Fear of flying?--economic analyses of airline safety

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WORKING PAPER
ALFRED P. SLOAN SCHOOL OF MANAGEMENT

FEAR OF FLYING? ECONOMIC ANALYSES
OF AIRLINE SAFETY

by

Nancy L. Rose
MIT Sloan School of Management

WP#3321-91-EFA

June 1991

MASSACHUSETTS

INSTITUTE OF TECHNOLOGY

50 MEMORIAL DRIVE

CAMBRIDGE, MASSACHUSETTS 02139

FEAR OF FLYING? ECONOMIC ANALYSES
OF AIRLINE SAFETY

by

Nancy L. Rose
MIT Sloan School of Management

WP#3321-91-EFA June 1991

FEAR OF FLYING? ECONOMIC ANALYSES OF AIRLINE SAFETY

Nancy L. Rose

Associate Professor of Applied Economics
MIT Sloan School of Management and NBER

June 1991

This paper was prepared for a Journal of Economic Perspectives
symposium on the airline industry.

MAR 3 0 1992

FEAR OF FLYING? ECONOMIC ANALYSES OF AIRLINE SAFETY

ABSTRACT

The safety of the conunercial airline industry has attracted considerable
public attention and debate since economic deregulation of the industry in 1978.
These concerns have energized economic research on three aspects of airline
safety. First, has the level of airline safety declined since deregulation?
Research on this topic investigates whether heightened public concerns about air
safety derive from objective increases in accident risks. Second, what accounts
for differences in safety performance across carriers? This literature analyzes
heterogeneity in carriers' safety records as a means of learning about factors
that influence safety performance. Third, how do markets respond to airline
accidents? This work explores the effectiveness of market incentives in
constraining the safety provision of firms. This paper describes our progress
in answering each of these queries .

Professor Nancy L. Rose
MIT Sloan School of Management
50 Memorial Drive, Room E52-434
Cambridge, MA 02139

The safety of the commercial airline industry has been of
long-standing interest to policy-makers and the general public.
This issue attracted particular attention in the wake of airline
deregulation, amid growing concerns that the historical
superiority of U.S. jet carriers' safety records may have been
inextricably linked to economic regulation of the industry by the
Civil Aeronautics Board. After all, economists argued that the
suppression of price competition led airlines to focus on service
competition, and public perceptions of service quality suggest
substantial reductions in at least some dimensions. Perhaps less
observable dimensions of product quality, such as safety, have
experienced equivalent or greater declines. If this were the
case, traditional measures of welfare gains from deregulation
could be greatly exaggerated.

These worries have energized economic research on a broad
range of issues relating to airline safety. Three questions have
attracted the most attention from economists. First, has airline
safety declined since deregulation? Research on this topic
investigates whether heightened public concerns about air safety
derive from objective increases in accident risks. Second, what
accounts for differences in safety performance across carriers?
This literature analyzes heterogeneity in carriers' safety
records as a means of learning about factors that influence
safety performance. It extends the before-and-after deregulation
research by examining through what links, if any, we might expect
economic regulation to affect aggregate safety. Third, how do
markets respond to airline accidents? This work explores the

effectiveness of market incentives in constraining the safety
provision of firms. If consumers and insurance companies
penalize airlines with worse safety records, carriers may be
disinclined to reduce safety investment, even if regulatory
changes would permit them to do so. I describe below our
progress in answering these queries.

1. Has airline safety declined since deregulation?

Aggregate statistics on U.S. airline safety provide
reassurance for travellers concerned that deregulation increased
the risks of air travel. Virtually all measures of accident or
fatality risk suggest that the long-term trend toward increased
airline safety has continued since economic deregulation of the
airline industry in 1978. This is illustrated in figure 1, which
plots the number of aircraft accidents per million departures for
large U.S. scheduled air carriers over the period 1955-1990.^
Both total and fatal accidents per million departures declined
substantially, although there is considerable variation in
accident rates from year to year.

There is little evidence that improvements in airline safety
have slowed appreciably since deregulation. Observed accident
rates since 1978 conform closely to those predicted by a trend
estimated over the 1955-1977 data, as illustrated in figure 2.
More formally, regression analysis of the log of accident rates

^ Referred to as "Part 121" carriers, these are carriers that
operate aircraft with capacity in excess of 60 seats. These
carriers currently operate primarily jet aircraft fleets.

on a time trend indicates that the coefficients on either a
deregulation dummy variable or a variable measuring time since
deregulation are insignificantly different from zero.^ Figure 2
does, however, suggest some scope for caution. Accident rates
over the last four years (1987-1990) lie slightly above trend.
There is not enough data to determine whether this reflects
normal variation in observed accident rates over short time
horizons or an elevation of the true underlying risk, nor is it
obvious that effects that do not materialize until ten years
after deregulation should be attributed to regulatory changes
rather than to some other cause. Nevertheless, these data may
suggest continued scrutiny of aggregate safety performance over
the next few years.

Passenger fatality rates also exhibit continued improvement
after deregulation. For example, Barnett and Higgins (1989)
calculate that fatality risks for passengers on U.S. domestic jet
airline flights declined from an average of 1 in 2.5 million
flights over 1971-78 to 1 in 7.4 million flights over 1979-86.
They argue, however, that the decline in risk would have been
even greater, but for the entry of new jet carriers post-1978.
As evidence, they separate the U.S. carriers into "established
carriers" (trunk and local service airlines existing as of 1978)
and new entrants (a group of 19 "jet children" of deregulation,

2 Rose (1989) presents results for 1955-1986 data; my updates
based on the 1955-1990 data yield similarly insignificant results.
This conclusion is reinforced by an analysis of the time fixed
effects (1958-1986) from the model of airline specific accident
counts in Rose (1990).

most now out of business) . For 1979-86, fatality risk for
passengers on established carriers averaged 1 per 11.8 million
flights. In contrast, the group of entrants Barnett and Higgins
analyze had an aggregate fatality risk of 1 per 870,000 flights!
This does not imply that the planes of the entrant carriers were
continually dropping out of the sky, however: only 3 of the 19
carriers had any domestic passenger fatalities during the 7 year
period, and these had just one fatal accident each. The high
risk arises from the fact that the entrants carried relatively
few passengers. The robustness of this conclusion and the safety
records of entrants will be discussed further when we analyze
differences in safety performance across carriers.

Analyses of the causes of airline accident rates can shed
additional light on the effects of deregulation. If deregulation
induced carriers to cut maintenance activities, for example, one
might expect to observe more accidents due to equipment failure.
Accidents due to pilot error should increase if airlines
compromised safety by hiring less experienced pilots, reducing
training, or working pilots harder. If increased congestion,
combined with the reductions in air traffic control (ATC) staff
after the 1981 controllers strike, degraded the air traffic
control system, accidents resulting from ATC errors or
interference by other aircraft should become more common.

To test whether deregulation has had these effects, Oster
and Zorn (1989) analyze National Transportation Safety Board
(NTSB) Accident Briefs for scheduled domestic passenger service

accidents over the 1971 through 1985 period. For each accident,
they select as the "primary cause" the event or action that
initiated the sequence of events culminating in the accident.-^
These causes are then grouped into categories that might be
sensitive to deregulation-induced changes, such as Pilot Error,
Equipment Failure, Air Traffic Control Error, and Other Aircraft
(General Aviation) , and categories that are unlikely to be
influenced by deregulation, including Weather, Seatbelt Not
Fastened, and Other. Between the regulated (1970-78) and
deregulated (1979-85) periods, total accidents per million
departures for trunk and local service carriers declined by 54%.
Accident rates due to equipment failure, pilot error, ATC error,
and other aircraft declined by this amount or more, topped by a
71% reduction in accidents initiated by equipment failures. This
suggests a relative decrease in accidents due to causes under a
carrier's control after deregulation.

Further evidence on the changes in maintenance practices and
their effects on safety since deregulation is provided by
Rennet's (1990) study of jet engine maintenance histories.
Kennet analyzes complete aircraft engine histories for 42 Pratt
and Whitney jet engines, operated by 7 different airlines. He
finds that the length of time between maintenance shop visits has
increased since deregulation, but that deregulation has had no

' Because their criterion differs from that used by the NTSB,
their distribution of accidents by cause differs from the NTSB
distribution. Broadly similar conclusions are reached by Morrison
and Winston (1988) , who analyze the distribution of fatal accidents
using NTSB causes.

effect on the probability of an engine shutdown. This may
reflect a drive toward more efficient maintenance policies and
practices in the wake of deregulation. The result that engine
shutdown probabilities have been unaffected suggests that these
maintenance changes have not compromised air safety, consistent
with Oster and Zorn's report of substantial relative declines in
accidents initiated by equipment failure.
Indirect effects of deregulation on travellers^ safety

There are a number of indirect channels through which
deregulation may have influenced safety. First, the shift from
jet airline to commuter airline service in many small communities
may have increased risks for passengers on these routes. Second,
increased reliance on hub-and-spoke networks may have increased
the average number of stops or plane changes passengers must
make. Since accident risks are roughly proportional to the
number of take-offs, this would tend to increase passengers'
risks per trip (origin-destination) . Third, the introduction of
price competition and service improvements may induce travellers
to substitute air travel for auto travel. Since the risk of a
highway accident substantially exceeds that for air travel over
even moderate distances, this substitution would enhance
travellers' safety.

Substitution of commuter service: By eliminating explicit
cross-subsidization and easing entry and exit restrictions,
airline deregulation may have encouraged established jet carriers
to abandon uneconomic service to small communities. While most

of these communities retain air service, it now typically is
provided by commuter carriers. Because commuter airlines have
higher accident rates than jet airlines, risks to travellers in
these communities may have increased. For example, over 1979-

1985, passenger fatalities were .38 per million passengers
enplaned on trunk airlines, but 1.27 per million passengers
enplaned on commuter airlines — more than three times greater for
commuters (Oster and Zorn, 1989) .

These simple comparisons may substantially overstate the
change in risk, however (Oster and Zorn, 1989) . First, the
largest commuter airlines are much safer than the smaller
commuters, and these are the ones that typically have replaced
jet carriers. The top 2 0 commuters, for instance, had passenger
fatalities of .67 per million enplanements, roughly half the risk
for commuters overall.^ Second, service substantially improved
on the routes where commuters replaced jets, with fewer inter-
mediate stops and more weekly departures. In a sample of 60
city-pair markets where commuters replaced jets between 1978 and

1986, the average number of intermediate stops fell by half (from
.59 to .30; see Oster and Zorn, 1989). Re-scaling the fatality
risk to reflect total risk per passenger trip on these routes
yields a risk of .60 per million trips for jet carriers (.38

* There have been no studies that look at commuter safety
under codesharing arrangements with major carriers (see Borenstein,
1991, for a discussion of codesharing) . Given the increased
scrutiny that codesharing imposes upon the commuters, it is likely
that their safety record is even better than implied by size alone.

fatalities per million enplanements times 1.59 average take-offs)
compared to a risk of .87 for the large commuters (.67 fatalities
per million enplanements times 1.30 average take-offs). While
the commuter risks are higher, the differences are less stark
than implied by the initial comparison.

Finally, the average weekly departures in these 60 markets
more than doubled after commuters took over service (from 2.88 to
6.29). The increased frequency of service appears to be
associated with increased ridership, at least part of which
reflects a switch from cars to planes for some travellers. Oster
and Zorn (1989) estimate the auto fatality rates in these markets
to lie between 1.9 and 2.3 per million passenger trips. Since
this is substantially greater than the risk for the larger
commuter airlines, the modal switch enhances overall safety for
these travellers.

Increases in the average number of stops per trip; The
second potential indirect effect of deregulation, possible
increases in the number of stops or plane changes passengers must
make en route to their final destination, has not been well-
documented. While the development of hub-and-spoke networks may
substitute one-stop or one-change service for nonstop service in
outlying markets, it is likely to increase nonstop service
availability for passengers travelling to and from the hub. The
net impact on average stops cannot be predicted a priori.

Some evidence on this effect is provided by Borenstein
(1991). He finds an increase in the number of passenger trips

8

that involve a change of plane, from 27.3% of trips in 1978 to
32.8% in 1990. If all remaining passengers flew nonstop, the
average number of flights per trip would have increased by 4.3%
over this period (from 1.273 to 1.328). While this increases air
travel risks, the overall impact is not substantial. The average
total (fatal and nonfatal) accident rate per million flights
declined by 54% between the 10 years prior to deregulation and
the 10 years after deregulation. Adjusting for a 4% increase in
average flights per trip reduces the effective decline to 52%.

In fact, direct (no change of plane) service includes both
nonstop and one- (or multi-) stop flights. Because there have
been no studies of the change in the average number of stops for
these passengers, we cannot determine the overall change in
average departures per trip. Based on the results for the change
of plane statistics, however, failure to account for this seems
unlikely to alter the basic conclusion.

Shifting traffic from highways to air; The lower average
fares and the widespread adoption of discount fares and
sophisticated price discrimination schemes that resulted from
deregulation substantially increased air travel. Between 1975
and 1985, domestic passenger enplanements for the largest U.S.
carriers grew at a rate of 6.6% per year and domestic revenue
passenger-miles (RPMs) grew at 7.5% per year. Some of this
increase represents new travel, that is, trips that otherwise
would not have taken place. Some of the increase represents a
shift from other modes of travel, such as automobile, rail, or

bus.

It is difficult to determine the precise extent to which
travellers have shifted from automobile travel to air travel as a
result of airline deregulation. Using annual aggregate data on
passenger car miles travelled and a dummy variable for airline
deregulation, McKenzie and Warner (1988) estimate a decline of
nearly 4% in passenger car miles as a result of airline
deregulation, or an average reduction of 43 billion car miles
annually during the 1979-85 period. They conclude that this
reduction in auto miles corresponds to roughly 1700 fewer auto
fatalities per year. If the average auto occupancy rate for
intercity traffic is 2.0, a shift of 43 billion car miles to air
travel would imply an increase of 86 billion passenger miles for
airlines. The number of air fatalities associated with this
amount of air travel averages about 41. A shift of this
magnitude from highway to air would have an enormous net savings
in lives: more than 1650 per year. Is this a credible estimate?

Airline RPMs increased by roughly 70 billion between 1975
and 1980, or 140 billion between 1975 and 1985. If the estimated
shift in highway travel is correct, the bulk of the increase in
air RPMs comes from displaced auto trips. This seems implausibly
large. Unfortunately, we do not have better estimates of the
true magnitude of the modal shift. Even if the effect is only
one-fifth as large as McKenzie and Warner estimate, however, more
than 300 lives would be saved each year by the shift to air

10

travel — more than the total U.S. airline passenger fatalities in
any of the last 10 years.

2. What accounts for differences in accident rates across
carriers?

Against the backdrop of substantial declines in aggregate
accident rates over time lie wide variations in accident rates
across individual carriers within any time period. Figures 3 and
4 illustrate this in histograms of total accident rates per
million departures for a sample of major airlines over the 1971-
75 and 1981-85 periods, respectively.^ The wide variation in
individual accident rates is not entirely surprising: given the
discrete and infrequent nature of accidents, one additional
accident in a five year period can generate an enormous increase
in a typical airline's accident rate per million departures.
This raises the question: do these statistics reflect expected
random fluctuations around a common mean accident rate or more
systematic differences in behavior and subsequent safety
performance across airlines?

Economists have concentrated their efforts to model
differences in carriers' safety records in three areas: the
impact of airlines' financial condition on their safety
performance, variations in safety performance between entrants

^ These plots are based on data for a sample of 35 large
airlines, as reported in Rose (1990) . The 1981-85 plot omits World
Airlines, which had two accidents and an accident rate of more than
51 per million departures. The next highest accident rate was 12.5
per million departures.

11

and established carriers, and the determinants of higher accident
rates for commuter carriers relative to jet airlines.
Financial impacts on airline safety

The potential impact of financial pressures on airlines'
safety performance has provoked a long-standing debate in policy
circles and attracted particular attention since deregulation.
The argument that competition has reduced profit margins and
forced carriers to "cut corners" on safety has been one of the
key weapons in the arsenal of re-regulation advocates. A variety
of economic models can generate predictions consistent with a
financial link to safety, including models of reputation
formation under asymmetric information, liquidity constraints on
investment behavior, and firm decision-making near bankruptcy.
None of these models implies that such a link must exist,
however, leaving the resolution of this debate to empirical
tests.

Early studies, typically based on short time series for
small cross sections of carriers (or industry aggregate time
series regressions) , detected no significant relationship between
financial variables such as profitability and airline accident
rates. For example, Golbe (1986), who looked at cross-sections
of 11 domestic trunks over the 1963-66 and 1967-70 periods, found
an insignificant positive relation between profitability and
accident rates. These studies share a common shortcoming,
however: the infrequent nature of airline accidents combined
with their small sample sizes may limit the power of their

12

statistical tests.

Analyses of more extensive data sets and alternative safety
measures find evidence that lower profit margins are associated
with worse safety performance, at least for some groups of
carriers. Rose (1990) explored the determinants of airline
safety performance for a panel of 35 part 121 U.S. carriers over
1957-1986. In the full sample, higher operating profits were
associated with lower accident rates in the following year. A 5
percentage point increase in the operating margin (e.g. from 5%
to 10%) implies about a 5% reduction in the total accident rate
and more than a 15% reduction in the fatal accident rate, other
things equal. This result for total accidents is replicated by
Evans (1989) in a study of accident rates for nearly 100 carriers
over 1970-87.

These average effects may themselves mask important
differences across carriers in the sensitivity of safety
performance to profitability changes. Rose's data suggest that
profitability effects may be strongest for the smaller and mid-
size carriers in the sample, and may not be important for the
very largest carriers studied. This pattern is particularly
clear in the analysis of airline incidents, in which higher
profits are associated with lower reported incidents for small
and mid-size carriers, but higher incident rates for the very
largest carriers. A 5 percentage point increase in the operating
margin implies about a 20% reduction in reported incidents for
the smallest carriers in the sample and a 10% - 12% reduction for

13

mid-size carriers.

The strength of the profitability-safety link for the small
and mid-size carriers may indicate greater flexibility in these
firms' safety investment choices. A number of factors could make
the safety investment levels of large firms less variable:
public information about underlying safety levels may be better
for the largest airlines (reducing information asymmetries) ,
large airlines may have better access to capital markets or
"deeper pockets" for internal financing, and FAA regulators may
more closely scrutinize these carriers. This heterogeneity also
may help to explain why the earlier studies, which tended to
focus only on the very largest (trunk) carriers, failed to detect
a link between profitability and safety performance.

A significant remaining gap in our analysis of financial
influences on safety is an understanding of the profitability
effects for the very smallest air carriers in the industry;
commuter carriers. While recent studies include a much broader
range of carriers than had previously been studied, they continue
to be limited to "jet" (Part 121) carriers due to the lack of
reliable financial data for commuter (Part 135) carriers.
Anecdotal evidence suggests that commuters may be quite sensitive
to financial pressures, and the argioments raised above for the
smaller jet carriers would seem to apply even more strongly to
commuters. Decisive conclusions about this segment of the
industry must await further data and study, however.
New entrant safety performance and the role of experience

14

A major concern after deregulation was the safety
performance of new entrants into the airline industry. Barnett
and Higgins' (1989) conclusion that entrant carriers were
substantially more risky than established carriers in terms of
passenger fatalities heightens this concern. The empirical
evidence on this issue is somewhat mixed, however. The relative
riskiness of entrants appears sensitive to the measures of safety
performance employed in the study, and also may depend on the
definition of entrant carriers and identities of the firms
included in the sample.

The most thoroughly studied measure of safety performance
for new entrants is total accidents per million aircraft
departures. Virtually all analyses using this measure of safety
indicate that entrants do not perform significantly worse than
established carriers (e.g., Kanafani and Keeler, 1989; Oster and
Zorn, 1989; and Evans, 1989). Kanafani and Keeler (1989), for
example, find that identifying a carrier as an entrant does not
add significant explanatory power to a regression model of total
accident rates over 1982-85, perhaps in part because of the
enormous variability in accident rates across the 25 entrants in
their sample. Evans (1989) argues that entrants appear to have
lower accident rates than established carriers, other things
equal. His analysis of 105 carriers over 1971-1987 suggests that
post-deregulation entrants have accident rates that are roughly

15

half those of established carriers, other things equal. ^ This
result is not sensitive to whether the entrants are defined as
completely new airlines or include carriers that previously
provided intrastate or charter service. Evans argues that this
result may reflect more intense regulatory scrutiny of airlines
newly certified in interstate service.

The general conclusion that entrant safety performance does
not significantly differ from that of established carriers holds
across a wide variety of safety measures. Oster and Zorn (1989)
find no significant differences between trunks and "other jet
carriers" for five of six aggregate safety measures over 1979-85,
including passenger fatalities and passenger injuries per million
enplanements, and total accidents, serious injury accidents, and
minor accidents per million aircraft departures. Their group of
"others" corresponds to the broadest definition of entrants used
in the literature. Kanafani and Keeler (1989) report no
significant difference in FAA inspection ratings for new entrants
under the National Air Transportation Inspection program and some
evidence that new entrants have lower near mid air collision
reporting rates than do established carriers (though the latter
may reflect differences in reporting incidence rather than

^ The relative accident rate for entrants in Evans's study
should be calculated as exp(NEW - DEREG) , where NEW is a dummy
variable for new entrants (estimated at about -1.3) and DEREG is a
dummy variable for established carriers post-1978 (estimated at
about -.50). This calculation yields the value .44, implying that
entrant accident rates are 44% of established carrier accident
rates, other things equal. Note that this is not the calculation
apparently reported by Evans.

16

differences in occurrence rates) .

The dominant exceptions to this sanguine view of new
entrants are based on analyses of fatal accident rates. In
addition to the Barnett and Higgins (1989) analysis discussed
earlier, Oster and Zorn (1989) report that entrants (their "other
jet carriers") had a substantially higher aggregate rate of fatal
accidents per million departures over 1979-85 (.90 v. .22 for
trunk and local service carriers) . As noted earlier, this poor
aggregate performance masks substantial heterogeneity across
carriers, with most entrants massed at zero fatalities and a few
extreme outliers pulling up the aggregate fatality rate.

Unfortunately, there have been no carrier specific analyses
of fatal accident rates to discern the sensitivity of the
conclusions to this heterogeneity or to the definition of entrant
airlines. For example. World Airlines, which had two accidents
and a fatal accident rate of 51 per million departures over 1981-
85, is included as an entrant in studies of entrant fatality
risk. While the airline was new to scheduled interstate service,
it had been operating charter service prior to deregulation.
Should World be grouped either with People Express, which entered
airline service de novo after deregulation, or with Pacific
Southwest Airlines, which had provided California intrastate
service since 1948? In most studies, "entrants" are defined to
include all of these types of carriers.

To understand which firms can be meaningfully grouped
together, we must first understand the possible underlying causes

17

of the entrant results. This is difficult to do with either
aggregate analyses or simple dummy variable regressions of
carrier differences. Unfortunately, few studies have attempted
to move beyond these approaches. Oster and Zorn (1989) report
that entrants as a group have a higher total accident rate
attributable to pilot error (.60 per million departures, compared
to .16 for trunks). This might be consistent with entrants'
pilots being on average less experienced or less well-trained,
either overall or relative to their new positions. Rose (1990)
provides evidence of some general learning-by-doing effects on
safety performance. For total accident rates, airline operating
experience has at most a weak negative effect, which vanishes in
specifications that control for a carrier's average accident
rate. For both fatal accidents and total incidents, however,
experience exerts a strong, statistically significant negative
effect: more experienced airlines have fewer fatal accidents and
fewer incidents, other things equal. Although these estimates
are not based solely on entrant performance, the results are
broadly consistent with studies that find no significant entrant
effect for total accident rates, but worse entrant performance on
fatal accidents. Additional investigation is required to
develop a better understanding of other sources of the apparent
differences in safety performance between entrants and
established carriers.
Commuter carriers

Commuter airlines, as a group, have substantially higher

18

accident and fatality rates than do jet carriers. The
implications of this observation depend critically upon the
source of these differences. For example, if commuter airlines
invest less in safety, other things equal, then more rigorous FAA
regulation of their safety practices would tend to improve their
safety records.^ Such regulation will have little effect if the
disparities arise from inherent differences in equipment
reliability (e.g., smaller, propeller aircraft are more prone to
failure, even when optimally equipped and maintained) or airport
facilities (e.g., commuters are more likely to serve airports
that lack advanced navigational aids or offer more hazardous
operating conditions) . Similarly, if most of the performance
differences are attributable to route rather than carrier
conditions, then sxibstituting one type of carrier for another on
a given route is unlikely to have much impact on safety.

Discerning the relative importance of carrier and route
conditions on commuter safety records would be difficult under
any circumstances. This task is further impeded by the dearth of
reliable, detailed firm level data for this segment of the
industry. Nevertheless, there is suggestive evidence that
carrier investment has a substantial impact on safety performance
in this sector. First, commuters that were part of the Allegheny
(USAir) commuter system had an overall safety record that matched
the jet carrier safety record over the 1970-80 period, despite

^ Whether this is socially optimal depends on whether
commuters currently underprovide safety.

19

substantially higher accident rates for the commuter industry as
a whole (Meyer and Oster, 1987) . This is unlikely to be solely
attributable to differences in the routes and equipment of these
firms.

Second, in 1978 the FAA substantially tightened commuter
safety regulations, increasing pilot qualification, crew
training, and maintenance requirements (particularly for larger
commuter aircraft) , and specifying for the first time minimum
equipment lists for commuter flights. This appears to have had a
dramatic impact on aggregate commuter safety. The commuter
passenger fatality rate per million enplanements declined by more
than half between 1970-78 and 1979-85, with the bulk of the
decline occurring in accidents caused by equipment failure, pilot
error, and weather (the latter presumably influenced by both
enhanced pilot certification and training requirements and
equipment rules governing instrument flight rule operations; see
Oster and Zorn, 1989) . Since commuter regulations remain less
stringent than those for jet carriers, additional improvements in
safety are likely to be possible — although whether these would
be welfare enhancing remains unknown.

3 . How do markets respond to airline accidents?

For air travellers, safety is an important aspect of product
quality. Unlike other characteristics of product quality, such
as schedule convenience, crowding, and on-board service,
consumers have difficulty observing air carrier safety levels

20

when they make their travel decisions. As in other markets where
consumers cannot observe or evaluate product characteristics,
there is reason to suspect that the market may supply less safety
than consumers would demand if fully informed. Concern with
potential market failure has led to a complex web of government
regulations that specify minimum safety input and performance
standards for air carriers. Airlines' and aircraft
manufacturers' reputations may provide an alternative (or
complementary) mechanism for insuring adequate safety provision.
If these are effective checks on behavior, we should observe
market penalties for firms that deviate from their established
reputations. This notion has given rise to a substantial
economics literature that evaluates market responses to air
carrier accidents.

We can analyze market responses to airline accidents from
two perspectives. First, does the market penalize aircraft types
involved in an accident: what is the effect of an accident on
the profits of the aircraft's manufacturer, the profits of
airlines that operate a substantial number of that aircraft type,
and the traffic patterns of passengers who previously flew on
that aircraft type? Questions of this sort will be most
appropriate when flaws in the aircraft itself are suspected to
have contributed to a particular accident. Second, does the
market penalize airlines that are involved in accidents: how
does an accident affect an airline's profits and traffic flows,
and the profits and traffic flows of its competitors? These

21

questions will be most appropriate when an airline's actions or
inaction are suspected to have contributed to the accident.

In this literature, profit effects typically are measured
using an event study methodology, which measures the change in
the equity share price of a firm following an accident. This
yields an estimate of the expected change in the present
discounted value of future profits resulting from the accident.
Traffic responses have been analyzed both by examining changes in
"before and after" market shares and by measuring the deviation
from predicted demand using econometric models of airline demand
functions. The samples are restricted to fatal accidents, and
most studies exclude cargo and crew only (re-positioning)
flights. These criteria select the worse and more highly
publicized accidents for analysis.
Aircraft reputation

Studies of aircraft reputation effects have focused on two
DC-10 crashes: the American Airlines Chicago crash on May 25,
1979, which is the worst domestic U.S. airline accident (273
fatalities), and the United Airlines Sioux City crash on July 19,
1989 (Barnett and LoFaso, 1983; Chalk, 1986; Karels, 1989;
Barnett, Menighetti, and Prete, 1990) . Both of these accidents
raised concerns about potential DC-10 manufacturing or design
problems. One study (Chalk, 1987) also examines accident effects
on aircraft manufacturers' profits across a broader sample of

22

"suspect" crashes. ° What do these analyses reveal?

The 1979 DC-10 crash provides some evidence of a market
penalty for aircraft manufacturers. McDonnell Douglas, the
manufacturer of the DC-10, lost roughly 10 percent of its equity
market value, or approximately $100 million, in the first four
days after the accident.' The firm's shares declined by an
additional 10 percent when the FAA announced its unprecedented
decertification of the DC-10, an action that grounded the entire
DC-10 fleet indefinitely. These market value declines are
substantially larger than any direct costs imposed by the
accident, and would be consistent with lower expected sales of
McDonnell Douglas aircraft as a result of the accident. ^°

These declines are not representative of responses to other
accidents, however. In contrast to the 1979 experience,
McDonnell Douglas appears to have been unaffected by the 1989
Sioux City accident. Despite early reports that the design of

^ Chance and Ferris (1987) find no effect on the manufacturer
for a sample of 46 accidents over the 1962-1985 period. Their
sample is not, however, stratified by likely cause of the accident.

' The accident occurred after the market close on Friday, May
25, of Memorial Day weekend. The share price response therefore is
measured from the Friday close to the Tuesday close. See Chalk
(1986) .

^° As new information suggested that improper maintenance
practices were the likely cause of the accident, at least part of
the initial share price declines were reversed. The exact
estimates of the net effect on McDonnell Douglas appear highly
dependent on the time period over which stock returns are
evaluated. Chalk (1986) reports statistically significant net
declines of 14 to 22 percent through various dates in July 1979.
Karels' (1989) attempts to reproduce these results yielded
estimates of +1 through -21 percent net returns, all statistically
insignificant .

23

the DC-10 hydraulic system was a major factor in the crash,
returns on McDonnell Douglas stock were commensurate with market
returns over the days following the accident." Chalk's (1987)
evidence on manufacturer losses for a sample of 19 accidents to
which aircraft failures contributed suggests modest profit
losses, but these estimates may be strongly affected by the
inclusion of the 1979 DC-10 crash in the sample. Chalk finds an
average share price decline of roughly 4% over the five business
days following an accident, corresponding to an average loss of
$21 million in market value. His data indicate no statistically
significant share price effects for accidents involving Boeing or
Lockheed aircraft, however, and the estimated average McDonnell
Douglas decline is likely to be quite skewed by the massive
declines associated with the 1979 crash.

Profit declines for aircraft manufacturers do not appear to
result from passenger avoidance of aircraft involved in fatal
accidents. Barnett and Lofaso's (1983) study of DC-10 market
shares 6 months before and 6 months after the 1979 crash revealed
no systematic changes in travellers' behavior on a sample of 18
routes. ^^ In a study of travel agency ticketing data, Barnett,

" The accident occurred after the market closed on July 19;
July 20 therefore is the first post-crash return day. McDonnell
Douglas shares lost nearly 7% on July 19, probably due to its
announcement on that day of unexpectedly large second quarter
losses. On July 20, McDonnell Douglas shares declined 0.9%,
compared to a 0.7% for the market as a whole. McDonnell Douglas
share prices rose over the next week.

^^ While Barnett and Lofaso control for some airline route
characteristics, they do not have data on average fares. It is
possible that airlines with DC-10 service lowered fares to retain

24

Menighetti, and Prete (1990) find evidence of very short-term DC-
10 avoidance following the 1989 Sioux City crash. In their
sample of 14 routes, 1 in 3 passengers who booked travel within
the first 2 weeks after the crash avoided choosing DC-10 flights,
relative to pre-crash behavior. This behavior quickly
dissipated, however, with booking shares returning to within 10%
of pre-crash levels by 8 weeks after the crash. ^^ Moreover,
despite the development of sophisticated pricing and inventory
management systems by 1989, airlines did not appear to lower
prices on DC-10 flights in response to initial traffic declines.

Finally, there is some evidence that the 1979 DC-10 crash
adversely affected airlines that owned substantial numbers of
these aircraft, although there have been no general studies of
this effect. Karels (1989) finds share price declines for both
American Airlines (the operator involved in the crash) and a
portfolio of other airlines operating DC-lOs in the aftermath of
the 1979 accident. The first response to the crash was a 2%
decline in share values, although this could not be statistically
distinguished from zero. The decertification announcement led to
a 5.3% decline for American and a 2.9% decline for the other DC-
10 airlines. A portfolio of non-DC-10 airlines was unaffected.

How should we interpret these studies? It seems premature

market shares. The study of the 1989 DC-10 crash suggests that
this explanation is unlikely to account for their result.

13 The study did not examine booking patterns beyond 8 weeks
post-crash.

25

to cite these as confirmation of a "reputation effect," at least
in the sense that "market forces can compel producers to invest
in safety, even if consumers are ignorant of all the technical
details of the product" (Chalk, 1986) J^ The strongest evidence
of market responses is associated with the 1979 American Airlines
DC-10 crash; evidence of market responses to other accidents is
weak to non-existent. In 1979, however, the market may have been
responding more to specific FAA interventions than to general
reputation effects. FAA airworthiness directives can require
airlines and manufacturers to invest substantial amounts in
inspections and repairs, replacements, or re-designs of aircraft
components. The FAA's 1979 decision to revoke the DC-10 's
certificate grounded the existing fleet of DC-lOs indefinitely
(inducing direct losses for DC-10 operators) and raised the
possibility that McDonnell Douglas would be required to make
extensive modifications as a prerequisite to selling any
additional aircraft (and re-certifying the existing fleet) .
While market reputation effects and direct FAA interventions both
may induce manufacturers to invest in aircraft safety, the policy
implications of these two mechanisms are quite different. The
existing empirical evidence does not decisively indicate which
mechanism is more important.
Airline reputation

^^ One should remember that while air passengers may not be
well informed about technical characteristics, they are only
indirect consumers of aircraft services. The direct customers of
aircraft manufacturers are airlines, which tend to be highly
knowledgeable and sophisticated buyers.

26

A number of studies have investigated market responses to
accidents at the airline level: does an accident reduce the
airline's expected profitability? Two of the more interesting
and careful of these analyses are Borenstein and Zimmerman's
(1988) study, which couples an investigation of profit effects
with traffic responses, and Mitchell and Maloney's (1989) study,
which pairs an examination of profit effects for different
classes of accidents with a study of insurance premia changes.
Both find evidence of modest profitability declines in response
to fatal accidents.

Borenstein and Zimmerman analyze responses to 74 fatal
accidents over 1962-85. For the 62 accidents that occurred while
passengers were on board the aircraft, they find an average
decline in equity value of roughly 1.3% on the first trading day
following the accident, and 1.5% over the first two days
following the accident. This translates into an average $12
million loss in 1990 dollars.''^ Mitchell and Maloney divide
their sample of 56 accidents over 1964-87 into 34 "pilot error"
crashes and 22 "carrier not at fault" crashes. For the pilot
error sample, they find a one day decline of roughly 1.6% and a
two-day decline of roughly 2.3%.^* This corresponds to an

^^ All dollar values reported in this section have been
escalated to 1990 dollars using the CPI.

^^ The point estimate declines for the carrier not at fault
sample are about half as large and are quite imprecisely estimated.
This may suggest, as Mitchell and Maloney conclude, that the market
does not penalize airlines for accidents not caused by pilot error.
From a different perspective, however, a pooling test across the
two samples would not reject the hypothesis that both sets of

27

average loss in equity value of $22 to $31 million in 1990
dollars. Because airlines typically carry quite complete
hull (aircraft) and liability insurance, most of the equity
decline appears to arise from prospective losses, rather than
actual cash outlays resulting from the current accident. Two
possible sources of prospective losses are increased insurance
premia and reduced demand due to reputation effects. Mitchell
and Maloney estimate that the additional liability insurance cost
over a five year period following an at-fault accident is roughly
90 percent of the one year premium pre-crash. The total present
discounted value of insurance increases average about $10 million
in 1990 dollars. ^^ This accounts for one-third to one-half of
their estimated decline in equity value.

Borenstein and Zimmerman investigate the impact of accidents
on demand for an airline's services. They find virtually no
effect of an accident on demand during the regulated period of
their sample (1960-77) . After deregulation, there may be a
short-term demand response to an accident. In their sample of 13
accidents over 1978-85, estimates of the total loss in demand
over a four-month period average 10% to 15% of one-month's
traffic voliome, although these estimates are at best of marginal
statistical significance. Consistent with the implications of

results are drawn from the same distribution.

^^ Their results for hull insurance increases are quite
sensitive to the specification of the model. An estimate of hull
insurance increases is included in the total dollar value of
insurance increases, however.

28

the DC-IO traffic response studies, this decline is <^ite short-
lived: „ost Of the effect appears to be experienced in the first
two months following a crash.

It is difficult to interpret these results. The demand
Changes during the deregulation era, while relatively small and
Short-ten., imply large revenue losses. For the sample of 13
accidents, the average implied revenue loss is over Sloo million
in 1990 dollars.- This suggests considerable mar.et penalties
for airlines involved in fatal accidents. The strength of this
conclusion is, however, limited by a number of factors. First
these results are based on a relatively small sample and are
estimated very imprecisely, second, the estimated revenue losses
substantially exceed the estimated declines in eguity value, and
the difference is unliKely to be accounted for by cost reductions
associated with serving fewer passengers in the very short-term.
Thxrd, revenue losses appear to be uncorrelated with the change
in equity value in this sample. Finally, there is relatively
little evidence that accidents have a significant effect on the
demand or profits of an airline's competitors. Over the entire
deregulation period, Borenstein and Zimmerman's point estimate of
the demand change for other airlines following an accident is
negative, but very small and imprecisely estimated. The 8
largest accidents (lOO or more fatalities) may have induced a
small (1%, one-month increase in demand for other airlines, but
the stock price of these airlines was unaffected. This suggests

" The uncertainty around this estimate is, however, enormous.

29

that most passengers who would have flown an airl ,•

i-xown an airline recently
involved in an accident instead choose not to ,lv whi.H

be entirely plausible Furth ■ "^ "°'

ible. Further investigation, using the

additional years o, post-deregulation data now available, appears
necessary to address these concerns and resolve the ^es J: ^
demand effects.

While the literature suggests th^ .. -u-, •
penalties . Possibility of some market

penalties for airlin^^ i-h,^*-

^•'^'^ experience passenger fatalities
these .nethodologies may be inherently incapable „, • '
definitive tests of the . ^"capable of providing

Of the strength of aircraft or airline
reputation ef feoi-c j» • i •

effects. Airline accidents, while newsworthy „av

no be very informative, .he expected .or optimal, levelo"

tnis, the occurrence of =„

xrence of an accident may not ca„c=^ ^
revic^o ^.u • ^^^ consumers to

revise their safety expectations for a firm if
not l^.r, ^"^ accident does

ea consumers to revise their priors about an aircraft-s or
- ne. safety, consumers should not penalise the firm involved
the accident. „ini„., _,„,, ^^^^_^^ ^^ ^^ ^^^^^^^^

r " "■' """ "-"^ *"" "^^^^"^ ^- -Pected safety
-vels would be severely punished and therefore are deterred from
ever ..cheating., and ineffective reputation mechanisms <e.g
Where consumers are unaware of the aircraft type used on
particular flights, have difficulty assessing safety records and
a Slow to update their priors in response to accidents, or
Slow to respond to differences in perceived accident ris.s

30

acres, aircraft or airlines, . The existing analyses do not
enable us to distinguish these two extremes.

Conclusinn

Economists have learned a substantial amount about airline
safety, even though many questions remain unanswered, m fact
one might wonder about the motivation for devoting so much energy
to studying such a low risK activity. Mrline safety analyses
appear to have garnered a disproportionate share of major Journal
pages in recent years, relative to more economically significant
riste. m,ile our professional fascination may be inspired in
part by the amount of time we spend in the air, we are not alone
m this interest. Airline accidents attract far more public
attention than most other sources of fatality risK, including
such popular concerns as cancer, homicide, and AIDS. A recent
analysis Of Mg,OC2XKJim^ front page coverage, reproduced in
table 1, revealed that "The 11^ had more page-one stories about
the dangers of flying than about any of . . . five other
[prominent, threats to life, and on a per-death basis, it had
orders of magnitude mere" (Barnett, 1990, . This national
preoccupation with airline safety may provide the ultimate
explanation for the high safety standards maintained by U.S.
carriers and the im.,ense improvements in air safety over time.

31

REFERENCES

Barnett, Arnold, "Air Safety: End of
the Golden Age," Chance: New
Directions for Statistics and
Computing. 1990, 3., 8-12.

Barnett, Arnold, and Mary Higgins,

"Airline Safety: The Last Decade,"

Management Science. January 1989,
35, 1-21.

Barnett, Arnold, and Anthony J. Lofaso,
"After the Crash: The Passenger
Response to the DC-10 Disaster,"
Management Science. November 1983,
29. 1225-1236.

Barnett, Arnold, John Menighetti, and

Matthew Prete, "The Public Response
to the Sioux City DC-10 Crash,"
mimeo, 1990.

Borenstein, Severin, "The Evolution of
U.S. Airline Competition," mimeo,
1991

Borenstein, Severin, and Martin

Zimmerman, "Market Incentives for
Safe Commercial Airline Operation,"
American Economic Review. December
1988, 78, 913-935.

Chalk, Andrew, "Market Forces and

Aircraft Safety: The Case of the
DC-10," Economic Inquiry^ January
1986, 24/ 43-60.

Chalk, Andrew, "Market Forces and
Commercial Aircraft Safety,"
Journal of Industrial Economics.
September 1987, 36, 61-81.

Chance, Don M. , and Stephen P. Ferris,
"The Effect of Aviation Disasters
on the Air Transport Industry: A
Financial Market Perspective,"
Journal of Transport Economics and
Policy. May 1987, 21, 151-165.

32

Evans, William N. , "Deregulation and
Airline Safety: Evidence from
Count Data Models," mimeo, June,
1989.

Golbe, Devra L. , "Safety and Profits in
the Airline Industry," Journal of
Industrial Economics. March 1986,
34. 305-318.

Kanafani, A. and Theodore E. Keeler,
"New Entrants and Safety: Some
Statistical Evidence on the Effects
of Airline Deregulation." In Leon
Moses and Ian Savage, eds. ,
Transportation Safety In an Age of
Deregulation. Oxford: Oxford
University Press, 1989.

Karels, Gordon V., "Market Forces and
Aircraft Safety: An Extension,"
Economic Inquiry. April 1989, 27.
345-354.

Kennet, D. Mark, "Airline Deregulation
and Aircraft Engine Maintenance:
An Empirical Policy Analysis,"
mimeo. Fall 1990.

McKenzie, Richard B. , and John T.

Warner, "The Impact of Airline
Deregulation on Highway Safety,"
mimeo, April 1988.

Meyer, John R. , and Clinton V. Oster,

Jr. , Deregulation and the Future of
Intercity Passenger Travel.
Cambridge: MIT Press, 1987.

Mitchell, Mark L. , and Michael T.

Maloney, "Crisis in the Cockpit?
The Role of Market Forces in
Promoting Air Travel Safety,"
Journal of Law and Economics.
October 1989, 32, 329-356.

Morrison, Steven A. , and Clifford

Winston, "Air Safety, Deregulation,
and Public Policy," The Brookings
Review. Winter 1988, 6, 10-15.

Oster, Clinton V. Jr. and C. K. Zorn,

33

"Airline Deregulation: Is It Still
Safe to Fly?." In Leon Moses and
Ian Savage, eds., Transportation
Safety In an Age of Deregulation.
Oxford: Oxford University Press,
1989.

Rose, Nancy L. "Profitability and
Product Quality: Economic
Determinants of Airline Safety
Performance," Journal of Political
Economy . October 1990, 98, 944-964.

Rose, Nancy L. "Financial Influences
on Airline Safety." In Leon Moses
and Ian Savage, eds. ,
Transportation Safety In an Age of
Deregulation. Oxford: Oxford
University Press, 1989.

34

Table 1

Front Page Stories for Six Sources of
Mortality Risk,

New York Tim^c, 10/1/88 - 9/30/89

, „ Stories

per 1,000

Risk Source Number of stories
U.S. deaths

Cancer 7

Suicide 1

Automobiles 4

.08

Homicide 35

AIDS 35

2.3

Commercial Jets 51

138.2

.02
.03

1.7

Source: Barnett (1990), Table 4.

35

Table 1

Front Page Stories for 6 Sources of Mortality Risk,

New York Times. 10/1/88 - 9/30/89

Risk Source

NuiriDer of Stories

Stories

per

1.000 U.S. deaths

Cancer

7

.02

Suicide

1

.03

Automobiles

4

.08

Hnmi cide

35

1.7

ATTTR

35

2.3

OuraiKituial Jets

51

138.2

Source: Bamett (1990), Table 4.

Figure 1

o totrate

A -fatrate

01
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a.

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20 -

15-

10 -

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60

55

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70 75

Year

BO

B5

90

Aggregate Accident Rates

Figure 2

01
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Actual V. Predicted Accident Rates

Figure 3

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^^o.^r^■K a.- ^P^^ accidents per million departures

Distribution of Cannier Accident Rates, 1971-75

20

Figure 4

01

ft

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Distribution of Carrier Accident Rates, 1981-85

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