【正文】 the 14 manufacturing industries listed in Table 1. Restricting the data to a single year circumvents estimation issues arising from variations in inflation rates, interest rates, and GDP growth rates as described by Mensah (1984) and Platt, Platt and Pedersen (1994). The sample includes every pany listed on the COMPUSTAT tape for the 14 industries to avoid choicebased sample bias (See Zmijewski, 1984). Further, the industry relative approach used to create financial ratios for panies within the 14 industries insures a more than adequate sample size. Companies on the COMPUSTAT tape were bifurcated into financially distressed and solvent groups with a threepart system, over a twoyear period, 1999 to 2020. Financial distressed firms were defined as those that met each of the following screening criteria for both years. ? Negative EBITDA interest coverage (similar to Asquith, Gertner and Scharfstein (1994)). ? Negative EBIT (similar to John, Lang, and Netter (1992)). ? Negative ine before special items (similar to Hofer (1980)). To avoid defining panies as financially distressed based on a single year of poor performance, the three screens above were calculated for the years 1999 and 2020. Companies were categorized as financially distressed if all three screens were negative in both years. Companies were defined as nonfinancially distressed otherwise. This approach yielded a total of 1403 panies for the analysis sample, including 276 financially distressed firms and 1,127 nonfinancially distressed panies. Two other financial distress identifiers previously employed by researchers were not included in the screening system: cash flow less than current maturities of longterm debt and layoffs, restructurings, or missed dividend payments. In the former case, the variable was excluded because it necessitates omitting panies without longterm debt. The later metric was dropped because prehensive data were not available. The threescreen system produced a total of 276 cases of financial distress across 14 industries as seen in Table 1. The table also includes the percentage of financial distressed firms in each industry and the number of no ndistressed panies. The requirement that panies fall below all three financial distress screen thresholds means that they are in a serious though not necessarily a fatal phase of distress. This methodology yields relatively more cases of financial distress in the Industrial Machinery amp。本文接著對是否存在相同的解釋因子對破產(chǎn)和財務(wù)困境同時產(chǎn)生關(guān)聯(lián)提出疑問。而早期的破產(chǎn)預(yù)測有利于企業(yè)重組和破產(chǎn)過程中的參與者，它為管理者或者是有職責(zé)扭轉(zhuǎn)一個處于危機或財務(wù)困難的企業(yè)的董事會提供了一些幫助。 除了諸如自然災(zāi)害，政府規(guī)章改變或者法律判決這些突發(fā)事件之外，財務(wù)困境都先于幾乎所有的破產(chǎn)。 Altman 和 Izan（ 1984 年）開創(chuàng)的行業(yè)相對比率將規(guī)范破產(chǎn)研究的行業(yè)之間存在的差異。財務(wù)困境企業(yè)被定義為兩個年度內(nèi)同時滿足以下標(biāo)準(zhǔn)的企業(yè)。 另外兩個以前被研究人員采用但不包括在篩選系統(tǒng)的財務(wù)困境標(biāo)識是：現(xiàn)金流量小于一年到期的長期債務(wù)和臨時裁員，重組，或錯過的分紅。三層篩選方法如何影響被標(biāo)識為財務(wù)困境企業(yè)的數(shù)目見表 2 中，表 2 對單個和多個屏幕進行了比較。財務(wù)困境企業(yè)被任意指定為 1 值，而財務(wù)正常企業(yè)被指定為 0 值。這些作為財務(wù)困境可能因素的比率是被測試。在整篇文件中，行業(yè)相對表示是被抑制為簡化表示法。這也從一個角度解釋了為什么許多財務(wù)困境企業(yè)并沒有最終申請破產(chǎn)保護。我們證明了結(jié)合幾 個先前提議定義的一個三屏幕標(biāo)準(zhǔn)帶來比任何一個或兩個標(biāo)準(zhǔn)屏模型相當(dāng)甚至更低的模型標(biāo)準(zhǔn)錯誤。 行業(yè)相對比率 ij=j行業(yè)平均比率 公司比率*100 （ 1） 其中，公司 i是行業(yè) j的成員之一， 用 100 調(diào)整百分比率以使標(biāo)值大于 。企業(yè)健康持續(xù)發(fā)展一個方面是健康種類，另一個方面則為破產(chǎn)種類，而財務(wù)困境則居于兩者之間。根據(jù)定義的三屏系統(tǒng)產(chǎn)生的財務(wù)困難最少的情況下，因為它是公司在各個屏幕路口升華。后者的度量被取消，因為無法獲得全面的數(shù)據(jù)。 ? 息稅前利潤為負（類似于 John, Lang, 和 Netter (1992 年 )）。本文也采 用了行業(yè)的相對框架，但是為了研究財務(wù)困境的預(yù)測。他們可能不會成為一個認定公司倒閉的事件而導(dǎo)致破產(chǎn)；與此不同的是，財務(wù)困境分階段和不同程度而發(fā)生。 在大多數(shù)情況下，破產(chǎn)發(fā)生于繼財務(wù)危機之后的一段時間。最 終的財務(wù)危機預(yù)警模型包括一個已經(jīng)存在于破產(chǎn)模型中的變量和 4 個