±¹¹® ÃÊ·Ï
ȸ°èÀÌÀÍ·üÀº OhlsonÀÇ ÃʰúÀÌÀÍÇÒÀθðÇü, NCI Áö½ÄÀÚ»êÆò°¡¸ðÇü µîÀÇ È¸°èºÐ¾ß ¿¬±¸¿Í ±ÝÀ¶±â°ü ¹× ½Å¿ëÆò°¡±â°üÀÇ ±â¾÷Æò°¡¾÷¹«¿¡¼ Áß¿äÇÑ ÁöÇ¥·Î »ç¿ëµÇ°í ÀÖÀ½¿¡µµ ºÒ±¸Çϰí ÀÌ¿¡ ´ëÇÑ ¿¹Ãø¿¬±¸´Â ¹ÌºñÇÏ´Ù. ¶ÇÇÑ, ±âÁ¸ÀÇ È¸°èÀÌÀÍ¿¹Ãø ¿¬±¸¿¡¼ »ç¿ëµÇ´Â ½Ã°è¿ ¸ðÇüÀº Àڱ⺯¼ö ¿µÇ⸸À» ¹Ý¿µÇÏ¿© ¿¹ÃøÄ¡¸¦ ÃßÁ¤ÇϹǷΠ´ÜÀϺ¯·® ¸ðÇü¼ö¸³¿¡´Â ÀûÇÕÇÏÁö¸¸ ¿ÜºÎ¿ä¼Ò ¿µÇâÀ»...
[´õº¸±â]
ȸ°èÀÌÀÍ·üÀº OhlsonÀÇ ÃʰúÀÌÀÍÇÒÀθðÇü, NCI Áö½ÄÀÚ»êÆò°¡¸ðÇü µîÀÇ È¸°èºÐ¾ß ¿¬±¸¿Í ±ÝÀ¶±â°ü ¹× ½Å¿ëÆò°¡±â°üÀÇ ±â¾÷Æò°¡¾÷¹«¿¡¼ Áß¿äÇÑ ÁöÇ¥·Î »ç¿ëµÇ°í ÀÖÀ½¿¡µµ ºÒ±¸Çϰí ÀÌ¿¡ ´ëÇÑ ¿¹Ãø¿¬±¸´Â ¹ÌºñÇÏ´Ù. ¶ÇÇÑ, ±âÁ¸ÀÇ È¸°èÀÌÀÍ¿¹Ãø ¿¬±¸¿¡¼ »ç¿ëµÇ´Â ½Ã°è¿ ¸ðÇüÀº Àڱ⺯¼ö ¿µÇ⸸À» ¹Ý¿µÇÏ¿© ¿¹ÃøÄ¡¸¦ ÃßÁ¤ÇϹǷΠ´ÜÀϺ¯·® ¸ðÇü¼ö¸³¿¡´Â ÀûÇÕÇÏÁö¸¸ ¿ÜºÎ¿ä¼Ò ¿µÇâÀ» ¹Ý¿µÇÏÁö ¸øÇÏ´Â ÇѰ踦 °®´Â´Ù. ÀÌ·¯ÇÑ ¹è°æ¿¡¼ º» ¿¬±¸´Â µ¿ÅÂÀû ÆÐ³Î(dynamic panel)¸ðÇüÀ» ÀÌ¿ëÇÏ¿© ȸ°èÀÌÀÍ·üÀ» ¿¹ÃøÇÑ´Ù.
µ¿ÅÂÀû ÆÐ³Î¸ðÇüÀº Àڱ⺯¼ö À̿ܿ¡µµ, ¿Ü»ýº¯¼ö¿Í °³º°±â¾÷ È¿°ú¸¦ ¹Ý¿µÇÏ¿© ¿¹ÃøÄ¡¸¦ ÃßÁ¤ÇÏ°Ô µÇ¾î ½Ã°è¿¸ðÇüÀÇ ´ÜÁ¡À» ±Øº¹ÇÒ ¼ö ÀÖ´Ù. º» ¿¬±¸´Â °¡µ¿·üÁö¼ö, »ý»êÀÚÁ¦Ç°Àç°íÁö¼ö ¹× 3³â ¸¸±â ȸ»çä¼öÀÍ·üÀ» ¿Ü»ýº¯¼ö·Î ÇÏ´Â µ¿ÅÂÀû ÆÐ³Î¸ðÇüÀ» »ç¿ëÇÏ¿© ¸ÅÃâ¾×¿µ¾÷ÀÌÀÍ·ü°ú ¸ÅÃâ¾×¼øÀÌÀÍ·üÀ» ¿¹ÃøÇÑ´Ù. ¿¹Ãø´É·ÂÀº ½ÇÁ¦Ä¡¿Í ¿¹ÃøÄ¡ Â÷ÀÌ·Î ÃøÁ¤µÇ´Â ¿¹ÃøÁ¤È®¼º, ±×¸®°í ¿¹ÃøÄ¡¿Í ÁֽļöÀÍ·üÀÇ °ü·Ã¼ºÀ¸·Î ÃøÁ¤µÇ´Â ½ÃÀå±â´ëÀÌÀÍ ´ë¿ëÄ¡·Î¼ ÀûÀý¼ºÀ» ±âÁØÀ¸·Î ·£´ý¿÷(random work) ¸ðÇü°ú ºñ±³ÇÏ¿© Æò°¡ÇÑ´Ù.
°ËÁõ°á°ú¿¡ ÀÇÇϸé, µ¿ÅÂÀû ÆÐ³Î¸ðÇüÀº ¸ðµç ¿¹Ãø´ë»ó ȸ°èÀÌÀÍ·ü¿¡¼ ³ôÀº ¿¹ÃøÁ¤È®¼ºÀ» ³ªÅ¸³ÂÀ¸³ª ½ÃÀå±â´ëÀÌÀÍ ´ë¿ëÄ¡·ÎÀÇ ÀûÀý¼º¿¡¼´Â ¿ì¿ù¼ºÀ» º¸¿©ÁÖÁö ¸øÇÏ¿´´Ù. ÀÌ·¯ÇÑ °ËÁõ °á°ú´Â Ç¥º»±â°£, ±â¾÷±Ô¸ð ¹× ¾÷Á¾À» ´Þ¸®ÇÏ¿©µµ µ¿ÀÏÇÏ¿´´Ù.
[´Ý±â]
¿µ¹® ÃÊ·Ï
This study examines the forecasting ability of the dynamic panel
model about accounting income ratios. The motive of a study stems from the following. First, although accounting income ratios are use...
[´õº¸±â]
This study examines the forecasting ability of the dynamic panel
model about accounting income ratios. The motive of a study stems from the following. First, although accounting income ratios are used as an important index in accounting study and practical business forecasting studies using them are rare. Second, time- series models used in the existing study have limits not verifying the relationship between dependent and independent variables, and consideration of the effect of external factors.
The dynamic panel model can overcome those limits by considering the effect of the extraneous variable and individual company as well as auto-variable.
We design the forecasting model using the dynamic panel model and select operating index, producer's inventory index and 3year company bond returns as the extraneous variables. The forecasting objectives are the ratio of operating income to sales and the ratio of net income to sales. The forecasting ability is estimated by the relative superiority to random work model on the basis of forecast accuracy and proxies for market earnings expectations The results indicate that the dynamic panel model shows a higher degree of forecasting accuracy and does not provide a more proper investors' expectation income than the random work model. These results are robust in most years, firm size and industries.
[´Ý±â]
¸ñÂ÷
°³¿ä
ABSTRACT
I. ¼ ·Ð
¥±. ¼±Ç࿬±¸ÀÇ °ËÅä
¥². ¿¬±¸¼³°è
¥³. ½ÇÁõºÐ¼®°á°ú
¥´. °á ·Ð
REFERENCES