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Using Social Connections and Financial Incentives to Solve Coordination Failure: A Quasi-Field Experiment in India’s Manufacturing Sector

Farzana Afridi, Amrita Dhillon, Sherry Xin Li, and Swati Sharma.

IZA Discussion Paper No. 11521, 2018.

Production processes are often organised in teams, yet there is limited evidence on whether and how social connections and financial incentives affect productivity in tasks that require coordination among workers. We simulate assembly line production in a lab-in-the-field experiment in which workers exert real effort in a minimum-effort game in teams whose members are either socially connected or unconnected and are paid according to the group output. We find that group output increases by 15% and wasted individual output is lower by 30% when workers are socially connected with their co-workers. Unlike the findings of existing research, increasing the power of group-based financial incentives does not reduce the positive effect of social connections. Our results are driven by men whose average productivity is significantly lower than that of women. These findings can be explained by pro-social behavior of workers in socially connected teams.

URL: https://www.iza.org/publications/dp/11521/using-social-connections-and-financial-incentives-to-solve-coordination-failure-a-quasi-field-experiment-in-indias-manufacturing-sector

Courtesy: IZA


Foreign Direct Investment, Firm Heterogeneity, and Exports: An Analysis of Indian Manufacturing

Maitri Ghosh and Saikat Sinha Roy
Asian Development Review 35(1):27-51 · March 2018

Using firm-level data, this paper investigates whether foreign direct investment and the presence of multinational enterprises explains India’s improved export performance during the post reform period. The recent literature stresses that firm heterogeneity gives some firms an edge over others to self-select into export markets. Apart from ownership, this paper considers firm heterogeneity and other firm-specific factors of export performance. Estimation results show that the impact of foreign ownership on export performance does not significantly differ from that of domestic firms across sectors in Indian manufacturing. Rather, firms build their international competitiveness by
importing raw materials and foreign technical know-how, and by investing in research and development. Further, firm heterogeneity, measured in terms of sunk costs, significantly impacts firm-level export intensity. The study also reveals that there are ownership-specific factors that determine firm-level exports.

url – https://www.mitpressjournals.org/doi/pdf/10.1162/adev_a_00104
courtesy – ADR

Do Management Interventions Last? : Evidence from India

World Bank Policy Research Working Paper, 2018


Beginning in 2008, the authors conducted a randomized controlled trial that changed management practices in a set of Indian weaving firms (Bloom et al. 2013). In 2017 the plants were revisited and the authors found three main results. First, while about half of the management practices adopted in the original experimental plants had been dropped, there was still a large and significant gap in practices between the treatment and control plants. Likewise, there remained a significant performance gap between treatment and control plants, suggesting lasting impacts of effective management interventions. Second, while few management practices had demonstrably spread across the firms in the study, many had spread within firms, from the experimental plants to the non-experimental plants, suggesting limited spillovers between firms but large spillovers within firms. Third, managerial turnover and the lack of director time were two of the most cited reasons for the drop in management practices in experimental plants, highlighting the importance of key employees.

URL: https://openknowledge.worldbank.org/handle/10986/29373

Courtesy: World Bank Group

Export Performance, Innovation, and Productivity in Indian Manufacturing Firms

Santosh Kumar Sahu, Sunder Ramaswamy and Abishek Choutagunta
Madras School of Economics, Working Paper, February 2017
This study re-examines the relationship between export performance and productivity in manufacturing firms in India for the period 2003-2015, using firm level information. Departing from the earlier studies on India economy,
we argue that product innovations boost export performance of the economy. The hypothesis being that, in the post-economic-reforms era competitive export market scenario, productivity alone, without product innovation and participation in R and D cannot drive export performance. We observe that the argument of highly productive firms
entering the export market without reallocating resources towards innovation and R and D seems to be invalid in our sample. Nevertheless, we find in our sample, that productivity as a selection criterion coupled with advertising and marketing strategies explains participation in R and D in boosting exports.
Courtesy :MSE

One size does not fit all: An analysis of the importance of industry-specific vertical policies for growing high technology industries in India

Sunil Mani
in India Development Report 2017, Edited by Mahendra Dev.
Oxford University Press.

[From the Introduction]
India, currently (c. 2015) is noe of the fastest growing countries in the world. But this growth is largely driven by its services sector. From around 2006 or so, country has been striving to industrialize through the manufacturing route as growth driven by the manufacturing sector has a long-lasting economic benefits.


Determinants of financial risk attitude among the handloom micro-entrepreneurs in North East India

Kishor Goswami, Bhabesh Hazarika, Kalpana Handique

Asia Pacific Management Review, Volume 22, Issue 4, December 2017

Indian economy as it is the second largest provider of rural employment after agriculture. The North Eastern states of India accounts for more than 65 percent of the total handloom households in India. However, with only 4.26 percent of the total working looms utilized for commercial purposes, the industry is beset with manifold problems such as obsolete technologies, unorganized production system, low productivity, inadequate working capital, and weak market linkages. Therefore, undertaking financial risk plays here a defining role in overcoming these obstacles. Based on the primary data collected from 332 respondents, the present study analyzes determinants of financial risk attitude of the handloom micro-entrepreneurs using the Ordinal Probit model. Education, access to credit, access to training, and individual’s income play a crucial role in influencing the risk aversion of the micro-entrepreneurs. These determinants are found to have a more dominant influence in lowering the risk aversion of female micro-entrepreneurs as compared to the male micro-entrepreneurs. The study suggests for providing vocational education and training programs that focus on entrepreneurship education to the rural female micro-entrepreneurs. Besides, it suggests for the provision and implementation of various financial inclusion programs for easy access to credit with proper follow up programs to ensure the efficient utilization of credit, with a primary focus on the female micro-entrepreneurs.

URL: https://www.sciencedirect.com/science/article/pii/S1029313216304201

Courtesy: Sciencedirect

Measuring Productivity at the Industry Level – The India KLEMS Database

Deb Kusum Das; Abdul Azeez Erumban; Suresh Aggarwal and Pilu Chandra Das

Reserve Bank of India, 2017

Chapter 1: Introduction
1.1 Background
1.2 Coverage: Industries and Variables
Chapter 2: Gross Value Added Series at the Industry Level
2.1 Methodology
2.2 Implementation Procedure
2.3 Outstanding Issues
Chapter 3: Gross Output Series at the Industry Level
3.1 Methodology
3.2 Implementation Procedure
3.3 Outstanding Issues
Chapter 4: Labour Input Series at the Industry Level
4.1 Methodology
4.2 Implementation Procedure
4.3 Outstanding Issues
Chapter 5: Capital Input Series at the Industry Level
5.1 Methodology
5.2 Data and Sources
Chapter 6: Intermediate Input Series at the Industry Level
6.1 Methodology
6.2 Implementation Procedure
6.3 Outstanding Issues
Chapter 7: Factor Income Share Series at the Industry Level
7.1 Methodology for Measuring Labour Income Share Series
7.2 Implementation Procedure
7.3. Outstanding Issues
Chapter 8: Growth Accounting Methodology
8.1 Methodology for Measuring Productivity Growth at the Industry level
8.2 Methodology for Aggregation across Industries
8.3 Implementation Procedure
List of Appendixes
Appendix A: Concordance table of INDIA KLEMS industries (minimal) with NICs
Appendix B: Employment Unemployment Survey (EUS) rounds of NSS
Appendix C: Definitions of Employment in NSSO employment & unemployment surveys
Appendix D: Concordance table of KLEMS industries and IOTT industries
Appendix Table 1: Population, WFPR and Persons Employed in Different EUS Rounds
List of Tables
Table 1.1: Industrial Classification for Phase I and II of the Project
Table 1.2: Variables in INDIA KLEMS Multifactor Productivity Database for 27 Industries (Annual Time Series 1980-81 onwards)
Table 2.1: List of Manufacturing Industries for which GVA data is directly available from NAS
Table 2.2: List of Manufacturing Industries for which Gross Output data is obtained by adjusting data for NAS Industries
Table 3.1: List of Manufacturing Industries for which Gross Output is directly available from NAS
Table 3.2: List of Manufacturing Industries for which Gross Output data is obtained by adjusting data for NAS Industries
Table 5.1: Capital Asset Types in National Accounts Statistics and Corresponding Our Study Types
Table 5.2: Asset Types in ASI and India KLEMS
Table 5.3: Asset Categories in NSSO Rounds
Table 5.4: Depreciation Rate by Asset Type Used in the Computation of Capital Input
Table 7.1: NAS Sectors and Corresponding Study Industries, for Computation of Labour Income Share
Table 7.2: Industries and Groups for which ƞ (proportion of labour income out of mixed income) has been estimated
List of Box
Box 1: The Heckman model

URL : https://www.rbi.org.in/Scripts/PublicationReportDetails.aspx?UrlPage=&ID=881

Courtesy: Reserve Bank of India