Relationship between Openness and Growth: - Research Questions and Methodology Sugata Marjit And Saibal Kar Centre for Studies in Social Sciences, Calcutta

Introduction Trade affects regional income of a geographically large developing country Egger, Huber and Pfaffermayr (2005) deals with trade openness of EUs and regional disparity (based on available regional trade data) Absence of regional trade data Lack of proper indicator of regional trade openness, and relation between openness and poverty, regional income differences, etc.

Methodological Questions How could one deal with the issue of trade openness and poverty? Two ways to approach the issue: Macro and Micro What we have done in this paper is a Macro exercise to devise a holistic measure of openness across regions - although same method might be applied to more disaggregated framework. One may make a journey from Macro to Micro.

Previous Studies Maiti (2004) and Marjit and Maiti (2006) observe trade exposure, specialisation and fragmentation in the labour market - expansion of informal sector through tying up with formal sector Purfield (2006) – NSS data on 15 largest states between 1973/74–2002/03 suggests - differences in policies adopted by states affect their individual patterns of growth. Topalova (2005)- using NSS data - trade liberalization had different impacts on poverty and inequality across states. In rural districts where industries were more exposed to liberalization, trade liberalization has had a negative effect on poverty reduction. Trade liberalization led to an increase in poverty and poverty gap in these rural districts, mainly owing to limited factor mobility across regions and sectors.

Openness Index - Methodology Unavailability of trade data by regions We try to devise a proxy for ‘trade’ by using production data at the state level. DGCIS is the source of trade data according to HS classification ASI is the source of State industrial data according to NIC classification Since ASI and DGCIS use different definitions, we reclassify and merge comparable data at the 2-digit level For a specific state, the level of output (i.e. sum of industrial and agricultural output) has been linked to all-India trade figures to get an approximate indicator of how much ‘open’ a particular state is. We exclude service sector due to lack of production or trade data

Openness Index : Methodology (Contd.) Firstly, State industrial data is reclassified as follows:

Openness Index : Methodology (Contd.) Second, trade is reclassified as follows: Table : DGCI&S trade classifications tallied with ASI data Table B: DGCI&S trade classifications tallied with ASI data Note: All data in this analysis has been converted to Rs lakh before further analysis. ASI NIC codeDGCI&S ( to ) DGCI&S ( to ) RS LAKHS RS THOUSAND RS LAKH FOOD, BEVERAGES & TOBACCO Section (0+1+4) Chapter 1-24 TEXTILES Division ( ) Chapter WOOD 20 Division (24+63) Chapter PAPER Division ( ) Chapter LEATHER 19 Division 61 Chapter CHEMICAL 24 Section 5-Division 58 Chapter RUBBER, PLASTICS &PETROLEUM 23,25 Section 3+ Division ( ) Chapter 27+ Chapter NONMETAL 26 Division 66 Chapter BASE-METALS 27 Division (67+68) Chapter METAL- PRODUCTS ,36 Division 69 Chapter MACHINERY &EQUIPMENTS Section7+ Division (87+88)- Division 78 Chapter Chapter TRANSPORT Division 78 Chapter 86-89

Opennes Index: Methodology (contd.) Third, for a particular state the share of value added by an industrial group is: where, = production share of i th industry in k th state at time period t; GVA k it = Gross Value Added of ith industry in k th state at time period t; NVA k it = Net Value Added of industry producing in k th state at time period t; DP k it = Depreciation of industry producing in k th state at time period t; = Total of all gross value added of industries to 34-35

Openness Index : Methodology (Contd.) Fourth, export and import shares are respectively the export and import of particular industry to respective total

Openness Index : Methodology (Contd.) Fifth, we derive the correlation between ‘share of industrial production of a state’ and the ‘share of industrial export for each state’ separately for each year and then rank the correlation coefficient. We assign the rank of 1 to the state with highest correlation and the rank of 15 to the state with lowest correlation. Sixth, similar to export performance rank we derive correlation between ‘share of industrial production of a state’ and the ‘share of industrial import for each state’ separately for each year and then rank the correlation coefficient. We assign the rank of 1 to the state with highest correlation and the rank of 15 to the state with lowest correlation.

Openness Index: Methodology (contd.) Lastly, equal weights are assigned to the average of export ranks and inverse of import ranks – which gives the ‘openness index of a state’

Relationship Between Openness and Interregional Income Disparity

Table 1: Correlation of openness of states with HDI ranks HDI ranks Rural HDI ranks NA Urban HDI rank NA

Table2 : Correlation of openness of states with unemployment rate and poverty ration YearUnemploym ent rate Poverty ratio NA Source: NSS report