Input–Output Table for India 2013–2014: Based on the New Series of National Accounts Statistics and Supply and the Use Table

Abstract

In our study, we attempt to produce a more up-to-date input–output (I-O) table for India based on the supply and use table (SUT) of the economy and the new series of National Accounts Statistics (NAS). The resulting table has been used to estimate output multipliers for 25 sectors, and these have been compared with multipliers from the last set of I-O officially estimated for the country in 2007–2008. A key difference between the two sets of tables is the inclusion of inputs in the public administration sector in the more recent one, as a result of which the Type-I multiplier of this sector is greater than one in the latter table compared to one in the former. For the same reason, the Type-II multipliers obtained from the 2013–2014 I-O table are broadly higher than those obtained from the 2007–2008 I-O table. Validation has also been done by comparing gross value added (GVA) as a basic price obtained from the national accounts data for 2013–2014 with the GVA arrived at from the constructed I-O table.

JEL Classification: C-67, E01

Keywords

Input – Output Table Supply and Use Table India Multiplier Effects

1. Background to Input–Output Tables in India

While input-output (I-O) tables have been constructed for more than 100 countries, India made a beginning in the early 1950s, when such tables were prepared by individual researchers at both the national and regional (state) levels (Saluja, 1980).¹ However, at the official level, the first national I-O table was prepared for 1968–1969, jointly by the Central Statistics Office (CSO) and the Planning Commission, comprising 60 sectors. Since 1973–1974, the CSO has been constructing and publishing these tables along with auxiliary tables and reports on methodology and data sources at intervals of 5 years, most recently for 2007–2008. These publications include the main tables as well as supplementary tables on input structure and the commodity composition of output; methodology; sources of data; and a brief analysis of the results. The methodology followed is almost the same each year.

Over the years, there has been an improvement in the methodology and reliability of the data required for the construction of I-O tables in India. The published tables for 1989–1990, 1993–1994 and 1998–1999 are for 115 sectors of the economy while for the earlier years these relate to 60 sectors only. The tables for 2003–2004 and 2007–2008 have 130 sectors (CSO, 2012). However, certain issues still need to be resolved.

1.1 Shift to Supply and Use Tables (SUTs) and a New Series of National Accounts Based on the System of National Accounts 2008²

The CSO brought out the new series of National Accounts Statistics (NAS) in January 2015 with the base year being 2011–2012, using new data sources and incorporating some of the recommendations of the System of National Accounts, 2008 (SNA-2008) (CSO, 2015a, 2015b). Along with the new NAS, the CSO for the first time, compiled and published a supply and use table (SUT) with 140 products and 66 industries of the economy for 2011–2012 and 2012–2013. The SUT includes the complete table, the details of the methodology adopted, and the database used (for an early work on SUT for India please see Sharma and Kolli (2011)).

The reason for the above-mentioned shift is highlighted in the Preface of the ‘Note on Compilation for the Years 2011–12 and 2012–13’, which states:

In Indian National Accounts Statistics due to disparate data sources, the GDP derived from the production side and the expenditure side often do not match, and the differences are termed as statistical discrepancies. This can be obviated with the compilation of supply and use tables (SUTs), which offer a detailed analysis of the process of production and the use of goods and services (also treated as products) and the income generated in that production.³

In earlier exercises, the CSO used to produce the ‘make matrix’ and ‘absorption matrix’, which have now been broadly renamed as the SUTs with an emphasis on the methodologies prescribed in SNA-2008.

The SUT framework focuses on the flow of production in an economy showing where goods and services are produced and where they are used as indicators of intermediate consumption, final consumption, gross capital formation and exports. The SUT framework leads to mutually consistent estimates of macroeconomic aggregates such as GDP, components of value added, imports, exports, private final consumption expenditure (PFCE), government final consumption expenditure (GFCE) and gross fixed capital formation (GFCF), among other things. It is, therefore, claimed that SUT provides a better description of the economy at the aggregate level with respect to production processes, interdependencies in production, the use of goods and services, and generation of income through production.

The supply and use equation for any given product in an economy is mathematically expressed as follows:

Output + imports = intermediate consumption + final consumption + gross capital formation (including changes in stocks and valuables) + exports

In order to maintain the mathematical identity, adjustments are needed for price differentials in respect of each items on both sides of the equation to get them converted to the same (purchaser’s) price level. Since output is at basic prices, taxes, net on products need to be added on the left-hand side. Accordingly, the previous equation has to be rewritten as follows:

Output − intermediate consumption + taxes on products − subsidies on products = final consumption (government and private) + gross capital formation (fixed, changes in stocks and valuables) + exports − imports

The PFCE includes both household FCE and the FCE of non-profit institutions serving households (NPISH). It may be noted that the left-hand side and right-hand sides in the previous equation represent the GDP at market prices and the expenditure components of the GDP, respectively.

2. Need for an Input–Output Table for 2013–2014 Based on the SUT

The CSO has not published I-O tables after it published the 2007–2008 tables. It may be mentioned that the application of SUT has been greatly enhanced after conversion of the tables into a symmetrical matrix of flows of commodities [Commodity × commodity: (C × C) matrix]. To fill this vacuum, we have attempted to create a symmetric C × C matrix for 2013–2014 using the SUT of 2012–2013.

3. Methodology

The objective was to prepare a 130 × 130-commodity-commodity matrix comparable to the 2007–2008 I-O tables consistent with the SUT published by the CSO. It may be noted that the SUT has a structure of 140-sector classification of products and 66-sector classifications of industries. Further, the supply table was available at basic prices while the use table was available at purchaser prices; however, the trade and transport margins (TTMs) and taxes on products were available for all 140 commodities in the supply table. The following steps were taken for this exercise.

3.1 Converting Supply and Use Tables into a 130 × 130 Matrix Structure

The 140-sector commodity structure of the SUT was converted into a 130-sector structure by mapping each commodity with the structure of the 2007–2008 absorption and make tables. While there is a direct concordance between most sectors, some sectors need specific care to make the table consistent with the 130 commodity structure. This required both aggregating of certain sectors and splitting some to arrive at a 130-sector structure.

The SUTs have 66 columns of the major sector, of these, agriculture as a whole has one column representing the entire 20 sectors of the I-O structure. The remaining 65 sectors represent industry and services. These 66 sectors were split into 130 sectors, including 20 for agriculture and the rest for industry and services. Within the industry and services sectors, there are several which have a direct concordance with the 130-sector structure. In order to split the 66 sectors, the structure of the 2007–2008 I-O tables were used as a first-round approximation.⁴ Sectors wherein inconsistencies were encountered were adjusted manually. While doing this, it was assumed that distributions at factor cost are not very different from distributions at purchaser prices or basic prices.

The 130 × 130 use table obtained was in purchaser prices and, therefore, needed to be converted into basic prices. This was done by making use of the ratio of basic prices to purchaser prices for each commodity as obtained from the SUT, thus giving us 130 × 130 SUTs at basic prices.

3.2 130 × 130 SUTs at Basic Prices

As mentioned earlier, the 130 × 130 use table is in purchaser price and needed to be converted into basic prices by subtracting the TTM and taxes. This required creating matrices of TTMs and taxes. However, it may be noted that TTMs are not readily available and, therefore, approximate methods were used to create these using the following procedure:

The TTM provided in the SUT was distributed proportionately across products (columns), which gave rise to an approximate TTM matrix. The TTM matrix was then subtracted from the use table.

There are four sub-sectors in transport, namely, railways, air, road and transport services. Thus, including trade, TTM has five components which need to be decomposed. The distribution of aggregate values of these five components has been used to distribute the aggregates of the columns of the TTM matrix into five components of TTM to obtain five row vectors corresponding to five components of TTM. In the absence of appropriate data, at this stage, this was the only way the distribution could be done. However, some adjustments were made based on information available in the SUTs of an earlier year. Nevertheless, there is scope of more work in improving the TTM matrix.

The finalised TTM matrix was subtracted from the 130 × 130 SUT constructed earlier to arrive at the TTM-adjusted use table.

Parallel to the construction of the TTM matrix, a product tax matric was created by distributing aggregate taxes in the SUT in proportion to the distribution of that product across column entries. The tax matric was then subtracted from the TTM-adjusted table to obtain a 130 × 130 table at basic prices.

3.3 Symmetrical Input–Output Table for 2012–2013

These SUTs have been used to prepare the symmetrical I-O table for 2012–2013 by making use of industry technology (Central Statistics Office, 2012; United Nations, 1999).

If A = input–output coefficient matrix that defines the product directly required to produce other products (product × product matrix)

Use matrix = U

Supply matrix = M

Industry output = g

Product output = q

Final demand = YC.

And the matrices with ‘hats’ represent their diagonal matrices.

Then, the use coefficient matrix or product coefficient matrix (product × industry) = B = $U {\hat{g}}^{- 1}$ and the

Market share matrix (industry by product) = D = $M^{'} {\hat{q}}^{- 1}$

Having obtained B and D, the ‘A’ matrix is estimated under industry technology assumption as: ABD

After arriving at the ‘A’ matrix, the product × product matrix and output multipliers are obtained using basic relationships:

q = Bg + YC

g = Dq

Therefore, q = BDq + YC = Aq +YC

(I−BD)q = YC or

(I−A)q = YC

3.4 Updating the Symmetric Product × Product Matrix for 2013–2014

The symmetrical I-O table for 2013–2014 was obtained by making use of estimates of output and value added of different sectors of the economy as obtained from the NAS 2015. The detailed item-wise output for the primary sectors and services sectors are readily available for almost all sectors from the I-O structure. However, the distribution of output and value added needed to be estimated for the manufacturing sector, which is available at the two-digit level, which was done using the structure of the 2012–2013 SUT.

Private final consumption expenditure (PFCE), GFCE and GFCF were obtained from the NAS 2015 and distributed according to the 2012–2013 I-O structure, as mentioned earlier. Data on exports and imports were obtained from the DGC (I&S); imports were directly taken at CIF values while export values were is available on an FOB basis. Both exports and imports were converted to basic prices.

The final balancing of the symmetrical I-O table for 2013–2014 was done with manual adjustments to the change in inventory and input coefficients after a close examination of the entire table.

3.5 Validation

In order to validate the consistency of the new I-O table, two exercises were carried out. First, the gross value added at basic prices (GVA_BP) obtained from the I-O table was compared with the estimates of GVA at basic prices reported in the NAS 2015. It was expected that the overall GVA at basic prices would be in the same order.

The estimates of the output multipliers obtained from the new I-O table were qualitatively compared with those obtained in 2007–2008. For this, two types of multipliers were estimated: Type-I and Type-II. The Type-I estimates take into account direct and indirect impacts, while the Type-II estimates take into account the induced effects in addition to the usual direct and indirect effects.

4. Results and Discussion

For the purpose of this article, the 130 × 130 matrix has been collapsed to a 25 × 25 matrix.⁵ The collapsed sectors are presented in Table A2 and the collapsed 25 × 25 commodity-commodity matrix is presented in Table A4.

4.1 Overall GVA at Basic Price

The overall estimate of the GVA at basic prices obtained from the I-O table constructed for 2013–2014 is ₹104,731,690 million, which compares very closely with the estimates of overall GVA for the same year reported in NAS 2015, which is ₹104,771,420 million.

4.2 Multiplier Analysis

Based on the 25 × 25 matrix, the output multipliers for 2013–2014 were estimated for the 25 sectors and compared with the output multipliers obtained from the official I-O table for 2007–2008. These multipliers are presented in Table 1 and Figures 1 and 2.

Table 1
Sector-wise Aggregate Multipliers Corresponding to the 2013–2014 and 2007–2008 Input–Output Tables

Sl. No. Aggregated Sectors Output Multiplier

2013–2014
2007–2008

Type-I_2013–2014 Type-II_2013–2014 Type-I_2007–2008 Type-II_2007–2008

1 Agriculture 1.49 4.81 1.70 4.49

2 Animal husbandry 1.67 4.93 1.69 4.47

3 Forestry 1.31 4.49 1.30 3.95

4 Fisheries 1.33 4.53 1.34 4.01

5 Fuel minerals 1.97 5.11 1.59 4.19

6 Non-fuel minerals 1.77 4.94 1.34 3.97

7 Manufacturing food and bev. and tobacco 2.37 5.78 2.59 5.32

8 Textiles and leather 2.49 5.64 2.61 5.25

9 Wood and paper products 2.25 5.31 2.34 4.87

10 Rubber, plastic, coke and petroleum products 2.74 5.81 2.46 4.96

11 Chemical and chemical products 2.65 5.76 2.79 5.31

12 Non-metallic minerals products 2.21 5.35 2.36 4.84

13 Metals and metal products 2.84 5.80 2.58 4.99

14 MFG_electrical and non-electrical 2.80 5.78 2.82 5.19

15 Transport equipment 2.69 5.68 3.02 5.39

16 Miscellaneous products 2.86 5.96 2.69 5.17

17 Construction 2.45 5.50 2.36 4.85

18 Electricity and water 2.64 5.69 2.19 4.76

19 Transport, storage and communication 2.33 5.41 2.11 4.57

20 Trade, hotel and restaurant 1.70 4.88 1.58 4.24

21 Banking and insurance 1.55 4.74 1.34 3.99

22 Real estate dwelling and other services 1.72 4.88 1.37 4.03

23 Education 1.48 4.66 1.19 3.88

24 Health 1.80 4.96 1.85 4.45

25 Public administration 1.57 4.76 1.00 3.70

Range and mean of output multipliers based on 25 × 25 input–output matrix

Mean 2.11 5.17 2.01 4.52

Maximum 2.86 5.96 3.02 5.39

Minimum 1.31 3.21 1.00 2.70

Range and mean of output multipliers based on 130 × 130 input–output matrix

Mean 2.29 5.36 2.22 4.84

Maximum 3.62 6.67 5.16 8.43

Minimum 1.11 4.25 1.00 3.73

Sl. No.	Aggregated Sectors	Output Multiplier
1	Agriculture	1.49	4.81	1.70	4.49
2	Animal husbandry	1.67	4.93	1.69	4.47
3	Forestry	1.31	4.49	1.30	3.95
4	Fisheries	1.33	4.53	1.34	4.01
5	Fuel minerals	1.97	5.11	1.59	4.19
6	Non-fuel minerals	1.77	4.94	1.34	3.97
7	Manufacturing food and bev. and tobacco	2.37	5.78	2.59	5.32
8	Textiles and leather	2.49	5.64	2.61	5.25
9	Wood and paper products	2.25	5.31	2.34	4.87
10	Rubber, plastic, coke and petroleum products	2.74	5.81	2.46	4.96
11	Chemical and chemical products	2.65	5.76	2.79	5.31
12	Non-metallic minerals products	2.21	5.35	2.36	4.84
13	Metals and metal products	2.84	5.80	2.58	4.99
14	MFG_electrical and non-electrical	2.80	5.78	2.82	5.19
15	Transport equipment	2.69	5.68	3.02	5.39
16	Miscellaneous products	2.86	5.96	2.69	5.17
17	Construction	2.45	5.50	2.36	4.85
18	Electricity and water	2.64	5.69	2.19	4.76
19	Transport, storage and communication	2.33	5.41	2.11	4.57
20	Trade, hotel and restaurant	1.70	4.88	1.58	4.24
21	Banking and insurance	1.55	4.74	1.34	3.99
22	Real estate dwelling and other services	1.72	4.88	1.37	4.03
23	Education	1.48	4.66	1.19	3.88
24	Health	1.80	4.96	1.85	4.45
25	Public administration	1.57	4.76	1.00	3.70
Range and mean of output multipliers based on 25 × 25 input–output matrix
	Mean	2.11	5.17	2.01	4.52
	Maximum	2.86	5.96	3.02	5.39
	Minimum	1.31	3.21	1.00	2.70
Range and mean of output multipliers based on 130 × 130 input–output matrix
	Mean	2.29	5.36	2.22	4.84
	Maximum	3.62	6.67	5.16	8.43
	Minimum	1.11	4.25	1.00	3.73

Source: Authors’ estimates.

Figure 1

Source: Data from Table 1.

Figure 2

Source: Data from Table 1.

The Type-II multiplier estimates required additional rows and columns to endogenise the effects of income and consumption of final products. It is argued that factor income earned as a result of the production process is ploughed back into the economy in the form of purchases of final products for consumption. Therefore, final consumption expenditure along with value added should also be included in the multiplier matrix to get a more holistic view of interdependence and circular flows in the economy. Such analysis is commonly done in the tradition of social accounting matrix.

Thus, in Equations (1)–(3) presented in the Appendix, the square matrix ‘A’ is called the I-O coefficient matrix, which can be used to obtain the Leontief inverse matrix (I-A)⁻¹. The entries of this inverse matrix are, in fact, the output multipliers, referred as Type-I multipliers and the sum of the column vectors represents the direct and indirect requirements of domestic intermediates for one unit of final demand.

The Type-II multipliers are obtained by endogenising value added and including final consumption expenditure into the ‘A’ matrix. When personal consumption expenditure and its corresponding counterpart, value added, are endogenised, value added becomes the source of revenue to finance final consumption expenditures of the household sector.

The values of Type-I multipliers obtained from the 25 × 25 I-O table for 2013–2014 range from 1.31 to 2.86 with a mean value of 2.11. The Type-II multipliers range from 3.19 to 5.94 with a mean value of 5.15.

It may be noted that the range and mean of disaggregated multipliers for the 2013–2014 I-O table may differ from the aggregated multipliers due to aggregation effects (see Singh & Saluja, 2016 for multipliers for all 130 sectors). In the 130 × 130 matrix, the Type-I output multipliers range from 1.11 to 3.62, with a mean value of 2.29, and the Type-II output multipliers range from 4.25 to 6.67 with a mean value of 5.36 (Table 1). Thus, the mean values are reduced after aggregation. A similar effect is observed in a comparison of the aggregated and disaggregated multipliers for the 2007–2008 I-O tables (Table 1).

5. Comparison of Multipliers from the 2013–2014 I-O Table with Those Obtained from the 2007–2008 Table

Comparing the estimates of multipliers from the 2013–2014 to the 2007–2008 I-O tables (Table 1 and Figures 1 and 2), the following observation can be made:

The Type-I multipliers as well as the Type-II multipliers based on the 2013–2014 I-O table and those from the 2007–2008 I-O table follow broadly a similar trend across sectors in relative terms, as it is evident from plots in Figure 1. However, the absolute values of the Type-I multipliers based on the 2013–2014 I-O table are higher than the multipliers based on the 2007–2008 I-O table in 14 cases. These sectors include forestry; fuel minerals; non-fuel minerals; rubber, plastic, coke and petroleum products; metals and metal products; miscellaneous products; construction; electricity and water; transport, storage and communication; trade, hotel and restaurant; banking and insurance; real estate dwelling and other services; education; and public administration. The maximum difference is observed for public administration where the multipliers based on the 2013–2014 I-O table are 57.1 per cent higher than the multipliers based on the 2007–2008 I-O table. The differences for the other sectors vary in the range of (−) 12.3 per cent in the case of agriculture to 32.5 per cent in the case of non-fuel minerals.

Public administration has a Type-I multiplier of 1.65 in 2013–2014 compared to one obtained from the 2007–2008 I-O table. This is a basic change because earlier I-O tables contained no inputs into public administration and the entire expenditure was considered as value added. In the supply and use framework, this deficiency has been rectified, and therefore, there is a multiplier of more than one, making the 2013–2014 I-O table more relevant, pragmatic and useful.

The Type-II multipliers corresponding to the 2013–2014 I-O and 2007–2008 I-O tables also follow a similar relative pattern across sectors. However, the Type-II multipliers corresponding to the 2013–2014 I-O table are systematically higher than those obtained from the 2007–2008 table. This again is an important difference, resulting from structural changes and modifications in the compilation of the SUT. It may be noted that the Type-I multiplier for public administration has changed from one to 1.65 due to the incorporation of inputs. For the same reasons, the induced effects of all sectors get enhanced in comparison to the Type-II effects obtained from the 2007–2008 I-O table, which contained no multiplier for public administration.

6. Conclusions and Remarks

In this article, an attempt has been made to produce a more recent I-O table for India using the SUT of the economy and the new series of NAS. The resulting I-O table has been used to estimate output multipliers for 25 sectors which have been compared with those obtained from the 2007–2008 I-O table, the most recent official I-O tables prepared by the CSO of India. A comparison of the multipliers shows that the SUT-based I-O table contains better information in terms of more appropriate multipliers for public administration compared to prior I-O tables, because of which the induced effects encompassed in the Type-II multipliers are higher in the new I-O table compared to earlier tables.

Footnotes

Appendix

An input–output (I-O) model is a quantitative technique that represents the linkages and interdependencies between outputs of different sectors of a national/regional economy. The origin of I-O tables is attributed to the work of Wassily Leontief (1906–1999), who earned the Nobel Prize in Economics for the development of this type of analysis. The importance of I-O analysis lies in the powerful mathematical representation of the interdependence of industrial activities provided by Leontief that allows for estimation of the impact of the final demand of any sector on all the other sectors and on the economy as a whole.

Notes

References

Central Statistics Office (2012). Input-output transactions table 2007–08. New Delhi: Central Statistical Organization, Ministry of Statistics and Programme Implementation, Government of India.

Central Statistics Office (2015a). National accounts statistics, 2015. New Delhi: Central Statistics Office, Ministry of Statistics and Programme Implementation, Government of India.

Central Statistics Office (2015b). Changes in methodology and data sources in the new series of national accounts, base year 2011–12 (June 2015). New Delhi: Central Statistics Office, Ministry of Statistics and Programme Implementation, Government of India.

Saluja

M.R.

(1980). Concepts, construction and application of input–output tables for India. New Delhi: Wiley Eastern.

Singh

& Saluja