The short and long run effects of entry on U.S. domestic air routes.

Figure 2 presents data on airline prices, before and after entry. Prices are indexed to 1 in the period before carder entry. In the quarter after a carrier enters a route, prices on that route fall 10 percent. Note that these are average prices for all carriers on a route. Prices continue to fall for the next two quarters, bottoming at 81 percent of the pre-entry price level in the second and third quarters after entry. Note that price changes resulting from the entry of a pre-deregulation carrier are not nearly as deep as changes resulting from the entry of Southwest onto a route. When a pre-deregulation carrier entered a route, prices declined to 88 percent of the pre-entry level by the second quarter after entry, before rising to 95 percent of the pre-entry price by the fourth quarter after entry. When Southwest entered a route, prices declined to 52 percent of the pre-entry level by the first quarter after entry and remained relatively stable at that level during the full year after entry. Price drops for the "other" carrier category fell in between those of Southwest and the pre-deregulation carriers with prices 18 percent below the entry level after one year.

Figure 3 shows passenger traffic changes on routes upon entry. On average, traffic increased by 32 percent upon entry, rising to 74 percent above pre-entry levels by the fourth quarter after entry. The results were not nearly as dramatic when a pre-deregulation carrier entered a route. Traffic was only 17 percent above pre-entry levels in the fourth quarter following entry. This compared to a traffic increase of 300 percent for Southwest and 182 percent for the "other" carriers.(15)

Figures 1 through 4 indicate that the impact of Southwest on a route differs substantially from the impact of pre-deregulation carriers. Not only is the impact different, but the type of route that Southwest enters is also different. Table 4 reports some characteristics of the routes entered by the four sets of carriers during the period from the fourth quarter of 1991 to the second quarter of 1994. As indicated in Table 4, Southwest enters shorter routes with higher levels of market concentration and fewer passengers prior to entry than the routes entered by the pre-deregulation carriers. The average Herfindahl Index on routes entered by the pre-deregulation carriers was 5,001, but the average Herfindahl Index on routes entered by Southwest was 6,461. The average distance of routes entered by the pre-deregulation carriers was 944 miles, while the average distance of the routes entered by Southwest was 373 miles. The average number of passengers carried on routes entered by the pre-deregulation carriers (prior to entry) was 114,800, while the average number of passengers on routes Southwest entered was 68,850. Clearly Southwest enters routes markedly different from the routes entered by the pre-deregulation carriers.

Figure 4 looks at the impact of exit on prices, the Herfindahl Index, and on passenger traffic. It appears that the exit of a carrier from a route has little, if any, impact on price. While passenger traffic is up after exit, it is not growing much more quickly than the general level of passenger traffic. However, it appears that a significant change is occurring on the routes prior to exit. In the three quarters preceding exit, prices fall by 27 percent and the Herfindahl Index falls by 17 percent. It appears that competition becomes more heated in the time period prior to exit. This could be due to the entry of a low cost carrier or the outbreak [TABULAR DATA FOR TABLE 4 OMITTED] of a fare war on the route. Concentration and prices fall dramatically prior to exit and this could be the cause of the exit event. While the exit results in an increase in concentration, prices do not rise to their former levels.

In summary, the data on entry suggest that entry leads to the following: a reduction in market concentration, as measured by the Herfindahl Index; a reduction in prices; and an increase in passenger traffic. The magnitude of the results, however, is largely dependent on the carrier that enters, with Southwest showing much larger price and passenger effects than average. Exit, on the other hand, appears to be the result of increased competition in the period prior to the exit. Exit itself has little impact on prices or passenger traffic. Our results also indicate that Southwest Airlines enters routes with markedly different characteristics than those routes entered by the pre-deregulation carriers.

MODELING THE EFFECT OF ENTRY ON PRICE

In the last section, the descriptive statistics showed that entry is associated with changes in market structure, price decreases, and traffic increases, and that these changes often depended on what type of carrier (pre-deregulation, Southwest, etc.) entered a route. In this section, a more formal model is developed and tested in an attempt to sort out some of these effects. In particular, we control for relevant variables influencing price in an attempt to determine whether entry itself is sufficient to lower prices on a route or whether entry must be by a particular carrier. The following two models were estimated:

(1)

PRICE = [[Beta].sub.0] + [[Beta].sub.1]HERF + [[Beta].sub.2]DIST + [[Beta].sub.3][DIST.sup.2] +

[[Beta].sub.4]PASS + [[Beta].sub.5]SLOT + [[Beta].sub.6] VACATION +

[[Beta].sub.7]HAWAII + [summation of] [[Beta].sub.t]QUARTERt where t = 8 to 18

[Mathematical Expression Omitted]

where:

* PRICE = the average one-way fare for all carriers on a route between two cities;(16)

* HERF- the Herfindahl Index measure of market concentration for a route;

* DIST is the great circle distance between the two cities on a route and [DIST.sup.2] is equal to the square of DIST;

* PASS is the total number of revenue passengers for all carriers on the route;(17)

* SLOT is a dummy variable coded 1 if either or both of the two cities on a route has slot-controlled airports and 0 otherwise;

* VACATION is a dummy variable coded 1 if one of the two cities on the route is in Florida, Nevada, Hawaii, or Puerto Rico and 0 otherwise;

* HAWAII is a dummy variable coded 1 if the route is an intra-Hawaiian route and 0 otherwise;

* the QUARTERt's are dummy variables for each quarter in our sample (except the base quarter) to account for changes in prices over time; and

* the CARRIERj's in the second equation are dummy variables to account for differential pricing strategies of the carriers in our sample.

The independent variables represent a mix of demand, cost, and market structure variables that may influence price. Market concentration, as measured by the Herfindahl Index, is hypothesized to be positively associated with route prices; that is, the greater the concentration on a route, the higher the prices. Route distance and the square of route distance are cost side variables. Price is expected to increase proportionately with route distance but inversely with the square of distance; that is, as the distance of a route increases, so does price but at a decreasing rate due to the fixed costs of flights. Passengers is both a demand side and cost side variable. On the demand side, increases in passengers (a shift to the right of the demand curve, holding supply constant) should be associated with higher prices. On the cost side, higher passenger density should be associated with cost economies and lower prices. The net effect of passengers on price cannot be determined a priori. Slot is a market structure variable to control for supply restrictions on take-off and landing slots. These restrictions are expected to result in higher prices. The vacation variable is a market structure variable. Vacation markets are expected to attract a higher ratio of pleasure to business travellers, resulting in lower yields to carriers. The Hawaiian variable is a market structure variable for the very short, high density routes found between the Hawaiian Islands. It is not known a priori what will be the sign on the coefficient for this variable.

The difference between the two models is in the use of dummy variables for the airlines, with only the second model using the airline dummies. The airline firm dummies allow for firm-specific characteristics to influence the price on a route. One major firm-specific variable that is not included in our model is airline costs. The firm dummies allow airline costs to [TABULAR DATA FOR TABLE 5 OMITTED] influence prices. A negative dummy implies that the carrier's presence leads to lower average prices on that route.

Table 5 provides the results of the estimation of the two models. An instrumental variable estimation was employed, instead of ordinary least squares, due to the endogeneity of two right side variables, Herfindahl Index and Passengers.(18) As expected, in both of the models the distance variable is positive and significant, indicating that longer routes have higher prices, while the distance squared variable is negative and significant, implying that prices increase with distance at a decreasing rate. The slot-controlled variable is positive and significant in both of the models, as expected, signifying that a route that has slot controls at one or both endpoints has significantly higher prices than a route with no slot controls at its endpoints. The vacation route dummy is negative and significant in the two regressions, implying, as hypothesized, that average fares on vacation routes are lower than fares in general. Finally, the dummy for intra-Hawaiian routes was negative and significant, indicating that, all other things being equal, fares on intra-Hawaiian routes are lower than on comparable routes elsewhere in the U.S.

The most interesting results were for the coefficient estimates for the Herfindahl Index and for Passengers. Both of these coefficients were positive and significant in Model 1 but not in Model 2.(19) The implication, with respect to the Herfindahl Index, is that concentration appears to be positively associated with higher prices only when individual carrier effects are not considered. When individual carrier effects are considered, as in Model 2, the effects from concentration are "swamped" by individual firm effects. Therefore, in order to lower prices on a route, it is much more important to have (for example) Southwest operating, even as a sole competitor, than it is to have low concentration. Adding a number of competitors to a route operated by Southwest (i.e., lowering concentration) will not lead to lower prices. It is the presence of Southwest itself that leads to the low prices.

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