TLDR: The most efficient way to simulate a multi-row VALUES clause is to create an array-of-arrays for the rows and columns of the data, and then unpack it and (if necessary) cast to the desired data types:

select rowdata[0]::varchar, rowdata[1]::decimal
from
    (select array(
        array('a', 1),
        array('b', 2)
    ) as arr) as data,
    data.arr as rowdata

(The data.arr as rowdata bit is to unnest the array.)

UNION ALL has the unfortunate behavior that each of the SELECT statements will be distributed across the cluster:

explain select * from (select 'a' union all select 'b' union all select 'c')

XN Subquery Scan derived_table1  (cost=0.00..0.09 rows=3 width=32) 
  ->  XN Append  (cost=0.00..0.06 rows=3 width=0) 
        ->  XN Network  (cost=0.00..0.02 rows=1 width=0) 
              Distribute Round Robin 
              ->  XN Subquery Scan "*SELECT* 1"  (cost=0.00..0.02 rows=1 width=0) 
                    ->  XN Result  (cost=0.00..0.01 rows=1 width=0) 
        ->  XN Network  (cost=0.00..0.02 rows=1 width=0) 
              Distribute Round Robin 
              ->  XN Subquery Scan "*SELECT* 2"  (cost=0.00..0.02 rows=1 width=0) 
                    ->  XN Result  (cost=0.00..0.01 rows=1 width=0) 
        ->  XN Network  (cost=0.00..0.02 rows=1 width=0) 
              Distribute Round Robin 
              ->  XN Subquery Scan "*SELECT* 3"  (cost=0.00..0.02 rows=1 width=0) 
                    ->  XN Result  (cost=0.00..0.01 rows=1 width=0)

On more than a few rows, this incurs an absurd overhead and makes queries extremely inefficient. Fortunately, we can use the SUPER data type as a workaround; when we select a single value (the array-of-arrays) the query planner sees this as a single query which it only needs to distribute to one node, which is much more efficient to execute.