In eloualiche/entrydatar: Download and process data of firm entry from BLS, Census, etc...

General information on the dataset

• Downloads data from the Census Business Dynamics Statistics: BDS website.
• The two main data resources are the firm characteristics tables and the establishment characteristics tables
• Codebook is available here

Using the package

For example to start and get the BED industry data:

library(entrydatar)
dt_firm  <- get_bds_cut(1977, 2014, "firm", "all")
dt_firm %>% as_tibble

# A tibble: 38 x 25
    year   firms  estabs      emp    denom estabs_entry estabs_entry_rate estabs_exit estabs_exit_rate job_creation job_creation_births job_creation_continuers job_cr… job_c… job_de… job_des… job_des… job_de… job_d… net_jo… net_jo… real… firmd… firmd… firmd…
   <int>   <int>   <int>    <int>    <int>        <int>             <dbl>       <int>            <dbl>        <int>               <int>                   <int>   <dbl>  <dbl>   <int>    <int>    <int>   <dbl>  <dbl>   <int>   <dbl> <dbl>  <int>  <int>  <int>
 1  1977 3417903 4153792 66091812 63987631       697749              17.1      526010             12.9     13919514             5858902                 8060612    9.20   21.8  9.71e⁶  3909657  5801496    6.10   15.2  4.21e⁶   6.60   30.4 350748 352967 2.22e⁶
 2  1978 3470239 4222683 69670352 67833282       626813              15.0      548965             13.1     14062357             4556103                 9506254    6.70   20.7  1.04e⁷  4283093  6105123    6.30   15.3  3.67e⁶   5.40   30.6 360442 362456 2.12e⁶
 3  1979 3598075 4376325 74016678 71830680       641788              14.9      471892             11.0     14443176             4998519                 9444657    7.00   20.1  1.01e⁷  3639187  6431992    5.10   14.0  4.37e⁶   6.10   28.0 293251 294890 1.67e⁶
 4  1980 3606457 4398753 74749924 74284989       580305              13.2      524356             12.0     12718175             4567680                 8150495    6.10   17.1  1.18e⁷  3948087  7840218    5.30   15.9  9.30e⁵   1.20   31.8 371483 373364 2.12e⁶
 5  1981 3566572 4341224 73539034 73601473       577646              13.2      609342             14.0     12783982             5219017                 7564965    7.10   17.4  1.29e⁷  5037764  7871097    6.80   17.5 -1.25e⁵  -0.100  34.8 365741 367682 2.13e⁶
 6  1982 3603989 4470714 74482223 73952271       679970              15.4      505221             11.5     13640132             6226777                 7413355    8.40   18.4  1.26e⁷  4052461  8527768    5.50   17.0  1.06e⁶   1.40   34.0 289788 290402 1.78e⁶
 7  1983 3688193 4556830 72716864 73461522       570715              12.6      514341             11.4     12154727             4725016                 7429711    6.40   16.5  1.36e⁷  4234634  9409409    5.80   18.6 -1.49e⁶  -2.10   33.0 328482 330449 1.96e⁶
 8  1984 3836247 4722769 77386763 75061635       662923              14.3      503719             10.9     14882807             5379201                 9503606    7.20   19.8  1.02e⁷  3776750  6455800    5.00   13.6  4.65e⁶   6.20   27.2 309350 310909 1.75e⁶
 9  1985 3975680 4876912 80896889 79558329       673580              14.0      530696             11.0     14585960             5364968                 9220992    6.70   18.3  1.19e⁷  4697213  7211629    5.90   15.0  2.68e⁶   3.30   30.0 336927 339182 2.20e⁶
10  1986 4085604 5010299 83467838 82133265       711750              14.4      559089             11.3     15485316             6244185                 9241131    7.60   18.9  1.28e⁷  4733570  8082600    5.80   15.6  2.67e⁶   3.30   31.2 364004 365473 2.39e⁶
# ... with 28 more rows

Or for another cut, say establishments from age sic (see below for the exact code for each cut)

dt_estab <- get_bds_cut(1977, 2014, "establishment", "agesic")
dt_estab %>% as_tibble

# A tibble: 3,249 x 28
    year  sic1 age4              Firms Estabs      Emp    Denom Estabs_Entry Estabs_Entry_Rate Estabs_Exit Estabs_Exit_Rate Job_Creation Job_Creation_Births Job_Cr… Job_C… Job_… Job_D… Job_D… Job_D… Job_… Job_… Net_Jo… Net_Job… Real… d_fl… firm… firm… firmd…
   <int> <int> <chr>             <int>  <int>    <int>    <int>        <int>             <dbl>       <int>            <dbl>        <int>               <int>   <int>  <dbl> <dbl>  <int>  <int>  <int> <dbl> <dbl>   <int>    <dbl> <dbl> <int> <int> <int>  <dbl>
 1  1977     7 a) 0               7479   7591    64866    34491         7306               192           0              0          60750               60750       0    176 176   0           0 0       0     0      60750  176       0       0    NA    NA     NA
 2  1977     7 l) Left Censored  28553  29385   210685   219312            0                 0        7083             21.4        45107                   0   45107      0  20.6 6.24e⁴  28458 3.39e⁴ 13.0  28.4  - 17253 -  7.80   41.2     0  4996  5006  19331
 3  1977    10 a) 0               3662   4440    77072    39356         4347               196           0              0          75432               75432       0    192 192   0           0 0       0     0      75432  192       0       0    NA    NA     NA
 4  1977    10 l) Left Censored  16075  21008   723184   730692            0                 0        3193             14.1       108765                   0  108765      0  14.9 1.24e⁵  50050 7.37e⁴  6.80 16.9  - 15016 -  2.00   29.8     0  1949  1958  20198
 5  1977    15 a) 0              83214  83723   372953   190165        81821               196           0              0         365576              365576       0    192 192   0           0 0       0     0     365576  192       0       0    NA    NA     NA
 6  1977    15 l) Left Censored 300699 305193  3025448  3109120            0                 0       56837             16.9       615519                   0  615519      0  19.8 7.83e⁵ 261504 5.21e⁵  8.40 25.2  -167345 -  5.40   39.6     0 38150 38173 174431
 7  1977    20 a) 0              36857  39676   809767   420084        38800               196           0              0         779366              779366       0    186 186   0           0 0       0     0     779366  186       0       0    NA    NA     NA
 8  1977    20 l) Left Censored 225993 277074 18516415 18433776            0                 0       31186             10.6      1945895                   0 1945895      0  10.6 1.78e⁶ 544425 1.24e⁶  3.00  9.70  165279    0.900  19.4     0 21326 21409 252009
 9  1977    40 a) 0              21528  25312   264124   135285        24749               196           0              0         257679              257679       0    190 190   0           0 0       0     0     257679  190       0       0    NA    NA     NA
10  1977    40 l) Left Censored 100563 138125  4039386  3972134            0                 0       17462             11.9       722946                   0  722946      0  18.2 5.88e⁵ 139602 4.49e⁵  3.50 14.8   134505    3.40   29.6     0 11998 12059  74049
# ... with 3,239 more rows

Detailed documentation

Detail of the data

By national firm characteristics

• Economy Wide all
• Sector sic
• Firm Size sz
• Initial Firm Size isz
• Firm Age age

By geography

• State st
• Metro metrononmetro
• MSA msa

By age interacted with ...

• Age x Size agesz
• Age x Initial Size ageisz
• Age x Sector agesic
• Age x Metro agemetrononmetro

Other data cuts ( in progress )

1. Size by ...
2. Initial size by ...
3. Age x X x Y

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(c) Erik Loualiche

eloualiche/entrydatar documentation built on Aug. 20, 2023, 1:56 p.m.