Tax wedge decomposition - TXWDECOMP

Data - OECD

Data Structure

Code
TXWDECOMP_var %>%
  pluck("VAR_DESC") %>%
  print_table_long
id description
COU Country
INDICATOR Indicator
FAM_TYPE Household type
ER % of total earnings
YEA Year
OBS_VALUE Observation Value
TIME_FORMAT Time Format
OBS_STATUS Observation Status

INDICATOR

Code
TXWDECOMP_var %>%
  pluck("INDICATOR") %>%
  arrange(id) %>%
  print_table_long
id label
AVG_CIT_PERC_LC average central income tax as % of labour costs
AVG_LIT_PERC_LC average local income tax as % of labour costs
AVG_TX_WEDGE average tax wedge (sum of the components) % labour costs
CASHBEN cash benefits
CASHBEN_PERC_LC cash benefits as % of labour costs
EMPESSC employee SSC
EMPESSC_PERC_LC employee SSC as % of labour costs
EMPRSSC employer SSC
EMPRSSC_PERC_LC employer SSC as % of labour costs
GROSS gross wage earnings
INCTAX_CEN income tax: central government
INCTAX_LOC income tax: local government
LAB_COST total labour cost
MRG_CASHBEN_PERC_LC marginal cash benefits as % of labour costs
MRG_CIT_PERC_LC marginal central income tax as % of labour costs
MRG_EMPESSC_PERC_LC marginal employee SSC as % of labour costs
MRG_EMPRSSC_PERC_LC marginal employer SSC as % of labour costs
MRG_LIT_PERC_LC marginal local income tax as % of labour costs
MRG_TX_WEDGE marginal tax wedge (sum of the components) % labour costs
NET net wage earnings
NET_P_AVE_TX net personal average tax rate % gross wage earnings
NET_P_MRG_TX net personal marginal tax rate % gross wage earnings
PCT % of average wage
TAX payroll taxes

FAM_TYPE

Code
TXWDECOMP_var %>%
  pluck("FAM_TYPE") %>%
  arrange(id) %>%
  print_table_long
id label
1ECPL one-earner married couple, 0 children
1ECPL2C one-earner married couple, 2 children
SGL single person, 0 children
SGL2C single parent, 2 children

ER

Code
TXWDECOMP_var %>%
  pluck("ER") %>%
  arrange(id) %>%
  print_table_long
id label
100 100%
101 101%
102 102%
103 103%
104 104%
105 105%
106 106%
107 107%
108 108%
109 109%
110 110%
111 111%
112 112%
113 113%
114 114%
115 115%
116 116%
117 117%
118 118%
119 119%
120 120%
121 121%
122 122%
123 123%
124 124%
125 125%
126 126%
127 127%
128 128%
129 129%
130 130%
131 131%
132 132%
133 133%
134 134%
135 135%
136 136%
137 137%
138 138%
139 139%
140 140%
141 141%
142 142%
143 143%
144 144%
145 145%
146 146%
147 147%
148 148%
149 149%
150 150%
151 151%
152 152%
153 153%
154 154%
155 155%
156 156%
157 157%
158 158%
159 159%
160 160%
161 161%
162 162%
163 163%
164 164%
165 165%
166 166%
167 167%
168 168%
169 169%
170 170%
171 171%
172 172%
173 173%
174 174%
175 175%
176 176%
177 177%
178 178%
179 179%
180 180%
181 181%
182 182%
183 183%
184 184%
185 185%
186 186%
187 187%
188 188%
189 189%
190 190%
191 191%
192 192%
193 193%
194 194%
195 195%
196 196%
197 197%
198 198%
199 199%
200 200%
201 201%
202 202%
203 203%
204 204%
205 205%
206 206%
207 207%
208 208%
209 209%
210 210%
211 211%
212 212%
213 213%
214 214%
215 215%
216 216%
217 217%
218 218%
219 219%
220 220%
221 221%
222 222%
223 223%
224 224%
225 225%
226 226%
227 227%
228 228%
229 229%
230 230%
231 231%
232 232%
233 233%
234 234%
235 235%
236 236%
237 237%
238 238%
239 239%
240 240%
241 241%
242 242%
243 243%
244 244%
245 245%
246 246%
247 247%
248 248%
249 249%
250 250%
50 50%
51 51%
52 52%
53 53%
54 54%
55 55%
56 56%
57 57%
58 58%
59 59%
60 60%
61 61%
62 62%
63 63%
64 64%
65 65%
66 66%
67 67%
68 68%
69 69%
70 70%
71 71%
72 72%
73 73%
74 74%
75 75%
76 76%
77 77%
78 78%
79 79%
80 80%
81 81%
82 82%
83 83%
84 84%
85 85%
86 86%
87 87%
88 88%
89 89%
90 90%
91 91%
92 92%
93 93%
94 94%
95 95%
96 96%
97 97%
98 98%
99 99%