Market vs Interventionist Approach 2016-2017: Cott

Dublin, Oct. 13, 2017 (GLOBE NEWSWIRE) -- The "Market vs Interventionist Approach: Cotton Production in India" report has been added to Research and Markets' offering.

India is the largest producer of cotton in the world, and is estimated to produce around 27 million 480lb bales of cotton, or more than a quarter (26%) of global cotton supply in 2016 (Index Mundi, 2016; National Cotton Council of America, 2016).

Assuming a normal monsoon season, yields are expected to increase in 2016/2017 due to better crop, pest and weed management practice. Supply side factors in India are largely driven by relative costs of production for competing crops, water availability, timely monsoons, expected price levels, and government support in the form of minimum support prices and investments in R&D facilities (Sood, 2016).

Data analysis:

The purpose of this analysis is to determine whether a market-oriented or interventionist approach would boost the productivity of the cotton industry in India. It will look at the periods between 1976/77 and 2015/16, with data accumulated from the World Bank (2016) and United States Department of Agriculture (2016). The following analysis will look for any relationships between cotton production and mill use, exports, domestic credit to the private sector, government spending, currency valuation to one US dollar, and foreign direct investments. The USDA records cotton production, exports and mill consumption between August and July.

Due to this, domestic credit to the private sector, government spending, and foreign direct investments all of which are obtained from the World Bank and are in USD will be estimated by a weighted average of five months of the previous year and seven months of the current year in question. For example, if credit to the private sector was $1 billion in 2015, and $3 billion in 2016, the 2016 figure would be $2.167 billion (=[$1 billion*5/12]+[$3 billion*7/12]) (See Appendix Part 1). Regression analysis will then be used to determine whether there is enough statistical evidence to conclude causality between various independent variables and cotton production. P-values will help determine which individual variable are statistically significant to cotton production in India, and therefore impact cotton production.

Since the data was collected over a period of time (time series), the Durbin-Watson Test will be used to determine whether residuals in the model are related to each other, and therefore exhibit autocorrelation (see Appendix Part 2). If there is evidence of autocorrelation, then a lagged variable will be used to resolve the issue. Where there is no evidence of autocorrelation, the model described in the paper will be used for analysis, to determine whether a variable has a positive, negative, or no effect on cotton production in India (Anderson et. Al, 2007; Stanford University, 2016)

Key Topics Covered:

1 Executive Summary 1.1 Where farming and production takes place 1.2 Which areas are most efficient for cotton production in India?

2 Data Analysis 2.1 Mill Use versus Cotton Production 2.2 Exported Cotton versus Cotton Production 2.3 Domestic Credit to the Private Sector versus Cotton Production 2.4 Government Spending versus Cotton Production 2.5 Foreign Direct Investments versus Cotton Production 2.6 Multiple Regression Analysis

3 Conclusion

Figures 1.1 Cotton Production By Country (Pie chart) 1.2 India Cotton Supply over a period of time (line Graph) 1.3 10-year average Inida Cotton Supply over a period of Time (Bar Chart) 1.4 10-year average Cotton Production in India: % of total Supply (Bar Chart) 1.5 Cotton Production in India: % of Total Supply (Line Graph) 1.6 10-year Average Cotton Consumption in India (Bar Chart) 1.7 Cotton Consumption in India % of Total Consumption (Bar Chart) 1.8 Cotton Consumption: % of Total Consumption (Line Graph) 1.9 Cotton Area Between October and December (2014-15 and 2015-16) 1.10 Domestic Cotton Production (170kg Bales) between October and September 1.11 Cotton Yield in India between October and September (2014-15 and 2015-16) 2.1 Mill use vs Cotton Production in India (Scatter Diagram) 2.2 Exported Cotton vs Cotton Production in India 2.3 Domestic Credit to the private Sector vs Cotton Production in India 2.4 Government Spending vs Cotton Production in India 2.5 Foreign Direct investments, net inflows vs Cotton Production 2.6 Government to Bank Ratio and Cotton Production in India Tables 1.1 Cotton Production by Country 1.2 Cotton Area,Production Yield in India: October to December 2014-15 1.3 Cotton Area, Production, and Yield in India: October to December 2015-16 Models 1.1 Independent Variables: Constant, Mill Use, Production t-1; Dependent Variable: Cotton Production 1.2 Independent Variables: Production t-1, Mill Use; Dependent Variable: Cotton Production 2.1 Independent Variables: Constant, Exports, Production t-1; Dependent Variable: Cotton Production 3.1 Independent Variables: Constant, Production t-1, Domestic Credit to the Private Sector, Domestic Credit to the Private Sector Squared; Dependent Variable: Cotton Production 4.1 Independent Variable: Constant, Government Spending, Government Spending Squared; Dependent Variable: Cotton Production 4.2 Independent Variable: Constant, Government spending Squared, Government spending, Production t-1; Dependent Variable: Cotton Production 5.1 Independent Variable: Constant, FDI, FDI-Sq, Production t-1; Dependent Variable: Cotton Production 6.1 Independent Varaibles: Constant, Mill Use, Production t-1, Exports, Government Spending, Domestic credit to the private sector, FDI net inflow; Dependent Variable: Cotton Production 6.2 Independent Variable: Mill Use, Production t-1, Exports, Government Spending, Domestic Credit to the Private Sector, FDI net Inflow; Dependent Variable: Cotton Production 6.3 Independent Variables: Mill Use, Exports; Dependent Variable: Cotton Production 6.4 independent Variables: Constant, Government to Private Sector Credit Ratio, Production T-1; Dependent Variable: Cotton Production

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