Showing papers on "Pooling published in 1974"

Quantitative pooling of Michaelis-Menten equations in models with parallel metabolite formation paths

Abstract: Pooling of Michaelis-Menten equations for models having parallel paths for formation of two or more metabolites is discussed. A theory which explains phenomena exhibited by pooled nonlinear pharmacokinetic systems and equations relating pooled Michaelis-Menten constants (V p ,K p )to microscopic constants (V i ,K i )are presented. The suitability of this type of pooling for use in pharmacokinetic modeling is also discussed. Use of pooling concepts in the design of clinical studies is demonstrated.

To Pool or Not to Pool in Hypothesis Testing

Abstract: Necessary and sufficient conditions for admissibility are given for test procedures based on a preliminary test of significance. Three types of problems are studied—testing the normal mean, fixed effects models of the analysis of variance and random effects models. Admissibility in this instance is equivalent to the intuitive and practical condition that acceptance regions of the procedures have convex sections in certain variables, while other variables are fixed. It is easy to check when the conditions hold. A discussion of optimality properties of these and other types of pooling procedures is given.

Optimum Allocation of Risk in a Market With Many Traders

Abstract: In a market with ‘many’ traders who bear risks, there is the possibility of pooling their independent risks and in this way to eliminate traders’ risks. There is a benefit from trade, and the way this benefit is divided between the traders depends on the system of exchange.

Chain pooling to minimize prediction error in subset regression

Abstract: Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.

Pooling time-series and cross-section data: A review

Abstract: Summary The increased availability of disaggregated information over time provides opportunities for a more complete analysis in economic research. It also poses the problem as to how to make a more efficient use of such data. Different methods of pooling time-series and cross-section data have been proposed. Some consider the problem of obtaining extraneous information from a cross-section sample in order to incorporate this into a time-series. Other methods focus on a specification of the error structure of the model. These methods are not mutually exclusive. This article reviews the different methods, outlining both their merits and limitations.

Pooling as a specification error-a note

Abstract: THE PRACTICE of pooling cross section data with time series has been found to be very useful in applied econometric work. Frequently, investigators have estimated some parameters from a single cross section sample and have used these estimates as prior restrictions in the time series equation. Tobin's study of demand for food [2] is a classic example of this. Tobin estimated the income elasticity of demand for food from family budget data for 1941 and used this as prior information in the time series equation for demand for food using annual observations from 19131941. This practice of pooling is justified by specifying the equation in a general (microeconomic) form and treating income elasticity as a long run parameter best estimated from cross section data, whereas price elasticity is designated as a short run response. The possibility, however, always exists that the income elasticity estimated from cross section data may not be the appropriate prior restriction for the time series equation. This may be due to reasons of aggregation bias or because of the fact that income may be a proxy for cyclical fluctuations in time series analysis. It is necessary, therefore, to test the validity of such a prior restriction. Maddala [1] has provided a likelihood ratio test for the pooling of a single cross section sample with time series data. Applying his method to Tobin's study, he found that pooling was inappropriate. In this note, we would like to suggest that the Durbin-Watson (DW) statistic may provide the same information. We compare the DW statistic for the restricted equation (i.e., using the cross section information) with that for the unrestricted equation. All other variables are identical, and therefore the statistics are comparable. Since it is well known that misspecification may lead to serial correlation, a drop in the DW statistic for the restricted as against the unrestricted equation is a clear indication that pooling is a specification error. Tobin's equation for demand for food can be written as

"pooling" human resources

Abstract: The first and perhaps most important step in setting up a ride pooling program is to ascertain management's role in, and attitude toward, the pooling program. After assigning responsibility for the program and surveying its potential, employers must convince prospective ride poolers that the financial benefits, the peer recognition, the special privileges, and the other advantages of ride pooling outweigh the benefits of convenience and privacy offered by one-passenger/one-vehicle commuting. Choosing between manual and computer-based matching systems is a fairly simple procedure and is influenced by the potential size of the pooling operation, the desired degree of control over the program, the availability of appropriate data processing equipment, and the probability of becoming part of a multi-employer or communitywide system.

The 3M Commute-A-Van Program

Abstract: The 3M Commute-A-Van Program is a system whereby the 3M Company furnishes a standard 12-passenger van to an employee willing to take at least 8 other employees to and from work. The employee driver is compensated with free rides, personal use of the van at a reasonable mileage rate and the excess fares for any passengers over the minimum of 8. The program began as a 6-van pilot operation at 3M Center in April 1973. Since that time, the program has expanded to include as of May 1974, a total of 57 vans. Further expansion of the program at 3M installations both in St. Paul, Minnesota, and elsewhere is anticipated. Many transportation, environmental, and energy benefits have been achieved as a direct result of 3M's Commute-A-Van Program. In addition, a substantial amount of ramp-type parking construction at 3M Center has been delayed. Many other van pooling programs have been started by other firms as a result of the 3M experience. It is felt that van pooling can certainly make a significant contribution towards solving many of our perplexing urban transportation problems. /Author/