Another look at risk apportionment

This paper presents a general result on the random selection of an element from an ordered sequence of risks and uses this result to derive additive and cross risk apportionment. Preferences favoring an improvement of the sampling distribution in univariate or bivariate first-order stochastic dominance are those exhibiting additive or cross risk apportionment. The univariate additive and multiplicative risk apportionment concepts are then related to the notion of bivariate cross risk apportionment by viewing the single-attribute utility function of an aggregate position (sum or product of attributes) as a 2-attribute utility function. The results derived in the present paper allow one to further explore the connections between the different concepts of risk apportionment proposed so far in the literature.     

Another look at sticky prices and output persistence

Price rigidity is the key mechanism for propagating business cycles in traditional Keynesian theory. Yet the new Keynesian literature has failed to show that sticky prices by themselves can effectively propagate business cycles. We show that price rigidity in fact can (by itself) give rise to a strong propagation mechanism in standard models, provided that investment is also subject to a cash-in-advance constraint. Reasonable price stickiness can generate highly persistent, hump-shaped movements in output under either monetary or non-monetary shocks. Hence, whether or not price rigidity is responsible for output persistence is not a theoretical question, but an empirical one.     

Another look at the naive estimator in a regression model

We consider the linear regression model where only a particular linear function of the dependent variables is observed, Stahlecker and Schmidt (1987) proposed a naive least squares (LS) estimator for regression coefficients in such a case. In this note we represent their estimator as a general ridge estimator. This observation leads to a view different from the previous work and provides an easy way of obtaining many important properties of the naive LS estimator. Our approach also gives some insight into the relationship between the naive LS estimator and the generalized least squares estimator.     

The baby boom and the housing market: Another look at the evidence

Based on tests for cointegration, the growth of housing demand resulting from the Baby Boom appears to be the major factor behind increased real residential investment, but not the major factor behind increased real housing prices in the postwar U.S. The housing market also passes a simple test for efficiency.     

Another look at Swedish business cycles, 1861–1988

The linearity of nine long Swedish macroeconomic time series, whose business cycle properties were discussed by Englund, Persson, and Svensson (1992), is tested and rejected for all but two. Non-linear (STAR) models are estimated, and their properties are investigated. Business cycle frequency variation does not seem to be constant over time for all series; it is difficult to find a ‘Swedish business cycle’. Pairwise Granger non-causality tests are adapted to the STAR case, and non-causality is tested. The results point at strong temporal interactions and indicate that the functional form (linear or STAR) strongly affects the outcome of these tests. Copyright © 1999 John Wiley & Sons, Ltd.     

A micro-macro linkage in the measurement of inequality: Another look at the Gini coefficient

The aim of this paper is to help readers understand the significance of the Gini coefficient. We have two major formulae for the Gini coefficient. One of the formulae bases on the idea of aggregation of the microscopic differences between individuals' incomes or wealth. The idea that underlies the other formula is macroscopic presentation of distribution or concentration of income or wealth. We will show an unabridged proof of the equivalence between these formulae to examine how the two conceptions of the measurement of inequality are linked to each other.     

Another look at the role of emotion in the organizational change: A process model

The paper proposes a cognitive–emotional model of organizational change. It is argued that employees' emotions go through four sequential but distinguishable stages in the organizational change process. In the first stage, primary appraisal induces emotions that are high in arousal, mixed in hedonic tones, and are anticipatory. In the second stage, the mixed emotional experiences give way to either positive or negative emotions as a result of the secondary appraisal. The emotional experience then affects employees' coping behaviors in the third stage. In the forth stage, discrete emotions that are evaluative and have distinct action tendencies are induced. Given this changing nature of employees' emotional experiences during the organizational change process, and considering emotions' influence on individuals' attitudes and behaviors, it is suggested that change agents adjust the timing and content of the information communicated in order to promote employee acceptance to change. Implications of this conceptualization are discussed, as are directions for future research.     

Stock returns and volatility: Another look

Most empirical work examining the intertemporal mean-variance relationship in stock returns has tended to use relatively simple specifications of the mean and especially of the conditional variance. We augment the information set to include economic variables that other researchers have found to be important and use GARCH-M models to explore the relation between volatility and expected stock returns. We find that the additional variables have little impact on the conditional variance and that any intertemporal relationship between volatility and stock returns is weak or unstable. Our results signal the need for theoretical models of the intertemporal volatility-return relationship, and call for further studies of the determinants of the conditional variance of stock returns.     

Public capital and regional output : Another look at some Japanese and American data

Japanese and American data are used to recover estimates of regional production functions that include government capital as an input. Estimated parameters are used to simulate allocations of government capital which would have resulted in equal per employee outputs across states and regions. Base case estimates indicate that complete equalization would have increased aggregate output by about 8 percent in 1954 but reduced it by 14 percent in 1963, in Japan, and reduced aggregate output by about 25 percent in the U.S. in 1972. Sensitivity analyses show that these results are not affected much by small changes in the parameters.     

Another Look at England

When Dr. Francis Neilson went abroad last year several commissions were given him by this J ournal . One was that he scout up promising young English scholars interested in our field. He found much interest, but only among the older scholars. Another was that by personal observation, interviewing informed friends and study of the periodical press, he make an informal survey of the social situation in England along the lines that William Cobbett found so fruitful. The results are given in the following report.     

Modeling Financial Sector Joint Tail Risk in the Euro Area

We develop a novel high‐dimensional non‐Gaussian modeling framework to infer measures of conditional and joint default risk for numerous financial sector firms. The model is based on a dynamic generalized hyperbolic skewed‐t block equicorrelation copula with time‐varying volatility and dependence parameters that naturally accommodates asymmetries and heavy tails, as well as nonlinear and time‐varying default dependence. We apply a conditional law of large numbers in this setting to define joint and conditional risk measures that can be evaluated quickly and reliably. We apply the modeling framework to assess the joint risk from multiple defaults in the euro area during the 2008–2012 financial and sovereign debt crisis. We document unprecedented tail risks between 2011 and 2012, as well as their steep decline following subsequent policy actions. Copyright © 2016 John Wiley & Sons, Ltd.     

A new look at the two-mode problem

This paper considers the second-best policy problem that arises when auto travel is priced below its marginal cost and there is a substitute mass transit mode. We analyze the problem by combining a model of a rail line based on Kraus and Yoshida (J. Urban Econ. 51 (2002) 170) with the highway bottleneck model. The model involves a transit authority which optimizes, in addition to the fare, two dimensions of transit capacity. These are (1) the number of train units serving the route and (2) the capacity of an individual train unit. Under a very weak condition, second-best optimality involves expanding both dimensions of transit capacity. The larger percentage effect is on train capacity.     

Industrial energy efficiency: A look at the data

It is extremely difficult to make a precise, quantitative assessment of the impact of the myriad of factors affecting the improvement in industrial energy efficiency. It is certainly not correct to conclude that housekeeping measures alone have led to the observed improvement. Changing product mix among four digit SIC industries within the same two digit classification, variations in capacity utilization (returns to scale) and energy price increases as well as technological innovations have all contributed to part of the realized reduction in energy use per dollar value added over the period of investigation. Unfortunately, data limitations as well as modeling weaknesses prohibit an exact delineation of the impact of each of the factors on the increase in energy efficiency. The best that can be done—and quite convincingly so—is to qualitatively show that unequivocally these factors had an impact on the efficiency with which energy was used in the manufacturing process for the ten most energy intensive industries in the period 1971–1976.     

A look at productivity at the firm level in eight French service industries

In this paper, we take advantage of information collected by the French annual survey of market services to analyze productivity differences and changes among firms in eight major industries (restaurants, hotels, engineering, computer programming, computer processing, legal services, accounting and building cleaning), over the five-year period 1984–1988. We find a pattern of cross-sectional and time-series type estimates of the Cobb-Douglas production function, which is comparable to that typically found in studies of manufacturing industries, thus raising similar issues of interpretation and modeling. Using a capital stock measure corrected for rented equipment and building and taking into account the number of hours of work of work per employee improve these estimates to some extent. An interesting finding is that the output elasticity seems significantly smaller with respect to hours per employee than with respect to the number of employees.