SECCIÓN III FASE CONTRACTUAL
DE LOS CONTRATOS PARA LA ADQUISICION DE BIENES Y/O CONTRATACIÓN DE SERVICIOS
17.1 The revised method which DASA has adopted for estimating employment dependent on UK expenditure has been described. The difficulties with the approach have been aired.
17.2 It is suggested that further work might be undertaken to improve the figures in a number of areas. These include:
(i) Capturing further data on International Collaborative tasks. This is a growing area with the introduction of the international procurement agency OCCAR (Organisation Conjointe de Co-opération en Matière d’Armements). As, under OCCAR, work shares will not apply per programme, assessing sums spent in the UK will be difficult. It is recognised that the treatment of work with international consortia does, prima facie, confuse the “direct” and “indirect” categorisation.
(ii) As part of this review, the decision was taken to suspend publication of the regional estimates. Further work is required to “clean” and update the MJRecs data base, and to include major international collaborative contracts. It has been recommended elsewhere that Commercial Branches should be reminded of the value of these data in their completion of Defform 57s, and the importance of providing the address/es where the work is to be undertaken, not just that of the Head Office. The determination of regional estimates needs further consideration.
(iii) Extending regional estimates to include indirect employees is not easily accomplished. The US approach of apportionments based on contribution to national statistics for manufacturing and ratios of defence expenditure as a proportion of local expenditure is unlikely to provide supportable figures for the UK. The alternative of a gravity model (which it is understood the Canadians have employed) which associates activity with proximity to the direct contractor is also likely to provide suspect figures. The relatively small size of the UK probably means that the scheme will face difficulties. Experiments might be carried out, however, using national data and
questionnaires of some contractors. In some cases (eg electricity) where the service is an interconnected grid across the UK means that local regional employment of the suppliers of the power is not
(v) DASA should consider enhancing how it reports defence exports’ data in UKDS so that the (exports’) figures that are used in the calculation of employment are readily identifiable.
(vi) The introduction of Resource Accounting and Budgeting and
apparent inability to remove VAT payments will severely reduce the accuracy of the figures.
(vii) Attempts might be made to assess the difference between turnover per head for defence contractors compared with others (the
homogeneity assumption). This might use information available to MOD or by contacting ONS. The variation within the civil sector may also be worth exploring.
(viii) The differences in rates between the ABI and the Input-Output Tables are a cause for concern which might be raised again with the ONS. We note that the ONS are planning to do further work on the labour estimates.
(ix) The timing problems of defence payments should be further modelled to see the impact: though variations in rates may swamp some of the effects.
(x) Given the increasing data problems which DASA are likely to face for the reasons described above, it is probably a subtlety to propose further work on the Input-Output matrix, better to reflect the share of intermediate products in output as the US do. The impact of
“merchanting” and need to move elements in the MOD final demand vector might be explored with ONS.
(xi) The ONS, however, should be requested to produce the Analytical Tables more regularly, perhaps annually, and closer to the year to which they apply. Concerns with changing outsourcing in the period would reduce.
(xii) Consideration might also be given to determining confidence limits in the published figures.
REFERENCES
BAE Systems, 2002. Annual Report 2001 BAE Systems.
Braddon, D. 2000. Exploding the Myth? The Peace Dividend, Regions and
Market Adjustment, p170. Harwood Academic Publishers. Amsterdam.
Briscoe, S. 2002. Employment data “have failed to keep up with work
changes”. Financial Times, 6 August 2002
Chalmers M, NV Davies, K Hartley, C Wilkinson. 2001. The Economic Costs
and Benefits of UK Defence Exports, Centre for Defence Economics,
University of York Research Monograph Series 13, November 2001. Cm 344-II, 1988. Statement on the Defence Estimates 1988 2. Defence
Statistics. London: HMSO
CSO, 1992. Standard Industrial Classification of economic activities. Central Statistical Office. London: HMSO
DASA 1984. Revisions to the Statistics of Employment Dependent on
Defence Expenditure. Defence Statistical Bulletin 3, DASA July 1984
EMAD, 2000A Defense-Related Employment of Skilled Labor: An
Introduction to LDEPPS, December 2000. Economic and Manpower Analysis
Division, Office of Secretary of Defense, Pentagon. (Published on the web site www.economics.osd.mil under History and Current Model)
EMAD, 2000B U.S. Defence Purchases: An Introduction to IDEPPS,
December 2000. Economic and Manpower Analysis Division, Office of Secretary of Defense, Pentagon. (Published on the web site www.economics.osd.mil under History and Current Model)
EMAD, 2000C. State-Level Defense Purchases: An Introduction to RDEPPS. December 2000. Economic and Manpower Analysis Division, Office of Secretary of Defense, Pentagon. (Published on the web site www.economics.osd.mil under History and Current Model)
Hartley, K and N. Hooper, 1995. Study of the Value of the Defence Industry
to the UK Economy. A Statistical Analysis for DTI, MoD, SBAC and DMA.
Lecomber, JRC, 1975. A Critique of Methods of Adjusting, Updating and
Projecting Matrices, Chapter 1 of “Estimating and Projecting Input-Output
Coefficients” Edited by R.I.G. Allen and W.F. Gosling, Input-Output Publishing Company: London
Leontief WW, 1936 Quantitative Input and Output Relations in the Economic
Systems of the United States. Review of Economics & Statistics 18(3) 105-25
Leontief, WW, 1941 The Structure of the American Economy, 1919–29. Harvard University Press: Cambridge, Massachusetts
Mahajan, S. (ed) 1997. Input-Output Methodological Guide 1997 Edition. Office for National Statistics: London
Mahajan, S (ed) 2001 United Kingdom Input-Output Analyses 2001. The Stationery Office 2001: London
Millard D, 1994. Input-Output Tables for the United Kingdom 1990. Economic Trends No 489 July 1994. The Stationery Office: London.
Nolan, B 2002 An audit of the Defform 57 entries on MJRecs. Unpublished internal MOD note, DASA: 2002
ONS, 1999. Manufacturing, Production and Construction Inquiries –
Summary Volume. (Data for 1997). Business Monitor PA 1002. Office for
National Statistics: Newport.
ONS, 2001. Definitions. Labour Market Trends, p S3, December 2001. The Stationery Office: London.
Pite C, 1980. Employment and Defence. Statistical News. November 1980 Rolls-Royce, 2002. Rolls-Royce Annual Report 2001.
Ruiz Y, United Kingdom Input-Output Analytical Tables, 1995. Published on the ONS web site (www.statistics.gov.uk) only, May 2002
Sandler T, and K Hartley, 1995. The Economics of Defense. Cambridge Surveys of Economic Literature. Cambridge University Press: Cambridge SIPRI, 2002. SIPRI Military Expenditure and Arms Production Project – May
2002. Available statistics on the value of output and the number of people
employed in arms production in various countries. SPRI web site: http://projects.sipri.se/milex/aprod/national data
UKDS 2001, UK Defence Statistics 2001. The Stationery Office: London UKDS 2002, UK Defence Statistics 2002. The Stationery Office: London
UN, 1999. Handbook of Input-Output Table Compilation and Analysis. Studies in Methods Series F No 74. Handbook of National Accounting. Department of Economic and Social Affairs: Statistics Division.
Annex A
FURTHER DESCRIPTION of the PRODUCT BY PRODUCT USE TABLE
A.1 The Symmetric Domestic (Product by Product) Use table shows which products (the rows) “go into” which products (the columns) as intermediate production. At the bottom of the Use table at basic prices are the product taxes (less subsidies) on the intermediate commodities, imports, and value added (compensation of employees and gross operating surplus). The total of a column is then the total output of that product. To the right of the intermediate products are the final demand columns (eg Gross Fixed Capital Formation, Exports, Households). The sum of a row then is also the total output of a product (ie overall row totals by product equals overall column totals for the same product).
Products X Products X * Note
Financial intermediation services indirectly measured (FISIM) is a complex arrangement so that the information included Input-Output tables for the Financial Intermediation sector reconcile with GDP. See Millard (1994) and Mahajan (2001). The allocation in the Analytical Tables is undertaken at the discretion of ONS. Millard indicates that the “method used for 1990 is equivalent to the one used for 1984 except that for 1990 the allocation of the financial services adjustment to industries was done on the basis of bank deposits and not gross output” (Millard, 1994 p 19).
Taxes less subsidies on production Compensation of employees Gross Operating surplus FISIM * Adjustment
Intermediate
Products Final
Demand
Taxes less subsidies on products
Mahajan, 2001, advises “The Financial Services Adjustment (FSA), as this adjustment was known prior to implementation of the ESA 95 in the UK accounts has been temporarily renamed as FISIM. FISIM will not be fully implemented in the UK accounts until a methodology is agreed by member states under the guidance of Eurostat. FISIM will then be allocated to the different category of users’ expenditure – final consumption expenditure and industries’ intermediate consumption” (Mahajan, 2001, p 91).
A.2 Taking a single column from a (reduced) domestic use table at basic prices (product by product) 1995 (Ruiz, 2002) shows:
Product Intermediate consumption by product group: Weapons and Ammunition £M 1. Agriculture 0.00
2. Mining and quarrying 0.08
3. Manufacturing (other than Weapons & Ammunition)
3a Weapons and Ammunition
224.42 220.37 4. Electricity, gas and water supply 16.16
5. Construction 0.00
6. Wholesale and retail trade 59.75 7. Transport and communication 12.86 8. Financial intermediation, real estate, rent
and business activities 112.77 9. Public administration 0.25 10. Education, health and social work 7.10
11. Other services 2.90
Total consumption 656.66
Import of goods and services 305.90 Taxes less subsidies on products 7.09 Taxes less subsidies on production 7.79 Compensation of employees 363.58
Gross operating surplus 117.25
FISIM adjustment -26.26
A.4 More generally, the Supply and Use tables are used to balance GDP measure, the inclusion of “imputed rental income for owner-occupiers” in the use table may also affect some of the employment calculations. There will be a “distortion” in the output at basic prices per fte, and a reduction in the coefficients for the relevant column in the A matrix.
Annex B EXAMPLE OF THE DERIVATION AND USE OF THE LEONTIEF INVERSE
B.1 In order to show the derivation of the A matrix and Leontief Inverse in a simple example, let us take a 3 sector model with high interdependence (so that the matrix is well populated):
Figure B1: Diagram of Interrelationships on 3 Products (Invented Example) B.2 This level of interdependence would probably mean a high level of
aggregation of the tables, so perhaps the Products here should be thought of as Product Groups. The loops in the above indicate those products from the group used in producing the products themselves – for example aircraft engines being used in aircraft (both are in the same SIC), or perhaps gas being used (for heating) within the gas industry.
B.3 In this example let us ignore all taxes and imports, and take it that the Supply table (which is not derived or shown) contains only diagonal elements, ie that there are no secondary products. We can represent the above in a Symmetrical Use table as follows:
Product
A Product B Product C Total Intermediate Consumption Final Demand Total 2.0 2.0 2.0 16.0 7.0 PRODUCT C Value added 5 Final demand 5.0 3.0 8.0 3.0 1.0 6.0 0.0 PRODUCT B Value added 10 PRODUCT A Value added 10
B.4 Dividing the columns by total output gives: Product A Product B Product C Product A 0.10 0.32 0.30 Product B 0.15 0.24 0.00 Product C 0.25 0.04 0.20 Value added 0.50 0.40 0.50
The top matrix (product by product) is the A matrix. B.5 Total Demand for 1 Unit of Product B
Let us now consider ordering 1 (monetary) unit of final demand of Product B.
So we have one unit of product B. But, to produce this unit we need 0.32 of Product A and 0.24 of product B and 0.04 of product C.
B.6 But to produce:
0.32 of Product A we require 0.032 (ie 0.32 x 0.1) of product A, 0.048 (ie 0.32 x 0.15) of Product B and 0.08 (ie 0.32 x 0.25) of Product C
0.24 of Product B we require 0.0768 (ie 0.24 x 0.32) of Product A, 0.0576 (ie 0.24 x 0.24) of Product B and 0.0096 (ie 0.24 x 0.04) of Product C.
0.04 of product C we require 0.012 (ie 0.04 x 0.3) of Product A, 0 of Product B and 0.008 (ie 0.04 x 0.20) of Product C.
And this goes on, theoretically, to infinity.
B.7 So summarising the requirements for each phase we get: We require 1 (monetary) unit of product B, so
1. We make 1 unit of product B,
2. But to make that we need 0.32 Product A, 0.24 Product B, 0.04 Product C,
3. But to make these we require (Phase 3) (adding the above for the second round):
0.1208 (ie 0.032 + 0.0768 + 0.012) of Product A, 0.1056 (ie 0.048 + 0.0576 + 0) of Product B, and 0.0976 (ie 0.08 + 0.0096 + 0.008) of Product C. etc
So the total transactions to provide 1 product B is stage 1 plus stage 2 plus stage 3 plus stage 4 plus stage 5 etc to stage ∞.
B.8 Matrix Method to Calculate Total Demand From Final Demand
To calculate this “manually” is very difficult, but it may be noticed that the first round is obtained by multiplying the A matrix by the demand vector, thus: A B C A 0.10 0.32 0.30 A 0 B 0.15 0.24 0.00 B 1 C 0.25 0.04 0.20 C 0 Which gives: A 0.32 B 0.24 C 0.04 For the next round we require A times the first round, ie
A B C A 0.10 0.32 0.30 A 0.32 B 0.15 0.24 0.00 B 0.24 C 0.25 0.04 0.20 C 0.04 Which gives: A 0.1208 B 0.1056 C 0.0976
It will be noted that this is exactly what the “manual” approach above gave. The above can be derived as A x A x final demand, ie A2f, which is
identical to A x (Af): the approach which was undertaken above. B.9 This, of course goes on to infinity (see B.7, above), ie:
(I + A + A2 + A3 + A4 +…..+ An ) B = (I – A) –1 (the Leontief Inverse) x B. B.10 Determination of Leontief Inverse
Inverting this matrix, gives: (I – A) –1 =
1.351111 0.595556 0.506667 0.266667 1.433333 0.100 0.435556 0.257778 1.413333 B.11 Matrix calculation of Total Output For Given Vector
So the total output for final demand of 1 product B:
1.351111 0.595556 0.506667 0 0.595556
0.266667 1.433333 0.100 X 1 = 1.433333
0.435556 0.257778 1.413333 0 0.257778
So to make one unit of final demand of Product B, requires total output of 0.595556 of Product A, 1.43333 of Product B and 0.257778 of Product C. B.12 It can then be seen that the outputs of various product groups can be
determined for various levels of final demand.
B.13 So let’s look at total output to produce the final demand in total, from above this is just (I – A) –1 f =
1.351111 0.595556 0.506667 7 20
0.266667 1.433333 0.100 X 16 = 25
0.435556 0.257778 1.413333 2 10
Which was exactly what we started with. B.14 Value Added
In determining the A matrix, we also showed that the value added
represented 0.5 of product A, 0.40 of Product B and 0.50 of product C, so we can work out the value added, using a matrix approach as:
0.50 0 0 20 10
0 0.4 0 X 25 = 10
0 0 0.5 10 5
B.15 Again as we started out. This is trivial in this example, but the same matrix multiplication can be used for any output, so for the 1 unit of Product B of final demand, the value added will be:
0.50 0 0 0.595556 0.297778
0 0.4 0 X 1.433333 = 0.573333
0 0 0.5 0.257778 0.128889
Summing these gives 0.297778 + 0.573333 + 0.128889 = 1.0 (Since total value added equals total final demand, this checks, too.)
Annex C
DASA Categories & Classification of 123 Input-Output industry/product groups by SIC (92) and (80)
DASA