The Industrial Sectors
In this SAM we have chosen to follow the North American Industry Classification System (NAICS) method of describing industrial sectors. The NAICS system is a six digit classification. The codes are arranged so that major classifications share the same first digit, for instance, agriculture, hunting and forestry all have 1 as the first digit. Crop production sectors all have the same first three digits, 111, while animal products are 112. Our industrial sectoring basically follows the first three digits of the NAICS codes, with some exceptions which we will discuss below. By following the NAICS codes, we are able to match different types of data, like employment data and input output data with a fair degree of accuracy. In the future when the NAICS system is completely adopted, without variation, by the major government statistical entities perfect matching will be possible.
By using the 3-digit NAICS codes as the basis for our sectoring we achieved a very fine (for a SAM) differentiation among sectors.
For a complete display of the names of the sectors, their descriptions and their concordance with the NAICS system, click here.
Major California Industries
The first criterion considered when establishing adequacy of the industrial sectoring is the importance of the industry in terms of its employment and revenue. Tables 1 and 2 display these figures. The largest net output sectors in the state are real estate, retail, computer related manufacturing, business services, banking, transportation, machinery, electronic parts manufacturing, agricultural manufacturing and agriculture. (The correspondence between the sector names and their descriptions is to be found in the appendix table.)
Table 1 Ten Largest Industries According to Value of Total Payment From Other Sectors (in billion$)
Sector
output (in billion)
Ratio to All Industry Output
RETAIL
125.99
6.68%
FIREAL
117.921
6.25%
FIBNKS
74.514
3.95%
CMPMFG
61.346
3.25%
AGRIC
55.693
2.95%
INFOPC
52.288
2.77%
MEDAMB
51.275
2.72%
CMPRTS
51.145
2.71%
WHLDUR
51.043
2.70%
CONOTH
48.734
2.58%
Total output in all industry
1887.199
The ranking of major industries according to the number of employees presented in the table below reproduces results similar to those in the previous table; service and trade industries are the dominant employment sectors for the State. The largest sector’s is 7% of the State’s output.
Table 2 Wage and Salary Workers by Major Industry, 2003
Sector name
Employment
Employment (in million)
Ratio to All Industry Emply
RETAIL
1584938
1.584938
12.74%
PERSRV
619458
0.619458
4.98%
CONOTH
519176
0.519176
4.17%
MEDAMB
498262
0.498262
4.00%
ACCRST
458189
0.458189
3.68%
ACCFST
435385
0.435385
3.50%
ADMTMP
428136
0.428136
3.44%
TRANSP
419580
0.41958
3.37%
BUSSRV
406096
0.406096
3.26%
AGRIC
374047
0.374047
3.01%
Total emply in all industry
12441952
12.441952
Source: JOBS is CA employment by sector, found by averaging employment levels in EDD data over Q2 2002 through Q1 2003
The retail sector has the largest employment in the state with 13% of the employees.
In terms of sectoralization, this scheme has isolated most of the potential targets for tax policy, particularly in the manufacturing sectors. In 1994, the major payers of taxes are given by table 3.
Table 3 Firms Reporting Net Income Subject to State Taxation of $1 Billion or More, 1992 (in thousand $)
Industry
Net income subject to state taxation
Investment and Insurance Companies
5,320,185
Wholesale Trade
4,126,940
Banks and Savings and Loans
3,388,928
Retail Trade
3,341,524
Electric Machinery and Equipment
2,636,639
Communications
2,537,911
Electric, Gas, and Utilities
2,406,728
Business Services
2,091,496
Petroleum, Coal, and Rubber Products
1,761,465
Beverages
1,608,991
Real Estate
1,538,680
Chemicals and Allied Products
1,512,653
Construction
1,088,195
Source: Information reported in California Statistical Abstract, DOF, 1994.
Note: The treatment of taxation sectors remains the same in this SAM as in the 1998 SAM.
All of these sectors are well isolated in our sectoring scheme.
The third criterion considered when establishing the industrial sectoring is the distributive impact of government taxation and spending. In order to trace effectively the impacts of government spending and taxation on the distribution and incidence of production, income, spending and savings in the economy, it is important to establish an industrial sectoring that can be used to map the effects of government policy. The sectoring in SAM distinguishes those industries that clearly stand to benefit from increased government spending from those industries that may incur negative repercussions from such spending.
As a first cut at differentiating the impacts of government policy, it is important to distinguish major taxpayers by size and by type of tax as was done in the previous section. Not only do the major taxpayers represent the primary source of funding for government spending but they also represent important variables in any industrial-development strategy. Targeted tax cuts or even general tax cuts to industry are primary tools in industrial-development incentive policy. The industrial sectoring must explicitly include the major taxpayers in order to trace the impact of such policies.
The industrial beneficiaries of government spending on infrastructure or education are difficult to isolate. Both theory and empirical observation suggest that the benefits of infrastructure and education are diffused throughout the economy. The direct beneficiaries of industrial-development spending are likely to be more narrowly delineated. A primary focus of many industrial-development strategies has been creating employment in wage-premium, high-export industries. Wage-premium jobs have a high salary to education ratio, and the earning effects of local employment are greater for new jobs in wage-premium industries. More jobs at higher wages provide the biggest “payoff” for employment-creation projects. Export industries are targeted because out-of-state earnings can have large economy wide impacts.
California’s largest wage-premium export industries (in 1998) were Aerospace, Motion Pictures, Engineering and Management Consulting, and Computer Software and Systems Development. Even if these industries are not specifically targeted by development incentives, they are important industries to track with the model. The economy wide impact resulting from changes in these industries should be large because they are large employers paying high salaries, making large export earnings.
Again, these sectors are well isolated in our sectoring scheme.
The sectoralization scheme mostly differs from a straight 3-digit NAICS set up by the breakout of energy or pollution important sectors, for instance cement, natural gas distribution and power generation. These sectors were selected for special treatment by ranking the 4 and lower digit NAICS sectors, so far as data would allow, by energy usage and preserving those with high energy usage as sectors by themselves. Table 4 shows the energy purchases by the major energy producing sectors in our final sectoralization.
Table 4.
Industry Total Purchases of Goods from Energy Industries (all $bn)
OILREF
21.46928
PLASTC
0.340307
TEXLTH
0.173429
PROOTH
0.08295
DSTGAS
6.111024
ACCHOT
0.331747
FDPROC
0.172258
PROCOM
0.081157
DISTEL
4.290048
CHMDRG
0.324989
FINOTH
0.155621
CONCRT
0.063585
FIREAL
3.413969
0.314367
ADMBLD
0.144514
PROLEG
0.06302
TRANSP
2.517194
INFOPC
0.314333
WOOD
0.1398
CMPCMM
0.055395
AGRIC
2.334113
WHLNON
0.310282
CONUTL
0.130648
CMPMED
0.05102
OILGAS
2.193922
PRIMTL
0.277611
SCAOTH
0.12783
DSTOTH
0.050288
CONOTH
1.125058
MEDAMB
0.263604
EDUC
0.123511
ACCSPC
0.048594
OTHPRI
0.744965
FINSEC
0.245905
APPREL
0.122085
VEHPRT
0.047999
CHMBAS
0.627995
CONNON
0.223896
ELCTRC
0.120694
INFCOM
0.042115
BUSSRV
0.596703
FIBNKS
0.223319
INDGAS
0.119477
PROADV
0.038759
PERSRV
0.572432
MACHIN
0.222316
FDMFG
0.119465
PROCNS
0.036452
RETAIL
0.56207
CMPMFG
0.217954
CEMENT
0.112848
ADMSEC
0.036121
WHLDUR
0.540194
INFOTL
0.215443
PAPER
0.106925
PROACC
0.031906
CMPRTS
0.518327
BEVTOB
0.209393
WHLAGN
0.106565
AUTOMF
0.024037
FDOTH
0.472232
CHMSPS
0.208917
PROARC
0.101806
PRODES
0.022482
ACCRST
0.469289
RECAMS
0.203625
GLASS
0.099425
ACCBRS
0.020381
CONSTR
0.456687
VEHAER
0.192586
MSCMFG
0.097282
VEHOTH
0.02032
ADMOTH
0.424884
CMPINS
0.19117
LABDNT
0.096067
VEHBDY
0.015226
CONRES
0.379514
MEDSA
0.18653
RECENT
0.095344
VEHSHP
0.012382
ACCFST
0.364136
PRORES
0.185788
INFOTH
0.092498
VEHMFG
0.007515
MTLFAB
0.354626
MEDNRS
0.179013
PLPMLL
0.091634
FINSUR
0.007218
MEDHSP
0.347479
CHMOTH
0.174594
FURN
0.090092
ADMTMP
0.005305
In order to evaluate pollution control, including greenhouse gas control proposals, the automotive sector has been preserved in less than three digit aggregation. Automobile and light truck manufacturing is kept distinct from heavy trucks; and body manufacturing and parts manufacturing are distinct industries.
Producing the Energy Consistent SAM for Industries
The fundamental method for producting the SAM rows and columns for the industries was to use the BEA data for 1997 to create an Input Ouput table for the US. The columns of the US table for each industry were then scaled by the ratio of wages paid in the the industry in California in calendar year 2003 the the ratio in the US in 1997 to produce estimates of the expenditures and revenues of California industry for 2003.
The industry flows estimated from the BEA data are not entirely consistent with the energy flows in CALEB, which are based on energy data. The reasons for the differences include: (1) the fundamentally different sources for the data: data on firms versus data on energy flows and (2) the construction of California from national data described above. In order to make the SAM consistent with CALEB, the CALEB data for energy use were assigned to the SAM sectors, to derive the use of each energy type by each sector in energy units (trillion Btu). Then, these data were combined with 2003 price information to correct the major SAM energy transactions for the actual Btus that changed hands at the actual prices. For example, the purchase of wholesale natural gas by the gas distribution sector (i.e. the payments made by DSTGAS to OILGAS) reflect actual Btus at the average 2003 utility gas procurement price. Further, smaller purchases by end use sectors were also adjusted for the changes in energy prices from 1997 to 2003, which were generally larger than wage inflation.