A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology

There are many opportunities and challenges in area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess performance of technical institutions based on multiple criteria. This paper is focused on performance evaluation and ranking of seven Indian Institute of Technology (IITs) in respect to stakeholders’ preference using an integrated model consisting of fuzzy AHP and COPRAS. Findings based on 2007–2008 data show that performance of two IITs need considerable improvement. To the best of our knowledge it is one of few studies that evaluates performance of technical institutions in India.     

On a property of orthogonal arrays and optimal blocking of fractional factorial plans

It is shown that fractional factorial plans represented by orthogonal arrays of strength three are universally optimal under a model that includes the mean, all main effects and all two-factor interactions between a specified factor and each of the other factors. Thus, such plans exhibit a kind of model robustness in being universally optimal under two different models. Procedures for obtaining universally optimal block designs for fractional factorial plans represented by orthogonal arrays are also discussed. Acknowledgements. The authors wish to thank the referees for making several useful comments on a previous version.     

Optimal variance- and efficiency-balanced designs for one- and two-way elimination of heterogeneity

Summary In this paper, a series ofE-optimal non-binary variance balanced (block or row-column) designs and a series ofE-optimal non-binary efficiency balanced (block or row-column) designs are provided in certain broad classes of competing designs. Furthermore, their high efficiencies by the usualA- andD-optimality criteria are shown.     

Predicting Downturns in the US Housing Market: A Bayesian Approach

This paper estimates Bayesian Vector Autoregressive (BVAR) models, both spatial and non-spatial (univariate and multivariate), for the twenty largest states of the US economy, using quarterly data over the period 1976:Q1–1994:Q4; and then forecasts one-to-four quarters-ahead real house price growth over the out-of-sample horizon of 1995:Q1–2006:Q4. The forecasts are evaluated by comparing them with those from an unrestricted classical Vector Autoregressive (VAR) model and the corresponding univariate variant of the same. Finally, the models that produce the minimum average Root Mean Square Errors (RMSEs), are used to predict the downturns in the real house price growth over the recent period of 2007:Q1–2008:Q1. The results show that the BVARs, in whatever form they might be, are the best performing models in 19 of the 20 states. Moreover, these models do a fair job in predicting the downturn in 18 of the 19 states.     

Bargaining and Search with Incomplete Information about Outside Options

This paper considers a model of bargaining in which the seller makes offers and the buyer can search (at a cost) for an outside option; the outside option cannot be credibly communicated, and the seller's offer is recallable by the buyer for one period. There are essentially two equilibrium regimes. For sufficiently high search cost, the game ends immediately; otherwise the search occurs in equilibrium. Compared to the case where the buyer can communicate his outside option, the seller is worse off, and the game results in search for a smaller set of values of the search cost, i.e., less equilibrium delay.C72.     

An Empirical Examination of the Divergence between Managers’ and Analysts’ Earnings Forecasts

We study circumstances when analysts’ forecasts diverge from managers’ forecasts after management guidance, and the consequences of this divergence for investors and analysts. Our results show that investors’ return response to earnings surprises based on analyst forecasts is significantly weaker when analyst and management forecasts diverge, and that this attenuating effect is stronger when the management forecast is more credible. When the divergent management forecast is more accurate than the analyst consensus forecast, the subsequent‐quarter analyst consensus forecast is significantly more accurate than that of the current quarter, and exhibits less serial correlation. Overall, our findings suggest that, when analyst and management forecasts diverge, investors find the two sources to contain complementary information, and analysts learn to improve their subsequent forecasts.     

Price convergence across regions in India

The paper attempts to examine whether there is price convergence across various regions in India. Using panel unit root tests that are robust to cross-sectional dependence, it is found that relative price levels among various regions in India are mean-reverting. Further, we decompose each series into a set of common factors and idiosyncratic components. The decomposition enables us to test stationarity and estimate half-lives of the common factors and the idiosyncratic components separately. Both these components are found to be stationary. Idiosyncratic price shocks, however, are found to be more persistent as compared to the common factor. Results also indicate that transportation cost proxied by distance can explain a part of the variation in prices between two locations in India. The authors would like to thank Dibyendu Bhaumik for arranging the data for this study. Views expresed in the paper are personal and do not reflect the views of the organizations.     

SOUTH–SOUTH TRADE: BEYOND GEOGRAPHY

Starting from a low base, south–south trade has picked up momentum over the last two decades. It is emerging as a new dimension of the global economy and can potentially usher in several benefits for developing economies. The emerging economies of the dynamic south (EEDS) not only provided a striking impetus to south–south trade but also contributed to the changing mise-en-scène of the global economy. However, given the moribund state of the Doha Round, additional policy measures need to be taken by the EEDS.     

Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period

The paper investigates the performance of Indian commercial banking sector during the post reform period 1992-2002. Several efficiency estimates of individual banks are evaluated using nonparametric Data Envelopment Analysis (DEA). Three different approaches viz., intermediation approach, value-added approach and operating approach have been employed to differentiate how efficiency scores vary with changes in inputs and outputs. The analysis links the variation in calculated efficiencies to a set of variables, i.e., bank size, ownership, capital adequacy ratio, non-performing loans and management quality. The findings suggest that medium-sized public sector banks performed reasonably well and are more likely to operate at higher levels of technical efficiency. A close relationship is observed between efficiency and soundness as determined by bank's capital adequacy ratio. The empirical results also show that technically more efficient banks are those that have, on an average, less non-performing loans. A multivariate analysis based on the Tobit model reinforces these findings.