000			01624cam a2200169 4500
100	1		_aNG Jason Wei Jian
700			_aRANGEL Gary John
700			_aCHIN Elsa Phung Yet
245			_aDid Urbanization or Ethnicity Matter More in Malaysia's 14th General Election?/ _cJason Wei Jian Ng, Gary John Rangel and Elsa Phung Yet Chin
260			_c2021
520			_aThis article focuses on identifying the variable which has the highest predictive power in predicting electoral behaviour. To do this, we apply a tree-based machine learning technique to data from Malaysia's 14th General Election. We find that constituencies' urbanization level has the most significant predictive power in determining vote share. Ethnicity, a long-touted variable of significance, plays a secondary role. Moreover, these predictors' marginal effects on the vote share are highly complex, non-linear and difficult to pick up by conventional regression methods. Other explanatory factors do not exhibit significant predictive qualities of electoral behaviour, although the extant literature has shown them to have important causal relationships. As our analysis reflects the significant predictive power of urbanization in predicting voting behaviour, we caution against the haste to dismiss its relevance in the Malaysian context.
650			_aURBANIZATION _xETHNICITY _xMALAYSIA _x14TH GENERAL ELECTION _xSOUTHEAST ASIA
773			_aContemporary Southeast Asia : _gVol. 43, No. 3, December 2021, pp.461-495 (19)
598			_aMALAYSIA, POLITICS
856			_uhttps://muse.jhu.edu/article/845142 _zClick here for more
945			_i66801.1001 _rY _sY
999			_c40925 _d40925