To make high-quality research more accessible and easier to explore.

Fields:
25 results

A Note of Identification and Information Loss through Aggregation

Econometrica 1976 44(4), 815
DISCUSSIONS OF IDENTIFICATION of parameters in simultaneous equation econometric models almost invariably assume that data are in the form of aggregative time series, i.e., only one measurement of each variable is available in each time period. This note shows that parameters in a model which is underidentified by the usual rank and order criteria at the aggregative level may be identified when disaggregated data aie available. The argument is presented in terms of a traditional textbook example of an underidentified model which consists of a demand and a supply function for a single commodity that are linear in price, and a market clearing equilibrium equation.

Keynes and the Quantity Theory: A Comment on The Friedman-Meiselman CMC Paper

The Review of Economics and Statistics 1964 46(4), 364
PROFESSORS Friedman and Meiselman' recently have reported that a simple theory model describes aggregate consumption more accurately than a simple autonomous expenditure model. They believe this result is evidence that the quantity theory is a better description of the American economy than the autonomous expenditure or Keynesian theory.2 If their interpretation were correct, the Friedman-Meiselman paper would be one of the most significant economic studies in many years. But it is not correct. Friedman and Meiselman have represented the autonomous expenditure theory in a very unorthodox form. Their statistical comparisons are extremely sensitive to how the autonomous expenditure theory is represented. Below, I employ a more conventional representation of the autonomous expenditure theory and demonstrate why Friedman and Meiselman's tests are misleading. Further, using this conventional model and some of their data, little empirical evidence is found which favors the theory. Finally some other conceptual weaknesses of the Friedman-Meiselman tests are illustrated. Briefly, Friedman and Meiselman compare simple, partial, and multiple correlation coefficients obtained from the following equations, estimated from annual (1897-1958) and quarterly (1945-1958) data for the United States: C=al+8(A (1) C=a2 +82M (2) C = a3+/33A +13P (3) C = a4 +84M+y4P (4) C = a5 + 35A + 85M (5) C = a6 + 86A + 86M + Y6P (6)