Clute Institute: Journals
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Government Deficits And The Public Debt: The Endless Controversy
No full textNo economic topic has attracted more attention during the 1980s than the size of Federal government budget deficits and the corresponding rapid rise in the public debt. Crowding out news regarding Third World debt problems, U.S. foreign trade deficits, and the break up of American Telephone and Telegraph, Federal government budget deficits have been blamed for everything from high interest rates to the deterioration in the moral fiber of the American people. Deficits and debt have also caused political reversal: historically free spending Democrats blaming Reagan deficits for a variety of economic ills while the conservative Republican president treats the deficit with benign neglect. The purpose of this paper is not to answer all of the questions that have been raised regarding the causes and consequences of government deficits and debt. The initial concern is instead with the facts and figures on the absolute and relative size of the Federal government’s recent deficits and debt. Next certain measurement issues are addressed for there is a continuing debate regarding appropriate procedures for expressing the government’s budgetary outcomes. The third and final section of the paper reviews some of the arguments, theoretical and empirical, on the relation between deficits and debt on the one hand and interest rates on the other. In each section the intent is to survey rather than to present new theoretical arguments or new empirical evidence.
Managing The Older Employee
No full textEmployers need to follow certain guidelines to effectively manage the older employee
Comparison Of The Performance Of Several Data Mining Methods For Bad Debt Recovery In The Healthcare Industry
Full text linkThe healthcare industry, specifically hospitals and clinical organizations, are often plagued by unpaid bills and collection agency fees. These unpaid bills contribute significantly to the rising cost of healthcare. Unlike financial institutions, health care providers typically do not collect financial information about their patients. This lack of information makes it difficult to evaluate whether a particular patient-debtor is likely to pay his/her bill. In recent years, the industry has started to apply data mining tools to reduce bad-debt balance. This paper compares the effectiveness of five such tools - neural networks, decision trees, logistic regression, memory-based reasoning, and the ensemble model in evaluating whether a debt is likely to be repaid. The data analysis and evaluation of the performance of the models are based on a fairly large unbalanced data sample provided by a healthcare company, in which cases with recovered bad debts are underrepresented. Computer simulation shows that the neural network, logistic regression, and the combined model produced the best classification accuracy. More thorough interpretation of the results is obtained by analyzing the lift and receiver operating characteristic charts. We used the models to score all “unknown” cases, which were not pursued by a company. The best model classified about 34.8% of these cases into “good” cases. To collect bad debts more effectively, we recommend that a company first deploy and use the models, before it refers unrecovered cases to a collection agency.  
Teaching Characteristics Of Successful College Professors
No full textDuring the past several years, the authors have devoted a great deal of time and energy in the pursuit of becoming effective college professors. After observing a number of excellent professors (and a number of less-than-excellent ones), the authors would like to share some of their observations and ideas.Although this article focuses specifically on effective classroom performance in a traditional lecture-based setting, many of the principles discussed can be applied to alternative styles of teaching such as seminar settings, individualized instruction, etc.