By Y.S. RANA, Chandigarh—The Punjab government is claiming to go full throttle on the infrastructural facilities to the industry sector with an aim of boosting the state’s economy from the morass. The state government has been saying that it was removing green hurdles to keep the economy in pink. These claims are belied by the recent study conducted by Frost and Sullivan when it revealed that Haryana was the most attractive destination for industry on account of economic and industrial performance and infrastructural facilities in the Northern region of the country.
While in the Southern region, Kerala benefits from its human capital, infrastructure, and economic performance. In the East, West Bengal, despite its anti-industry image, leads the pack although Madhya Pradesh is a very close second. Maharashtra and Gujarat both share the mantle of regional leaders in the West with each of these states excelling in at least three areas. Lastly, in the Northeastern region, Assam excels on the back of its human capital, industry performance, and infrastructure. It is revealed in a study ‘Indian States Attractiveness Index’ conducted by Frost & Sullivan.
The study has assessed how individual state within different regions has performed at a broader level and their attractiveness to industry. The results of the in-depth comparative study of states show that the best performing states in each region typically excel in at least one of the areas of assessment
The study examines the friendliness of states to industry by comparing them across multiple areas. The results of the study highlight the distinguishing aspects of well-performing states that sets them apart from the rest of the pack. More importantly, it is a starting point for state administrations that are interested in enhancing their competitiveness and attracting investments from the industry at large.
Frost and Sullivan developed a very robust methodology which tracks the different elements of state-level performance that were identified and broadly classified into six main buckets. These buckets are natural and human capital, economic growth, fiscal flexibility, infrastructural robustness, industrial development, and monetary stability. The key criterion for selecting an indicator under each bucket was its suitability to ensure comparison, its frequency, and availability. Equally, care was taken to ensure that there was no bias in any of the indicators selected. For instance, under economic indicators, GDP growth rate was taken rather than the actual GDP value, as ranking by GDP value would give a misleading interpretation when comparing bigger states with smaller ones. Comparison on growth rates paints a more objective picture of state-level performance.
To ensure cross-indicator comparison, the identified indicators were normalized with the minimum and maximum value normalized to 0 and 1, respectively, and the rest between these two. Importantly, the normalization of data was not at the national level but at the regional level. In other words, the maximum and minimum values were based on the lowest and highest value for each indicator within the data set of the states in that region. The normalized data under each bucket was then averaged with equal weights to arrive at an index for each bucket, thereby giving six sub-indices. These sub-indices were then assigned different weights to arrive at the overall composite index.