The Measurement of Economic Relationships presents a critical review of the established approach to measuring relationships in business and economics and of the one that preceded it. The first approach is based on the notion of a process "generating" the observations in a certain "random" manner, the second on the concept of approximating the observations of the variable of interest as closely as possible. It is shown that both approaches offer measures of the contribution of the determining variables, interval estimates and tests concerning the effects of the variables, and interval forecasts; in general, however, their solutions are different. In reviewing the two approaches since their first appearance at the end of the 18th century, little justification is found for the manner in which the established approach perceives the economic world. Doubts are raised that substantial real progress has been made since the advent of the so-called "probabilistic revolution." It is suggested that the simplicity and transparency of the approximating approach should be preferred.
1 Introduction.- 1.1 The Status Quo.- 1.2 The CLM in Academic Studies.- 1.3 The CLM in Practice.- 1.4 Extensions of the CLM.- 1.5 The Road Ahead.- 2 The Fitting Method: An Introduction.- 2.1 Introduction.- 2.2 The Problem.- 2.3 The Available Information.- 2.4 One Solution.- 2.5 Least Squares and Spreadsheets.- 2.6 Constrained Least Squares.- 2.7 Tolerance Intervals.- 2.8 Joint Tests and Tolerance Regions.- 2.9 Interval Forecasts.- 2.10 Computer Output.- 2.11 In Summary.- 3 The Fitting Method: A Formal Treatment.- 3.1 Introduction.- 3.2 Relationships.- 3.3 Unrestricted Least Squares.- 3.4 Restricted Least Squares.- 3.5 Ordinary Tolerance Intervals and Regions.- 3.6 A Tolerance Region for All Parameters.- 3.7 Tolerance Interval Forecasts.- 3.8 Possible Extensions.- 4 The Clasical Linear Model.- 4.1 Introduction.- 4.2 The Assumptions of the CLM.- 4.3 Estimates and Their Properties.- 4.4 Statistical Inference.- 4.5 Specification Error.- 4.6 On Confidence Interval Estimates.- 4.7 The Many Problems of Significance.- 4.8 On Confidence Interval Forecasts.- 4.9 The Art and Practice of Statistical Inference.- 4.10 Bad Practice or Bad Theory?.- 5 The Central Assumptions.- 5.1 Introduction.- 5.2 True Parameters?.- 5.3 The Randomness of Error.- 5.4 Probability.- 5.5 The Central Limit Theorem and Normality.- 5.6 Are the Unknown Factors Random Variables?.- 5.7 Serial Correlation.- 5.8 The “As If” Argument.- 5.9 A Probable Deviation.- 5.10 On the Distribution of Residuals.- 5.11 In Summary.- 6 Random Processes.- 6.1 Introduction.- 6.2 The Coin Toss.- 6.3 Of Births and Deaths.- 6.4 Stock Market Prices.- 6.5 Some Perils of Time Series Analysis.- 6.6 In Conclusion.- 7 The “Probabilistic Revolution”.- 7.1 Introduction.- 7.2 Before Haavelmo.- 7.3 Haavelmo on Relationships.- 7.4Haavelmo in Contemporary Reviews.- 7.5 The Probability Approach Reconsidered.- 7.6 Random Sampling.- 7.7 The Assumptions Reconsidered, Continuation.- 7.8 In Summary.- 8 Assessment.- 8.1 The Fitting Method in Perspective.- 8.2 The Tolerance Level.- 8.3 The Technical Pursuit of Fit.- 8.4 The Success Rate of Tolerance Interval Forecasts.- 8.5 The Poverty of Properties.- 8.6 Does It Matter?.- 8.7 Subjective Probability.- 8.8 Determinism and Probabilism.- 8.9 The “As If” Assumption Revisited.- 8.10 Why the Status Quo?.- 8.11 A Pragmatic Approach.- References.
