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         \begin{center}   
\begin{large}   
Judicial Independence in a Civil Law Regime:  The Evidence from Japan  
\end{large}   
            
 
  
        \bigskip   J. Mark Ramseyer  (The University of 
Chicago,Mark\_Ramseyer@law.uchicago.edu ) and Eric B. Rasmusen  (Indiana 
University, Erasmuse@indiana.edu)  
   \vspace{ 24pt  }

        {\it Abstract}   
        \end{center}   
     Because the Japanese judiciary exclusively hires young and unproven jurists 
for its lower courts, it maintains elaborate career incentive structures.  We 
use personnel data  on 276   judges (every judge hired between 1961 and 1965) to 
explore the determinants of career success and test whether politicians 
manipulate those incentives.  We find strong evidence that the system rewards 
the most productive judges,  but  little  evidence of on-going school cliques, 
and no evidence that the system favors judges who mediate over those who write 
opinions.  We also find that even as late as the 1980s, those judges who joined 
a prominent leftist organization in the 1960s were still receiving less 
attractive jobs than their colleagues.  Moreover,   judges who decided a case 
against the government  incurred the  risk that the government would punish them 
with  less attractive posts.   Finally, judges who declared unconstitutional a 
crucial section of the electoral law   received less attractive posts than those 
who held it constitutional.

\begin{small}
          We gratefully acknowledge the helpful comments and suggestions of John 
Haley, Bruce Johnsen, David Johnson, Daniel Klerman, Masaru Kohno, Richard 
Lempert, John Lott,  Matthew McCubbins, Setsuo Miyazawa, Yoshiro Miwa, Randal 
Picker, Steve Reed, Frances Rosenbluth, Tokuo Sakaguchi, Richard Samuels, Gary 
Saxonhouse, Stewart Schwab, Gary Schwartz,  Pablo Spiller, Michael Thies, Eiji 
Tsukahara, two anonymous referees, and participants in workshops at the American 
Law and Economics Association, the National Bureau of Economic Research, 
University of California--Berkeley, University of Chicago, George Mason 
University, Georgetown University, Harvard University, Hitotsubashi University, 
IIT Chicago-Kent, Indiana University, University of Michigan, University of 
Tokyo, University of Virginia,  Waseda University, and Washington University St. 
Louis.  We received generous financial assistance from The Lynde and Harry 
Bradley Foundation, the Sarah Scaife Foundation, The University of Chicago Law 
School and Committee on Japanese Studies.  
   \end{small}   
   


  %---------------------------------------------------------------%    
\newpage

\begin{center}
1.  INTRODUCTION
\end{center}

	Because Japanese courts hire unproven jurists at the outset of their 
careers, they use elaborate incentive structures to prevent those judges from 
shirking.  They do so through an administrative office called the Secretariat.  
The Secretariat  regularly monitors and evaluates each judge, and uses that 
information  to assign   judges to new posts every three years.  Because not all 
posts are   equal, it can use  the system to induce judges to work hard.   If it 
were willing, it   could also  use that  power to   induce them  to follow   
political orthodoxy.     	

In the article that follows, we explore both the general determinants of 
judicial career success  and the   extent of political influence.  Toward that 
end, we assembled  career data on all 276  judges hired from 1961 to 1965 (not a 
sample).   Within this data base, we find strong evidence that the Secretariat 
rewards the most productive judges.  We find  little  evidence of on-going 
school cliques, and no evidence of rewards for  judges who mediate  rather than  
adjudicate.  	More controversially, we also find   signs that political 
considerations may influence the careers of sitting judges.  First, even as late 
as the 1980s, those judges who joined a prominent leftist organization in the 
1960s were receiving less attractive jobs.   Second, if  a judge decided a case 
against the government, he incurred a significant risk that the Secretariat 
would   punish him with a less attractive post.  Third, those judges who 
invalidated the statutory ban on door-to-door canvassing,    a ban advantageous 
to the majority party,   were more likely to receive unattractive posts than 
those who upheld it.	

   We do not argue that  Japanese politicians  overtly  intervened in   the 
courts.  Rather, we show that Japanese judges faced incentives that were biased 
in favor of the   Liberal Democratic Party (the LDP,   in power continuously 
from 1955 to 1993).   Thus, the LDP was able to obtain the results it wanted 
without overt  intervention.   The logic behind this is basic to the Positive 
Political Theory developed so elegantly in the pages of this journal, and  basic 
to understanding the Japanese judiciary:  given the right institutional 
structure, visible intervention will be an out-of-equilibrium phenomenon.

	We begin by outlining the theoretical and empirical literature on judicial 
independence (Section 2).  We then explain the structure of Japanese courts 
(Section 3) and the nature of our data base (Section 4).  Using  ordered probit, 
we  explore the determinants of a judge's initial job posting (Section 5.1), and  
posts later in his career (Section 5.2).  With more extensive data on the class 
of 1965, we   test whether a judge who decides cases against the government 
receives less attractive posts (Section 6).  Finally, we turn to the most 
commonly cited example of a link between the political content of a judge's 
decisions and his career success: cases involving the constitutionality of the 
ban on door-to-door canvassing (Section 7).



\begin{center}
 2.  JUDICIAL INDEPENDENCE 
 \end{center}

	{\it 2.1.  Manipulability. }
  To understand the potential manipulability of Japanese courts, consider first-
- by way of contrast-- the U.S. federal courts.  To them, the President 
generally appoints only prominent middle-aged lawyers.  Most have proven 
themselves  politically loyal and congenitally workaholic.  He appoints these 
men and women to particular posts in particular towns.  There, they hear cases 
for the rest of their working lives.  

 Sometimes, a federal judge will move from the District Court to the Court of 
Appeals.  A Stephen Breyer will move from the Court of Appeals to the Supreme 
Court.  A William Webster will move from the courts to the FBI.  Otherwise, a 
typical judge never moves out of town, never changes jobs, and never earns a 
raise except in lockstep with every other federal judge.\footnote{ State court 
judges may face greater mobility.  Yet even they seldom worry that an 
administrator might move them from Los Angeles to Fresno, or demote them from   
appellate court to traffic court. } 
Judge Harold Baer pushed his luck with Bill Clinton when he excluded 80 pounds 
of cocaine as evidence, but  even then, Clinton could do nothing but 
fulminate.\footnote{President Clinton did call on Judge Baer to resign, but his 
influence was purely informal, and even for  expressing his opinion he was 
heavily criticized.  ``Baiting the Baer,'' {\it  Newsweek}, Apr. 1, 1996, at 64.    
}   For  most federal judges, how they do their job will have little effect on 
tenure, advancement, or compensation.
 
	Not so in some civil law regimes such as  Japan.  There, judges may  face  
just such threats.  Often, they join the courts immediately upon passing the 
bar.  Because they are young and unproven, the government has relatively little 
information about them.  It  seldom knows their political preferences.  Perhaps 
more basic, neither  does it know how hard or  fast they work.  Instead, it   
needs to make do with proxies such as exam performance. 


Because of this limited information, the Japanese government uses an elaborate 
monitoring and incentive system to induce its judges to work hard.\footnote{   
Presumably, if judges were appointed without track records, the risk of 
irresponsible judging would be more severe.} It maintains a judicial 
administrative office.  Through that office, it grades a judge's work and 
dispenses rewards.  When it reassigns a judge, much of the time it does so 
randomly simply to prevent judges from developing ties to the local mob. 
Sometimes, though, it also uses   assignments to reward and punish: the better 
the work, the more attractive the job it will give a judge and the more money it 
will pay him.	
Incentive structures, however, are manipulable.  A government may introduce an 
institutional structure to induce effort but use it to enforce political 
loyalty.  At least in theory,   it could use the structure to reward judges by 
the political complexion of the judgments they issue and the opinions they 
write.  The loyal it could ply with prestigious posts in attractive cities and a 
quick climb up the pay scale.  The heterodox it could let languish with low pay 
in branch offices in the outback.  In most cases, politics will not matter, for 
most cases involve no political issues of moment.  In a few cases it will. Our 
question  is whether   a judge faces politically skewed incentives in those   
unusual but   vitally important cases.



{\it 	2.2.  Theory. }
  Whether (or when) rational politicians will manipulate judicial incentives 
turns on a variety of questions external to the courts.\footnote{Whether 
politicians are self-interested or public-interested is not a central issue 
here.  It is by no means clear that an unselfish politician would necessarily 
prefer judicial independence; he does not want the judiciary to thwart the 
policies he proposes for the public good, whether because the judge disagrees 
with the policy  or because the beneficial policy is truly unconstitutional. } 
On the one hand, independent courts potentially solve several vexing political 
problems, which is perhaps why they  remain perennially popular  with voters, 
statesmen,  and law reviews. 

 First,  as McCubbins and Schwartz (1984)    prominently note,  independent 
courts help the ruling party  police the bureaucracy.  By giving disaffected  
citizens the right to sue  before an impartial tribunal, the ruling party can 
potentially obtain access to information about how well its bureaucrats perform. 
Armed with that information, it can   improve bureaucratic performance, and,  
crucially, improve its  electoral advantage.  


   

	Second, independent courts add credibility to governmental promises.
Whether to maximize the rents it extracts (Landes and Posner) or to lower the 
cost of its debt (North and Weingast), a  ruling party will want to make its 
commitments credible.  Subjecting its promises to the judgment of an independent 
court  does  just that.  
 

	Third, independent courts minimize a party's losses while out of power.  
To the extent judges are independent, they do not necessarily serve the party in 
control.  That they do not, in turn, will often comfort out-of-power politicians 
and their electoral sympathizers (Ramseyer).  To the extent that  politicians 
and their supporters expect   to be out of power,   they may rationally prefer 
courts whose  independence  reduces the stakes to controlling the government.  
	


On the other hand, independent courts introduce political problems of their own.  
Politicians do not maximize votes by promising desired policies, but rather by 
delivering  such  policies.  Independent judiciaries can obstruct that 
delivery.\footnote{ Though even independent judges may sometimes find that 
restraining their own behavior earns them returns of various sorts.  See 
Rasmusen (1994); Spiller and Gely (1992); Spiller and Spitzer (1992).}  
Moreover, many politicians rationally take short-term perspectives.  They care 
less about long-term credibility than about the next election.   The ruling 
party will always have a temptation to cheat on judicial independence in small 
ways.  For the party in power, the ideal judges are those with a reputation for 
independence (thus making its promises credible and cowing the bureaucracy) who 
actually toe the party line.  	


Ultimately,  therefore,   how independent      judges will be of    politicians      
depends on  factors external to the courts.    The more readily politicians can 
make their promises credible, the more cheaply they can monitor their 
bureaucrats, and the less likely they are to revert to minority status, the 
smaller their incentive to keep judges independent.  Because they will always 
wish to pretend that the judges are independent, however, any  control will 
necessarily be indirect. Any test will necessarily involve an analysis of    
outcomes, not words.  



	{\it 2.3.  Empirical studies.} Existing empirical studies do not tell us 
whether politicians in civil law systems like Japan do keep their courts 
independent.  Although several scholars have begun to publish sophisticated 
empirical analyses of judicial independence,  most  have studied   the 
comparatively hard-to-manipulate common-law systems (Spiller and Gely [1992]; 
Toma [1991]; Anderson, Shughart and Tollison [1989]; Cohen [1991]).  In perhaps 
the most sophisticated of the studies, however, Spiller and Gely (1992)  find 
evidence that courts do respond to interest group and voter pressures through 
the impact of political institutions.

	Although civil law systems like Japan would seem to give more 
opportunities for political intervention, we know of no systematic  multivariate   
study of judicial independence in a civil law environment.  A few scholars have 
considered the relationship of civil law judges to politicians.  To date, 
though, they have used historical rather than quantitative approaches,  and 
emphasized crises rather than routine situations (e.g., Muller [1991] on German 
judges under Nazi rule). 

	Even in Japan, where the debate has sometimes taken an aggressively 
political tone,  the debate remains open (compare Haley [1995]  and Miyazawa 
[1991]).  On the one hand, the ruling LDP almost never involved itself overtly 
in the courts.  Yet the absence of overt intervention does not mean the LDP gave 
judges   politically unbiased incentives. Critics of the Japanese judiciary have   
marshalled a variety of anecdotes that suggest just such bias.\footnote{For 
studies in English, see Hayakawa (1971), Miyazawa (1991),  Ramseyer (1994), and  
Ramseyer and Rosenbluth (1993: chs. 8-9).  The best original empirical research 
in Japan is probably Sakaguchi (1988)  and Tsukahara (1991).   }  
   The most common  stories are about   the ban in \S 138 of the Public Offices 
Elections Act on door-to-door canvassing (Koshoku senkyo ho [Public Offices 
Elections Act], Law No. 100 of 1950, \S 138).  
 Because incumbents obtain free media coverage while  challengers do not, the 
ban disproportionately benefits incumbents.  Because the   LDP  had the most 
incumbents during this period,  the ban disproportionately benefited the LDP.  
	

From time to time, a few lower court judges insisted that the canvassing ban 
violated the constitutional guarantee of freedom of expression.  According to  
anecdotal accounts, they suffered when they did (e.g., Ramseyer and Rosenbluth 
[1993: ch. 9]).  Take Haruhiko Abe.  He held \S 138 unconstitutional in 1968, 
and by 1990 had spent 11 years in branch offices, far more years than normal, as 
can be seen from  Table 2 later in this article.  Or take Masato Hirayu.  He 
held \S 138 unconstitutional in 1979, and by 1990 had spent 8 years in branch 
offices.  Among the judges who started in the same year as he did, he was now in 
the bottom 8 percent (Ramseyer and Rosenbluth: 171-172).   In the article that 
follows, we ask  whether a systemic multivariate approach will confirm the bias  
these anecdotes suggest. 

	
\begin{center}3.  THE JAPANESE COURTS	
 \end{center}

 {\it 3.1.   Lower Court Appointment and Reappointment.  }   All lower-court 
(i.e., High, District, and Family court)  judges in Japan  begin their judicial 
careers immediately  upon finishing their legal education.     They then stay 
judges for most of their working lives.  By the early 1990s, the courts employed 
some  2,800  judges (see Table 1).  Formally,  they  worked a series of 10-year 
terms;  in substance, they almost always found their terms renewed.  Legally,   
the Prime Minister  had the power to determine  both initial appointments and 
later reappointments; in fact, he usually deferred   to the Secretariat.  
Generally, he reappointed all sitting judges until they either resigned or 
reached mandatory retirement  at age 65.   

Lower-court judges handle some cases alone, but decide the more important cases 
as three-judge panels (a point that fogs but does not bias our data).   
Dissenting judges do not publish their opinions.\footnote{The judges themselves, 
however, know who dissents, and since promotion  is  handled within the judicial 
system, this information is available for  that purpose.  Also, non-publication 
of dissents prevents  the dissenter from appealing to the public at the same 
time as it fails to prevent the information from reaching the Secretariat.  }   
No lower court judge uses law clerks.  The rules by which cases are assigned to 
specific judges are set by the local court, and are generally non-discretionary.  


--------------------------------------------------------------------------------
--\\
 Place Table 1 here\\
--------------------------------------------------------------------------------
----\\
  

   
{\it 3.2.  Lower-Court  Postings. } During their careers of thirty-odd years, 
lower-court  judges in Japan move through a variety of jobs.  These jobs  vary 
along several dimensions. 

 First, they vary by geography.  The Secretariat can-- and  does -- routinely 
move judges from city to city.  Often it does so simply to keep judicial quality 
uniform and to prevent corruption.  
 
Second, the posts vary along the judicial hierarchy.  The Secretariat can-- and 
again does-- bounce judges up and down the hierarchy from the High Courts (the 
courts of appeals) to the District Courts (the trial courts) to the Family 
Courts (hearing cases involving, divorces, juveniles, guardians, etc.), to the 
branch offices of the District and Family Courts.   It routinely sends judges to 
the   less prestigious postings,   and such   assignments do   not necessarily 
signal disgrace, as can be seen from Table 2.\footnote{Note that the  custom of  
rotating the  high-quality assignments   necessarily means  that any   formula 
trying to explain  who gets such assignments will have relatively low predictive 
power-- low  ``$R^2$'' if a linear regression is  used.   }  Third, some posts 
involve prestigious administrative duties. The most successful judges become one 
of eight High Court Presidents. Modestly successful judges become District or 
Family Court Chief Judges. Almost all judges spend some time as a district judge 
with internal personnel responsibilities (a {\it sokatsu} assignment).  And a 
few judges work several years in the Secretariat or at the Ministry of Justice.  
The Secretariat itself selects the judges who staff the Secretariat; it 
apparently negotiates the Ministry of Justice postings with the Ministry's own 
personnel office.  Visibility and influence do not completely overlap; a staff 
position within the Secretariat can be highly influential, even if  less visible 
than  a seat on a High Court.    

 As a result, a judge who moves to a worse posting may have -- but has not 
necessarily -- been identified for special treatment.   This can be seen from 
the following two examples: 	
 
	
   {\it  Katsuya Onishi, an exceptional judge.}  Born in 1928. Kyoto University 
graduate.  1953: Kyoto District Court (DC).  1958: Secretariat. 1961: Hakodate 
DC. 1964: Secretariat. 1968: Tokyo DC.  1970: Osaka High Court (HC).  1971: 
Osaka DC, sokatsu. 1974: Tokyo DC. 1974: Tokyo DC, sokatsu. 1975: Secretariat. 
1985: Kofu DC (Chief Judge). 1986: Tokyo HC,  sokatsu. 1986: Secretariat 
(Secretary General). 1989: Tokyo HC (President).  1991:   Supreme Court.


 {\it  Masakazu Kuwamori, a typical judge.  } Born in 1926. No university 
information. 1953: Yamaguchi DC Branch Office. 1957: Osaka DC. 1960: Sendai HC. 
1962: Sendai DC. 1963: Nagasaki Family Court. 1968:  Osaka Family Court.  1970: 
Osaka DC sokatsu.  1971: Fukuoka DC,  sokatsu.  1974: Fukuoka HC.  1977: Osaka 
HC.  1979:  Fukuoka DC Branch Office (Chief). 1985:  Tokushima DC (Chief Judge).  
1986: retired (notary public).  
 
 xxx Note that Onishi went down as well as up. In 1961, Onishi had a worse job 
than  Kuwamori.  Both were sokatsu on the Osaka District Court at about the same 
time. 

--------------------------------------------------------------------------------
--\\
 Place Table 2 here\\
--------------------------------------------------------------------------------
----\\
  

\bigskip
 
 The Secretariat can also promote judges along the pay scale at different 
speeds.  By the Constitution, it cannot cut a judge's pay.  It can vary the rate 
of promotion, however, and critics have accused it of penalizing the politically 
heterodox by doing just that.  Unfortunately, we lack judicial pay data and    
cannot explore this issue.




\bigskip   

 {\it 3.3.  Judicial preferences.}  To determine the relative attractiveness of 
the various lower-court appointments, we talked with a wide range of Japanese 
observers and looked at the careers of the most successful judges.  
Idiosyncratic preferences aside, most judges seem to prefer Tokyo posts to all 
others, and to prefer other metropolitan centers if they cannot be in Tokyo.  
They mildly prefer High and District Court posts to Family Court posts, and 
strongly prefer all such posts to lower court branch offices.  Most aspire to 
some administrative responsibilities.  

 Although some American readers balk at the notion that judges would prefer 
Tokyo assignments, within Japan the point is uncontroversial. Tokyo is an 
upscale Manhattan and the Japanese cultural Mecca, but it is much more besides.  
For aspiring professionals, it is the quintissential information hub-- the seat  
not just of the national government but of the political opposition, most media 
organizations,  and most major corporate headquarters.   At least as important 
for  upper middle class families,  it is home to the University of Tokyo and two 
other first-tier national universities, to most of the best private 
universities,  and to most of the best preparatory schools.  For any parent with 
educational ambitions for his child, no city beats Tokyo. And for just that 
reason, many judges assigned to the provinces will (like their peers in 
business) move there alone and leave their families in Tokyo.\footnote{ So long 
as most judges prefer metropolitan centers, the hypothetical chance that a 
dissident judge prefers a provincial post does not eliminate the general 
deterrent effect of using provincial posts as punishment-- any more than the 
occasional criminal who  likes to spend his winters in jail eliminates the 
deterrent effect of jail time.   } 

	In Table 2 we display the    percentage of   career spent in various 
assignments for two groups of judges:  (a) the most successful judges (who  
eventually became Supreme Court justices or High Court Presidents), and (b) all 
those in the cohort of judges who began their careers in 1965, whether successes  
or  failures, who had not retired or left the judiciary early (before 1990).  
Note that the most successful judges spend more time in Tokyo and Osaka (the 
second largest city), more time in the Secretariat and other non-judicial posts 
(e.g., the Ministry of Justice), and less time in branch offices.  They do not 
spend much more time as {\it sokatsu} than other judges, but this is because 
they more quickly move to higher administrative roles like chief judgeships.

\bigskip
 	{\it 3.4.  The Supreme Court and the Secretariat. } The Japanese Supreme 
Court  is structured along entirely different lines from the lower courts. 
Fifteen justices comprise the Court.  They    are appointed by the Prime 
Minister, and serve until mandatory retirement at age 70. They do not rotate 
among different judicial posts. They hear most cases on five-judge panels, but 
the most important {\it en banc}.  Unlike lower-court judges, they use law 
clerks and sometimes publish dissents.   Among the last 20 justices appointed 
through 1990, the mean age at appointment was 64.  Six were promoted from the 
lower-courts, eight had been practising lawyers,  three had been prosecutors, 
two had been in the foreign service, and one had been a professor.  Of the 
justices, the  Chief Justice supervises the Secretary General, the head of the 
Secretariat.  Generally, at least one Supreme Court justice is  himself a former 
Secretary General.

	Because the LDP appointed Supreme Court Justices late in life, for most of 
the post-war years the   Court included only recent appointees.  By appointing 
them at age 64 with mandatory retirement at 70, the LDP effectively mitigated 
the ``Harry Blackmun problem'':  the risk that a politically loyal appointee 
would evolve over time into a very different beast  who promotes his new agenda 
over  his benefactor's.  In contrast to U.S. Presidents, the LDP could safely 
appoint Supreme Court Justices who would soon retire because it faced  such high 
odds (though less than 1) of staying in power.  

	By appointing older Supreme Court Justices, the LDP   also increased its 
stock of patronage capital.  Suppose (as seems likely)  the marginal utility to 
a judge of a  year of Supreme Court appointment declines with the number of 
years.   If so,  the LDP   increased its patronage capital by appointing more 
judges  for shorter periods.  Given the extent to which even the miniscule 
probability of a Supreme Court appointment  seems to motivate    some American 
judges, this carrot may have been quite useful. 

	Note two further points.  First, because the  Supreme Court Chief Justice 
supervised the Secretariat, the Supreme Court potentially controlled lower-court  
appointments.  Through his control over the Secretariat,   the Chief Justice and 
his colleagues   had the power to reward lower-court judges who performed as the 
Supreme Court wished   and to punish those who did anything else.  
  Second, because the Supreme Court included at least one justice who recently 
had headed the Secretariat, it  had the information necessary to use that  
potential   control  over the lower courts effectively.  These were not 
supervisors paralyzed by an inability to understand the large bureaucracy they 
headed. They   knew where the bodies were buried--  and indeed, to embroider the 
metaphor a bit, had actually buried some of them.  Indirectly,  by controlling 
Supreme Court appointments,  the LDP potentially controlled lower-court judicial 
careers as well.  	



\bigskip
 {\it 3.5.  This project. } In this study, we test whether the LDP exercised  
its  potential control over the lower courts.  Because posts vary in quality and 
rotations were normal practice, by controlling the Secretariat the LDP could   
control judicial careers without visibly intervening.  Invisibility is 
important, because constitutions seldom prevent politicians from intervening if 
they are willing to be heavy-handed enough.  If American Senators dislike a 
judge's decisions, for example, the U.S. Constitution leaves them   free to 
impeach him on trumped-up charges.  Hypothetically, they might even be able to 
transfer him to an undesirable city by changing the statutory structure of the 
courts (Ramseyer).  By doing so, however,  they would incur high political 
costs-- both because of the time involved and because of the effect such a 
public action  would have on the appearance of judicial independence.  	

The Japanese Prime Minister has analogous high-stakes options.  For instance, he 
can refuse on    political grounds to reappoint a sitting judge.  He will incur 
high political costs if he does, however, as the government discovered in 1971 
when one leftist judge was not reappointed (Ramseyer and Rosenbluth:165).  
Perhaps the Prime Minister could even intervene directly in the Secretariat to 
manipulate postings.  Because the statutory structure of the courts does not 
formally allow such direct intervention, though, we doubt that he could 
intervene consistently for forty years in such a direct manner and still keep it 
quiet.

	We test for a more subtle and indirect political strategy:   maintaining   
a politically skewed incentive structure.   In effect, we argue that the Prime 
Minister  appointed LDP loyalists to the Supreme Court,  and that those 
loyalists used their control over the lower courts to ensure that ordinary 
judges faced  incentives to toe the political party line. Granted, the 
Secretariat generally suggested the Supreme Court nominees to the Prime 
Minister,  and the  Prime Minister generally rubber stamped those suggestions.  
But that is irrelevant. For if we are right, because the Secretariat knew the 
Prime Minister had the power and inclination to reject the politically 
heterodox, it nominated only LDP loyalists.  The Prime Minister  approved its 
nominees-- but only because he knew it had every incentive to suggest appointees 
he could trust. 	Note that we are testing for objective evidence of political 
control, not investigating the psychology of the judges themselves.  Several 
readers of earlier drafts observed, for example, that Secretariat judges were 
often adamant (and apparently sincere) about preventing professional politicians 
from intervening in their affairs.  One way they kept the politicians at bay, 
they explained, was by punishing judges who acted in ways the ruling party 
abhorred.  They did not punish judges because they wanted to obey the LDP, in 
other words, but because they wanted to keep the LDP away.  This account of the 
psychology is perfectly consistent, of course, with our argument:  by keeping 
credible its threat indirectly to intervene, the LDP was able to induce the 
courts to monitor judges and punish those who acted in politically heterodox 
ways.

  

\begin{center}
 4. THE DATA
 \end{center}
 
 {\it 	4.1.  Sources. } We collected data from several  sources.  First, 
for information on judicial careers, we used the  {\it Zen saibankan keireki 
soran} (ZSKS),   a list of all postings for every judge hired after 1948.   

Second, for data on judicial opinions, we used the TDK LEX/DB data base (by 1997 
known as the {\it Hanrei taikei} data base) of judicial opinions.  Available on 
eight CD-ROM disks (by 1997 on ten disks), the data base works much like the 
Lexis and Westlaw systems.  Unfortunately, the collection is still slightly 
incomplete.  TDK began compiling the opinions only a few years ago and had 
nothing like the West national reporter system from which to work.  Nonetheless, 
we have checked the compilation scheme  and have no reason to think the coverage 
is biased in any way relevant here.	

Third, we obtained the membership roster for the leftist Young Jurists League 
(YJL) from {\it Osorubeki saiban }.  The authors of that book took the roster -- 
current as of mid-1969-- from the League's own newsletter.  	

Last, to investigate whether family status affected career success, we checked 
the Japanese cross between the {\it Who's Who} and the {\it Social Register} ( 
the {\it Nippon shinshi roku}) for 1969.  Because none of the judges from the 
classes of 1961 to 1965  appeared in the book, we did not construct a family 
status variable. This is actually  a useful negative finding--- the judiciary 
appears {\it not}  to be a career for those well connected by birth, despite the 
large number of judges who attended prestigious universities. 
 
\bigskip
 { \it  4.2.  Datasets.}  From this material, we produced four datasets.	
{\it  (a) Exceptional judges. } We collected data on the most successful of the 
post-war judges:  all judges in the ZSKS who eventually obtained postings to 
either the Supreme Court or the Presidency of a High Court.  As discussed above, 
we used this data to learn which posts constitute advantageous assignments (see 
Table 2).  

	{\it (b) Judges who ruled on Section 138 cases. } To explore whether 
judges who decided politically sensitive cases in ways contrary to LDP interests 
received unfavorable assignments, we investigated all judges who published 
opinions on the issue most commonly cited in this context:  the 
constitutionality of the ban on door-to-door canvassing under \S 138 of the 
Elections Act.  	

{\it c) Judges from the classes of 1961 to 1965.}  We compiled career data on 
all judges-- not just a sample-- who entered the courts during 1961 to 1965.  In 
order to compare careers of equal length, we then dropped those judges who had 
left the judiciary by April 1990.\footnote{Of the cohort of 394 judges who 
finished their legal training in 1961 to 1965, 3 began their careers in private 
practice; 12 died in judicial office; 4 retired at mandatory retirement age; 1 
was fired; 97 resigned; and 3 were dropped for other reasons. Of the 97 
resignations, 31  (32 percent) were YJL members. This is comparable to the 
judicial population as a whole---according to Table 1, 35 percent  oft hose  who 
did not resign were YJL members.}  Some critics accuse the Secretariat of 
pressing left-leaning judges into early retirement.  To the extent that this 
happened, our findings  understate the true scope of any political 
discrimination.  

Because Supreme Court justices have a large  body  of professional judges at 
their disposal to work as law clerks,  elsewhere (e.g., for purposes of 
calculating OPINIONS/YEAR for Table 2) we treated elevation to the Supreme Court 
as retirement.  Although in other circumstances this might have biased our data,  
it did not do so here for a simple reason.  As of 1990, none of the judges in 
the classes of 1961-65 had been named to the Supreme Court.	

{\it (d) Judges from the class of 1965.} For judges in the class of 1965 (a 
subset of dataset (c)), we investigated every decision they  published that 
involved the government as litigant in one of four fields:  labor, 
administrative, tax, and criminal law.  We included all opinions, whether 
written alone or by a three-judge panel.  We coded an opinion as ``anti-
government'' if the party fighting the government won a full or partial victory. 

 	Thoughtful readers will note the imprecision of this test.  Many of these 
opinions, for example, do not  involve distinctly political issues.   For a wide 
variety of reasons, moreover, the government may not want to win  every suit.  
If it used biased judges to win every case, its litigators would have less 
incentive to work hard.   If those litigators did not always represent 
government interests (whether because they were heterodox or lazy), it would 
find some victories hollow.  If the commitment problem Landes and Posner 
identified is real, any overt control over the judiciary would reduce its rent-
extractive potential.  And if it perceived its judges as biased in its favor, it 
might simply take more egregious positions-- to the point where even its pro-
government judges would balk (this selection effect reappears in Section 6.3(a) 
below).  

	Despite these objections, we use our coding scheme for two basic reasons.  
First, our scheme is simple and objective.  We considered coding opinions 
according to our subjective sense of whether they furthered LDP interests, but 
concluded that doing so would invite charges that we ``cooked''  the data.  To 
minimize the chance of conscious or unconscious bias on our part, we opted for a 
less precise but more objective test instead.  Importantly, given the 
politically sensitive nature of our findings within Japan, this objectivity 
insures the replicability of our results.	

Second, caveats about incentive effects, promissory credibility, and agency 
slack notwithstanding, governments generally litigate disputes because they want 
to win them.  To that straightforward and forthrightly simplistic extent, a 
decision that  goes against the  government   is an ``anti-government'' decision 
that will generally disappoint the men in power.  	


\bigskip
\noindent
 {\it 4.3.  The variables.}  We construct the following variables. 

	STARTING AGE:  The age at which a judge joined the judiciary.  To become a 
judge (or lawyer or prosecutor) in Japan, one must graduate from the government-
run two-year Legal Research and Training Institute (the LRTI).  During most of 
the years at stake, the pass  rate on the  LRTI entrance exam   ranged from 1 to 
4 percent.   Almost no one passed it the first time they took it.  Instead, 
would-be lawyers, prosecutors, and judges typically passed   only on their 3rd, 
4th, or 5th tries.  Although it remains hypothetically possible that someone 
became a judge at age 30 because he decided to switch careeers at age 28, it is 
far more likely that he simply failed the exam every year from age 21   to age 
28.  	We hypothesize, therefore, that the lower the age at which a person 
graduates from the Institute,   the higher his cognitive ability, the  higher 
the opportunity cost of his years spent  studying,   and the greater his 
willingness to work hard.  Because the quality of a judge's work will   depend 
in part on   his intelligence  and his drive,  these  factors should together 
correlate with judicial performance.  Necessarily, to the extent that the 
Japanese courts try to maintain a meritocratic environment, STARTING AGE should 
inversely correlate with career success.

	SEX:  1 if a judge is male and 0 if female.  

	TOKYO U:  1 if a judge went to Tokyo University, and 0 otherwise.  Because 
observers widely consider the Tokyo University Law Department the most 
selective, graduation there should positively correlate with intelligence and 
drive.  In addition,  many critics argue that Tokyo University alumni form a 
clique within the courts and help each other in their careers, independent of 
ability.  	

KYOTO U:  1 if a judge went to Kyoto University, and 0 otherwise.  
Traditionally, observers have considered the Kyoto University Law Department 
second only to Tokyo University.  Critics have accused Kyoto University alumni 
of running a clique as well.  

	CHUO U:  1 if a judge went to Chuo University, and 0 otherwise.  Chuo 
University operates a large and respectable but not first-tier law department.  
We include the variable because so many judges attended the school.

	NO UNIVERSITY:  1 if the ZSKS lists no university for a judge, and 0 
otherwise.  A 1   mean   either that he  attended the LRTI without graduating 
from a university (possible but unlikely) or that he chose not to disclose his 
educational background (a choice that suggests he graduated from an 
unprestigious school).    	

OPINIONS/YEAR:  the number of recorded decisions a judge published up to 1990 
divided by the number of years he spent on the bench.  We exclude those years 
during which he handled only administrative work. 

	Note a potential problem here.  The law reporters, both official and 
unofficial,  do not publish all opinions.  Instead, they publish an opinion only 
if the editors find it interesting or important.  If a branch office judge hears 
less important cases, this could mean that he will not publish as much even if 
he works hard, leading to a    simultaneity problem.  Suppose OPINIONS/YEAR  is 
positively correlated with career success.  That fact could mean either that 
judges receive inferior assignments because they publish less, or that they 
publish less because they receive inferior assignments.     To check for  this 
problem, we used our Class of 1965 data to create another variable:  
productivity for all years in courts other than lower court branch offices or 
summary courts.  Fortunately for our purposes, the correlation between that new 
variable and OPINIONS/YEAR  was .98, indicating that adjusting for poor 
assignments would make little difference.\footnote{Table 8 provides further 
support for this. The prior opinions variable takes values of 1.12 and 1.28 for 
the two groups in that table, despite  large differences in job quality in the 
other dimensions shown.} 

 We will examine four variables that measure  job quality for a judge.   The 
numerical values in all of them are ordinal, not cardinal, measures.   A value 
of 3 in 1ST POST does not mean that  this  judge's first job was 3 times better 
than that of his classmate who received a value of 1, only that it is a better 
job.   The regressions will use  the job quality variables as dependent 
variables in ordered probit, a procedure which  uses only the ordinality of the 
dependent variables.  

	1ST POST:  the prestige of the first assignment a judge receives.  The 
variable is 3 if it involves an administrative assignment,   1 if it is on a 
District or Family Court, and 0 if it involves a lower court branch office or 
Summary Court.     For the vast majority of judges, the value was 1.\footnote{We 
do not let this variable take a value of 2 because  we judge there are  fewer 
gradations of quality of first post than  in  later posts or location. Given 
that the variables are purely ordinal, the cardinal number we assign is 
unimportant to the econometrics.    In the next variable, 1980s POST, a value of 
2 will be used to indicate {\it sokatsu} posts, but beginning judges never 
receive that type of post.  }   	
 

1980s POST:  the prestige of a judge's assignments during the 1980s.  If he 
spent at least 3 years in an administrative assignment, it is 3; if he spent at 
least 3 years in either an administrative assignment or a {\it sokatsu} post 
(but not 3 years in an administrative assignment), it is 2; if he does not 
qualify for the categories above and spent at least 3 years in a lower court 
branch office or Summary Court, it is 0; otherwise, it is 1.  For this and the 
other variables, we count time in the branch office only if the judge was not 
the official head of the branch office and did not have {\it sokatsu} status.	

1ST LOCATION:  the location of a judge's initial assignment.  This is 3 if the 
judge's first assignment was in Tokyo (including Hachioji), 2 if in  Osaka, 1 if   
in another large metropolitan area (Yokohama, Nagoya, Sapporo, Kobe, Kyoto, 
Fukuoka, Kawasaki, Hiroshima, or Kitakyushu), and 0 if otherwise.

	1980s LOCATION:  a judge's location during the 1980s.  It is 3 if he    
spent at least 5 years in Tokyo, 2 if at least 5 years in Osaka or Tokyo (but 
not 5 years in Tokyo), 1 if at least 5 years in a major metropolitan area (but 
not 5 years in Tokyo or Osaka), and 0 if otherwise.

	YJL:  membership in the Young Jurists League (YJL).  The YJL is an 
organization of lawyers, law professors, and judges that generally supports 
leftist causes and which its detractors consider a Japan Communist Party 
affiliate.  The variable is 1 if the judge was a member in 1969, and 0 
otherwise.	

EARLY ANTI-GOVT:  the number of anti-government decisions (defined at Section 
4.2(d)) that a judge issued during 1965-74.  	

LATE ANTI-GOVT:  the number of anti-government decisions that a judge issued 
during 1975-84.

	
	ANY EARLY ANTI-GOV:  1 if a judge issued any anti-government decisions 
during 1965-74, and 0 otherwise.

	ANY LATE ANTI-GOV:  1 if a judge issued any anti-government decisions 
during 1975-84, and 0 otherwise.



\bigskip
\begin{center}	5.  THE RESULTS	
 \end{center}

   {\it 5.1.  First assignments. }
  We begin by investigating the factors that determine a judge's initial 
assignment.  The best jobs, our regressions suggest, go to the judges with the 
potential for highest performance.  Table 3 reports the results of  an ordered 
probit regression of  two measures of the attractiveness of his first job  on 
the judge's personal  characteristics.  Consider each column separately.  	

{\it Column A:}   Recall that 1ST POST measures whether a judge receives 
administrative responsibilities, receives a routine District or Family Court 
assignment, or is stationed to a branch office or Summary Court.  Because  only 
a very few  judges  (3 in our sample) begin   their careers with administrative 
responsibilities, column A effectively shows only that the worst jobs (primarily 
the branch office assignments) go to the oldest novice judges.  Because age at 
appointment    correlates with the number of times the judge failed the LRTI 
exam, it inversely correlates potential performance.  The worst initial jobs, 
the regression   suggests, go to the judges least likely to do good work.	

{\it Column B: }  The regression on 1ST LOCATION asks who receives the prized 
Tokyo and Osaka assignments.  According to the results, those jobs go to the 
judges (i) who are youngest, and (ii) who attended the most selective 
universities.  Once more, the regression suggests that the best jobs go to the 
judges most likely to perform well.  

	The coefficient for YJL is insignificant in both regressions.  Because the 
League's membership rolls did not become public until 1969, the Secretariat 
probably would not have known who was a member.  Nonetheless, if the coefficient 
had been significant, it would have suggested that the Secretariat both had 
access to other information about a judge's political beliefs, correlated with 
YJL membership, and used that information to discriminate by ideology.  In fact, 
it seems not to have done so.


--------------------------------------------------------------------------------
--\\
 Place Table 3 here\\
--------------------------------------------------------------------------------
----\\
  
 The discussion above focussed on which variables were statistically 
significant, rather than  on the values of the   coefficients. 
 Interpreting probit  coefficients requires some care.   To find  the predicted 
post or location for a judge,  one combines   the estimated Table 3 coefficients 
and each judge's variable values, as with linear regression.  We then use these 
terms to generate a ``score'' for each judge.  As ordered probit also generates 
estimated  ``cutoff scores'',  we match each judge's ``score'' to the cut-offs 
in order to generate a predicted posting for each judge.
  

To explore how this works, consider Takeo Wada, the very last judge in our 
sample,   who can fairly be called a typical judge based on observable measures.   
For the regression in Table 3.B., the  cutoff scores  were -3.25, -2.57, and -
2.05.  Table 4 shows that Judge Wada's   location  score is -3.52.     Because -
3.52 falls below the bottom cutoff of  -3.25,  the modal value of  his predicted 
location is 0.  If his score were  -2.90 instead, he would fall in the -3.25  to 
-.2.57 range and have a predicted modal location of 1.  


--------------------------------------------------------------------------------
--\\
 Place Table 4 here\\
--------------------------------------------------------------------------------
----\\


	Because for each judge we have only an estimated score,   our predictions 
do not take straightforward integer values.  If we knew with certainty that 
Judge Wada's true location  score were -3.52, we could predict with certainty a 
posting of 0.  Because -3.52 is just an estimate, however, his true score might 
be higher or lower.  With positive probability,  his score  might even be 0.5,  
for example,  in which case  his predicted posting would be 3 rather than 0.  
 Accordingly, if Judge Wada's  score  is -3.52, our best prediction is not a 
posting of 0 but a weighted average of 0, 1, 2, and 3.  Those weights will be 
our estimated probabilities of the true score lying in the four intervals of $[-
\infty, -3.25], [-3.25, -.2.57], [-.2.57, -2.05]$, and  $[-2.05, +\infty]$, 
found    by using the standard error of  the  estimate.  Our predicted career 
quality is the resulting weighted average. 


For Judge Wada, with a  score of -3.52,  
the expected value of  his first location is .64.  (The actual value for  his 
first location was 0, so the residual is -.64.) 
If the score rose from -3.52  to   --3.10 because the judge began at   3 years 
younger, the expected location would improve to 1.05, and the modal location 
would jump to 1.   Thus,   the coefficient on age is not only statistically 
significant, but is large enough that  a reasonable change in its value leads to 
a real change in the predicted job location. 


Table 4 can also be used to see    the relative importance of the different 
variables.     If the judge were three years older, his score would    fall by  
.42, as just discussed.    If the judge were female,  her  score would fall by  
.35.  Both of these are  realistic magnitudes of change within the population, 
implying  that  sex and age  are of   roughly the same   importance.

  

Interpreting the   posting   regression  is   similar, but has  less interesting 
results.  Judge Wada  has    an expected first   posting of  .90  and a modal 
location of  1.       (His actual posting value   was 3.) 
If the score were to rise from -4.46  to   -4.10 because the judge began     3 
years younger, the expected location would improve to  .98, and the modal 
location would remain at 1.   As this shows, the posting  regression  has less 
predictive power than the location regression. It  takes a much bigger 
improvement in characteristics to get a sizeable improvement in predicted 
career. Not only are the coefficients in the first posting regression mostly 
statistically insignificant; they are also ``economically insignificant''.  
  

\bigskip
 {\it 	5.2.  Late assignments. } Turn now to Table 5, the determinants of 
late-career success.  In this set of regressions, we ask which judges received 
the prized jobs in the 1980s, some 20 years after they joined the courts.  

	First, in the location regression STARTING AGE is significant, but in both 
regressions university affiliation is not.  That STARTING AGE continues to be 
important decades later suggests that interest in the law, intelligence, and 
drive matter, and in ways beyond their effect on the judge's first job.  That 
university affiliation loses significance (other than through its effect on 1ST 
LOCATION)   suggests that critics   exaggerate the importance of university 
cliques.  If cliques mattered, university affiliation should affect later 
assignments, perhaps even more than the initial assignment  since over the 
course of time a judge's university classmates would rise to power in the 
judicial establishment.  That a judge's university matters only through the 
initial assignment,  whereas STARTING AGE has an independent continuing effect,  
implies that the Secretariat uses it as a proxy for ability in determining a 
judge's initial assignment, but finds   it becomes less useful as a proxy once 
the judge has developed a track record.	

Second, 1ST LOCATION correlates with a judge's later assignments.  Although  
``1ST LOCATION = 2'' cannot be significantly distinguished from the other 
levels, ``1ST LOCATION = 1''  and  ``1ST LOCATION = 3'' are both significantly 
better than  ``1ST LOCATION = 0'', the dummy left out of the regression, and  
``1ST LOCATION = 3'' has the bigger coefficient, as one would expect.   This 
corroborates those accounts suggesting that the Secretariat places new judges on 
fast and slow tracks, and that an initial assignment to the Tokyo District Court 
predicts later success.\footnote{There is, however, an econometric caveat   to  
this conclusion.   !ST LOCATION is itself  influenced by ability. To the extent 
that  other variable fail to  completely  control for ability,  part of the 
explanatory power of 1ST LOCATION  in Table 5 will be due to its proxying for 
ability, rather than any independent effect.  }  	

Third, OPINIONS/YEAR matters:  judges who write many publishable opinions do 
better than those who write few.  Although this restates the importance of 
intelligence and hard work, its significance goes further.  From time to time, 
observers suggest that Japanese society may reward judges who settle cases 
rather than decide them.\footnote{The classic account tying low levels of 
litigation in japan to a cultural
aversion to clear-cut court outcomes is Takeyoshi Kawashima (1963).} Because of 
a cultural preference for negotiated settlements, they argue, Japanese encourage 
their judges to settle cases when they can.  Because settlements do not appear 
in our data, we do not know whether the most successful judges settle the lowest 
percentage of their disputes.  We do know that the most successful judges are 
the most prolific in writing published opinions for the cases that failed to 
settle. 	

Last, independent of the quality of a judge's work, political preferences 
matter:  whether a judge was a YJL member inversely correlates with whether he 
received prestigious administrative responsibilities in the 1980s.  Those judges 
named as part of the Marxist group in 1969 were still receiving less attractive 
jobs 10 to 20 years later.  Curiously, YJL membership did not affect the 
location where the judge worked.  Perhaps the Secretariat was willing to assign 
leftists to the cities.  Crucially, however,  it tended not to give them   the 
highest positions within the judicial hierarchy.



	The correlation between YJL and STARTING AGE is -.31.  Disproportionately, 
it seems, the most able members of the judiciary joined the group.\footnote{This 
should not surprise readers.  During the 1960s, the SDS's  influence was 
greatest in  the   elite U.S. universities.}  The point explains why some 
analyses that simply compare the jobs of League members and non-members find no 
discrimination (e.g., Ramseyer and Rosenbluth: ch. 9), and underscores the 
importance of multivariate analysis.  Given their superior talent, the YJL 
members ought to have done better than average.  Doing just as well as their 
classmates  would  therefore  be a sign  of failure.  


--------------------------------------------------------------------------------
--\\
 Place Table 5 here\\
--------------------------------------------------------------------------------
----\\


Interpreting these regression coefficients  requires the same procedure as with 
the regressions for the first job.   Again we will use Judge Wada, in Table 6.  
As with Table 4,  we  ask how a realistic change in the value of a variable 
would affect the score.  Converting from male to  female,  the   score would 
fall by .22.  If the judge were three years older, his score would    fall by  
.21. Both of these are  realistic magnitudes of change within the population, 
and so one might conclude that  sex and age  are of  approximately equal  
importance.  The  location score gives the judge an expected location of .94  
and a modal location of  0.      (The actual value for this judge was 1.) 
If  we add .22 to increase the score   from -1.11  to   -.89, the expected 
location would improve to 1.17  and the modal location would jump to 1.  

--------------------------------------------------------------------------------
--\\
 Place Table 6 here\\
--------------------------------------------------------------------------------
----\\

 Indeed, it seems that   in the location regression the variables which are 
statistically significant all   have coefficients that are also  of meaningful 
size, though some other variables (like sex) that are statistically 
insignificant also have large coefficients.\footnote{ Note the big coefficient 
in  Table 4 for Chuo University, which also comes up to at least the15 percent 
significance level.  Perhaps the place to look for an  
 Old Boy Effect is   Chuo,  not Tokyo.     }
   Most interesting, perhaps, is the very large coefficient of 1.13 on  ``1st 
location =3''.   It contributes 1.13 to the judge's score if his first job was 
in Tokyo,   a very strong effect  in terms of getting   later Tokyo  jobs.  Note 
that this is not just the effect of inertia.  The  location variable here is  
based on number of years spent in a location, but almost  all   judges  rotate  
out of Tokyo   at some point    even if they begin there.  

  The posting regression's coefficients for the variables which were   also 
statistically significant in the location regression--  ``1st Location=1'', 
``1st Location=3'', and  OPINIONS/YEAR--- are of  the same order of magnitude.  
STARTING AGE has a coefficient size about half that in the location regression,  
so its size is reasonably large, but the error is greater, and so it is not 
statistically significant in the posting regression.    YJL has the  reasonably 
large coefficient of  $-.28$  and is   statistically significant,  but  the 
error distribution in the posting regression is flat enough that the coefficient 
of .28 does not have  strong effect on the predicted posting.    The  posting  
score  of  -.03   gives  our  benchmark,   Judge   Wada,   an expected location 
of 1.84   and a modal posting of  2.      (His actual value   was 1.) 
If  we convert him to a YJL member and subtract .28, his    score falls  from -
.03  to   -.31,    the expected postng falls to 1.63, and the modal  posting   
remains at  2.   For the modal posting to fall to  1 would require a decrease of 
the score to -.77, while to increase to 3 would require an increase to .92.  
What this tell us is that although the posting regression may be able to tell us 
what variables are  statistically significant,  its overall performance in 
predicting posting is poor-- factors not in our regression equation are 
relatively more important than in the location regression.   

  
\begin{center}
 6.  THE EFFECT OF ANTI-GOVERNMENT OPINIONS
 \end{center}
 
	{\it 6.1.  The method. }
  Our first political variable was YJL membership, which is  cleanly defined and 
relatively easy to collect for the entire cohort of 276 judges.  We now turn to 
a more complex inquiry:  whether the way a judge decides a case influences the 
jobs he obtains.  More specifically, we ask whether a  tendency to decide cases 
against the government hurts his career.\footnote{Note that since the Liberal 
Democratic Party controlled the government during this entire period, we cannot 
distinguish between  the two hypotheses that (a) judges who went contrary to the 
party in power had worse careers, and (b) judges who went contrary to the LDP 
had worse careers.}   We find that it may.   This inquiry, however, introduces 
problems in measurement, theory, and econometrics.   We have already discussed   
measurement issues,  in Section 4.2(d).   

 

 The    theoretical  issue arises because of  the Priest-Klein (1984)  selection 
effect.     Litigated cases are not a random sample of all disputes,  and  who 
wins the cases that go to trial     may say  more about    which  cases go to 
trial  than  about how the judge views  the two sides.     In order to avoid  
trial  costs, most disputants settle disputes when  they agree about the likely 
litigated outcome.    As a result, cases do not go to trial randomly.  Instead, 
they go to trial when the judge's expected decision is unclear.  Just because 80 
percent of judge Y's decisions are pro-plaintiff does not necessarily mean he is 
pro-plaintiff:  he may only be pro-plaintiff in the most complicated cases, 
where the litigants found his decisions hardest to predict.  For the purposes of 
this analysis, settlement could have an even more bizarre effect: it may be that 
the government goes to trial with its most outrageous cases only when it knows 
the judge is particularly pro-government, and is only moderately displeased when 
the government's arguments are too weak even for that judge to swallow.  Thus, 
the judges who rule against the government   might be the most  pro-government 
judges.	

Two further complications are (a)  under Japanese public law, the government 
will find it hard to settle many types of cases out of court (e.g., tax 
disputes, as Kaneko (1992: 78) explains), and (b) some observers claim that many 
Japanese plaintiffs litigate public law disputes for their publicity effect  
rather than to win.  To the extent that either phenomenon occurs, the selection 
bias will be less and the percentage of government victories will convey more 
information about a judge's political preferences.   
A potential problem nonetheless remains. 


 Settlement will be most common where the parties know a judge's style and 
biases most precisely.  If they know nothing about a judge, he will hear cases 
that are randomly selected.  Given that randomness, his verdict rate will indeed 
tend to disclose his biases.  A judge with a shorter track record is one about 
whom litigants will have less information.  Accordingly,   the selection bias  
should  be strongest among judges at the end of their careers, and weakest at 
the start.  
   
	The econometric issues result from the enormous amount of time necessary 
to collect this data.  Because of this problem, we examined the opinions only of 
the 54 judges in the Class of 1965 who stayed in the judiciary through 1985.  We 
now must combine our 54 observations on judicial opinions with our 276 
observations on all the other variables relevant to a judicial career.  If we 
were willing to drop 222 observations, the econometrics would be simple:  we 
would repeat the probit regressions in Table 5, but with opinion variables added 
to the right-hand-side.  This not only discards information, however, but raises 
doubts about the validity of the estimates and the standard errors, since probit 
is a nonlinear, asymptotic technique for which having a large sample is 
especially important.   

	Instead,  we take a different approach.  We begin with the regressions of 
Table 5, which use all 276 observations to predict career success.  These 
regressions do not explain all the variance in the data, and generate an 
unexplained residual for each judge.  If we can explain this residual using 
judicial opinion variables, we will have shown that a judge's opinions matter, 
and ought to have been in the regressions in Table 5.  Moreover, because the 
residual is a continuous variable, we can use ordinary least squares, which does 
not rely on asymptotics for its validity.  	

More specifically, we first turn to our Class of 1965 dataset and use our Table 
5 regressions to generate a  ``residual'' for each judge: his 
 predicted career quality minus his  actual posting  of 0, 1, 2, or 3. This 
residual is   a continuous variable that measures judge X's unexplained career 
quality.  If positive, it indicates that he did better than our regression 
predicted; if negative, it indicates he did worse.  We then  used a logit 
transformation to map the value of the residual, which lies between -3 and +3, 
to the entire real line between positive and negative infinity,  mapping  the 
raw residual $u$ to $log[(u + 3)/(3 - u)]$. 
This allows us to use a formal test of a model  in which  we test the null 
hypothesis that this transformed residual is just   a normally distributed 
disturbance against the alternative   that it also depends on  political 
variables.       If    a judge's decisions had no impact on his career, then 
regressing his residual on a variable summarizing his decisions would yield an 
insignificant coefficient.  If they did have an impact, then-- crucial to the 
analysis here-- the coefficient would be significant.	


\bigskip


{\it 6.2.  Results.}  According to Table 7, judges who decide cases against the 
government  receive less attractive jobs.  In Part A of Table 7, the   number of 
anti-government opinions that a judge wrote in 1975-84 inversely correlates with 
the odds of receiving a post in an attractive city in the 1980s.  In Part B, 
whether a judge decided any anti-government opinions (a 0-1 variable) in 1975-84 
inversely correlates with receiving high-status posts in the judicial hierarchy 
in the 1980s.	

The simplest explanation for this phenomena is that it represents a 
straightforward punishment strategy:  if  a judge  decides cases against the 
government, the expected value of  his  next several jobs falls.  The 
probability of punishment may well be less than 1.  After all, the government 
will not care equally about all its cases; it will not want to win every case 
(for the reasons discussed in Section 4.2(d)); and it will not   punish every 
judge on a 3-judge panel.   Notwithstanding these caveats, according to Table 7  
anti-government opinions translate directly into less attractive posts in the 
near future.    

We  find the haphazard confidence levels a puzzle.  In regression  7A, only the 
location residual is significant, and in 7B only the post residual.  We suspect 
that this reflects the noise in the data  discussed in the immediately preceding 
paragraph  and the relatively small sample size.   Speculatively, however, we 
might suggest that for the sensitive administrative posts in part B,  having any 
anti-government opinions at all is  a black mark, whereas for location, more 
closely measuring the value of the job to the judge himself,   rewards and 
punishments  take a more gradual form. This would accord with the  negative 
effect on post  but not location  of YJL membership found earlier in this 
article.    It is  most important to the government to have  appropriate judges   
in the right posts, even though it may be more important to   a judge to have 
the right location.  At any rate, it should also be noted that     despite the 
often large standard errors,  the signs for the late opinions are negative in 
all four regressions.

 
--------------------------------------------------------------------------------
--\\
 Place Table 7 here\\
--------------------------------------------------------------------------------
----\\
 
\begin{center}
  	7.  ELECTORAL LAW DECISIONS 	
 \end{center}

 
Notwithstanding  this evidence,  several readers of earlier drafts of this 
article noted that  Section 6 does not show distinctly {\it political} control. 
It suggests that the courts favor the government, but not whether they favor one 
political party over another.  Some political scientists assert that Japanese 
bureaucrats operate almost completely autonomously from the government.  If so, 
then the results in Section 6 could simply imply that judges answered to the 
prosecutors in the Ministry of Justice,  and  elected officials had no 
influence.  To explore this issue, we chose an issue on which the LDP and much 
of the opposition took  flatly opposing views and in which Ministry of Justice 
bureaucrats would   have had no independent preference: the constitutionality of 
the ban in \S 138 of the Elections Act  on door-to-door canvassing. As discussed 
earlier, because incumbents have greater access to the media than challengers 
and the LDP had more incumbents than any other party, LDP leaders favored the 
ban.  For precisely the same reasons,  many opposition leaders (partularly among 
the Communists) opposed it.\footnote{ (xxx ADD CITE HERE.)}

Compare, therefore, the posts received by judges who held the ban constitutional 
with posts received by  those  who held it unconstitutional.   Among the lower 
court judges, we located 37 who held the ban constitutional and 9 who held it 
unconstitutional (the Supreme Court consistently held it 
constitutional).\footnote{See   Japan v. Taniguchi, 21 Saihan keishu 1245 (Sup. 
Ct.
Nov. 21, 1967). } Using data on these 46 judges, we test whether a judge's 
decision on the issue affected  his assignments. To this end, let us introduce 
several new variables, the average values of which are shown in Table 8 
separately for the two groups of judges.   

 

PRIOR POSTS:  the prestige of a judge's assignment before the \S 138 decision.  
The variable equals 3 if he spent at least 3 years in an administrative job 
during the 10 years before the decision; 2 if he did not meet that requirement 
but spent at least 3 years in an administrative or {\it sokatsu} capacity; 0 if 
he did not meet either of those requirements but spent at least 3 years in a 
lower court branch office or Summary Court; and 1  otherwise. 

	LATER POSTS:  the equivalent to PRIOR POSTS for the 10 years after the 
decision.  It takes the values  0, 1,2, or 3. 	

PRIOR LOCATION:  the desirability of the judge's location before the \S 138 
decision.  The variable is 3 if the judge spent at least 5 of the previous 10 
years in Tokyo; 2 if at least 5 years in Tokyo or Osaka (but not 5 in Tokyo); 1 
if at least 5 years in metropolitan areas generally; and 0  otherwise.	

LATER LOCATION:  the equivalent to PRIOR LOCATION for the 10 years after the 
decision.  It takes the values  0, 1,2, or 3. 	

	 
PRIOR BRANCH:  the percentage of years a judge spent in branch offices during 
the 10 years (adjusted appropriately, if fewer years on the bench) before the \S 
138 decision.

	LATER BRANCH:  the equivalent to PRIOR BRANCH for the 10 years after the 
\S 138 decision. 

	PRIOR {\it Sokatsu}:  the percentage of years a judge spent in {\it 
sokatsu} assignments for the 10 years (adjusted appropriately, if fewer years on 
the bench) before the \S 138 decision.	

LATER {\it Sokatsu}:  the equivalent to PRIOR {\it sokatsu} for the 10 years 
after the \S 138 decision.

PRIOR OPINIONS/YEAR:  the judge's productivity (published opinions per year on 
bench) for the 10 years before the \S 138 decision. 



	\S138 DECISION:  0 if the judge held the canvassing ban constitutional and 
1 if otherwise.

The summary statistics in Table 8 suggest  that the judges who held the ban 
unconstitutional were already in worse jobs before they heard the controversial 
case. The average prior post  is .44 for them, compared to 1.41 for the  other 
37 judges,  prior location is .00 compared to 1.05, prior sokatsu is .00,  while 
prior time in branch offices is .50 compared to .10.  The percentage YJL 
membership was .56 compared to .14, so the politics of these judges may have 
been well known long in advance of their anti-government decisions.  

  ------------------------------------------------------------------------------
----\\
 Place Table 8 here\\
--------------------------------------------------------------------------------
----\\


  
  A glance at Table 8 seems to show that  the careers of the  unfortunate 9 
judges actually improved after their \S 138 decisions.  Ordered probit 
regressions of   Later Posts and Later Location on earlier career variables and 
the \S 138 decision  failed to show   significant  relationships, however, and 
the improvement may just be regression to the mean.   When careers are bad 
enough (e.g., an average location of 0.00), there is nowhere to go but up.    
Ordered probit is undependable in this context, though, since there are only 46 
observations. 

   Two other career  variables, however, show a  distinct punishment effect.  
 Table 9 shows the results of  two tobit regressions using  time in branch 
offices and time as {\it sokatsu} as the dependent  variables.   Tobit is 
appropriate rather than ordinary least squares because the dependent variables, 
being number of years,  are  bounded below by zero.      These variables  are 
narrower than the career variables used in the previous regressions in this 
paper, and this may aid in finding significant results with a small sample.  
Tobit, while a nonlinear regression technique, is much closer to ordinary least 
squares than ordered probit, imposing more structure on the regression.  


	The results in Table 9  tend to support   the popular accounts of the \S 
138 controversy.    The position a judge takes on the constitutionality of \S 
138 ban significantly affects both the time he spends in branch offices and the 
time he spends with {\it sokatsu} duties.   The  coefficients  for    the   \S 
138 decision  variable  are large, and significant at the 1 percent and  8 
percent level for  both Later Branch and  Later  {\it Sokatsu }, and this is 
true even conditioning on the judge's previous  job quality.      Should he hold 
the  \S 138 ban unconstitutional (i) he   increases the amount of time he will 
likely spend in branch offices over the next 10 years, and (ii) he   decreases 
the amount of time he will spend with {\it sokatsu} responsibilities.  


--------------------------------------------------------------------------------
--\\
 Place Table 9 here\\
--------------------------------------------------------------------------------
----\\
  

\begin{center}
  8.  CONCLUSIONS
 \end{center}

	Because the Japanese courts hire unproven jurists, they maintain elaborate 
incentive structures to prevent their judges from shirking.  In this article, we 
used career data from the courts   to explore the general determinants of career 
success   and to test how extensively the government manipulates those 
incentives toward political ends.  

	We find considerable evidence that the government rewards the smartest and 
hardest working judges.  We find little evidence of ongoing school cliques (more 
precisely, no evidence beyond the school advantage in the initial job 
assignment).  We also find no evidence that the Japanese system rewards judges 
who mediate over those who adjudicate.  Rather, the judges who do best are those 
who publish the most opinions.	

More controversially, we locate several potentially political phenomena.  First, 
those judges who joined a prominent leftist organization in the 1960s were still 
receiving less attractive jobs than their peers in the 1980s.  Second, those 
judges who decided cases against the government faced a straightforward short-
term penalty:  on average, they received less attractive assignments over the 
next several years.  Third,  those judges who held the ban on door-to-door 
canvassing  unconstitutional,  contrary to the hopes of the LDP, spent more time 
in branch offices and less with local administrative responsibilities than  
their peers who held it constitutional.  All told, the evidence suggests that 
LDP appointees may have created and maintained an incentive structure with a 
distinct political bias.  

 \newpage
 FOOTNOTES
 
xxx The footnotes all need to be moved here. If we do that now, we might miss 
the significance of the footnotes, though. 

 The paper needs to be double spaced too. 





\newpage
\begin{center}
 REFERENCES
 \end{center}

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\newpage
 	TABLES

 

  \begin{tabular}{lrll}   
   \multicolumn{4}{c}{  TABLE 1:}\\
   \multicolumn{4}{c}{ BACKGROUND STATISTICS}\\
\hline
\hline
     \multicolumn{4}{c}{   }\\
  \multicolumn{4}{c}{ A:  Selected Summary Statistics, Classes of 1961-65}\\
            \multicolumn{4}{c}{   }\\
        &   Mean  &   Minimum   &  Maximum\\
\hline
   Starting Age&	28.73&	24&	 38\\
 Sex	&  .96	& 0	&  1\\
 Tokyo U	 & .16	& 0	&  1\\
Kyoto U	&  .19	& 0	& 1\\
 Chuo U	&  .14&	 0&	  1\\
No University	&  .43	& 0	&  1\\
 Opinions/Year	& 2.02   	& .04&	 10.42\\
1st Post	&  .91	& 0	 & 3\\
1980s Post	& 1.83&	 0	&  3\\
1st Location& 1.00&	 0	&  3\\
1980s Location	& 1.06	& 0	&  3\\
YJL	  &.35	& 0&	  1\\
  \multicolumn{4}{l}{  }\\
  \multicolumn{4}{l}{  { Observations: } 276. }\\
 \hline
 \multicolumn{4}{l}{  }\\
    \multicolumn{4}{l}{ {   Note:  } Variables are as defined in Section 4.3. 
}\\
  \multicolumn{4}{l}{  }\\
   \multicolumn{4}{l}{  }\\
 \multicolumn{4}{l}{  }\\
   \multicolumn{4}{c}{ B.  Aggregate postings, as of 1990  }\\
 \multicolumn{4}{l}{  }\\
 \multicolumn{ 1}{c}{   By court hierarchy}    &   &   \multicolumn{1}{c}{               
By geography } &\\
 \hline 
      Secretariat & 	  45&Tokyo&	537\\
 Other non-judicial	&  96	&Osaka&	231\\
 High Court&	 295&	Other metropolitan&	416\\
  District Court	&1101&	Non-metropolitan   &   1742\\
 Family Court&	 541&Branch Offices&	 848\\
 {\it {\it Sokatsu}} &	 353 &   &\\
\hline
 \end{tabular}\\   
\bigskip   
             
\newpage
 
\begin{footnotesize}
 \hspace*{-64pt}
  \begin{tabular}{l rrr | rrr     }   
   \multicolumn{7}{c}{ TABLE 2:}\\ 
 \multicolumn{7}{c}{  EXCEPTIONAL JUDGES AND THE CLASS OF  1965                     
}\\
\hline
\hline
     \multicolumn{7}{c}{  }\\ 
  &     \multicolumn{3}{c}{  Exceptional Judges  }&      \multicolumn{3}{c}{  
Class of 1965           }\\
      &Mean  &   Minimum &  Maximum  &   Mean  & Minimum  &Maximum\\
 \hline
{\it  Personal data:}  &     \multicolumn{6}{c}{ }\\
    Starting Age   &    26.84& 	23& 	32	& 29.85& 	24 	& 38 \\
   Sex	&  .96	&  0& 	 1& 	  .91	&  0&  1  \\
  Tokyo U	 &.76&	 0	 &1	&  .2	& 0	& 1 \\
   Kyoto U	& .12	& 0	& 1	&  .036&	 0	& 1  \\
  Chuo U&	0.00	& 0& 0	&  .2	& 0	& 1\\
 No University	 &.04	& 0	& 1	&  .47	& 0	& 1\\
  Opinions	&4.02	& 0 	&16.5	& 1.75&	  .16&	7.82  \\
  YJL	& .08&	 0	& 1	 & .27	& 0&	 1\\
     \multicolumn{7}{c}{  }\\ 
 {\it  Amount of career in various posts: } &     \multicolumn{6}{c}{ }\\
  {\it    (not mutually exclusive):} &     \multicolumn{6}{c}{ }\\
 Tokyo	&.52	&0	&.89	&.23	&0&	.88  \\
  Osaka	&.14&	0&	.73	&.068	&0	&.56  \\
  {\it Sokatsu} 	&.14&	0	&.33	&.10&	0&	.4  \\
 Secretariat	&.17&	0	&.58	&.007&	0  &.12 \\
  Other non-judicial &.12	&0	&.78&.083&0&  .56\\
   Branch offices&	.043	&0&	.19	&.15	&0	&.58\\
   \multicolumn{7}{c}{  }\\ 
 Observations: &     \multicolumn{3}{c}{ 	25} & 		  
\multicolumn{3}{c}{ 		55}\\
\hline
   \multicolumn{7}{c}{  }\\ 
 \end{tabular}   
 \vspace*{-18pt}\\
  {   Notes:	}The variables are as defined in Section 4.3.\\  
 ``Exceptional judges'' are those judges who were   eventually  named  either to 
the Supreme Court or to the Presidency of a High Court  and whose career records 
appear in the ZSKS.  This rules out those appointed to these positions early in 
the post-war era, as they would have begun their careers prior to the 1948 and 
thus would not appear in the ZSKS.  \\
 	For purposes of deriving these figures, the time of appointment to the 
Supreme Court is treated as the time of retirement. \\
 The percentage postings figures give the percentage of career, as of 1990, 
spent in the various positions.

 \end{footnotesize}

\newpage
 


  \begin{tabular}{l cc c  |   ccc}   
   \multicolumn{7}{c}{  TABLE 3: }\\
   \multicolumn{7}{c}{   DETERMINANTS OF FIRST ASSIGNMENT     }\\
\hline
\hline
  \multicolumn{7}{c}{      }\\
      &    \multicolumn{3}{c}{    A    } &       \multicolumn{3}{c}{                
B }          \\
       &    \multicolumn{3}{c}{         1st Post        } &       
\multicolumn{3}{c}{         1st Location}          \\
\hline
Sex	 &   -.56&  (.97)&   [.33]	&  .35& (.98) &  [.33]\\
 Starting Age&	-.12 &(3.16)& [.00]&	-.14& (4.87)& [.00]\\
 Tokyo U&	-.19 &(.39) & [.70]	&1.36& (4.39)& [.00]\\
 Kyoto U&	-.73& (1.60)& [.11]	& .71 &(2.43)& [.02]\\
 Chuo U&	-.54& (1.17)& [.24]	& .11&(.32) & [.75]\\
 No University&	-.49& (1.15)& [.25]	& .18& (.63) & [.53]\\
 YJL&	-.07& (.32) & [.75]	&-.01& (.09) & [.93]\\
  \multicolumn{7}{c}{      }\\
 Observations:	& \multicolumn{3}{c}{   276  }  & \multicolumn{3}{c}{   276}\\
  \multicolumn{7}{c}{      }\\
\hline
  \multicolumn{7}{c}{      }\\
 \end{tabular}\\   
          Notes:     Coefficients, followed by t-statistics in parenthesis, and 
confidence levels in brackets.   \\
  	 Program:  STATA, running ordered probit.
  \bigskip   

\newpage
 
 \hspace*{-64pt}
\begin{tabular}{l  rr  | r r  |  rr}
  \multicolumn{7}{c}{TABLE 4: }\\
 \multicolumn{7}{c}{ INTERPRETING FIRST JOB COEFFICIENTS   }\\
\hline
\hline
    \multicolumn{7}{c}{      }\\
        &  Mean in   &  Value for     &    Posting    &  Contribution   
&Location      &  Contribution   \\
 Variable     &   Population &    Judge Wada   &    Coefficient   &   for Wada   
&    Coefficient   &  for Wada   \\
    &    (a) & (b)     &   (c)    &   (b)*(c)   & (d)      &   (b)*(d)   \\
 \hline
 Sex     &   .91  & 1    &   -.56     &   -.56       &  .35  &      .35 \\
        Starting Age     & 29.85  &   29     &  -.12*     &  -3.48         &-
.14*   &  -4.06 \\
   Tokyo U.    &   .20 &     0     &   -1.8   &   0       & 1.37*  &0  \\
   Kyoto U.    & .04  &  0     &  -.72    &     0    &       .71*  &0  \\
  Chuo U.     &    .20   &    1    &  -.54    &   -.54         &  .11  & .11 \\
 No  University    &   .47     &    0    & -.49    &    0        &  .18  &0 \\
     YJL  &  .27  &    0   &  -.07    &    0   &         -.01 &  0  \\
 \hline
 Total Score:    &  ---    & --    &   --   &  -4.46  &   --   & -3.52 \\
\hline 
   \multicolumn{7}{c}{      }\\
     \end{tabular}\vspace*{-12pt}\\
 Note: Coefficients statistically significant at the .10 level are starred.\\
The cut points for regression 3A are -5.69 and 1.19.  \\
 The cut points for regression 3B are -3.25, -2.57, and -2.05.\\

\newpage
 

  
 \begin{tabular}{l  ccc|ccc}   
   \multicolumn{7}{c}{TABLE 5:  }\\
\multicolumn{7}{c}{ DETERMINANTS OF CAREER SUCCESS     }\\
\hline
\hline
      \multicolumn{7}{c}{      }\\
      &    \multicolumn{3}{c}{                 A     }           &    
\multicolumn{3}{c}{                 B}\\
                   &    \multicolumn{3}{c}{     1980s Post       }           &    
\multicolumn{3}{c}{             1980s Location }\\
 \hline
   Sex	& .33&  (.97)&  [.33]&	 .22 & (.57) & [.57]	\\
Starting Age&	-.03& (1.05)& [.29]&	-.07 & (2.35)& [.02]\\
Tokyo U&	 .03 &(.11)&  [.91]&	 .02& (.05)&  [.96]\\
Kyoto U	& .20& (.67)&  [.50]&	 .15&(.46) & [.65]\\
Chuo U	& .19 & (.61)&  [.54]&	 .48 & (1.40)& [.16]\\
No University&	-.07&  (.27)  &[.78]	&-.04 & (.14) & [.89]\\
  1st location =1	& .33 & (1.84)& [.07]&	 .36 & (1.85) &[.07]\\
  1st location =2	& -.14 & (.63)& [.53]&	 .30 & (1.27) &[.20]\\
  1st location =3	& .79 & (3.42)& [.00]&	 1.13 & (4.53) &[.00]\\
Opinions/Year	& .19 & (4.32)&[.00]	& .20 & (4.27)& [.00]\\
YJL	&-.28&  (1.94)& [.05]	& .16&  (.32) & [.15]\\
 \multicolumn{7}{c}{      }\\
    Observations:&	  \multicolumn{3}{c}{    276 } &    \multicolumn{3}{c}{  
276}\\
\hline
 \multicolumn{7}{c}{      }\\
\end{tabular}   \\   
 	{  Notes: } Coefficients, followed by t-statistics in parenthesis, and 
confidence levels in brackets.\\
 { Program: } STATA, running ordered probit.
\newpage
 


   \hspace*{-64pt}
  \begin{tabular}{l    |  rr  | r r  |  rr}
  \multicolumn{7}{c}{TABLE 6: }\\
 \multicolumn{7}{c}{ INTERPRETING CAREER COEFFICIENTS   }\\
\hline
\hline
    \multicolumn{7}{c}{      }\\
             &    Population &  Value for     &    Posting    &   Contribution   
&Location      &   Contribution   \\
 Variable     &Mean     &    Judge Wada   &    Coefficient   &  for Wada   &    
Coefficient   &    for Wada   \\
  &    (a) & (b)     &   (c)    &   (b)*(c)   & (d)      &   (b)*(d)   \\
 \hline
 Sex     &   .91  & 1    &    .33      &   .33       &  .22  &      .22  \\
        Starting Age     & 29.85  &   29     &    -.03    &     -.87        & -
.073*   &  -2.12 \\
   Tokyo U.    &   .20 &     0     &   .03    &    0      &  0.18  &0  \\
   Kyoto U.    & .04  &  0     &   .20    &      0   &       .15  &0  \\
  Chuo U.     &    .20   &    1    &    .19    &   .19         &  .48  & .48 \\
 No University   & .47  &   0     &    -.07   &    0        &  -.04   &0  \\
  1st location =1    &  .22 &   0      &  .33*     &  0          &   .36*  & 0 
\\
 1st location =2    &  .13 &  0       &   -.14    &     0      &  .30  & 0 \\
   1st location =3   & .18 &    0      &   .79*    &    0       &  1.13*  & 0 \\
    Opinions/Year    &   1.75   & 1.55        &   .19*    &   .29         &  
.20*  &  .31    \\
   YJL  &  .27  &    0   &   -.28*   &    0   &          .16  &  0  \\
 \hline
 Total Score:    &   --   & --    &   --   &  -.03    &   --   & -1.11 \\
\hline 
  \multicolumn{7}{c}{      }\\
     \end{tabular}  \vspace*{-12pt}\\
 Note: Coefficients statistically significant at the .10 level are starred.\\
  	 The cut points for regression 5A are -1.29, -.77, and .92. \\
 The cut points for regression 5B are -.94, -.61, and -.25.\\
 


\newpage


 \begin{tabular}{l  ccc ccc}   
   \multicolumn{7}{c}{ TABLE 7:}\\
   \multicolumn{7}{c}{  UNEXPLAINED CAREER SUCCESS AND }\\
     \multicolumn{7}{c}{ ANTI-GOVERNMENT DECISIONS}\\
\hline
\hline
  \multicolumn{7}{c}{  }\\
    \multicolumn{7}{c}{   A.  Number of Anti-Government Decisions:      }\\                   
\multicolumn{7}{c}{  }\\
&  \multicolumn{3}{c}{1. Post Residual }& \multicolumn{3}{c}{2.   Location 
Residual}\\
  Early Anti-Govt	& .030&(.92) & [.36]	& .021&(.66) &[.51]\\
 Late Anti-Govt	&-.11& (1.32) &[.19]	&-.21 & (2.60)&[.01]\\
   \multicolumn{7}{c}{  }\\
 R$^2$:	 & \multicolumn{3}{c}{ .04}& \multicolumn{3}{c}{ .12}\\
   \multicolumn{7}{c}{  }\\
  \multicolumn{7}{c}{   B.  Any Anti-Government Decisions:    }\\                        
\multicolumn{7}{c}{  }\\
&  \multicolumn{3}{c}{ 1. Post Residual  } &  \multicolumn{3}{c}{ 2. Location 
Residual}\\
  Any Early Anti-Govt 	& .18 &(1.21)& [.23]&	-.21& (1.34)&[.19]\\
Any Late Anti-Govt	&-.35& (1.90)& [.06]	&-.05 &(.28)&[.78]\\
    \multicolumn{7}{c}{       }\\
 R$^2$:	 & \multicolumn{3}{c}{ .07}& \multicolumn{3}{c}{ .06}\\
      \multicolumn{7}{c}{  }\\
Observations:	 &  \multicolumn{3}{c}{ 54 }&  \multicolumn{3}{c}{ 54}\\
\hline
  \multicolumn{7}{c}{  }\\
 \end{tabular}\\   
     { Notes:  }Coefficients, followed by t-statistics in parentheses, and 
confidence levels in brackets.\\
 {   Program:}  STATA, running ordinary least squares on a logistic conversion 
of the residual from the career regression.  
\bigskip   
\newpage
 \begin{tabular}{lrr}   
   \multicolumn{3}{c}{TABLE 8: }\\
 \multicolumn{3}{c}{  Summary \S 138 Statistics }\\
\hline
\hline
        \multicolumn{3}{c}{   }\\
 & Constitutional  & Unconstitutional         \\
      &        Mean   &           Mean    \\
\hline
   \multicolumn{3}{c}{   }\\
 Prior Posts&	{\bf   1.41} &	{\bf   .44}\\
 Later Posts	&1.70 &	1.56 \\
Prior Location	&{\bf  1.05} &	{\bf   .00}\\
 Later Location	&1.14 &	 .44\\
 Prior Branch &	{\bf   .14	}&{\bf   .24}\\
Later Branch 	& .10	& .50\\
Prior {\it Sokatsu} 	&{\bf   .12}&	{\bf   .00}\\
Later {\it Sokatsu} 	& .28&	 .03\\
Prior Opinions	&1.12	&1.28\\
Sex	&1.00 &	1.00 \\
YJL	& {\bf .14 }& {\bf  .56} \\
  \multicolumn{3}{c}{   }\\
  Observations&	37&	9\\
\hline
 \end{tabular}\\   
 
  



\newpage

  \begin{tabular}{l ccc  ccc}   
   \multicolumn{7}{c}{TABLE 9: }\\
  \multicolumn{7}{c}{  EFFECT OF \S 138 OPINIONS ON BRANCH OFFICE }\\
  \multicolumn{7}{c}{   AND SOKATSU POSTINGS       }\\
\hline
\hline
         \multicolumn{7}{c}{  }\\
&    \multicolumn{3}{c}{  Later Branch}    &    \multicolumn{3}{c}{    Later 
{\it Sokatsu}  }\\
\hline 
Constant	&-.67 &(2.46)& [.02]     &.24 &1.65 &[.11]\\
 Prior Branch	&.97 &(1.36)& [.18]     &-- & -- &--\\
 Prior {\it Sokatsu}	&	-- &-- & -- & .88& (2.05)& [.05]\\
 Prior Opinions	&.06 &(.96)& [.34]&-.22& (1.55)& [.12]\\
\S138  Decision	&  {\bf .80 }& {\bf  (2.67)}&{\bf  [.01] }& {\bf -.47}& {\bf 
(1.79)} &{\bf [.08]} \\
            \multicolumn{7}{c}{  }\\
Observations:&    \multicolumn{3}{c}{ 	46}&    \multicolumn{3}{c}{ 46}\\
 \hline
         \multicolumn{7}{c}{  }\\
  \end{tabular}\\   
             {    Notes: } Coefficients, followed by t-statistics in 
parentheses, and confidence levels in brackets. \\
            {    Program:  }STATA, running tobit.
\bigskip   
	Note that a majority of the judges who held the ban unconstitutional  were 
members of the YJL.  This suggests the possibility that the negative coefficient 
on  YJL membership in Table 5 may reflect other (uninvestigated) politically 
controversial options they wrote during the course of their career.


\end{document} 


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