Analyzing the Structural Change and Growth Relationship in India:  State-Level Evidence

Cortuk, Orcan; Singh, Nirvikar

doi:10.2139/ssrn.3039173

Cited by 10 publications

(8 citation statements)

References 18 publications

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“…Cortuk and Singh (2015) undertake a similar analysis of the linkage between structural change and growth for the 16 states of India for the period 2000–2006. The authors found out that there is one-way positive impact from structural change to growth for the period 2000–2006.…”

Section: Review Of Literature On Structural Changes and Growthmentioning

confidence: 99%

Structural Change and Economic Growth across Major States of India

Thind

Singh

2018

Millennial Asia

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The structural change in an economy is an important feature of the economic development process. Structural change becomes a potential source of growth in an economy as it induces reallocation of labour from low-productivity to high-productivity sectors, thus leading to fuller and better utilization of overall resources. This article studies the relationship between structural change and growth in 15 major states of India over the 30-year period from 1983–1984 to 2014–2015. The study aims at discovering whether structural changes have contributed to economic growth of these states or otherwise. This is achieved by decomposing the overall labour productivity growth of states into contribution by structural change and within sector change. The results show that in all the states under study structural changes have contributed positively to growth; however, contribution of within sector changes is found to be much more than structural change in all states except Maharashtra.

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Section: Review Of Literature On Structural Changes and Growthmentioning

confidence: 99%

Structural Change and Economic Growth across Major States of India

Thind

Singh

2018

Millennial Asia

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“…Using these “purer” measures of structural change, Cortuk and Singh (2011) conducted an empirical analysis for India that found causality from structural change to growth. Extending this approach to state-level growth performance, Cortuk and Singh (2015) found similar results with a panel regression analysis.…”

Section: Introduction [1]mentioning

confidence: 53%

“…As each change is counted twice, the scaling factor corrects for this and ensures that the measure lies between 0 and 1. In a departure from Cortuk and Singh (2011, 2015), in this paper, the index is calculated with respect to a fixed base year, so in the following empirical analysis, it is a cumulative measure rather than an annual change. This modification facilitates comparison with structural change calculations that are based on the McMillan–Rodrik approach, which are based on cumulative changes.…”

Section: Data Concepts and Stylized Factsmentioning

confidence: 99%

Structural change and economic growth in India: a comparative study of Punjab

Sanyal

Singh

2021

IGDR

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Purpose The Green Revolution transformed agriculture in the Indian State of Punjab, with positive spillovers to the rest of India, but recently the state’s economy has fallen dramatically in rankings of per capita state output. Understanding the trajectory of Punjab’s economy has important lessons for all of India. Economic development is typically associated with changes in economic structure, but Punjab has remained relatively reliant on agriculture rather than shifting economic activity to manufacturing and services, where productivity growth might be greater. Design/methodology/approach The authors empirically examine structural change in the Punjab economy in the context of structural change and economic growth across the States of India. The authors calculate structural change indices and map their pattern over time. The authors estimate panel regressions and time-varying parameter regressions, as well as performing productivity change decompositions into within-sector and structural changes. Findings Panel regressions and time-varying-coefficient regressions suggest a significant positive influence of structural change on state-level growth. In addition, growth positively affected structural change across India’s states. The relative lack of structural change in Punjab’s economy is implicated in its relatively poor recent growth performance. Comparisons with a handful of other states reinforce this conclusion: Punjab’s lack of economic diversification is a plausible explanation for its lagging economic performance. Originality/value This paper performs a novel empirical analysis of structural change and growth, simultaneously using three different approaches: panel regressions, time-varying parameter regressions and productivity decompositions. To the best of the authors’ knowledge, it is the only paper we are aware of that combines these three approaches.

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“…By using monthly data to study the relationship between industrial structure change and economic growth in Japan from 1978 to 2006, Nutahara [12] found that the long-term trend of industrial structure change has a significant correlation with economic growth and the emergence of new industries caused by new technologies in industrial structure change will generally lead to long-term economic growth. Cortuk and Singh [13] used panel data to study the relationship between industrial structure change and economic growth in India from 2000 to 2006, and found that the industrial structure change in this period had a positive impact on the economic growth rate.…”

Section: Related Literaturementioning

confidence: 99%

Threshold Effect of Industrial Structure Change on Economic Growth

Du¹

2019

IJBER

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Based on the framework of neoclassical growth theory, this paper constructs a time series threshold co-integration model to test and analyze the impact of ratio of the tertiary and the secondary industry, the tertiary and the primary industry, the productive service industry and the service industry on economic growth during 1979-2015 in China. The following conclusions are drawn: (1) there is a threshold effect of industrial structure change on economic growth. The time node of the threshold effect is about 2009-2010. (2) threshold effect of industrial structure on economic growth is mainly achieved by changing the output efficiency of labor factors. After 2009-2010, the labor output efficiency declines significantly, while the capital output efficiency remains basically unchanged. The conclusions of the study show that the premature development of service industry and the excessive non-productive tendency of service industry development are very detrimental to the sustained growth of China's economy in the middle and late stages of industrialization. This paper provides some policy suggestions, such as continuing to promote the mechanization and large-scale development of the agricultural industry, deepening the development of manufacturing industry, and focusing on the development of productive services, to maintain the high-speed economic growth of China.

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Analyzing the Structural Change and Growth Relationship in India: State-Level Evidence

Cited by 10 publications

References 18 publications

Structural Change and Economic Growth across Major States of India

Structural Change and Economic Growth across Major States of India

Structural change and economic growth in India: a comparative study of Punjab

Threshold Effect of Industrial Structure Change on Economic Growth

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