195 twhee edsi ft fi emrae tnec et hien fdoilsl colwo si ne dg lroagt iint gms obdeet lw(eHeynpnoet hweas insd2i)n: c u m b e n t C R A s a t i s s u a n c e , Higher by Newijt = α 0 + α1 Creditor Friendliness Score s(i) + Tranche, Issuer and Market Controlsijt + ϵijt The dependent variable Higher by New is when a tranche received a more optimistic rating by a new CRA at issuance compared with the incumbent. DBRS and KBRA are representatives of new CRAs and Moody’s, S&P, and Fitch as incumbent ones. The independent variable is the Creditor Friendliness Score and all controls correspond to those of Equation (5.1). Fa vi ne ar al lgy,e wc ree ldoi ot kr aat ti ntgh eo fi ma RpMa cBt So tf rcarnesdaict ot iro np r(oHt ye pc toi ot hne os ifsU3S) . sWt aet euss eo no rtdhien as ri zyel eaansdt squares (OLS) regression models with Log Transaction Value as the dependent variable and the Creditor Friendliness Score as the independent variable, Equation (5.3). The model is specified as follows: Log Transaction Valueijt = β 0 + β1 Creditor Friendliness Score s(i) + Tranche, Issuer and Market Controlsijt + εijt In the OLS regressions, Equation (5.3), we include all controls60 similar to those of Equations (5.1) and (5.2) and we additionally add Log GDP and the Log House Price per state. We do so to control for the fact that the average house price and GdeDfPiniendainstSaetcetimonig5h.t influence the size of a RMBS transaction. All variables are 60incNloutdeetdhaast iancEoqnutraotilofnac(t5o.r3)inwtehiussme LoodgelT. ransaction Value as our dependent variable. This variable is therefore not Chapter 5 - The Impact of Creditor Protection
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