Nowcasting sales growth of manufacturing companies in India

The performance of private corporate sector is used as an important demand indicator for monetary policy making. As these data are received with a lag, assessing and monitoring of corporate sales on a real-time basis poses a significant challenge to policy makers in India. In this context, this article attempts to nowcast quarterly sales growth of Indian manufacturing companies and GDP growth of India using dynamic factor modelling framework. A multiple-level framework through turning point analysis and elastic net structure is used to overcome the overfitting problem during variable selection. Empirical results show improvement in forecast accuracy for one quarter ahead nowcast using 3-factor and 4-factor models over the benchmark model. However, absolute dominance of 3-factor models over 4-factor models was not established. As such, the article has proposed a forecast combination technique to nowcast sales growth of manufacturing companies in India.     

Time varying consumption covariance and dynamics of the equity premium: Evidence from the G7 countries

We examine implications of time-varying correlation and covariance between excess equity returns and consumption growth for the equity premium of the G7 countries. We find that the correlation and covariance are higher when there is a negative shock to labor income and a positive shock to returns. The combined effect is that the correlation and covariance are countercyclical and so is the equity premium. We test asset pricing models with time-varying consumption risk and find that the conditional price of risk is generally positive. These results survive several robustness checks. Our results highlight the importance of labor income for understanding dynamics of the equity premium.     

Statistical Causality and Strategic Behavior in Industrial Markets

This paper proposes a simple test of the leader-follower model of strategic behavior. This test relates the temporal notions of leadership central to such models to the empirical methods of statistical causality. This test is performed using data from the US softwood plywood industry of the last three decades. Others have productively explored the spatial pricing practices of this industry by applying a leader-follower model. Similarly, we find that a leader-follower model explains well the temporal relations between key strategic variables (prices) in the industry. We conclude that the leader-follower model imposes meaningful restrictions on observable time-series data and that statistical causality is a useful method for testing these restrictions.     

Optimal Bond Refunding: A Practical Approach

Although there is substantial research on optimal bond refunding, an important real-life feature is missing from the existing literature: imperfect adjustment or 'stickiness' of bond yields to short term interest rate changes. Our model takes this behavior into account, and also has the ability to handle mean reverting interest rates. The results indicate that the former has a significant effect on the optimal refunding policy (especially for longer maturities), but the latter does not. By incorporating these features, our model will hopefully offer a fairly complete and easily implementable guide to managers with regard to the bond refunding decision.     

Externalities, potential, value and consistency

We provide new characterization results for the value of games in partition function form. In particular, we use the potential of a game to define the value. We also provide a characterization of the class of values which satisfies one form of reduced game consistency.     

ILLIQUIDITY RISK,PROJECT CHARACTERISTICS,AND THE OPTIMAL MATURITY OF CORPORATE DEBT

I derive the optimal maturity period for corporate debt used to finance a specific project, when costly financial distress is triggered by the inability to meet coupon obligations. My model predicts a negative relation between bond risk and maturity, and it explains why high-grade bonds show greater maturity dispersion than low-grade bonds, as observed in U.S. corporate bond markets. The major determinant of bond maturity is project duration for low-risk bonds and project risk for high-risk bonds. Other determinants of bond maturity are debt burden, reorganization costs, corporate tax rate, interest rate, and project growth rate.     

Belief Networks for Expert System Development in Auditing

This study examines the use of a belief network based expert system for an auditing task—financial distress evaluation for banks. A belief network uses probability measures to store important dependencies across variables of interest in a problem domain, and makes inferences based on observed evidence using probability calculus. This paper discusses how belief network structures can be constructed, and used to assist auditor's in making appropriate recommendations regarding the financial health of a bank under audit. The ability of a belief network to make reliable predictions depends on how well the network structure reflects the underlying dependencies across variables in the problem domain (e.g. financial ratios and the financial health of a bank). The first part of this study illustrates how a computer program developed by the authors can be used to generate and evaluate different feasible belief network structures based on historical data. The program uses an information-theoretic measure to compare the alternative structures. The ability of the program to identify existing dependencies across variables is demonstrated by using it to reconstruct a known network structure from simulated data. Next, the program is used on a database of twelve important bank financial ratios over a three-year period. The predictive ratios identified by the program reflect important areas of a bank's health, such as loan quality, efficiency, profitability and capital adequacy. Finally, a belief revision mechanism is encoded for the belief network structure identified earlier, and is used to illustrate how it can assist auditors in making recommendations about financial health based on a bank's critical financial ratios. The probability estimates provided by the system are validated using data on banks not used in the network design stage, and are found to be reliable.     

Does competition under Medicare Prospective Payment selectively reduce expenditures on high-cost patients?

Competition and prospective payment have been widely used to control health care costs but may together provide incentives to selectively reduce expenditures on high-cost relative to low-cost patients. We use patient discharge and hospital financial data from California to examine the effects of competition on costs for high- and low-cost admissions in the 12 largest Diagnosis-Related Groups before and after the Medicare Prospective Payment System (PPS). We find that competition increased costs before PPS, but that this effect decreased afterward, especially inpatients with the highest costs.We conclude that competition and PPS selectively reduced spending among the most expensive patients and that careful assessment of these patients' outcomes is important.