The first attempt at measuring a demand function was probably by Charles Davenant in 1699 (but generally attributed as Gregory King's Law) and consisted of a simple schedule of prices and quantities of wheat. By the late nineteenth century, simple comparisons had given way to mathematical formulations of such demand laws. For example, Aldrich (1987) discusses how Jevons (1871) fitted ‘by inspection’ an inverse quadratic function to the six data points of Gregory King's Law. Wicksteed (1889) disagreed with Jevons' function and found that a cubic equation fitted the data exactly. Although this sort of function fitting was possible with six data points, it was obviously inappropriate for large data sets, and by the beginning of the twentieth century investigators had turned to the field of statistics for help in measuring demand relationships.

It quickly became clear that simply applying statistical methods to the price and quantity data did not necessarily lead to sensible results and the work of econometricians in the first two decades of the twentieth century reveals both insight and confusion about why this should be so, as we shall see in the first section of the chapter. The ways in which econometricians formulated the difficulties they faced and then tried to solve them first by adjusting their data and then by developing more complex econometric models of demand are discussed in the following two sections. Other aspects of the difficulties raised in this early work are held over for discussion until Chapter 6.