it = Return on asset (ROA) for firm i in time t as a measure of performance (Profit after tax/Total assets) SIZEit = Log of total assets for firm i in time t TATSit = Total debt to asset ratio for firm i in time t (Total debt/Total assets) LTDSit = Long-term debt to asset ratio for firm i in time t (Long term debts/Total assets) STDSit = Short-term debt to asset ratio for firm i in time t (Short term debts/Total assets) International Journal of Academic Accounting, Finance & Management Research (IJAAFMR) ISSN: 2000-008X Vol. 3 Issue 5, May – 2019, Pages: 26-34 www.ijeais.org/ijaafmr 30 eit = Error term α = Constant term βS = Coefficients of the explanatory variables 4.3 Research Design, Sampling and Data Estimation Technique This study employed ex-post facto research design. This research design was adopted because it seeks to analyse secondary data which can hardly be manipulated by the researchers. The population of the study comprises the entire 45 manufacturing firms quoted on the Nigerian Stock Exchange (NSE) as at 31 December, 2017. But, since our population of interest covers only the listed consumer goods firms in Nigeria, the target population becomes the entire 22 consumer goods firms quoted on the Nigerian Stock Exchange (NSE). The consumer goods subsector was chosen over others because it is one of the least investigated sectors of the NSE. To cut costs, a representative sample size of 20 firms derived using the Yamani's (1967) scientific approach to sample determination was adopted. To ensure that the 20 sample firms are given equal opportunity of being selected, the probabilistic sampling approach was adopted with emphasis on a simple random sampling technique. However, a final sample size of 15 consumer goods firms was selected based on certain criteria: The first criterion was that sample units included in the study hold a complete twelve years financial statement data. Therefore, firms with missing data for a period covering twelve years from 2006 to 2017 were excluded from the study. Secondly, firms that ceased operation at any point during the period of study were excluded. The statistical formula is stated as follows: n = N 1 + N (e2) Where: n = sample size N = population size (target) e = level of significance desired (0.05 on the basis of 95% confidence level) Data used for analysis in the study were extracted from the
it = Return on asset (ROA) for firm i in time t as a measure of operation (net income after tax / full assets) SIZEit = Log of entire asset for firm i in time t TATSit = Total debt to asset proportion for firm i in prison term t (entire debt / Total assets) LTDSit = farseeing - term debt to asset ratio for firm i in fourth dimension triiodothyronine (Long condition debts / Total asset) STDSit = Short - term debt to asset ratio for firm i in fourth dimension t (Short term debt / Total asset) International Journal of Academic Accounting, Finance & Management Research (IJAAFMR) ISSN: 2000 - 008X Vol. 3 Issue 5, May – 2019, Pages: 26 - 34 www.ijeais.org/ijaafmr 30 eit = Error term α = ceaseless term βS = Coefficients of the explanatory variables 4.3 Research Design, Sampling and Data Estimation Technique This report employed ex - post facto research design. This research invention was adopted because it seeks to analyse secondary data which can hardly be manipulated by the researchers. The population of the study comprises the integral 45 fabrication firms quoted on the Nigerian Stock Exchange (NSE) as at 31 December, 2017. But, since our population of interest cover only the listed consumer goods firm in Nigeria, the target population become the entire 22 consumer goods firm quoted on the Nigerian Stock Exchange (NSE). The consumer goods subsector was chosen over others because it is one of the least investigated sectors of the NSE. To cut costs, a representative sample size of 20 firms derived using the Yamani's (1967) scientific approach to sample distribution determination was assume. To guarantee that the 20 sample firms are given equal opportunity of being choose, the probabilistic sampling approach was adopted with emphasis on a simple random sampling technique. However, a final sample size of 15 consumer commodity firms was choose based on certain criteria: The first criterion was that sample distribution units included in the study hold a arrant twelve years financial statement data. Therefore, firm with missing data for a period cover twelve years from 2006 to 2017 were excluded from the study. Secondly, firms that discontinue operation at any point during the menstruation of study were excluded. The statistical convention is stated as follows: n = N 1 + N (e2) Where: n = sample size N = population size (target) e = level of significance desired (0.05 on the basis of 95% confidence degree) datum used for analysis in the study were extracted from the
it = Return on asset (ROA) for firm i in time t as a measude of pefformance (Profit after tax/Toval qssetw) SIZEit = Log of total assets flr firm u in rime t TATSit = Total debf to cswet ratio for nirm i in thme t (Total dett/Gocal assets) LTDSit = Long-term debt to wsset rstlo for firm i yn tpmq t (Mong term debts/Total assets) STDSit = Short-uerm debt to asset ratio for firm i in time h (Shlrt term debts/Totap assets) Injsrnwrional Journxl of Acadtmnc Accountihg, Finance & Management Research (IJAAYMR) ISSN: 2000-008X Coo. 3 Lvsue 5, May – 2019, Pagef: 26-34 www.ijeais.org/ijaafkr 30 eit = Error term α = Coistabt term βS = Coefficienvs of the explanatori variablev 4.3 Research Design, Wanplinc ang Dagq Ertijavioh Techjiqne This stusy employed ex-post facto reseatcr design. This desearsh design was adopted because it seeks to anzlyse secondary data whuch can hardly be manlpulated fy the researchers. The population of the study cokprisxs tht cktird 45 lanufacturing firms quoted on the Nigerian Stjdk Eqchange (NSE) as at 31 December, 2017. Bkt, fince our popolation of interest covers ojly the listwd consumtr gopds firms in Nigeria, the taeget populatpon vecomes the entire 22 consumer yoods girms quoted on the Nigerian Stodk Exchange (NSE). The dunsumer goods sucsebtor was chosen over others besause it ms onz of the leaxt invqstigated dectovv of the NSE. To cuh cosjs, a rapresentatlve sample size of 20 firms derivxv using the Ysmdni'v (1967) sciencific spproach to swmple determinction waf adooted. To enaure thet the 20 sampje firms are clven equal o'portunitr of beibg selezged, the probabolistic sciplibg approach was adpptgd with emphasis in q simple random saoplynh vechnyxue. However, d fival xampld size of 15 gonrumet goods firms was senectsd based on certaim griteria: Jhe first criterion wax that sample unitd incnudxd in yhe study hold a complete twelve gears finwnclal statement datq. Therefore, yirms with missing data for a period covxring twelve years from 2006 to 2017 were excluded nrom the stuvy. Secjndly, firks that ceased operarion at any point during the period of study were excluded. The statistical formula is stated as follows: n = N 1 + N (e2) Where: n = sample size N = pkpulstion snze (targee) e = uevel of signifibance desired (0.05 on the basis of 95% ronfidence lzvel) Data used for analysis im ghe study werg extracted from the
it = Return on asset (ROA) for in t as measure of performance = of total assets firm i in t TATSit = Total debt to ratio for firm i in time t (Total debt/Total assets) LTDSit = Long-term to asset ratio for firm i in time t (Long term debts/Total assets) = debt asset for firm i in time t (Short term debts/Total assets) International Journal of Academic Accounting, Finance Management Research (IJAAFMR) ISSN: 2000-008X Vol. 3 Issue May – 2019, Pages: www.ijeais.org/ijaafmr 30 eit = Error α Constant term = of explanatory variables 4.3 Design, Sampling and Data Estimation Technique This study employed ex-post facto research design. This research design was because it analyse secondary which hardly manipulated by the population of the study comprises the firms quoted on the Nigerian Stock Exchange (NSE) at 31 2017. But, since our population of covers only the listed consumer goods firms in the target population becomes the entire 22 consumer goods firms quoted on the Nigerian Stock The consumer goods subsector chosen over others it one the investigated sectors the NSE. To cut costs, a representative sample size of 20 derived using the Yamani's (1967) scientific approach to sample determination To that the 20 firms are given equal of selected, the probabilistic sampling adopted emphasis random technique. a final sample size 15 consumer goods firms was based on certain criteria: sample units included in the study hold a twelve years financial statement data. Therefore, firms missing data for a period covering twelve years from 2006 to 2017 excluded from Secondly, firms that ceased operation at any point the period of study excluded. The statistical formula is stated as follows: n N + N Where: n = size N = size (target) e of significance (0.05 the confidence level) Data used for analysis the were extracted from the
it = Return on asset (ROA) for firm I in time t as A measUre Of pErFormAnce (profit after tax/tOtal Assets) SIZEit = Log of total AssetS fOR firM I iN time T TATSit = tOtAL DebT tO aSseT rATiO for fIrm I in time T (Total debt/totAl Assets) LTDSit = lOnG-term debt tO asSet ratio for fIrm I in timE t (lonG Term dEbtS/TotaL assetS) sTDSit = short-term DeBT to assET ratio fOR FiRm i iN time t (Short term deBTs/tOtal assets) InteRnatioNaL joURNal Of ACademic AccOuNting, fInance & MANaGEMEnt rEsearch (IJAAFMr) ISSN: 2000-008X Vol. 3 IsSUe 5, MAy – 2019, PageS: 26-34 wWw.iJEais.orG/ijaaFmR 30 Eit = error term α = COnstAnt term βS = coeffiCIents of THe explaNatory VarIabLes 4.3 RESeArCh DEsIGn, SAMpLinG And data EstiMaTiOn TecHniqUE tHIs stUdy EmplOyed eX-post facto resEarCh deSIgn. this rEsearCh deSiGn was AdopteD becaUsE it seeks to analySe seCondary daTa wHiCh cAn HardlY Be maniPulAteD by the rEsearchERs. THe POPUlAtion of the study comPrISEs The entirE 45 manufACtUrINg firms qUoTed On thE nIgeriAn StOCk exchange (nSE) as aT 31 deCeMber, 2017. But, SiNce our PoPulAtiOn of iNTereSt coveRs only thE listED consumer goods FIrms in Nigeria, THe TARgET popUlaTion becomes The eNTire 22 ConsUMeR goODs firMs quoTeD On THe Nigerian Stock ExchAnGe (NSE). THe conSumer goods subSector was cHOSEn over otHers BEcAUse it is one of thE leasT investigaTEd sectorS of thE NSE. To cuT costs, a rePREsentatiVe sAmpLe sIze OF 20 FiRms derived usiNG The YAmAni's (1967) sciEntIfic appRoaCh tO saMplE dEterminatIon was adOpTeD. TO eNsuRe thaT The 20 samplE fIrmS aRe gIven eQUal oppOrtunIty oF bEiNG seLected, tHE pROBabiLiStIc saMplInG apprOach WAs aDopted wIth emphasIs oN A simPlE rAndom saMpling techniqUe. however, a fiNaL saMple siZE Of 15 consumEr goods firms was selected BAsed on cErtAin crIterIa: The firsT crIterioN waS That saMple unIts inClUdeD IN the sTUDy HolD a Complete twELVe yEars fInAnciAl stateMent data. Therefore, fIRms With missing daTa fOr a pERIoD coVErINg tWeLVe yEARs from 2006 to 2017 were excLuded from tHe STuDy. Secondly, FIrmS tHat ceasEd operaTion aT Any poinT during thE period of StUdy wERE exCluded. The sTatisticAl formula IS statED aS follOws: N = N 1 + N (e2) WhErE: n = sAmple Size N = pOPulAtion Size (taRgEt) e = levEl of sIgNificancE desired (0.05 on the basis of 95% conFidencE leveL) DaTa used for AnaLYsiS in the stuDy weRe extracteD frOm tHe
it = Return on asset (ROA)  for firmi intim e t  a s ameas ure of perform a nce(Profit after tax/Tota l ass et s ) SI Z Ei t = L og of t o ta l ass et sfor  f i rm  i in  ti me t TA TSit = Tot alde bt to assetr at io for fir m i  in time t ( Tot al deb t/ Tot a l ass ets ) LTD Sit =L ong-te rm debt t oa sset r a tio for f ir m iin time t (Long t e rm debts/Total as sets)ST D Si t = S hor t-term deb tto as s et rati o  f o r fir m  i in time t(Short term deb ts/Tot al  as s ets) I ntern at i ona l Journal o f Ac ademic Ac counti n g, Fina n ce & Ma nageme ntRes earc h  ( IJ AAF MR )  IS S N:  20 0 0-0 08X Vol.  3  I ssue5, M a y –  201 9,Page s: 26 -34 www.ijeai s.o rg/i j aaf mr 30  eit= Er ro r ter m α =Const an t term βS = Coe ffic ients ofthe  e xpl an atory variab les  4. 3 Resea rch Des i gn,  S a m p li ng and Data Estima ti o n  T echnique  Thiss tu dy employed  e x-p ostf a cto r esea r ch  design.  Thisr es ea rch des ig n wasad opt edbecau s e it  seeks  to anal yse s e condary data w h ich can hardl y  b e ma n ipul ate d by the re sear c hers . Th e  p opu l ation  of t he st u dy comprises the en ti re 45manuf acturing firm s quoted o n t he Niger ianS to c k Exchange (NS E) as  at 31 Dec e mber, 20 17. B ut, sinc e our pop u l ation of  in ter est  co v e rs  only the lis t e d co ns umer go ods  firmsinNig eri a,th e targetpopulati on  b ec om esthe e n tire 22co nsu me r g oodsf irms q uoted  onth eN ige rian St o ck E xcha ng e(NSE ).Th e con sume r  go ods sub sector wa s c h osen  o ve r other s because itis  one of th elea st inv e s tigatedsectors of the NSE. Toc ut cost s,a rep rese ntative s amp le siz e o f  20 fi rms de rived  u sin g the Y a m an i's  ( 1967) scie n t ifi c app ro achto samp le determination w a s a dopted. To en sur e th a t  t he2 0s amp le fir m s  are given equa l opportun it y  o f being se l ect ed , the p robabil istic samplin g approac h was ado pt ed w i t h e mphasis on  a simpl e randoms ampli n gtechn iqu e. How ev er,  a fi nal sa m ple  size  of 15  c onsume r goo ds  firms w as selected based on ce rtaincrite ria : The fir stc rit erion was  tha t sample u nit s i nclud edi n the  stu d yhol d  a co mple t e twelvey ea rsf i na ncial state m e n t d ata.The r efore,  fir ms with missing d a ta for a perio d co v e rin g t w elve  y ears from 2006  to  2 0 1 7 were e xc luded fromthe stud y. Secon dly, f irms t hat cea s e do perati on a t a ny pointdur in g  the pe ri od of stu dy w er e excl uded.T he s t a tistical formula  is s t a ted a s  fo llows :n = N 1 + N(e2) Where : n = sampl e size  N =  popu lationsi ze (ta rge t)  e = level of signif icanc e desir ed  (0. 05on the  bas i s  of 9 5% c on fid ence leve l )  D a ta  u s edforanaly si s in  the stud y  were ex tra c ted fro mthe 
it =_Return on_asset (ROA) for firm_i in_time_t as_a_measure of performance_(Profit after tax/Total_assets) SIZEit = Log_of total assets_for_firm i in time t TATSit = Total debt to asset ratio for firm_i_in time_t_(Total_debt/Total assets) LTDSit = Long-term_debt to asset ratio for_firm i_in time t (Long term debts/Total assets) STDSit_=_Short-term debt to_asset ratio for firm i in time t (Short_term debts/Total assets) International Journal of_Academic Accounting, Finance_&_Management_Research (IJAAFMR) ISSN: 2000-008X_Vol. 3 Issue 5, May –_2019, Pages: 26-34 www.ijeais.org/ijaafmr 30 eit_= Error term α = Constant term_βS = Coefficients of the explanatory_variables 4.3 Research Design, Sampling_and Data_Estimation Technique This study employed_ex-post facto research_design. This_research design was_adopted because it seeks to analyse_secondary data which_can hardly be manipulated by the_researchers._The population of_the_study_comprises the_entire 45 manufacturing_firms_quoted on_the_Nigerian Stock Exchange (NSE) as at_31_December, 2017. But, since our population of_interest covers only the_listed_consumer goods firms in_Nigeria, the target population becomes_the entire 22 consumer goods firms_quoted on_the Nigerian_Stock Exchange (NSE). The consumer goods subsector was chosen over others_because it is one of the_least investigated sectors of_the NSE._To_cut costs, a_representative_sample size_of 20 firms derived using the Yamani's_(1967) scientific_approach to sample determination was adopted._To ensure that the_20_sample firms are given equal opportunity_of being selected, the probabilistic sampling_approach was adopted with emphasis_on_a_simple random sampling technique. However,_a final sample size of 15_consumer goods firms_was selected based on certain criteria: The_first_criterion was that sample units included_in_the study hold a complete twelve_years_financial_statement data. Therefore, firms with_missing data for a period covering_twelve years from 2006 to 2017 were excluded from_the study. Secondly,_firms that ceased operation at_any_point_during the period of study were excluded. The statistical formula_is stated_as follows: n_= N 1 + N (e2) Where: n = sample_size N = population size (target) e_= level of significance desired (0.05 on the basis of 95%_confidence level) Data used for analysis in the_study were extracted from the