Value-added disaggregated social accounting matrix for the Indian economy of the year 2007-2008

Pal, Barun Deb; Bandarlage, Jayatilleke S. Article Value-added disaggregated social accounting matrix for the Indian economy of the year 2007-2008 Journal of Economic Structures Provided in Cooperation with: Pan-Pacific Association of Input-Output Studies (PAPAIOS) Suggested Citation: Pal, Barun Deb; Bandarlage, Jayatilleke S. (2017) : Value-added disaggregated social accounting matrix for the Indian economy of the year 2007-2008, Journal of Economic Structures, ISSN 2193-2409, Springer, Heidelberg, Vol. 6, Iss. 14, pp. 1-20, https://doi.org/10.1186/s40008-017-0074-y This Version is available at: https://hdl.handle.net/10419/194881 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Value‑added disaggregated social accounting matrix forthe Indian economy ofthe year 2007–2008 Barun Deb Pal1* and Jayatilleke S. Bandarlage2 1 Introduction The Indian economy is growing fast since the introduction of the economic reform process has been recognized by policy analysts and policy makers (Kotwal etal. 2011; Ahluwalia 2002). However, the poverty and income distributional implications of Abstract India is pioneer in constructing the social account matrices for its economy for various years, but limited efforts have been made to construct a SAM for India with detailed description about types labour input employed in various economic activities and subsequently the distribution of labour income across various households groups. To bridge this gap, we have constructed a 78-sector SAM for India which takes into account 48 types of labour input for economic activities and 80 types of households classes in India. Integrating the existing input–output database of the year 2007–2008, a 78-sector SAM of the year 2007–2008 and unit-level data published by National Sample Survey Office of India. This SAM differs from the existing 78-sector SAM in terms of its sectoral classification and especially the level of disaggregation of value-added and households account. Further, in this study we have illustrated some applicability of this SAM in analysing income inequality across various social groups of households in India and their contribution to the national income of India. It is observed from this SAM that the rural other social category of households constituted 17% of total population in India and contributed 13% of its net national income, whereas the special social category households of rural areas (SC, ST and OBC) contributed significantly lower in India’s NNP than their share in population. Hence, these categories of households in rural India remain unproductive than the other social category of households. Contrary to this fact, the urban counterparts of these social groups of households are more productive in India. We have also estimated the Gini coefficients corresponding to each social group of households as a measure of level of income inequality. Further, the SAM multiplier model has been applied to observe the impact of agricultural growth on rural income and income equality. The estimated Gini coefficients revealed the facts that the growth in paddy crops will lead to high increase with low income inequality among the SC and ST households, whereas for the OBC and other category households the same phenomena is observed corresponding to livestock sector. Keywords: SAM, India, Household category, Value added, Agriculture, Poverty, Income inequality, Inclusive growth Open Access © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. RESEARCH Pal and Bandarlage Economic Structures (2017) 6:14 DOI 10.1186/s40008‑017‑0074‑y *Correspondence: [email protected] 1 International Food Policy Research Institute, NASC Complex, New Delhi 110012, India Full list of author information is available at the end of the article Page 2 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 economic policy reforms have often been the subject of policy debate in India. In order to examine such implications of economic policy reforms, an economy-wide database such as a social accounting matrix (SAM) that includes a detailed component of household income distribution of different socio-economic groups is required. Furthermore, an economy-wide model based on such a detailed database is required to examine the impact of policy reforms on different socio-economic groups in the Indian economy. Therefore, the purpose of this paper is to outline a detailed framework for the construction of an Indian SAM for the year 2007–2008. The main contribution of the proposed SAM is the disaggregation of the value-added component of each sector in Indian economy in a detailed manner. The structure of the rest of the paper is as follows. The section2 provides a brief overview of a SAM and its historical evolution. The section3 describes steps involved in extending the exisitng SAM of the year 2007-08 into a value added disaggregated SAM of the same year for India. Subsequently the consistency of the SAM has been validated using data on key macro economic indicators and this is described in the section4. The section5 briefly described the application of this SAM in analysing income inequality in India. In this section also we have applied the SAM multiplier analysis to assess the impact of sector specific growth on income inequality across various social groups. At the end the section6 concludes this paper by citing the key limitiation of this SAM as well. 2 A brief overview ofSAMs andhistorical evolution ofcompiling SAMs forIndia A social accounting matrix is simply defined as a single-entry accounting system whereby each macroeconomic account is represented by a column for outgoings (payments) and a row for incomings (receipts) (Hayden and Round 1982). It is represented in the form of a square matrix with rows and columns, which brings together data on production, income generation, consumption, investment and external transaction. In a SAM, incomings are indicated as receipts for the row accounts in which they are located and outgoings are indicated as expenditure for their column accounts. Since all incomings must be, in a SAM, accounted for the outgoings, the total of rows and columns must be equal for each account. Taylor and Adelman (1996) sees the SAM as a tabular presentation of the accounting identities, stating that incomings must be equal to outgoings for all sectors of the economy. The SAM is a data system, including both social and economic data for an economy. The data sources for a SAM come from input–output table, national income statistics, and household income and expenditure statistics. Therefore, a SAM is broader than an input–output table and typical national account, showing more detail about all kinds of transactions within an economy. However, an input–output table records economic transactions alone irrespective of the social background of the transactors. A SAM, on the contrary the national accounts, “… attempts to classify various institutions to their socio-economic backgrounds instead of their economic or functional activities” (Chowdhury and Kirkpatrick 1994: 58). The history of SAMs goes back to Stone’s (Stone 1962) pioneering work for the UK. Since the 1970s, Pyatt, Thorbeck and their associates (Pyatt and Roe 1978; Thorbecke and Jung Page 3 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 1996; Pyatt and Round 1979) have extended Stone’s work to developing countries to address distribution issues of economic reforms. As a result, early SAMs were constructed for a number of developing countries such as Sri Lanka (Pyatt and Round 1979), Malaysia (Chander etal. 1980), Botswana (Hayden and Round 1982) and Indonesia (Thorbecke and Jung 1996). As summarized by Hayden and Rounds (1982), three principle motivations underlie compilation of SAMs. Firstly, a SAM assists us to bring together different sources of information to describe the main structural characteristics of an economy. Secondly, a SAM provides a proper accounting framework to identify the link between income distribution and different sectors of an economy. Thirdly, a SAM provides a detailed and comprehensive database to construct a computable general equilibrium (CGE) as a benchmark database. The popularity of SAM has also been recognized in many South Asian countries such as Sri Lanka (Bandara and Kelegama 2008), Pakistan and India (Pal etal. 2012). India was an early leader in compiling SAMs and developing models based on SAMs. To our best knowledge, Sarkar and Subbarao (1981) of National Council of Applied Economic Research (NCAER) constructed the first SAM for India way back in the 1980s, which provided the consistent database for their computable general equilibrium (CGE) model. Subsequently a number of SAMs were constructed over the years for Indian economy by different researchers. Table1 provides a brief overview of the published SAMs and their salient features. It is apparent from the above table that most of the SAMs for India have taken into account the aggregate labour and capital as primary factor input. But the labours are paid according to their level of skill and wage rates also vary across sectors. Again the factor income is key source of income for the households; disaggregation of labours and households will give detailed picture about the income distribution and source of income inequality in India. For example, the income distribution across different social groups of households depends on the amount of capital they are endowed with and the level of skilled labour they supply to different economic activities. Therefore, if a SAM can take into account more disaggregated level of factor income and its distribution across various social groups of households, it will be of intense use for understanding the causes of income inequality and poverty in the Indian economy. Moreover, if we can understand the sectorwise share of income received by various types of labour and their relationship with various types of households, it will help government to prioritize interventions for poverty alleviation in India. However, the available SAMs for India as listed in Table1 are not able to explain this phenomenon. In this regard, the only evidence is obtained from the draft report on “Policy Dilemmas in India: The impact of Agricultural Prices on Rural and Urban Poverty” prepared by Polaski etal. (2008). In this study, the authors have constructed a Micro SAM for India consisting of 115 sectors, 49 primary factors and 352 households. The factors of production are classified into 49 groups according to their social group (SC/ST/OBC), their education level and their sex (male/female). But the base year of this SAM is 1998– 1999 which is too old as compared to current structure of the Indian economy. Given the backdrop of above-mentioned SAM constructed for India, we have decided to construct a latest SAM for India which will take into account detailed structure of value-added income by various sources of labour. As the latest available IO table for Page 4 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 Table 1 Stylized facts ofSAMs ofIndia. Source: Pal etal. (2012) S. no. Name ofresearchers andtheir SAM-based study Salient features ofSAM 1. Sarkar and Subbarao (1981)Base year 1979–1980 Sectors (3 in all) Agriculture, industry and services Agents Non-agricultural wage income class, non-agricultural nonwage income class, agricultural income class and government Factors of production Labour and capital 2. Sarkar and Panda (1986)Base year 1983–1984 Sectors (6 in all) Agriculture (2), industry (2), infrastructure and services Agents Non-agricultural wage income class, non-agricultural nonwage income class, agricultural income class and government Factors of production Labour and capital 3. Bhide and Pohit (1993)Base year 1985–1986 Sectors (6 in all) Agriculture (2), livestock and forestry, industry (2), infrastructure and services Agents Government, non-agricultural wage income earners, nonagricultural profit income earners and agricultural income earners Factors of production Labour and capital 4. Pradhan and Sahoo (1996)Base year 1989–1990 Sectors (8 in all) Agriculture (2), mining and quarrying, industry (2), construction, electricity combined with water and gas distribution and services (3) Agents Government, agricultural self-employed, agricultural labour and non-agricultural self-employed and other labour Factors of production Labour and capital 5. Pradhan et al. (1999)Base year 1994–1995 Sectors (60 in all) Agriculture (4), livestock products (2), forestry sector, mining (4), manufacturing (27), machinery and equipment (6), construction, electricity, transport (2), gas and water supply, other services (11) Agents Government, self-employed in agriculture (rural and urban), self-employment in non-agriculture (rural and urban), agricultural wage earners (rural and urban), other households (rural and urban), private corporate and public non-departmental enterprises Factors of production Labour and capital 6. Pradhan et al. (2006)Base year 1997–1998 Sectors (57 in all) Agriculture (4), livestock products (2), forestry, mining, manufacturing (27), machinery and equipment (6), construction, electricity, transport (2), gas and water supply, other services (11) Agents Government, self-employed in agriculture (rural and urban), self-employment in non-agriculture (rural and urban), agricultural wage earners (rural and urban), other households (rural and urban), private corporate and public non-departmental enterprises Factors of production Labour and capital 7. Sinha et al. (2007a, b)Base year 1999–2000 Sectors (13 in all) Agriculture (informal), formal manufacturing (9), construction (informal), other services (formal and informal) and government service Agents Rural occupation class, 4 urban occupation class, government and private corporations Factors of production Labour and capital 8. Saluja and Yadav (2006)Base year 2003–2004 Sectors (73 in all) Agriculture (12), livestock products (4), forestry, mining (4), manufacturing (28), machinery and equipment (7), construction, energy, gas distribution, water supply, transport (2), other services (10) Agents 5 rural households’ expenditure classes, 5 urban households expenditure classes, private corporation, public enterprises and government Factors of production Labour and capital Page 5 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 India is 2007–2008, we have constructed the proposed SAM for the year 2007–2008. The following section describes in detail about the method construction and data sources. 3 Steps involved inconstructing value‑added disaggregated SAM forthe year 2007–2008 The latest official input–output (IO) table of Indian economy is available for the year 2007–2008 which consists of 130 sectors (CSO 2012). Further, this IO table has been used by Pradhan etal. (2013) to construct a SAM for India for the year 2007–2008 which consists of 78 sectors. Therefore, we have considered the 130-sector IO table, the 2007–2008 SAM, as the basis of our proposed disaggregated SAM for India for the year 2007–2008. Although the basis of our proposed SAM is the available SAM of the Indian economy for the year 2007–2008, they are significantly different in terms of the value-added disaggregation and the household classification. Our proposed SAM is an extension of the existing SAM of the year 2007–2008. As in compiling any SAM, the construction of our proposed disaggregated SAM involves a number of steps and these are explained as follows. Step 1 Identify types of factor input and relevant data for every selected sector of SAM. Step 2 Identify households’ classes and their source of income from various primary factors. Step 3 Itemwise consumption expenditure of various households groups. Step 4 Estimate sources of income other than factor income for various categories of Indian households. Step 5 Balancing the database and consistency checks. The detailed description of these steps is given in the subsequent paragraphs of this paper. Table 1 continued S. no. Name ofresearchers andtheir SAM-based study Salient features ofSAM 9. Pal et al. (2012)Base year 2003–2004 Sectors (85 in all) Agriculture and allied sectors (21), mining (9), manufacturing (23), machinery and equipment (9), construction, electricity (3), biomass, water supply, transport (5), other services (12) Agents 5 rural households’ occupation classes, 4 urban households occupation classes, private corporation, public enterprises and government Factors of production Labour, capital and land 10. Pradhan et al. (2013)Base year 2007–2008 Sectors (85 in all) Agriculture and allied sectors (22), mining (9), manufacturing (29), machinery and equipment (3), construction, electricity, water supply, transport (4), other services (18) Agents 5 rural households’ occupation classes, 4 urban households occupation classes, private corporation, public enterprises and government Factors of production Labour, capital and land Page 6 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 3.1 Step 1: identify types offactor input andrelevant data forevery selected sector ofSAM For the proposed disaggregated SAM, we have disaggregated only the labour input into 48 various types of labour. Here we have used region, social class, education and gender as four indicators to classify the labour input. The detail about these indicators is given in Table2. Once we classify the types of labour according to their location, social status, level of education and gender, our next task is to obtain data on payment for these types of labour by different sectors. In this case, we have estimated the distribution of labour payment across the SAM sectors by using the unit-level households survey data on employment and unemployment situation in India. The National Sample Survey Organization (NSSO) of India conducts detailed household survey in every 5years separately for consumption expenditure and employment unemployment situation in India. The 68th round survey data for the year 2011–2012 are latest available quinquennial survey data for both consumption expenditure and employment–unemployment situation in India. Prior to the 68th round survey, immediate latest quinquennial survey data are available for the year 2009–2010 (66th round) and for the year 2004–2005 (61st round). Therefore, it was challenging for us to select a database to fulfil the data need for this proposed SAM. It is also worth noting that the Indian economy has experienced 9% GDP growth during the periods from 2005–2006 to 2007–2008. Although the real GDP growth dipped down at 6.7% level in the year 2008–2009, it has reached more than 8% level and continued at that level till 2011–2012 (CSO 2012). Now with the faster economic growth between 2004–2005 and 2011–2012, structure of the economy has also changed and hence the structure of employment. Table3 presents the compound annual growth rate (CAGR) of employment between the year 2004–2005 and 2011–2012. Table3 shows that the employment in agriculture sector has fallen during this period at a rate of 1.55%, Table 2 Description ofindicators toclassify labour input Region (2)×Social class (4)×Education (3)×Gender (2)=48 Region Social class Education Gender Rural Schedule caste (SC) Illiterate Male Urban Schedule tribe (ST) Up to high school Female Other backward class (OBC) Graduate and above Others Table 3 Sector‑specific employment growth between2004–2005 and2011–2012 (CAGR) Activities Male (%) Female (%) Total (%) Agriculture −1.60 −1.51 −1.55 Mining and quarrying −2.57 5.96 0.00 Manufacturing 0.36 2.23 1.35 Electricity, water, etc. 5.96 0.00 4.20 Construction 9.70 23.57 13.06 Trade, hotel and restaurants −0.52 2.64 0.26 Transport, storage and communications 1.44 0.00 1.37 Other services 1.39 4.20 2.56 Page 7 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 whereas it has increased significantly at a rate of 13% in the construction sector. Apart from that, other sectors also experience positive growth in employment between the year 2004–2005 and 2011–2012. Now since the base year of our proposed SAM is 2007–2008, the NSSO 61st round data will not capture the structural change happened during the golden periods of Indian economy during post-2004–2005 periods. Again as there was severe drought in India in the year 2009–2010, the 66th round quinquennial survey has been updated with 68th round survey for the year 2011–2012. Therefore, to capture the structural change in Indian economy during post-2004–2005 period, we have selected NSSO 68th round data to estimate required data for our proposed SAM of India for the year 2007–2008. The NSSO employment survey classifies industries at the 5-digit level as described in National Industrial Classification (NIC) guideline. The households demographic and social profile data of the same survey have been first organized to classify the types of labour according to the description as mentioned in Table3. Further, we have aggregated the industries according to their map of concordance with the sectors of our proposed SAM. In this context, the map of concordance between the sectors of our proposed SAM and the NIC 5-digit classification of industries is given in “Appendix 1”. 3.2 Step 2: identify households’ classes andtheir relationship withvarious primary factors To make our value-added disaggregated SAM useful for poverty analysis, understanding structure of consumption expenditure across various social classes of households is important. Therefore, we have classified households into 80 different classes. In Table4, we have listed various indicators which have been used to classify households. After classifying households according to the above-mentioned categories of classes, we have estimated sources of income of these households from different types of labour and capital. It is also important to note that household’s typewise data on capital stocks are not readily available for Indian economy. Therefore, we have used the income of selfemployed and own account category of households as proxy of the capital income. Now to estimate the capital income this way, we have cross-tabulated the NSSO 68th round employment–unemployment survey data between households categories (using demographic profile) and types of labour (using status of work profile of the households). Again to obtain the income of the households from different types of labour, we have Table 4 List ofindicators toclassify households Region (2)×Social class (4)×MPCE (10)=80 Region Social class MPCE deciles class Rural Schedule caste (SC) MPCE1 Urban Schedule tribe (ST) MPCE2 Other backward class (OBC) MPCE3 Others MPCE4 MPCE5 MPCE6 MPCE7 MPCE8 MPCE9 MPCE10 Page 8 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 prepared another cross-table between the household categories and the types of labour we have defined for our study purpose. 3.3 Step 3: itemwise consumption expenditure ofvarious households groups To complete the construction of consumption block of this proposed SAM, we have used National sample survey (NSS) 68th round data on households’ consumption expenditure. But the descriptions of commodities in these databases are different than the sectors of our proposed SAM. So to overcome this problem also, we have used the map of concordance between the NSSO items and SAM sectors as given by Pradhan etal. (2013). 3.4 Step 4 andStep 5: estimating households income fromother sources andbalancing the SAM In the above-mentioned steps, we have estimated the required data for our proposed SAM especially for those accounts which make this SAM significantly different from others. Now in this step, we have completed the construction by obtaining data on households’ income other than factor income. This includes transfer income from government, interest receive from public bonds and remittances from the abroad. To obtain these data corresponding to the different category of households, we have first taken the aggregate data from 2007 to 2008 SAM and then distributed it among the different class of households according to their share in aggregate consumption expenditure as obtained in the previous step. Therefore, by following above-mentioned steps we have constructed a value-added disaggregated SAM for India for the year 2007–2008 which consists of 171 rows and column. The entire SAM is given as the supporting document along with this paper (Additional file1: Appendix S1). But construction of proposed accounts for this SAM with NSSO data does not ensure that this SAM is balanced. This implies the row total is not equal to corresponding column total, because the NSSO data are obtained through primary sample survey and are available in market price, whereas data presented in IO table are based on factor price. Therefore, to make this SAM balanced we have followed following two steps. First, estimate the distribution patterns for households factor income from different types of labour and itemwise consumption expenditure and sector wise labour payment using the NSSO data. Secondly, a prorata adjustment method has been applied to distribute the aggregated data of existing 2007–2008 SAM according the distribution pattern. Thus, we have adjusted the NSSO data with the aggregate-level data on household income, consumption expenditure and sectorwise labour payment as obtained from the existing SAM of the year 2007– 2008 to complete the construction procedure. 4 Validation ofthe value‑added disaggregated SAM The construction of value-added disaggregated SAM, as described above sections, requires data from different secondary sources. For example, the National Accounts Statistics (NAS) provides aggregated data for most of the macroeconomics indicators such as gross domestic product (GDP), private final consumption expenditure, households’ savings, government savings, corporate savings, savings of the public non-departmental Page 15 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 the households of those classes than the growth in other sectors. In totality, the rural income inequality will be lower, i.e. 0.17, due to growth in paddy crops than the growth in other activities reacted to agriculture and listed in this above table. It is also interesting to observe that the growth in pulses crops will lead to overall growth in income by 0.807 unit which is lower than other farm-related activities but higher than the growth in food processing industry, i.e. 0.723. Yet again the growth in income due to growth in pulses crops leads to rise in rural income inequality (i.e. 0.38) than the growth in paddy (0.17), livestock (0.23) and even vegetables crop (0.32). Moreover, growth in pulses crop leads to rise in income inequality among various social groups of households. The SAM multiplier is a static observation for the year 2007 and is highly influenced by the social and economic structure of the Indian economy. Cereals being a principal crop in Indian agriculture (especially paddy) and paddy being the major staple food for most of the India, a large share of agricultural land is employed for this crop cultivation. As a result, the growth in paddy crop leads less income inequality among the rural households in India. Further, the pulses crops are dominated in arid and dry agro-climatic zones in India, and due to such in equal distribution of pulses growers, the income effects also lead to rise in income inequality in Indian economy. Therefore, unless the area under pulses increases in other parts of the country the inequality in rural income cannot be reduced. In this context, Government of India has integrated pulses crop under national food security mission to promote pulses crops in India and rice fallow region of eastern India is also the prime focus for pulses production. Once achieved, we may expect reduction in income inequality within the rural area. It is also to be noted that the Indian economy has been moving through the structural transformation process since 1991, but to reduce the income inequality, a structural transformation is required within the agriculture sector with more focus towards livestock and pulses crops. 6 Conclusion The SAM has been applied by various developed and developing countries since its inception in the academic literatures by the pioneer work by Stone (1962). India is not exception to this and it has been adopted as a policy planning tool for its government during decades of 1980s and 1990s. Despite this, limited effort has been made to extend the existing structure of a SAM with more detailed accounts so that more micro-level analyses can be done with the focus of inclusive growth. In this context, our attempt to construct a value-added disaggregated SAM for India fills the gap in macroeconomic database. Again the brief description about application of this SAM gives an overview of the social structure of the Indian economy and their contribution to the national income. Another important application of this SAM is that we have shown in this study by estimating Gini coefficient for each social group of households. It is also important to note here that the database presented in this SAM is robust as it is consistent with the official macroeconomic data of the Indian economy. Moreover, the analysis on income inequality, using this SAM data, does not diverge from theoretical foundation of Kuznets curve as well as the reality of the Indian economy. Furthermore, this value-added disaggregated SAM can be applied as balanced data source for a computable general equilibrium (CGE) model especially to analyse various Page 16 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 policy options on social inclusion and inclusive growth. The analysis can also be done to understand the impact on types of labour demand (skilled and unskilled) due to various policies. The demand of such types of analyses is crucial for the developing country such as India to guide her policy makers with suitable policy options to achieve sustainable goal. However, addressing this issue requires further research using this database. However, constructing such a disaggregated level of SAM database is a tedious job and requires readily available data. Although we have made a challenging attempt to adjust the data obtained from different sources into a single matrix form, this task can be made more easily if Government of India can publish its IO table regularly corresponding to each NSSO rounds survey. Hence, the novelty of the SAM lies on its level of disaggregation and further research is needed to make the data available and their applicability in policy making. This issue is also important for the developing country as they are planning to move towards sustainable development goals. Last but not the least, the SAM multiplier analysis can be extended by including more crops or economic economics to identify key economic activities to reduce rural income inequality as more than 70% population in India are living in rural areas. However, this analysis can be made more robust if we can have a SAM of the latest year, say, for the year 2014–2015. A latest available SAM will help us to observe the recent structural transformation and its impact on rural income inequality in India. Therefore, Indian IO table is available at a regular interval to conduct such types of robust analysis for the benefit of the scholars and policy makers across the world. Authors’ contributions Both the authors contributed to this article. Both authors read and approved the final manuscript. Author details 1 International Food Policy Research Institute, NASC Complex, New Delhi 110012, India. 2 Department of Accounting, Finance and Economics, Griffith Business School, Griffith University, Building N50, Room 1.55 Nathan Campus, 170 Kessels Road, Nathan, QLD 4111, Australia. Acknowledgements We deeply express our sincere thanks to Professor Ross Guest Head, Department of Accounting, Finance and Economics, Griffith University, for his kind support to make us possible to work together to prepare this paper of our research interest. Competing interests The authors declare that they have no competing interests. Availability of data and materials The entire 78-sector SAM can be made available for the readers by the publishers on request. Consent for publication Both the authors have consent to publish this manuscript with Journal of Economic Structure. Appendix 1 See Table9. Additional file Additional file1: Appendix S1. Value-added disaggregated SAM for India for the year 2007–2008 (Unit: Rs. Lakh). Page 17 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 Table 9 Map ofconcordance between sectors ofour SAM andNIC 5‑digit classification ofIndian Industries Sectors ofproposed SAM NIC 5-digit sector 1 Paddy 01121/01124 2 Wheat 01111 Jowar 01112 Bajra 01112 Maize 01113 Gram and pulses 01114 Sugarcane 01140 Groundnut 01116 Coconut 01261 Other oilseeds 01115, 01117, 01118, 01119 Jute 01162 Cotton 01161 Tea 01271 Coffee 01272, 01273 Rubber 01291 Tobacco 01150 Fruits 01221/01225, 01229, 01231/01233, 01239, 01241/01243, 01249, 01251/01252, 01259, 01262, 01269 Vegetables 01131/01137, 01139 Other crops 01279, 01611, 01612, 01619, 01620, 01631/01633, 01639, 01640, 01700 Animal husbandry 01411/01413, 01420, 01430, 01441/01443, 01450, 01461, 01462, 01463, 01491/01493, 01499, 01500 Forestry and logging 02101/02102, 02109, 02201/02203, 02209, 02301/02303, 02309, 02401, 02402 Fishing 03111/03113, 03211/03214, 03215, 03219, 03221/03223, 03229 Coal and lignite 05101/05103, 05109, 05201/05203, 05209 Natural gas 06201/06202 Crude petroleum 06101/06102 Iron ore 07100 Manganese 07293 Bauxite 07292 Copper 07291 Other metallic minerals 0794/07296, 07299 Other non-metallic minerals 07210, 08101/08109, 08911/08915, 08919, 08920, 08931, 08932, 08991/08999, 09101/09104, 0900 Sugar and khandsari 10721/10729 Vanaspati 10401/10407 Tea and coffee processing 10791/10792 Processed food 10101/10109, 10201/10207, 10209, 10301/10309, 10409, 10501/10505, 10509, 10611/10619, 10621/10626, 10629, 10711/10712, 10719, 10731/10736, 10739, 10740, 10750, 10793/10799, 10801/10803, 10809 Beverages 11011/11012, 11019, 11020, 11031/11033, 11039, 11041/11045, 11049 Tobacco products 12001/12009 Textiles 13111/13114, 13119, 13121/13124, 13129, 13131/13136, 13139, 13911/13913, 13919, 13921/13926, 13929, 13931/13935, 13939, 13941/13946, 13949, 13991/13999 Textile products 14101/14105, 14109, 14201/14202, 14209, 14301, 14309 Page 18 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 Table 9 continued Sectors ofproposed SAM NIC 5-digit sector Furniture and fixture 31001/31005, 31009, 32111/32114, 32119, 32120, 32201/32204, 32209, 32300, 32401/32405, 32409, 32501/32507, 32509, 32901/32904, 32909 Wood and wooden products 16101/16103, 16109, 16211/16213, 16219, 16221/16222, 16229, 16231/16233, 16239, 16291/16297, 16299, Paper and paper products 17011/17017, 17019, 17021/17024, 17029, 17091/17097, 17099 Printing, publishing and allied activities 18111/18115, 18119, 18121/18122, 18129, 18200 Leather and leather products 15111/15116, 15119, 15121/15123, 15129, 15201/15202, 15209 Rubber products 22111/22113, 22119, 22191/22194, 22199 Plastic products 22201/22209 Petroleum products 19201/19204, 19209 Coal tar products 19101, 19109 Chemicals 20111/20119, 20131/20133, 20211/20213, 20219, 20221/20224, 20229, 20231/20239, 20291/20297, 20299, 20301/20302, 20203, 20304, 21001/21006, 21009 Fertilizer 20121/20123, 20129 Cement 23101/23107, 23109, 23911/23913, 23919, 23921/23923, 23929, 23931/23935, 23939, 23941/23945, 23949, 23951/23956, 23959, 23960, 23991/23994, 23999 Non-metallic mineral products 23101/23107, 23109, 23911/23913, 23919, 23921/23923, 23929, 23931/23935, 23939, 23941/23945, 23949, 23951/23956, 23959, 23960, 23991/23994, 23999 Metals 24101/24109, 24201/24205, 24209, 24311, 24319, 24320 Metal products 25111, 25112, 25113, 25119, 25121/25123, 25129, 25131/25133, 25139, 25200, 25910, 25920, 25931/25934, 25939, 25991/25996, 25999 Non-electrical machinery 28110, 28120, 28131, 28132, 28140, 28150, 28170, 28180, 28211/28213, 28219, 28221/28223, 28229, 28230, 28241/28246, 28249, 28251/28256, 28259, 28261/28266, 28269, 28291/28293, 28299 Transport equipment 29101/29104, 29109, 29201/29202, 29209, 29301/29304, 30111/30115, 30120, 30201/30206, 30301/30305, 30400, 30911/30913, 30921/30923, 30991, 30999 Other manufacturing 28161/28162, 28170, 28180, 28191/28195, 28199, 32111/32114, 32119, 32120, 32201/32204, 32209, 32300, 32401/32405, 32409, 32501/32507, 32509, 32901/32904, 32909, 33111/33114, 33119, 33121/33127, 33129, 33131/33133, 33140, 33150, 33190, 33200, 27101/27104, 27201/27202, 27310, 27320, 27331/27339, 27400, 27501/27504, 27509, 27900, 26101/26107, 26109 Construction 41001/41003, 42101/42103, 42201/42206, 42209, 42901/42904, 42909, 43110, 43121/43123, 43129, 43211/43214, 43219, 43221/43222, 43229, 43291/43292, 43299, 43301/43303, 43309, 43900 Electricity 35101/35107, 35109, 35201/35202, 35301/35303 Water supply 36000, 37001/37003 Railways 49110, 49120 Land transport 49211/49213, 49219, 49221/49226, 49229, 49231/49232, 49300 Water transport 50111/50113, 50119, 50120, 50211/50213, 50219, 50220 Air transport 51101/51102, 51109, 51201/51202 Supporting service 52211, 52212, 52213, 52219, 52220, 52231, 52232, 52241/52243, 52291/52294 Storage and warehouse 52101/52102, 52109 Communication 53100, 53200, 58111/58113, 58121, 58122, 58131, 58132, 58191, 58199, 58201/58203, 59111/59113, 59121/59123, 59131/59133, 59141/59142, 59201/59202, 60100, 61101/61104, 61201/61202, 61209, 61301, 61309, 61900, Page 19 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Received: 17 September 2016 Accepted: 23 May 2017 References Ahluwalia MS (2002) Economic reforms in India since 1991: has gradualism worked? J Econ Perspect 16(3):67–88 Bandara JS, Kelegama S (2008) Compiling input–output (I–O) tables and social accounting matrices (SAMs) for Sri Lanka: review of the progress, problems and the challenge. In: Senanayake SMP, Wimalaratana W, Silva AD (eds) Development perspectives: growth and equity in Sri Lanka. A Festschrift in Honour of Prof. W. D. Lakshman. Department of Economics, University of Colombo, Colombo Bhide S, Pohit S (1993) Forecasting and policy analysis through a CGE model for India. Margin 25:271–285 Central Statistical Organization (CSO) (2012) Input–output table for India 2007–2008. Ministry of Statistics and Program Implementation, Government of India Central Statistical Organization (CSO) (2014) National accounts statistics of India. Ministry of Statistics and Program Implementation, Government of India Chander R, Gnasegarah S, Pyatt G, Round J (1980) Social accounts and the distribution of income: the Malaysia economy in 1970. Rev Income Wealth 26(1):67–85 Chowdhury A, Kirkpatrick C (1994) Development policy and planning: an introduction to models and techniques. Routledge, London Hayden C, Round J (1982) Developments in social accounting methods as applied to the analysis of income distribution and employment issues. World Dev 10:451–465 Table 9 continued Sectors ofproposed SAM NIC 5-digit sector Trade 45101,45102, 45200, 45300, 45401/45403, 46101/46103, 46109, 47110, 47190, 47211/47215, 47219, 47221, 47222, 47230, 47300, 47411/47414, 47420, 47510, 47521/47522, 47523, 47531, 47532, 47591/47595, 47599, 47611, 47612, 47613, 47620, 47630, 47711/47714, 47721/47722, 47731/47739, 47740, 47810, 47820, 47890, 47911, 47912, 47990 Hotel and restaurants 55101, 55102, 55109, 55200, 55901, 55902, 56101/56104, 56210, 56291/56292, 56301/56304 Banking and insurance 64110, 64191/64192, 64199, 64200, 64300, 64910, 64920, 64990, 65110, 65120, 65020, 65300, 66110, 66120, 66190, 66210, 66220, 66290, 66301, 66302, 66309 Ownership of dwelling 68100 Education and research 85101/85104, 85109, 85211/85213, 85221/85223, 85301/85307, 85410, 85420, 85491/85494, 85499, 85500, 72100, 72200, Medical and health 86100, 86201/86202, 86901/86906, 86909, 87100, 87200, 87300, 87900 Business service 69100, 69201/69202, 70100, 70200, 71100, 71200, 73100, 73200, 74101/74103, 74109, 74201/74204, 74209, 74901/74904, 74909 Real estate 68100, 68200 Other service 62011/62013, 62020, 62091, 62092, 62099, 63111/63114, 63119, 63121, 63122, 63910, 63991/63992, 63999, 75000, 77100, 77210, 77220, 77291/77294, 77299, 77301/77309, 77400, 78100, 78200, 78300, 79110, 79120, 79900, 80100, 80200, 80300, 81210, 81291, 81292, 81299, 81300, 82110, 82191, 82192, 82199, 82200, 82300, 82910, 82920, 82990, 88100, 88900, 90001/90006, 90009, 91010, 91020, 92001, 92002, 92009, 93110, 93120, 93190, 93210, 93290, 94110, 94120, 94200, 94910, 94920, 94990, 95111, 95112, 95120, 95210/95222, 95230, 95240, 95291/95295, 95299, 96010, 96020, 96030, 96091/96092, 96903/96908, 97000, 98100, 98200, 99000 Public administration 84111, 84112, 84119, 84121, 84122, 84129, 84130, 84210, 84220, 88230, 84300 Page 20 of 20 Pal and Bandarlage Economic Structures (2017) 6:14 Kotwal A, Ramaswami B, Wadhwa W (2011) Economic liberalization and Indian economic growth: what’s the evidence? J Econ Lit 49(4):1152–1199 NSSO (various rounds), Employment and unemployment situation in India, Ministry of Statistics and Program Implementation, Government of India NSSO (various rounds), Employment and unemployment survey database, Ministry of Statistics and Program Implementation, Government of India NSSO (various rounds), Households consumption expenditure database, Ministry of Statistics and program Implementation, Government of India Pal BD, Pohit S, Roy J (2012) Social accounting matrix for India. Econ Syst Res 24:77–99 Polaski S, Panda M, Gangesh Kumar A, McDonald S, Robinson S (2008) Policy dilemmas in India: the impact of agricultural prices on rural and urban poverty. Indira Gandhi Institute of Development Research, Mumbai June 2008, WP-2008-012 Pradhan, B. K. and A. Sahoo (1996), “Social Accounting Matrix and Its Multipliers for India”,Margin, Vol. 28 (2), Jan-May. Pradhan BK, Sahoo A, Saluja MR (1999) A social accounting matrix for India 1994-95. Econ Polit Wkly 34(48):3378–3394 Pradhan BK, Saluja MR, Sharma AK (2013) A social accounting matrix for India 2007–08, IEG Working Paper No. 326, Institute for Economic Growth, New Delhi, India Pradhan BK, Saluja MR, Singh SK (2006) Social accounting matrix for India: concepts, construction and applications. Sage Publications, New Delhi Pyatt G, Roe A (1978) Social accounting for development planning with special reference to Sri Lanka. Cambridge University Press, Cambridge Pyatt G, Round JI (1979) Accounting and fixed price multipliers in a social accounting matrix framework. Econ J 89:850–873 Hayden C, Round JI (1982) Developments in social accounting methods as applied to the analysis of income distribution and employment issues. World Develop 10(6):451–465 Saluja MR, Yadav B (2006) Social accounting matrix for India 2003–2004. http://planningcommission.nic.in/reports/sereport/ser/sr_sam.pdf Sarkar H, Panda M (1986) Quantity-price money interaction in a CGE model. Margin 18:31–47 Sarkar H, Subbarao SV (1981) A short term macroforecasting model for India: structure and uses. Ind Econ Rev 16:55–80 Sinha A, Siddiqui KA, Munjal P (2007a) A SAM framework for the Indian informal economy. Oxford University Press, Oxford Sinha A, Siddiqui KA, Munjal P (2007b) A SAM framework for the indian informal economy. In: Harriss-White B, Sinha A (eds) Trade liberalization and India’s informal economy. Oxford University Press, New Delhi, pp 233–306 Stone R (1962) A social accounting matrix for 1960. Volume 2S in a programme for growth. Chapman and Hall, London Taylor J, Adelman I (eds.) (1996) Village economies. Cambridge University Press, Cambridge Thorbecke E, Jung H-S (1996) A multiplier decomposition method to analyse poverty alleviation. J Dev Econ 48(2):279–300