%Paper: ewp-io/9502001
%From: Neil Gandal <gandal@econ.tau.ac.il>
%Date: Wed, 15 Feb 1995 15:24:28 +0200 (IST)


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\pagestyle{myheading}\markright{NEVER WORKS}
\begin{document}
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\newtheorem{defn}{DEFINITION}
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\newtheorem{cor}{Corollary}
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\begin{titlepage} \vspace*{0.05in}
\begin{center}

{\Large\bf  Sequential Auctions of Israeli Cable Television
Licenses:  The Morning Effect}
\\
\vspace{.15in}  Neil Gandal\\
Tel-Aviv University \\
E-mail: gandal@ccsg.tau.ac.il\\
Fax: 972 3 640 9908 \\
\vspace{0.15in}\today \\
\vspace{.1in}{\bf Abstract}\\\end{center}

{\em In Israel,
area cable television (CATV) licenses were auctioned
sequentially.  This paper  empirically finds a
``morning" effect, that is, greater competition in later rounds of
the
auction.  While three factors (interdependencies among
neighboring licenses,  interdependencies among all licenses, and
cautious bidding in early rounds) likely contributed to the
``morning"
effect, the evidence suggests that interdependencies among
neighboring licenses were the primary cause.}

\vspace{3 mm}

\noindent   I am grateful to Avi Alcalay, the director of the Cable
Television Division (CTD) of the Ministry of Communications
and his staff for providing me with the data for this study, and to
Sarit Markowitz for high-quality research assistance.  I thank
Larry Cole, Zvi Eckstein, Chaim Fershtman, David Frankel, David
Genesove, Shane
Greenstein, Victor Lavy, Assaf 
Razin, David Salant, Yossef Spiegel, Manuel Trajtenberg, Andrew
Weiss and seminar participants at the Bank of Israel, GTE
Laboratories, Hebrew University, and Tel Aviv University  for many
helpful suggestions and discussions.

\vspace{0.05in}\noindent
%\begin{description}
%\item {\bf Keywords:} Sequential Auctions
%\end{description}
\end{titlepage}
\baselineskip=0.25in

\section{Introduction}

One of the most important developments in the Israeli
Telecommunications sector was the 
decision to establish a Cable Television (CATV) industry in the
country.  The original decree,  passed in 1986, and subsequent
amendments led to the
establishment of the Cable 
Broadcasting Council (CBC).  This body was given the responsibility
of allocating franchises 
and regulating the industry via the Cable Television Division (CTD)
of the Ministry of 
Communications. 

The CBC divided the country into  31 areas (see
figure 1) and some of 
the areas were linked together into a single license.  For the most
part, less populated areas in the north and south of the country
were linked with more populated areas in 
the center of the country, in order to insure that
these outlying regions would be served. 
The CBC elected to auction the licenses in sequential blocks. 
Within each block, the licenses were offered on a 
``license-by-license" basis, that is, combinatorial bidding for
groups of licenses was not
allowed.
 
This paper  empirically tests whether  competition for licenses
was more intense  in the early or later rounds of the
auction.
While there are no formal theoretical models that examine the path
of prices in sequential auctions when  there are interdependencies
among licenses, there are several reasons why competition might
have intensified over
time in this auction:

\begin{itemize}

\item It is likely,  due to economies of scale in infrastructure
development, that the values of neighboring cable television are
interdependent.  Further, this auction had the following
properties.
(i) neighboring
licenses were auctioned sequentially, (ii) some of the
licenses
auctioned in later rounds shared a border with several other
licenses in major metropolitan areas, and (iii) no one firm held
all
relevant ``neighboring"
licenses at the time of the bidding.  In particular, for each
``interdependent" license 
that was auctioned during the later rounds, there were  at
least two firms that held bordering licenses.\footnote{If one  firm
had obtained all relevant ``border" licenses, it is likely that
interdependencies among neighboring licenses would have been
resulted in diminished competition in later rounds.} 
 

\item More generally, it is possible that the values of all
licenses are interdependent due to economies of scale in purchasing
programming (movies), billing, etc.

\item Since there had been no previous auctions of cable television
licenses in Israel, it is likely that most bidders were not well
informed about the values of the licenses.  Thus, the bidders may
have elected to bid cautiously in the early rounds, in order to
avoid the winner's curse. 



 \end{itemize}

On the other hand, there is a reason 
why competition might have been more intense in early rounds:

\begin{itemize}

\item Because of the potential interdependencies among
licenses, the competitors may have concluded that losers in the
``early" rounds would be less likely to bid for interdependent
licenses offered  late.  This could have encouraged aggressive
bidding early in the hope of facing less competition in later
rounds.

\end{itemize}
 
I find compelling evidence that competition for licenses offered in
early rounds was less intense than competition for licenses offered
in later rounds, that is, there was a ``morning" effect.  While it
is likely that all three factors
(interdependencies among
neighboring licenses,  interdependencies among all licenses, and
cautious bidding in early rounds) contributed to the ``morning"
effect, the evidence suggests that interdependencies among
neighboring licenses were the primary cause.
 
This paper builds on a small but growing literature on the
auctioning of multiple objects.\footnote{Chakravorti et al (1994)
provide a nice survey of the recent literature.}   A theme common
in this literature is that competition will be more intense in
the early rounds of a sequential auction.  This phenomenon is known
as the ``afternoon" effect. 

In Hausch (1986), bidders have correlated
valuations for identical objects which are auctioned
sequentially, using first-price sealed bids.   He shows that
informed bidders
with high valuations have incentives to underbid in early rounds.
This signal jamming can lead less informed bidders to conclude that
the value of the objects is low, which
reduces price competition in later rounds. 
Pitchik and Schotter (1988) show that when some
bidders face budget constraints, other bidders (without budget
constraints) may bid aggressively in early rounds.  By depleting
the resources of their cash-constrained rivals, bidders with deep
pockets reduce price competition in the later rounds.

McAfee and Vincent (1993)
show that risk averse
bidders are more likely to bid more aggressively in early
rounds of
sequential auctions.  The intuition is that losing early in order
to try to win in future rounds is a gamble and risk averse bidders
are willing to pay
a premium to avoid gambles.  Finally Krishna (1993) shows that
prices may fall in  a setting in
which
bidders' valuations are independent and there is full information. 
The intuition for her result is that a high valuation bidder, who
could win in each auction, may prefer to lose in early rounds
because her rival may be relatively uninterested in acquiring more
than one unit.  If such a rival wins in an early round, he  may not
even participate in the later rounds; hence competition will
be reduced in later rounds. 


Empirical support for price
declines over time in sequential auctions
comes from Milgrom and Weber (1982), Ashenfelter (1989), and
Ashenfelter and Genesove (1992).  Milgrom and Roberts (1982) found
that late winners obtained more attractive leases on
telecommunications transponders, while Ashenfelter (1989) found
that prices for  identical lots of wines were twice as likely to
fall as they were to rise.   Ashenfelter and Genesove (1993) found
that ``face-to-face" buyers obtained  discounts relative to prices
paid in sequential auctions of identical condominiums and that
these discounts were larger for condominiums purchased earlier in
the auction. 
 

In all of the above papers, the value of each object was
independent of all other objects to be auctioned.  In many multiple
auctions, however, the values of the objects are interdependent. 
Hendricks and Porter's (1988) study of auctions for drainage leases
is an example.    They find that firms holding neighboring tracts
 to drainage tracts that were auctioned were better informed
 about the value of the drainage tracts than firms 
that did not hold neighboring 
tracts; as a consequence, the informed firms
 earned higher rents on the drainage tracts they obtained
than did the non-informed firms.
  In the auction of Israeli
Cable Television licenses, there is also evidence that neighboring
licenses were interdependent and that these interdependencies
contributed to the
``morning" effect. 

\section{Background}

Recall that the CBC elected to auction the licenses in sequential
blocks.  Bids were solicited for each license area according to the
schedule shown in Table 1 below. 
A bid was considered 
acceptable if the potential licensee  could
finance the development of the 
infrastructure  and had the knowledge to operate and maintain 
service.  Additionally,  minimum infrastructure standards were
established.

\begin{table}[ht]
\begin{center}
\begin{tabular}{r||c|c|c|c|c||}
                 \\ \hline 
 $License Area$            & $Tender$     & $Bid Due$     & $Winner
Announced$ 
   & $Block$ & Group  \\
\hline\hline
A18  & December $1987$ & March $1988$ & July $1988$  & One & IE  \\
\hline
A4, A22 & December 1987 & March 1988 & July 1988 & One & IE \\
\hline
A29 & December 1987 & March 1988 & August 1988 & One & NI
\\ \hline
A10, A11, A24 & January 1988 & April 1988 & October 1988 & One & IE
\\ \hline
A21 & December 1987 & April 1988 & October 1988 & One & IE
\\ \hline
A27 & January 1988 & April 1988 & November 1988 & One & NI
\\ \hline
A13, A14 & September 1988 & December 1988 & January 1989 & Two & NI
\\ \hline
A9, A26 & September 1988 & December 1988 & February 1989 & Two & NI
\\ \hline
A8, A20 & September 1988 & December 1988 & February 1989 & Two & IL
\\ \hline
A7, A19 & September 1988 & December 1988 & February 1989 & Two & IL
\\ \hline
A1, A2 & September 1988 & December 1988 & March 1989 & Two & NI \\
\hline
A3, A5, A23 & March 1989 & June 1989 & August 1989 & Three & IL \\
\hline
A25 & March 1989 & June 1989 & August 1989 & Three & IL
\\ \hline
A17, A28, A30, A31 & March 1989 & June 1989 & December 1989 & Three
& IL
\\ \hline
A15 & March 1989 & June 1989 & May 1990 & Three & IE
\\ \hline
A12 & July 1989 & November 1989 & March 1990 & Three & IL
\\ \hline
A6, A16 & June 1990 & August 1990 & January 1991 & Four  & IL \\
\hline
\end{tabular}
\end{center}
\caption{Bid and License Dates}
\label{dates.t}\end{table}

Each bidder had to specify the number and type of services that
would be offered in the basic tier and the (real) maximum monthly
basic 
service prices that would be charged.\footnote{If premium channels
were also offered, maximum prices for these services also had to be
specified.}      The CBC chose among 
acceptable bids by comparing maximum prices for basic service and
the  number and variety of offerings in the basic
tier.  The maximum monthly
service  price was binding on the winner.
Monopoly licenses were issued in each franchise area for an initial
period of twelve years. 

The price to be paid by the winning licensee was set at \$25,000
and \$ 6250 each year 
for the following eleven years.   Additionally the licensees pay
royalties: In the second (third) 
year of the license, these royalties were set at three (four)
percent of gross revenues;  From 
the fourth year, licensees pay five percent of their gross
revenues.

Table 1 shows that the outcomes of the first six licenses (block
one) were announced before bids were due for the
following five licenses.  Similarly, the winners in the second
block were announced before bids were due for the remaining
licenses. 
The original plan of the CBC was to auction 18 licenses in three
blocks.  A separate tender for Eilat (A31) was put out along with
the other block one tenders in January 1988, with a final bid date
of April
1988.  However, a license was not awarded since no acceptable bids
were received.  This tender was put out again in block two with the
same results.  Finally, this area was
added to the  A17, A28, \& A30 license and auctioned in block
three. 
Similar to the case of
Eilat, there were three tenders for the  A6 \&
A16 license.  In this case, however, the third tender was
successful and the
winner of this final license was announced in
January 1991.\footnote{The auction for the A12 license was slightly
delayed so that it took place after some of the block three winners
were announced.  Nothing in the analysis changes if this license is
classified as block four.} 
The original licenses were awarded to seven different firms.  The
bidders (1) and the winner (1*) in 
each license area are shown in Table 2 below. 

\begin{table}[ht]
\begin{center}
\begin{tabular}{r||c|c|c|c|c|c|c|c|c|}
\\ \hline 
Licenses & Golden & Matav & Tevel & ICS & Gvanim & CN & Telem &
Other & Total
\\ \hline
A18 & 1* & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 4
\\ \hline
A4, A22 & 0 & 1* & 0 & 0 & 0 & 0 & 0 & 1 & 2
\\ \hline
A29 & 0 & 0 & 1 & 1* & 0 & 0 & 0 & 0 & 2
\\ \hline
A10, A11, A24 & 0 & 0 & 1 & 0 & 1* & 0 & 0 & 0 & 2
\\ \hline
A21 & 1 & 1 & 1* & 0 & 0 & 1 & 0 & 1 & 5
\\ \hline
A27 & 0 & 0 & 1* & 1 & 0 & 0 & 0 & 1 & 3
\\ \hline
A13, A14 & 0 & 1 & 0 & 0 & 0 & 1* & 0 & 0 & 2
\\ \hline
A9, A26 & 0 & 0 & 0 & 1* & 0 & 0 & 0 & 0 & 1 
\\ \hline
 A8, A20 & 1 & 0 & 1* & 0 & 0 & 0 & 0 & 0 & 2
\\ \hline
A7, A19 & 1* & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 2
\\ \hline
A1, A2 & 1* & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1
\\ \hline
A3, A5, A23 & 0 & 1* & 0 & 0 & 1 & 0 & 0 & 0 & 2
\\ \hline
A25 & 0 & 0 & 0 & 0 & 1* & 0 & 0 & 0 & 1 
\\ \hline 
A17, A28, A30, A31 & 1 & 0 & 0 & 0 & 0 & 0 & 1* & 1 & 3
\\ \hline
A15 & 0 & 1 & 0 & 0 & 0 & 1* & 0 & 0 & 2
\\ \hline
A12 & 0 & 0 & 0 & 0 & 1* & 1 & 0 & 0 & 2
\\ \hline
A6, A16 & 1 & 1* & 0 & 0 & 0 & 0 & 0 & 0 & 2
\\ \hline
Total & 7 & 7 & 7 & 3 & 4 & 5 & 1 & 4 & 38
\\ \hline
\end{tabular}
\end{center}
\caption{Bidders and Winners in Each Area}
\label{bidders.t}\end{table}

There was consolidation in the industry because two of the firms
awarded licenses were unable
to begin operations.  CableNet (CN) was originally awarded
licenses to serve Haifa (A13 \& A14) and Hadera (A15). 
After
the failure of CableNet, these licenses were offered by the CBC to
the only other bidder: Matav.\footnote{This license was
acquired by Matav following the awarding of the A12 license, 
but before the final auction took place.} 
Similarly
Telem was awarded the A17, A28, A30,\& A31 license, but Golden
Channels took over (as
a majority stockholder) due to Telem's financial difficulties. 
Golden Channels was offered the option of acquiring  the license
 by the
CBC because its bid
was more attractive than that of the only other firm (Goshen) that
bid for the license.  In each case, the {\em bid} of the
winning firm  was binding on the firm that obtained the
license.
 


Cable television has been remarkably successful.   By June 1994,
the operators had achieved a 64 percent penetration
rate\footnote{The penetration rate is defined as the number of
subscribers divided by the number of homes passed.} and fully 54
percent of the households in the country had CATV service.    As of
June 1994, Golden Channels had 383,000
subscribers, Matav had 375,000, and Tevel had 321,000 subscribers;
at the same point in time, ICS and Gvanim had 175,000 and 140,000
subscribers respectively. 


\section{Data}


The data used for this ``event study" are cross-sectional.
For the case of more than one area in a license, the data are for 
the major metropolitan area included in the license.  We now
describe the data available for
the study.

\begin{enumerate}
 
\item PRICE - The (real) maximum price in March 1988 New Israeli
Shekels  for basic service offered by
the winning bidder.\footnote{The exchange rate in March 1988 was
$1.6$ New Israeli Shekels = \$ 1.00.}

\item NUMBER -  The number of basic channels offered by the winning
bidder.  These include over-the-air channels, satellite services,
and self-broadcast channels.  All winning bids offered the five
over-the-air channels (Israel 1, 
Israel 2, Jordan 1, Jordan 2, and Middle East
Television).

\item PRICE/CHANNEL (P/C) - The real maximum price per channel
offered by the winning bidder.

\item  DENSITY - The number of potential subscribers divided by the
number of kilometers of cable needed to serve the license area.

\item AUTOMOBILES - The number of automobiles per 1000
residents.\footnote{Data on income is not disaggregated by
license area, but the number of automobiles per 1000 residents is
delineated according to license area.    This variable is the best
available proxy for income.} These data are collected periodically;
we use the latest figures, which are for the  1992/1993 period. 
\item TOTAL - the number of firms that bid on each license. 
Although the number of bidders and their identities are available,
price and channel data on losing bids are unavailable.

\item PBIDS - the {\em potential} number of bidders on each
license.
The definition of this variable is provided in section 4.2.

\item GROUP - This variable takes on the value one if the license
is in the set of interdependent licenses auctioned late (IL); it
takes on the value two if the license area is not interdependent
(NI), and takes on the value three if the license area is in the
set of interdependent licenses auctioned early (IE).  (See section
4.1 for group definitions).

\item EARLY - This is a dummy variable that takes on the value one
if the license is in the set of interdependent licenses auctioned
early (IE) and zero otherwise.

\item BLOCK - This is a variable that takes on the value 1
if the license was auctioned in block one, 2 if the license
auctioned was in block 2, etc. (See table 1.) 

\item LINKED - This is a dummy variable that takes on the value 1
if the main area was linked with one or more other service areas.
\end{enumerate}

The following table contains descriptive statistics on the
above variables. 

\begin{table}[ht]
\begin{center}
\begin{tabular}{r||c|c|c|c||}
\\ \hline 
Variable & Mean & Std. Dev. & Maximum & Minimum
\\ \hline
\\ \hline 
PRICE & 30.5 & 4.24 & 40.0 & 25.94 
\\ \hline
NUMBER & 20.41 & 7.91 & 39.00 & 6.00
\\ \hline 
PRICE/CHANNEL (P/C) & 1.83 & 1.04 & 4.87 & 0.80
\\ \hline
EARLY & 0.29 & 0.47 & 1.00 & 0.00
\\ \hline
GROUP & 1.88 & 0.86 & 3.00 & 1.00
\\ \hline
BLOCK & 2.06 & 0.97 & 4.00 & 1.00
\\ \hline
LINKED & 0.53 & .51 & 1.00 & 0.00
\\ \hline
TOTAL & 2.24 & 1.03 & 5.00 & 1.00
\\ \hline
PBIDS & 2.59 & 0.87 & 5.00 & 1.00
\\ \hline
DENSITY  & 200.2 & 69.96 & 308.82 & 103.63
\\ \hline
AUTOMOBILES & 218.8 & 52.3 & 304 & 148
\\ \hline
\end{tabular}
\end{center}
\caption{Descriptive Statistics}
\label{descriptive.t}\end{table}

\section{Analysis}
 
 Recall that the CBC chose among acceptable bids by comparing the
maximum price for basic service and the number of channels offered
in the basic tier.  Although the exact relationship between these
two variables was not specified by the CBC, a natural
measure of the degree of competition during the bidding process  is
the maximum price per channel offered by the winning bidder for
each license. 
 
Although all channels are not identical, careful examination of
each of the winning bids reveals that the
channels offered in the basic tier during the bidding
process were over-the-air broadcast stations, satellite services,
superstations, and non-premium self broadcast channels.\footnote{In
the case of
A18 and A6 \& A16,  a premium movie
channel was included in the basic service bid.  In order to be
consistent, this channel was
excluded and the basic service price was reduced by the average
price of a premium movie channel offered by bidders in the premium
tier.
Nothing in the analysis changes if the premium channel is simply
counted as another channel and the price of basic service is not
adjusted.}
   This corresponds to
the types of offerings included in  the basic cable tier in the
U.S. Because of the relative uniformity within a tier, the price
per channel within a tier is often used to measure competition in
the cable television industry.\footnote{A 1993 U.S. FCC Report, for
example, showed how CATV rates per channel (within a tier) varied
by the degree of competition in the area.} 

We now discuss how the independent variables used in the study are
expected to affect the degree of competition (the winning price per
basic channel) during the bidding process:
 
If a ``morning" effect exists due to interdependencies among
neighboring licenses, the winning price per basic channel should be
higher for IE licenses than for other licenses; in a regression
with PRICE/CHANNEL as the dependent variable, the coefficient on
EARLY should be positive.
 
If a ``morning" effect exists due to interdependencies among
neighboring licenses and if there was also very intense competition
for the IL licenses, the winning price per basic channel should be
higher for licenses in group IE than licenses in group NI, and the
winning price per channel should be higher for group NI than for
group IL; given the definition of GROUP, its coefficient should be
positive. 

If a ``morning" effect exists due to a winner's curse, so that
competitors bid conservatively in early rounds,
competition should be greater for the licenses auctioned later.  Of
course, a ``morning" effect due to the presence of
interdependencies among all licenses should
also lead to more conservative bidding in early rounds.  Hence, it
will not be possible to distinguish between these two factors.  In
both cases, the winning price per basic channel should decline over
time as BLOCK increases.\footnote{It is possible that the over time
competitors learned more about how the regulatory authority chose
the winning bids; this would also result in more competitive bids
over time;  hence the effect would also be captured by the variable
BLOCK and would be indistinguishable from the other two factors.} 

An increase in the number of bidders should increase competition
for the following two reasons:  (1) Vickrey (1961) showed that when
a single object is auctioned, bidders are symmetric, risk neutral,
and have independent private values, the expected revenue of the
seller is the same regardless of the auction format and equal to
the valuation of the second highest bidder.  Hence as the number of
bidders  increases, the  expected valuation of the second highest
bidder increases.   (2) In our setting, there is a significant cost
to making  a bid;\footnote{These costs included providing detailed
technical specifications for the CATV system, conducting market
research, obtaining financing, etc.} hence only firms with high
valuations
and hence high probabilities of winning will be inclined to enter
the
bidding. Therefore, the winning
 price per basic channel should be lower for areas in
which more bidders participated.

 
Clearly, the areas are not homogeneous; ignoring potential
interdependencies, the marginal cost per channel of providing
service was expected to vary across license areas. 
Empirical studies suggest that there are some 
economies of density and scale in the CATV industry.\footnote{See
Jaffe and
Kantor (1990) and Rubinovitz (1993).}  If the operators
expected that more densely populated areas had lower marginal
costs, the winning price per basic channel should be lower for more
densely populated license areas. 


The expected effect of LINKED on the winning price per basic
channel is
unclear.  On the one hand, major areas that are linked with
sparsely populated areas may have been less
attractive to bidders
and on the other hand,
since the winner of a linked license receives multiple
areas, the  linked areas
might have been viewed as a bonus.

Rubinovitz (1993) also found that per capita income was a proxy for
factor costs in an area and that higher factor costs would lead to
higher marginal costs.  AUTOMOBILES (the best available proxy for
income) was hence included as an explanatory variable. 
If this is the case, winning bids should be higher in areas with
more automobiles per capita.
 
\subsection{Initial Tests for a ``Morning" Effect due to
Interdependencies among Neighboring Licenses}

In order to initially test for a  ``morning" effect, due to
interdependencies among neighboring licenses in a metropolitan
area,  the sample was split into three groups.  The first group
consisted of interdependent licenses that were auctioned early
(denoted IE), the second group consisted of 
licenses that were not interdependent (NI), and the final group
consisted of interdependent
licenses that were auctioned late (IL).  Licenses were considered
interdependent if they met both of the following
criteria:

\begin{itemize}

\item The license areas physically shared a common border in a 
metropolitan area.



\item The license areas had similar demographic characteristics,
including population, and potential subscribers.


\end{itemize}

Using the above criteria, one obtains five IE licenses, five NI
licenses and seven IL licenses.\footnote{It is possible that
licenses A15 and A6 \& A16 could have been classified as NI, rather
than IE and IL respectively. Nothing in the analysis changes under
the alternative classification.  Region A12 includes Haifa's
northern suburbs.
Since the population of A12
is much smaller than
the population of the Haifa metropolitan area (A13, A14), 
the value of the Haifa license was most likely
independent of whether the A12 license was received or not.  On the
other hand, the value of the A12 was probably higher for the winner
of the Haifa license than for firms that did not hold neighboring
licenses.  Indeed CableNet did bid on the A12 license.}
The licenses are shown in Table 4 below with the pairs of
interdependent
licenses grouped together.
\pagebreak

\begin{table}[ht]
\begin{center}
\begin{tabular}{r||c|c|c|c|c|c|c||}
\\ \hline 
Licenses & Price & Channels &  P/C
 & Block & Bidders &  Group & Winner
\\ \hline
A18 & 31.2 & 12 & 2.60 & 1 & 4 & IE & Golden 
\\ \hline
A7, A19 & 30.1 & 15 & 2.00 & 2 & 2 & IL & Golden
\\ \hline
A17, A28, A30, A31 & 31.9 & 23 & 1.39 & 3 & 3 & IL &  Telem-Golden 
\\ \hline
\\ \hline
A4, A22 & 29.5 & 9 & 3.28 & 1 & 2  & IE & Matav
\\ \hline
A3, A5, A23 & 27.2 & 30 & 0.91 & 3 & 2  & IL & Matav
\\ \hline
\\ \hline
A10, A11, A24 & 29.2 & 6 & 4.87 & 1 & 2  & IE & Gvanim
\\ \hline
A25 & 27.6 & 20 & 1.38 & 3 & 1  & IL & Gvanim 
\\ \hline
A12 & 25.9 & 23 & 1.13 & 3 & 2 & IL & Gvanim 
\\ \hline
\\ \hline
A15 & 32.0 & 16 & 2.00 & 3 & 2 & IE & CN-Matav
\\ \hline
A6 \& A16 & 31.1 & 39 & 0.80 & 4 & 2 & IL & Matav
\\ \hline
\\ \hline
A21 & 26.5 & 22 & 1.20 & 1 & 5 & IE & Tevel
\\ \hline
A20, A8 & 29.6 & 22 & 1.34 & 2 & 2 & IL & Tevel 
\\ \hline
\\ \hline
A29  & 40.0 & 20 & 2.00 & 1 & 2 & NI & ICS
\\ \hline
A27 &  26.5 & 22 & 1.20 & 1 & 3 & NI & Tevel
\\ \hline
A13, A14 & 26.4 & 24 & 1.10 & 2 & 2 & NI & CN-Matav
\\ \hline
A9, A26 & 34.0 & 28 & 1.21 & 2 & 1 & NI & ICS
\\ \hline
A1, A2 & 39.8 & 15 & 2.66 & 2 & 1 & NI & Golden
\\ \hline
\end{tabular}
\end{center}
\caption{Winning Bids in Each Area}
\label{bid.t}\end{table}

\pagebreak

Table 4 provides support for the hypothesis that
competition for the group of the interdependent licenses that were
auctioned in later periods was greater than competition for the
interdependent licenses that were auctioned early.  In particular,
the price per basic channel is significantly lower for the second
license in each group and the number of channels offered is
significantly higher for each of the first four groups in the
above table.



In the case of the Tel Aviv licenses, both the price per channel
and the number and variety of offering are nearly identical.  Note
that the first Tel Aviv license was contested by five firms.  Since
the first Tel Aviv license was not linked, and since Tel Aviv is
the economic hub of the country, it is not surprising that there
was fierce competition in the early round. 

If one only looks at the first four groups of interdependent
licenses, the data are consistent with the alternative hypothesis
that it (exogenously) became less costly to offer additional
channels over time as the auction progressed and that hence the
increased competition may not be due to the interdependencies among
neighboring licenses.  The two Tel Aviv licenses and all the five
interdependent licenses provide strong evidence against this
alternative hypothesis.\footnote{Shortly before the final auction, 
four of the five Israeli cable operators  formed a joint venture
called
ICP in December 1989 to jointly 
acquire programming.   The CBC supported the venture in exchange
for the addition of several premium channels to the basic tier.
It is clear that the ICP
affected the number and types of services offered for this license.


In particular, this bid was the only one to offer 
``ICP" channels. 
Hence, the marginal cost of offering
additional channels did fall in that case.}  In particular, in six
of these license areas, the number of channels offered by the
winning
bidder remained in a narrow range (from 20 to 28) and there is no
discernable trend in the number of channels over time.  Indeed, the
lowest number of offerings in this group is for the Jerusalem (A1,
A2) license, which took place in the second block. 

 

\subsection{Further Tests for a ``Morning" Effect}

Despite the fact that there are only 17 license areas, we now
conduct a more formal analysis by running several regressions.  The
dependent variable in both of these regressions is the winning
price per number of basic channels in each license area. 



The first
regression in table 5 (6) uses  the variable EARLY (GROUP) to test
for a ``morning"
effect due to interdependencies among neighboring
licenses, while
the second regression in the table uses the variable
GROUP.  The BLOCK variable is also included in these regressions in
order to determine which of the factors (GROUP/EARLY or BLOCK) was
more important in terms of explaining the ``morning"
effect.  The first regression in tables 5 and 6 is estimated by
ordinary least squares (OLS)
using the variable TOTAL. 

Since the total number of bidders (TOTAL) is probably endogenous,
the exogenous variable PBIDS is employed as an instrument for TOTAL
in the second regression in tables 5 and 6.  For licenses that were
auctioned in blocks 2,3 and 4, the {\em potential} number of 
bidders in a license area (PBIDS) is simply the number of firms
that hold licenses in adjacent major metropolitan
areas.\footnote{This is similar to the strategy employed by
Hendricks and Porter (1988).}  In the case of the block one
licenses, the potential number of bidders is simply the average
number of bidders  (three) in the block one license areas with the
exception of the
first Tel Aviv license.  In this case, the potential number of
bidders is set equal to the actual number (five) of bidders.  The
generally held view at the time was that this was by far the most
valuable
license auctioned in the initial block and it was expected that
this license would be attractive to most bidders.  The correlation
between TOTAL and PBIDS is 0.53.

Comparing the regressions, there is little difference between the
OLS and instrumental variable (IV) estimates,
suggesting that the simultaneity bias is quite small.
Since there are so few observations, only the variables that are
moderately significant are included in the regressions.  In
particular, the variables AUTOMOBILES, LINKED and DENSITY 
are all insignificant and hence not included in the
regressions.\footnote{These variables are insignificant even in
regressions for which TOTAL is excluded.} 

Despite the relatively high degree of
collinearity between GROUP and BLOCK (-0.67) and EARLY and  BLOCK
(-0.63), the GROUP and EARLY variables are statistically
 significant in the
regressions of Tables 5 and 6.  BLOCK is 
statistically significant in the regressions in Table 5,
and non-negligible in the regressions in Table 6.  The signs of
these
coefficients are as expected.\footnote{Further, the coefficient on
the
total number of bidders  is
negative and significant in all regressions, 
suggesting that the winning price per basic
channel was lower when more firms participated.}  The EARLY/GROUP
variables are consistently more significant that the BLOCK
variable;
this provides additional evidence that the ``morning effect" is
primarily due to interdependencies among neighboring licenses. 

 



\begin{table}[ht]
\begin{center}
\begin{tabular}{r||c|c||c|c||}
                 \\ \hline 
& \multicolumn{2}{c||}{Model One: OLS} 
& \multicolumn{2}{c||}{Model Two: IV}
\\ \hline
 Variable   & Coefficient  & T-Statistic &  Coefficient  &
T-Statistic
\\ \hline
CONSTANT & $3.68$ & $5.77$ & $3.86$ & $3.36$ 
\\ \hline
EARLY & 1.56 & 3.82 & 1.59      & 3.00
\\ \hline 
BLOCK & $-0.48$ & $-2.56$ & -0.49 & -2.37 
\\ \hline
TOTAL & $-0.59$ & $-3.30$ & $-0.67$ & $-1.57$
\\ \hline
Adjusted $R^2$ & .64 & & .63 & 
\\ \hline
Std. Err. & 0.63 & & 0.63 &
\end{tabular}
\end{center}
\caption{Regression Results:  EARLY used to test for ``morning"
effect due to interdependencies.}
\label{regression.t}\end{table}

 
\begin{table}[ht]
\begin{center}
\begin{tabular}{r||c|c||c|c||}
                 \\ \hline 
& \multicolumn{2}{c||}{Model One: OLS} 
& \multicolumn{2}{c||}{Model Two: IV}
\\ \hline
 Variable   & Coefficient  & T-Statistic &  Coefficient  &
T-Statistic
\\ \hline
CONSTANT & $2.23$ & $1.89$ & 2.71 & 1.65 
\\ \hline
GROUP & $0.66$ & $2.07$ & 0.70 & 1.99 
\\ \hline
BLOCK & -0.35 & -1.25 & -0.40 & -1.28 
\\ \hline
TOTAL &  $-0.41$ & $-1.92$ & -0.62 & -1.15
\\ \hline
Adjusted $R^2$ & .42 & & .38 &
\\ \hline
Std. Err. & 0.80 & & 0.87 &
\end{tabular}
\end{center}
\caption{Regression Results:  GROUP used to test for ``morning"
effect due to interdependencies.}
\label{regression1.t}\end{table}
 

\section{Conclusion}

Although there are  data limitations due to the fact that only
seventeen cable television licenses were awarded in Israel, there
is relatively strong empirical support for the hypothesis that a
``morning" effect exists and  that interdependencies among
neighboring licenses in a metropolitan
area were the primary cause.   Additional support for the
hypothesis that interdependencies
among neighboring licenses (increasing returns to scale) led to the
``morning" effect comes from the bidding pattern for the  seven
interdependent licenses that were auctioned late.  In five of these
cases (A8 \& A20, A7 \& A19,
A3 \& A5\& A23, A12, A6 \& A16), there were two bidders and each of
the bidders held licenses in  bordering
areas.  In the other two cases (A25, [A17, A28, A30, \& A31],)
one of the two firms that held a neighboring license elected to
bid.  Further, no bids were submitted for any of the IL licenses
from license holders who did not have neighboring
licenses.\footnote{In the case of A17, A28, A30 \& A31,
bids were received by firms who bid
only once during the whole auction.}



%\pagebreak
\baselineskip=0.2in
\begin{thebibliography}{99}

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\end{thebibliography}

\baselineskip=0.3in

\end{document}



------------------------------------------------------------------------------
Neil Gandal					Fax: 972-3-640-9908
Assistant Professor				Tel: 972-3-640-9604
Eitan Berglas School of Economics
Tel Aviv University
69978 Tel Aviv
Israel

E-mail: gandal@econ.tau.ac.il
------------------------------------------------------------------------------


