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This paper explores the relationship between the translation quality and the retrieval effectiveness in Machine Translation (MT) based Cross-Language Information Retrieval (CLIR). To obtain MT systems of different translation quality, we degrade a rule-based MT system by decreasing the size of the rule base and the size of the dictionary. We use the degraded MT systems to translate queries and submit the translated queries of varying quality to the IR system. Retrieval effectiveness is found to correlate highly with the translation quality of the queries. We further analyze the factors that affect the retrieval effectiveness. Title queries are found to be preferred in MT-based CLIR. In addition, dictionary-based degradation is shown to have stronger impact than rule-based degradation in MT-based CLIR.