Manufacturing share in GDP: Comparing India with China and South Korea

It is commonly believed that Indian manufacturing performance is weak, as the sector has not been able to capture a large enough GDP share. Presenting a comparison of manufacturing share in gross domestic product in India, China and South Korea, Bishwanath Goldar argues that this can be explained predominantly by changing terms of trade between manufacturing and services, and manufacturing translating technological and productivity advances into lower prices and better-quality products for customers in India.

Several Indian economists – and some foreign scholars – have expressed disappointment with the growth performance of India’s manufacturing sector, on the grounds that the share of manufacturing in GDP (gross domestic product) has stagnated (see, for example, Basu and Veeramani 2021, Ghani 2024). Some recent media articles have drawn attention to a slight fall or stagnation in the manufacturing share in GDP between 2013-14 and 2023-24 and voiced dissatisfaction with the manufacturing sector’s growth performance (Pande and Pradhan 2024, Sabnavis 2025). Among scholars engaged in research on India’s economic growth, there is a widely held belief that the performance of manufacturing has been weak, and the desired structural change in favour of the sector has not taken place.

In an article co-authored with Pilu Chandra Das (Goldar and Das 2024), we have shown, using the India KLEMS database of the Reserve Bank of India (RBI),¹ that if the real gross value added (GVA) of different sectors of the economy is measured by applying the double deflation procedure², the share of manufacturing in aggregate GVA at 2004-05 prices would increase significantly from about 16% in 2003-04 to about 32% by 2018-19 (see also, Goldar (2024)).³

In this post, I present a comparison of manufacturing share in GDP among India, China and South Korea to contribute to a better understanding of India’s industrial growth dynamics.

Comparing manufacturing share in GDP at current prices

The shares of manufacturing in GDP at current prices in India, China and South Korea are shown in Figure 1. It is seen that, between 2011 and 2023, the GDP share of manufacturing declined in all three countries. The fall was greater in China (6 percentage points (pp)) and South Korea (4 pp) than in India (3.2 pp). During 2011-2023, the share of manufacturing in GDP at current prices fell by about 3.1 pp in Indonesia, 4.1 pp in Thailand and 5.5 pp in Philippines. Evidently, India’s performance has been relatively better than several East Asian and Southeast Asian countries.

Figure 1. Share of manufacturing in GDP at current prices (%)

Source: Created by the author using the World Bank World Development Indicators.

The changes in the GDP share of manufacturing at current prices are caused both by the differential growth in physical output of different sectors of the economy, and by changes in the prices of different products and services. If the relative price changes against manufacturing, the share of manufacturing could fall even though the share of manufacturing in physical output or the level of economic activity in the economy is stagnant or rising. Further, if the rate of increase in the prices of manufacturing products is less than that in the prices of agricultural raw materials, minerals, energy and services, used as intermediate inputs, there is a downward pressure on nominal GVA of manufacturing and hence the nominal GDP share of manufacturing tends to go down.

The fall in the manufacturing share in aggregate GVA (hereafter, MVA share) at current prices is connected with ‘productivity advances’. Rodrik (2016) notes that the relative price of manufacturing tends to decline as a country gets richer. A relatively higher growth rate in manufacturing productivity reduces its relative price vis-à-vis other sectors of the economy through the standard demand-supply channels. Islam and Iversen (2018) note that a change in productivity in an industry may have a significant price effect. In particular, they said that higher productivity advances made by the manufacturing sector may cause the relative price of the sector to decrease, thus hiding the more pronounced changes in its physical output.

In short, one should not read too much into the observed post-2011 fall in the manufacturing share in GDP (computed at current prices) in India. The same applies to a series based on single deflation, a practice adopted by India’s national accounts. A more sophisticated analysis is needed to understand better the growth dynamic of Indian manufacturing.

Comparing manufacturing share in double-deflated aggregate GVA

Figure 2 shows the real MVA share in India, China and South Korea after applying the double deflation method.⁴ It reveals that, in 2004, the real MVA share in India was much less than that of China and South Korea. India narrowed the gap in real MVA share vis-à-vis South Korea and, by 2018, the real MVA share in India exceeded that of South Korea. In contrast, the gap in the real MVA share between China and India was about 15 pp in 2004, which remained more or less at the same level until 2017, when the real MVA share in China reached about 50%.

Figure 2. Manufacturing share in aggregate double deflated GVA, 2004-2018

Note: The series are at 2004 prices (in the case of India, at 2004-05 prices). Estimates for India are for financial years (for example, 2018 connotes 2018-19 for India), and those for China and South Korea are in calendar years.
Source: Created by the author using data outlined in Note 4.

Wu and Li (2021) have presented estimates of growth rates in real GVA of industry in China and the aggregate economy based on the Tornqvist index (an economic index used to measure changes in prices or quantities over time) and double deflation. The growth rates were 15.8%, 12.9%, and 7.1% per annum in the periods 2001-2007, 2007-2012 and 2012-2018, respectively, for industry (of which manufacturing has about 90% share). The growth rates in real GVA of the aggregate Chinese economy in those three periods were relatively lower at 10.7%, 8.1%, and 5.3% per annum. These estimates are consistent with a significant rise in the manufacturing share in real GVA in China, as depicted in Figure 2.

The excess of real MVA share in India in 2018 over that of South Korea will probably go up by about 2 pp if a deficiency in the deflator used for the information and communication technology (ICT) equipment industry in India’s national accounts is addressed (see Goldar (2025). The price index of ICT equipment corrected for product quality should show a significant fall, but India’s Wholesale Price Index (WPI) for 2018-19 (with base 2011-12) shows a rise by 16% for personal computers and 17% for telephones and mobile handsets. Between 2015-16 and 2022-23, the WPI for personal computers rose by 6% and that for telephone and mobile handsets rose by 23%. In contrast, the Producer Price Index (PPI) for China shows a fall by about 11% between 2011 and 2018 (and 5% fall between 2015 and 2022) for electronic and telecommunication equipment (which includes ICT equipment). In South Korea, the PPI for computers and peripherals fell by about 9%, and that for communication and broadcasting equipment, video and audio apparatus (including mobile handsets) fell by about 29%, between 2015 and the end of 2022. In other words, due to a deficiency in the deflator used, India’s national accounts understate the growth in the ICT equipment industry, and hence the manufacturing sector growth.

Inference about manufacturing sector productivity performance

The finding of a significant upward trend in real MVA share coexisting with a downward trend in nominal MVA share in China and India (compare Figures 1 and 2) is explained mainly by changes in the relative prices between manufacturing and non-manufacturing sectors going against manufacturing and favouring the non-manufacturing sector (Figure 3). Another possible explanation probably lies in a faster growth in total factor productivity (TFP) in manufacturing than in services. There is supporting evidence for this: The estimates of industry contribution to aggregate economy TFP growth in China available in Wu and Zhang (2024) indicate that during 2001-2018, the contributions of manufacturing, producer services and consumer services were positive, marginal, and negative, respectively. Similar research undertaken for India shows that the contribution of manufacturing was about 0.8 pp per year during 2003-2018, whereas that of market services (which includes transport services, telecommunication services, trade, and financial and business services among other services) was 0.4 pp during 2003-2007 and negative (-0.3 pp) during 2008-2018 (Krishna et al. 2022).

Figure 3. Implicit deflator for GVA in India’s national accounts, manufacturing and market services

Note: 2011-12 is taken as the base (2011-12=1)
Source: Author’s computations based on the India KLEMS database.

There has been incessant criticism of Indian manufacturing in not being able to capture a bigger part of GDP, in academic research as well as media reporting. However, the basis for this is the changing terms of trade between manufacturing and services, going against manufacturing increasingly and the fact that manufacturing has translated technological progress and productivity advances into lower priced and better-quality products for its customers. Is that not grossly unfair?

The views expressed in this post are solely those of the author, and do not necessarily reflect those of the I4I Editorial Board.

Notes:

KLEMS refers to capital (K), labour (L), energy (E), materials (M), and services (S). It is a framework used to analyse inputs in production and assess productivity advances made by different sectors of the economy.
In the double deflation method, the value of output is deflated by an output deflator, while raw materials are deflated by a raw material deflator. Then the two real numbers are subtracted, to obtain real GVA estimates. This is the method recommended by the System of National Accounts, 2008, and applied by most of the G20 countries. In the single deflation method, on the other hand, the real GVA estimates are obtained by deflating nominal value added by the output deflator. In effect, the nominal value of output is deflated by an output deflator, and the nominal value of raw materials is deflated by the same output deflator, not by a raw material deflator.
Given that the manufacturing share in aggregate GVA in India, measured at current prices, has never crossed 20% in the last 75 years, some may find it hard to comprehend how the real MVA share could have reached 32% in 2018-19 (re-estimated at 34% in Goldar (2025)). The interpretation of and explanation for the significant hike in the manufacturing share in India’s GDP at constant prices, based on double deflation, between 2003 and 2018 have been provided in Goldar and Das (2024) and will not be repeated here.
The computed series for India is based on the India KLEMS database. The computed series for China is based on the China Industrial Productivity Database (CIP 4.0). The computational methodologies are explained in Goldar (2025).

For South Korea, the series has been prepared by using output, intermediate input, and price data from the KLEMS database for South Korea. The series on manufacturing share in aggregate double-deflated GVA has been formed from 2004 to 2009. Then, a second series from 2009 to 2018 has been formed by using data on constant-price value added of manufacturing and total economy from the Economic Transformation Database (ETD) (Kruse et al. 2022). The two series, 2004-2009 and 2009-2018, have been spliced. It should be noted that the national accounts for South Korea shifted to double deflation method from 2004 (Alexander et al. 2017), with a transition from the fixed weighted method to the chained weighted method in 2009. The series formed gives manufacturing sector share in aggregate double-deflated GVA in South Korea.