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Working Papers | 2006

Wheat Marketing and its Efficiency in India

Vasant P. Gandhi and Abraham Koshy

The study examines the marketing of wheat in India, focusing on the private marketing system, the marketing efficiency and quality. Wheat is now a major food staple in India, crucial to India's food economy and security. With production reaching 70 to 75 million tons and a large demand, India's wheat economy is the second largest in the world. The efficiency of marketing is crucial to farmer incomes, consumer welfare, as well as government budgets and the economy. Substantial changes are taking place in the marketing of wheat. The study finds that the farmers now almost invariably sell in the nearby primary markets rather than to village traders. The farmer choice of varieties is now becoming market oriented with quality and market acceptance becoming as important as yield. The typically market intermediary provides hardly any special, value adding or developmental services in return for the commissions and margins. The farmers see considerable scope for improvement in the marketing system. The consumer demand for wheat varies considerably across the country. But wheat has made inroads into food consumption in the east and the south. The retailers are increasingly conscious of consumer demand and quality, and keep a varietiy of wheat and wheat products. Direct buying of wheat grain, storing, and own recourse to processing are common in the north and the west, whereas direct purchase of wheat products such as flour is the norm in the east and the south. The trend is towards direct purchase of processed wheat products, and within this from loose to packaged branded wheat products. The estimated average total marketing cost of wheat is found to be of the order of Rs. 266 per quintal, and in this transport has the largest share of 40 percent, commission and taxes make up 25 percent, and wastage another 15 percent. When compared to the consumer-farmer price spread, the marketing costs account for 74 percent of the spread, leaving 26 percent for margins-this is fairly efficient but there is significant scope for improvement. On an average, the farmers receive 66 percent of what the consumer pays. The government channel marketing cost is reported to be Rs. 309 per quintal, but this does not cover the whole chain and is not strictly comparable. Examination of the question of market integration for wheat is difficult due to data and quality difference problems. Co-integration analysis using monthly price data for eight markets for the period April 1997 to June 2004 indicates that nationally the markets are integrated but the LOP (Law of One Price) does not hold, and the presence of six common stochastic trends implies the absence of full pair-wise co-integration.

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Working Papers | 2006

Economic Liberalization and Rural Land and Labour Markets in India: A Study

Vasant P. Gandhi

The paper examines the rural land and labour markets in the context of economic liberalization in India. Land and labour are the two fundamental resources available to the rural people for income generation. The access to land and to employment for labour become basic determinants of well-being for the rural households. Reforms are often seen as hostile to rural areas and the poor, although they should be beneficial not only for overall growth, but also rural growth and poverty alleviation. The study based on primary household data examines the land and labour markets in the reform period and the underlying linkages of these to different characteristics of the household. The study finds that over the reform period in India the land markets are leading to less landlessness rather than more, and growth in marginal and medium farm sizes rather than large. Lease markets are leading to operated land in more hands. Land purchase behaviour is related to less land, more education, greater crop diversification, and higher crop and livestock revenues. Leasing-in is also related to many of the same variables and is showing great diversity in lease agreements involving outputs, inputs and rent. Labour-employment is showing diversity of occupations but the primary dependence on agriculture is still about 80 percent. There has been some change in the occupational structure. Non-farm employment is associated with higher overall employment. Own-farm employment is strongly related to crop diversification and livestock activity; other farm employment to number of male and female family members and irrigation; and non-farm employment to education. Broadly, liberalization does not show adverse consequences but rather some positive impact on rural land and labour markets.

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Working Papers | 2006

Does the Gravity Model Explain India Direction of Trade? A Panel Data Approach

Bhattacharyya Ranajoy and Tathagata Banerjee

In this paper we apply the gravity model to the panel consisting of India's yearly bilateral trade data with all its trading partners in the second half of the twentieth century. The main conclusions that emerge from our analyses are: (1) The core gravity model can explain around 43 per cent of the fluctuations in India's direction of trade in the second half of the twentieth century (2) India's trade responds less than proportionally to size and more than proportionally to distance (3) Colonial heritage is still an important factor in determining India's direction of trade at least in the second half of the twentieth century (4) India trades more with developed rather than underdeveloped countries, however (5) size has more determining influence on India's trade than the level of development of the trading partner.

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Working Papers | 2006

Scaling Sparse Constrained Nonlinear Problems for Iterative Solvers

Gajulapalli Ravindra S and Lasdon Leon S

We look at scaling a nonlinear optimization problem for iterative solvers that use at least first derivatives. These derivatives are either computed analytically or by differncing. We ignore iterative methods that are based on function evaluations only and that do not use any derivative information. We also exclude methods where the full problem structure is unknown like variants of delayed column generation. We look at related work in section (1). Despite its importance as evidenced in widely used implementations of nonlinear programming algorithms, scaling has not received enough attention from a theoretical point of view. What do we mean by scaling a nonlinear problem itself is not very clear. In this paper we attempt a scaling framework definition. We start with a description of a nonlinear problem in section (2). Various authors prefer different forms, but all forms can be converted to the form we show. We then describe our scaling framework in section (3). We show the equivalence between the original problem and the scaled problem. The correctness results of section (3.3) play an important role in the dynamic scaling scheme suggested. In section (4), we develop a prototypical algorithm that can be used to represent a variety of iterative solution methods. Using this we examine the impact of scaling in section (5). In the last section (6), we look at what the goal should be for an ideal scaling scheme and make some implementation suggestions for nonlinear solvers.

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Working Papers | 2006

Scaling Sparse Matrices for Optimization Algorithms

Gajulapalli Ravindra S and Lasdon Leon S

To iteratively solve large scale optimization problems in various contexts like planning, operations, design etc., we need to generate descent directions that are based on linear system solutions. Irrespective of the optimization algorithm or the solution method employed for the linear systems, ill conditioning introduced by problem characteristics or the algorithm or both need to be addressed. In [GL01] we used an intuitive heuristic approach in scaling linear systems that improved performance of a large scale interior point algorithm significantly. We saw a factor of 10*3* improvements in condition number estimates. In this paper, given our experience with optimization problems from a variety of application backgrounds like economics, finance, engineering, planning etc., we examine the theoretical basis for scaling while solving the linear systems. Our goal is to develop reasonably "good" scaling schemes with sound theoretical basis. We introduce concepts and define "good" scaling schemes in section (1), as well as explain related work in this area. Scaling has been studied extensively and though there is a broad agreement on its importance, the same cannot be said about what constitutes good scaling. A theoretical framework to scale an m x n real matrix is established in section (2). We use the first order conditions associated with the Euclidean metric to develop iterative schemes in section (2.3) that approximate solution in O(mn) time for real matrice. We discuss symmetry preserving scale factors for an n x n symmetric matrix in (3). The importance of symmetry preservation is discussed in section (3.1). An algorithm to directly compute symmetry preserving scale factors in O(n2) time based on Euclidean metric is presented in section (3.4) We also suggest scaling schemes based on rectilinear norm in section (2.4). Though all p-norms are theoretically equivalent, the importance of outliers increases as p increases. For barrier methods, due to large diagnal corrections, we believe that the taxicab metric (p = 1) may be more appropriate. We develop a linear programming model for it and look at a "reduced" dual that can be formulated as a minimum cost flow problem on networks. We are investigating algorithms to solve it in O(mn) time that we require for an efficient scaling procedure. We hope that in future special structure of the "reduced" dual could be exploited to solve it quickly. The dual information can then be used to compute the required scale factors. We discuss Manhattan metric for symmetric matrices in section (3.5) and as in the case of real matrices, we are unable to propose an efficient computational scheme for this metric. We look at a linearized ideal penalty function that only uses deviations out of the desired range in section (2.5). If we could use such a metric to generate an efficient solution, then we would like to see impact of changing the range on the numerical behavior.

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Working Papers | 2006

A New Algorithm for Continuous Optimization

Desai Tejas A

We present a new algorithm for continuous, nonlinear or linear, and constrained or unconstrained optimization. After proving its convergence, we apply it to unconstrained and constrained maximum likelihood estimation, and compare its performance to that of the Newton-Raphson algorithm.

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Working Papers | 2006

Maternal Health Financing – Issues and Options: A Study of Chiranjeevi Yojana in Gujarat

Bhat Ramesh, Amarjit Singh, Sunil Kumar Maheshwari, and Saha Somen

Government of Gujarat announced a "Chiranjeevi Yojana" in April 2005. The objective of this scheme is to encourage private medical practitioners to provide maternity health services in remote areas which record the highest infant and maternal mortality and thereby improve the institutional delivery rate in Gujarat. The scheme was finally launched as a one year pilot project in December 2005 in five districts viz., Banaskantha, Dahod, Kutch, Panchmahal, and Sabarkantha. The private empanelled providers are reimbursed on capitation payment basis according to which they are reimbursed at a fixed rate for deliveries carried out by them. The payments are made for a batch of 100 deliveries. This is expected to take care of case-mix differences (i.e., normal or complicated deliveries) and help the providers to keep the costs below the reimbursed amounts. The scheme proposes to use a voucher system to target the people living below poverty line. The objective of this paper is to document the experience in implementing this scheme and discuss the issues in up-scaling it further.

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Working Papers | 2006

An Optimization-Based Decision Support System for Strategic Planning in a Process Industry: The Case of a Pharmaceutical Company in India

Goutam Dutta, Robert Fourer, Majumdar Akhilesh, and Dutta Debabrata

We describe how a generic multi-period optimization-based decision support system (DSS) can be used for strategic planning in process industries. Built on five fundamental elements-materials, facilities, activities, time periods and storage areas-this DSS requires little direct knowledge of optimization techniques to be used effectively. It is user friendly and requires little knowledge of optimization. Results based on real data from a pharmaceuticals company in India demonstrate significant potential for improvements in revenues and profits.

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Working Papers | 2006

Managing Bullwhip Effect: Two Case Studies

N. Ravichandran

The purpose of this article is to present two examples based on real life experiences where the Bullwhip effect in supply chain is considerably reduced. Both examples relate to the consumer durables industry in India. The first example uses Enterprise Resource Planning and Vendor Managed Inventory as tools to reduce the Bullwhip Effect. The second example uses a modification of the classical inventory control policies to eliminate Bullwhip Effect. Based on these two empirical case studies, we argue that managing Bullwhip Effect is a strategic initiative by organization and the best approach is a combination of several tactical initiatives.

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Working Papers | 2006

Feasibility Study of Setting up Information Technology-Enabled Services (ITES) and Business Process Outsourcing (BPO) Hubs in the North Eastern States of India: A Report

Rajanish Dass and Lethil Nangmuansang

This report aims at identifying the various state administrative/commercial capital cities in the North East Region where IT-enabled service industry could be set up, and whether the necessary conditions conducive to the industry exist. It is also an attempt to rank the various cities in terms of their investment friendliness when it comes to the ITES industry. This report involves a macro environmental analysis where the focus is mainly on the STEEP sector of the business environment-social, technological, economic, environmental and political aspects that impact competitiveness.

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