163 ap ol sa irtgi vee CcRoAe f ifsi c ui ennrte liantde idc attoe st hteh as tmtahl el CsRmAa’ sl l rCaRt iAn gt isgthatnednasr di tss, ar antdi nag ssi tganni df i ac ar dnst with a higher market share of the large CRA.50 We start by looking at the rating standards of DBRS in columns (1) to (4) of Panel A. Column (1) shows a negative significant coefficient for MS Moody’s by Frequency, and this effect is also economically significant, as shown in column (2) which present the economic magnitude of the coefficient estimates. 51 This icnodr ri ceastpeos n dt hs a tt o aa no nuep- sgtraanddea rodf 0d. e9v4i ant iootnc h i ni nc r eDaBsRe S ’i nr aMt i nogosd. yI’ sn t emr ea sr kt ientg lsyh, awr ee find no significant result for S&P’s market share in column (3). This suggests tf rhoamt DMBoRoSd yl o’ so, sbeunts ni tost rf raot imn gS &s tPa. nWd aer da rse ma losroe i wn the er ens ti te df aicne st hme oc roen tcrooml vpaertiiat ibol ne Number of Ratings as it indicates whether DBRS adjust its rating standards to a greater extent when dealing with dual or triple rated tranches, compared to a single DBRS rating. In columns (1) and (2) we observe a negative coefficient for Number of Ratings, indicating that a one-standard deviation increase in the number of ratings corresponds to an upgrade of a 0.76 notch in DBRS’ rating. We find similar results in columns (3) and (4). Hence, DBRS is more likely to provide better ratings when a tranche also received a rating from another CRA. Ns teaxntd, awred sm, or ev pe ot or t tehde isna mc opl ul emonf sa l(l 5K)BtRo A(-8r )a tiend Pt ar annecl hAe. s I tnot earneasltyi zneg lKy,BwR Ae ’ sf i rnadt i nn og significant results in columns (5) to (8), suggesting that the market share of large CRAs and Number of Ratings is unrelated to KBRA’s rating standards. 50 In other tests we have repeated the regression models in Tables 4.6 and 4.7 with our other market share manedasfiunrdess:imMiSlaDr BreRsSulbtys. Balance, MS KBRA by Balance, MS Small CRAs by Balance, and MS Small CRA by Tranche, 51t o Tuhnedceores ft fai nc ide nt ht ee set icmo na ot ems iicn saing noirf di cearnecde l. oTghi te mr eof odreel , sihno lwi nteh ewui tnhi tAs lopf (t 2h 0e 1l a3t)e, nwt ev aersi at ibml ea, tme at hk ei nagviet rraagt eh ecrhda inf fgi ec ui lnt ratings that would results from a change in the relevant explanatory variable. The economic magnitude is calculated as follows: the coefficient of the explanatory variable, for example Tranche Count, is multiplied by its standard deviation and divided by the average rating notch length (measured in terms of latent variables). For a dummy variable, such as Top Ten Issuer, this means that the coefficient is only divided by the rating notch length. Chapter 4 - Intensified Competition and the Impact on Credit Ratings
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