In this paper we decompose the interest rate swap yield curves of 10 major currencies into their common factors and find that the first two factors, interpreted as parallel shift and rotation, explain between 97.1% and 98.6% of the variation in the interest rate swap rates across all 10 currencies. The main contribution of the paper however is that we then model these two factors as simplified synthetic factors so that they may be used to develop an innovative approach to the computation of Value-at-Risk (VaR) for a portfolio of interest rate swaps.

Recent studies report an increasing use of nonfinancial measures such as product quality, customer satisfaction, and market share in performance measurement and compensation systems. A growing literature suggests that because current nonfinancial measures are better predictors of long-term financial performance than current financial measures, they help refocus managers on the long-term aspects of their actions. However, little empirical evidence is available on the relation between nonfinancial measures and financial performance, and even less is known about performance impacts of incorporating nonfinancial measures in incentive contracts. Using time-series data for 72 months from 18 hotels managed by a hospitality firm, this study provides empirical evidence on the behavior of nonfinancial measures and their impact on firm performance. The results indicate that nonfinancial measures of customer satisfaction are significantly associated with future financial performance and contain additional information not reflected in the past financial measures. Furthermore, both nonfinancial and financial performance improve following the implementation of an incentive plan that includes nonfinancial performance measures.

College educated couples are increasingly located in large metropolitan areas. These areas were home to 32 percent of all college educated couples in 1940, 39 percent in 1970, and 50 percent in 1990. We investigate whether this trend can be explained by increasing urbanization of the college educated or the growth of dual career households and the resulting severity of the colocation problem. We argue that the latter explanation is the primary one. Smaller cities may therefore experience reduced inflows of human capital relative to the past and thus become poorer.

Aït‐Sahalia (1996) and Stanton (1997) use nonparametric estimators applied to short‐term interest rate data to conclude that the drift function contains important nonlinearities. We study the finite‐sample properties of their estimators by applying them to simulated sample paths of a square‐root diffusion. Although the drift function is linear, both estimators suggest nonlinearities of the type and magnitude reported in Aït‐Sahalia (1996) and Stanton (1997) . Combined with the results of a weighted least squares estimator, this evidence implies that nonlinearity of the short rate drift is not a robust stylized fact.

We provide a simple explanation for the observation from the U.S. manufacturing sector that the job destruction rate fluctuates more than the job creation rate. In our model, proportional plant-level costs of creating and destroying jobs cause shrinking plants to be more sensitive to aggregate shocks than growing plants. We describe circumstances in which this microeconomic asymmetry is preserved in the aggregate and show that it can account for much of the observed asymmetries in gross job flows. This is so even though we abstract from job matching frictions, incomplete contracts, and aggregate congestion effects.

This paper demonstrates that the use of GARCH-type models for the calculation of minimum capital risk requirements (MCRRs) may lead to the production of inaccurate and therefore inefficient capital requirements. We show that this inaccuracy stems from the fact that GARCH models typically overstate the degree of persistence in return volatility. A simple modification to the model is found to improve the accuracy of MCRR estimates in both back- and out-of-sample tests. Given that internal risk management models are currently in widespread usage in some parts of the world (most notably the USA), and will soon be permitted for EC banks and investment firms, we believe that our paper should serve as a valuable caution to risk management practitioners who are using, or intend to use this popular class of models.

Saving and growth are strongly positively correlated across countries. Recent empirical evidence suggests that this correlation holds largely because high growth leads to high saving, not the other way around. This evidence is difficult to reconcile with standard growth models, since forward-looking consumers with standard utility should save less in a fast-growing economy because they know they will be richer in the future than they are today. We show that if utility depends partly on how consumption compares to a “habit stock” determined by past consumption, an otherwise-standard growth model can imply that increases in growth can cause increased saving.

Losing Sleep at the Market: The Daylight Saving Anomaly by Mark J. Kamstra, Lisa A. Kramer and Maurice D. Levi. Published in volume 90, issue 4, pages 1005-1011 of American Economic Review, September 2000

Money, Sticky Wages, and the Great Depression by Michael D. Bordo, Christopher J. Erceg and Charles L. Evans. Published in volume 90, issue 5, pages 1447-1463 of American Economic Review, December 2000