Author of study on race and bribes cautions against generalisations

Amid PAS' attempt to weaponise a PhD thesis on race and corruption, its author has cautioned against generalisations.

In a brief emailed reply to Malaysiakini, Christine Chong Siew Pyng said her study was indeed based on past MACC statistics but sought to distance her research away from the conclusions it has spawned.

"Just to share with you, my paper is on bribe givers and indeed the statistics from the MACC 2010-2014 convicted bribe givers showed approximately 88 percent were non-Malay (sic).

"My thesis has also found approximately 82 percent of convicted bribe solicitors/takers were Malay," she said.

"The conclusions drawn from the profile are merely suggestive, and therefore, should not be taken as a generalisation. I have no comment on allegations made by the political parties," Chong added.

Over the last two weeks, PAS president Abdul Hadi Awang has come under attack over his assertion that non-Muslims and non-bumiputera comprise the bulk of the “root of corruption” in Malaysia.

To back Hadi, the party's central committee member Mohd Zuhdi Marsuki cited a "survey" by a local university, which contained many of the figures Zuhdi had quoted.

The study, conducted by researchers based at Universiti Sains Malaysia and Tunku Abdul Rahman University College in Penang, and published in the journal Asian Economic Papers in January 2017, however, mostly focused on the bribe givers’ perspective, particularly the factors that could lead to a larger bribe being offered.

The role of bribe recipients in corruption is mostly outside the scope of the paper and left unexplored.

In addition, MACC's Corruption Offender Database, from which data for the study was drawn, also only contained information on those who have been convicted.

This meant no analysis can be done on those who did not engage in bribery, those who did but were not caught, and those who were caught but were not convicted.

“These omissions are likely to bias our estimates. Unfortunately, there is no ready means to correct for this selection bias,” the authors noted in the study. - Mkini