Instrumental Variables in Qualitative Research 

 In large-N quantitative research, instrumental variables are often used to address the problem of endogeneity. In small-N qualitative research such as comparative historical case studies, researchers examine historical sequence and intervening causal process between an independent variable(s) and the outcome of the dependent variable in order to establish causal direction and illuminate causal mechanisms (Rueschemeyer and Stephens 1997). However, careful examination of sequence and intervening process through process-tracing may not solve the problem of endogeneity. When Y affected X initially and X, in turn, influenced Y later, looking at the sequence and intervening causal process in the latter part without examining the former process will produce a misleading conclusion. 

 In my comparative historical  case study  of corruption in South Korea, relative to Taiwan and the Philippines, I attempted to test my hypothesis that income inequality increases corruption and to identify causal mechanisms. It was easy to show the correlations between inequality and corruption. Both inequality and corruption have been the highest in the Philippines and the lowest in Taiwan, with Korea in between. I found that the success of land reform in Korea and Taiwan produced much lower levels of inequality in assets and income than was true of Philippines, where land reform failed. I provided plausible evidence that the different levels of inequality due to success and failure of land reform accounted for different levels of corruption, and identified some causal mechanisms. Also, between Korea and Taiwan, I found that Korea's  chaebol  (large conglomerate)-centered industrialization and Taiwan's avoidance of economic concentration led to a divergence of inequality over time, which contributed to divergence of corruption level.  

 However, the process-tracing for the period after the success or failure of land reform and for the period after the adoption of different industrial policies was not sufficient to establish causal direction because different levels of corruption might have influenced the success and failure of land reform as well as the industrial policy. Hence, I had to show that success and failure of land reform was affected very little by corruption, but largely determined by external factors such as the threat of communism and the differences in the US policy toward these countries. Also, I had to provide evidence that the initial adoption of different industrial policies by Park Chung-hee in Korea and by the KMT leadership in China were not affected by the different levels of corruption. Essentially, land reform and industrial policy played the role of instrumental variables in statistical studies. These were exogenous events that produced different levels of inequality and thereby caused different levels of corruption but had not been influenced by corruption. Thus, the idea of instrumental variable can be useful in qualitative research as well.