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Working Papers | 2017

Exploring Linkages between Innovation and public policy- challenges and Opportunities

Rakesh Basant

Significant research has gone into the analysis of the complex linkages between public policy and innovation. While this research has generated a lot of interesting insights, it has also identified several gaps in our understanding of these linkages. This paper is an attempt to pool together some of the ideas that academic research has highlighted on the linkages between innovation and public policy and identify the current challenges as well as opportunities for meaningfully exploring these linkages further. Through a select review of the literature the paper (i) provides a broad overview of the public policy-innovation interface; (ii) discusses issues of conceptualizing and measuring innovation, innovation related activities and policy changes; (iii) summarizes mechanisms through which various policies impact innovation along with available evidence on the same; and (iv) identifies challenges in exploring policy-innovation interface along with a few potential areas of research in the context of India.

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Working Papers | 2017

Mathematical Modelling for Time-of-Use Pricing of Electricity in Monopoly and Oligopoly

Nidhi Kaicker, Goutam Dutta, Debamanyu Das, and Subhashree Banerjee

This study establishes the feasibility condition for efficiency gains to arise from time-of-use pricing in the electricity market in a monopolistic and oligopolistic set up using constrained optimization. In an oligopolistic set-up, the strategic interaction between producers depends on the level of demand. In case of high demand, the producers compete on the basis of output they will produce, resulting in a Cournot-type competition. On the other hand, in case of low demand, an oligopolistic structure may break with only the most efficient firm operating, or results in the emergence of leader firms and follower firms, i.e. the Stackleberg model.

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Working Papers | 2017

Vertical Integration, Market Structure and Competition Policy: Experiences of Indian Manufacturing Sector during the Post Reform Period

Rakesh Basant and Pulak Mishra

In the context of declining degrees of vertical integration in major industries of Indian manufacturing sector during the post-reform period, the present paper is an attempt to examine how such 'vertical disintegration' has affected firms' market power and its implications for competition policy. Using panel dataset of 49 majors industries of Indian manufacturing sector for the period 2003-04 to 2010-11 and applying the system GMM approach to estimate of dynamic panel data models, the paper finds that vertical integration does not cause any significant impact on average market power of firms in an industry. Instead, it is influenced by market size, and selling and technology related efforts. While selling intensity has a positive impact on market power, the impact of market size and technology intensity is found to be negative. Notably, like vertical integration, market concentration, import to export ratio, and capital intensity also do not have any significant impact on market power. The findings of this paper, therefore, have important implications for competition law and policy in general and policies and regulation relating to technology development and international trade in particular.

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Working Papers | 2017

Globalization and Inequality- A Pathway Through Education (Revised as on 02.04.18)

Kishan P K V

This study investigates the effect of globalization on economic inequality in a country through the channel of education. We measure globalization by the KOF globalization index (a composite index consisting of elements of economic, social, and political dimensions of globalization), economic inequality by the Gini coefficient of consumption/income distributions, and education outcomes by mean years of schooling in a country. An econometric model using appropriate panel data techniques is estimated for a sample of about 150 countries over the period 1980-2013. The results suggest that globalization improves the situation of economic inequality in a country, i.e. inequality in the country decreases. However, the precondition to this is that the population of the country is very less educated. As the country becomes more globalized, and the educational outcomes improve, the restorative effects of globalization on income inequality go down. At a turnaround point of about 6.73 mean years of schooling, globalization works towards worsening income inequality. The empirical results are robust to the use of inequality index from a separate data source and the change in time span of the study (1980-2008).

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Working Papers | 2017

Are the temperature of Indian cities Increasing?: Some Insights Using Change Point Analysis with Functional Data

A. K. Laha and Poonam Rathi

In recent years there has been considerable concern expressed worldwide regarding increase in temperature popularly called the global warming problem. In this paper we examine monthly temperature data of nine Indian cities for the period 1961 to 2013. We introduce a new Gaussian process based method for change point detection with functional data and use it to investigate the
existence of change point for the temperature data series of nine Indian cities. It is found that there has been a rise in the average temperature for eight of
the nine cities during this period. The magnitude of warming is found not to be uniform but vary across cities located in different parts of India. The cities
located in hilly areas is seen to have warmed more than those located in the plains. The estimated change points for the eight cities are not identical but most of them are in the period 1994 - 2001. The findings suggest that immediate policy measures are required to ensure that no further warming happens in these cities.

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Working Papers | 2017

New Approaches to Prediction using Functional Data Analysis

A. K. Laha and Poonam Rathi

In this paper we address the problem of prediction with functional data. We discuss several new methods for predicting the future values of a partially observed curve when it can be assumed that the data is coming from an underlying Gaussian Process. When the underlying process can be assumed to be stationary with powered exponential covariance function we suggest two
new predictors and compare their performance. In some real life situations the data may come from a mixture of two stationary Gaussian Processes. We
introduce three new methods of prediction in this case and compare their performance. In case the data comes from a non-stationary process we propose a modification of the powered exponential covariance function and study the performance of the three predictors mentioned above using three real-life data sets. The results indicate that the KM-Predictor in which the training data is clustered using the K-Means algorithm before prediction can be used in several real life situations.

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Working Papers | 2017

Managing the Power Grid Ramping challenges critical to success of India's Renewable Energy Targets

Rajeev Annaluru and Amit Garg

Power grids operators around the world have been experiencing challenges in operating the grid with increasing penetration of Variable Generation (VG) sources like Solar PV and Wind. Variability in one form of generation must always be compensated with other forms of generation at all times to ensure grid stability. This paper focuses on the diurnal variability introduced into the Indian power grid and the consequent increase in ramping requirements due to the 175GW by 2022 renewable energy target enunciated by the Government of India. Ramping requirements were quantified for 3 potential renewable energy penetration levels on the grid by the year 2027. Nine separate solution alternatives are created using Coal, Natural Gas and Renewable & Emerging technologies as solution options to meet the identified ramping needs. Energy-mix and carbon prices are calculated for each of the solution scenarios and compared with the baseline scenario computed from the Intended Nationally determined Contribution (INDC) adopted by India in COP22. The paper concludes that the most energy cost and carbon price efficient paths for India to integrate ambitious RE capacity into India's power grid would be to convert and operate existing coal plants as peaker plants instead of as base load plants.

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Working Papers | 2017

Assessment of Density Forecast for Energy Commodities in Post-Financialization Era

Bisht Deepak and A. K. Laha

Probability density for the future price of an asset can be estimated from historical asset prices or exchange-traded derivatives. In this paper, prices of futures and options contracts that embed the forward-looking information are used to obtain the density forecast of the underlying asset under Q- measure. Along with Probability Integral Transform (PIT), various statistical testes are conducted to determine whether the option-implied density forecast is unbiased under the real world measure, P. We have worked with the settlement prices of NYMEX traded futures and options contracts for WTI crude oil and Henry Hub natural gas during the post-financialization period of 2006 to 2013. Statistical analysis of the PIT values indicate that the option-implied density forecast is unbiased under the real world measure, P.

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Working Papers | 2017

Pricing Option on Commodity Futures under String Shock

Bisht Deepak and A. K. Laha

Forward curve movements, particularly of industrial and energy commodities, suggests that futures price do not move in tandem with the spot price, and not all futures contracts move in the same direction. We incorporate these subtleties into our model with parsimony. This article offers a new approach to value commodity derivatives by using string shock. We use it to perturb the term structure of future convenience yield as if every futures contract has its source of risk. The no-arbitrage condition on the drift of future convenience yield and closed-form formula for the European call option written on a futures contract is derived. Our model has separate volatility and correlation functions that ensure easier parameterization and calibration to market data. We compare absolute and relative option pricing errors of our model with the two factor Schwartz (1997) model for 440 trading days. It is found that the new string shock based model has better performance than the Schwarz's model regarding having lesser pricing errors.

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Working Papers | 2017

The Horror of Urban Development in India – Identifying The Real Issues

Sebastian Morris

The horror of India's urban spaces cannot be understood without recognizing the core errors in planning and in the approach of infrastructural development. These stem mainly from the low FSI's that are used, the lack of any recognition of central place needs of different economic activities, the lack of even a modicum of integration of transport planning with layout planning (the so called "Master Plans"), an" architects' approach" to urban design, and most importantly to the organization mess-up that the urban local bodies are. Unless these change the large sums of money that would be spent would actually result in much subtraction of social and public value.

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