****************************************************;
*** Program adapted from                            ***;
*** Using SAS in Financial Research                 ***;
*** by Ekkehart Boehmer, John Paul Broussard, and   ***;
*** Juha-Pekka Kallunki (SAS Press, Cary, NC, 2002),***;
*** Chapter 8 "Predicting Bankruptcy from Financial ***;
*** Distress Characterization Models"               ***;
****************************************************;

/* The description of the data is taken from Boehmer,
   Broussard, and Kallunki (2002, p. 92):
   The data used in this chapter are from Theodossiou, P.,
   E. Kahya, and R. Saidi, and G. Philippatos (1996), 
   "Financial Distress and Corporate Acquisitions: Further
   Empirical Evidence," Journal of Business Finance and
   Accounting 23: 699 - 838.  In their study, a firm is
   defined as financially distressed if it meets at least
   one of the following conditions: (1) actual debt default,
   (2) management negotiations with creditors to restructure
   terms of debt instruments, or (3) difficulty in meeting
   the payment requirements of debt contracts.  All data are
   gathered from Compustat and include only firms listed
   on NYSE or AMEX from 1981 through 1989.  The sample
   consists of 181 manufacturing firms, of which 86 are 
   classified as financially distressed at some point
   during this period.  Data for the distressed firms are
   gathered approximately one year prior to
   exhibiting the first sign of distress.  The firm-specific
   variables used include size measures and ratios measuring
   liquidity, debt, managerial efficiency, and profitability;
   they are defined below.  */ 

/* Read financial-statement data and sort by distress status;
 read data from text file and sort by distress status  */

/*Import the excel file data into SAS */
PROC IMPORT DATAFILE= "F:\E6352\Yixiang Programs\distress.xlsx" 
     OUT= distress
     DBMS=xlsx REPLACE;
     SHEET="data"; 
     GETNAMES=YES;
RUN;

/*Another way to import the data is using the datalines statement*/
/*data distress;
input yd tdta gempl opita invsls lsls lta nwcta cacl qacl ebita reta ltdta mveltd fata;
datalines;
1	0.8248516	-0.1518011	0.0304792	0.2419484	7.0990563	6.9841196	0.1967887	1.4685785	0.8222975	0.0015462	-0.1327088	0.2869419	0.2032662	0.1489044		
1	1.0335096	-0.1326395	0.0306986	0.1617942	6.7135387	6.4417273	0.0945615	1.1702723	0.7879421	0.0002978	-0.641455	0.2741081	0.1310257	0.2264629		
1	0.2977786	0.0119556	0.060537	0.0521915	3.0288666	3.5886431	0.2712726	3.1315842	2.8972755	0.0227047	0.6095286	0.107307	3.6599936	0.220958		
1	0.1082585	0.0098057	0.0372077	0.2320091	4.2003334	5.3670289	0.105996	2.2504215	1.3981411	0.0313227	0.7725004	0.0192089	5.6607933	0.0553714		
1	0.4621917	0.0072771	0.0958427	0.0822659	5.044668	5.0601009	0.1327464	1.9608082	1.3744929	0.0415032	0.3169592	0.2022219	1.0785992	0.6487616		
1	0.5358883	0.0570969	0.1125745	0.1110052	6.7326564	6.6693358	0.1361118	1.7829656	1.1026819	0.0684624	0.3740854	0.2419769	0.5588853	0.5208287		
1	0.8612232	0.1393788	0.0412159	0.117316	5.0590256	5.3226449	0.0914567	1.371655	1.0053919	-0.0565365	0.0258017	0.5354678	0.463836	0.3907114		
1	0.5433472	-0.1162309	0.0795822	0.2560436	3.367881	3.9875445	0.3962911	1.7401123	1.482788	0.0706697	0.4351819	0.0078997	0.6835921	0.0577287		
1	0.661019	-0.0627051	0.051116	0.0884808	5.5381638	5.7938786	0.0484363	1.2051941	0.9149341	0.012167	0.2433573	0.3755348	0.443554	0.5239427		
1	0.6024582	-0.0825494	-0.3320791	0.1401727	2.9002706	1.7032442	0.4364184	1.8978328	0.9432406	-0.3569098	0.1442187	0.1163782	0.6475071	0.0672185		
1	0.5909825	0.0450813	0.2244577	0.2667159	4.3868541	3.6827621	0.4257152	1.9941545	0.7347453	0.2050127	0.3291005	0.1443268	1.3498102	0.1460668		
1	1.0129593	-0.0471677	-0.1108081	0.1571172	6.124256	6.2908083	0.1788276	1.3675686	1.0941709	-0.1357425	-0.0801535	0.5206613	0.4085025	0.1080674		
1	0.4196441	-0.007018	0.219395	0.177784	6.7532031	6.2055233	0.340837	1.9973823	1.0977564	0.1985253	0.5300358	0.0462743	1.6470434	0.2190887		
1	0.2677425	-0.0868463	0.2751837	0.1525721	4.5783477	4.2885044	0.5459582	3.6866948	2.6834396	0.2520461	0.6768459	0.0589394	5.7819075	0.2423449		
1	1.5129908	-0.1642891	-0.1538614	0.1861137	5.4264964	4.4813209	0.2338165	1.7279517	0.2369083	-0.2108007	-0.958997	0.2454505	0.0577338	0.3857425		
1	0.3864648	-0.1098669	0.0019542	0.3443175	5.0108983	5.7295464	0.208148	1.6253158	1.1211407	-0.0211296	0.4594995	0.03146	2.5112187	0.1438679		
1	0.5180436	0.0170552	0.1468571	0.1685087	5.2977084	4.8090286	0.3464917	2.0965769	1.2272171	0.1135669	0.29119	0.1712788	1.174145	0.271892		
1	0.5517836	-0.0263528	0.0076706	0.1915647	4.1559733	3.5558591	0.3732052	2.2768122	1.0824911	-0.0403961	0.3483854	0.251072	0.2858569	0.3300556		
1	0.4999806	0.0414664	0.1080963	0.1772188	5.9877649	5.060282	0.6122419	3.6680104	1.7155828	0.0927818	0.3178792	0.2705052	0.8685266	0.1069587		
1	0.4725329	0	0.0619479	0.1862711	5.3565468	4.9363976	0.3208366	2.1303166	1.1313978	0.0295226	0.30065	0.1609855	0.9337609	0.376705		
1	0.4113172	0.0238362	0.2653707	0.2435292	4.3314035	3.6737162	0.48888	2.3243489	1.0509009	0.250123	0.4085758	0.0361939	1.3016009	0.1185313		
1	0.8807775	0.0139452	0.0202798	0.1741963	8.9384922	8.6761166	0.0293816	1.082683	0.4454064	-0.0189167	-0.1551367	0.3403367	0.1483934	0.5109807		
1	0.6037153	-0.1690236	-0.1181577	0.485257	2.847273	2.7700295	0.4187049	1.9944675	0.7493775	-0.1705686	0.1858258	0.1826811	0.6727115	0.1379571		
1	0.750466	0.1262479	0.0471908	0.13111	4.3963858	3.2527311	0.3294269	1.5664428	0.8589605	0.0370709	0.0170972	0.1688948	0.2157382	0.0574167		
1	1.1948127	-0.0425729	0.0590454	0.2112972	3.3995085	3.1759427	0.2431636	1.9064217	0.9214611	0.0215174	-0.6871598	0.9020172	0.2570617	0.2911303		
1	0.8239512	-0.1433397	-0.1753002	0.147754	4.7721263	4.3011174	0.0548788	1.1158556	0.6162722	-0.2279131	0.0592442	0.2661831	0.0529808	0.3639463		
1	0.507353	-0.0490206	0.087848	0.0815846	7.465802	7.7071556	0.2218835	2.8565839	2.3203191	0.0526214	0.2681453	0.0383287	0.1358952	0.5860148		
1	0.588802	0.149216	0.1501776	0.2390792	6.3810535	6.2407341	0.2832782	1.9791583	1.0282878	0.1237083	0.2540991	0.2746546	0.562862	0.2866809		
1	0.7042962	0.0106272	-0.0225112	0.1500036	6.6135992	6.2940942	0.1186478	1.3904842	0.7109605	-0.0751514	0.1848773	0.3723326	0.1334282	0.5370457		
1	1.0734669	-0.0564613	-0.3995384	0.3058596	4.3975157	4.0300432	0.2525183	1.524625	0.6069911	-0.4821509	-0.173055	0.5880804	0.2560055	0.1925325		
1	0.5079982	-0.2879793	0.105693	0.0679974	5.934785	5.2412588	0.0773867	1.2067345	0.8432934	0.0841074	0.3431196	0.0391109	3.3272349	0.1644481		
1	0.7739663	-0.1835033	0.0448149	0.1400758	3.593569	3.3100195	0.2023942	1.4697641	1.0380574	0.0188114	-0.5840462	0.3431246	0.2134781	0.333367		
1	0.585507	0.0145994	0.1888968	0.0535308	4.2435437	4.102051	0.166754	2.1239061	1.7082758	0.1541336	0.2022918	0.397453	0.9595487	0.5774656		
1	0.3524879	-0.0833932	0.1041323	0.2245026	3.6929874	3.8729354	0.7144765	6.8380812	5.3057486	0.0895158	0.4216656	0.0751707	2.8315043	0.1312773		
1	0.8655028	-0.1102577	0.064076	0.1780177	6.2351309	5.8538139	0.5104258	3.9767513	2.4566349	0.0406867	-0.0112079	0.0067028	0.20016	0.2117367		
1	1.1972617	0.0138942	0.2220793	0.1339013	6.410458	6.4358309	0.1887648	1.6554723	1.2021586	0.1976336	-0.2163968	0.0175891	0.5551336	0.2093488		
1	0.8245901	-0.0365137	0.0386526	0.1848524	4.5719664	3.9847919	0.140241	1.2743265	0.6238603	0.0151639	0.0217725	0.3100666	0.2878045	0.3071465		
1	0.7736941	-0.136779	-0.022664	0.2676949	5.2538947	4.6662046	0.316745	1.6065509	0.6839196	-0.0424759	0.0772825	0.1925134	0.3678989	0.159038		
1	0.7438458	-0.0036581	0.1028837	0.2583551	6.7582873	6.381062	0.3578932	2.4745566	0.9223415	0.0746171	0.151312	0.4394668	0.1302515	0.3945198		
1	0.7754228	-0.1500878	0.0622541	0.3445056	6.4739664	6.631824	0.4249434	3.0086535	1.6180176	-0.0039521	-0.0151677	0	0.376974	0.3381529		
1	0.6975749	-0.0599622	0.2286354	0.2651078	4.4005136	3.6528309	0.2701852	1.8053626	0.136322	0.1668293	0.1402195	0.3620923	0.2126431	0.3804925		
1	0.9971208	0.0045356	-0.1103814	0.2114412	6.6570258	6.8416184	0.3144677	2.7990267	1.7932913	-0.2212094	-0.2683537	0.0137912	0.296263	0.2461134		
1	1.0747966	-0.0154714	-0.070062	0.0347787	4.5896899	5.5891964	-0.2205942	0.704061	0.6868882	-0.0818949	-0.1883298	0.2879003	0.1316512	0.4599432		
1	0.5169765	-0.0710471	0.1861542	0.1394918	4.5066486	3.8482496	0.4100155	2.8568421	1.6365539	0.155007	0.1694758	0.2799267	0.9292176	0.2913252		
1	0.7342635	-0.1189216	0.0339937	0.2827977	5.9518273	6.1356952	0.2317365	1.8187291	0.987408	0.0068685	0.2423625	0.2963755	0.3798405	0.4603433		
1	0.5391169	0.0183609	0.1378381	0.2416622	6.8273998	6.8512141	0.5112452	5.4198598	3.3797874	0.1199206	0.3004538	0.3335265	0.6109	0.2928356		
1	0.4915605	-0.0716823	0.1634448	0.1107576	4.3641723	3.537519	0.3974711	2.0364755	1.3763324	0.1357319	0.4748567	0.0765098	0.9482565	0.2130301		
1	0.708715	-0.0755199	0.0332376	0.1450065	6.9175387	7.0680808	0.10246	1.6053648	0.8683593	-0.0067149	0.0754349	0.4323208	0.1451753	0.6379372		
1	1.0409914	-0.2216294	-0.3425781	0.0508379	4.466424	2.7603546	-0.362462	0.536236	0.178009	-0.427457	-0.3502091	0.0843776	0.7300142	0.1822335		
1	0.6172266	-0.0112582	0.1143309	0.1803756	7.1750854	6.8241463	0.2490902	2.081666	0.9691012	0.0496369	0.298755	0.2939409	0.2936341	0.4901937		
1	0.8298967	-0.0430578	0.0557999	0.1066736	8.0580801	7.6159981	0.0146467	1.0431096	0.5545881	-0.0138901	-0.2769512	0.3853562	0.24477	0.5603982		
1	1.0507733	-0.186105	-0.3081447	0.1375299	4.3322249	3.4411837	0.2956362	1.6689457	0.9103601	-0.3323256	-0.4641628	0.5999228	0.319525	0.2018393		
1	0.5036472	-0.1375588	-0.011899	0.3345613	6.5036164	6.4753332	0.2190095	1.7134443	0.5923143	-0.0674294	0.3366571	0.1808767	1.296913	0.2373029		
1	0.6146526	-0.071549	0.0844966	0.2204957	5.938536	5.5185679	0.345459	1.9379968	1.0268362	0.0625671	0.2601045	0.1943309	0.6176351	0.1757158		
1	0.6799123	0.2006738	0.1143884	0.205206	5.643138	5.6344897	0.0905194	1.2407389	0.6902475	0.0869775	0.0529308	0.2826091	0.2487053	0.2294789		
1	0.584596	-0.0111624	0.3667678	0.0469114	10.009634	9.5025299	0.0916545	1.3380657	1.0507506	0.310211	0.3182426	0.1464714	0.9526626	0.5822154		
1	0.5177049	-0.0631529	0.004336	0.3771399	2.9255468	2.127856	0.4383582	1.9637752	0.1226564	-0.0278941	0.2506142	0.0628704	0.4331554	0.0917763		
1	0.8573705	0.3528682	-0.0064327	0.3885843	4.8213695	5.1012764	0.1439211	1.3243797	0.6623884	-0.0345963	0.0701993	0.4136893	0.632147	0.2779958		
1	0.7520904	-0.0342698	-0.0168117	0.1818855	4.9431125	3.7782218	0.1376199	1.2550259	0.1745711	-0.0572351	0.2303495	0.2103689	0.3320995	0.2891912		
1	0.5966352	-0.1328396	0.0680591	0.1685237	6.7113204	6.9481263	0.2569327	2.0592541	1.5109793	0.023842	0.0743997	0.2562563	1.0577851	0.2761244		
1	0.7588121	-0.0622817	0.0181057	0.1603698	6.0203379	5.4431824	0.2205584	1.548619	0.8381823	-0.0228842	-0.0100368	0.2482106	0.0943306	0.3462554		
1	0.4865504	0.0064566	0.1607822	0.0629705	5.2681544	4.4909709	0.1811358	1.5489945	1.1338234	0.0849118	0.240938	0.1041607	0.9103076	0.440934		
1	0.9000771	-0.0237494	-0.0104929	0.8366592	2.1923039	2.3446593	-0.0189642	0.9777426	0.1345611	-0.0528495	0.0157874	0.0409126	0.3715909	0.1669233		
1	0.3221771	-0.1305	0.0704794	0.2795421	6.0810328	6.1456075	0.389965	3.0249161	1.6641478	0.0286101	0.5907356	0.0871095	1.4502886	0.3325762		
1	1.0281594	-0.0335046	-0.0229265	0.0561474	5.7215394	4.2637075	0.0492064	1.0818373	0.6806124	-0.0609505	-0.4277213	0.426888	0.0741454	0.1943449		
1	0.3933389	-0.1698624	0.0488108	0.3210761	5.513742	5.4722358	0.4162727	3.2936045	1.4495468	0.0079159	0.5101976	0.1803824	0.6846044	0.3205798		
1	0.603791	0.0347999	0.1565568	0.0847629	8.6563472	7.3578551	0.0749881	1.2306914	0.2753191	0.0994372	0.2812767	0.2163391	0.5931968	0.5300306		
1	0.4999897	-0.0782517	0.0864531	0.1772763	4.328114	3.8516204	0.4538299	2.5755331	1.5844194	0.0444959	0.0699644	0.205435	1.1979512	0.242017		
1	0.4906389	-0.1090465	0.1137883	0.2307774	5.7465317	4.8250831	0.3582682	2.0489409	0.3510257	0.0805119	0.0886239	0.1342358	0.9264949	0.1875344		
1	0.5233682	0.0477391	0.1157495	0.149927	7.1804418	6.6186168	0.1824347	1.5870272	0.7409145	0.0761407	0.3521149	0.174695	0.5157443	0.4364309		
1	0.7507181	0.0587943	0.1160254	0.0555992	5.7202975	4.2739999	0.1597374	1.407548	0.8050442	0.0558334	0.1706617	0.3125333	0.3283313	0.2981023		
1	0.6435415	0.1075664	0.0869979	0.213254	6.8382346	6.5714674	0.2252071	1.7042044	0.8335029	-0.0073488	0.067721	0.3106917	0.2848647	0.4093685		
1	0.4699268	-0.0547653	0.137956	0.1574654	5.8239808	5.7098449	0.3534997	1.8808248	1.4410258	0.0938567	0.3493183	0.0521028	1.5561629	0.219615		
1	0.2690064	-0.0021282	0.1844367	0.247379	4.0400073	3.7851732	0.4380149	4.3647797	1.9128743	0.1327333	0.5414216	0.1092852	5.3518665	0.3733528		
1	0.6148708	0.073593	0.1048678	0.2272088	3.7232926	3.8000873	0.2283574	1.8416206	1.0661329	0.0546194	0.2069387	0.3384098	0.94739	0.4519369		
1	0.5167998	-0.0036987	0.011052	0.0567071	5.9177248	5.0988865	0.0260189	1.0734486	0.7104136	-0.0732963	0.3082723	0.1463506	0.4388845	0.5670181		
1	0.2132748	-0.0692603	-0.0229498	0.1995402	3.5011155	2.9333222	0.4856566	4.4930629	1.9608681	-0.085864	0.4875361	0.0346226	2.6407768	0.3641312		
1	0.4977579	-0.0911048	0.0862306	0.0570687	6.8772324	6.50583	0.3610004	3.6003772	3.0044066	0.0324626	0.3825888	0.1835521	1.1839013	0.4419164		
1	0.7549751	0.0367254	0.1218582	0.0561554	6.0656312	4.5842939	0.0097271	1.026456	0.3546098	0.0373426	0.040635	0.3844576	0.302725	0.5896731		
1	0.902526	-0.0386005	-0.0020089	0.2445464	3.4782076	3.6885277	-0.4294932	0.478824	0.2383608	-0.0705822	-0.5106715	0.0578014	0.8317941	0.5266157		
1	0.5079005	-0.0269326	0.1111055	0.2047735	7.2776879	7.5663768	0.177261	1.8153253	1.1096328	0.0417349	0.4127488	0.1566038	0.8852736	0.5361926		
1	0.5765308	0.2363541	0.1377796	0.4661752	4.930979	4.6469265	0.3437462	1.5974495	0.5210465	0.1294693	0.0876674	0.0002793	6.5552436	0.0319701		
1	0.4643028	-0.0308778	0.111912	0.2087607	4.6236345	4.1339072	0.3921502	2.1962257	1.1570349	0.0777039	0.3455877	0.1364798	0.5939072	0.2767664		
1	0.4831608	0.0702096	0.0977739	0.159145	5.0733856	4.676519	0.351986	2.3023415	1.4266533	0.0542193	0.0554739	0.0936693	0.925157	0.3331211		
1	0.8476671	-0.1864826	0.1740864	0.0946584	6.0296577	4.8230768	0.340733	2.082642	1.077468	0.1362358	-0.3703752	0.4726062	0.4880104	0.2421906		
1	0.5414321	-0.0631719	0.0871299	0.1879337	7.5003843	6.9654768	0.3453161	2.2827824	1.0908593	0.0565422	0.2243951	0.1575536	0.7799759	0.3561874		
0	0.3653072	0.112021	0.2979582	0.030893	5.5941675	5.0382907	0.112856	1.6990798	1.3654412	0.2576111	0.5957167	0.1242666	3.1525139	0.4574656		
0	0.5497258	0.0223149	0.2159049	0.2753595	8.7528791	8.8006186	0.2510055	2.1499162	0.9472362	0.1862888	0.3722121	0.166362	0.827223	0.4462523		
0	0.6365287	-0.0168462	0.2080651	0.181162	8.8696566	8.6621849	0.0715735	1.2586751	0.4529751	0.1302397	0.3141833	0.2691177	0.595166	0.6332782		
0	0.5019974	-0.0086899	0.182323	0.3305697	8.5544795	8.4803282	0.2003011	1.5956838	0.5369198	0.163544	0.3881767	0.1350294	0.9980478	0.1549772		
0	0.3823067	0.0243334	0.1950342	0.082878	5.6586716	4.8215018	0.3676509	2.5923602	1.7632288	0.1475215	0.5356717	0.0715278	2.4882041	0.3834269		
0	0.6133737	0.0514622	0.0886088	0.1064586	7.6373555	7.4034275	0.046947	1.1580585	0.7051774	0.0314877	0.2458583	0.2725958	0.6760874	0.6024769		
0	0.2309309	0.1201105	0.1489176	0.1298999	5.2287898	5.1484459	0.4152768	3.7983409	2.849781	0.0889517	0.2870261	0.0184325	4.5742575	0.4200983		
0	0.4383486	0.0335822	0.166709	0.1661736	8.1316769	7.4129075	0.3328288	2.4889212	0.9635685	0.1374866	0.2948416	0.1616072	2.2032102	0.3982903		
0	0.3035335	0.0298836	0.1246306	0.2706287	7.2624956	6.7476017	0.6715704	4.7088726	2.2077225	0.1046201	0.5267048	0.122462	4.158828	0.1066554		
0	0.6184723	0.0240355	0.2521872	0.1756531	4.1924782	3.5813401	0.2983068	1.5304837	0.9549398	0.2239322	0.1571054	-99.99	1.4076991	0.1052025		
0	0.5476468	0.0270661	0.1948656	0.1525138	6.8258367	6.2782394	0.2203423	2.0698773	0.7894241	0.1419679	0.3815636	0.2516531	0.932221	0.5155579		
0	0.5448755	-0.0727925	0.1852604	0.1332415	6.0956277	5.5865447	0.2400009	1.799777	1.061044	0.1293534	0.2985532	0.1918569	1.0778307	0.3564547		
0	0.157739	-0.0029739	0.2619184	0.0163295	5.3509786	5.1495347	0.3841594	3.5299161	3.3983778	0.2153813	0.6535754	-99.99	8.9620689	0.23779		
0	0.2077052	0.0283467	0.2939058	0.060723	5.5911927	5.3229806	0.1829322	2.2864227	1.7280431	0.2496788	0.7016025	0.0026497	14.511942	0.543027		
0	0.504469	-0.0358074	0.1679022	0.0944103	4.3030594	3.6351905	0.3441248	3.2353082	2.0394149	0.110966	0.3329338	0.3356952	0.532988	0.4234069		
0	0.4828193	0.0395327	0.0904239	0.2813943	5.4201552	5.2384645	0.4364686	2.9240081	1.4364417	0.0523074	0.2783027	0.2244945	0.8736294	0.2896962		
0	0.7280706	-0.070058	0.1053237	0.0955155	5.0902092	3.6835804	0.1244142	1.2328205	0.5031681	0.0515681	0.1650953	0.1936921	0.2652164	0.3077404		
0	0.6217579	0.0506111	0.1369968	0.1780885	8.0694335	7.602944	0.2312944	2.0936048	0.7510716	0.1024358	0.1827453	0.3574515	0.4895063	0.4678715		
0	0.6079811	-0.0250317	0.0955213	0.2055826	5.6541697	4.8561891	0.3652803	2.0843314	0.7288904	0.0714797	0.2557447	0.2187097	0.7188046	0.258767		
0	0.5697746	-0.0365543	0.1175661	0.089887	8.2948753	8.6121158	0.0117876	1.0972356	0.557326	0.0726787	0.2387546	0.3468686	0.7751228	0.8049787		
0	0.1455394	0.1053423	0.2492498	0.075232	2.8325629	3.1960055	0.7936063	6.4528483	6.0934469	0.2405799	0.3832438	0	27.604182	0.0272014		
0	0.402722	-0.1123334	-0.1844752	0.150792	5.0243355	4.2055254	0.3792304	2.2075145	1.1186542	-0.2256668	0.2818439	0.0778948	1.0909411	0.2856807		
0	0.3136411	0.0049022	0.0965607	0.2533637	3.3411588	2.9569797	0.4115545	2.4455381	1.1387854	0.0720703	0.4334848	0	2.4762929	0.2778476		
0	0.6929718	0.1138332	0.1095099	0.1645915	7.0570593	6.1711076	0.2111479	1.4243248	0.6221241	0.0879503	0.1900227	0.1871598	0.411987	0.2521466		
0	0.3582842	-0.0019675	-0.0175223	0.082576	6.8634841	5.909703	0.1840369	1.775137	0.8724251	-0.0791759	0.2922055	0.0085474	0.643337	0.5142171		
0	0.5862266	0.0525194	0.077849	0.158118	6.7347905	5.8108347	0.2613966	1.5950376	0.6882726	0.0547886	0.3808403	0.0962942	0.645877	0.1763418		
0	0.2218707	0.3193186	0.1633	0.1975626	3.8931464	4.3494492	0.5745386	5.8500131	4.7932964	0.1017953	0.0258606	0.1034095	8.3140041	0.2860586		
0	0.4259343	-0.1010208	0.2119095	0.1080653	5.9321786	5.3129266	0.2127199	2.0545304	1.0594112	0.1494917	0.6215545	0.1850462	1.7822981	0.4850458		
0	0.3947601	0.0712021	0.2036788	0.2407373	3.9464713	3.6836165	0.494068	3.0765288	1.7605436	0.1658589	0.4598165	0.1186446	2.2960969	0.2608657		
0	0.3626217	0.0675547	0.2770596	0.2545603	8.2219877	7.7585573	0.4403686	2.633888	1.132607	0.2347168	0.5735228	0.0931002	3.204629	0.2569881		
0	0.4594232	0.0038804	0.2493961	0.2202022	5.5495211	5.2172588	0.4888425	3.0558928	1.7648136	0.2250948	0.4541561	0.212079	2.584024	0.174947		
0	0.5440595	-0.032561	0.2191124	0.0517534	11.37875	11.017034	0.0311957	1.1293154	0.8212906	0.158333	0.4817472	0.0806757	0.9282302	0.6760012		
0	0.4092618	0.1603711	0.1266047	0.1627269	2.9682332	3.1583933	0.341705	2.2649866	1.7668958	0.0980863	0.0068589	0.1391368	2.7557664	0.2262906		
0	0.4635334	0.0168162	0.1158759	0.0850947	4.2800219	3.5079756	0.4309728	2.0717975	1.6138023	0.0951133	0.4597108	0.0402729	0.9831815	0.1235211		
0	0.641008	-0.0128247	0.1354181	0.0350791	6.7821177	6.8609078	0.0334501	1.2020557	1.0062145	0.0996593	0.3400157	0.4113831	0.8627135	0.2511065		
0	0.3489755	0.037872	0.2122616	0.2044945	6.6403486	6.0783873	0.3303984	2.3732837	0.8823421	0.1821509	0.579031	0.0773119	2.5012616	0.3549516		
0	0.3004339	0	-0.0399542	0.2374581	5.7642037	6.5360327	0.0823983	1.6932019	0.769935	-0.0477861	0.6482036	0.1129026	1.6379258	0.0764011		
0	0.6189301	0.0582413	0.1609074	0.1477038	6.6347224	6.614799	0.1957072	2.2191247	1.2805136	0.1101086	0.2367024	0.3217707	1.3411989	0.3666746		
0	0.4307621	-0.0745019	0.1229418	0.1947073	6.73632	6.5381293	0.392169	3.0346776	1.8030547	0.0581654	0.4631366	0.173762	1.3745872	0.3705163		
0	0.6283859	0.0173371	0.2052145	0.1306029	5.2076026	4.5403155	0.2890463	1.6443758	1.0769309	0.1418997	0.2787142	0.1773637	0.2911872	0.1771726		
0	0.5440344	-0.0397826	0.1037576	0.2105781	3.7748981	3.2996144	0.3456101	2.0822265	1.0216108	0.0660859	0.5685092	0.1561069	0.3982751	0.2874361		
0	0.4605938	-0.0296274	0.1718108	0.0791446	7.2441772	6.2257523	0.2024131	1.7279574	0.9398504	0.1203071	0.5170069	0.1079243	1.1663318	0.5024139		
0	0.5792285	0.1282274	0.1652074	0.1431439	5.6271899	4.8967805	0.4156368	2.272991	1.3628745	0.1366216	0.2456652	0.2433499	0.7324122	0.2349842		
0	0.7116485	0.0796085	0.1638268	0.1352783	5.5231185	5.1947338	0.1750584	1.5365972	0.9607473	0.1335543	0.0369469	0.2705614	0.7166916	0.410125		
0	0.5223719	-0.0104489	0.1605249	0.1015299	7.0551402	6.1756406	0.3309159	2.3999251	1.364919	0.1336577	0.4022262	0.216763	0.8939436	0.3247685		
0	0.4122924	0.0328114	0.1955691	0.0415228	6.2652054	5.762898	0.0388877	1.3090449	0.7637324	0.1276153	0.5376708	0.2165154	2.5392959	0.7801239		
0	0.5483481	0.4564754	-0.0636567	0.3225927	2.2433844	2.3202105	0.350026	2.3718645	1.2010171	-0.0920255	0.0377962	0.2846393	1.4712139	0.2458917		
0	0.6435538	-0.0312541	0.0700111	0.2855994	5.8961162	5.8024378	0.2851491	1.8225711	0.9177915	0.0159173	0.1896652	0.2842284	0.7791279	0.2616023		
0	0.5893756	-0.0109018	0.1652246	0.1767557	6.4209289	5.8640135	0.3747588	2.1815887	1.2089465	0.1305542	0.3966553	0.2371127	1.3510407	0.1351691		
0	0.285424	0.0112499	0.1497204	0.162897	3.3028204	2.3823738	0.6049772	3.1324747	1.6910139	0.1274756	0.6729305	0	1.5867439	0.1093956		
0	0.5561706	-0.0427773	0.1569521	0.1656442	7.7388256	7.9022452	0.0367958	1.1669129	0.5288035	0.0592641	0.3975904	0.1751872	1.0593748	0.6968414		
0	0.2709406	0.0160076	0.2414838	0.0299708	7.2076751	6.9300568	0.0859258	1.4884715	1.2635752	0.2115016	0.6962969	0.0506026	3.7640723	0.3398036		
0	0.5907011	-0.0279815	0.0920724	0.2044275	4.9774542	4.6119131	0.2542206	1.9325027	0.8517379	0.0491615	0.3776648	0.2787084	0.6024776	0.4429437		
0	0.5233964	0.0440859	0.19132	0.1542121	5.8734684	5.3098222	0.3333218	2.4515162	1.2715625	0.1487752	0.3917719	0.2688271	1.5101983	0.3363043		
0	0.7526157	0.2807935	0.0912483	0.3937725	6.4450867	7.1992693	0.1674433	1.682402	0.9275173	0.0716136	0.1645148	0.4548537	0.8986225	0.323287		
0	0.4996104	0	0.1268066	0.1366618	7.225678	7.4510602	0.0523326	1.468076	0.4923922	0.0632178	0.2979645	0.303264	1.0537299	0.7084958		
0	0.3069159	0.0586364	0.382154	0.0881903	5.0894529	4.5036558	0.1717754	1.97538	1.075795	0.2844865	0.1134419	0.0504804	-99.99	0.5799053		
0	0.4328487	-0.00885	0.221142	0.1614942	7.3978603	6.8374985	0.4717607	3.0721026	1.8298541	0.1851919	0.5547647	0.1847256	2.1105736	0.2683521		
0	0.2025695	-0.0321924	0.280728	0.2379831	2.4431324	2.2383142	0.585332	6.1333354	3.5718323	0.2330835	0.4838329	0.0517131	8.3267723	0.2933619		
0	0.6409379	0.0267146	0.1498165	0.2304084	5.4085087	5.4041582	0.3389766	2.2347097	1.3917967	0.1075762	0.1381371	0.3029352	0.8586706	0.3747836		
0	0.461548	0.1219727	0.124741	0.1667545	5.9183533	4.9082545	0.4555725	2.8688853	0.990507	0.0886937	0.3312998	0.1928429	2.0889602	0.2346913		
0	0.541322	0.0167988	0.1780516	0.1829084	6.578366	5.853879	0.2428685	1.6066167	0.6638211	0.1171861	0.4247201	0.1353551	0.6082692	0.2948626		
0	0.464525	0.0072749	0.1835125	0.1347843	7.4156404	7.056761	0.1690024	1.4833276	0.9314442	0.088852	0.2098558	0.020976	2.2003431	0.4414513		
0	0.2523573	0.074248	0.1678157	0.2340115	4.3934743	3.9870213	0.5482355	4.3891577	2.2170459	0.1435461	0.2797522	0.0221444	4.5828417	0.22982		
0	0.6027546	0.0222146	0.0335383	0.2674471	3.2868719	3.2042711	0.255634	2.1657685	0.8411077	0.0081094	0.1595013	0.3445538	2.5687929	0.5045441		
0	0.489363	-0.0064921	0.1565549	0.1164982	8.2151107	8.1967724	0.1346723	1.6592634	1.078413	0.1052644	0.4248207	0.1553379	1.2322309	0.6085151		
0	0.6262413	-0.2730399	0.0818315	0.0192874	5.7916732	6.3992156	-0.0073804	0.9371722	0.8477403	0.0418057	0.15582	0.3944932	0.5049107	0.531647		
0	0.4810175	0.0417804	0.200011	0.0588328	6.2486581	4.760984	0.1586969	1.6662054	0.5728851	0.1409829	0.4497589	0.2334366	0.7818304	0.5999812		
0	0.5253095	0.1830087	0.0890926	0.0956092	6.9966057	6.9062418	0.1742882	5.0277914	2.6093075	0.0406576	0.3506738	0.4185775	2.1289867	0.3185168		 
0	0.6727151	-0.054518	-0.0512013	0.1674107	4.1026598	3.351699	0.2309666	1.4530277	0.7572076	-0.0790172	0.0350951	0.0666033	0.347517	0.2554419		
0	0.4076245	0.0886916	0.140878	0.1548439	5.5421911	5.4382217	0.1858959	2.5951842	1.1208753	0.0712858	0.5216701	0.2608587	1.6026883	0.6324183		
0	0.5195657	0.036088	0.1708105	0.0889381	6.8084185	6.4023809	0.1420781	1.7241613	1.0438061	0.1147108	0.422355	0.1726344	1.5013701	0.5593588		
0	0.1823597	-0.2573278	-0.053062	0.0429145	4.0318152	3.9702057	0.4373568	3.4330039	3.1791012	-0.3566792	0.2181017	0.0025997	3.6440607	0.3660794		
0	0.4457515	-0.0119228	0.221946	0.0932687	8.6565605	7.7999963	0.1601533	1.7588639	0.7180697	0.1749322	0.4953349	0.1823305	1.3438926	0.5510933		
0	0.5634028	0.0839026	0.0868657	0.1797401	4.7299643	4.3938513	0.257539	2.0594852	1.0246553	0.047673	0.1785826	0.2706802	1.509353	0.4822587		
0	0.5991887	-0.0208516	0.1434131	0.2524481	2.9634053	2.4932134	0.5167038	3.7725146	1.6047807	0.103324	0.1488227	0.3732103	0.5001825	0.273783		
0	0.1969582	0.2055173	0.2217966	0.1583912	4.0255144	3.8276491	0.5955406	4.3191323	3.2432222	0.2006712	0.0111385	0.0010324	27.631832	0.1629869		
0	0.6812963	0.0243114	0.1470503	0.067012	9.8162138	8.306961	0.033769	1.0975775	0.2216979	0.0853377	0.2866676	0.3148493	0.3573431	0.609106		
0	0.3175898	0.0154621	0.1356679	0.2204472	5.6970962	5.4403498	0.2777129	2.8894575	0.9505855	0.1115597	0.6287595	0.1424958	3.1960833	0.54711		
0	0.2936115	0.4281081	0.2580113	0.1698311	4.7331122	4.5826744	0.5345086	3.2219258	2.4013355	0.2070324	0.2323677	0.0530505	12.474924	0.214703		
0	0.5599171	0.0342527	0.1965865	0.1622461	8.7453491	8.1910799	0.220082	1.6057551	0.8284296	0.1532337	0.3694977	0.1641094	0.7570034	0.2973923		
0	0.2546646	0.0977284	0.2278698	0.0891506	6.8151214	6.7469343	0.512323	3.5840322	3.1026483	0.176469	0.3615902	0.0093183	10.365155	0.261363		
0	0.2518933	0.0456396	0.059856	0.2494947	4.3277404	3.8712559	0.4434724	3.7681999	1.3098666	0.0284794	0.8352498	0.091691	2.7901596	0.3424656		
0	0.5730193	0.0330378	0.2027841	0.189908	2.6399333	1.9688696	0.4700214	2.2429218	1.2604757	0.18651	0.040257	0.1642399	1.7573422	0.1501071		
0	0.2207773	0.0414735	0.284551	0.3116122	5.6886329	5.5243741	0.5010991	3.6327116	1.7032738	0.2490068	0.7103061	0.0132638	8.5585408	0.3023127		
0	0.4614469	0.0004599	0.2887948	0.1305927	5.6954601	5.1935801	0.4657426	3.2084265	2.185559	0.2488106	0.439588	0.1881886	3.1998845	0.3233638		
0	0.7085766	0.0668712	0.3064973	0.0714383	7.8180661	7.5122642	0.0346419	1.1126223	0.7972944	0.2632989	0.1868072	0.2847357	1.2680119	0.5506749		
0	0.7997144	-0.0030182	0.080778	0.2385249	6.5955723	6.2637943	0.3572029	2.5935395	1.1107795	0.0498692	0.0985411	0.5660806	0.3057399	0.1833719		
0	0.5211444	0.0705077	0.2256984	0.1169495	6.2418762	5.4244568	0.3118015	2.2761092	1.1921606	0.1754351	0.3107281	0.2406473	1.246249	0.3858605		
0	0.3611742	-0.0538973	0.2246639	0.0682361	3.8775269	3.48894	0.2285915	1.8405777	1.4705001	0.1819767	0.5916182	0.0892281	1.3321196	0.2763553		
0	0.3409215	0.1348546	0.2287683	0.120886	5.1410085	4.7432369	0.2800689	2.8296386	1.654128	0.1683432	0.5836105	0.1157068	1.9612837	0.484897		
0	0.4579452	0.0095897	0.1799007	0.088959	7.4302146	7.2704008	0.1935018	2.6365193	1.7537802	0.1258931	0.3885853	0.2556619	1.0758894	0.6803961		
0	0.6009653	-0.0823794	0.1705399	0.1486187	7.2320722	6.7338415	0.2886671	1.795277	1.1214109	0.1459449	0.2264552	0.1603401	0.4902529	0.2123327		
0	0.2414106	-0.1476019	0.0785937	0.1379037	5.0585974	4.6326226	0.3448785	2.4585373	1.5655899	0.0536659	0.3900781	0	4.7086357	0.2314887		
0	0.4798424	0.017525	0.1527736	0.2133445	8.745114	7.9738614	0.2564413	1.7804428	0.3763838	0.1254926	0.4662019	0.104274	1.8102845	0.3734465		
;
*/

/*If we have the SAS data set distress.sas7bdat, then we can create a library and use the SAS data set directly*/
/*The following statement creates a library called "eco6352"; We can choose the directory we like and put the distress.sas7bdat into that directory;*/
/*When we want to refer the data set, we need to use "eco6352.distress"*/

/*   libname eco6352 "C:\Users\37311408\Documents\eco6352";   */


/* Assign labels to the variables */ 
data distress;
set distress;
label       yd     = "Distress Dummy"
            tdta   = "Debt to Assets"
            gempl  = "Employee Growth Rate" 
			opita  = "Op. Income to Assets"
		   	invsls = "Inventory to Sales" 
			lsls   = "Log of Sales" 
			lta    = "Log of Assets" 
			nwcta  = "Net Working Cap to Assets"
		   	cacl   = "Current Assets to Current Liab" 
			qacl   = "Quick Assets to Current Liab" 
			ebita  = "EBIT to Assets" 
		   	reta   = "Retained Earnings to Assets"
            ltdta  = "LongTerm Debt to TotAssets"
            mveltd = "Mkt Value Eqty to LTD" 
			fata   = "Fixed Assets to Assets";
run;


/* Logit model to explain financial distress  */
/* Using backward selection to choose best variables  */
/* The "descending" option is used because we want to 
   model Prob(y=1) instead of the default of modeling
   Prob(y=0).  */ 

proc logistic data=distress descending;
	title "logistic analysis of distress characteristics";
	model yd = tdta gempl opita invsls lsls /rsquare selection = backward slstay=0.05;
run;

/* Here we use the Probit model.  Unfortunately, it does not have a stepwise
	 selection option.  We have to do it manually.  */

/* Like Proc Logistic, Proc Probit chooses to model Prob(y=0) as its default.  In 
	econometrics we usually model Prob(y=1) instead.  Thus below, we use the "order=data"
	option to make sure that Proc Probit models Prob(y=1).  Also you should note
	that Proc Probit (like Proc Logit) does not allow more than one model statement per Proc step.
	Thus we have to estimate the separate models with separate Proc Probit steps.  Notice the
	use of the "class" statement in Proc Probit.  The class statement is not required
	in Proc Logistic.  */ 

/*  In the first probit estimation below, two variables are statistically insignificant at the 5% level, 
	namely, invsls and lsls.  The p-values for these two variables are, respectively,
	0.1092 and 0.0903.  We drop invsls because it has the higher p-value.  Upon dropping
	this variable we see that the remaining variables are all statitistically significant
	at the 0.05 level.  This final model has the same variables in it as the final variables
	chosen in the logit model when the backward variable selection technique is used.  */

proc probit data=distress order=data;
	title "probit analysis of distress characteristics";
	class yd;
	model yd = tdta gempl opita invsls lsls /lackfit;
	run;

proc probit data=distress order=data;
	title "probit analysis of distress characteristics";
	class yd;
	model yd = tdta gempl opita lsls /lackfit;
	run;

/*  Below we try backward selection via Proc Logistic on ALL of the variables that are in the data set.
    We get a slightly different final equation with the variables tda gempl opita invsls and qacl.  */

proc logistic data=distress descending;
	title "logistic analysis of distress characteristics";
	model yd = tdta gempl opita invsls lsls lta nwcta cacl qacl ebita reta ltdta mveltd fata/rsquare selection = backward slstay=0.05;
    run;

/*  Consider the two models we presented above (based on Proc Logistic).  The first model was an "abbreviated" one
	used solely for demonstration by Ekkehart Boehmer, John Paul Broussard, and Juha-Pekka Kallunki.  After backward
    selection, that model has the explanatory variables tda gempl opita and lsls with the Goodness-of-Fit statistics of
	AIC = 193.530 and SC = 209.522.  However, our second more comprehensive backward selection resulted in a model
	with the explanatory variables tdta gempl opita invsls and qacl with the Goodness-of-Fit statistics of
	AIC = 192.166 and 211.357.  Which of these models is better?  According to the AIC criterion the second model is
	preferred while according to the SC criterion the first model is preferred.  As usual, between the two criteria
	the SC criterion tends to choose the more parsimonious model, other things held constant.  According to Occam's razor,
	we would then choose the first model.  Of course, Goodness-of-Fit is not the only consideration.  One also needs to
	make sure that a chosen model is "congruent with economic theory."  That is the estimated signes of the coefficients
	should match up with the "a priori" signs suggested by economic reasoning.  This is in fact the case
	with respect to the first (SC chosen) model.  The a priori signs on the variables are as follows: tdta (+), 
	gempl (-), opita (-), and lsls (-).  As desired, the signs of the estimated coefficients do match the a priori
	signs suggested by economic reasoning.  Recall that we are modeling Prob(y=1), i.e. the probability of bankruptcy,
	not Prob(y=0).  */ 

/* If you are checking these SAS results with those produced by EVIEWS, notice that EVIEWS
	models Prob(y=1) as its default.  */