206 5.6 Results Idni stchl ioss seedc at inodn , own et he xe adme ianl es itzhee oi mf RpMa cBt So ft rcarne sdai tcot iropnrso, tbeoc tt hi o ant oi sns tuhaenccree. dI ni t sr ea ct itni ogns 5p .r6o. t1e, c wt i oensot af rUt Sbsyt aat ne sa’l ymz oi nrgt g at hgee leaxwt esni tn ttoh ewi rhci rcehd iCt RrAa tsi ncgo. nWs ied es er etkh teo carneadliyt zoer icfocnrsei dd ietroerdpar mo toe nc tgi sotndiimf f epraecnt st Ct hReAcsr. eI dn i ts ercattiionng 5a .n6d. 2w, wh ee t ahne ar l tyhzies iifs tchoentswi sot ennet wl y CRAs are more likely to inflate its credit rating, compared to the incumbent three, w5 . 6h .e3n, wt heee xt raamn ci nhee i fi sc ri se sdui teodr ipnr oat emc toi roen corfeUd Si t sotra- tf er ise’ nmdol yr t sgtaagt ee . l aFwi nsahl lays, iann si me cpt iaocnt on the deal size of RMBS. Table 5.3 provides the results for Equation (5.1), the Credit Rating is the dependent variable and the Creditor Friendliness Score the independent variable. Imne aTsaubrl ee f5o. r4 ,c rweed i tr erpaet iantg t wh ei t ha ntahley scirse doift Traabt ilneg 5o. 3f ebauc th rCeRpAl a cs ee poaur ar t ecloym: b i n e d DBRS, Moody’s, KBRA, S&P, and Fitch. We do so to analyze whether CRAs use a different aNpepx rt ,owa ceh t ews th tehne ci mo npsai dc te roifncgr ecdr iet do irt oprr-of rt ei ecnt idolni noens st hi en rtaht ei ni rg dc ri fef de ri te nr ca et i nb ge t w( He1e )n. new and incumbent CRA, where Higher by New is the dependent variable and the Creditor Friendliness Score the independent variable (H2). These results are rEeqpuoarttieodn i(n5.T3a)binleT5a.b5lean5d.6,atrheebased on Equation (5.2). We report the results of Log Transaction Value is the dependent variables, and the Creditor Friendliness Score is the primary independent variable (H3). In Table 5.7, we provide several robustness analyses to all our models. 5.6.1 Creditor rights and credit ratings The results of the ordered logit regressions with the combined credit rating as
RkJQdWJsaXNoZXIy MTk4NDMw