Overview challenges the methodology -short version

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1 Overview challenges the methodology -short version
Nordic Forum for Geo-Statistics Copenhagen 12 September 2013

2 Typical ”map” press release from DST NYT Nr. 604 http://www. dst
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3 The data matrix - NYT 604 Income data:
META CODE_LOCAL Name 1 Indkomst i alt ( ) PARSETYPE S F ID NA indkialt SLICE 2000 2001 2002 2003 2004 2005 UNIT kr. 101 København 199399 208105 214480 218405 223092 231309 147 Frederiksberg 246957 257956 260933 263208 270809 279613 151 Ballerup 226356 233007 239410 241735 247145 253093 153 Brøndby 204274 211601 216739 220049 224804 231890 155 Dragør 275107 285832 288806 294078 301001 306818 157 Gentofte 356158 375403 369633 374701 385928 426345 159 Gladsaxe 224788 235682 241990 245399 252131 261384 161 Glostrup 221986 229659 235090 239094 246060 254058 163 Herlev 214756 221516 228022 232831 237988 244787 165 Albertslund 209562 217205 221858 223806 227476 231123 167 Hvidovre 209894 218727 224283 228554 235010 242983 169 Høje-Taastrup 223684 233120 237919 240737 245049 253872 173 Lyngby-Taarbæk 280880 290287 294403 296130 304560 320645 175 Rødovre 210839 219949 224010 228865 233911 242881 183 Ishøj 206501 214987 219992 222920 225731 232416 185 Tårnby 219981 228438 233396 237741 244487 251452 187 Vallensbæk 260520 270191 275143 280039 282984 290802 190 Furesø 287728 298462 300607 305252 309612 320632 201 Allerød 285727 297466 299279 310317 319318 334759 210 Fredensborg 267569 275831 284167 285503 292077 306596 217 Helsingør 234948 241040 265638 253281 258796 271274 219 Hillerød 248129 258721 266944 268968 277090 289096 223 Hørsholm 367339 370191 370732 366486 378834 400091 230 Rudersdal 360487 365401 373214 371589 386900 408605 240 Egedal 263456 278016 280950 284124 290577 300772 250 Frederikssund 229823 241822 246609 250565 257281 267126 253 Greve 251950 261798 267123 269987 276230 285687 259 Køge 226886 235337 240836 245391 252164 259782 260 Halsnæs 207907 215817 222560 225922 232552 242264 265 Roskilde 243080 254080 259405 262948 269951 279379 269 Solrød 264139 275373 280728 285498 291254 302770 270 Gribskov 228514 239628 244211 248731 255283 265709 306 Odsherred 196386 203098 208795 214823 220119 227637 316 Holbæk 213432 222380 228491 233079 240187 249490 320 Faxe 211986 222163 227924 231691 237942 246315 326 Kalundborg 206791 215640 220556 223880 230816 238871 329 Ringsted 217707 226010 230269 235275 242944 251595 330 Slagelse 201917 208979 215266 219141 225514 232534 336 Stevns 220883 229367 234079 237546 242901 253351 340 Sorø 213318 223462 227468 232190 240734 249159 350 Lejre 248147 258291 263437 268199 273481 284360 360 Lolland 183832 191595 196892 200190 205776 212884 370 Næstved 207844 216122 221514 226148 232636 241125 376 Guldborgsund 191689 199254 203468 207760 213633 221302 390 Vordingborg 199693 206733 211303 215845 220735 230494 Income data: The geographic subdivision (98 municipalities) Time (11 years) Types of income (10) Attachment to the labourmarket data: Time (9 years) Attachment to the labourmarket (3 types) Different agegroups(3 types) Overall matrix (98*11*10) + (98*9*3*3) = cells Or 48 normal pages…. 10/21/2019

4 Left or right - interaktion with the users
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5 The Geo-visual twist – NYT 604 -this is feedback
Test om tilføjelse af noter 10/21/2019

6 Privat pensions should be investment/ property income?
The Geo-visual twist challenging the methodology used the last ten years for social generated income (9) The social generated income is the sum of ( ): Pensions, etc total (10) + Daily benefits (17) + Other social social generated income (22) Pensions, etc total (10) is the sum of ( ) Social pensions including supplements (11) Pension from ATP (12) Early retirement pay (13) Special early retirement pay (14) Public servants pension (15) Other pensions (16). Daily benefits (17) is the sum of ( ) Cash benefits (18) Unemployment benefits (19) Temporary leave benefits (20) Other benefits (21) Other Social generated income (22) is the sum of ( ) Education grants (23) Rent subcidies(24) Family allowance (25) Privat pensions should be investment/ property income? 10/21/2019

7 The impact of using maps for dissemination….
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8 Dissemination of data Better/more use of data
New users and better feedback Conventional thinking being challanged More interesting for the user as well as for the producer ……… 10/21/2019