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

options(width = 999)
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE,
                      cache = FALSE, tidy = FALSE, size = "small")

General information on the dataset

Downloads data from the BED website. Of main importance is the flat file with establishment level count by industry (3 digits naics) every quarter. This page includes all the individual industry tables and the flat file is at the bottom under this url.

Note that there is also a ftp with other data.

Using the package

For example to start and get the BED industry data:

library(entrydatar)
dt_ind <- get_bed("industry", level = T) 

Or if you also want to process the levels (employment and count of establishments):

dt_ind[]

      date_ym naics3 year period ent_emp note1 exit_emp ent_cnt exit_cnt nent_emp nent_cnt ent_lvl_emp exit_lvl_emp ent_lvl_cnt exit_lvl_cnt  tot_count     tot_emp
   1:  199209    111 1992    Q03     4.8     P      4.7    10.9      8.9      0.1      2.0       27754        27031        4171         3402  38266.055   578208.33
   2:  199209    112 1992    Q03     2.3     P      1.6     4.7      4.1      0.7      0.6        3532         2499         736          631  15659.574   153565.22
   3:  199209    113 1992    Q03     3.0     P      3.7     7.1      8.3     -0.7     -1.2        2698         3353         851         1000  11985.915    89933.33
   4:  199209    114 1992    Q03    13.2     P     10.1    20.4     15.4      3.1      5.0        1655         1259         457          344   2240.196    12537.88
   5:  199209    115 1992    Q03     9.8     P      7.8    10.5      9.7      2.0      0.8       25944        20799        1337         1232  12733.333   264734.69
  ---                                                                                                                                                              
8696:  201706    721 2017    Q02     0.9     P      0.9     3.6      4.0      0.0     -0.4       18235        17749        2278         2518  63277.778  2026111.11
8697:  201706    722 2017    Q02     1.9     P      1.4     3.6      3.5      0.5      0.1      219145       158658       20349        19916 565250.000 11533947.37
8698:  201706    811 2017    Q02     1.6     P      1.6     3.9      4.0      0.0     -0.1       21313        21280        7819         8057 200487.179  1332062.50
8699:  201706    812 2017    Q02     1.9     P      1.7     4.3      4.3      0.2      0.0       27266        25570        8321         8283 193511.628  1435052.63
8700:  201706    813 2017    Q02     1.1     P      1.0     3.0      3.2      0.1     -0.2       14714        13594        3934         4156 131133.333  1337636.36

Where does the data come from

Take for example industry naics = 111, Crop Production. The data comes from two tables:

head(dt_ind[ naics3 == "111"])

   date_ym naics3 year period ent_emp note1 exit_emp ent_cnt exit_cnt nent_emp nent_cnt ent_lvl_emp exit_lvl_emp ent_lvl_cnt exit_lvl_cnt tot_count  tot_emp
1:  199209    111 1992    Q03     4.8     P      4.7    10.9      8.9      0.1      2.0       27754        27031        4171         3402  38266.06 578208.3
2:  199212    111 1992    Q04     4.0     P      5.1     8.2     11.1     -1.1     -2.9       22055        27995        3128         4193  38146.34 551375.0
3:  199303    111 1993    Q01     4.9     P      4.2    10.4      9.3      0.7      1.1       26148        22265        3883         3478  37336.54 533632.7
4:  199306    111 1993    Q02     5.2     P      4.0    10.6      8.6      1.2      2.0       29233        22413        4022         3281  37943.40 562173.1
5:  199309    111 1993    Q03     5.0     P      4.5    10.6      8.4      0.5      2.2       28777        26201        4143         3272  39084.91 575540.0
6:  199312    111 1993    Q04     4.0     P      4.7     7.7     10.6     -0.7     -2.9       22228        26235        2966         4094  38519.48 555700.0

Table 7

• Private sector establishments by direction of employment change, as percent of total establishments, seasonally adjusted
• ent_cnt is Establishment gaining jobs, Opening establishments
• exit_cnt is Establishment losing jobs, Closing establishments
• nent_cnt is the difference between the number of opening establishments and the number of closing establishments.

Crop Production (Percent)
                                            Establishments gaining jobs           Establishments losing jobs
Year  3 months ended  Net change(2)  Total    Expanding      Opening       Total    Contracting       Closing
                                           establishments establishments         establishments   establishments

1992  September            2.0        43.4       32.5          10.9         41.4       32.5             8.9
      December            -2.9        37.5       29.3           8.2         43.8       32.7            11.1

1993  March                1.1        42.9       32.5          10.4         39.5       30.2             9.3
      June                 2.0        43.4       32.8          10.6         39.6       31.0             8.6
      September            2.2        43.5       32.9          10.6         40.5       32.1             8.4
      December            -2.9        37.5       29.8           7.7         43.6       33.0            10.6

Table 3

• Private sector gross job gains and losses, as a percent of employment, seasonally adjusted
• ent_emp is Gross job gains, Opening establishments
• exit_emp is Gross job losses, Closing establishments
• nent_emp Net change is the difference between total gross job gains and total gross job losses.

Crop Production (Percent)
                                                  Gross job gains                       Gross job losses
Year  3 months ended  Net change(2)  Total    Expanding      Opening      Total     Contracting      Closing
                                           establishments establishments           establishments establishments

1992  September           -1.4       32.4        27.6           4.8        33.8        29.1             4.7
      December            -2.0       29.1        25.1           4.0        31.1        26.0             5.1

1993  March                0.6       28.7        23.8           4.9        28.1        23.9             4.2
      June                 3.0       31.7        26.5           5.2        28.7        24.7             4.0
      September           -0.8       31.2        26.2           5.0        32.0        27.5             4.5
      December            -0.7       29.4        25.4           4.0        30.1        25.4             4.7

Some more details about where the data actually comes from:

Table 5

Crop Production                                                                      
                                            Establishments gaining jobs           Establishments losing jobs
Year  3 months ended  Net change(1)  Total    Expanding      Opening       Total    Contracting       Closing
                                           establishments establishments         establishments   establishments

1992  September            769      16,623     12,452         4,171       15,874     12,472           3,402
      December          -1,065      14,226     11,098         3,128       16,587     12,394           4,193

• Number of private sector establishments by direction of employment change, seasonally adjusted
• The variable ent_cnt (and respectively exit_cnt and nent_cnt) is the ratio of establishments gaining jobs: opening establishments over the total number of establishments both gaining jobs and losing jobs adjusted for their share in the total number of establishments in the economy
• Example for 1992Q3: Opening establishments is 4171. Total establishments gaining jobs is 16623. The fraction of total establishments gaining jobs is 43.4% (see Table 7). So the entry rate is 4171 / (16623 / 0.434) = 10.9%

Table 1

Crop Production                                                                      
                                                  Gross job gains                       Gross job losses
Year  3 months ended  Net change(1)  Total    Expanding      Opening      Total     Contracting      Closing
                                           establishments establishments           establishments establishments

1992  September         -7,856    187,375     159,621        27,754     195,231     168,200          27,031
      December         -11,035    160,672     138,617        22,055     171,707     143,712          27,995

• Number of private sector establishments by direction of employment change, seasonally adjusted
• The variable ent_emp (and respectively exit_emp and nent_emp) is the ratio of establishments gaining jobs: opening establishments over the total number of establishments both gaining jobs and losing jobs adjusted for their share in the total employment of establishments in the economy
• Example for 1992Q3: Employment gains for opening establishments is 27,754. The fraction of total establishments gaining jobs is 32.4% (as a fraction of employment, see Table 3). So the employment weighted entry rate is 27754 / (187375 * 0.324) = 4.6%.

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Other elements in the package (Work in Progress)

All the flat files are available here. Of main importance is the doc To find a series it is important to read the series ID, for example BDS0000000000000000210101LQ5 which can be broken out into:

• data abbreviation: BD
• seasonal_code: S Seasonally adjusted, U Not seasonally adjusted
• msa_code: 00000 National
• state_code: 00 U.S. totals, see docs
• county_code: 000
• industry_code: 000000 Total Private, see doc for breakdown by naics two and three digits.
• unitanalysis_code: 1 Establishment
• dataelement_code: 1 Employment, 2 Number of Establishments
• sizeclass_code: 00: All size classes and see docs for other
• dataclass_code: 01 Gross Job Gains, 02 Expansions, 03 Openings, 04 Gross Job Losses, 05 Contractions, 06 Closings, 07 Establishment Births, 08 Establishment Deaths
• ratelevel_code: L Level, R Rate
• periodicity_code: A Annual, Q Quarterly
• ownership_code: 5 Private Sector

To be able to get all these series the code is required to download the full flat file which can be quite heavy (requires confirmation).

library(entrydatar)
dt_ind <- get_bed_detail("industry")
dt_ind[]

Other information

Business Employment Dynamics Program Contacts is available via email at: [e-mail] or by phone on 202-691-6553.

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1. Erik Loualiche

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