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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.

This thesis aims to provide new and useful insights into the effects that various tax, labour and product market reforms have on the overall economic performance. Additionally, it aims also to provide insights about the optimal monetary and fiscal policy behaviour within the economy characterized with various real labour market frictions. We analyze the benefits of tax reforms and their effectiveness relative to product or other labour market reforms. A general equilibrium model with imperfect competition, wage bargaining and different forms of tax distortions is applied in order to analyze these issues. We find that structural reforms imply short run costs but long run gains; that the long run gains outweigh the short run costs; and that the financing of such reforms will be the main stumbling block. We also find that the effectiveness of various reform instruments depends on the policy maker's ultimate objective. More precisely, tax reforms are more effective for welfare gains, but market liberalization is more valuable for generating employment. In order to advance our understanding of the tax and product market reform processes, we then develop a dynamic stochastic general equilibrium model which incorporates search-matching frictions, costly ring and endogenous job destruction decisions, as well as a distortionary progressive wage and a at payroll tax. We confirm the negative effects of marginal tax distortions on the overall economic performance. We also find a positive effect of an increase in the wage tax progressivity and product market liberalization on employment, output and consumption. Following a positive technology shock, the volatility of employment, output and consumption turns out to be lower in the reformed economy, whereas the impact effect on inflation is more pronounced. Following a positive government spending shock the volatility of employment, output and consumption is again lower in the reformed economy, but the inflation response is stronger over the whole adjustment path. We also find detrimental effects on employment and output of a tax reform which keeps the marginal tax wedge unchanged by partially offsetting a decrease in the payroll tax by an increase in the wage tax rate. If this reform is anticipated one period in advance the negative effects remain all over the transition path. We investigate the optimal monetary and fiscal policy implication of the New-Keynesian setup enriched with search-matching frictions. We show that the optimal policy features deviation from strict price stability, and that the Ramsey planner uses both inflation and taxes in order to fully exploit the benefits of the productivity increase following a positive productivity shock. We also find that the optimal tax rate and government liabilities inherit the time series properties of the underlying shocks. Moreover, we identify a certain degree of overshooting in inflation and tax rates following a positive productivity shock, and a certain degree of undershooting following a positive government spending shock as a consequence of the assumed commitment of policy maker.