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Methods for Assessing the Likelihood of Country Grain Elevator Failure in the United States James C

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Methods for Assessing the Likelihood of Country Grain Elevator Failure in the United States James C Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 1989 Methods for assessing the likelihood of country grain elevator failure in the United States James C. McConnon Jr. Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Agricultural and Resource Economics Commons, and the Agricultural Economics Commons Recommended Citation McConnon, James C. Jr., "Methods for assessing the likelihood of country grain elevator failure in the United States " (1989). Retrospective Theses and Dissertations. 9219. https://lib.dr.iastate.edu/rtd/9219 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. INFORMATION TO USERS The most advanced technology has been used to photo­ graph and reproduce this manuscript from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. 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University Microfilms International A Bell & Howell Information Company 300 North Zeeb Road, Ann Arbor, fvll 48106-1346 USA 313/761-4700 800/521-0600 Order Number 8920164 Methods for assessing the likelihood of country grain elevator failure in the United States McGonnon, James C., Jr., Ph.D. Iowa State University, 1989 UMI 300N.ZeebRd. Ann Aibor, MI 48106 Methods for assessing the likelihood of country grain elevator failure in the United States by James C. McConnon, Jr. A Dissertation Submitted to the Graduate Faculty in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY Department : Economics Major: Agricultural Economics Approved Signature was redacted for privacy. Signature was redacted for privacy. Signature was redacted for privacy. For the Major Departmen, Signature was redacted for privacy. For the Graduate College Iowa State University Ames, Iowa 1989 Copyright 1989 James C. McConnon, Jr. All rights reserved. ii TABLE OF CONTENTS Page CHAPTER I. INTRODUCTION 1 Backround 1 Problem Statement 5 Review of the Literature 17 Research Objectives 40 Following Chapters 41 CHAPTER II. RESEARCH METHODS 43 Discriminant Analysis 43 Linear Discriminant Analysis (Fisher's Method) 44 Expected Cost of Misclassification Rule 49 Estimation of Misclassification Probabilities 57 Logistic Regression Analysis 59 The Logit Function 61 Parameter Estimation 65 CHAPTER III. EMPIRICAL PROCEDURES 67 Sample Data 67 Sample Selection 74 Insolvent Grain Elevator Sample 75 Solvent Grain Elevator Sample 80 Sample Characteristics 83 Characteristics of Insolvent Grain Elevator Sample 83 Characteristics of Solvent Grain Elevator Sample 95 ill Page Variable Selection 104 Empirical Models for Estimation 114 Discriminant Function Model 114 Logistic Regression Function Model 116 Empirical Procedure 118 CHAPTER IV. ANALYSIS 121 Variable Profile 121 Comparison of Variable Means 122 Variable Frequency Distributions 125 Change in Variable Means Prior to Failure 133 Hotelling Test Statistic 135 Discriminant Function Model 139 Tests of the Assumptions of the linear Model 140 Parameter Estimates 148 Estimation of Misclassification Probabilities 156 Resubstitution Method 160 Jackknife Method 167 Quadratic Discriminant Function 172 Estimation of Misclassification Probabilities 173 Logistic Regression Function Model 181 Parameter Estimates 183 Marginal Analysis 188 Estimation of Misclassification Probabilities 193 iv Page Comparison of Model Performance 208 CHAPTER V. SUMMARY AND CONCLUSIONS 214 Summary 214 Conclusions 219 Further Research 222 BIBLIOGRAPHY 224 ACKNOWLEDGEMENTS 235 APPENDIX 237 V LIST OF FIGURES Page Figure 2.1. Graphical illustration of Fisher's classification 48 rule for two distinct populations Figure 2.2. Graphical illustration of Fisher's discriminant 50 procedure Figure 2.3. Graphical illustration of the impacts of changes in 55 the ratio of expected costs of misclassification on the cutoff value and probabilities of misclassification Figure 2.4. Graphical illustration of the logistic cumulative 64 distribution function with q - 1 and > 0 Figure 3.1. Balance sheet for a hypothetical ASCS regulated 70 grain elevator Figure 3.2. Operating statement for a hypothetical ASCS 73 regulated grain elevator Figure 3.3. Number of ASCS regulated elevator failures, 77 January 1980 thru May 1986 Figure 4.1. Relative frequency of estimated linear 155 discriminant scores for the sample grain elevators Figure 4.2. Linear discriminant model resubstitution 164 classification results Figure 4.3. Linear discriminant model jackknife 170 classification results Figure 4.4. Resubstitution vs. jackknife method of 171 estimating classification results using the linear discriminant model Figure 4.5. Quadratic discriminant model resubstitution 177 classification results Figure 4.6. Quadratic vs. linear discriminant model 179 resubstitution classification results vi Page Figure 4.7. Comparison of quadratic and linear discriminant 180 model resubstitution classification performance Figure 4.8. Change in the likelihood of failure associated 191 with changes in the adjusted working capital to sales ratio holding the remaining Independent variables of the logistic regression model at their means Figure 4.9. Relative frequency of probabilities of failure 197 for the sample grain elevators estimated by the logistic regression model Figure 4.10. Logistic regression model resubstitution 202 classification results Figure 4.11. Comparison of early warning model resubstitution 211 classification performance vil LIST OF TABLES Page Table 1.1. General claims information for bankrupt grain 8 elevators in the United States, 1974 thru 1979 Table 1.2. General claims information for insolvent grain 8 elevators in the north central United States, 1974 thru May 1982 Table 3.1. Number of ASCS regulated elevators that failed 79 between January 1983 and May 1986 by type of participation in the study Table 3.2. Number of insolvent grain elevators in the sample 85 by year of insolvency Table 3.3. Number of Insolvent grain elevators in the sample 86 by type of failure Table 3.4. Number of Insolvent grain elevators in the sample 88 by type of organizational structure Table 3.5. Number of insolvent grain elevators in the sample 90 by state Table 3.6. Number of insolvent grain elevators in the sample 92 by region of the country Table 3.7. Number of Insolvent grain elevators in the sample 94 by most recent licensed capacity Table 3.8. Number of solvent grain elevators in the sample 96 by type of organizational structure Table 3.9. Number of solvent grain elevators in the sample 98 by state Table 3.10. Number of solvent grain elevators in the sample 100 by region of the country Table 3.11. Number of solvent grain elevators in the sample 102 by most recent licensed capacity Table 3.12. Selected characteristics of the variables chosen 108 for inclusion in the study viii Page Table 3.13. Code names and expected signs of the coefficients 109 for the variables Included In the study Table 4.1. Comparison of means and standard deviations of the 123 Independent variables between the insolvent and solvent grain elevator samples Table 4.2. Distribution of the adjusted working capital to 126 sales ratio for the insolvent and solvent grain elevator samples Table 4.3. Distribution of the debt to assets ratio for the 128 insolvent and solvent grain elevator samples Table 4.4. Distribution of the adjusted cash flow to debt 129 ratio for the insolvent and solvent grain elevator samples Table 4.5. Distribution of the asset turnover ratio for the 130 insolvent and solvent grain elevator samples Table 4.6. Distribution of the return on assets ratio for the 132 insolvent and solvent grain elevator samples Table 4.7. Comparison of means and standard deviations of the 134 independent variables for the insolvent grain elevator sample, one, two, and three years prior to failure Table 4.8. Shapiro-Wilk and Kolmogorov-Smirnov test statistics 142 for testing univariate
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