This paper compared the total factor productivity (TFP) estimation methods

of growth accounting (GA) and the stochastic frontier model (SFM). In

specific, we were interested in comparing the TFP distribution with the

variance and skewness of these two methods. We used the Mining and

Manufacturing Survey from the Statistics Korea, and compared the

distributions of the TFP estimates obtained by GA and SFM. We found that

the two estimation methods resulted in significantly different findings. First,

GA produced larger variations in TFP than SFM. GA estimates TFP based on

a residual of a production function while SFM attempts to decompose an error

term into TFP and random noise. This decomposition in SFM may result in

smaller variations in the TFP estimates. Second, the two estimation methods

also identified different findings regarding the relationship between market

competition and TFP dispersion. According to GA, there is no clear

relationship between market competition and TFP dispersion. Alternatively,

SFM identified a negative relationship between the TFP dispersion and market

competition. This empirical finding of SFM is consistent with previous

empirical studies that suggested competitive environment forces less productive

firms to exit the market, resulting in narrower TFP distribution.