Date of Award:
Doctor of Philosophy (PhD)
Economics and Finance
John E. Kieth
John E. Kieth
Don C. Reading
Jay C. Anderson
The imposition of water quality controls may affect the economy chiefly by altering aggregate production and changing the factor payments, These two effects could not only reallocate resources among production possibilities, but also could change the distribution of benefits of production among members of the society.
This study attempted to provide a workable theory to establish an empirical test of the impacts of water quality controls on family income distribution. It consists of two separate areas: first, to analyze methodologies of measuring income distribution changes, and , second, to develop a theoretical model that is useful for empirical tests of the impacts of different water quality controls.
A number of alternative probability density functions have been proposed as models of personal income distribution. The lognormal, displaced lognormal, gamma, and beta distribution functions were considered as appropriate methodologies, since each allows more productive power for income distribution as suggested in the past literature. Detailed information on income distribution can be extracted from the approximations of the distribution functions.
One of the objectives of the research was to evaluate the different methodologies for usefulness. The gastwirth bounds for Gini coefficient were used as the test of goodness to fit; the beta density was clearly superior to the other densities for the SMSA data.
Next, a theoretical model was constructed, emphasizing the production sector and the distribution sector. Water quality controls were introduced in the production process as a negative input. Water quality data were collected for all states, and indices of quality were estimated using analysis of variance techniques. The equilibrium conditions in commodity and factor markets generated the first impacts of water quality controls on total output and factor payments in the economy.
The specific assumption was made as a theoretical bridge connecting family income distribution and factor payments in the distribution sector. It was assumed that a family's income equals total payments received from owned labor and capital in the production process. Thus, changes in factor payments and total output were included in the distribution equations. Water quality controls would, therefore, effect family income distribution through changes in total output and changes in factor payment.
The simultaneous equation regression results for 72 SMSA's were not conclusive. It appeared that water quality parameter may effect the wage rate and total output, if the parameter was not, in fact, a surrogate for other excluded variables in the system. The effect of wage changes on income distribution was not significant, but changes in total output appeared to be the most significant variable in the distribution equations.
In an attempt to account for the many variables which might be expected to effect income distribution, factor analysis was performed on the SMSA's. Two groups of SMSA's were identified and regressions were performed for these groups. Results from these regressions were similar in sign to the results from the 172 observations regressions, although many of the coefficients were not significant.
Interpreting the results of the research was somewhat difficult, even though some results did appear consistent among all regressions. It does appear that there is some evidence to indicate that water quality controls lead to less equal family income distribution. Better data are required from more complete and accurate analysis.
The principle thrust of the study was to develop a model to organize the complexity of economic causality with respect to income distribution change and water quality policy. It appeared that this type of systematic econometric approach can be fruitful in analyzing income distribution change.
Chen, Ming Chien, "Income Distribution Effects of Water Quality Controls: An Econometric Approach" (1977). All Graduate Theses and Dissertations. 3280.
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