Missing values are "missing values" when other necessary data exist but some cells are empty, so the test disregards the other data as well and reports "missing values". Otherwise, if all the cells needed for a particular task or test are empty together, it won't report a missing value. And, again if no tests have been done, there is no missing value by default. But the default can be tweaked by editing the rules for missing values. This is quoted from the help of SPSS (I don't know is it breaching copyright or not, but if it did, please moderate it):
Missing Values defines specified data values as user-missing. For example, you might want to distinguish between data that are missing because a respondent refused to answer and data that are missing because the question didn't apply to that respondent. Data values that are specified as user-missing are flagged for special treatment and are excluded from most calculations.
• User-missing value specifications are saved with the data file. You do not need to redefine user-missing values each time you open the data file.
• You can enter up to three discrete (individual) missing values, a range of missing values, or a range plus one discrete value.
• Ranges can be specified only for numeric variables.
• All string values, including null or blank values, are considered to be valid unless you explicitly define them as missing.
• Missing values for string variables cannot exceed eight bytes. (There is no limit on the defined width of the string variable, but defined missing values cannot exceed eight bytes.)
• To define null or blank values as missing for a string variable, enter a single space in one of the fields under the Discrete missing values selection."