@fanxy
2016-09-19T20:20:14.000000Z
字数 8321
阅读 1793
樊潇彦 复旦大学经济学院 中级宏观
# 准备工作install.packages("readxl") # 读取excel数据install.packages("stringr") # 处理字符串install.packages("corrplot") # 作相关关系图install.packages("igraph") # 作网络图install.packages("forecast") # 作季节调整library(readxl) # 读取excel数据library(stringr) # 字符串处理library(corrplot)library(igraph)library(forecast)library(stats) # 基础包，不用安装直接调用library(dplyr)library(tidyr)library(data.table)library(foreign)library(readstata13)library(haven)library(ggplot2)library(ggrepel)library(dygraphs)library(plotrix)library(lubridate)library(zoo)library(mFilter)setwd("D:\\...") # 设定工作目录rm(list=ls())
total=read_excel("Ch03_Data.xls",sheet="total", skip=1,col_names=T,col_types=c("date",rep("numeric",4)))gdp=read_excel("../Ch02/Ch02_Data.xlsx",col_names=T,sheet="gdp_idx")gdp=gdp%>%filter(!is.na(year))%>%select(year,GDP)tax_str=total%>%mutate(year=year(`指标名称`))%>%left_join(gdp,by="year")%>%mutate(`国家财政收入/GDP`=`国家财政收入`/GDP)%>%mutate(`国家财政赤字/GDP`=(`国家财政收入`-`国家财政支出`)/GDP)%>%select(year,`国家财政收入/GDP`,`国家财政赤字/GDP`,`中央财政收入:占比`,`中央财政支出:占比`)%>%arrange(year)%>%gather(var,share,-year)%>%filter(!is.na(share))ggplot(tax_str[tax_str$var %in% c("国家财政收入/GDP","国家财政赤字/GDP"),],aes(year,share,color=var))+geom_line(size=1)+geom_vline(xintercept=1958,linetype = "dotdash",col="black")+geom_vline(xintercept=1978,linetype = "dotdash",col="black")+geom_vline(xintercept=1984,linetype = "dotdash",col="black")+geom_vline(xintercept=1994,linetype = "dotdash",col="red")+labs(title="国家财政收入与赤字占GDP的比重",x="",y="")+scale_x_continuous(breaks = c(1952, 1958, 1978, 1984, 1994, 2015))+guides(color = guide_legend(title = NULL)) +theme_bw()+ theme(legend.position = 'bottom')ggplot(tax_str[tax_str$var %in% c("中央财政收入:占比","中央财政支出:占比"),],aes(year,share,color=var))+geom_line(size=1)+geom_vline(xintercept=1958,linetype = "dotdash",col="black")+geom_vline(xintercept=1978,linetype = "dotdash",col="black")+geom_vline(xintercept=1984,linetype = "dotdash",col="black")+geom_vline(xintercept=1994,linetype = "dotdash",col="red")+labs(title="中央财政收入和支出占比（%）",x="",y="")+scale_x_continuous(breaks = c(1952, 1958, 1978, 1984, 1994, 2015))+guides(color = guide_legend(title = NULL)) +theme_bw()+ theme(legend.position = 'bottom')
class=read_excel("Ch03_Data.xls",sheet="class",col_names=T,col_types=c(rep("text",2),rep("numeric",66)))colnames(class)=c("varid","var",1950:2015)class_var=class[,c(1,2)]class=class%>%select(-varid)%>%gather(year,value,-var)%>%filter(!is.na(value))%>%mutate(year=as.numeric(year))%>%mutate(level=substr(var,1,2))%>%mutate(item=sub(".*:","",var))%>%mutate(var=sub(".*公共财政支出.*","公共财政支出",var))%>%mutate(var=sub(".*公共财政收入:税收收入.*","公共财政收入:税收",var))%>%mutate(var=sub(".*公共财政收入:非税收收入.*","公共财政收入:非税收",var))%>%mutate(item=sub("事务","",item))%>%mutate(item=sub("医疗卫生与计划生育","医卫计生",item))%>%mutate(item=sub("社会保障和就业","社保就业",item))%>%arrange(level, var, item, year)inc_str=class%>%filter((var=="公共财政收入:非税收" | var=="公共财政收入:税收") &item!="合计" & year>=2007)%>%group_by(year,level, var)%>%summarise(total_inc=sum(value))%>%spread(var,total_inc)%>%mutate(tax_share=`公共财政收入:税收`/(`公共财政收入:税收`+`公共财政收入:非税收`))ggplot(inc_str,aes(year,tax_share,color=level))+geom_line(size=1)+labs(title="各级财政税收收入占比",x="",y="")+guides(color=guide_legend(title=NULL))+theme_bw()+theme(legend.position="bottom")
tax_str=class%>%filter(var=="公共财政收入:税收" & item!="合计" & year %in% c(2010,2015))%>%group_by(year,level)%>%mutate(total_inc=sum(value))%>%mutate(share=value/total_inc)%>%select(year,level,item, share)%>%mutate(rk=ifelse(year==2015,n()+1-min_rank(share),0))%>%group_by(level,item)%>%mutate(rk=max(rk))%>%filter(rk<=7 & rk>0)%>%group_by()%>%arrange(year,level,rk)labs=tax_str$item[tax_str$year==2015 & tax_str$level=="全国"]names(labs)=tax_str$rk[tax_str$year==2015 & tax_str$level=="全国"]ggplot(tax_str[tax_str$level=="全国",],aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="全国财政税收收入结构",x="",y="")+guides(fill=guide_legend(title=NULL))+scale_x_continuous(breaks=1:length(labs),labels=labs)+theme_bw()+theme(legend.position="bottom")labs=tax_str$item[tax_str$year==2015 & tax_str$level=="地方"]names(labs)=tax_str$rk[tax_str$year==2015 & tax_str$level=="地方"]ggplot(tax_str[tax_str$level=="地方",],aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="地方财政税收收入结构",x="",y="")+guides(fill=guide_legend(title=NULL))+scale_x_continuous(breaks=1:length(labs),labels=labs)+theme_bw()+theme(legend.position="bottom")labs=tax_str$item[tax_str$year==2015 & tax_str$level=="中央"]names(labs)=tax_str$rk[tax_str$year==2015 & tax_str$level=="中央"]ggplot(tax_str[tax_str$level=="中央",],aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="中央财政税收收入结构",x="",y="")+guides(fill=guide_legend(title=NULL))+scale_x_continuous(breaks=1:length(labs),labels=labs)+theme_bw()+theme(legend.position="bottom")
ind=read_excel("Ch03_Data.xls",sheet="ind",col_names=T,col_types=c(rep("text",2),rep("numeric",5)))colnames(ind)=c("varid","var",2010:2014)ind_var=ind[,c(1,2)]ind=ind%>%mutate(level=sub("税收收入:","",var))%>%mutate(industry=sub(".*:","",level))%>%mutate(level=sub(":.*","",level))%>%mutate(level=ifelse(level==industry,"全国合计",level))%>%select(-varid,-var)ind_total=ind%>%filter(level=="全国合计" &!industry %in% c("第一产业","第二产业","第三产业"))%>%select(-level)%>%gather(year,inc,-industry)%>%mutate(year=as.numeric(year))%>%filter(year %in% c(2010,2014))%>%group_by(year)%>%mutate(total=sum(inc))%>%mutate(share=inc/total)%>%mutate(rk=ifelse(year==2014,n()+1-min_rank(share),0))%>%group_by(industry)%>%mutate(rk=max(rk))%>%filter(rk<=7 & rk>0)%>%arrange(year,rk)labs=ind_total$industry[ind_total$year==2014]names(labs)=ind_total$rk[ind_total$year==2014]ggplot(ind_total,aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="税收收入行业结构",x="",y="")+guides(fill=guide_legend(title=NULL))+scale_x_continuous(breaks=1:length(labs),labels=labs)+theme_bw()+theme(legend.position="bottom")
ind_guo=ind%>%filter(level=="国家税务局"&!industry %in% c("第一产业","第二产业","第三产业"))%>%gather(year,guo,-level,-industry)%>%mutate(id=paste(industry,year,sep=""))%>%select(-level)ind_di=ind%>%filter(level=="地方税务局"&!industry %in% c("第一产业","第二产业","第三产业"))%>%gather(year,di,-level,-industry)%>%mutate(id=paste(industry,year,sep=""))%>%select(-level,-industry,-year)relative=merge(ind_guo,ind_di,by="id")relative=relative%>%filter(year %in% c("2010","2014"))%>%mutate(diff=guo-di)%>%select(-id,-guo,-di)%>%spread(year,diff)ggplot(relative,aes(`2010`,`2014`))+geom_point(size=2,color="red")+geom_text_repel(aes(label=industry))+labs(title="国家与地方税务局税收收入差额",x="2010年",y="2014年")+theme_bw()
exp_str=class%>%filter(var=="公共财政支出" & year %in% c(2010,2015))%>%group_by(year,level)%>%mutate(total_exp=sum(value))%>%mutate(share=value/total_exp)%>%select(year,level,item,share)%>%mutate(rk=ifelse(year==2015,n()+1-min_rank(share),0))%>%group_by(level,item)%>%mutate(rk=max(rk))%>%filter(rk<=7 & rk>0)%>%arrange(year,level,rk)labs=exp_str$item[exp_str$year==2015 & exp_str$level=="全国"]names(labs)=exp_str$rk[exp_str$year==2015 & exp_str$level=="全国"]ggplot(exp_str[exp_str$level=="全国",],aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="全国财政支出结构",x="",y="")+guides(fill=guide_legend(title=NULL))+scale_x_continuous(breaks=1:length(labs),labels=labs)+theme_bw()+theme(legend.position="bottom")labs=exp_str$item[exp_str$year==2015 & exp_str$level=="地方"]names(labs)=exp_str$rk[exp_str$year==2015 & exp_str$level=="地方"]ggplot(exp_str[exp_str$level=="地方",],aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="地方财政支出结构",x="",y="")+scale_x_continuous(breaks=1:length(labs),labels=labs)+guides(fill=guide_legend(title=NULL))+theme_bw()+theme(legend.position="bottom")labs=exp_str$item[exp_str$year==2015 & exp_str$level=="中央"]names(labs)=exp_str$rk[exp_str$year==2015 & exp_str$level=="中央"]ggplot(exp_str[exp_str$level=="中央",],aes(rk,share,fill=as.factor(year)))+geom_bar(stat="identity", position = "dodge")+labs(title="中央财政支出结构",x="",y="")+scale_x_continuous(breaks=1:length(labs),labels=labs)+guides(fill=guide_legend(title=NULL))+theme_bw()+theme(legend.position="bottom")