1 List of Mergers

# 
# files = paste0("C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/HMDA/Ultimate Panel Data/",as.character(2000:2016),".fst")
# 
# panel = lapply(files, read_fst, as.data.table = TRUE,columns=c("respondentid","agencycode","reportername","asofdate","parentname","parentidentifier","reporterhomecity","reporterhomestate","rssd"))
# panel <- do.call(rbind , panel)
# 
# panel[,asofdate:=as.integer(asofdate)]
# panel <- panel[!duplicated(panel[,c("respondentid","agencycode","asofdate")])]
# panel[,parentidentifier:=stri_trim(parentidentifier)]
# 
# panel[,rssd:=as.numeric(rssd)]
# 
# panel[,hmda_id:=paste0(agencycode,"-",respondentid)]
# 
# files <- NULL
# files  <- list.files(pattern="*.fst",path = "C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/HMDA/pre2004/OO_NP/",full.names = TRUE)
# files  <- c(files,list.files(pattern="*.fst",path = "C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/HMDA/pre2004/OO_RF/",full.names = TRUE))
# files  <- c(files,list.files(pattern="*.fst",path = "C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/HMDA/OO_NP/",full.names = TRUE))
# files  <- c(files,list.files(pattern="*.fst",path = "C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/HMDA/OO_RF/",full.names = TRUE))
# 
# hmda = lapply(files, read_fst, as.data.table = TRUE,
#               columns=c("asofdate","respondentid","agencycode","state","countycode","msa"))
# hmda <- do.call(rbind , hmda)
# hmda[,lender:=paste0(agencycode,"-",respondentid)]
# hmda[,countycode:=paste0(state,countycode)]
# 
# 
# cbsa_fips <- fread("C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/Crosswalk Files/cbsa_countyfips.csv")
# cbsa_fips[,fips:=ifelse(nchar(fips)==4,paste0("0",fips),paste0(fips))]
# 
# hmda <- merge(hmda,cbsa_fips,by.x="countycode",by.y="fips",all.x=T)
# hmda[,c("agencycode","respondentid"):=list(NULL)]
# 
# gc()
# 
# 
# 
# mergers <- list()
# 
# temp <- list(1,"BANK ONE - JPMORGAN CHASE 2004",
#              c("1-0000000008","1-0000007621","1-0000003106","1-0000011230","1-0000013655","1-0000013759","1-0000013914","1-0000014320","1-0000015184","1-0000018785","1-0000021969","1-0000023237","2-0000331647","3-0000002487"),
#              unique(c(unique(panel[parentidentifier %in% c("0000002370","0000000008","0001039502","0000852218","0001040795"),]$hmda_id),"2-0000852218","1-0000023160","2-0000043557","1-22-1092200","1-0000000008")),
#              2000,"JPMORGAN CHASE BANK, NA",2004)
# mergers[[1]] <- temp
# 
# temp <- list(2,"COUNTRYWIDE - BANK OF AMERIC 2009" ,c("1-0000024141","2-0001644643","2-0003267484","7-20-2241771","1-0000024141","4-0000018039"),c("1-0000013044"),
#              2005,"BANK OF AMERICA, N.A.",2009)
# mergers[[2]] <- temp
# 
# temp <- list(3,"FLEET NA - BANK OF AMERICA 2005",c("1-0000000200"),c("1-0000013044"),
#              2003,"BANK OF AMERICA, N.A.",2005)
# mergers[[3]] <- temp
# 
# temp <- list(4,"WACHOVIA BK NA - WELLS FARGO 2010", c("1-0000000001","1-0000022559","1-56-0811711"), panel[substr(reportername,1,7)=="WELLS F"]$hmda_id,
#              2005,"WELLS FARGO BANK, N.A.",2009)
# mergers[[4]] <- temp
# 
# temp <- list(5,"LASALLE BK - BANK OF AMERICA 2008",panel[substr(reportername,1,7)=="LASALLE" & asofdate<=2005]$hmda_id,c("1-0000013044"),
#              2005,"BANK OF AMERICA, N.A.",2008)
# mergers[[5]] <- temp
# 
# 
# temp <- list(6,"ABN AMRO MTG GROUP - CITI BANK 2007",c("1-36-3744610"),unique(panel[parentidentifier=="0001951350"]$hmda_id),
#              2004,"CITIMORTGAGE, INC.",2007)
# mergers[[6]] <- temp
# 
# temp <- list(7,"UNION PLANTERS BANK - REGIONS FINANCIAL CORP 2004",
#              c("1-0000013349"),
#              c("9-0000233031","2-0000233031"),
#              2002,c("REGIONS BANK"),2004)
# mergers[[7]] <- temp
# 
# temp <- list(8,"AmSouth Bancorporation - REGIONS FINANCIAL CORP 2006",
#              c("2-0000245333"),
#              c("9-0000233031","2-0000233031"),
#              2004,c("REGIONS BANK"),2006)
# mergers[[8]] <- temp
# 
# 
# temp <- list(9,"Washington Mutual - JPMORGAN CHASE 2008",
#              c("4-0000008551","4-0000011905"),
#              unique(c(unique(panel[parentidentifier %in% c("0000002370","0000000008","0001039502","0000852218","0001040795"),]$hmda_id),"2-0000852218","1-0000023160","2-0000043557","1-22-1092200","1-0000000008")),
#              2005,"JPMORGAN CHASE BANK, NA",
#              2008)
# mergers[[9]] <- temp
# 
# 
# 
# ## target operated in 5 msas; small share.
# temp <- list(10,"Greater Bay Bank - Wells Fargo 2007",
#              c("1-0000024489"),
#              panel[substr(reportername,1,7)=="WELLS F"]$hmda_id,
#              2005,c("WELLS FARGO BANK, N.A."),2007)
# mergers[[10]] <- temp
# 
# 
# temp <- list(11,"MBNA NA - BANK OF AMERICA 2005",c("1-0000024095"),c("1-0000013044"),
#              2003,"BANK OF AMERICA, N.A.",2005)
# mergers[[11]] <- temp
# 
# temp <- list(12,"Merrill Lynch - BANK OF AMERICA 2008",c("2-0000421203","7-13-3403204","3-13-3098068","3-13-3399559","3-0000027374","3-0000091363","3-13-3399559","4-0000014460","3-68-0518519","4-0000014460", "4-0133098068"),c("1-0000013044"),
#              2005,"BANK OF AMERICA, N.A.",2008)
# mergers[[12]] <- temp
# 
# 
# temp <- list(13,"FIRST INTERSTATE BK CA  - Wells Fargo 1996",c("2-0000669667"),panel[substr(reportername,1,7)=="WELLS F"]$hmda_id,1994,"WELLS FARGO BANK, N.A.",1996)
# mergers[[13]] <- temp
# 
# temp <- list(14,"PACIFIC NORTHWEST  - Wells Fargo 2004",c("3-0000030887","3-0000027346"),panel[substr(reportername,1,7)=="WELLS F"]$hmda_id,
#              2002,"WELLS FARGO BANK, N.A.",2004)
# mergers[[14]] <- temp
# 
# 
# temp <- list(15,"MERIDIAN MOME MORTGAGE, LP  - Wells Fargo 2010",c("1-74-3082948"),panel[substr(reportername,1,7)=="WELLS F"]$hmda_id,
#              2005,"WELLS FARGO BANK, N.A.",2010)
# mergers[[15]] <- temp
# 
# 
# temp <- list(16,"The Leader Mtg Co - US Bank 2004",
#              c("7-3814209995"),
#              panel[substr(reportername,1,5)=="U S B"]$hmda_id,
#              2002,c("U.S. BANK N.A."),2004)
# mergers[[16]] <- temp
# 
# temp <- list(17,"PFF BANK & TRUST  - US Bank 2008",
#              c("4-0000001405"),
#              panel[substr(reportername,1,5)=="U S B"]$hmda_id,
#              2005,c("U.S. BANK N.A."),2008)
# mergers[[17]] <- temp
# 
# 
# temp <- list(18,"DOWNEY SAVINGS AND LOAN ASSOCIATION, F.A.   - US Bank 2008",
#              c("4-0000006189"),
#              panel[substr(reportername,1,5)=="U S B"]$hmda_id,
#              2005,c("U.S. BANK N.A."),2008)
# mergers[[18]] <- temp
# 
# 
# cbsas <- unique(hmda$cbsa)
# yrs <- 2000:2016
# acqbanks <- NULL
# for(i in 1:length(mergers)) {
#   acqbanks <- c(acqbanks,mergers[[i]][6][[1]])
# }
# acqbanks <- c(unique(acqbanks),"other")
# 
# cbsas1 <- merge(cbsas,yrs)
# cbsas2 <- merge(cbsas,acqbanks)
# 
# cbsas <- merge(cbsas1,cbsas2,by="x")
# names(cbsas) <- c("cbsa","acyr","bank")
# cbsas <- data.table(cbsas)
# 
# cbsas[,bank:=as.character(bank)]
# cbsas[,acqbank:=0]
# cbsas[,pred_share:=0]
# cbsas[,suc_share:=0]
# cbsas[,nationwide_msacq:=0]
# 
# 
# cbsa_bnk <- NULL
# lender_bank <- NULL
# sumtable <- NULL
# 
# for(i in 1:length(mergers)) {
#   # print(i)
#   mid=mergers[[i]][1][[1]]
#   mname=mergers[[i]][2][[1]]
#   pred_hmda_id=mergers[[i]][3][[1]]
#   suc_hmda_id=mergers[[i]][4][[1]]
#   yr=mergers[[i]][5][[1]]
#   acname = mergers[[i]][6][[1]]
#   acyr = mergers[[i]][7][[1]]
# 
#   temp <- hmda[asofdate == yr ]
#   temp[,pred:=ifelse(lender %in% pred_hmda_id,1,0)]
#   cw <- temp[,.(pred_share=mean(pred)),by=.(cbsa)]
#   cw[,nationwide_msacq:=mean(temp$pred,na.rm=T)]
# 
#   temp1 <- hmda[asofdate == (acyr-1) ]
#   temp1[,suc:=ifelse(lender %in% suc_hmda_id,1,0)]
#   cw1 <- temp1[,.(suc_share=mean(suc)),by=.(cbsa)]
# 
#   cw <- merge(cw,cw1,by="cbsa",all.x=T)
#   cw <- cw[!is.na(cbsa)]
#   cw[is.na(cw)] <- 0
# 
#   cw[,joint_share:=pred_share+suc_share]
#   cw[,bank:=acname]
#   cw[,acyr:=acyr]
# 
#   cw[,c("joint_share"):=list(NULL)]
#   cbsa_bnk <- rbind(cbsa_bnk,cw)
# }
# 
# 
# cbsa_bnk[,acqbank:=1]
# 
# 
# cbsa_bnk <- rbind(cbsa_bnk,cbsas)
# cbsa_bnk <- cbsa_bnk[!duplicated(cbsa_bnk[,c("cbsa","acyr","bank")])]
# cbsa_bnk <- cbsa_bnk[!is.na(cbsa)]
# 
# temp <- cbsa_bnk
# 
# cbsa_bnk_1 <- cbsa_bnk[,c("cbsa","pred_share","suc_share","bank","acyr")]
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_1","suc_share_1","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_2","suc_share_2","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_3","suc_share_3","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_4","suc_share_4","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_5","suc_share_5","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_6","suc_share_6","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_7","suc_share_7","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_8","suc_share_8","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# names(cbsa_bnk_1) <- c("cbsa","pred_share_9","suc_share_9","bank","acyr")
# cbsa_bnk_1[,acyr:=acyr+1]
# cbsa_bnk <- merge(cbsa_bnk,cbsa_bnk_1,by=c("cbsa","bank","acyr"),all.x = T)
# 
# cbsa_bnk[,pred_share_1:=ifelse(is.na(pred_share_1),0,pred_share_1)]
# cbsa_bnk[,pred_share_2:=ifelse(is.na(pred_share_2),0,pred_share_2)]
# cbsa_bnk[,pred_share_3:=ifelse(is.na(pred_share_3),0,pred_share_3)]
# cbsa_bnk[,pred_share_4:=ifelse(is.na(pred_share_4),0,pred_share_4)]
# cbsa_bnk[,pred_share_5:=ifelse(is.na(pred_share_5),0,pred_share_5)]
# cbsa_bnk[,pred_share_6:=ifelse(is.na(pred_share_6),0,pred_share_6)]
# cbsa_bnk[,pred_share_7:=ifelse(is.na(pred_share_7),0,pred_share_7)]
# cbsa_bnk[,pred_share_8:=ifelse(is.na(pred_share_8),0,pred_share_8)]
# cbsa_bnk[,pred_share_9:=ifelse(is.na(pred_share_9),0,pred_share_9)]
# 
# cbsa_bnk[,msinc13:=pred_share_1+pred_share_2+pred_share_3+0.00001]
# cbsa_bnk[,msinc46:=pred_share_4+pred_share_5+pred_share_6+0.00001]
# cbsa_bnk[,msinc79:=pred_share_7+pred_share_8+pred_share_9+0.00001]
# cbsa_bnk[,suc_share:=suc_share_1]
# 
# 
# cbsa_bnk[,msinc13G:=ifelse(msinc13<=0.0001,"0. 0",
#                            ifelse(msinc13<0.01,"1. Less than 1pct",
#                            ifelse(msinc13<0.05,"2. 1 - 5pct",
#                                   ifelse(msinc13<0.1,"3. 5pct - 10pct", "4. More than 10pct"))))]
# 
# cbsa_bnk[,msinc46G:=ifelse(msinc46<=0.0001,"0. 0",
#                            ifelse(msinc46<0.01,"1. Less than 1pct",
#                            ifelse(msinc46<0.05,"2. 1 - 5pct",
#                                   ifelse(msinc46<0.1,"3. 5pct - 10pct", "4. More than 10pct"))))]
# 
# 
# cbsa_bnk[,msinc79G:=ifelse(msinc79<=0.0001,"0. 0",
#                            ifelse(msinc79<0.01,"1. Less than 1pct",
#                            ifelse(msinc79<0.05,"2. 1 - 5pct",
#                                   ifelse(msinc79<0.1,"3. 5pct - 10pct", "4. More than 10pct"))))]
# 
# cbsa_bnk[,msinc4plus:=msinc46+msinc79]
# 
# write_fst(cbsa_bnk,"C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Projects/Bank Mergers/Before June2023/data/cbsa_bnk_33.fst",compress = 100)
cbsa_bnk <- read_fst("C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Projects/Bank Mergers/Before June2023/data/cbsa_bnk_33.fst",as.data.table = T)
cbsa_bnk[,other_msinc13:=sum(msinc13,na.rm=T),by=.(cbsa,acyr)]
cbsa_bnk[,other_msinc46:=sum(msinc46,na.rm=T),by=.(cbsa,acyr)]
cbsa_bnk[,other_msinc13:=other_msinc13-msinc13]
cbsa_bnk[,other_msinc46:=other_msinc46-msinc46]
cbsa_bnk[,msinc13_dummy:=ifelse(msinc13>1e-05,1,0)]
cbsa_bnk[,yr_msa2:=paste(acyr,cbsa)]
cbsa_bnk[,msinc13_total:=sum(msinc13),by=yr_msa2]
cbsa_bnk[,msinc13_total:=ifelse(msinc13==1e-05,1e-05,msinc13_total)]
cbsa_bnk[,msinc13G:=ifelse(msinc13<=0.0001,"0. 0",
                           ifelse(msinc13<0.025,"1. 0 to 2.5pct",
                           ifelse(msinc13<0.05,"2. 2.5- 5pct","5. More than 5pct")))]
                                

cbsa_bnk[,msinc46G:=ifelse(msinc46<=0.0001,"0. 0",
                           ifelse(msinc46<0.025,"1.  0 to 2.5pct",
                           ifelse(msinc46<0.05,"2. 2.5- 5pct","5. More than 5pct")))]
freddie <- list.files(pattern="*.fst",path = "C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/Freddie/Acq",full.names = TRUE)
freddie = lapply(freddie, read_fst,as.data.table=T, columns = c("fico","dt_first_pi","cd_msa","ltv","dti","orig_upb","int_rt","prop_type","zipcode","id_loan","orig_loan_term","seller_name","loan_purpose","cltv","occpy_sts"))
freddie <- do.call(rbind , freddie)

freddie <- freddie[orig_loan_term==360 & prop_type=="SF" ]
freddie[,loanyr:=year(dt_first_pi)]
freddie[,msa:=cd_msa]
freddie[,primary_occ:=ifelse(occpy_sts=="P",1,0)]
freddie[,c("orig_loan_term","dt_first_pi","prop_type","cd_msa","occpy_sts"):=list(NULL)]
freddie[,seller_name:= ifelse(seller_name %in% c("JPMORGAN CHASE BANK, NA","JPMORGAN CHASE BANK, NATIONAL ASSOCIATION","CHASE MANHATTAN MORTGAGE CORPORATION","CHASE HOME FINANCE LLC","CHASE HOME FINANCE","CHASE HOME FINANCE, LLC","JPMORGAN CHASE BANK, NATIONAL ASSOCIATION","JPMORGAN CHASE BANK, N.A."),"JPMORGAN CHASE BANK, NA",seller_name)]
freddie[,seller_name:= ifelse(seller_name %in%  c("CITIMORTGAGE, INC.","ABN AMRO, NKA CITIMORTGAGE INC.","CITIMORTGAGE, INC."),"CITIMORTGAGE, INC.",seller_name)]
freddie[,seller_name:= ifelse(seller_name %in% c("WELLS FARGO HOME MORTGAGE, INC.","WELLS FARGO BANK, N.A."),"WELLS FARGO BANK, N.A.",seller_name)]

freddie[,bank:=seller_name]
freddie[,bank:=ifelse(bank %in% unique(cbsa_bnk$bank),bank,"other")]
freddie[,freddie:=1]
freddie[,newpurchase:=ifelse(loan_purpose=="P",1,0)]
freddie[,ltvorg:=ltv]
freddie[,ltv:=cltv]
fannie <- list.files(pattern="*.fst",path = "C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/Fannie/Acq",full.names = TRUE)
fannie = lapply(fannie, read_fst,as.data.table=T, columns = c("loan_identifier","seller_name","original_interest_rate","original_upb","original_loan_term","origination_date","original_ltv","original_dti","credit_score","property_type","property_state","zip_code","msa","loan_purpose","original_cltv","occupancy_type"))
fannie <- do.call(rbind , fannie)


fannie <- fannie[original_loan_term==360 & property_type=="SF" ]
fannie[,loanyr:=year(origination_date)]
fannie[,seller_name:= ifelse(seller_name %in% c("JPMORGAN CHASE BANK, NA","JPMORGAN CHASE BANK, NATIONAL ASSOCIATION","CHASE MANHATTAN MORTGAGE CORPORATION","CHASE HOME FINANCE LLC","CHASE HOME FINANCE","CHASE HOME FINANCE, LLC","JPMORGAN CHASE BANK, NATIONAL ASSOCIATION","JPMORGAN CHASE BANK, N.A."),"JPMORGAN CHASE BANK, NA",seller_name)]
fannie[,seller_name:= ifelse(seller_name %in%  c("CITIMORTGAGE, INC.","ABN AMRO, NKA CITIMORTGAGE INC.","CITIMORTGAGE, INC."),"CITIMORTGAGE, INC.",seller_name)]
fannie[,seller_name:= ifelse(seller_name %in% c("WELLS FARGO HOME MORTGAGE, INC.","WELLS FARGO BANK, N.A."),"WELLS FARGO BANK, N.A.",seller_name)]

fannie[,bank:=seller_name]
fannie[,bank:=ifelse(bank %in% unique(cbsa_bnk$bank),bank,"other")]
fannie[,freddie:=0]
fannie[,ltvorg:=original_ltv]
fannie[,primary_occ:=ifelse(occupancy_type=="P",1,0)]
setnames(fannie,"zip_code","zipcode")
setnames(fannie,"original_ltv","ltv")
setnames(fannie,"original_upb","orig_upb")
setnames(fannie,"original_interest_rate","int_rt")
setnames(fannie,"loan_identifier","id_loan")
setnames(fannie,"credit_score","fico")
setnames(fannie,"original_dti","dti")
setnames(fannie,"original_cltv","cltv")

fannie[,c("property_type","property_state","original_loan_term","origination_date","occupancy_type"):=list(NULL)]
fannie[,loan_purpose:=ifelse(loan_purpose=="R","N",loan_purpose)]

fannie <- fannie[loan_purpose != "U"]
fannie[,id_loan:=as.character(id_loan)]

fannie[,newpurchase:=ifelse(loan_purpose=="P",1,0)]
fannie[,ltv:=cltv]
moodys <- read_fst("C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/Moodys/0001/LoanChars.fst",as.data.table = TRUE, columns=c("loanid","loanoriginationdate","zipcode","originalloanbalance","originalcltv","state","originator","armflag","originalfico","originalterm","originalltv","documentationtype","originalinterestrate","purposetype","assettype","occupancytype")) 

cbsa <- fread("C:/Users/dratnadiwakara2/Documents/OneDrive - Louisiana State University/Raw Data/Crosswalk Files/ZIP_CBSA.csv")
cbsa[,ZIP:=ifelse(nchar(ZIP)==3,paste0("00",ZIP),ifelse(nchar(ZIP)==4,paste0("0",ZIP),paste0(ZIP)))]
setorder(cbsa,ZIP,-RES_RATIO)
cbsa <- cbsa[!duplicated(cbsa[,c("ZIP")])]
cbsa[,c("RES_RATIO","BUS_RATIO","OTH_RATIO","TOT_RATIO"):=list(NULL)]
names(cbsa) <- c("zipcode","msa")
moodys <- merge(moodys,cbsa,by=c("zipcode"))

moodys <- moodys[originalterm==360 & armflag=="F" ] # & occupancytype=="PRI"
moodys[,loanyr:=as.numeric(substr(loanoriginationdate,1,4))]
moodys[,seller_name:= originator]
moodys[,seller_name:= ifelse(seller_name %in% c("JPMORGAN CHASE BANK, NA","JPMORGAN CHASE BANK, NATIONAL ASSOCIATION","CHASE MANHATTAN MORTGAGE CORPORATION","CHASE HOME FINANCE LLC","CHASE HOME FINANCE","CHASE HOME FINANCE, LLC","JPMORGAN CHASE BANK, NATIONAL ASSOCIATION","JPMORGAN CHASE BANK, N.A.","JP MORGAN CHASE BANK NA","CHASE MANHATTAN MORTGAGE CORP"),"JPMORGAN CHASE BANK, NA",seller_name)]
moodys[,seller_name:= ifelse(seller_name %in%  c("B OF A"),"BANK OF AMERICA, N.A.",seller_name)]
moodys[,seller_name:= ifelse(seller_name %in% c("WELLS FARGO HOME MORTGAGE, INC.","WELLS FARGO BANK, N.A.","WELLS FARGO BANK N.A"," WELLS FARGO HOME MTG, INC"),"WELLS FARGO BANK, N.A.",seller_name)]

moodys[,int_rt:=originalinterestrate]
moodys[,dti:=0]
moodys[,ltv:=originalcltv]
moodys[,ltvorg:=originalltv]
moodys[,fico:=originalfico]
moodys[,orig_upb:= originalloanbalance]
moodys[,primary_occ:=ifelse(occupancytype=="PRI",1,0)]

# moodys[,c("originalinterestrate","originalltv","originalfico","originalloanbalance","msacode","csacode","divcode","loanoriginationdate","armflag","originalterm"):=list(NULL)]

moodys[,fulldocumentation:=ifelse(documentationtype=="FU",1,0)]
gc()
##             used   (Mb) gc trigger    (Mb)   max used    (Mb)
## Ncells  38944498 2079.9   72962977  3896.7   39101064  2088.3
## Vcells 695890762 5309.3 1622107426 12375.7 1581096478 12062.9
moodys[,bank:=seller_name]
moodys[,bank:=ifelse(bank %in% unique(cbsa_bnk$bank),bank,"other")]
moodys[,newpurchase:=ifelse(purposetype=="PUR",1,0)]

moodys <- moodys[assettype != "UN"]
regsample <- rbind(freddie,fannie)

regsample <- merge(regsample,cbsa_bnk,by.x=c("bank","msa","loanyr"),by.y=c("bank","cbsa","acyr"))

regsample[,bank_msa:=paste(seller_name,msa)]
regsample[,yr_msa:=paste(loanyr,msa)]
regsample[,fico:=fico/100]
regsample[,homevalue:= orig_upb*100/ltvorg]
regsample[,fico_cat:=ifelse(fico<6.6,"Less than 660",ifelse(fico<7.2,"660-720","0720 or more"))]
regsample[,dti_cat:=ifelse(dti<20,"0Less than 20",ifelse(dti<40,"20-40","40 or more"))]
regsample[,msinc13G2:=ifelse(msinc13>0.1,"6. More than 10 pct",msinc13G)]
regsample[,msinc46G2:=ifelse(msinc46>0.1,"6. More than 10 pct",msinc46G)]
regsample[,zip_year:=paste(loanyr,zipcode)]
regsample[,bank_year:=paste(seller_name,loanyr)]
regsample[,active:=ifelse(suc_share>0 & msinc13>1e-05,1,0)]

temp <- regsample[msinc13> 0.000010, c("msinc13")]
temp[,msinc13Q:=ntile(msinc13,4)]
temp <- temp[!duplicated(temp[,c("msinc13")])]
regsample <- merge(regsample,temp,by="msinc13",all.x=T)
regsample[,msinc13Q:=ifelse(is.na(msinc13Q),0,msinc13Q)]

temp <- regsample[msinc46> 0.000010, c("msinc46")]
temp[,msinc46Q:=ntile(msinc46,4)]
temp <- temp[!duplicated(temp[,c("msinc46")])]
regsample <- merge(regsample,temp,by="msinc46",all.x=T)
regsample[,msinc46Q:=ifelse(is.na(msinc46Q),0,msinc46Q)]


nw_acq <- regsample[,c("bank","loanyr","nationwide_msacq")]
nw_acq <- nw_acq[!duplicated(nw_acq)]
setorder(nw_acq,bank,loanyr)
nw_acq[,nationwide_msacq_1:=shift(nationwide_msacq,type="lag"),by=bank]
nw_acq[,nationwide_msacq_1:=ifelse(is.na(nationwide_msacq_1),0,nationwide_msacq_1)]
nw_acq[,nationwide_msacq_2:=shift(nationwide_msacq_1,type="lag"),by=bank]
nw_acq[,nationwide_msacq_2:=ifelse(is.na(nationwide_msacq_2),0,nationwide_msacq_2)]
nw_acq[,nationwide_msacq_3:=shift(nationwide_msacq_2,type="lag"),by=bank]
nw_acq[,nationwide_msacq_3:=ifelse(is.na(nationwide_msacq_3),0,nationwide_msacq_1)]
nw_acq[,nationwide_msacq_4:=shift(nationwide_msacq_3,type="lag"),by=bank]
nw_acq[,nationwide_msacq_4:=ifelse(is.na(nationwide_msacq_4),0,nationwide_msacq_2)]
nw_acq[,nationwide_msacq13:=nationwide_msacq+nationwide_msacq_1+nationwide_msacq_2]
nw_acq[,nationwide_msacq46:=nationwide_msacq_3+nationwide_msacq_4]
nw_acq <- nw_acq[,c("bank","loanyr","nationwide_msacq13","nationwide_msacq46")]

regsample <- merge(regsample,nw_acq,by=c("bank","loanyr"))



regsample2 <- merge(moodys,cbsa_bnk,by.x=c("bank","msa","loanyr"),by.y=c("bank","cbsa","acyr"))


regsample2[,bank_msa:=paste(seller_name,zipcode)] #
regsample2[,assettype:=ifelse(assettype=="Prime","0Prime",assettype)]
regsample2[,yr_msa:=paste(loanyr,msa)]
regsample2[,fico:=fico/100]
regsample2[,homevalue:= orig_upb*100/ltvorg]
# regsample2[,msinc13G:=ifelse(msinc13G %in% c("4. More than 10pct","3. 5pct - 10pct"),"3. 5pct or more",msinc13G)]
regsample2[,zip_year:=paste(loanyr,zipcode)]
regsample2[,bank_year:=paste(seller_name,loanyr)]
regsample2[,active:=ifelse(suc_share>0 & msinc13>1e-05,1,0)]
# regsample2[,msinc13_total:=sum(msinc13),by=yr_msa]
# regsample2[,msinc13_total:=ifelse(msinc13==1e-05,1e-05,msinc13_total)]

temp <- regsample2[msinc13> 0.000010, c("msinc13")]
temp[,msinc13Q:=ntile(msinc13,4)]
temp <- temp[!duplicated(temp[,c("msinc13")])]
regsample2 <- merge(regsample2,temp,by="msinc13",all.x=T)
regsample2[,msinc13Q:=ifelse(is.na(msinc13Q),0,msinc13Q)]

nw_acq <- regsample2[,c("bank","loanyr","nationwide_msacq")]
nw_acq <- nw_acq[!duplicated(nw_acq)]
setorder(nw_acq,bank,loanyr)
nw_acq[,nationwide_msacq_1:=shift(nationwide_msacq,type="lag"),by=bank]
nw_acq[,nationwide_msacq_1:=ifelse(is.na(nationwide_msacq_1),0,nationwide_msacq_1)]
nw_acq[,nationwide_msacq_2:=shift(nationwide_msacq_1,type="lag"),by=bank]
nw_acq[,nationwide_msacq_2:=ifelse(is.na(nationwide_msacq_2),0,nationwide_msacq_2)]
nw_acq[,nationwide_msacq13:=nationwide_msacq+nationwide_msacq_1+nationwide_msacq_2]
nw_acq <- nw_acq[,c("bank","loanyr","nationwide_msacq13")]

regsample2 <- merge(regsample2,nw_acq,by=c("bank","loanyr"))

regsample2[,upb_bin:=ntile(orig_upb,100),by=bank_msa]

2 Effect of Mergers on Interest Rate

2.1 GSE Sample

r <- list()

  r[[1]] <- felm(int_rt~msinc13+msinc4plus+suc_share+nationwide_msacq13+nationwide_msacq46+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+freddie+newpurchase+primary_occ|bank_msa+loanyr|0|zipcode,data=regsample[ !(suc_share==0 & msinc13>1e-05) & fico<8.5 & fico>3 & ltv<100])
 # r[[2]] <- felm(int_rt~factor(msinc13G)+factor(msinc46G)+suc_share+nationwide_msacq13+nationwide_msacq46+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+freddie+newpurchase+primary_occ|bank_msa+loanyr|0|zipcode,data=regsample[  !(suc_share==0 & msinc13>1e-05) & fico<8.5 & fico>3 & ltv<100])
  r[[2]] <- felm(int_rt~factor(msinc13Q)+factor(msinc46Q)+suc_share+nationwide_msacq13+nationwide_msacq46+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+freddie+newpurchase+primary_occ|bank_msa+loanyr|0|zipcode,data=regsample[  !(suc_share==0 & msinc13>1e-05) & fico<8.5 & fico>3 & ltv<100])
  # r[[3]] <- felm(int_rt~msinc13+suc_share+nationwide_msacq+fico+I(fico^2)+I(fico^3)+ltv+I(ltv^2)+dti+log(orig_upb)+freddie+newpurchase+primary_occ|bank_msa+loanyr|0|zipcode,data=regsample[  !(suc_share==0 & msinc13>1e-05) & loanyr<2008 & fico<8.5 & fico>3 & ltv<95])

# covlabs <- c("MSAcq1-3","MSAcq4Plus","MSAcq1-3 (0,2.5]","MSAcq1-3 (2.5,5]","MSAcq1-3 (5,.]","MSAcq4-6 (0,2.5]","MSAcq4-6 (2.5,5]","MSAcq4-6 (5,.]","Acquirer Share","Full documentation","FICO Score", "Combined loan-to-value","FICO Score2","FICO Score3", "Combined loan-to-value2","Combined loan-to-value3","Debt-to-income","log(Loan amount)","Freddie Mac","New purchase","Alt-A","Subprime","Primar residence","Nationwide MSAcq")

stargazer(r,no.space = T,align = T,omit.stat=c("ser","f", "rsq"),style = "qje",omit.table.layout = "n", dep.var.labels.include = FALSE,type="text",
          # column.labels=c("GSE Sample"),column.separate=c(2,1,2),
          add.lines = list(c("Bank*Zipcode", rep("Y",6)),c("Year", rep("Y",6)))
          )
## 
## ========================================
##                       (1)        (2)    
## ----------------------------------------
## msinc13             0.415***            
##                     (0.073)             
## msinc4plus          0.729***            
##                     (0.053)             
## factor(msinc13Q)1              0.020*** 
##                                (0.004)  
## factor(msinc13Q)2              0.079*** 
##                                (0.003)  
## factor(msinc13Q)3              0.052*** 
##                                (0.003)  
## factor(msinc13Q)4              0.055*** 
##                                (0.004)  
## factor(msinc46Q)1              0.023*** 
##                                (0.005)  
## factor(msinc46Q)2              0.038*** 
##                                (0.004)  
## factor(msinc46Q)3              0.038*** 
##                                (0.003)  
## factor(msinc46Q)4              0.045*** 
##                                (0.003)  
## suc_share            0.002    -0.176*** 
##                     (0.013)    (0.016)  
## nationwide_msacq13 -0.762***  -0.959*** 
##                     (0.041)    (0.060)  
## nationwide_msacq46  0.807***   0.264*** 
##                     (0.083)    (0.071)  
## fico               -0.452***  -0.451*** 
##                     (0.015)    (0.015)  
## I(fico2)            0.021***   0.021*** 
##                     (0.001)    (0.001)  
## ltv                -0.002***  -0.002*** 
##                     (0.0001)   (0.0001) 
## I(ltv2)            0.00004*** 0.00004***
##                    (0.00000)  (0.00000) 
## dti                0.0001***  0.0001*** 
##                    (0.00000)  (0.00000) 
## log(orig_upb)      -0.163***  -0.163*** 
##                     (0.002)    (0.002)  
## freddie             0.048***   0.052*** 
##                     (0.001)    (0.001)  
## newpurchase         0.022***   0.022*** 
##                     (0.001)    (0.001)  
## primary_occ        -0.341***  -0.341*** 
##                     (0.004)    (0.004)  
## Bank*Zipcode           Y          Y     
## Year                   Y          Y     
## N                  21,345,165 21,345,165
## Adjusted R2          0.890      0.890   
## ========================================

2.2 Non-agency Sample

upb_max <- 98 

r <- list()
r[[1]] <- felm(int_rt~msinc13+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="0Prime" & fico<8.5 & fico>5 & ltv<100 & upb_bin<upb_max])  
# r[[2]] <- felm(int_rt~factor(msinc13G)+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="0Prime" & fico<8.5 & fico>5 & ltv<100])  
r[[2]] <- felm(int_rt~factor(msinc13Q)+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="0Prime" & fico<8.5 & fico>5 & ltv<100& upb_bin<upb_max]) 
r[[3]] <- felm(int_rt~msinc13+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Alt-A" & fico<8.5 & fico>5 & ltv<100& upb_bin<upb_max])
# r[[5]] <- felm(int_rt~factor(msinc13G)+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Alt-A" & fico<8.5 & fico>5 & ltv<100])
r[[4]] <- felm(int_rt~factor(msinc13Q)+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Alt-A" & fico<8.5 & fico>5 & ltv<100& upb_bin<upb_max])
r[[5]] <- felm(int_rt~msinc13+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Subprime" & fico<8.5 & fico>5 & ltv<100  & upb_bin<upb_max]) 
# r[[8]] <- felm(int_rt~factor(msinc13G)+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode,data=regsample2[originalterm==360 &  assettype=="Subprime" & fico<8.5 & fico>5 & ltv<100 ])  
r[[6]] <- felm(int_rt~factor(msinc13Q)+suc_share+nationwide_msacq13+fico+I(fico^2)+ltv+I(ltv^2)+dti+log(orig_upb)+newpurchase+primary_occ+fulldocumentation|loanyr+seller_name+zipcode|0|zipcode,data=regsample2[originalterm==360 &  assettype=="Subprime" & fico<8.5 & fico>5 & ltv<100 & upb_bin<upb_max])  

covlabs <- c("MSAcq1-3","Alt-A","Subprime","FICO Score", "Combined loan-to-value","FICO Score2","FICO Score3", "Combined loan-to-value2", "Combined loan-to-value3","Acquirer Share","Full documentation","log(Loan amount)","New purchase","Primary residence","Nationwide MSAcq")
  
stargazer(r,no.space = T,align = T,omit.stat=c("ser","f", "rsq"),style = "qje",omit.table.layout = "n", dep.var.labels.include = FALSE,type="text",#covariate.labels = covlabs,
          column.labels=c("Prime","Alt-A","Subprime"),column.separate=c(2,2,2),
          add.lines = list(c("Bank*Zipcode", rep("Y",6)),c("Year", rep("Y",6))))
## 
## ==============================================================================
##                           Prime               Alt-A             Subprime      
##                       (1)       (2)       (3)       (4)       (5)       (6)   
## ------------------------------------------------------------------------------
## msinc13            2.413***            8.533***            10.899***          
##                     (0.298)             (0.769)             (0.830)           
## factor(msinc13Q)1            -0.192***            0.070**              0.022  
##                               (0.010)             (0.028)             (0.206) 
## factor(msinc13Q)2            -0.114***           0.202***            0.575*** 
##                               (0.008)             (0.029)             (0.199) 
## factor(msinc13Q)3            0.087***            0.432***            1.517*** 
##                               (0.010)             (0.031)             (0.070) 
## factor(msinc13Q)4            0.052***            0.452***            1.516*** 
##                               (0.011)             (0.034)             (0.070) 
## suc_share          0.784***  0.868***  1.930***  1.685***  -0.675*** -0.867***
##                     (0.046)   (0.047)   (0.155)   (0.157)   (0.253)   (0.254) 
## nationwide_msacq13 5.653***  6.003***  8.629***    3.620   9.114***  4.453*** 
##                     (0.773)   (0.774)   (2.131)   (2.330)   (1.739)   (1.454) 
## fico               -2.327*** -2.321*** -1.774*** -1.785*** -1.887*** -1.898***
##                     (0.087)   (0.087)   (0.117)   (0.117)   (0.075)   (0.075) 
## I(fico2)           0.145***  0.145***  0.096***  0.097***  0.106***  0.107*** 
##                     (0.006)   (0.006)   (0.008)   (0.008)   (0.006)   (0.006) 
## ltv                -0.040*** -0.039*** -0.087*** -0.087*** -0.080*** -0.080***
##                     (0.001)   (0.001)   (0.001)   (0.001)   (0.001)   (0.001) 
## I(ltv2)            0.0004*** 0.0004*** 0.001***  0.001***  0.001***  0.001*** 
##                    (0.00000) (0.00000) (0.00001) (0.00001) (0.00001) (0.00001)
## dti                                                                           
##                     (0.000)   (0.000)   (0.000)   (0.000)   (0.000)   (0.000) 
## log(orig_upb)      -0.607*** -0.608*** -1.017*** -1.017*** -1.217*** -1.217***
##                     (0.005)   (0.005)   (0.007)   (0.007)   (0.008)   (0.008) 
## newpurchase         -0.003    -0.002   -0.032*** -0.033***   0.005     0.005  
##                     (0.002)   (0.002)   (0.005)   (0.005)   (0.007)   (0.007) 
## primary_occ        -0.305*** -0.304*** -0.247*** -0.250*** -0.181*** -0.184***
##                     (0.003)   (0.003)   (0.006)   (0.006)   (0.010)   (0.010) 
## fulldocumentation  -0.155*** -0.154*** -0.306*** -0.306*** -0.474*** -0.474***
##                     (0.002)   (0.002)   (0.005)   (0.005)   (0.006)   (0.006) 
## Bank*Zipcode           Y         Y         Y         Y         Y         Y    
## Year                   Y         Y         Y         Y         Y         Y    
## N                  1,334,536 1,334,536  482,429   482,429   563,634   563,634 
## Adjusted R2          0.469     0.470     0.403     0.403     0.291     0.292  
## ==============================================================================

3 Effect of Mergers on Loan Amount

3.1 GSE Sample

r <- list()

  r[[1]] <- felm(log(orig_upb)~msinc13+msinc4plus+suc_share+nationwide_msacq13+nationwide_msacq46+fico+I(fico^2)+log(homevalue)+dti+freddie+newpurchase+primary_occ|bank_msa+loanyr|0|zipcode,data=regsample[ !(suc_share==0 & msinc13>1e-05) & fico<8.5 & fico>3 & ltv<100])
  r[[2]] <- felm(log(orig_upb)~factor(msinc13Q)+factor(msinc46Q)+suc_share+nationwide_msacq13+nationwide_msacq46+fico+I(fico^2)+log(homevalue)+dti+freddie+newpurchase+primary_occ|bank_msa+loanyr|0|zipcode,data=regsample[  !(suc_share==0 & msinc13>1e-05) & fico<8.5 & fico>3 & ltv<100])


stargazer(r,no.space = T,align = T,omit.stat=c("ser","f", "rsq"),style = "qje",omit.table.layout = "n", dep.var.labels.include = FALSE,type="text",
          column.labels=c("GSE Sample","GSE<2008","Non-agency sample"),column.separate=c(2,1,2),
          add.lines = list(c("Bank*Zipcode", rep("Y",6)),c("Year", rep("Y",6)))
          )
## 
## ========================================
##                         GSE Sample      
##                       (1)        (2)    
## ----------------------------------------
## msinc13              0.080*             
##                     (0.046)             
## msinc4plus           -0.021             
##                     (0.031)             
## factor(msinc13Q)1               0.001   
##                                (0.002)  
## factor(msinc13Q)2             -0.016*** 
##                                (0.004)  
## factor(msinc13Q)3              0.009*** 
##                                (0.002)  
## factor(msinc13Q)4               -0.003  
##                                (0.002)  
## factor(msinc46Q)1               -0.001  
##                                (0.002)  
## factor(msinc46Q)2               0.004*  
##                                (0.002)  
## factor(msinc46Q)3              0.014*** 
##                                (0.002)  
## factor(msinc46Q)4               0.002   
##                                (0.001)  
## suc_share           0.081***   0.130*** 
##                     (0.019)    (0.029)  
## nationwide_msacq13  -0.045*   -0.071*** 
##                     (0.025)    (0.025)  
## nationwide_msacq46   0.061     0.115*** 
##                     (0.051)    (0.038)  
## fico                0.962***   0.962*** 
##                     (0.009)    (0.009)  
## I(fico2)           -0.071***  -0.071*** 
##                     (0.001)    (0.001)  
## log(homevalue)      0.840***   0.840*** 
##                     (0.004)    (0.004)  
## dti                0.00003*** 0.00003***
##                    (0.00000)  (0.00000) 
## freddie            -0.017***  -0.017*** 
##                     (0.001)    (0.001)  
## newpurchase         0.137***   0.137*** 
##                     (0.001)    (0.001)  
## primary_occ         0.074***   0.074*** 
##                     (0.002)    (0.002)  
## Bank*Zipcode           Y          Y     
## Year                   Y          Y     
## N                  21,345,167 21,345,167
## Adjusted R2          0.819      0.819   
## ========================================

3.2 Non-agency Sample

r <- list()
r[[1]] <- felm(log(orig_upb)~msinc13+suc_share+nationwide_msacq13+fico+I(fico^2)+log(homevalue)+dti++newpurchase+primary_occ+fulldocumentation|bank_msa+loanyr|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="0Prime" & fico<8.5 & fico>5 & ltv<100  & upb_bin<upb_max])  

r[[2]] <- felm(log(orig_upb)~factor(msinc13Q)+suc_share+nationwide_msacq13+fico+I(fico^2)+log(homevalue)+dti+newpurchase+primary_occ+fulldocumentation|bank_msa+loanyr|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="0Prime" & fico<8.5 & fico>5 & ltv<100 & upb_bin<upb_max]) 

r[[3]] <- felm(log(orig_upb)~msinc13+suc_share+nationwide_msacq13+fico+I(fico^2)+log(homevalue)+dti+newpurchase+primary_occ+fulldocumentation|bank_msa+loanyr|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Alt-A" & fico<8.5 & fico>5 & ltv<100  & ((upb_bin<10 & msinc13Q %in% c(1,2,3))|( msinc13Q %in% c(0,4)))])

r[[4]] <- felm(log(orig_upb)~factor(msinc13Q)+suc_share+nationwide_msacq13+fico+I(fico^2)+log(homevalue)+dti+newpurchase+primary_occ+fulldocumentation|bank_msa+loanyr|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Alt-A" & fico<8.5 & fico>5 & ltv<100 & ((upb_bin<10 & msinc13Q %in% c(1,2,3))|( msinc13Q %in% c(0,4)))])

r[[5]] <- felm(log(orig_upb)~msinc13+suc_share+nationwide_msacq13+fico+I(fico^2)+log(homevalue)+dti+newpurchase+primary_occ+fulldocumentation|bank_msa+loanyr|0|zipcode,data=regsample2[originalterm==360 & armflag=="F" & assettype=="Subprime" & fico<8.5 & fico>5 & ltv<100   & upb_bin<upb_max ]) 
 
r[[6]] <- felm(log(orig_upb)~factor(msinc13Q)+suc_share+nationwide_msacq13+fico+I(fico^2)+log(homevalue)+dti+newpurchase+primary_occ+fulldocumentation|bank_msa+loanyr|0|zipcode,data=regsample2[originalterm==360 &  assettype=="Subprime" & fico<8.5 & fico>5 & ltv<100  & upb_bin<upb_max & ((upb_bin>10 & msinc13Q %in% c(1,2,3))|( msinc13Q %in% c(0,4)))])  

covlabs <- c("MSAcq1-3","Alt-A","Subprime","FICO Score", "Combined loan-to-value","FICO Score2","FICO Score3", "Combined loan-to-value2", "Combined loan-to-value3","Acquirer Share","Full documentation","log(Loan amount)","New purchase","Primary residence","Nationwide MSAcq")
  
stargazer(r,no.space = T,align = T,omit.stat=c("ser","f", "rsq"),style = "qje",omit.table.layout = "n", dep.var.labels.include = FALSE,type="text",#covariate.labels = covlabs,
          column.labels=c("Prime","Alt-A","Subprime"),column.separate=c(2,2,2),
          add.lines = list(c("Bank*Zipcode", rep("Y",6)),c("Year", rep("Y",6))))
## 
## ==============================================================================
##                           Prime               Alt-A             Subprime      
##                       (1)       (2)       (3)       (4)       (5)       (6)   
## ------------------------------------------------------------------------------
## msinc13            1.170***              1.389              -0.829            
##                     (0.196)             (0.915)             (0.686)           
## factor(msinc13Q)1            0.017***             -0.009               0.093  
##                               (0.005)             (0.022)             (0.149) 
## factor(msinc13Q)2            0.018***             -0.027               0.069  
##                               (0.005)             (0.026)             (0.052) 
## factor(msinc13Q)3            0.016***             -0.017               0.107  
##                               (0.006)             (0.023)             (0.072) 
## factor(msinc13Q)4            0.041***             0.067*              -0.035  
##                               (0.007)             (0.035)             (0.026) 
## suc_share          -0.089*** -0.107***  -0.064    -0.054   -0.227*** -0.248***
##                     (0.017)   (0.017)   (0.060)   (0.060)   (0.084)   (0.085) 
## nationwide_msacq13 0.628***   0.521**  3.103***  3.842***   -0.416    -0.164  
##                     (0.217)   (0.218)   (0.977)   (1.030)   (0.557)   (0.599) 
## fico               0.810***  0.809***  0.666***  0.666***   0.028*    0.028*  
##                     (0.032)   (0.032)   (0.038)   (0.038)   (0.017)   (0.017) 
## I(fico2)           -0.058*** -0.058*** -0.048*** -0.048***   0.002     0.002  
##                     (0.002)   (0.002)   (0.003)   (0.003)   (0.001)   (0.001) 
## log(homevalue)     0.896***  0.896***  0.900***  0.900***  0.903***  0.903*** 
##                     (0.002)   (0.002)   (0.002)   (0.002)   (0.002)   (0.002) 
## dti                                                                           
##                     (0.000)   (0.000)   (0.000)   (0.000)   (0.000)   (0.000) 
## newpurchase        0.098***  0.098***  0.012***  0.012***  -0.032*** -0.033***
##                     (0.001)   (0.001)   (0.002)   (0.002)   (0.002)   (0.002) 
## primary_occ        0.030***  0.030***  -0.011*** -0.011*** -0.015*** -0.015***
##                     (0.001)   (0.001)   (0.002)   (0.002)   (0.002)   (0.002) 
## fulldocumentation  0.024***  0.024***  0.064***  0.064***  -0.007*** -0.007***
##                     (0.001)   (0.001)   (0.001)   (0.001)   (0.001)   (0.001) 
## Bank*Zipcode           Y         Y         Y         Y         Y         Y    
## Year                   Y         Y         Y         Y         Y         Y    
## N                  1,334,632 1,334,632  483,512   483,512   563,652   561,748 
## Adjusted R2          0.835     0.835     0.749     0.749     0.781     0.781  
## ==============================================================================