Bishwanath Goldar Institute of Economic Growth, New Delhi, India Third World KLEMS Conference, Tokyo, May 19-20, 2014

 A Methodological Issue in TFP/MFP Measurement  Need for separating domestic and imported intermediate inputs in TFP/MFP studies  Objective of the Present Study and Methodology  Analyze TFP growth in Indian manufacturing, with and without separation of domestic and imported materials input  Background Information for the Study  Trends in production and trade, Indian manufacturing,  Data Sources and Measurement of Output and Inputs for TFP Estimation  Estimates of TFP Growth in Indian Manufacturing Industries,  Conclusions TFP=Total Factor Productivity; MFP=Multifactor Productivity

 Several studies have found that the use of imported intermediate input favorably impacts productivity of industrial firms:  Topalova and Khandelwal (2011) for India; Schor (2004) for Brazil; Amiti and Konings (2007) and Blalock and Veloso (2007) for Indonesia; Kasahara and Lapham (2008) for Chile,, Vogel and Wagner (2010) for Germany, Halpern, Koren and Szeidl (2011) for Hungary, and Altomontem, Barattieri and Rungi (2014) for Italy.  This raises the following Issue:  Should domestically sourced and imported intermediate inputs be treated as separate inputs in TFP/MFP Studies?

 There have been a number TFP studies for Indian manufacturing using the KLEM or KLEMS (captial-labour-energy-materials-services) framework:  Rao (1996); Trivedi, Prakash and Sinate (2000); Goldar and Kumari (2003); Das (2004); Trivedi (2004); Veeramani and Goldar (2005); Banga and Goldar (2007); Das and Kalita (2011); Virmani, and Hashim (2011).  None of these studies has made a distinction between imported and domestically sourced intermediate inputs.

 In some productivity studies for the US, domestically sourced and imported intermediate inputs have been separated into different inputs:  Gollop and Roberts (1981) - cost function estimation for the US manufacturing industries.  Kruz and Lengermann (2008) - MFP in various industry groups or sub-sectors within the US private business sector.  Eldridge and Harper (2010) - MFP in the private business sector and the manufacturing sector of the US.  Houseman et al. (2011) - MFP in the US manufacturing and sub-sectors - distinction made between domestically sourced and imported materials input. Joregenson, et al. (2005) separate non-comparable imports from competitive imports.

 Kruz and Lengermann (2008), Eldridge and Harper (2010) and Houseman et al. (2011) have drawn attention to the offshoring bias in the productivity estimates for the US.  Other studies: Howells et al. (2013) for the US and Fukao and Arai (2013) for Japanese manufacturing.  Houseman et al. (2011) conclude that because of the offshoring bias, the average annual growth rate in MFP in the US manufacturing is overstated by 0.1 to 0.2 percentage points.  This issue is probably relevant also for Indian manufacturing, but not studied in the paper.

 The aim is to analyze TFP growth in Indian manufacturing industries at two-digit industry level and at the aggregate level for the period to  The KLEMS framework is used. Tornqvist index of TFP is computed.  Domestically sourced and Imported materials input are separated using domestic flow and import flows input-output tables.  Aggregate level TFP estimates are made by the production possibility frontier (PPF) approach (Tornqvist index of real value added growth is used).

Early economic reforms Major economic reforms Consolidation of reforms Industrial growth rate in the 2000s was higher than that in the 1980s as well as that in the 1990s.

Accelerated growth in manufacturing sector output in India in the 2000s was accompanied by accelerated growth in exports and imports of manufactured products. The trend growth rates in imports: about 5% per annum during to and about 20 % per annum during to

The materials import intensity of Indian manufacturing almost doubled between 1998 and The upward trend in materials import intensity got halted or became sluggish after Source: Based on WIOD

At the aggregate level, the share of imported raw materials increased from 44% in to 49% in In several industries, import intensity fell. Based on CMIE, Corporate Sector, April 2013 Import intensity fell in metals, metal products, and machinerey

 Annual Survey of Industries (Central Statistical Office)  It covers only the organized or registered sector (units with 10+ workers with power or 20+ workers without power)  Input-output tables, , and – domestic and import flows matrices have been constructed  Wholesale price index series, implicit deflator for GDP of services sectors, implicit deflator for fixed capital formation in manufacturing  Unit value indices for imports (disaggregated)

 Gross output: Deflated value of output  Labour: No. of persons engaged  Capital : Net fixed capital stock at constant prices  Energy: Deflated value of fuel and power used  Services: Total input minus value of materials, fuel and power; the series is then deflated by services input price index constructed on the basis of implicit deflators and I/O tables.

 Materials input: Two variants  Variant - A  Value of materials used by each industry is deflated by a price index constructed on the basis of domestic wholesale price indices and weights taken from input-output matrices.  For this purpose, the two-digit industries are mapped into the sectoral classification of input- output tables.

 Materials input: Variant - B  Value of materials for each industry split into domestic and imported parts on the basis of domestic and import flow input-output matrices.  Domestically sourced and imported materials are deflated, respectively by a price index based on domestic wholesale price indices and a price index formed on the basis of unit value indices of imports.  The weights are based on domestic flows input- output matrix and import flows input-output matrix.

 Variant-B measure of materials input – which builds in the split into domestic and imported – is the preferred method. TFP estimate based on this method is referred to as Estimate-1  Variant-A measure of materials is the conventional method. TFP estimate based on this method is referred to as Estimate-2.

 Estimate-1 (preferred estimate) is relatively higher than Estimate-2 in most cases.  The gap is about 0.2 percentage points per annum or more in:  wood and wood products; chemicals and chemical products; rubber and plastic products; fabricated metal products; electrical machinery; electronic and optical goods, including computers; and transport equipment other than motor vehicles.  There is possibly a downward bias in the second set of TFP growth estimates for the reason that it does not separate out imported materials input from domestically procured materials input.

Industry Code (2-digit) Description of IndustriesTFP growth rate (% per annum) Share of imported materials in total materials consumed (%), Estimate-1Estimate-2 15Manufacture of food products and beverages Manufacture of tobacco products Manufacture of textiles Manufacture of wearing apparel; dressing and dyeing of fur Tanning and dressing of leather; manufacture of luggage, handbags, saddler, harness and footwear Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plating materials Manufacture of paper and paper products Publishing, printing and reproduction of recorded media Manufacture of coke, refined petroleum products and nuclear fuel Manufacture of chemicals and chemical products Manufacture of rubber and plastics products Manufacture of other non-metallic mineral products Manufacture of basic metals Manufacture of fabricated metal products, except machinery and equipment Manufacture of machinery and equipment not elsewhere classified Manufacture of electrical machinery and apparatus not elsewhere classified Manufacture of office, accounting and computing machinery; Manufacture of radio, television and communication equipment and apparatus; Manufacture of medical, precision and optical instruments, etc Manufacture of motor vehicles, trailers and semi-trailers Manufacture of other transport equipment Manufacture of furniture; manufacturing not elsewhere classified

 Estimate-1 is negative while that given by Estimate-2 is positive and more than two percent per annum.  The problem is that the domestic price index for crude oil has increase by about 190% between and , whereas the unit value index of crude oil imports has increase only by about 90% in this period.  Crude oil is the main material used in petroleum refining, and 80% of crude oil used is imported.  Inference: Estimate-2 is flawed, Estimate-1 is reliable.

 The estimates are obtained by the PPF approach and Tornqvist index of real value added growth.  Estimate-1 shows a fall in the annual growth rate in TFP after 2007 from 10% to 3%, but Estimate- 2 shows an acceleration in TFP growth during  Estimate-2 does not seem right because it indicates a hike in TFP growth after 2007, whereas Indian manufacturing was adversely affected by the recent global slowdown.  The problem with Estimate-2 is traceable in part to the treatment of crude oil (noted above).

TFP growth estimate for Indian manufacturing using Tornqvist index of value added by Bollard, Klenow and Sharma (2013) for is 8.4% per annum

 In earlier TFP studies for Indian manufacturing, the gross output function was applied to aggregate manufacturing sector data on output and inputs.  This can be objected to on methodological grounds.  Yet, for the sake of comparison, a set of estimates taking the same approach has been made.  The comparison shows:  acceleration in TFP growth in the 2000s compared to 1990s;  estimates of this study are in agreement with the estimates of earlier studies.

 Two weaknesses of the previous studies on TFP growth in Indian manufacturing are highlighted:  TFP growth estimates for the 1990s and 2000s are probably biased because the imported materials input has not been separated from the domestically sourced materials input;  The gross output function and the associated Tornqvist index of TFP has been applied to the aggregate manufacturing sector data which can be objected to on methodological grounds.

 The PPF approach based estimate of TFP growth rate in India’s organized manufacturing in the period to is found to be about 8% per annum.  From data on organized manufacturing sector GDP reported in the National Accounts Statistics, the growth rate in output is found to be about 9.5% per annum for the same period.  It seems growth in manufacturing GDP is possibly getting understated, because real GDP growth in manufacturing is derived by using single deflation.