Inducing Efficiency in Oligopolistic Markets with Increasing Returns to Scale

We consider a Cournot Oligopoly market of firms possessing increasing returns to scale technologies. It is shown that an external regulating agency can increase total social welfare without running a deficit. It offers to subsidize one firm an amount which depends on the output level of that firm. The firms bid for this contract and the regulator collects the highest bid and subsidizes the highest bidding firm. It is shown that there exists a subsidy schedule such that (i) The regulator breaks even (namely the winning bid equals the total subsidy) (ii) The winning firm obtains zero net profit and charges a price equal to its average cost (iii) Every other firm willingly exit the market and (iv) Market price decreases, consumers are better off and total welfare improves.Regulation, Oligopoly, Increasing Returns

SOCIAL SIMULATION WITHIN CONSUMER GOODS INDUSTRY: THE WAY FORWARD

ABSTRACT Simulation based research, especially for social systems have grown in size and matured in the last two decades. But in spite of high potential impact, adoption and applicability within businesses is relatively low, especially so in the consumer goods industry. This paper indicates some key focus areas in research which, if pursued consistently, are most likely to have the highest impact. These areas are: providing complementary predictive capability to standard market mix models, modelling disruptive changes in the market, increased partnership with the automated personalized algorithms research community and focussing on toolkits which can be directly used by businesses for training and research purposes. It goes on to point out strategies which can be adopted by the research community which will increase the chances of effectively focussing research onto the areas mentioned above

Generator Contribution Based Congestion Management using Multiobjective Genetic Algorithm

 Congestion management is one of the key functions of system operator in the restructured power industry during unexpected contingency. This paper proposes a method for generator contribution based congestion management using multiobjective genetic algorithm. In the algorithm, both real and reactive losses have been optimised using optimal power flow model and the contributions of the generators with those optimised losses are calculated. On second level, the congested lines are identified by the proposed overloading index (OI) during contingency and those lines are relieved with the new contribution of generators, which is the outcome of the developed algorithm. The planned method depicts the information related to congestion management to minimize the investment cost, without installing any external devices and to maximise the consumer welfare by avoiding any load curtailment without affecting the voltage profile of the system as well as the optimised total system loss. IEEE 30 bus system is used to demonstrate the effectiveness of the method

Use of SIMD-Based Data Parallelism to Speed up Sieving in Integer-Factoring Algorithms

Many cryptographic protocols derive their security from the apparent computational intractability of the integer factorization problem. Currently, the best known integer-factoring algorithms run in subexponential time. Efficient parallel implementations of these algorithms constitute an important area of practical research. Most reported implementations use multi-core and/or distributed parallelization. In this paper, we use SIMD-based parallelization to speed up the sieving stage of integer-factoring algorithms. We experiment on the two fastest variants of factoring algorithms: the number-field sieve method and the multiple-polynomial quadratic sieve method. Using Intel’s SSE2 and AVX intrinsics, we have been able to speed up index calculations in each core during sieving. This performance enhancement is attributed to a reduction in the packing and unpacking overheads associated with SIMD registers. We handle both line sieving and lattice sieving. We also propose improvements to make our implementations cache-friendly. We obtain speedup figures in the range 5--40%. To the best of our knowledge, no public discussions on SIMD parallelization in the context of integer-factoring algorithms are available in the literature

Is India Ready for Inflation-Targeting?

In this paper we analyze whether the current macroeconomic environment in India is suitable for implementation of inflation targeting as a monetary policy strategy, in light of the recommendation of the Urjit Patel Committee Report. Our results indicate that historically the Reserve Bank of India has given more importance to inflation compared to output growth and exchange rate changes in its monetary policy conduct and that in recent times there has been an increased emphasis on monetary independence thereby comfortably placing the RBI on a path to move towards inflation targeting. However we also find factors, that are traditionally outside the control of monetary policy, do exert a strong impact on aggregate prices in India thereby making the choice of nominal anchor a tricky one. Furthermore, the success of monetary policy in containing inflation is found to be crucially contingent on an appropriate fiscal policy as well

University research and knowledge transfer: A dynamic view of ambidexterity in british universities

This paper examines the dynamic interlinkages between the two pillars of ambidexterity in universities, research and knowledge transfer. We propose a theoretical model linking these two pillars at the organisational level. The model is tested using the longitudinal HE-BCI survey data juxtaposed against two consecutive rounds of research evaluation in the UK higher education sector. Results indicate that a university's past performance along the research pillar strengthens the knowledge transfer pillar over time, through both commercialisation and academic engagement channels. This positive impact is negatively moderated by the university's size and reputation, in the sense that in larger or more reputed universities, the marginal impact of research on knowledge transfer declines significantly. Additionally, we find that knowledge transfer reinforces the research pillar through positive mediation between past and future research, but only through academic engagement channels. The results also indicate that contract research routes provide the maximum benefit for most universities in enhancing their ambidexterity framework, both in the short and the long run. For the relatively more reputed universities, it is the collaboration route which provides the maximum benefit. Interestingly, no such reinforcement could be detected in the case of the research commercialisation channels

Is India Ready for Inflation-Targeting?

In this paper we analyze whether the current macroeconomic environment in India is suitable for implementation of inflation targeting as a monetary policy strategy, in light of the recommendation of the Urjit Patel Committee Report. Our results indicate that historically the Reserve Bank of India has given more importance to inflation compared to output growth and exchange rate changes in its monetary policy conduct and that in recent times there has been an increased emphasis on monetary independence thereby comfortably placing the RBI on a path to move towards inflation targeting. However we also find factors, that are traditionally outside the control of monetary policy, do exert a strong impact on aggregate prices in India thereby making the choice of nominal anchor a tricky one. Furthermore, the success of monetary policy in containing inflation is found to be crucially contingent on an appropriate fiscal policy as well