Factors influencing investment into Indian States

1. Factors influencing investment into Indian States Dr. Abhijit Phadnis

2. Overview of presentation • Research objectives & gaps • Unique contributions of the study • Roadmap of work • Research questions • Research methodology • Literature review • Results based on primary survey • Results based on secondary data • Key findings from Gujarat Case study • Conclusion & further scope of work

3. Research objectives • Understand the factors considered important by decision makers when they set up their manufacturing or service facilities • Empirically examine which factors have influenced investment in Indian states • Understand the initiatives taken by a state to improve its investment attractiveness

4. Research gaps • Absence of a comprehensive primary survey which focuses on criteria influencing investment decisions • Limitations of earlier studies • Limited time period • Limited number of states • Limited number of variables • In popular domains rather than with academic rigor • Absence of a holistic case study on state initiatives

5. Unique contributions • A comprehensive primary survey to which more than 200 firms responded out of over 1,000 approached. • We also compiled and analyzed secondary data for a period of 14 years, from 1989 to 2002. Compiling this data from various sources was a difficult task considering the state of statistical data publishing in India. • This data was used to identify variables which influenced capital formation in different states and for analyzing comparative performance of states in attracting investments. • Use of data envelopment analysis for examining comparative performance of states is a novel application in this study. • Further, we carried out a case study of the state of Gujarat which is often portrayed as having a very vibrant investment climate. This case study along with findings from primary and secondary data analyses offers some interesting insights for state governments which intend to attract new investments.

6. Roadmap of work

7. Research questions • Criteria important for decision makers • Which criteria? How much importance to each? • Do firms belonging to different classification groupings give the same importance to each criterion? • Do manufacturing and service firms give the same importance to each criterion? • Which criteria together differentiate responses of manufacturing firms & services firms?

8. Research questions • Historical data on states • How does the investment performance of states and union territories compare over 1989 to 2002 period? • Which variables explain the observed differences in investment performance? • How do states differ in investment performance given the financial and physical resources at their disposal?

9. Research questions • State level initiatives • What are the initiatives that a state in India (Gujarat) has taken to be able to create a popular perception that it is an attractive investment destination?

10. Literature Review R E S E A R C H M E T H O D O L O G Y Pilot Survey (14) Primary Survey (203) Analysis for insights Secondary data requirement Data Compilation Gujarat case study Data Analysis Thesis Documentation

11. Research methodology • Pilot & primary survey • To understand the thought process of the decision makers • Analysis techniques: Single-factor ANOVA, Factor analysis, Cluster analysis, Discriminant function analysis, Logistic regression analysis • Compilation & analysis of secondary data on states • To examine the empirical evidence on factors influencing investment • Analysis techniques: Panel regression, Data envelopment analysis • Gujarat case study • To study state initiatives for improving investment climate • Comparison with other states

12. Literature surveyTheoretical Framework • Subject matter of many disciplines: • Operations research • Industrial engineering • Geography • Urban planning • Economics • Within economics: • Trade theory & economic geography • Regional economics • Development economics • Competitiveness

13. Literature surveyEmpirical research • Empirical research: global context • Empirical research: Indian context • Studies by institutions & in popular media

14. Pilot & primary survey Objective: understand the thought process of decision makers

15. Pilot Survey • Carried out in personal meetings with 14 senior executives • Questionnaire • Part I : Response sought on criticality of listed criteria, rating requested in four alternatives • Part II: Respondents requested to suggest any other criteria that they consider important • Part III : Respondents requested to provide ranking of these criteria. Unenthusiastic response for this aspect. • Part III was, therefore, dropped from the survey instrument used for more comprehensive survey

16. Primary Survey Process • Request letter, introduction letter & questionnaire • Polite follow-up twice after gaps of 1 month • Over 1000 firms (companies) contacted • Data integrity by receiving faxes on SJM SOM fax / letters to SJM SOM address • Interesting experiences !

17. Grouping of respondents by size

18. Grouping of respondents by type

19. Respondents by NIC codes NIC codes with more than 10 responses reported above

20. Statewise respondents

21. Infosys TCS Tata Motors NRB Bearings HSBC Bombay Dyeing Tata Technologies Bharat Forge Bajaj Electricals Grindwell Norton Aventis Pharma ACC Exide Industries HPCL Bharat Electronics Gujarat Alkalies National Fertilizers Patni Johnson & Johnson Tata Chemicals RCF Phillips Dr. Reddy’s Marico Zydus Cadila State Bank of Hyd. ABB I-flex (Now Oracle) Welspun CEAT Thermax United Phosphorous Eveready Motherson Sumi Some of the large respondents • SKF India • Kirloskar Oil • Siemens Info-systems • IL&FS • Cummins • Cipla • Cadbury’s • HCL Infotech • Essel Propack • SKF • VIP industries • Tata Metallics • Colgate • Orchid Chemicals • Rane Group • Titan Industries

22. Criteria(Finalised after literature survey & pilot) • Physical Infrastructure factors (11) • Business Infrastructure factors (3) • Social Infrastructure factors (2) • State Income & Unemployment Level (2) • Political Stability (3) • Geographical factors (2) • State Administrative Efficiency & transparency (3) • State’s investment for the future (4) • Government Financial Stability Factors (3) • Financial Incentives/ Disincentive Factors (4) • Factor Costs & Conditions (4)

23. Criteria with highest & lowest mean scores • Criteria with highest mean scores, in descending order: power, telecom connectivity, national highway network, managerial talent, tap water, skilled labour, state highways, expenditure on infrastructure, wages, and single window clearance • Criteria with lowest mean scores, in ascending order: domestic seaport, bureaucracy spend, revenue deficit, state debt, unemployment level, coalition vs. single party government, availability of small scale industries, per capita income, tax on transfer of property, industrial clusters

24. Do firms belonging to different classification groupings give the same importance to each criterion? • The single-factor ANOVA F-test for each criterion across firms belonging to different NIC codes indicates that in 31 criteria, our expectation about equality or otherwise of mean scores held good. • In respect of the following 11 criteria, firms seems to give statistically different importance: domestic seaport, international seaport, international airport, national highway, state highway, tap water availability, availability of SSI, availability of industrial clusters, higher learning institutions, expenditure on IT • When firms are classified into three categories – manufacturing, service, and manufacturing and service, ANOVA F-test results are as expected for 33 criteria.

25. Do manufacturing and service firms give the same importance to each criterion? • When manufacturing & service firms are analysed separately, the null hypothesis of equality of mean scores is not rejected for 35 criteria in case of manufacturing firms, and for 38 criteria in case of services firms. • The mean responses of Maharashtra firms are equal to Non-Maharashtra firms for 33 criteria in case of manufacturing firms. It is interesting to note that the mean scores assigned by firms located in Maharashtra to the remaining 8 criteria are lower than those assigned by other firms. • Mean scores are equal for all the 41 criteria in case of service sector firms with head office in Maharashtra vs. those outside the state of Maharashtra.

26. Results from factor & cluster analysis • Factor analysis of responses identifies 11 factors with neat groupings of criteria, the first three factors being governance and government’s investment for the future, incentives and taxes, and state finances. • Cluster analysis of the responses shows that firms don’t assign similar importance to different criteria, even if they belong to the same industry (NIC code). • When responses are clustered into three groups, the top-10 criteria with highest F-values indicate that the highest contribution to cluster separation is by criteria related to governance, government’s investment for the future, and state finances. • When responses are classified based on their NIC codes into 9 clusters, separation is also based on other criteria such as sales tax concessions, international airport, and industrial clusters in addition to those mentioned above.

27. What differentiates manufacturing & service sector firms? • Based on the re-classification of firms only into manufacturing and service categories, we found nine criteria with significantly different mean scores. • A discriminant analysis of these criteria identified four criteria which distinguish manufacturing firms from service sector firms: international seaport, international airport, small scale industries, and sales tax concessions. • Due to violation of some assumptions underlying discriminant analysis, we also carried out logistic regression analysis.

28. Secondary data analysis

29. We accessed many sources .. Statistical Abstract of India Economic Political Weekly Annual Survey of Industries Reserve Bank of India Website Education In India State Statistical abstracts India Infrastructure Database State Government Responses State Economic Surveys Central Ministerial Reports Indiastat & sister websites CMIE data – limited access State government websites Annual Power Survey Domestic Product of States Central Government Websites Papers – Mala Lalwani, P. Lakhchaura Industrial Policy, I T Act, notifications Review of Industrial Disputes Crime In India

30. Secondary Data Compilation • Initial data hunt ! • Data collected for over 140 variables, but not available for all time periods • Suggested criteria by respondents also taken into account in finalizing the variables • Letters to Chief Ministers ! In two rounds !!

31. Database creation Data tabulation Literature & Primary Data Hunt Add new variables Inadequate Check data availability Drop certain variables Adequate Inadequate State-level availability Drop certain small states Data estimation Adequate Data deflation Correlation Matrix Drop variables to avoid multicollinearity Auxiliary Regressions Log Transformation Fixed vs. Random effects VAR I ABLE SELECT ION PROCESS Data Analysis

32. How does the investment performance of states and union territories compare over 1989 to 2002 period? • Maharashtra, Gujarat, Uttar Pradesh, Tamil Nadu, and Madhya Pradesh are the top five states based on gross fixed capital formation (factory sector) during the period 1989 to 2002. • When data on gross fixed capital formation (factory sector) is normalized by area, population, and SDP, the rankings of states undergo a significant change. The regions ranked first are union territory of Puducherry based on area, Goa based on population, and Gujarat based on SDP. • The compounded annual growth rates in gross fixed capital formation (factory sector) vary across states. The point to point estimates of growth conceal significant year to year variation in some states. The variation is significant in Goa, Gujarat, Karnataka, Orissa, Himachal Pradesh, and Puducherry. • The physical and social infrastructure endowments differ among states.

33. Which variables explain the observed differences in investment performance? • The gross fixed capital formation exhibits a significant correlation with most explanatory variables as evident from the partial correlation coefficients. The signs of the coefficients are as expected except for accidents due to natural causes. • We observed correlations among explanatory variables and ran auxiliary regressions to remove multicollinearity. We found that a fixed effects model is better than random effects model. • The panel regression for 24 cross-sections (regions) for the period 1989 to 2002 included explanatory variables lagged by one year as investment in a period may be influenced by performance of a state during the preceding period. The plot of error terms indicates that their distribution is not normal. We used log transformation of the dependent variable to reduce skewness of the distribution of errors.

34. Regression analysis • Out of the 24 regions, certain smaller regions have certain unique features. We run 4 regressions beginning with all the regions and then excluding the smaller regions one by one. • These regions are: Jammu & Kashmir (JK), Delhi (DL), Puducherry (PU) and north-eastern states (NE) viz. Assam, Manipur, Meghalaya, Nagaland and Tripura • It is significant that in all the regressions, the signs of the coefficients are consistent indicating robustness.

35. Accidents caused by natural causes Access to domestic airports Average wages Banking centres Buses (public transport) Corruption Development expenditure Mandays lost due to industrial disputes Remoteness Educational institutions – high schools Forest areas Coalition vs. single party government Access to drinking water Educational Institutions – Higher education Live register at employment exchanges Value of production of minerals Net value added Outstanding liabilities of the state Share of industry & services Dependence on captive power Revenue deficit Stamp duty Proportion of areas entitled to tax benefit Share of cargo by sea Teledensity Total Highways Final panel regression model Gross Fixed Capital Formation – Factory Sector is a function of:

36. Summary regression results

38. Key findings • The results suggest that access to domestic airport and development expenditure are positive and significant as expected. Outstanding liabilities of a state and tax concessions (as a measure of backwardness) are negative and significant as expected. These variables are significant in all the regressions. • The other significant variables with positive coefficients in at least two regressions include average wages, number of banking centers, public transport, high schools, and drinking water. The other significant variables with negative coefficients in at least two regressions include accidents due to natural causes, and forest area, which is a proxy for difficult terrain. • There are two significant variables in all regressions with unexpected signs: share in the total cargo handled by seaports (negative), and stamp duty rates (positive). The negative coefficient of share of total cargo handled by seaports suggests that industry is moving towards the hinterland. The positive coefficient of stamp duty suggests that firms are willing to invest in states with higher stamp duties if they find other factors favourable and vice versa. Even if states with unfavourable investment climate bring down the stamp duty, that is not sufficient to attract investment.

39. How do states differ in investment performance given the financial and physical resources at their disposal? • We use Data Envelopment Analysis for this purpose • Efficiency Measurement System (EMS) software developed by Prof. Holgar Scheel • The tool helps us in assessing the output level given various inputs • Inputs can be classified as discretionary & non-discretionary • Data envelopment analysis: • Various physical and financial resources at the disposal of the state are inputs to this model • Gross fixed capital formation is the output. • Gross fixed capital formation – factory sector (14 year data) • Gross fixed capital formation – overall – (7 year estimates) • Ranks are assigned based on the output slack. The ranks for the 14-year and 7-year periods are estimated separately, for each year. • Rank migration provides interesting insights.

40. Variables considered

41. Top 15 Ranks based Gross Fixed Capital Formation - factory sector

42. Top 15 Ranks based Gross Fixed Capital Formation - all sector estimates

43. Findings • Some of the smaller states in remote corners of India seem to attract relatively more investment despite less resources available to them. • States such as Gujarat, Maharashtra, and Tamil Nadu are ranked much lower than expected. They were not able to attract more investment despite higher endowments and access to coast and seaports, during this period. • Among the bigger states, Punjab has been ranked consistently higher. • Surprisingly, the ranks of Uttar Pradesh and Kerala are better than what is widely believed. • Andhra Pradesh and West Bengal recorded poor performance with a significant decline in the rank of West Bengal.

44. Gujarat case study What are the initiatives that Gujarat has taken to be able to create a popular perception that it is an attractive investment destination?

45. Highlights • Gujarat was the fastest to respond both the times • Initial visit in December 2005 • Three visits in 2007 • Met several government officials • Perused their websites & publications • Put-together & analysed comparative data

46. Gujarat, a historical perspective and its vision Physical infrastructure and endowments - Power and energy - Telecom, information technology and e-governance - Roads and highways - Water - Port infrastructure - Railway network - Airports - Mineral endowments - Public transportation - Urban development - Natural hazards Industrial scenario in Gujarat - Industrial policy - Industrial base - Industrial peace - Environment conservation and pollution control - Special Economic Zones (SEZ) - Credit availability Social infrastructure of Gujarat - Education - Health - Tourism - Law & order and security Gujarat Economy - Income and unemployment - Agriculture and other primary activities Gujarat finances Investment track record and investment promotion - Investment facilitation and promotion - Leveraging Gujarati Diaspora - Tax exemptions and other incentives Recent developments Gujarat aspects studied

47. Key findings • While ‘marketing’ of the state is important, it is not a substitute for an all round development. • Since physical infrastructure cannot be created overnight, a vision needs to be formulated and vigorously pursued to achieve the objectives. • The states should also invest their efforts in making drinking water available, guiding farmers in selection of crops, security, public transport, and education. • Private sector should be encouraged to participate in state priorities through a public-private partnership mode. • The public sector can be entrepreneurial too. State government, through its public sector units, can also make strategic investments which would help the state in the long-term. • States should exploit technology to find new ways of knowing the problems faced by people and solve the same. • They can encourage setting-up of institutions of higher learning to ensure the supply of skilled labour. • They can be innovative in creating their marketing strategy. • States need to find new niche areas to attract new income and investment flows: Medical tourism, port-based development, Delhi – Mumbai corridor.

48. Conclusion & Further research opportunities

49. Emerging policy lessons • It is critical that state governments ensure reliability of power and a high quality transport infrastructure connecting all important industry & trade centers. Harnessing water resources is also of utmost importance. • Governments should ensure air connectivity of important centers in their states with those in rest of the country. They should ensure that each district centre has adequate banking access. • State governments should ensure that their governance is transparent, fair, and focused on overall development of the state including social infrastructure such as health and education. • While private sector is likely to invest in areas which are already vibrant, the state government could direct its investments in areas which are industrially backward. • It is particularly important to set up institutions that offer programmes relevant for industry, so that industry finds employable youth in the state. • State governments can play an important role in ensuring a peaceful industrial environment and those with troubled industrial history should provide priority to attracting service sector firms, since they are free from that baggage. • Governments should be committed to fiscal prudence to reduce non-development expenditure and increase development spending. Our analysis shows incentives are inadequate to attract investment if state fails to offer the required infrastructure facilities to industry. • While ‘marketing’ of the state is important, it is not a substitute for an all round and inclusive development effort and states should be innovative and consistent in their marketing strategy. • Since physical infrastructure cannot be created overnight, a vision needs to be formulated and vigorously pursued. Further, instead of aping other states, it is important that state finds its own niches.

50. Limitations • The data is not available for all the variables after 2002-03. • The gross fixed capital formation (factory sector) does not distinguish between private investment and public investment. • The services sector contributes to about 60% of the country’s GDP. But, in the absence of state level time series data on investments in this sector, we had no option but to analyze data on investments in registered manufacturing sector, though our primary survey includes service sector firms.