 Industry Dynamics and Secondary Markets: Theory and Evidence from Commercial AviationAlessandro Gavazza No 717, 2004 Meeting Papers from Society for Economic Dynamics Abstract: This paper develops a dynamic stochastic model of an imperfectly competitive industry with an active secondary market for inputs to study the commercial aviation industry. The model predicts that carriers in more competitive routes have (1) a higher volatility of output; (2) a higher probability of exit; (3) a larger fraction of their fleet under lease. These predictions are tested by using two data sets covering routes and fleets for US carriers. In a number of durable goods markets, substantial trade in used assets is observed. Cars are the typical example of consumer durables and the number of transactions in the market for used units is more than twice as large as the purchases of new units. But very active markets for used equipment exists for several durable goods that are inputs to a firm production. For example, more than two thirds of all machine tools sold in the United States in 1960 were used (Waterson (1964)); more than half of the total number of trucks traded in the United States in 1977 were traded in secondary markets (Bond (1983)) and active markets exists for several used equipments, such as aircraft, medical equipment and farm tools. Since the mid 80's, trade in the secondary markets for aircraft has grown steadily. Today, the number of transactions for Narrowbody aircraft on the used market is about four times the number of purchase of new aircraft. Moreover, a large share of transactions of aircraft is due to leasing. A substantial number of the planes currently operated by major carriers is under an operating lease, a pure rental contract between a lessor and an airline for the use of the plane for a short period of time (4-5 years). Evidence shows that lessors are actively engaged in the purchase of new aircraft and their acquisitions have increased rapidly in recent years, reaching today approximately 30% of new aircraft deliveries. But lessors are very active participants of the secondary markets too, since they lease out each aircraft several times during its useful lifetime. The purpose of this paper is to study theoretically the link between product market competition and trade in equipment with a focus on the commercial aviation industry and test several empirical implications combining data on routes with data on fleets for US carriers. The model combines two key ingredients. The first is a dynamic model of an imperfectly competitive industry with a large number of atomistic output markets. Firms have heterogeneous stochastic productivity and compete a la Cournot in isolated local markets (routes) that differ in their size. The second element is an active market for inputs (aircraft), which can be bought or leased. Larger markets are more competitive. Competition makes the marginal revenue curve more elastic. For a given shock to the productivity of the firm, this implies a larger volatility of the firm's output and inputs. We further show that more competitive markets exhibit a higher turnover of firms, since price-cost margins are smaller. In the absence of transaction costs, leasing plays no role in the markets for inputs. The frictionless environment is obviously equivalent to a perfect rental market. We then introduce transaction costs on resale but not on leasing. The transaction cost is meant to include search costs for a potential buyer and other trading frictions. Since the primary activity of lessors is to rent the fleet they own, it seems natural to consider they have a cost advantage in the transactions. Lessors exploit their advantage by charging higher rental rates. This creates a trade-off for airlines between the lower implicit rental rate of ownership and the higher flexibility of leasing. We show that firms facing more competition prefer to lease. The intuition for this preference for leasing is as follows. The transaction costs increase with the amount of inputs sold. A higher volatility of inputs increases the probability of very large transaction costs. As a consequence, firms facing bigger volatility choose more flexible inputs (leased aircraft). Thus, leasing allows firms subject to higher volatility to leverage uncertainty and limit downside risk. In the empirical section, we test the cross sectional implications of the model combining data on routes with data on fleets for US carriers. Data on route characteristics are obtained from the Department of Transportation Air Carrier Statistics (Form 41 Traffic). Data on airlines fleet characteristics have been provided to me by AVSOFT, an aviation software company. AVSOFT produces a detailed information system database for the aviation market. For each Western built fixed wing civil aircraft, the database contains information on aircraft characteristics - such as age, engine, total number of hours flown, the total number of landings - and also on the history of the aircraft, including the list of operators. For each leased aircraft, it contains information such as type of lease (Financial vs. Operating), length of the contract and expiration date. We find that in more competitive routes the volatility of departures performed and passengers transported by each carrier is higher. We find that routes served by three or more operators have significantly a higher turnover of carriers over time than duopoly or monopoly routes. Moreover, firms operating in more competitive markets lease a higher percentage of their fleet. The result is robust to the inclusion of several indicators that control for the financial condition of the firm and that previous literature identified as increasing the propensity to lease. We argue that the growth of trade in the secondary markets for aircraft since the mid 80s are consistent with our model. The Airline Deregulation Act of 1978 dramatically reduced entry costs thereby increasing the competitiveness of airline markets. The increase in competitiveness amplified the volatility of firm level output and carriers then needed to adjust their fleets more frequently. The volume of trade on secondary market increased substantially due to higher inter-firm reallocation of inputs. This paper identifies lessors as intermediaries that provide liquidity and reduce frictions in secondary markets. The entry of lessors in the mid 80s as documented in the data therefore exactly coincides with a period of expansion of trade in secondary markets, when the need for market intermediaries to coordinate sellers and buyers becomes stronger. Thus, we highlight a role for leasing in durable goods markets that has largely been ignored in the literature. We believe that the mechanisms identified in these paper are not unique to the aircraft market, but they can help explain the recent increased popularity of leasing for a wide range of durable goods. This paper abstracts from an important force behind trade, the depreciation of goods. The heterogeneity of individual preference and depreciation of goods have been identified as the key motivations for the large volume of trade observed in consumer durables. Recent dynamic models of the secondary markets explain trade because high-value consumers sell their used goods to enjoy the higher quality offered by a newer one. Therefore, in these models, each individual is at the same time a buyer of a newer good and the seller of an older one. We believe these motivations isolate an important effect, but they are inconsistent with the trends observed in primary and secondary markets for two main reasons: (1) the primary markets do not show the same trend as the secondary markets; (2) carriers' fleets show substantial fluctuations over time, as already documented in the literature by Pulvino (1998) and Goolsbee and Gross (2000). Both facts seem to point to inter-firm reallocation as the main engine of growth of trade in the market for used aircraft Keywords: aircraft; firm dynamics and secondary markets (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:red:sed004:717 Access Statistics for this paper More papers in 2004 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC. |
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