橫斷面(cross sectional)的評價模式中,大約可分成一般迴歸模式與追蹤資料(panel data)迴歸模式兩類。本研究以台灣證券交易所上市之公司為樣本,在價格模式下,以正確性及解釋變動能力為標準,嘗試比較一般與追蹤資料迴歸模式對於權益價值的解釋力及預測力。實證結果發現:不管是在正確性或解釋變動能力方面,追蹤資料迴歸模式均具有較佳解釋同期股價之能力;而在預測方面,也發現追蹤資料迴歸模式預測值之正確性及解釋變動能力均顯著優於一般迴歸模式。在考量不同產業與盈餘正負等因素後,所得到的結論亦相同。因此,在使用追蹤資料迴歸模式的情形下,不論是估計值對同時點價值的解釋力,或是對真實價值的預測力,皆具有較好的效果。
Cross-sectional valuation models include general regression model and panel data regression model. Using a sample of listed firms in Taiwan Security Exchange, we compare alternative empirical estimates of intrinsic value using two criteria: accuracy and explainability. The study compares the reliability of value estimates from general regression model and panel data regression model. The empirical results show that the panel data regression model's estimates are more accurate and explain more of the variation in security prices than the general regression models. On the other hand, the accuracy and explainability of panel data regression mode's forecasts are also better than general regression model's. For the sensitivity test, we consider financial industry and negative earnings. The sensitivity test results are similar to previous outcomes. In summary, we provide evidence to support that panel data regression model's estimate is a better model and can raise the effectiveness of valuation model.