.0
Average Age of Male Executives Per Firm 50.972 3.702 37.25
65.333
CEO Age 55.648 7.359 34.0 85.0
Average Years of Company
Tenure of Male Executives
10.871 5.959 1.0 41.0
Average Years in Current
Position of Male Executives

3.692 2.746 0.0 25.0
Number of Male Executives
Per Firm
9.696 4.790 2.0 50.0
Lowest Level in Executive Hierarchy of
Male Executives
4.394 0.860 2.0 7.0
Ratio of Line to Total Positions
of Male Executives
0.492 0.177 0.0 1.0
Firm Profitability (Return on Sales) 4.870 10.449 �93.230
131.020
Firm Revenues (logarithm) 8.252 0.965 7.058 12.150
Number of observations � 900
Hambrick, D. C. & Mason, P. A. 1984. Upper Echelons:
The Organization as a Reflection of Its Top Managers.
Academy of Management Review, 9: 193–206.
Harris, D. & Helfat C. E. 1997. Specificity of CEO human
capital and compensation. Strategic Management Journal,
18: 895–920.
Harris, D. & Helfat, C. E. 1998. CEO duality, succession,

capabilities and agency theory: Commentary and re-
search agenda. Strategic Management Journal, 19: 901–
904.
Hayward, M. L. A., Rindova, V., & Pollack, T. G. 2004.
Believing one’s own press: The causes and consequences
of CEO celebrity. Strategic Management Journal, 25(7):
637– 653.
Hillman, A. J., Shropshire, C., & Cannella, A. A. 2005.
Organizational predictors of women in top management
teams and corporate boardrooms. Working Paper, Ari-
zona State University.
Himelstein, L. & Forest, S. A. Breaking through. Business
Week. 3 February 1997, 64.
Hitt, M. A., Bierman, L., Shimizu, K., & Kochhar, R. 2001.
Direct and moderating effects of human capital on strat-
egy and performance in professional service firms: A
resource-based perspective. Academy of Management
Journal, 44(1): 13–28.
Hymowitz, C. & Schelhardt, T. D. The glass ceiling. Wall
Street Journal Special Report on Corporate Women. 24
March 1986.
Kanner, B. 2004. Pocketbook power. New York: McGraw-
Hill.
Kirchmeyer, C. 1998. Determinants of managerial career
success: Evidence and explanation of male/female differ-
ences. Journal of Management, 24(6): 673– 692.
Lyness, K. S. & Thompson, D. E. 2000. Climbing the
corporate ladder: Do female and male executives follow

the same route? Journal of Applied Psychology, 85(1):
86 –101.
Metz, I. & Tharenou, P. 2001. Women’s career
advancement: The relative contribution of human and
social capital. Group & Organization Management, 26(3):
312–342.
Miller, C. C., Burke L. M., & Glick, W. H. 1998. Cognitive
diversity among upper-echelon executives: Implications
for strategic decisions. Strategic Management Journal,
19(1): 39 –58.
Morrison, A. & Von Glinow, M. A. 1990. Women and
minorities in management. American Psychologist, 45:
200 –208.
Powell, G. N. 1999. Reflections on the glass ceiling: Recent
trends and future prospects. In G. N. Powell (Ed.), Hand-
book of Gender & Work (pp. 325–345). Thousand Oaks,
CA: Sage Publications.
Powell, G. N. & Butterfield, D. 1994. Investigating the
“glass ceiling” phenomenon: An empirical study of ac-
tual promotions to top management. Academy of Man-
agement Journal, 37: 68 – 86.
Richard, O. C., Barnett, T., Dwyer, S., & Chadwick, K.
2004. Cultural diversity in management, firm perfor-
mance, and the moderating role of entrepreneurial ori-
entation dimensions. Academy of Management Journal,
47(2): 255–266.
Society for Human Resource Management, 2004. The glass
ceiling: Domestic and international perspectives. HR
Magazine, 2004 Research Quarterly, 49:2–10.

Valcour, P. M. & Tolbert, P. S. 2003. Gender, family and
career in the era of boundarylessness: Determinants and
effects of intra- and inter-organizational mobility. Journal
of Human Resource Management, 14(5): 768 –787.
Van Emmerik, I. J. H., Euwema, M. C., Geschiere, M., &
Schouten, M. F. A. G. 2006. Networking your way
through the organization: Gender differences in the re-
lationship between network participation and career sat-
isfaction. Women in Management Review, 21(1): 54 – 66.
Watson, W. E., Kumar, K., & Michaelsen, I. K. 1993.
Cultural diversity’s impact on interaction process and
performance: Comparing heterogeneous and diverse task
groups. Academy of Management Journal, 36(3): 590 –
602.
Zelechowski, D. D. & Bilimoria, D. 2003. The experience of
women corporate inside directors on the boards of For-
tune 1,000 firms. Women in Management Review, 18(7):
376 –381.

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