Cluster vs. non-cluster query planning

I'm running postgres 8.0.7, and I've got a table of orders with about
100,000 entries. I want to just look at the new orders, right now 104 of
them.

EXPLAIN ANALYZE
SELECT
    order_id
    FROM
        orders
    WHERE
        order_statuses_id = (SELECT id FROM order_statuses WHERE id_name
= 'new');

 Seq Scan on orders o  (cost=1.20..11395.51 rows=7029 width=8) (actual
time=286.038..287.662 rows=104 loops=1)
   Filter: (order_statuses_id = $0)
   InitPlan
     ->  Seq Scan on order_statuses  (cost=0.00..1.20 rows=1 width=4)
(actual time=0.030..0.039 rows=1 loops=1)
           Filter: ((id_name)::text = 'new'::text)
 Total runtime: 288.102 ms

The dreaded sequential scan.  I've got an index on order_statuses_id and
I've VACUUM ANALYZEd the table, but I'm currently clustered on the
primary key (order_id).

With enable_seqscan = off, I get:
-------------------------------------------------
 Index Scan using orders_status_btree_idx on orders o
(cost=4.64..12457.14 rows=7031 width=8) (actual time=0.164..0.664
rows=104 loops=1)
   Index Cond: (order_statuses_id = $0)
   InitPlan
     ->  Index Scan using order_statuses_id_name_key on order_statuses
(cost=0.00..4.64 rows=1 width=4) (actual time=0.128..0.134 rows=1 loops=1)
           Index Cond: ((id_name)::text = 'new'::text)
 Total runtime: 1.108 ms

If I hard-code the 'new' status ID, I get:
-------------------------------------------------
EXPLAIN ANALYZE
SELECT
    order_id
    FROM
        orders
    WHERE
        order_statuses_id = 1;

 Index Scan using orders_status_btree_idx on orders o
(cost=0.00..4539.65 rows=1319 width=8) (actual time=0.132..1.883
rows=104 loops=1)
   Index Cond: (order_statuses_id = 1)
 Total runtime: 2.380 ms

Here is the pg_stats entry for orders.order_statuses_id:
 schemaname | tablename |      attname      |  null_frac  | avg_width |
n_distinct | most_common_vals |          most_common_freqs
|    histogram_bounds     | correlation

------------+-----------+-------------------+-------------+-----------+------------+------------------+--------------------------------------+-------------------------+-------------
 public     | orders    | order_statuses_id | 0.000208333 |         4
|         14 | {8,24,10,25}     | {0.385417,0.242083,0.230625,0.07875} |
{1,7,7,9,9,9,9,9,23,26} |    0.740117

This is with SET STATISTICS = 16 on the column, since that's how many
different values the column can currently take.

Now, here's the thing - if I cluster on the index on order_statuses_id,
the original query produces:
 Index Scan using orders_status_btree_idx on orders o
(cost=1.20..978.94 rows=8203 width=8) (actual time=0.097..0.598 rows=104
loops=1)
   Index Cond: (order_statuses_id = $0)
   InitPlan
     ->  Seq Scan on order_statuses  (cost=0.00..1.20 rows=1 width=4)
(actual time=0.056..0.065 rows=1 loops=1)
           Filter: ((id_name)::text = 'new'::text)
 Total runtime: 1.042 ms

Estimated cost went way down. The pg_stats entry becomes:

 schemaname | tablename |      attname      | null_frac | avg_width |
n_distinct | most_common_vals |           most_common_freqs
|  histogram_bounds   | correlation

------------+-----------+-------------------+-----------+-----------+------------+------------------+----------------------------------------+---------------------+-------------
 public     | orders    | order_statuses_id |         0 |         4
|         12 | {8,24,10,25}     | {0.386458,0.244167,0.238333,0.0720833}
| {1,7,7,9,9,9,22,26} |           1

I'm hesitant to cluster on the order_statuses_id index, because there
are a lot of other queries using this table, many of which join on
order_id. I also feel like I ought to be able to get the planner to do
an index scan without hard-coding the order_statuses_id value.

Questions:
* What can I do to reduce the estimated row count on the query?
* Why does clustering drive down the estimated cost for the index scan
so much? Does a change in correlation from .72 to 1 make that much of a
difference?
* Can I convince my query planner to index scan without clustering on
the order_statuses_id index, or setting enable_seqscan = off?

Potential note of interest:  This is a very wide, monolithic table - no
less than 100 columns, with several check constraints, foreign key
constraints, and indexes, including three functional indexes.

Side question: Sometimes, when I VACUUM ANALYZE the table, the pg_stats
entry for order_statuses_id has almost all of the possible values in
most_common_vals, instead of just a handful.  Example:

 schemaname | tablename |      attname      | null_frac | avg_width |
n_distinct |         most_common_vals
|
most_common_freqs
| histogram_bounds | correlation

------------+-----------+-------------------+-----------+-----------+------------+-----------------------------------+------------------------------------------------------------------------------------------------------------------------------+------------------+-------------
 public     | orders    | order_statuses_id |         0 |         4
|         13 | {8,24,10,25,9,7,23,26,1,22,2,5,4} |

{0.393125,0.240208,0.226042,0.07875,0.0275,0.0145833,0.0110417,0.00291667,0.00229167,0.001875,0.000625,0.000625,0.000416667}

|                  |           1

This doesn't appear to influence whether the index scan is chosen, but I
am curious as to why this happens.