Please update your browser.
COVID-19 has rapidly transformed everyday life. 虽然大流行的范围是全球性的,但消费者在当地受到经济影响.
帮助决策者了解COVID-19大流行对当地经济的影响, 我们创建了一个本地商业数据系列,它提供了一个基于地点的本地消费视图. 基于平均每月超过7000万信用卡和借记卡用户的交易, the series provides a view of local commerce spending growth.
可下载的数据和图表显示了16个都市区的年增长率和当地商业支出的增长贡献. “国家”观点被构建为这16个都市区的总体趋势. 对于所有地区,增长是按消费者年龄、产品类型(如.g. restaurants), and channel (i.e. 在线/离线),以帮助当地利益攸关方更好地了解消费者支出在大流行之前和期间的变化.
![Map of America](/content/dam/jpmc/jpmorgan-chase-and-co/institute/infographics/local-commerce-data-series--pandemic-spending/Map_LCI_v3.png)
With spending growth continuing to decline after October 2020, 城市的增长率是自2020年7月之前以来的最低水平
![4月份,所有cbsa的支出都出现了大幅收缩](/content/dam/jpmc/jpmorgan-chase-and-co/institute/infographics/local-commerce-data-series--pandemic-spending/national-all-cbsas-growth-rate.png)
cur_periodid | level | growth_rate |
2019-01 | Atlanta | 0.058200254 |
2019-01 | Seattle | 0.106540533 |
2019-01 | San Francisco | 0.194660931 |
2019-01 | San Diego | 0.127566422 |
2019-01 | Portland | 0.05077627 |
2019-01 | New York | 0.10076935 |
2019-01 | New Orleans | 0.023489644 |
2019-01 | Miami | 0.152645235 |
2019-01 | Phoenix | 0.159069561 |
2019-01 | Houston | 0.080988142 |
2019-01 | Detroit | 0.122944113 |
2019-01 | Denver | 0.119224576 |
2019-01 | Dallas | 0.050891634 |
2019-01 | Columbus | 0.135556388 |
2019-01 | Chicago | 0.118133044 |
2019-01 | Los Angeles | 0.18287275 |
2019-02 | New Orleans | -0.00611204 |
2019-02 | Seattle | 0.034042279 |
2019-02 | San Francisco | 0.170279957 |
2019-02 | San Diego | 0.100428302 |
2019-02 | Portland | 0.01200764 |
2019-02 | Phoenix | 0.094955987 |
2019-02 | New York | 0.070394499 |
2019-02 | Miami | 0.140630709 |
2019-02 | Dallas | 0.05868755 |
2019-02 | Houston | 0.056007999 |
2019-02 | Detroit | 0.140202397 |
2019-02 | Denver | 0.126166108 |
2019-02 | Columbus | 0.151885776 |
2019-02 | Chicago | 0.151411418 |
2019-02 | Atlanta | 0.025092288 |
2019-02 | Los Angeles | 0.156624955 |
2019-03 | New Orleans | -0.034050859 |
2019-03 | Seattle | 0.088329076 |
2019-03 | San Francisco | 0.173368281 |
2019-03 | San Diego | 0.109601782 |
2019-03 | Portland | 0.025262182 |
2019-03 | New York | 0.065281676 |
2019-03 | Miami | 0.148698845 |
2019-03 | Phoenix | 0.102947795 |
2019-03 | Houston | 0.049703928 |
2019-03 | Detroit | 0.130299703 |
2019-03 | Denver | 0.0983242 |
2019-03 | Los Angeles | 0.16726163 |
2019-03 | Dallas | 0.037930532 |
2019-03 | Columbus | 0.147366423 |
2019-03 | Chicago | 0.139137398 |
2019-03 | Atlanta | 0.021701731 |
2019-04 | San Francisco | 0.185532465 |
2019-04 | San Diego | 0.187287152 |
2019-04 | Portland | 0.161834647 |
2019-04 | Phoenix | 0.186276205 |
2019-04 | New York | 0.193287375 |
2019-04 | New Orleans | 0.139805074 |
2019-04 | Miami | 0.166560426 |
2019-04 | Seattle | 0.19470071 |
2019-04 | Houston | 0.137441359 |
2019-04 | Detroit | 0.188267109 |
2019-04 | Denver | 0.201827841 |
2019-04 | Dallas | 0.244084188 |
2019-04 | Columbus | 0.21858702 |
2019-04 | Chicago | 0.17446428 |
2019-04 | Atlanta | 0.18238502 |
2019-04 | Los Angeles | 0.188434426 |
2019-05 | Seattle | 0.180950289 |
2019-05 | San Francisco | 0.176372065 |
2019-05 | San Diego | 0.174837905 |
2019-05 | Portland | 0.14996004 |
2019-05 | Phoenix | 0.161447197 |
2019-05 | New York | 0.145972907 |
2019-05 | New Orleans | 0.127135103 |
2019-05 | Miami | 0.163247804 |
2019-05 | Los Angeles | 0.182043187 |
2019-05 | Detroit | 0.1252134 |
2019-05 | Denver | 0.17815327 |
2019-05 | Dallas | 0.215643562 |
2019-05 | Columbus | 0.153723053 |
2019-05 | Chicago | 0.128130775 |
2019-05 | Atlanta | 0.17541374 |
2019-05 | Houston | 0.111280997 |
2019-06 | New Orleans | 0.101447205 |
2019-06 | Seattle | 0.160328715 |
2019-06 | San Francisco | 0.147355187 |
2019-06 | San Diego | 0.147381997 |
2019-06 | Portland | 0.126136404 |
2019-06 | New York | 0.126184708 |
2019-06 | Miami | 0.128766176 |
2019-06 | Phoenix | 0.138001615 |
2019-06 | Houston | 0.091267004 |
2019-06 | Atlanta | 0.130534515 |
2019-06 | Chicago | 0.118124618 |
2019-06 | Columbus | 0.142265271 |
2019-06 | Los Angeles | 0.156218493 |
2019-06 | Denver | 0.154223443 |
2019-06 | Detroit | 0.118398978 |
2019-06 | Dallas | 0.192394533 |
2019-07 | Seattle | 0.143611913 |
2019-07 | San Francisco | 0.144366914 |
2019-07 | San Diego | 0.149774288 |
2019-07 | Portland | 0.117932096 |
2019-07 | Phoenix | 0.144954957 |
2019-07 | New Orleans | 0.082793632 |
2019-07 | Miami | 0.126786733 |
2019-07 | New York | 0.134241222 |
2019-07 | Houston | 0.112841009 |
2019-07 | Detroit | 0.130703753 |
2019-07 | Denver | 0.163206342 |
2019-07 | Dallas | 0.215842939 |
2019-07 | Columbus | 0.151017251 |
2019-07 | Chicago | 0.123566624 |
2019-07 | Atlanta | 0.136466381 |
2019-07 | Los Angeles | 0.150235659 |
2019-08 | New Orleans | 0.109608079 |
2019-08 | Seattle | 0.139874312 |
2019-08 | San Francisco | 0.130962802 |
2019-08 | San Diego | 0.136249471 |
2019-08 | Portland | 0.125500097 |
2019-08 | Phoenix | 0.135769746 |
2019-08 | New York | 0.123589018 |
2019-08 | Miami | 0.146596653 |
2019-08 | Columbus | 0.144239817 |
2019-08 | Houston | 0.111236313 |
2019-08 | Detroit | 0.127111472 |
2019-08 | Denver | 0.155933864 |
2019-08 | Dallas | 0.205170305 |
2019-08 | Chicago | 0.112574049 |
2019-08 | Atlanta | 0.13158135 |
2019-08 | Los Angeles | 0.150314868 |
2019-09 | Miami | 0.074857548 |
2019-09 | San Francisco | 0.107965394 |
2019-09 | San Diego | 0.120250777 |
2019-09 | Portland | 0.094836512 |
2019-09 | Phoenix | 0.116930292 |
2019-09 | New York | 0.111968439 |
2019-09 | New Orleans | 0.088385249 |
2019-09 | Seattle | 0.107474012 |
2019-09 | Los Angeles | 0.12239335 |
2019-09 | Detroit | 0.092449434 |
2019-09 | Denver | 0.126502876 |
2019-09 | Dallas | 0.185559243 |
2019-09 | Columbus | 0.120482228 |
2019-09 | Chicago | 0.081137815 |
2019-09 | Atlanta | 0.107736859 |
2019-09 | Houston | 0.081141324 |
2019-10 | Seattle | 0.122025039 |
2019-10 | San Francisco | 0.110762981 |
2019-10 | San Diego | 0.127691205 |
2019-10 | Portland | 0.101773636 |
2019-10 | Phoenix | 0.136009795 |
2019-10 | New York | 0.098529228 |
2019-10 | New Orleans | 0.077556599 |
2019-10 | Miami | 0.109083469 |
2019-10 | Houston | 0.104835049 |
2019-10 | Detroit | 0.108936662 |
2019-10 | Denver | 0.127622311 |
2019-10 | Dallas | 0.189640157 |
2019-10 | Columbus | 0.125064823 |
2019-10 | Chicago | 0.095740602 |
2019-10 | Atlanta | 0.110013292 |
2019-10 | Los Angeles | 0.133712907 |
2019-11 | New Orleans | 0.066491216 |
2019-11 | Seattle | 0.096982924 |
2019-11 | San Francisco | 0.075866696 |
2019-11 | San Diego | 0.090303069 |
2019-11 | Portland | 0.073909482 |
2019-11 | Phoenix | 0.099197128 |
2019-11 | New York | 0.083052936 |
2019-11 | Miami | 0.101439515 |
2019-11 | Atlanta | 0.090689726 |
2019-11 | Houston | 0.069346525 |
2019-11 | Detroit | 0.086846822 |
2019-11 | Denver | 0.092081182 |
2019-11 | Dallas | 0.159492591 |
2019-11 | Columbus | 0.102060737 |
2019-11 | Chicago | 0.070110508 |
2019-11 | Los Angeles | 0.104160885 |
2019-12 | New Orleans | 0.099462497 |
2019-12 | Seattle | 0.11553444 |
2019-12 | San Francisco | 0.109451284 |
2019-12 | San Diego | 0.116058859 |
2019-12 | Portland | 0.093744533 |
2019-12 | Phoenix | 0.122426099 |
2019-12 | New York | 0.104500964 |
2019-12 | Miami | 0.105312386 |
2019-12 | Los Angeles | 0.116875027 |
2019-12 | Houston | 0.10997912 |
2019-12 | Detroit | 0.113083445 |
2019-12 | Denver | 0.143825521 |
2019-12 | Dallas | 0.178345636 |
2019-12 | Columbus | 0.122302549 |
2019-12 | Chicago | 0.089880634 |
2019-12 | Atlanta | 0.121659866 |
2020-01 | San Francisco | 0.083807221 |
2020-01 | San Diego | 0.153334302 |
2020-01 | Portland | 0.214388855 |
2020-01 | Phoenix | 0.13407954 |
2020-01 | New York | 0.187590246 |
2020-01 | New Orleans | 0.214145165 |
2020-01 | Miami | 0.117137012 |
2020-01 | Seattle | 0.17923577 |
2020-01 | Houston | 0.12974581 |
2020-01 | Detroit | 0.128390618 |
2020-01 | Denver | 0.206390047 |
2020-01 | Dallas | 0.234639634 |
2020-01 | Columbus | 0.1450886 |
2020-01 | Chicago | 0.110829545 |
2020-01 | Atlanta | 0.242393627 |
2020-01 | Los Angeles | 0.110693868 |
2020-02 | Seattle | 0.30136091 |
2020-02 | San Francisco | 0.130119915 |
2020-02 | San Diego | 0.209503326 |
2020-02 | Portland | 0.293591724 |
2020-02 | Phoenix | 0.224033731 |
2020-02 | New York | 0.235926659 |
2020-02 | New Orleans | 0.25523888 |
2020-02 | Miami | 0.140649748 |
2020-02 | Los Angeles | 0.162071199 |
2020-02 | Detroit | 0.146293703 |
2020-02 | Denver | 0.224440532 |
2020-02 | Dallas | 0.272611768 |
2020-02 | Columbus | 0.164528553 |
2020-02 | Chicago | 0.137247008 |
2020-02 | Atlanta | 0.278349237 |
2020-02 | Houston | 0.170785822 |
2020-03 | New York | -0.062796082 |
2020-03 | Seattle | -0.065536499 |
2020-03 | San Francisco | -0.16428026 |
2020-03 | San Diego | -0.073396514 |
2020-03 | Portland | 0.007520426 |
2020-03 | Phoenix | 0.004895158 |
2020-03 | New Orleans | 0.010061623 |
2020-03 | Miami | -0.116983881 |
2020-03 | Houston | -0.082333659 |
2020-03 | Detroit | -0.113307536 |
2020-03 | Denver | -0.026728358 |
2020-03 | Dallas | 0.002670019 |
2020-03 | Columbus | -0.081463216 |
2020-03 | Chicago | -0.131089477 |
2020-03 | Atlanta | 0.000132238 |
2020-03 | Los Angeles | -0.120640196 |
2020-04 | Seattle | -0.252556278 |
2020-04 | San Francisco | -0.339393276 |
2020-04 | Portland | -0.199443758 |
2020-04 | Phoenix | -0.162044811 |
2020-04 | New York | -0.332145127 |
2020-04 | New Orleans | -0.209087073 |
2020-04 | Miami | -0.283899836 |
2020-04 | San Diego | -0.276892421 |
2020-04 | Houston | -0.267361557 |
2020-04 | Detroit | -0.271561171 |
2020-04 | Denver | -0.251522146 |
2020-04 | Dallas | -0.209237368 |
2020-04 | Columbus | -0.201954607 |
2020-04 | Chicago | -0.248295554 |
2020-04 | Atlanta | -0.248700265 |
2020-04 | Los Angeles | -0.285664846 |
2020-05 | Seattle | -0.201907327 |
2020-05 | San Francisco | -0.297026346 |
2020-05 | San Diego | -0.197025599 |
2020-05 | Portland | -0.158858373 |
2020-05 | Phoenix | -0.080548029 |
2020-05 | New York | -0.238631836 |
2020-05 | New Orleans | -0.110369239 |
2020-05 | Miami | -0.188493511 |
2020-05 | Detroit | -0.108724543 |
2020-05 | Houston | -0.154878032 |
2020-05 | Denver | -0.143437945 |
2020-05 | Dallas | -0.088309987 |
2020-05 | Columbus | -0.080939873 |
2020-05 | Chicago | -0.170097131 |
2020-05 | Atlanta | -0.145353437 |
2020-05 | Los Angeles | -0.221253362 |
2020-06 | Phoenix | -0.049477207 |
2020-06 | New York | -0.151594864 |
2020-06 | Portland | -0.110961234 |
2020-06 | New Orleans | -0.049902747 |
2020-06 | San Francisco | -0.229551089 |
2020-06 | Seattle | -0.151242734 |
2020-06 | San Diego | -0.133007065 |
2020-06 | Miami | -0.075079564 |
2020-06 | Denver | -0.085936423 |
2020-06 | Houston | -0.107664612 |
2020-06 | Detroit | -0.023812369 |
2020-06 | Los Angeles | -0.155582134 |
2020-06 | Dallas | -0.049007557 |
2020-06 | Columbus | -0.018451205 |
2020-06 | Chicago | -0.08330433 |
2020-06 | Atlanta | -0.07284014 |
2020-07 | Seattle | -0.097872853 |
2020-07 | San Francisco | -0.19040968 |
2020-07 | San Diego | -0.119855354 |
2020-07 | Portland | -0.071596287 |
2020-07 | Phoenix | -0.053372162 |
2020-07 | New York | -0.080541923 |
2020-07 | New Orleans | -0.012035514 |
2020-07 | Miami | -0.058751248 |
2020-07 | Houston | -0.112634932 |
2020-07 | Detroit | 0.007676247 |
2020-07 | Denver | -0.07325438 |
2020-07 | Dallas | -0.053206893 |
2020-07 | Columbus | -0.01960377 |
2020-07 | Chicago | -0.048005922 |
2020-07 | Atlanta | -0.062845592 |
2020-07 | Los Angeles | -0.131780042 |
2020-08 | New Orleans | -0.072791943 |
2020-08 | Seattle | -0.11085624 |
2020-08 | San Francisco | -0.192546589 |
2020-08 | San Diego | -0.130473723 |
2020-08 | Portland | -0.099350983 |
2020-08 | Phoenix | -0.06600566 |
2020-08 | New York | -0.105095377 |
2020-08 | Miami | -0.115907512 |
2020-08 | Atlanta | -0.090535561 |
2020-08 | Houston | -0.11862985 |
2020-08 | Detroit | -0.036225471 |
2020-08 | Denver | -0.090129149 |
2020-08 | Dallas | -0.069972996 |
2020-08 | Columbus | -0.055362105 |
2020-08 | Chicago | -0.069441782 |
2020-08 | Los Angeles | -0.143639415 |
2020-09 | New Orleans | -0.052938136 |
2020-09 | San Francisco | -0.166288752 |
2020-09 | San Diego | -0.093712336 |
2020-09 | Portland | -0.091716431 |
2020-09 | Phoenix | -0.03602762 |
2020-09 | Seattle | -0.099510076 |
2020-09 | New York | -0.06005734 |
2020-09 | Miami | -0.016540303 |
2020-09 | Denver | -0.068426714 |
2020-09 | Houston | -0.074718525 |
2020-09 | Detroit | 0.007066663 |
2020-09 | Dallas | -0.043159673 |
2020-09 | Columbus | -0.020588906 |
2020-09 | Chicago | -0.039615155 |
2020-09 | Atlanta | -0.068510129 |
2020-09 | Los Angeles | -0.119734383 |
2020-10 | Seattle | -0.080802999 |
2020-10 | San Francisco | -0.137571566 |
2020-10 | San Diego | -0.088539595 |
2020-10 | Phoenix | -0.031590485 |
2020-10 | New York | -0.060742681 |
2020-10 | New Orleans | -0.06513071 |
2020-10 | Miami | -0.056453265 |
2020-10 | Portland | -0.05313808 |
2020-10 | Houston | -0.080329209 |
2020-10 | Detroit | 0.006890302 |
2020-10 | Denver | -0.059890682 |
2020-10 | Dallas | -0.02524814 |
2020-10 | Columbus | -0.020408824 |
2020-10 | Chicago | -0.037121702 |
2020-10 | Atlanta | -0.053406823 |
2020-10 | Los Angeles | -0.097689411 |
2020-11 | San Diego | -0.108132546 |
2020-11 | Portland | -0.101943136 |
2020-11 | Phoenix | -0.069625924 |
2020-11 | New York | -0.106189313 |
2020-11 | New Orleans | -0.076018776 |
2020-11 | Miami | -0.098599445 |
2020-11 | Los Angeles | -0.115842564 |
2020-11 | Dallas | -0.072564893 |
2020-11 | Detroit | -0.058766485 |
2020-11 | Denver | -0.098943277 |
2020-11 | Columbus | -0.06736115 |
2020-11 | Chicago | -0.091026248 |
2020-11 | Atlanta | -0.087062505 |
2020-11 | San Francisco | -0.141351976 |
2020-11 | Houston | -0.108693479 |
2020-11 | Seattle | -0.122819195 |
While online growth continues to be positive over time, 整体增长主要是线下支出的收缩
![While online growth continues to grow over time, 整体增长主要是线下支出的收缩.](/content/dam/jpmc/jpmorgan-chase-and-co/institute/infographics/local-commerce-data-series--pandemic-spending/national-channel-growth-rate.png)
cur_periodid | level | growth_contribution |
2019-01 | Offline | 0.054711 |
2019-01 | Online | 0.065416 |
2019-02 | Offline | 0.046341 |
2019-02 | Online | 0.057807 |
2019-03 | Offline | 0.053917 |
2019-03 | Online | 0.047614 |
2019-04 | Offline | 0.11833 |
2019-04 | Online | 0.067444 |
2019-05 | Offline | 0.100992 |
2019-05 | Online | 0.05509 |
2019-06 | Offline | 0.093087 |
2019-06 | Online | 0.041793 |
2019-07 | Offline | 0.09182 |
2019-07 | Online | 0.048754 |
2019-08 | Offline | 0.100315 |
2019-08 | Online | 0.034275 |
2019-09 | Offline | 0.069672 |
2019-09 | Online | 0.039566 |
2019-10 | Offline | 0.080409 |
2019-10 | Online | 0.035524 |
2019-11 | Offline | 0.077758 |
2019-11 | Online | 0.012573 |
2019-12 | Offline | 0.056706 |
2019-12 | Online | 0.056801 |
2020-01 | Offline | 0.103059 |
2020-01 | Online | 0.046806 |
2020-02 | Offline | 0.133819 |
2020-02 | Online | 0.060741 |
2020-03 | Offline | -0.08828 |
2020-03 | Online | 0.006651 |
2020-04 | Offline | -0.2937 |
2020-04 | Online | 0.020402 |
2020-05 | Offline | -0.23236 |
2020-05 | Online | 0.047274 |
2020-06 | Offline | -0.17936 |
2020-06 | Online | 0.064189 |
2020-07 | Offline | -0.14659 |
2020-07 | Online | 0.0623 |
2020-08 | Offline | -0.15925 |
2020-08 | Online | 0.054829 |
2020-09 | Offline | -0.13202 |
2020-09 | Online | 0.062691 |
2020-10 | Offline | -0.12224 |
2020-10 | Online | 0.059182 |
2020-11 | Offline | -0.16776 |
2020-11 | Online | 0.067286 |
尽管2020年夏季的消费增长迅速,但在一般商品上的支出(如.g. 百货公司,大型在线零售商)在2020年第四季度显著下降
![食品杂货是唯一一种在整个疫情图表中始终保持正增长的产品类型](/content/dam/jpmc/jpmorgan-chase-and-co/institute/infographics/local-commerce-data-series--pandemic-spending/national-product-growth-rate.png)
cur_periodid | level | growth_rate |
2019-01 | Clothing | 0.136736026 |
2019-01 | Fuel | 0.048069832 |
2019-01 | General Good | 0.132183394 |
2019-01 | Grocery | 0.083942655 |
2019-01 | Home | 0.116628415 |
2019-01 | Leisure | 0.075688835 |
2019-01 | Personal Care | 0.189086127 |
2019-01 | Pharmacy | 0.051023066 |
2019-01 | Professional Consumer | 0.18801602 |
2019-01 | Restaurant | 0.181957235 |
2019-01 | Transportation | 0.204213143 |
2019-02 | Transportation | 0.216945163 |
2019-02 | Restaurant | 0.169333294 |
2019-02 | Professional Consumer | 0.173377454 |
2019-02 | Pharmacy | 0.048384056 |
2019-02 | Personal Care | 0.162024236 |
2019-02 | General Good | 0.118576086 |
2019-02 | Home | 0.07748679 |
2019-02 | Grocery | 0.073642396 |
2019-02 | Fuel | 0.034504132 |
2019-02 | Clothing | 0.097597248 |
2019-02 | Leisure | 0.049143667 |
2019-03 | Personal Care | 0.123107811 |
2019-03 | Transportation | 0.206363518 |
2019-03 | Restaurant | 0.178238347 |
2019-03 | Professional Consumer | 0.158648788 |
2019-03 | Leisure | 0.124811961 |
2019-03 | Pharmacy | 0.03480068 |
2019-03 | Grocery | 0.046472418 |
2019-03 | Home | 0.068696547 |
2019-03 | General Good | 0.100363676 |
2019-03 | Fuel | 0.075522254 |
2019-03 | Clothing | 0.069060841 |
2019-04 | Restaurant | 0.191392403 |
2019-04 | Professional Consumer | 0.23869508 |
2019-04 | Pharmacy | 0.143479308 |
2019-04 | Personal Care | 0.230860181 |
2019-04 | Leisure | 0.235644723 |
2019-04 | Transportation | 0.264454712 |
2019-04 | Grocery | 0.156177301 |
2019-04 | General Good | 0.191667517 |
2019-04 | Fuel | 0.188914006 |
2019-04 | Clothing | 0.186717774 |
2019-04 | Home | 0.155497058 |
2019-05 | Transportation | 0.263921692 |
2019-05 | Restaurant | 0.216413765 |
2019-05 | Professional Consumer | 0.23189898 |
2019-05 | Pharmacy | 0.091581424 |
2019-05 | Personal Care | 0.176889936 |
2019-05 | Leisure | 0.190686482 |
2019-05 | Grocery | 0.124239373 |
2019-05 | General Good | 0.15436382 |
2019-05 | Fuel | 0.144326333 |
2019-05 | Clothing | 0.10791984 |
2019-05 | Home | 0.104035146 |
2019-06 | Personal Care | 0.125905114 |
2019-06 | Transportation | 0.211676198 |
2019-06 | Restaurant | 0.191501787 |
2019-06 | Professional Consumer | 0.19223422 |
2019-06 | Leisure | 0.181950274 |
2019-06 | Pharmacy | 0.066973055 |
2019-06 | Grocery | 0.118666794 |
2019-06 | Clothing | 0.091284306 |
2019-06 | Fuel | 0.092883649 |
2019-06 | Home | 0.085013024 |
2019-06 | General Good | 0.141705501 |
2019-07 | Transportation | 0.181079897 |
2019-07 | Restaurant | 0.16058578 |
2019-07 | Professional Consumer | 0.229955047 |
2019-07 | Personal Care | 0.159555123 |
2019-07 | Leisure | 0.279188573 |
2019-07 | Pharmacy | 0.079228393 |
2019-07 | Grocery | 0.10341264 |
2019-07 | General Good | 0.154849137 |
2019-07 | Fuel | 0.111197829 |
2019-07 | Clothing | 0.072690726 |
2019-07 | Home | 0.132494464 |
2019-08 | Pharmacy | 0.060208304 |
2019-08 | Transportation | 0.14841928 |
2019-08 | Restaurant | 0.189940591 |
2019-08 | Professional Consumer | 0.184435168 |
2019-08 | Personal Care | 0.143991884 |
2019-08 | Fuel | 0.091669401 |
2019-08 | Home | 0.104540864 |
2019-08 | Grocery | 0.121439848 |
2019-08 | General Good | 0.133346726 |
2019-08 | Clothing | 0.065858231 |
2019-08 | Leisure | 0.232851732 |
2019-09 | Personal Care | 0.110290285 |
2019-09 | Restaurant | 0.149452901 |
2019-09 | Professional Consumer | 0.224820574 |
2019-09 | Pharmacy | 0.057046941 |
2019-09 | Transportation | 0.116217832 |
2019-09 | Leisure | 0.233539722 |
2019-09 | Grocery | 0.071852465 |
2019-09 | General Good | 0.118508948 |
2019-09 | Fuel | 0.080860016 |
2019-09 | Clothing | -0.000191038 |
2019-09 | Home | 0.1097657 |
2019-10 | Restaurant | 0.159365256 |
2019-10 | Professional Consumer | 0.1673739 |
2019-10 | Pharmacy | 0.049902732 |
2019-10 | Personal Care | 0.136002076 |
2019-10 | Leisure | 0.233445007 |
2019-10 | Transportation | 0.104256102 |
2019-10 | Grocery | 0.097112049 |
2019-10 | General Good | 0.121627632 |
2019-10 | Fuel | 0.084118766 |
2019-10 | Clothing | 0.027416143 |
2019-10 | Home | 0.099296353 |
2019-11 | Transportation | 0.086035728 |
2019-11 | Restaurant | 0.169538614 |
2019-11 | Professional Consumer | 0.130244718 |
2019-11 | Pharmacy | 0.038705569 |
2019-11 | Personal Care | 0.126502865 |
2019-11 | Leisure | 0.179825664 |
2019-11 | Grocery | 0.096966097 |
2019-11 | General Good | 0.045133442 |
2019-11 | Fuel | 0.101275608 |
2019-11 | Clothing | -0.020299681 |
2019-11 | Home | 0.060070946 |
2019-12 | Pharmacy | 0.055658065 |
2019-12 | Transportation | 0.095593206 |
2019-12 | Restaurant | 0.10743481 |
2019-12 | Professional Consumer | 0.202290203 |
2019-12 | Personal Care | 0.079334242 |
2019-12 | Leisure | 0.197618574 |
2019-12 | Home | 0.14056239 |
2019-12 | Grocery | 0.054579642 |
2019-12 | General Good | 0.147399602 |
2019-12 | Fuel | 0.137448295 |
2019-12 | Clothing | 0.085583152 |
2020-01 | Restaurant | 0.185558793 |
2020-01 | Professional Consumer | 0.194032354 |
2020-01 | Pharmacy | 0.090311653 |
2020-01 | Personal Care | 0.139771474 |
2020-01 | Leisure | 0.261354009 |
2020-01 | Transportation | 0.112517835 |
2020-01 | Grocery | 0.11040293 |
2020-01 | General Good | 0.13942091 |
2020-01 | Fuel | 0.205627545 |
2020-01 | Clothing | 0.070290437 |
2020-01 | Home | 0.121756899 |
2020-02 | Transportation | 0.11309409 |
2020-02 | Restaurant | 0.22065154 |
2020-02 | Professional Consumer | 0.209620966 |
2020-02 | Pharmacy | 0.11893563 |
2020-02 | Personal Care | 0.171743049 |
2020-02 | Leisure | 0.304313487 |
2020-02 | Grocery | 0.165171741 |
2020-02 | General Good | 0.205048916 |
2020-02 | Fuel | 0.229300381 |
2020-02 | Clothing | 0.124247313 |
2020-02 | Home | 0.178156133 |
2020-03 | Pharmacy | 0.154524681 |
2020-03 | Transportation | -0.435912191 |
2020-03 | Restaurant | -0.348104414 |
2020-03 | Professional Consumer | -0.036513636 |
2020-03 | Personal Care | -0.434249513 |
2020-03 | Leisure | -0.209350124 |
2020-03 | Home | -0.035362392 |
2020-03 | Grocery | 0.344261502 |
2020-03 | General Good | 0.032705525 |
2020-03 | Fuel | -0.162551735 |
2020-03 | Clothing | -0.456450929 |
2020-04 | Restaurant | -0.558452188 |
2020-04 | Professional Consumer | -0.187831753 |
2020-04 | Pharmacy | -0.16678114 |
2020-04 | Personal Care | -0.890627396 |
2020-04 | Leisure | -0.457128518 |
2020-04 | Transportation | -0.821620269 |
2020-04 | Grocery | 0.171286768 |
2020-04 | General Good | -0.060208005 |
2020-04 | Fuel | -0.479151387 |
2020-04 | Clothing | -0.659318694 |
2020-04 | Home | -0.116762952 |
2020-05 | Transportation | -0.769779505 |
2020-05 | Restaurant | -0.442605506 |
2020-05 | Professional Consumer | -0.157651725 |
2020-05 | Pharmacy | -0.140180641 |
2020-05 | Personal Care | -0.728741443 |
2020-05 | Leisure | -0.440935973 |
2020-05 | Grocery | 0.161069625 |
2020-05 | General Good | 0.041693619 |
2020-05 | Fuel | -0.365415205 |
2020-05 | Clothing | -0.507310817 |
2020-05 | Home | 0.060362028 |
2020-06 | Pharmacy | -0.08823372 |
2020-06 | Transportation | -0.664116012 |
2020-06 | Restaurant | -0.341096483 |
2020-06 | Professional Consumer | -0.01363751 |
2020-06 | Personal Care | -0.456801958 |
2020-06 | General Good | 0.117536703 |
2020-06 | Home | 0.167090392 |
2020-06 | Grocery | 0.074115929 |
2020-06 | Leisure | -0.367613244 |
2020-06 | Fuel | -0.261064958 |
2020-06 | Clothing | -0.276247211 |
2020-07 | Restaurant | -0.265528356 |
2020-07 | Professional Consumer | 0.01492988 |
2020-07 | Pharmacy | -0.065126608 |
2020-07 | Personal Care | -0.384288224 |
2020-07 | Leisure | -0.382822191 |
2020-07 | Transportation | -0.602961635 |
2020-07 | Grocery | 0.092212218 |
2020-07 | General Good | 0.123785627 |
2020-07 | Fuel | -0.228062128 |
2020-07 | Clothing | -0.164947951 |
2020-07 | Home | 0.130559651 |
2020-08 | Transportation | -0.581209021 |
2020-08 | Restaurant | -0.242716644 |
2020-08 | Professional Consumer | -0.022760621 |
2020-08 | Pharmacy | -0.117078945 |
2020-08 | Personal Care | -0.440756147 |
2020-08 | Leisure | -0.362627242 |
2020-08 | Grocery | 0.038359419 |
2020-08 | General Good | 0.100385257 |
2020-08 | Fuel | -0.230344101 |
2020-08 | Clothing | -0.237625258 |
2020-08 | Home | 0.099877597 |
2020-09 | Pharmacy | -0.088706594 |
2020-09 | Restaurant | -0.203330099 |
2020-09 | Professional Consumer | 0.039867572 |
2020-09 | Transportation | -0.536460155 |
2020-09 | Personal Care | -0.328570946 |
2020-09 | General Good | 0.126673697 |
2020-09 | Home | 0.173694633 |
2020-09 | Grocery | 0.03541159 |
2020-09 | Fuel | -0.228633555 |
2020-09 | Clothing | -0.11079142 |
2020-09 | Leisure | -0.322023556 |
2020-10 | Transportation | -0.529508592 |
2020-10 | Restaurant | -0.165384512 |
2020-10 | Pharmacy | -0.110268433 |
2020-10 | Personal Care | -0.301113705 |
2020-10 | Leisure | -0.333157289 |
2020-10 | Professional Consumer | 0.014353888 |
2020-10 | Grocery | 0.057659939 |
2020-10 | General Good | 0.141516137 |
2020-10 | Fuel | -0.23791192 |
2020-10 | Clothing | -0.118894391 |
2020-10 | Home | 0.112754365 |
2020-11 | Restaurant | -0.271727323 |
2020-11 | Clothing | -0.169407958 |
2020-11 | Fuel | -0.272211885 |
2020-11 | General Good | 0.098621228 |
2020-11 | Grocery | 0.008288792 |
2020-11 | Home | 0.12124383 |
2020-11 | Leisure | -0.322655097 |
2020-11 | Personal Care | -0.367991035 |
2020-11 | Pharmacy | -0.142397783 |
2020-11 | Professional Consumer | 0.028499098 |
2020-11 | Transportation | -0.557641029 |
我们希望这些数据可以更好地了解当前的当地经济状况,并为帮助当地经济复苏的持续努力提供信息. Let us know of any feedback or questions by emailing institute@jpmchase.com.
Frequently Asked Questions
本地商业数据为我们追踪的都市地区零售支出的演变提供了一个视角. In the context of COVID-19, 这些数据使当地利益攸关方能够更好地了解对大流行的初步反应, the path of consumer spending as policy interventions change, 支出正在恢复到大流行前的水平. In more general terms, 地方商业模式揭示了州和地方政府重要财政基础的趋势.
The data are organized in a directory structure by geography. Data that span the 16 metro areas we track are in the National directory. 的子目录中包含每个都市区的相同视图 CBSA directory. 每个数据视图都由图表和相关的数据文件组成.
本地商业数据的用户还应该知道,这些系列是有版本的产品. 我们的目标是在任何给定时间提供我们所能提供的本地商业支出的最佳视图. 在一定程度上,对抽样、报告的度量或属性集进行了更新.g. 频道),将提供较旧版本的数据系列以供比较.
There are 16 metro areas in data:
- Atlanta
- Chicago
- Columbus
- Dallas-Ft. Worth
- Denver
- Detroit
- Houston
- Los Angeles
- Miami
- New Orleans
- New York
- Phoenix
- Portland (OR)
- San Diego
- San Francisco
- Seattle
每个都会区由与相关区域相交的邮政编码集合表示
流行病支出(PS)系列与之前的本地商业指数(LCI)主要在两个方面有所不同. First, 以前的LCI是根据在都市地区内的场所发生的交易计算的.e. the Sellers'/Merchant view). The PS series, by contrast, 是基于居住在特定都市区域内的人执行的交易(i.e. the Buyers'/Consumer view). These two views overlap, but are different in important ways. 除此之外,买家视角更好地报道了网上购物.
The PS series also differs in the sampling approach. 前LCI和PS系列都依赖于一个“稳定队列”的版本。. 前者在目标(e)中拥有完全相同的人口.g. January 2020) and comparison (e.g. January 2019) months in the growth calculation, 而后者只会阻止新客户在一年内加入样本. PS系列的不同之处在于将样品冻结在现状的最后一个月,即2020年2月. See "How are people selected for inclusion into the sample?" for details.
在某种程度上,我们正在寻求估计更广泛经济的增长, we leverage a stable cohort approach. For transactions to be included in our series, 进行交易的人必须在目标月份(e)内清除我们的交易阈值.g. January 2020) and the comparison month in the growth calculation (e.g. January 2019). This approach precludes, for example, 增长是由于一年中新加入样本的人. 这种抽样方法还意味着,用于2020年1月计算的人口可能与用于2019年12月计算的人口不同.
为重点关注大流行的影响,我们将于2020年2月停止更新人口. 因为我们要求人们清除事务阈值以包含在示例中, we would have lost people when everyone pulled back spending. 衡量与大流行病有关的开支削减的影响, 我们冻结我们的样本,以包括那些在2月份超过阈值的人,并在随后的所有月份使用相同的人群.
Acknowledgments
We thank Chris Wheat, Marvin Ward, Lindsay Relihan, James Duguid, Anu Raghuram, 以及Bryan Kim,感谢他们对这一系列数据的制作和分析做出的重大贡献. 我们也感谢澳博官方网站app研究所的同事们提出的意见和建议.