The origin and growth of industry clusters

The origin and growth of industry clusters:The making of Silicon Valley and Detroit
Steven Klepper *
Department of Social and Decision Sciences,Carnegie Mellon University,Pittsburgh,PA,United States
a r t i c l e i n f o Article history:
Received 7May 2009
Revised 10September 2009
Available online 17September 2009JEL classification:L2L6R1
Keywords:Clusters Spinoffs
Competence
a b s t r a c t
Data for all producers of automobiles and integrated circuits on their origins,base location,and perfor-mance are used to analyze the factors behind the historical clustering of the two industries in Detroit and Silicon Valley,respectively.Key ideas concerning organizational reproduction and heredity are elabo-rated and used to explain how spinoffs from incumbent firms in the same industry can lead to clustering.Findings concerning the spawning of spinoffs,entry by firms in related industries,and firm performance suggest that organizational reproduction and heredity were the primary forces underlying the clustering of the two industries.
Ó2009Elsevier Inc.All rights reserved.
1.Introduction
Arguably the two most impressive industry clusters in the his-tory of the United States are the semiconductor industry in Silicon Valley and the automobile industry in Detroit.Silicon Valley got its name from the semiconductor industry and Detroit’s moniker as the Motor City was derived from the automobile industry.At the start of the semiconductor industry in 1950,the population of San-ta Clara County,the heart of Silicon Valley,was.3million people.In the next 30years,nearly 100semiconductor firms entered in Sili-con Valley,including five of the industry’s top 10firms,and the population of Silicon Valley more than quadrupled to 1.3million.In its heyday,Detroit’s growth was even more impressive.During the first 30years of the automobile industry,over 100automobile firms entered in the Detroit area,including over half of the indus-try’s leaders,and the population of Wayne County,the home of Detroit,swelled from .3to 1.8million people.
Such extreme industry clusters are rare (Ellison and Glaeser,1997)and call out for explanation,particularly when there is no obvious regional natural advantage underlying the clustering.Yet there has been little systematic empirical analysis of the forces that caused the semiconductor industry to be so concentrated in Silicon Valley,1and until recently the same could be said about the automo-bile industry and Detroit.Numerous articles and books have been
written about the rise of Silicon Valley,including the well known book by Saxenian (1994)concerning the triumph of Silicon Valley over Route 128and the recent history of the semiconductor industry in Silicon Valley by Lecuyer (2006).They lay out a theory that reso-nates with modern theories of geography.Once semiconductor firms began to congregate in Silicon Valley after the emergence of Fairchild Semiconductor as a leader of the industry,labor pooling,technolog-ical spillovers,and a rich supplier industry stimulated further firm growth and entry of semiconductor firms in the Valley.The evidence that has been compiled about clusters is broadly consistent with the importance of such agglomeration economies (Rosenthal and Strange,2004).While this was not the story told historically about Detroit and the automobile industry (cf.May,1975;Rae,1980),no consensus has emerged around these historical accounts,which has left the door open for explanations based on agglomeration economies (Tsai,1997).
The main purpose of this paper is to bring together data col-lected and analyzed by Klepper (2007,2008)for US automobile en-trants and Klepper (2009)and Klepper et al.(2009)for US semiconductor entrants to compare the factors behind the geo-graphic clustering of the two industries.These data include infor-mation about the origins of the entrants,including whether they produced other products prior to entry,and for new firms whether they were spinoffs,defined as firms whose founders previously worked for another firm in the same industry.Spinoffs have been celebrated in the semiconductor industry (Lindgren,1971;Saxe-nian,1994;Sporck,2001;Lécuyer,2006)and implicated by indus-try insiders as key to the clustering of the industry in Silicon Valley (Sporck,2001;Moore and Davis,2004).Klepper (2007)argued that
0094-1190/$-see front matter Ó2009Elsevier Inc.All rights reserved.doi:10.1016/j.jue.2009.09.004
*Fax:+14122686938.
E-mail address:sk3f@ 1
See Scott and Angel (1987),Fallick et al.(2006),and Ketelhöhn (2006)for three relevant analyses.
Journal of Urban Economics 67(2010)
15–32
Contents lists available at ScienceDirect
Journal of Urban Economics
www.elsevier.c
om/locate/jue
spinoffs were also key to the clustering of the automobile industry around Detroit.2The analysis focuses on the role of spinoffs,and more broadly organizational competence and heredity,in the evolu-tion of the Detroit automobile and Silicon Valley semiconductor clusters.
Key ideas concerning organizational reproduction and heredity based on a theoretical model in Klepper(2008)are elaborated and used to explain how spinoffs can lead to clustering.The theory has a number of implications regarding entry andfirm performance that are used to analyze the evolution of the automobile and semi-conductor industries.Consistent with the theory,afirm’s pre-entry experience critically shaped its performance and its performance in turn influenced the rate at which its employees left to form spin-offs.Detroit and Silicon Valley each had an early exemplary per-former that got the spinoff process going in their regions. Subsequently,betterfirms reproduced at a higher rate and their offspring were superior performers.With spinoffs not venturing far from their geographic origins,this led to a buildup of superior firms in Detroit and Silicon Valley.In both regions,this superiority manifested itself at the time of entry;in autos,the superior perfor-mance offirms in the Detroit area was due to the disproportionate number that descended from the leadingfirms and entered at the largest sizes,and in semiconductors the superior performance of Silicon Valleyfirms was due to the disproportionate number that descended from the leadingfirms and the greater propensity of Sil-icon Valleyfirms to enter at the technological frontier.
The role played by the spinoff process in the clustering of both industries suggests that organizational reproduction and inheri-tance were key to their clustering.The evidence also indicates, however,that the spinoff process operated more intensively in De-troit and Silicon Valley,raising the specter of some kind of influ-ence of regional conditions on entry.Numerous other questions are raised by the importance of spinoffs in the two clusters.Most fundamentally,why do spinoffs occur?Furthermore,why is the performance of spinoffs and their‘‘parents”related,how do spin-offs contribute to the growth of regions,do thefindings for semi-conductors and automobiles pertain to other industries as well, and is the formation of spinoffs influenced by public policies bear-ing on employee mobility?While definitive answers are hardly available,hopefully the questions will help frame future investiga-tions concerning the emergence and growth of industry clusters.
The paper is organized as follows.In Section2,the data used to analyze each industry is discussed.In Section3,the broad evolu-tion of the two industries and their clusters is reviewed.In Section 4,the theoretical framework used to analyze the data is presented. In Sections5and6,entry and performance of auto and semicon-ductorfirms,respectively,are analyzed.In Section7,thefindings are discussed and various theoretical and policy-related questions are raised and considered.
2.Data
The analysis of both industries begins with their commercial inception,which is dated as1895for automobiles and1949for semiconductors.
Data on US automobile producers were compiled primarily from Smith(1968),which lists the names,base location(state and city),and prior products of producers of all makes of automo-biles manufactured in the United States from1895to1966,and Kimes and Clark(1996),which provides a brief description of the founding conditions of every automobile producer.Firm entry and exit dates of producers are based on thefirst and last year of production of all makes afirm produced in Smith(1968).Entrants were classified as diversifiers,spinoffs,or startups according to their founding histories in Kimes and Clark(1996)and whether they were listed in Smith as producing other products prior to automobiles.Diversifiers arefirms that added automobiles to their product line orfirms that were founded by individuals that previ-ously headed pre-existingfirms.3Spinoffs arefirms with one or more founders that previously worked at another automobilefirm on Smith’s list.The prior employer of the main founder is designated as the spinoff’s parent,and if the main founder worked at a priorfirm on Smith’s list or a secondary founder worked at anotherfirm on Smith’s list,thatfirm is designated as a secondary parent of the spin-off.All other entrants were lumped into a residual category labeled startups.4
Data were also collected on the initial sizes of automobile pro-ducers and on the output of the largest producers.Thomas’Register of American Manufacturers,an annual marketing directory that has been published since1905,was used to determine the initial cap-italization of producers,which was used as a measure of entry size.5The output of the leading producers of automobiles each year was determined from Bailey(1971),which lists the annual number of cars produced of the leading makes of automobiles(up to20 makes are listed in any given year).
Data on US semiconductor producers were compiled from the annual Electronics Buyer’s Guide(EBG),which lists the producers of electronics products through1987,after which it was no longer published.The semiconductor industry clustered in the era of inte-grated circuits(ICs),and the EBG listed producers of various types of ICs from1965to1987.This was used to determine thefirst and last year of production of every IC producer.6Separate lists were also provided for many different types of ICs(the types changed over time as new ICs were introduced).The different types of ICs were aggregated into three broad categories:monolithic ICs(all compo-nents made on doped semiconductor substrates),hybrid ICs(a mix-ture of conventional components and semiconductor substrates), andfilm ICs(composed of layers offilm on top of semiconductor substrates),and for eachfirm thefirst and last year of production of each type of IC was recorded.The EBG also listed transistor pro-ducers(from1949to1987),diode producers(from1952to1987), and active module7producers(from1962to1987),and these lists were used to determine the producers of each product and theirfirst and last year of production.For each IC producer,it was also deter-
2Buenstorf and Klepper(2009a)also feature the role spinoffs played in the clustering of the US tire industry historically around Akron,Ohio.
3Manyfirms entered the automobile industry with very similar but not exactly the same names as pre-existingfirms.It was often difficult to tell whether they were new firms organized by the head of the pre-existingfirm with the similar name or pre-existingfirms that modified their names to reflect an expanded product line when they diversified into automobiles.Previously an attempt was made to separate these two types offirms but they performed similarly(Klepper,2007),and for simplicity they are combined here.The main product each diversifier produced prior to automobiles was determined from Kimes and Clark(1996).
4See Klepper(2002,2007)for detailed procedures that were followed in compiling the data,including the treatment of acquisitions(firms acquired by non-automobile producers were treated as continuing producers as were automobile producers that acquired other automobile producers,with the acquired automobile producers treated as censored exits).
5See Klepper(2008)for how the annual lists of automobile producers in Thomas’Register was matched to Smith’s(1968)list.
6Some IC producers had multiple locations listed in some years;their main location was determined based on where their production was concentrated over time.Inexplicably somefirms that produced ICs continuously based on other sources were not listed in some years as producers,and these were corrected based on the available information.Somefirms,including a few prominent ones,that began producing ICs toward the end of the data period(1965–1987),were not listed as IC producers and thus are not included in the analysis.
7Active module producers werefirst listed in1962,3years before ICs,and some of the early producers of ICs were listed initially as active module producers,which appears to encompass producers of all kinds of circuits of assembled discrete electronics components.
16S.Klepper/Journal of Urban Economics67(2010)15–32
mined when theyfirst produced any electronics product listed in the EBG.
The pre-entry backgrounds of the IC producers were also traced. Firms that were listed in the EBG as producers of transistors, diodes,active modules,or other electronics products at least 5years before they were listed as IC producers were classified as diversifiers into ICs.8It was not possible to trace comprehensively the backgrounds of all of the other IC producers.For Silicon Valley, a genealogy was compiled by the organization SEMI listing the foun-ders of every semiconductor entrant in Silicon Valley between1955 and1986.Nearly all of thesefirms were spinoffs,and the genealogy was used to identify the IC entrants in Silicon Valley that were spin-offs and their parents,defined as the prior semiconductor employer of the spinoff’s primary founder.A private consulting company,Inte-grated Circuit Engineering(ICE),compiled annually the sales of mer-
chant semiconductor producers whose sales exceeded a minimum threshold for the period1974–2002.A total of101firms that entered by1986were identified,and Klepper(2009)traced the backgrounds of92of thesefirms using the Silicon Valley genealogy,web searches, and other sources.This information was used to identify(the largest) spinoffs outside of Silicon Valley and their parents.9
3.Evolution of the automobile and semiconductor industries
Following Klepper(2009),the broad outlines of the evolution of the automobile industry around Detroit and the semiconductor industry around Silicon Valley are described.
3.1.Automobiles
The annual number of automobile entrants,exits,and producers from1895to1966based on Smith(1968)is plotted in Fig.1.Entry into the industry was concentrated in itsfirst15years.From1895 to1900,entry averaged11.5firms per year,which increased to 36.8firms per year from1901to1905and then peaked at82firms in1907.Entry remained high for the next3years and then dropped to approximately15firms per year from1911–1922,after which only15firms entered through1966.The number offirms peaked at272in1909.Subsequently it fell sharply,dropping to9by 1941despite enormous growth in the industry’s output.
Table1lists the leading eight states in terms of the total num-ber of automobile entrants.While Michigan was the leading state, entrants were dispersed throughout the Northeast and Midwest. Fig.2plots the annual percentage offirms located in the Detroit area10through1941.None of the initial69entrants from1895to 1900entered in the Detroit area,with thefirst entrant in the Detroit area,Olds Motor Works,entering in1901.Subsequently the percent-age of producers in the Detroit area rose steadily,reaching around 25%in the mid1920s and then over50%by1941.
The share of automobilefirms in the Detroit area in the early years greatly understates the clustering of the automobile industry there.Table2,which lists the market shares of the leading automo-bile producers every5years from1900to1925,11indicates that by 1910seven of the top10producers of automobiles were located in the Detroit area,with Detroit areafirms having a combined market share of65%.This share rose further after1910as the leading Detroit areafirms,led by Ford,General Motors,and later Chrysler,increased their dominance of the industry.
Much of the growth of the industry around Detroit was attrib-utable to spinoffs.Olds Motor Works,which was a successful en-gine producer,was thefirst greatfirm in the industry and in its short life as an independentfirm(it was acquired by General Motors in1908)it spawned the most spinoffs of anyfirm in the industry,12including three of the industry’s leaders.Nearly all the rest of the later entrants in the Detroit area that became
Table1
Automobile entry by state and background for the leading eight states,ordered by
population.
State Total entry Diversifiers Startups Spinoffs
NY98354815
PA52132811
IL7025396
OH89353816
MO278172
MA5515364
IN69233016
MI1353046
59
8The5-year rule was used to exclude from diversifiersfirms that entered with the
intent of producing ICs butfirst produced other,simpler electronics products.The
closest product to ICs in terms of technology and market was the transistor,followed
by diodes,active modules,and then other electronics products,and diversifiers were
classified into(only)one of the four product categories based on this hierarchy.
9A few of thefirms classified as spinoffs werefinanced by non-semiconductor
firms(and sometimes organized as subsidiaries)or involved a reconstitution of an
existing semiconductorfirm in which the new‘‘founders”were given an ownership
interest.Fairchild,for example,wasfinanced by and later became a subsidiary of
Fairchild Camera and Instrument,a Long Island military contractor.National
Semiconductor,which was located in Connecticut,was an example of a reconstituted
firm that brought in Charles Sporck,the head of manufacturing at Fairchild,to
reconstitute its efforts in Silicon Valley,effectively giving birth to a newfirm.
Following general practice,National was classified as a spinoff of Fairchild.One other
firm,MOS Technology,had a similar history to National and was classified as a spinoff
of Motorola(see Klepper(2009)).
10Firms were classified in the Detroit area if they located in Michigan within
100miles of Detroit.The100-mile distance was chosen to reflect movement and
branching offirms within approximately a100-mile distance of Detroit.Eleven of the
entrants moved in or out of the100-mile region,and they were classified as in the
region if they spent the majority of their years producing there.
11This was compiled from annual data reported in Bailey(1971)on the output of
the leading makes of automobiles and data from the FTC(1939)on the total annual
production of automobiles.
12General Motors and its constituents had as many spinoffs over a longer period.
S.Klepper/Journal of Urban Economics67(2010)15–3217
leaders of the industry(see Table2)were spinoffs.Table1,which breaks down the entrants in the leading states into diversifiers, spinoffs,and startups,illustrates the importance of spinoffs in Michigan versus the other leading states.Michigan had a total of 59spinoffs that constituted44%of all of its entrants.In contrast, the next closest states in terms of number of spinoffs were Ohio and Indiana with16each,which constituted18%and23%of their entrants,respectively.
3.2.Semiconductors
The transistor was invented in1947by three Bell Labs(AT&T) scientists and effectively started the semiconductor industry.Un-der antitrust pressure,AT&T liberally disseminated its know-how and licensed its transistor patents and agreed to produce transis-tors only for its own use and the government market.Numerous firms entered into the production of transistors,as reflected in Fig.3,which presents the annual number of transistor entrants,ex-its,and producers from1949to1987based on the EBG.After the first few years,entry was fairly steady,averaging11firms per year from1953to1973,and then it dropped to7.8firms per year from 1974to1987.The number of producers grew steadily to90by 1975and then leveled off.
Fig.4reports the fraction of transistor producers in four consol-idated metropolitan statistical areas:Boston,Los Angeles,New York,and San Francisco,where the latter region is primarily com-posed of Silicon Valleyfirms(and hereafter is referred to as the Sil-icon Valley area).Producers concentrated early around thefirst three cities,with New York accounting for around40%of the pro-ducers and Boston and LA around15%by the latter half of the 1950s.Silicon Valley had no producers before1955and no more than8%of the producers through1960.
Table2
Market shares of leading US automobilefirms,1900–1925.
Early entrants Entry year Entry location190019051910191519201925
Pope1895Hartford,CT36
Stanley1896Watertown,MA2
Locomobile1899Bridgeport,CT18
Knox1900Springfield,MA0.3
Packard1900Warren,OH/Detroit,MI221
H.H.Franklin1900Syracuse,NY4
White Sewing Machine1901Cleveland,OH0.024
Olds/GM1901Detroit/Lansing,MI26121 Cadillac/GM1902Detroit,MI166211 Jeffery/Nash1902Kenosha,WI1623
Later entrants
Studebaker1902South Bend,IN8534 Anderson/Union1902Anderson,IN2
Ford1903Detroit,MI718562244 Maxwell Briscoe/Maxwell/Chrysler1903Tarrytown,NY/Detroit,MI36524 Buick/GM1903Flint,MI317565 Willys1903Terre Haute,IN91066 Reo1904Lansing,MI442
Stoddard1904Dayton,OH1
E.R.Thomas-Detroit/Chrysler1906Detroit,MI41
Brush1907Detroit,MI6
Oakland/GM1907Pontiac,MI2121 Hupp1909Detroit,MI3113 Hudson1909Detroit,MI3127 Paige-Detroit1909Detroit,MI1 Chevrolet/GM1911Flint,MI1612 Saxon1913Detroit,MI2
Chandler1913Cleveland,OH2
Dodge Brothers/Chrysler1914Detroit,MI575 Dort1915Flint,MI1
Durant1921New York,NY3
Detroit-areafirms05865835285
18S.Klepper/Journal of Urban Economics67(2010)15–32
Thefirst notable semiconductor producer in Silicon Valley was Fairchild Semiconductor,which entered in1957.Along with Texas Instruments,it pioneered the silicon transistor and then the inte-grated circuit(IC),which wasfirst commercially produced in 1961and eventually took over much of the industry.Fig.5presents the annual number of IC entrants,exits,and producers from1965 to1987based on the EBG.From1965to1973entry averaged39.7firms per year and the number of producers grew to154.13Subse-quently entry dropped to an average of20.9firms per year through 1987and the number offirms leveled off until it grew again after 1980,reaching a high of210in1987.
Fig.6,which reports the share of IC producers in the New York, Los Angeles,Boston,and San Francisco areas,indicates that atfirst IC producers were concentrated in New York,Los Angeles,and Bos-ton,each of which contained around20%of the producers.Subse-quently the percentage of producers in the Silicon Valley area steadily rose and by1979Silicon Valley was the leading area with around20%of the IC producers,which increased further to over 23%by1987.Fig.4indicates that the share of transistor producers in the Silicon Valley area also grew after the advent of ICs,largely driven by the co-production of transistors and ICs by IC entrants.
13The sharp drop in the number offirms in1970corresponds to a change in the
categories of ICs listed.
S.Klepper/Journal of Urban Economics67(2010)15–3219
Similar to Detroit,the share of transistor and IC firms in Silicon Valley greatly understates the clustering of the semiconductor industry there.Table 3lists the periodic market shares of the lead-ing semiconductor producers from 1957to 1990.14By 1975five of the top 10semiconductor producers were located in Silicon Valley and collectively Silicon Valley firms accounted for 43%of the output of the industry,which increased to 48%five years later.Much of this growth was driven by Fairchild Semiconductor,through its own growth but even more importantly as the source of many of the sub-sequent leaders of the industry.Among the other four leading Silicon Valley firms in 1975,three were spinoffs from Fairchild and the fourth was a second generation descendant of Fairchild.
Fairchild was responsible for an extraordinary number of spin-offs,as will be discussed further below.It is instructive to consider
the backgrounds of IC entrants in the different regions in the US to understand the effect spinoffs had on Silicon Valley.In Table 4,IC entrants in New York,Los Angeles,Boston,San Francisco,and the rest of the US are broken down according to whether they pro-duced transistors,diodes,active modules,or other electronics products before ICs,with the rest of the IC producers placed in a residual category labeled ‘‘other firms.”The latter category in-cludes all the firms that were determined to be spinoffs and the remaining IC producers,many of which may also have been spin-offs but whose background could not be determined.Table 4con-veys a clear message:80%of the IC entrants in the Silicon Valley area were not prior producers of transistors,diodes,active mod-ules,or other electronics products versus 57%of the IC entrants in New York,61%in Boston,61%in LA,and 56%elsewhere.This re-flects both the paucity of prior electronics producers in Silicon Val-ley before the advent of ICs and also the richness of the spinoff process there,as reflected in the Silicon Valley genealogy.
Table 4
Backgrounds of IC entrants by region.
Transistors
Diodes Active modules Electronics Other firms Total Boston
569114879Los Angeles 7182462102New York 86122771124San Francisco 421106885Other 1682158130233Total
40
23
51
130
379
623
Table 3
Market shares of leading US semiconductor producers,1957–1990.Sources :see Tilton (1971)for sources for 1957,1960,1963,and 1966market share data;the 1975,1980,1985,and 1990market shares are based on annual compilations of ICE.Receiving tube firms Entry year a Metropolitan location 5760636675808590General Electric 1951Syracuse,NY 9888C C C C RCA
1951Camden,NJ 6757432Raytheon 1951Boston,MA 54––1110.5Sylvania
1953Boston,MA 43––Westinghouse 1953Pittsburgh,PA 2645C
C
C
C
Philco-Ford 1954Philadelphia,PA 3643Other early leaders Texas Instruments 1953Dallas,TX 2020181720191815Transitron 1953Boston,MA 129330.5TRW 1954Los Angeles,CA ––4–C C C C Hughes
1955Los Angeles,CA 115––C C C C General Instrument 1955Long Island,NY –––43210.5Delco Radio (GM)1956Kokomo,IN
–––4C C C C Fairchild 1957Mountain View,CA –5913975A Motorola
1958b Phoenix,AZ –
5
10128111317
Later leaders Signetics
1961Sunnyvale,CA –
–565Analog Devices 1965Boston,MA –1122AMI
1966Santa Clara,CA –
4211National 1967Santa Clara,CA 1011109Harris 1967Melbourne,FL 2334Intel 1968Santa Clara,CA 7101017AMD 1969Sunnyvale,CA 2576Mostek
1969Dallas,TX 2
6A Micron Technology 1978Boise,ID –0.52VLSI Technology 1979San Jose,CA –12LSI Logic
1980
Milpitas,CA
–23Silicon Valley Share Leading firms c
5
913
38424238Leaders +other ICE firms c
43
48
49
47
–:Firm was producer,but no market share data reported.
C:Captive producer in the listing of Integrated Circuit Engineering (ICE).A:Acquired by a semiconductor producer.a
Dates for receiving tube firms and early leaders based on Tilton (1971).b
According to Tilton (1971),Motorola used semiconductors only for its own purposes before 1958.c
Includes Raytheon,which was based in Silicon Valley as of 1975.
14This was compiled from market share data reported in Tilton (1971,p.66)for the years 1957,1960,1963,and 1966and the ICE sales data for subsequent years.
20S.Klepper /Journal of Urban Economics 67(2010)15–32
4.Theory
The brief accounts of the evolution of the automobile and semi-conductor industries indicate that the composition of entrants var-ied greatly across regions,with spinoffs playing a key role in the clustering of both industries.In this section a few key ideas regard-ing organizational competence based on a model of industry evo-lution in Klepper(2008)are laid out and used to explain prominent shared features of the Detroit and Silicon Valley clus-ters.The ideas are also used to derive various predictions that will serve as a basis for testing the theory.15
A key component of the theory is thatfirms differ innately in terms of their competence.16For simplicity,potential entrants into a new industry are assumed to come in two types,high(H)and low (L)competence.At the time of entry,the profits of potential entrants with competence k=L or H equal P k+e,where e is a idiosyncratic factor that is assumed to be drawn from a uniform distribution de-fined over the interval[À1/2,1/2],and P L and P H are normalized such thatÀ1/2<P L<P H<1/2.Potential entrants enter if their prof-its are nonnegative.This implies that the probability of entry of po-tential entrants of type k is P k+1/2and the profits at entry of entrants of type k are uniformly distributed over the interval [0,P k+1/2].There is assumed to be a1–1mapping between the size offirms at entry and their profits,denoted as q(Á),with q(0)>0and q0>0.Hence at the time of entry,the output of entrants of type k is uniformly distributed over the interval[q(0),q(P k+1/2)].
The competence offirms is based on their pre-entry experience. Three types of entrants into a new industry in terms of their pre-entry experience are distinguished:diversifiers,spinoffs,and (other)startups.Diversifiers are assumed to be either high or low competence producers in their original industry.It is assumed that for a diversifier to be an Hfirm in the new industry it must be an H firm in its own industry.This is only a necessary condition,though, as being an Hfirm in the new industry depends on thefirm’s ability to transfer its experience into the new industry.Let p d denote the probability that an Hfirm in another industry will be an Hfirm in the new industry.It is assumed that the more relevant a diversi-fier’s industry to the new industry,the greater the value of p d.
Spinoffs can exploit knowledge about the new industry that their founders gained while working in the industry at their‘‘par-ent”firm.Spinoffs are typically formed by high level employees. For simplicity,it is assumed that everyfirm has the same number of such employees that can found spinoffs and each has the same probability of leaving to form a spinoff in any given period.Various theories of spinoffs predict that more competentfirms spawn bet-ter-performing spinoffs(Franco and Filson,2006;Cassiman and Ueda,2006;Klepper and Thompson,2009),which is supported by studies of spinoffs in a number of industries(Agarwal et al., 2004;Franco and Filson,2006;Klepper,2007;von Rhein,2008; Buenstorf and Klepper,2009a).Accordingly,it is assumed that for a spinoff to be an Hfirm,its parent(in the new industry)must be an Hfirm.This is only a necessary condition,though,as being high competence depends on the ability of the spinoff founder to exploit his or her experience at the parentfirm.Let p s denote the probability that a spinoff of an H incumbentfirm will itself be an Hfirm in the new industry.Spinoffs are expected to inherit traits from their parents.Let s denote the probability thatfirms in the new industry have some particular trait.It is assumed that the probability of a spinoff having the trait is greater than s if its parent had the trait(when the spinoff was founded)and less than s otherwise.
The last group of entrants,startups,is composed of newfirms founded by individuals without experience in the new industry. They are all assumed to be Lfirms in the new industry,reflecting their lack of organizational and industry experience.
Entrants have a home region.For diversifiers this is where they produced in their industry,for spinoffs it is where their founders worked(i.e.,where their parentfirm was located),and for startups it is where their founders previously worked and/or resided.It is assumed that entrants have valuable economic and social knowl-edge about their home region.For simplicity,it is assumed that all entrants locate in their home region to exploit this knowledge. Otherwise the location offirms has no effect on their perfor-mance—for example,afirm’s profitability is not affected by the number or market share offirms in its home region.
A number of results about entrants follow directly from this framework.First,H potential entrants have a higher probability of entry than L potential entrants and among entrants,the average and maximum entry size is greater for H than Lfirms.Only diver-sifiers that are Hfirms in their original industry and spinoffs of H incumbentfirms can be Hfirms in the new industry.Therefore,it follows that(see the Appendix for proofs of all propositions):
Proposition1.(a)Hfirms in another industry are more likely than L firms in the same industry to enter the new industry;(b)The more related an industry is to the new one(i.e.,the larger p d)then the greater the probability thatfirms in the industry enter the new industry,ceteris paribus;and(c)Hfirms in the new industry spawn a greater expected number of spinoff entrants than Lfirms in the new industry.
Since the average and maximum entry size of Hfirms is greater than Lfirms and only diversifiers that are Hfirms in their original industry and spinoffs of H incumbents can be Hfirms in the new industry,it follows that:
Proposition2.The maximum and average entry size of spinoffs is greater than startups,and spinoffs of H incumbents enter at a greater maximum and average size than spinoffs of L incumbents.
To explain differences in the length offirm survival in the new industry,a mechanism to induce exit is needed.It is assumed that in every period t,firms experience a permanent additive shock l t to their profits and exit if their profits fall below0.For simplicity, it is assumed that l t can take on three possible values,g>0,Àg,or 0,with probabilities p,p,and(1À2p)respectively,so that E(l t)=0.Consider the hazard of exit t periods after entry offirms of type k=L or H,where it is assumed that gt<P L+1/2.The only firms at risk of exit are those that had profits at the time of entry less than or equal to gt and that are still in the industry.For sim-plicity,let the fraction of thesefirms of type k that survive to the beginning of period t equal its expected value of a t,which is the same forfirms of either type.Analogously,let the fraction of these survivors with profits less than or equal to g equal its expected va-lue of b t,which is also the same forfirms of either type.Then t peri-ods after entry,the hazard of exit offirms of type k equals p a t b t tg/ [P k+1/2À(1Àa t)tg],which implies that the hazard of exit is greater for L than Hfirms.17Coupled with H entrants in a new industry being either diversifiers that were Hfirms in their original industry or spinoffs of H incumbentfirms,it follows that: Proposition3.Among contemporaneous entrants,on average the hazard of exit in each period is lower for:(a)diversifiers and spinoffs than startups;(b)diversifiers that are H versus Lfirms in their own industry;(c)diversifiers from more related industries(i.e.,for which p d is greater);and(d)spinoffs from H versus L incumbents.
15Buenstorf and Klepper(2009a)used a similar approach to analyze the historical clustering of the US tire industry.
16In high-tech industries like semiconductors and automobiles,competence would centrally involve afirm’s ability to manage technological change.
17Intuitively,in every period a smaller percentage of H than Lfirms are at risk of exit.
S.Klepper/Journal of Urban Economics67(2010)15–3221。