SOME ASPECTS OF THE DYNAMIC PROPERTIES OF ECONOMETRIC MODELS*

Recent efforts by several authors have resulted in the development of techniques for analytically describing the dynamic properties of linear stochastic difference equation models ¹ 1 For examples of this work see Chow [1]; Chow and Levitan [2] [3]; Howrey [8] [9]; Howrey and Kelejian [10] and Howrey and Klein [11].
. Since these techniques have not been extensively applied to econometric models and consequently are not generally familiar to economic modelers, the purpose of this paper is to summarize the techniques these researchers have developed and to illustrate them using a simple (and admittedly unrealistic) econometric model.     

A NOTE ON A MULTIVARIATE GENERALIZATION OF THE KRUSKAL-WALLIS TEST

Marketers are often interested in testing whether the mean vectors of multivariate distributions are equal. The test usually applied, one-way MANOVA, assumes the distributions are multinormal. Unfortunately, this assumption is not supported in many studies. As an alternative, a nonparametric multivariate one-way analysis of variance procedure is presented.     

Catch-up as a Survival Strategy in the Solar Power Industry

We evaluate the strategies of the emerging market firms in the context of nascent industries. We use the Indian solar power industry as the empirical setting, against the backdrop of the evolution of the global industry, While in traditional industries emerging market firms learn from advanced economy multinational enterprises (MNEs) and slowly upgrade their capabilities, in the intensely competitive environment of nascent innovative industries, emerging market firms are exposed to global competition in their home market right from the early years. This shortens their catch-up clock. As a result, their long-term survival depends on their ability to catch-up fast, both in output and innovation capabilities. In the solar power industry, we find that innovations stem, in the main, from advanced economy firms. Further, Chinese firms are beginning to move from cost-based imitation to innovation. In contrast, with a few key exceptions, most firms in the Indian solar industry remain locked within a narrow niche of downstream site-based installation. Their operations are opportunistic, short term, and without specific catch-up goals, a scenario that does not bode well for the industry's future in India.     

Decision Making in `Random in a Broad Sense' Environments

It is shown that the uncertainty connected with a `random in a broad sense' (not necessarily stochastic) event always has some `statistical regularity' (SR) in the form of a family of finite-additive probability distributions. The specific principle of guaranteed result in decision making is introduced. It is shown that observing this principle of guaranteed result leads to determine the one optimality criterion corresponding to a decision system with a given `statistical regularity'.     

Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.     

Bayesian prediction of waiting times in stochastic models

The authors show how saddlepoint techniques lead to highly accurate approximations for Bayesian predictive densities and cumulative distribution functions in stochastic model settings where the prior is tractable, but not necessarily the likelihood or the predictand distribution. They consider more specifically models involving predictions associated with waiting times for semi‐Markov processes whose distributions are indexed by an unknown parameter θ. Bayesian prediction for such processes when they are not stationary is also addressed and the inverse‐Gaussian based saddlepoint approximation of Wood, Booth & Butler (1993) is shown to accurately deal with the nonstationarity whereas the normal‐based Lugannani & Rice (1980) approximation cannot, Their methods are illustrated by predicting various waiting times associated with M/M/q and M/G/1 queues. They also discuss modifications to the matrix renewal theory needed for computing the moment generating functions that are used in the saddlepoint methods.     

Residential preferences and population distribution

Public opinion research has revealed decided preferences for living in rural areas and small towns, and proponents of population deconcentration have interpreted this as support for their policies. This study, based on a national sample, yielded similar results, but when we introduced the additional possibility of a preference for proximity to a larger city, then the rural areas preferred were found, for most respondents, to be those within the commuting range of a metropolitan central city. Although persons wishing to live near large cities were found to be looking for the same qualities of living sought by those who prefer a more remote location, these findings are not, in general, consistent with the argument that public preferences support strategies of population dispersal into nonmetropolitan areas. Instead they indicate that most of those who wish to live in a different location favor the peripheral metropolitan ring areas that have, in fact, been growing rapidly by in-migration.     

Congestion,quality deterioration,and optimal use: Wilderness recreation in the Spanish peaks primitive area

With increasing demand for low-density recreational services and limited supply of facilities to provide them, congestion is becoming an important management problem. The purpose of this paper is to outline a model of congestion, estimate the effect of it upon individual willingness to pay for wilderness experiences, and illustrate how these results might be used for efficient management. A survey of users of the Spanish Peaks Primitive Area indicates that their revealed willingness to pay is significantly affected by encroachments upon the solitude they experience during their trip. Consequently, congestion effects for such services can be measured and used in the formation of administrative policy.     

Effects of Group Practice of the Transcendental Meditation Program on Preventing Violent Crime in Washington,D.C.: Results of the National Demonstration Project,June--July 1993

This paper reports the results of a prospective experiment in which a group of approximately 4,000 participants in the Transcendental Meditation and TM-Sidhi programs of Maharishi Mahesh Yogi assembled in Washington, D.C., from June 7 to July 30, 1993. It was hypothesized that levels of violent crime in the District of Columbia would fall substantially during the Demonstration Project, as a result of the group's effect of increasing coherence and reducing stress in the collective consciousness of the District. A 27-member Project Review Board comprising independent scientists and leading citizens approved the research protocol and monitored the research process. Weekly crime data was derived from database records provided by the District of Columbia Metropolitan Police Department (DCMPD), which are used in the FBI Uniform Crime Reports. Statistical analysis considered the effect of weather variables, daylight, historical crime trends and annual patterns in the District of Columbia, as well as trends in neighboring cities. Consistent with previous research, levels of homicides, rapes and assaults (HRA crimes) correlated with average weekly temperature. Robberies approximately followed an annually recurring cycle. Time series analysis of 1993 data, controlling for temperature, showed that HRA crimes dropped significantly during the Demonstration Project, corresponding with increases in the size of the group; the maximum decrease was 23.3% (p < 2 × 10–9) [24.6% using a longer baseline, with 1988--1993 data (p < 3 × 10–5)], coincident with the peak number of participants in the group during the final week of the assembly. When the same period in each of the five previous years was examined, no significant decreases in HRA crimes were found. Robberies did not decrease significantly. However, a model that jointly estimated the effect of the Demonstration Project on both HRA crimes and robberies showed a significant reduction in violent crimes overall of 15.6% (p = 0.0008). Further analysis showed that the effect of the coherence-creating group on reducing HRA crimes could not be accounted for by additional police staffing. The time series analysis for HRA crimes gave results that are highly robust to alternative model specifications, and showed that the effect of the group size was cumulative and persisted after the Demonstration Project ended. Also, calculation of the steady state gain based on the time series model predicted that a permanent group of 4,000 coherence-creating experts in the District would have a long-term effect of reducing HRA crimes by 48%.