ols1 <- plm(incomedata ~fintechindex+infaction+Tfinance+uemployment,model="pooling",data=fintechindex)
Error in model.frame.default(terms(formula, lhs = lhs, rhs = rhs, data = data, :
invalid type (list) for variable 'incomedata'
str(incomedata)
'data.frame': 7 obs. of 30 variables:
tjincome : num 9224 11307 12894 15727 16538 ...
hbincome : num 20394 24516 26575 29421 29806 ...
sxincome : num 9201 11238 12113 12761 12766 ...
nmgincome : num 11672 14360 15881 17770 17832 ...
lnincome : num 18457 22227 24846 28627 28669 ...
jlincome : num 8668 10569 11939 13803 14063 ...
hljincome : num 10369 12582 13692 15039 15084 ...
shincome : num 17166 19196 20182 23568 25123 ...
jsincome : num 41425 49110 54058 65088 70116 ...
zjincome : num 27722 32319 34665 40173 42886 ...
ahincome : num 12359 15301 17212 20849 22006 ...
fjincome : num 14737 17560 19702 24056 25980 ...
sdincome : num 39170 45362 50013 59427 63002 ...
hnincome : num 23092 26931 29599 34938 37002 ...
hubincome : num 15968 19632 22250 27379 29550 ...
hunanincome : num 16038 19670 22154 27037 28902 ...
gdincome : num 46013 53210 57068 67810 72813 ...
gxincome : num 9570 11721 13035 15673 16803 ...
hainanincome: num 2064 2523 2856 3501 3703 ...
cqincome : num 7926 10011 11410 14263 15717 ...
scincome : num 17185 21027 23873 28537 30053 ...
gzincome : num 4602 5702 6852 9266 10503 ...
ynincome : num 7224 8893 10309 12815 13619 ...
xzincome : num 507 606 701 921 1026 ...
shanxiincome: num 10123 12512 14454 17690 18022 ...
gsincome : num 4121 5020 5650 6837 6790 ...
qhincome : num 1350 1670 1894 2303 2417 ...
nxincome : num 1690 2102 2341 2752 2912 ...
xjincome : num 5437 6610 7505 9273 9325 ...
bjincome : num 14114 16252 17879 21331 23015 ...