The Census recently held dissemination workshops in several Indian cities for promoting use of its data (www.censusindia.gov.in). Given that it is expensive to ask questions in huge population surveys, such caution exercised in promoting dissemination of its data is well placed. Census and other data published by CSO and NSSO have implications for usage for our Prime Minister’s Make in India call, which has appealed to firms in India and globally to manufacture in India, and make the country a hub for such goods. This is a major new national programme designed to facilitate investment, foster innovation, enhance skill development, protect intellectual property and build the best-in-class manufacturing infrastructure (www.makeinindia.gov.in). It makes eminent sense since India leapfrogged the manufacturing revolution and made the transition from agriculture to become a service-based economy.

However, how do foreign or Indian firms know the comparative advantages of cities/regions, to enable them to make certain goods rather than others? At help we have many regional economic tools to enable us to assess this.

Central to an understanding of a region’s core competence for the government of India is how employment in industries A and B are concentrated across regions of the nation, and for regional planners to understand which industries are concentrated in their own regions. The location quotient (LQ) is a device for comparing a region’s share (of employment, value added or output) of a certain activity with its share of some basic aggregate, say manufacturing, which the Census of India or the Annual Survey of Industries (ASI) data report. If LQ>1 for a region in an industry, it is an export industry; if LQ<1, then the good we are examining in the region would be an import industry. If LQ>1, it means that the industry employs a greater share of local workforce than it does nationally, which implies that the industry is producing more than is consumed locally, indicating its expertise in producing that good. If LQ<1, it means that local residents and businesses are purchasing goods and services from outside the local area.

There are limitations with the approach. It is possible that propensities to consume, income levels, industrial mixes and labour productivity may be different across regions, hence even in some cases when LQ>1, the region may be importing the goods and vice-versa. Given this limitation, a way in which the method can be used is to see changes in LQ over time for a region. In such an approach, large declining LQs would indicate that the industry is important to the local economy and losing it would create problems. Small and growing LQs indicate that the industry will promise future growth for the local economy, and that it should be supported. Small declining LQs indicate that they are not important to the local economy; large increasing LQs are desirable since they are the base of the local/regional economy. Analysis of the region/city’s LQs for all industries would, therefore, send signals as to what the area’s competitive advantage is and how it is changing over time.

Shift-share analysis is another tool to analyse regional and local competencies to manufacture goods. This technique enables one to disaggregate employment growth in a regional economy into three components: the impact of the growth of the national economy; the growth of the industry in which the firm is located overall; and the local competitive advantages due to which local employment growth can be attributed. If the local competitive advantage in an industry is high, then a major portion of employment growth in the local/regional economy will be due to this effect. Hence, it is important for policy-makers to understand what local/regional economies are competent at. While shift-share analysis will help to disaggregate the part of employment growth which is entirely due to local competitiveness, it will not help to identify the source of the comparative advantage—which could be availability of raw materials, proximity to markets, skilled labour force suited especially for the kind of industry, local leadership or institutions.

Further, there are economic base techniques which originated with the need to predict the effects of new economic activity on cities and regions. The Commonwealth Games in Delhi would have created a number of forward-linkages (stores and businesses which sold merchandise) and backward-linkages (real estate, construction—to build accommodation and other facilities for the athletes no matter how poor they were—roads and other sectors which were put in place in preparation for the games) to other local businesses. One may like to answer the question: What was the impact of the Commonwealth Games on Delhi’s local economy?

The Economic Base (EB) model is an analytical tool that can answer this question which will enable the regional planner/policy-maker to understand the ‘basic’ sector in a city or a region’s economy. The basic sector is one that is dependent on external factors. For example, an airplane manufacturer builds and sells airplanes to companies and countries throughout the world. It does not sell planes to families or households locally, so their business is dependent on exporting their goods. Non-basic sectors are dependent largely on local business conditions as, for instance, a local grocery store. Hence, here we assume that all economic activities can be identified as basic or non-basic.

EB theory asserts that the means of strengthening and growing the local economy is to develop and enhance the basic sector which is the ‘engine’ of the local economy; pointing out that the local economy is the strongest when it develops economic sectors which are not closely tied to the local economy, because it can better insulate itself from economic downturns given external markets will remain strong, even if the local economy experiences problems. By contrast, a local economy wholly dependent on local factors will have trouble responding to economic slumps. Therefore, to determine a city/region’s core competence, the basic sector needs to be identified.

Thus, there are a number of analytical tools which can help the regional planner, policy-maker and the firm to make an informed decision regarding what to make and where to make them. It is already 2014 and the Census of India 2011 still has not released the data which would enable us to compute the above. The government should expedite the publication of relevant data by Census and other agencies in a timely fashion, to benefit from the research and to determine where and what to make in India.

By Kala Seetharam Sridhar

The author is professor, Centre for Research in Urban Affairs, Institute for Social and Economic Change. Views are personal