In MichaelGurkov/FinSynch:
knitr::opts_chunk$set(
collapse = TRUE,echo = FALSE,message = FALSE,warning = FALSE,
comment = "#>"
)
devtools::load_all()
library(ggplot2)
library(stargazer)
params_list = make.params.list()
dataset = import_dataset()
fin_reg_list = lapply(list(NULL,
params_list$strong_countries_pairs,
params_list$weak_countries_pairs,
params_list$cross_country_pairs,
c(params_list$cross_country_pairs,
params_list$weak_countries_pairs)),
function(temp_vec){
form = formula(Fin_ret ~ bank_gdp + trade_gdp +
FO_ind_tot + FX_stab_avg +
FD_avg + MI_ind_tot)
reg_df = dataset$fin_reg_df %>%
{if(!is.null(temp_vec)) filter(.,CountryPair %in%
temp_vec) else .}
temp_reg = plm(formula = form,
model = "within",effect = "twoways",
data = reg_df,
index = c("CountryPair","Date"))
return(temp_reg)
})
within_reg_list = lapply(list(NULL,
params_list$strong_countries_pairs,
params_list$weak_countries_pairs,
params_list$cross_country_pairs,
c(params_list$cross_country_pairs,
params_list$weak_countries_pairs)),
function(temp_vec){
form = formula(Fin_ret ~ bank_gdp)
reg_df = dataset$fin_reg_df %>%
{if(!is.null(temp_vec)) filter(.,CountryPair %in%
temp_vec) else .}
temp_reg = plm(formula = form,
model = "within",effect = "twoways",
data = reg_df, index = c("CountryPair","Date"))
return(temp_reg)
})
panel_reg_list_pooling = lapply(list(NULL,
params_list$strong_countries_pairs,
params_list$weak_countries_pairs,
params_list$cross_country_pairs,
c(params_list$cross_country_pairs,
params_list$weak_countries_pairs)),
function(temp_vec){
form = formula(Fin_ret ~ bank_gdp)
reg_df = dataset$fin_reg_df %>%
{if(!is.null(temp_vec)) filter(.,CountryPair %in%
temp_vec) else .}
temp_reg = plm(formula = form,
model = "pooling",
data = reg_df, index = c("CountryPair","Date"))
return(temp_reg)
})
panel_reg_list_time_FE = lapply(list(NULL,
params_list$strong_countries_pairs,
params_list$weak_countries_pairs,
params_list$cross_country_pairs,
c(params_list$cross_country_pairs,
params_list$weak_countries_pairs)),
function(temp_vec){
form = formula(Fin_ret ~ bank_gdp)
reg_df = dataset$fin_reg_df %>%
{if(!is.null(temp_vec)) filter(.,CountryPair %in%
temp_vec) else .}
temp_reg = plm(formula = form,
model = "within",effect = "time",
data = reg_df, index = c("CountryPair","Date"))
return(temp_reg)
})
panel_reg_list_countrypair_FE = lapply(list(NULL,
params_list$strong_countries_pairs,
params_list$weak_countries_pairs,
params_list$cross_country_pairs,
c(params_list$cross_country_pairs,
params_list$weak_countries_pairs)),
function(temp_vec){
form = formula(Fin_ret ~ bank_gdp)
reg_df = dataset$fin_reg_df %>%
{if(!is.null(temp_vec)) filter(.,CountryPair %in%
temp_vec) else .}
temp_reg = plm(formula = form,
model = "within",effect = "individual",
data = reg_df, index = c("CountryPair","Date"))
return(temp_reg)
})
Motivation
\begin{itemize}
\setlength\itemsep{1.5em}
\item
Kalemi-Ozcan et all (Journal of Finance, 2013) find \textbf{negative}
association between financial integration and business cycles synchronization
\item
The authors use data of 18 ("strong OECD" such as Australia,Sweden,
United Kingdom, etc..) countries for 1978-2006 period.
They construct panel of 153 country pairs in each year.
\item
Possible economic mechanism: money moves from bad productivity shock to other places and that results productivity divergency
\end{itemize}
Motivation
The general finding is \textbf{negative} association between financial integration and business cycles synchronization
\begin{itemize}
\setlength\itemsep{2em}
\item
The \textit{cross country} (between model) association is significantly
\textit{positive}.
\item
The \textit{panel} (within model with time and country pair fixed effects)
association is significantly \textit{negative}.
\item
Authors suggest that common global time shocks and specific country pair characterisitcs explain the difference
\end{itemize}
Financial Cycle - Cross country Scatter plot
ggplot(dataset$fin_reg_df %>%
select(CountryPair, Fin_ret, bank_gdp) %>%
group_by(CountryPair) %>%
summarise_all(.,.funs = list(.~mean), na.rm = TRUE),
aes(x = bank_gdp, y = Fin_ret * 100,
color = ifelse(CountryPair %in% params_list$strong_countries_pairs,
"\"Strong\" countrypairs","Other"))) +
geom_point() +
geom_smooth(method = "lm",se = FALSE) +
theme_bw() +
labs(title = paste0("Average synchronization of financial growth rates",
"\n (Between countrypairs)"),
y = "Growth rate negative difference (percent)",
x = "Cross border bank balance to gdp") +
theme(plot.title = element_text(hjust = 0.5, size = 25),
legend.position = "bottom",
legend.title = element_blank(),
axis.text = element_text(size = 20),
legend.text = element_text(size = 20))
Financial Cycle - Panel data Scatter plot
temp_df = dataset$fin_reg_df %>%
select(CountryPair,Date,Fin_ret,bank_gdp) %>%
ungroup() %>%
filter(complete.cases(.))
clean_df = data.frame(Fin_Res = lm(Fin_ret~factor(CountryPair) + factor(Date), data = temp_df)$residuals,Bank_Res = lm(bank_gdp~factor(CountryPair) + factor(Date), data = temp_df)$residuals)
clean_df = cbind.data.frame(clean_df, temp_df %>%
select(CountryPair, Date))
ggplot(clean_df, aes(x = Bank_Res, y = Fin_Res,
color = ifelse(CountryPair %in%
params_list$strong_countries_pairs,
"\"Strong\" countrypairs","Other"))) +
geom_point() +
geom_smooth(method = "lm", se = FALSE) +
labs(title = paste0("Average synchronization of financial growth rates",
"\n (Within countrypairs,",
" netting time and country pair fixed effects)"),
y = "Growth rate negative difference (percent)",
x = "Cross border bank balance to gdp") +
theme_bw() +
theme(plot.title = element_text(hjust = 0.5, size = 25),
legend.position = "bottom",
legend.title = element_blank(),
axis.text = element_text(size = 20),
legend.text = element_text(size = 20))
Financial Cycle - Cross country
between_reg_list = lapply(list(NULL,
params_list$strong_countries_pairs,
params_list$weak_countries_pairs,
params_list$cross_country_pairs,
c(params_list$cross_country_pairs,
params_list$weak_countries_pairs)),
function(temp_vec){
form = formula(Fin_ret ~ bank_gdp)
reg_df = dataset$fin_reg_df %>%
{if(!is.null(temp_vec)) filter(.,CountryPair %in%
temp_vec) else .}
temp_reg = plm(formula = form,
model = "between",data = reg_df,
index = c("CountryPair","Date"))
return(temp_reg)
})
stargazer(between_reg_list, header = FALSE,
dep.var.labels = rep("",5),
dep.var.caption = "Credit cycle synchronization",
column.labels = c("All","Strong","Weak","Cross","Cross and Weak"),
omit.stat = c("f","adj.rsq"), font.size = "scriptsize",
report = "vc*", title = "Cross country averages",
omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle - Panel data
stargazer(within_reg_list, header = FALSE,
dep.var.labels = rep("",5),
dep.var.caption = "Credit cycle synchronization",
column.labels = c("All","Strong","Weak","Cross","Cross and Weak"),
omit.stat = c("f","adj.rsq"), font.size = "scriptsize",
report = "vc*",title = "Panel fixed effect time and country pair",
omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle Regressions
stargazer(fin_reg_list, header = FALSE,
dep.var.labels = rep("",5),
dep.var.caption = "Credit cycle synchronization",
column.labels = c("All","Strong","Weak","Cross","Cross and Weak"),
omit.stat = c("f","adj.rsq"), font.size = "scriptsize",
report = "vc*",title = "Panel regression with controls and fixed effects",
omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Summary Statistics
ggplot(dataset$fin_reg_df %>%
as.data.frame() %>%
mutate(G = ifelse(CountryPair %in% params_list$strong_countries_pairs,
"\"Strong\" countrypairs","Other")) %>%
group_by(G) %>%
summarise_at(.,.vars = vars(FD_avg,FO_ind_tot,FX_stab_avg,MI_ind_tot),
.funs = list(~mean(., na.rm = TRUE))) %>%
gather(key = Indicator, value = Val, -G),
aes(x = Indicator, y = Val, group = G, fill = G)) +
geom_bar(stat = "identity", position = "dodge") +
# scale_x_discrete(labels = rep("A",4)) +
labs(title = "Controls comparison", y = "", x = "") +
theme_bw() +
theme(legend.position = "bottom",legend.title = element_blank(),
plot.title = element_text(hjust = 0.5),
legend.spacing.x = unit(10, "pt"))
Financial Cycle - Panel data
stargazer(panel_reg_list_pooling, header = FALSE,
dep.var.labels = rep("",5),
dep.var.caption = "Credit cycle synchronization",
column.labels = c("All","Strong","Weak","Cross","Cross and Weak"),
omit.stat = c("f","adj.rsq"), font.size = "scriptsize",
report = "vc*",title = "Panel Pooling",
omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle - Panel data
stargazer(panel_reg_list_time_FE, header = FALSE,
dep.var.labels = rep("",5),
dep.var.caption = "Credit cycle synchronization",
column.labels = c("All","Strong","Weak","Cross","Cross and Weak"),
omit.stat = c("f","adj.rsq"), font.size = "scriptsize",
report = "vc*",title = "Panel fixed effect time",
omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle - Panel data
stargazer(panel_reg_list_countrypair_FE, header = FALSE,
dep.var.labels = rep("",5),
dep.var.caption = "Credit cycle synchronization",
column.labels = c("All","Strong","Weak","Cross","Cross and Weak"),
omit.stat = c("f","adj.rsq"), font.size = "scriptsize",
report = "vc*",title = "Panel fixed effect country pair",
omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
MichaelGurkov/FinSynch documentation built on Oct. 30, 2019, 9:27 p.m.
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knitr::opts_chunk$set( collapse = TRUE,echo = FALSE,message = FALSE,warning = FALSE, comment = "#>" )
devtools::load_all() library(ggplot2) library(stargazer)
params_list = make.params.list() dataset = import_dataset()
fin_reg_list = lapply(list(NULL, params_list$strong_countries_pairs, params_list$weak_countries_pairs, params_list$cross_country_pairs, c(params_list$cross_country_pairs, params_list$weak_countries_pairs)), function(temp_vec){ form = formula(Fin_ret ~ bank_gdp + trade_gdp + FO_ind_tot + FX_stab_avg + FD_avg + MI_ind_tot) reg_df = dataset$fin_reg_df %>% {if(!is.null(temp_vec)) filter(.,CountryPair %in% temp_vec) else .} temp_reg = plm(formula = form, model = "within",effect = "twoways", data = reg_df, index = c("CountryPair","Date")) return(temp_reg) })
within_reg_list = lapply(list(NULL, params_list$strong_countries_pairs, params_list$weak_countries_pairs, params_list$cross_country_pairs, c(params_list$cross_country_pairs, params_list$weak_countries_pairs)), function(temp_vec){ form = formula(Fin_ret ~ bank_gdp) reg_df = dataset$fin_reg_df %>% {if(!is.null(temp_vec)) filter(.,CountryPair %in% temp_vec) else .} temp_reg = plm(formula = form, model = "within",effect = "twoways", data = reg_df, index = c("CountryPair","Date")) return(temp_reg) }) panel_reg_list_pooling = lapply(list(NULL, params_list$strong_countries_pairs, params_list$weak_countries_pairs, params_list$cross_country_pairs, c(params_list$cross_country_pairs, params_list$weak_countries_pairs)), function(temp_vec){ form = formula(Fin_ret ~ bank_gdp) reg_df = dataset$fin_reg_df %>% {if(!is.null(temp_vec)) filter(.,CountryPair %in% temp_vec) else .} temp_reg = plm(formula = form, model = "pooling", data = reg_df, index = c("CountryPair","Date")) return(temp_reg) }) panel_reg_list_time_FE = lapply(list(NULL, params_list$strong_countries_pairs, params_list$weak_countries_pairs, params_list$cross_country_pairs, c(params_list$cross_country_pairs, params_list$weak_countries_pairs)), function(temp_vec){ form = formula(Fin_ret ~ bank_gdp) reg_df = dataset$fin_reg_df %>% {if(!is.null(temp_vec)) filter(.,CountryPair %in% temp_vec) else .} temp_reg = plm(formula = form, model = "within",effect = "time", data = reg_df, index = c("CountryPair","Date")) return(temp_reg) }) panel_reg_list_countrypair_FE = lapply(list(NULL, params_list$strong_countries_pairs, params_list$weak_countries_pairs, params_list$cross_country_pairs, c(params_list$cross_country_pairs, params_list$weak_countries_pairs)), function(temp_vec){ form = formula(Fin_ret ~ bank_gdp) reg_df = dataset$fin_reg_df %>% {if(!is.null(temp_vec)) filter(.,CountryPair %in% temp_vec) else .} temp_reg = plm(formula = form, model = "within",effect = "individual", data = reg_df, index = c("CountryPair","Date")) return(temp_reg) })
Motivation
\begin{itemize}
\setlength\itemsep{1.5em}
\item Kalemi-Ozcan et all (Journal of Finance, 2013) find \textbf{negative} association between financial integration and business cycles synchronization
\item The authors use data of 18 ("strong OECD" such as Australia,Sweden, United Kingdom, etc..) countries for 1978-2006 period. They construct panel of 153 country pairs in each year.
\item Possible economic mechanism: money moves from bad productivity shock to other places and that results productivity divergency
\end{itemize}
Motivation
The general finding is \textbf{negative} association between financial integration and business cycles synchronization
\begin{itemize}
\setlength\itemsep{2em}
\item The \textit{cross country} (between model) association is significantly \textit{positive}.
\item The \textit{panel} (within model with time and country pair fixed effects) association is significantly \textit{negative}.
\item Authors suggest that common global time shocks and specific country pair characterisitcs explain the difference
\end{itemize}
Financial Cycle - Cross country Scatter plot
ggplot(dataset$fin_reg_df %>% select(CountryPair, Fin_ret, bank_gdp) %>% group_by(CountryPair) %>% summarise_all(.,.funs = list(.~mean), na.rm = TRUE), aes(x = bank_gdp, y = Fin_ret * 100, color = ifelse(CountryPair %in% params_list$strong_countries_pairs, "\"Strong\" countrypairs","Other"))) + geom_point() + geom_smooth(method = "lm",se = FALSE) + theme_bw() + labs(title = paste0("Average synchronization of financial growth rates", "\n (Between countrypairs)"), y = "Growth rate negative difference (percent)", x = "Cross border bank balance to gdp") + theme(plot.title = element_text(hjust = 0.5, size = 25), legend.position = "bottom", legend.title = element_blank(), axis.text = element_text(size = 20), legend.text = element_text(size = 20))
Financial Cycle - Panel data Scatter plot
temp_df = dataset$fin_reg_df %>% select(CountryPair,Date,Fin_ret,bank_gdp) %>% ungroup() %>% filter(complete.cases(.)) clean_df = data.frame(Fin_Res = lm(Fin_ret~factor(CountryPair) + factor(Date), data = temp_df)$residuals,Bank_Res = lm(bank_gdp~factor(CountryPair) + factor(Date), data = temp_df)$residuals) clean_df = cbind.data.frame(clean_df, temp_df %>% select(CountryPair, Date))
ggplot(clean_df, aes(x = Bank_Res, y = Fin_Res, color = ifelse(CountryPair %in% params_list$strong_countries_pairs, "\"Strong\" countrypairs","Other"))) + geom_point() + geom_smooth(method = "lm", se = FALSE) + labs(title = paste0("Average synchronization of financial growth rates", "\n (Within countrypairs,", " netting time and country pair fixed effects)"), y = "Growth rate negative difference (percent)", x = "Cross border bank balance to gdp") + theme_bw() + theme(plot.title = element_text(hjust = 0.5, size = 25), legend.position = "bottom", legend.title = element_blank(), axis.text = element_text(size = 20), legend.text = element_text(size = 20))
Financial Cycle - Cross country
between_reg_list = lapply(list(NULL, params_list$strong_countries_pairs, params_list$weak_countries_pairs, params_list$cross_country_pairs, c(params_list$cross_country_pairs, params_list$weak_countries_pairs)), function(temp_vec){ form = formula(Fin_ret ~ bank_gdp) reg_df = dataset$fin_reg_df %>% {if(!is.null(temp_vec)) filter(.,CountryPair %in% temp_vec) else .} temp_reg = plm(formula = form, model = "between",data = reg_df, index = c("CountryPair","Date")) return(temp_reg) }) stargazer(between_reg_list, header = FALSE, dep.var.labels = rep("",5), dep.var.caption = "Credit cycle synchronization", column.labels = c("All","Strong","Weak","Cross","Cross and Weak"), omit.stat = c("f","adj.rsq"), font.size = "scriptsize", report = "vc*", title = "Cross country averages", omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle - Panel data
stargazer(within_reg_list, header = FALSE, dep.var.labels = rep("",5), dep.var.caption = "Credit cycle synchronization", column.labels = c("All","Strong","Weak","Cross","Cross and Weak"), omit.stat = c("f","adj.rsq"), font.size = "scriptsize", report = "vc*",title = "Panel fixed effect time and country pair", omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle Regressions
stargazer(fin_reg_list, header = FALSE, dep.var.labels = rep("",5), dep.var.caption = "Credit cycle synchronization", column.labels = c("All","Strong","Weak","Cross","Cross and Weak"), omit.stat = c("f","adj.rsq"), font.size = "scriptsize", report = "vc*",title = "Panel regression with controls and fixed effects", omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Summary Statistics
ggplot(dataset$fin_reg_df %>% as.data.frame() %>% mutate(G = ifelse(CountryPair %in% params_list$strong_countries_pairs, "\"Strong\" countrypairs","Other")) %>% group_by(G) %>% summarise_at(.,.vars = vars(FD_avg,FO_ind_tot,FX_stab_avg,MI_ind_tot), .funs = list(~mean(., na.rm = TRUE))) %>% gather(key = Indicator, value = Val, -G), aes(x = Indicator, y = Val, group = G, fill = G)) + geom_bar(stat = "identity", position = "dodge") + # scale_x_discrete(labels = rep("A",4)) + labs(title = "Controls comparison", y = "", x = "") + theme_bw() + theme(legend.position = "bottom",legend.title = element_blank(), plot.title = element_text(hjust = 0.5), legend.spacing.x = unit(10, "pt"))
Financial Cycle - Panel data
stargazer(panel_reg_list_pooling, header = FALSE, dep.var.labels = rep("",5), dep.var.caption = "Credit cycle synchronization", column.labels = c("All","Strong","Weak","Cross","Cross and Weak"), omit.stat = c("f","adj.rsq"), font.size = "scriptsize", report = "vc*",title = "Panel Pooling", omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle - Panel data
stargazer(panel_reg_list_time_FE, header = FALSE, dep.var.labels = rep("",5), dep.var.caption = "Credit cycle synchronization", column.labels = c("All","Strong","Weak","Cross","Cross and Weak"), omit.stat = c("f","adj.rsq"), font.size = "scriptsize", report = "vc*",title = "Panel fixed effect time", omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
Financial Cycle - Panel data
stargazer(panel_reg_list_countrypair_FE, header = FALSE, dep.var.labels = rep("",5), dep.var.caption = "Credit cycle synchronization", column.labels = c("All","Strong","Weak","Cross","Cross and Weak"), omit.stat = c("f","adj.rsq"), font.size = "scriptsize", report = "vc*",title = "Panel fixed effect country pair", omit.table.layout = paste0("-","=","-!","=!","a", collapse = ""))
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