LABOR PRODUCTIVITY AS A FACTOR FOR BANKRUPTCY PREDICTION

Daniel BRÎNDESCU OLARIU West University f Timisara LABOR PRODUCTIVITY AS A FACTOR FOR BANKRUPTCY PREDICTION Empirical study Keywrds Crprate finance Risk Failure Financial rati Financial analysis Classificatin accuracy JEL Classificatin G32, G33, M21 Abstract The current study evaluates the ptential f the labr prductivity in predicting crprate bankruptcy. The ppulatin subjected t the analysis included all cmpanies frm Timis Cunty with yearly sales f ver 2200 Eurs. The interest fr the labr prductivity was based n the recmmendatins f the scientific literature, as well as n the availability f infrmatin cncerning its values t all stakehlders. The event n which the research was fcused was represented by the manifestatin f bankruptcy 2 years after the date f the financial statements f reference. All tests were perfrmed ver a paired sample f 1424 cmpanies. The methdlgy emplyed in evaluating the ptential f the labr prductivity was based n the general accuracy ensured by the rati (63.2%) and the Area Under the ROC Curve (0.665). The results cnfirm the practical utility f the labr prductivity in the predictin f bankruptcy. 27

1. Intrductin In the cntext f the ecnmic crisis, as well as that f the changes generated by the entrance f Rmania in the Eurpean Unin, the annual frequency f bankruptcy cases has increased at natinal level, reaching almst 3% by the end f 2013 (Brîndescu-Olariu, 2014a). The increased frequency f the annual bankruptcy cases was accmpanied by an increase in the lan default rati, Rmania tpping in this regard at the end f 2012 the 4 th place within the Eurpean Unin. Befre 2007, the imprtance f the bankruptcy phenmenn frm a macrecnmic perspective was limited in Rmania, as there was little culture fr bankruptcy filing at micrecnmic level. With the bankruptcy nt representing a cncerning phenmenn in the past, limited effrts were made at natinal level fr the develpment f specific bankruptcy risk assessment tls. Instead, the scientific interest fr the assessment f the bankruptcy risk was purely theretical, with mst researchers settling fr testing freign mdels fr bankruptcy predictin ver small islated samples f Rmanian cmpanies. Several natinal mdels were elabrated ver time, but mst f the develpment methdlgies were relatively superficial, as the public interest fr the subject was lw. The general gals f cmpanies are usually related t maximizing prfits and sharehlders wealth ( Ștefea and Circa, 2006). In rder t reach such gals, capital must be invested. The investment decisins must be fundamented nt nly n predicted return ratis, but als n risk analyses. The increase f the annual bankruptcy frequency has made the public significantly mre aware f the phenmenn. As the state f bankruptcy affects all the stakehlders f the cmpany, the existence f instruments fr bankruptcy predictin becmes imprtant. Under these circumstances, there is a need fr the develpment f methdlgies specific t the current characteristics f the Rmanian cmpanies. Recent studies ( Brîndescu Olariu, 2014b, Dima et al., 2011) have recnfirmed the ptential f financial ratis in the predictin f the bankruptcy risk, financial risk, financial perfrmance r stck prices. The present paper is fcused n testing the ptential f labr prductivity indicatrs fr crprate bankruptcy predictin, 2 years prir t the pssible event. Previus studies (Mldvan, Lbnț și Niclescu, 2013) have shwn that the managers frm Rmanian cmpanies see the human capital as having nly a lw t average influence n the crprate cmpetitiveness. The hypthesis f the research is that labr prductivity indicatrs are negatively crrelated t the bankruptcy risk and thus can represent useful tls fr the assessment f the bankruptcy risk. Only publically available data was used. If the research wuld prve the usefulness f the prductivity indicatrs in the predictin f bankruptcy, it culd be cntinued with the develpment f a methdlgy f analysis fr the assessment f the bankruptcy risk based n public data and thus accessible t all stakehlders. 2. Ppulatin and methdlgy The ppulatin initially subjected t the analysis included all the cmpanies frm the Timis Cunty that submitted financial statements t the fiscal authrities in the perid 2001 2011 (247,037 yearly financial statements). Financial rati analysis was nt cnsidered applicable fr cmpanies with n yearly incme, as the cntinuity f the perating activity represents a fundamental hypthesis f the financial rati analysis. Three phenmenns with natinal impact were als cnsidered fr their ptential f changing the prfile f the cmpanies that declare bankruptcy: The changes brught t the laws cncerning bankruptcy thrugh the adptin f law 85/2006; The entrance within the Eurpean Unin in 2007; The manifestatin f the ecnmic crisis starting with the last quarter f 2008. Under these circumstances, it was cncluded that the initial ppulatin shws imprtant prblems f hmgeneity, which d nt recmmend a unitary treatment: The cmpanies with n activity cannt be evaluated based n the same methdlgy as the cmpanies with a financial histry; The cmpanies that became bankrupt after the issue f law 2006/2006 shw different characteristics cmpared t the cmpanies that went bankrupt befre 2007, under different laws; The cases f bankruptcy registered after 2009 have different causes cmpared t the cases appeared befre the beginning f the ecnmic crisis. Taking all the afrementined differences int accunt, the initial ppulatin was adjusted: all the yearly financial statements that reprted sales under 10000 lei were excluded; nly financial statements frm the perid 2007 2010 were retained. The research targeted the risk f bankruptcy after 2 years frm the date f the financial statements taken as reference in the analysis. As the interest was fcused n the phenmenn f bankruptcy during the crisis perid, the first financial statements included in the study were frm 2007. 28

The last year fr which data cncerning the status f the cmpanies was available was 2012. Under these circumstances, the last financial statements included in the study were thse frm 2010. Hlding all the abve int accunt, the target ppulatin included all cmpanies frm Timis Cunty that submitted yearly financial statements t the fiscal authrities during the perid 2007-2010 and that registered yearly sales f at least 10000 lei (aprx. 2200 Eurs). In accrdance, 53,252 financial statements frm the perid 2007-2010 were included in the analysis. The cmpanies f which financial statements were included fr ne year were nt necessarily included fr the fllwing perids. As the study did nt target a dynamics analysis, the yearly financial statements can be regarded as individual subjects. The surce f the data was represented by the nline publicatins f the Ministry f Public Finances f Rmania. The current study emplyed methds fr calculating the financial ratis that wuld make the prpsed methdlgy f analysis accessible t all stakehlders. Of the entire target ppulatin, 712 cmpanies went bankrupt in the perid 2009 2012, tw years frm the date f the financial statements f reference: f the 12,570 cmpanies included with financial statements fr 2007 in the research, 30 went bankrupt in 2009 (0.24%); the rest f the cmpanies f the 13,037 cmpanies included with financial statements fr 2008 in the research, 94 went bankrupt in 2010 (0.72%); the rest f the cmpanies f the 12,574 cmpanies included with financial statements fr 2009 in the research, 159 went bankrupt in 2011 (1.26%); the rest f the cmpanies f the 15,071 cmpanies included with financial statements fr 2010 in the research, 429 went bankrupt in 2012 (2.85%); the rest f the cmpanies Tw prductivity ratis were tested fr their ptential in the assessment f the bankruptcy risk. Cmmnly, prductivity ratis are based n a vlume measure f utput and a measure f input (number f hurs wrked r ttal emplyment). As public data des nt include infrmatin cncerning the prductin vlume f cmpanies, yearly turnver (as an expressin f the gds and services sld) was used as an utput indicatr instead. Thus, the first rati had the fllwing frm: Labr prductivity 1 = Sales Ttal emplyment Anther ppular apprach in labr prductivity analysis uses the grss added value as an utput indicatr. The nly cmpnent f the yearly value added that is publically available is the grss prfit. Althugh the grss prfit des nt generally remunerate the emplyees (it ges t the state, stakehlders r remains as part f the equity), it is directly cnnected t the grss added value and thus, indirectly cnnected t the ttal emplyment. Grss Labr prductivity 2 = Ttal emplyment In accrdance with many f the appraches frm the internatinal literature, the ratis were tested ver a paired sample. In rder t build a paired-sample, each f the 712 cmpanies that went bankrupt in the perid 2009 2012 was assciated with a cmpany frm the same ecnmic field that had the clsest turnver in the year f reference fr the financial statements included in the analysis. The data was prcessed by using the SPSS sftware. The state f the cmpany tw years frm the date f the financial statements f reference was defined as the dependent variable, a binary variable that can take the fllwing values: 1, fr the cmpanies that went bankrupt 2 years after the date f the financial statements f reference; 0, fr the cmpanies that cntinued their activity under nrmal cnditins at least until the end f 2012. In rder t simplify the explanatins, the cmpanies that went bankrupt 2 years after the date f the financial statements f reference will simply be referred t as bankrupt, while the cmpanies that cnditins at least until the end f 2012 will be referred t as nn-bankrupt. When defining the target ppulatin, the cmpanies that clse their activity fr ther reasns than bankruptcy during the perid f analysis were excluded. As an example, the value f the variable State was 1 fr all the cmpanies that went bankrupt in 2011 and it was assciated with the financial ratis f the respective cmpanies frm 2009. These cmpanies were nt included in the analysis fr the fllwing years (fr 2010 with the financial statements and fr 2012 with the state variable), even if they still existed. Initially, the perfrmance f each rati as predictr f bankruptcy was tested thrugh the Area Under the ROC Curve ver the entire paired sample f 1424 cmpanies. 29

The ROC Curve reflects graphically the relatinship between the sensitivity and the specificity fr all pssible cut-ff values (van Erkel, Pattynama, 1998). The area under the ROC Curve thus islates the classificatin perfrmance f a classifier with n cnnectin t a specific cutff value, which makes it ne f the mst viable slutins fr measuring the classificatin perfrmance and fr cmparing classifiers (Hanely, McNeil, 1982, Faragi și Reiser, 2002). The area under the ROC Curve (AUC), can take values between 0 and 1 (Skalska și Freylich, 2006). An AUC f 0.5 crrespnds t a by chance classificatin accuracy, while an AUC f 1 crrespnds t a perfect accuracy. The evaluatin f predictrs by their AUCs is usually based n the fllwing grid (Tazhibi, Bashardst și Ahmadi, 2011): 0.5 0.6: fail; 0.6 0.7: pr; 0.7 0.8: fair; 0.8 0.9: gd; 0.9 1: excellent. In a secnd step, fr the ratis cnfirmed as pssible predictrs by their AUCs (ver 0.6), the general classificatin accuracy was determined. The general accuracy f the classificatin represents the percentage f cmpanies crrectly classified, a weighted average f the sensitivity and the specificity. The sensitivity represents the accuracy f the classificatin f bankrupt cmpanies. The specificity represents the accuracy f the classificatin f nn-bankrupt cmpanies. The ptimal cut-ff value fr the 2010 sample was used fr ut-f sample tests (ver the 2007-2009 samples). The ptimal cut-ff value fr the 2010 sample was determined thrugh the inspectin f the crdinating pints f the ROC Curve. As the samples used were paired, the weight f the bankrupt cmpanies was equal t the weight f the nn-bankrupt cmpanies (50%). Fr such a sample, the by chance accuracy is 50% (by classifying all 1424 cmpanies as bankrupt, the analyst wuld be crrect in 50% f the cases). A rati is cnsidered a useful classifier if it allws fr a general accuracy at least 25% higher than the by chance accuracy (Chung, K., Tan, S., Hldswrth, D., 2008). Based n this benchmark, the ratis wuld be cnsidered as ptentially useful if they wuld ffer an accuracy f at least 62.5% (a = 50% x 125%). 4. Results The Area Under the ROC Curve ver the 2007-2010 paired sample specific t the labr prductivity 1 (based n sales) was f 0.539, which excludes the rati as a pssible bankruptcy predictr. The area under the ROC Curve ver the 2007-2010 paired sample specific t the labr prductivity 2 (based n grss prfits) was f 0.665, which can be evaluated as relatively pr, but valid classificatin accuracy (Tazhibi, Bashardst and Ahmadi, 2011). Under these circumstances, the rati based n grss prfits was submitted t additinal tests. The AUC was determined fr each f the 4 yearly paired samples. The AUC remains ver 0.6 fr each yearly sample (figure 1), which cnfirms the classificatin capability f the rati. Based n the crdinating pints f the ROC Curve fr 2010, an ptimal cut-ff value was determined (labr prductivity = -6055 lei). By classifying all the cmpanies frm the 2010 paired sample that registered labr prductivities lwer than -6055 as bankrupt and all the cmpanies frm the 2010 paired sample that registered labr prductivities higher than -6055 as nn-bankrupt, the general classificatin accuracy wuld be f 64.1%. Thus, the in-sample general accuracy verlaps the 62.5% benchmark. Out f sample accuracy tests were perfrmed ver the 2007-2009 paired samples. The ptimal cut-value fr 2010 was used. The general accuracy maintained its level fr the 2009 sample (64.2%), but decreased t 59.0% fr 2008 and t 58.3% fr 2007. The ut-f-sample general accuracy fr the entire 2007-2009 sample was f 61.8%. The variatins f the general accuracy registered in 2008 and 2007 are mstly generated by variatins f the cut-ff value (and less by the reductin f intrinsic classificatin capabilities f the labr prductivity). The general accuracy levels crrespndent t the ptimal cutff values fr the 4 yearly paired samples are reflected in figure 2. The general accuracy fr the entire sample f 1424 cmpanies was f 63.2%. 5. Cnclusins The Area Under the ROC Curve fr the entire paired sample shws that the labr prductivity based n sales is nt a useful classifier. Instead, the value f the AUC suggests that the labr prductivity based n grss prfits can be used a tl fr the assessment f the bankruptcy risk. This cnclusin is sustained by a general classificatin accuracy f 63.2% ver the entire paired sample f 1424 cmpanies. Cmmnly used in this field, the paired sample was useful in evaluating the ptential f the ratis. Nevertheless, as the structure f bth the basesample and the test-sample are significantly different frm the structure f the target ppulatin, an ptimal cut-ff value fr the entire ppulatin cannt be determined. The research prves the ptential f the labr prductivity rati in the predictin f bankruptcy and underlines the need fr determining an ptimal cut-ff value thrugh research ver the entire ppulatin (r a sample with the same structure). 30

6. References [1] Brîndescu Olariu, D. (2014a). The ptential f the equity wrking capital in the predictin f bankruptcy, Management Intercultural, XVI (31), 2014, pp. 25-32. [2] Brîndescu Olariu, D. (2014b). The crrelatin between the autnmy rati and the return n equity. Management Intercultural, XVI (31), 2014, pp. 407-414. [3] Chung, K., Tan, S., Hldswrth, D. (2008). Inslvency predictin mdel using multivariate discriminant analysis and artificila neural netwrk fr the finance industry in New Zealand. Internatinal jurnal f business and management, 39 (1), pp.19-29. [4] Dima, B., Mldvan, N., Lbnţ, O., Niclescu, C. (2011). Financial assets valuatin and issuers financial ratis. Prceedings f the Internatinal Cnference EBES, pp. 533-539. [5] van Erkel, A., Pattynama, P. (1998). Receiver perating characteristic (ROC) ana lysis: Basic principles and applicatins in radilgy, Eurpean Jurnal f Radilgy, 27 (2), pp. 88-94. [6] Faragei, D, Reiser, B (2002). Estimatin f the area under the ROC curve. Statistics in medicine, 21, pp. 3093-3106. [7] Hanley, J.A., McNeil, B.J. (1982). The meaning and use f the area under a receiver perating characteristic (ROC) curve. Radilgy, 143 (1), pp.29-36. [8] Mldvan, N., Lbnț, O., Niclescu, C., (2013) Empirical Study Regarding the Determining Factrs f the Rmanian Cmpanies Cmpetitiveness. Analele Universităţii din Oradea, Seria Ştiinţe Ecnmice, 1 (1), pp. 272-281. [9] Skalska, H., Freylich, V. (2006). Web - Btstrap Estimate f Area Under ROC Curve. Australian Jurnal f Statistics, 35 (2&3), pp. 325-330. [10] Ștefea, P., Circa, C., 2006. Reflecting Perfrmance Cmprehensive Incme. Accunting and Management Infrmatin Systems - Supplement/2006, Editura ASE, Bucuresti, pp. 214-225. [11] Tazhibi, M, Bashardst N, Ahmadi, M (2011). Kernel Smthing Fr ROC Curve And Estimatin Fr Thyrid Stimulating Hrmne. Internatinal Jurnal f Public Health Research, Special Issue 2011, pp. 239-242. 31

Figures and tables: Area Under the ROC Curve - labr prductivity 2 0.7 0.686 0.68 0.672 0.66 0.64 0.62 0.6 0.616 0.624 0.58 2007 2008 2009 2010 Figure 1. Area Under the ROC Curve ver a paired sample - labr prductivity 2 65.5% 65.0% 64.5% 64.0% 63.5% 63.0% 62.5% 62.0% 61.5% 61.0% 60.5% 60.0% General accuracy with ptimal cut-ff values fr each year 64.8% 64.1% 63.3% 61.7% 2007 2008 2009 2010 Figure 2. General accuracy with ptimal cut-ff values fr each year 32