Most studies on unions have concentrated on examining the union impact on wages. This thesis, in two essays, examines the union impact on wages, hours, earnings and employment, particularly focussing on the union impact on hours of work. The first essay summarizes previous theoretical union models which normally assume fixed hours of work and extends them so that hours as well as wages and employment can be determined by collective bargaining. Three kinds of union models are employed to examine union impacts on hours as well as union impacts on wages and employment: the monopoly union model (Oswald [1982]), the right to manage model (Nickell [1981]; Nickell and Andrews [1983]) and the efficient contracts model (McDonald and Solow [1980]). The predicted union impact on hours and employment is found to be ambiguous while the union impact on wages is found to be positive. The second essay is concerned with estimating union-nonunion wage, hours and earn ings differentials. Using the 1990 Labour Market Activity Survey, this essay finds that (1) union-nonunion hours differentials are ambiguous for males, but they are positive for females, (2) employers in the union sector extract more hours from more able workers and this contributes greatly to the positive union-nonunion hours differential and (3) union-nonunion hours differentials are smaller for males than for females and as a result, union-nonunion earnings differentials are larger for females than for males. / Arts, Faculty of / Vancouver School of Economics / Graduate

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published_or_final_version / abstract / Business / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Business / Doctoral / Doctor of Philosophy

Least cost formulations for surimi seafood were studied by linear programming (LP) and nonlinear programming (NLP). The effects of water and starches on functional properties of Alaska pollock and Pacific whiting surimi gels were investigated. Six starches (modified potato starch, potato starch, modified wheat starch, wheat starch, modified waxy corn starch, and corn starch) and their mixtures were used as ingredients. Mixture and extreme vertices design were used as experimental designs. Canonical models were applied to the optimization techniques. Blending different kinds of surimi showed linear trends for each functional property, so that LP was successfully employed to optimize surimi lots. Strong interactions were found between surimi and starch or in starch mixtures. Two optimum solutions, obtained from LP and NLP, were compared in this study. Corn starch and modified waxy corn starch greatly improved the functional properties. / Graduation date: 1997

Farm equipment is becoming an increasingly important financial asset for many farmers. Tractors probably represent the single largest component of equipment asset value. As such, changes in tractor values can have a dramatic effect on a farmer's financial situation. Changes in equipment value can be attributed to depreciation and the value of output produced. The general objective of this study was to identify a specific set of variables explaining changes in equipment value and to determine the relative importance of these variables. The Box-Cox power transformation technique was employed in estimating the depreciation patterns. The method was applied to two different sources of used tractor prices--auction and advertised. Remaining value (RV), defined as the real market price in time t divided by real purchase price, was regressed against several independent variables. These independent variables were age, usage per year, condition, horsepower, manufacturer, regions of the U.S., auction types, and net farm income. A number of these variables were found to have some important impact on RV. Depreciation patterns were found to differ between manufacturers. Significant differences in remaining values (RV) were found to exist for different regions of the U.S. and different auction types. For both auction and advertised data, an increase in usage produces a noticeable decrease in RV. For auction data, however, the level of usage tends to have greater influence on RV when the tractor is newer. The results did not closely approximate any clear depreciation pattern. The depreciation patterns are accelerated relative to straight-line method and are a combination of the geometric and sum-of-the-year's digits functions. The RV model was used to examine optimal replacement ages for farm tractors. Annual usage levels had the most influence on the age at which tractors were replaced. Expensing and some tax law changes had a less significant impact. / Graduation date: 1989

Japan is the largest market for U.S. forest products. Therefore, export of wood products to this country is critical to the economic life of the forest industry in the U.S. and particularly for the Pacific Northwest. Hence, economic conditions and developments in Japan may significantly affect the volume of trade for the products of concern and, in turn, the well-being of the U.S. lumber and log production-consumption system. Few studies have addressed forest product trade between the U.S. and Japan. This study is designed to determine the effect of several selected market factors on the Japanese import demand for U.S. softwood lumber and logs and to estimate the influence of these factors on Japan's future trade. A numerical model was developed incorporating these selective factors, thought to be relevant, to determine their effects on the Japanese market for the U.S. forest products. The evaluation considers the effects of variations in: Japanese income, domestic production of softwood logs in Japan, domestic prices of the products of concern, petroleum purchased by Japan, nominal interest rates in Japan, the exchange rates, and finally a weighted average of prices of the products from the Pacific Northwest (Oregon and Washington, only). Given the available resources, two empirical time series models for each commodity were estimated by OLS technique using annual data from 1961 through 1985. The results indicate that the Japanese import demands for both products are inelastic. This finding, along with other evidence, suggests the distortion of the Japanese import demand for U.S. forest products by factors other than economic, mainly politics involved in trade restraint between the two countries. The study shows that GNP per capita, housing starts, and the interest rates in Japan, significantly affect the Japanese import demand for lumber from the U.S. Housing starts is the only significant factor in the case of the Japanese import demand for U.S. logs. In the latter case, the exchange rates and log export prices to Japan (deflated by Japan's wholesale price index), are significant only when the log linear model has been applied. / Graduation date: 1988

M.Com. (Economics) / Please refer to full text to view abstract

M.Com.(Econometrics) / The objective of this study is to evaluate different estimation techniques that can be used to estimate the coefficients of a model. The estimation techniques were applied to empirical data drawn from the South African economy. The Monte Carlo studies are unique in that data was statistically generated for the experiments. This approach was due to the fact that actual observations on economic variables contain several econometric problems, such as autocorrelation and MUlticollinearity, simultaneously. However, the approach in this study differs in that empirical data is used to evaluate the estimation techniques. The estimation techniques evaluated are : • Ordinary least squares method • Two stage least squares method • Limited information maximum likelihood method • Three stage least squares method • Full information maximum likelihood method. The estimates of the different coefficients are evaluated on the following criteria : • The bias of the estimates • The variance of the estimates • t-values of the estimates • The root mean square error. The ranking of the estimation techniques on the bias criterion is as follows : 1 Full information maximum likelihood method. 2 Ordinary least squares method 3 Three stage least squares method 4 Two stage least squares method 5 Limited information maximum likelihood method The ranking of the estimation techniques on the variance criterion is as follows : 1 Full information maximum likelihood method. 2 Ordinary least squares method 3 Three stage least squares method 4 Two stage least squares method 5 Limited information maximum.likelihood method All the estimation techniques performed poorly with regard to the statistical significance of the estimates. The ranking of the estimation techniques on the t-values of the estimates is thus as follows 1 Three stage least squares method 2 ordinary least squares method 3 Two stage least squares method and the limited information maximum likelihood method 4 Full information maximum likelihood method. The ranking of the estimation techniques on the root mean square error criterion is as follows : 1 Full information maximum likelihood method and the ordinary least squares method 2 Two stage least squares method 3 Limited information maximum likelihood method and the three stage least squares method The results achieved in this study are very similar to those of the Monte Carlo studies. The only exception is the ordinary least squares method that performed better on every criteria dealt with in this study. Though the full information maximum likelihood method performed the best on two of the criteria, its performance was extremely poor on the t-value criterion. The ordinary least squares method is shown, in this study, to be the most constant performer.