Determinants of Competitiveness of the Indian Auto Industry

1. This study analyses the determinants of competitiveness in the Indian auto industry. It is based on a field survey and a quantitative analysis of secondary data. The field survey covers 45 firms all over India, of which 31 are auto-component firms and 14 are Original Equipment Manufacturers (OEMs). 2. From 2001-02 to 2005-06, the Indian automobile sector has grown at an average annual rate of over 18 per cent in terms of value of output at constant 1993-94 prices and the auto-component sector has grown at about 26 per cent. During the same period, in terms of domestic sales in numbers, two-wheelers have grown at over 13 per cent per annum; three-wheelers at more than 15 per cent commercial vehicles at about 25 per cent per annum and the number of passenger vehicles by 17 per cent per annum. 3. Vehicle exports at constant 1993-94 prices have grown at an average annual rate of more than 55 per cent from 2001-02 to 2005-06, while auto-component exports have grown at 21 per cent. Two-wheeler exports have seen an annual average growth rate of 27 per cent; passenger car exports have grown at 80 per cent; and commercial vehicles at about 55 per cent. 4. The effective rate of protection on automobiles is much higher than on components. For example, during 2006-07, while nominal custom duties were 60 per cent for automobiles (other than commercial vehicles), 12.5 per cent for commercial vehicles and 12.5 per cent for auto-components, effective rates of protection were 183.5 per cent, 12.5 per cent and 10.1 per cent, respectively. 5. With the higher countervailing duty and other cesses/levies, the effective rate of protection for automobile sector would be even higher. 6. This differential rate of effective protection distorts resource allocation and investment pattern in the industry. 7. The auto-component sector has much higher employment-generation potential and export-intensity than the auto assembly segment of the sector. The component manufacturers are now globally competitive and are also maintaining reasonable profitability levels despite a tariff protection of only 7.5 per cent. 8. The import tariff for the assembled vehicles is 60 per cent. Given the low level of protection both for the auto components and CKD/SKD kits, this clearly reflects a policy bias in favour of auto assemblers. 9. The reduction in import duties on assembled units may be undertaken in a phased manner and after ensuring that Indian automobile companies get comparable access to ASEAN and Chinese markets. 10. The anti-dumping mechanism should be strengthened to prevent the dumping of vehicles in the Indian market. 11. The government must also ensure that the large infrastructure deficit faced by this important sector is addressed urgently so that any adverse impact of macroeconomic policies is avoided. These are important steps if import duty structure is to be rationalized. 12. Materials cost is the major component in production cost and its share is increasing. Policy measures to reduce domestic indirect taxes on all inputs for the auto industry would be a welcome step to enhance competitiveness. The Chinese auto industry faces a flat 17 per cent indirect tax incidence, so our aim should be to reach that level. 13. Significant scaling up is required at all levels in the Indian auto-component sector so that economies of scale are gained and cost of production reduced. 14. One of the major constraints for the smaller auto-component manufacturers in increasing their scales of production is lack of credit availability at interest rates comparable to other countries. This is also confirmed by our econometric analysis. 15. R&D expenditure as a share of turnover is low in the Indian auto-component sector ranging between 0 and 1.5 per cent while it is 0.5-3 per cent for the automobile sector. In fact, most of the smaller auto-component firms and a few of the bigger ones do not have an R&D facility. Policy intervention is urgently needed to improve the R&D activities in the Indian auto industry. Since fiscal incentives are not working, a scheme of special credit for R&D would be useful to induce the R&D activities. 16. Indias current levels of tariff on capital goods are higher than those in the ASEAN and China. Thus, these tariffs should be brought down further to enhance competitiveness. 17. The Indian auto industry does not possess good design facilities. The Government needs to significantly strengthen non-proprietary R&D and design capacity that has strong connections with research institutes like IITs. This could be used by all the players in the industry to develop new models, reduce material costs and become more competitive. 18. Skill shortages and skill mismatches have emerged as a major constraint. To address this critical concern, the proposed National Auto Institute1 should be quickly established with active participation of private industry players. 19. There is a significant and increasing use to contract workers in the industry. Labour reforms, aimed at more flexibility, are widely considered among the industrialists as an essential step. This will encourage firms to employ and retain more permanent workers and improve learning and raise productivity levels. 20. It is important to recognize that labour reforms are expected to increase overall employment in the auto sector and will also help firms in the organised sector to scale up. 21. The unorganised sector contributes 30 per cent to total employment, 15 per cent to fixed assets and only 1.5 per cent to output in auto industry in India. This sector has much lower capital and labour productivity than the organised sector. The share of power/fuel cost in total costs are much higher in the unorganised sector. Hence, policy measures are required to incentivise these smaller firms to use power and fuel more efficiently, by adopting better technologies and taking steps to minimise wastage. 22. In the econometric analysis, foreign equity participation is found to be correlated with technical efficiency. Therefore, both centre and state governments should create a conducive environment for attracting more FDI. 23. The trend of mid-sized vehicles capturing a large market share is expected to continue in the foreseeable future. 24. A detailed roadmap for strict implementation of emission standards that are harmonised across states should be drawn up. This could go a long way in ensuring that the entire automotive supply chain upgrades quality and technology. 25. While the implementation of VAT is a positive step, remaining differential in indirect taxes should be eliminated by moving to the GST. The currently prevalent region-specific fiscal concessions are creating the unsustainable locational distortions in the industry. 26. So far, Indias FTA with Thailand has resulted in a net trade gain for India. The government must, however, ensure comparable, if not preferential, market access to domestic firms in partner countries, especially in the Asia-Pacific region, while negotiating FTAs. 27. The principles pertaining to the rules of origin have to be strictly implemented.Indian Auto Industry, competitiveness, Efficiency and Indian Auto Policy

Determinants of Competitiveness of the Indian Auto Industry

This paper analyses the determinants of competitiveness of auto industry in India, based on a field survey and a quantitative analysis of secondary data. It highlights that all segments of Indian auto sector are growing at a fairly high rates and their productivity as well as export intensity is on the rise. Domestic sales are rising, but they have declined in certain sub-segments of vehicles. However, the R&D expenditure has been scarce. Effective rate of protection of automobile assembly is far higher than that of auto-components manufacturing. Unorganised sector, which is quite significant in auto-component manufacturing, has grown more rapidly in the urban areas than in the rural areas. The econometric analysis suggests various measures that could be taken by the government, particularly, the credit facilitation for SMEs. A field survey comprising auto manufacturers in India underlines various constraints faced by the sector, such as the shortage of skilled manpower along with poor infrastructure, fluctuating steel prices and unavailability of land at reasonable price. This suggests that the government could facilitate the industry in becoming more competitive by taking steps such as structural fiscal reforms, cut in import duties of raw materials and capital goods, promotion of R&D and FDI, training facilities, research-backed negotiations of FTAs, roadmap for harmonising emission norms across the country and infrastructure improvement. Industry, on the other hand, should improve its R&D capabilities and market research.Indian Auto Industry, Competitiveness, Efficiency and Indian Auto Policy

Glassy Phase of Optimal Quantum Control

We study the problem of preparing a quantum many-body system from an initial to a target state by optimizing the fidelity over the family of bang-bang protocols. We present compelling numerical evidence for a universal spin-glass-like transition controlled by the protocol time duration. The glassy critical point is marked by a proliferation of protocols with close-to-optimal fidelity and with a true optimum that appears exponentially difficult to locate. Using a machine learning (ML) inspired framework based on the manifold learning algorithm t-SNE, we are able to visualize the geometry of the high-dimensional control landscape in an effective low-dimensional representation. Across the transition, the control landscape features an exponential number of clusters separated by extensive barriers, which bears a strong resemblance with replica symmetry breaking in spin glasses and random satisfiability problems. We further show that the quantum control landscape maps onto a disorder-free classical Ising model with frustrated nonlocal, multibody interactions. Our work highlights an intricate but unexpected connection between optimal quantum control and spin glass physics, and shows how tools from ML can be used to visualize and understand glassy optimization landscapes.Comment: Modified figures in appendix and main text (color schemes). Corrected references. Added figures in SI and pseudo-cod

Kuramoto model with coupling through an external medium

Synchronization of coupled oscillators is often described using the Kuramoto model. Here we study a generalization of the Kuramoto model where oscillators communicate with each other through an external medium. This generalized model exhibits interesting new phenomena such as bistability between synchronization and incoherence and a qualitatively new form of synchronization where the external medium exhibits small-amplitude oscillations. We conclude by discussing the relationship of the model to other variations of the Kuramoto model including the Kuramoto model with a bimodal frequency distribution and the Millennium Bridge problem.Comment: 9 pages, 3 figure

DENDRITIC CELL DIFFERENTIATION BLOCKED BY PRIMARY EFFUSION LYMPHOMA-RELEASED FACTORS IS PARTIALLY RESTORED BY INHIBITION OF P38 MAPK

To better understand the molecular mechanisms underlying the dendritic cell (DC) defects in cancer, we analyzed which signaling pathway is implicated in the abnormal monocyte differentiation into DC determined by the presence of Primary effusion lymphoma (PEL) released factors. Our results indicate that the DC, obtained in this condition, together with phenotypic abnormalities and reduced allostimulatory function, showed hyperphosphorylation of signal transducer and activator of transcription 3 (STAT3) and p38 mitogen-activated protein kinase (MAPK) molecules, in comparison to the DC differentiated in the absence of PEL-released factors. The inhibition of p38 MAPK but not of STAT3 phosphorylation, with specific inhibitors, was able to revert the effect of the PEL-released factors on the DC phenotype. This study suggests that p38 MAPK signaling pathway is an important contributor to the abnormal differentiation of DC in PEL

Broken symmetry in a two-qubit quantum control landscape

We analyze the physics of optimal protocols to prepare a target state with high fidelity in a symmetrically coupled two-qubit system. By varying the protocol duration, we find a discontinuous phase transition, which is characterized by a spontaneous breaking of a $\mathbb{Z}_2$ symmetry in the functional form of the optimal protocol, and occurs below the quantum speed limit. We study in detail this phase and demonstrate that even though high-fidelity protocols come degenerate with respect to their fidelity, they lead to final states of different entanglement entropy shared between the qubits. Consequently, while globally both optimal protocols are equally far away from the target state, one is locally closer than the other. An approximate variational mean-field theory which captures the physics of the different phases is developed

Reinforcement Learning in Different Phases of Quantum Control

The ability to prepare a physical system in a desired quantum state is central to many areas of physics such as nuclear magnetic resonance, cold atoms, and quantum computing. Yet, preparing states quickly and with high fidelity remains a formidable challenge. In this work we implement cutting-edge Reinforcement Learning (RL) techniques and show that their performance is comparable to optimal control methods in the task of finding short, high-fidelity driving protocol from an initial to a target state in non-integrable many-body quantum systems of interacting qubits. RL methods learn about the underlying physical system solely through a single scalar reward (the fidelity of the resulting state) calculated from numerical simulations of the physical system. We further show that quantum state manipulation, viewed as an optimization problem, exhibits a spin-glass-like phase transition in the space of protocols as a function of the protocol duration. Our RL-aided approach helps identify variational protocols with nearly optimal fidelity, even in the glassy phase, where optimal state manipulation is exponentially hard. This study highlights the potential usefulness of RL for applications in out-of-equilibrium quantum physics.Comment: A legend for the videos referred to in the paper is available on https://mgbukov.github.io/RL_movies