16 Suppose that perfectly competitive firms and a monopsonistic firm had different linear<sup>18</sup> demand (D1 for the less efficient firm and D2 for the more efficient firm) and supply curves positioned such that the same set of price and quantity (E1) could be a result of monopsony or perfect competition. If supply were to shift outward (S1 to S2), and the equilibrium were to move from E1 to E2, the two structures would still be observationally equivalent. Figure 2 illustrates the central difficulty in all empirical attempts to measure market power when marginal cost is not directly observable. The NEIO literature therefore measures market power through the econometric identification of the λ parameter.<sup>19</sup> NIEO models have been applied to both monopoly and monopsony (Azzam and Pagoulatos 1990; Azzam and Schroeter 1991a; Durham _, et al._ 1992; Just _, et al._ 1980). They have been extensively refined to include dynamic theories of noncooperative behavior (Green and Porter 1984; Rotemberg and Saloner 1986); to test for both input and output market power simultaneously (Atkinson and Kerkvliet 1989; Azzam _, et al._ 1990; Schroeter 1988); and at estimating market power in multiple markets (Hyde and Perloff 1998; Raper, Love, and Shumway 2000), thereby permitting the detection of market structures like cooperative bilateral monopoly (Raper _, et al._ 2000). Finally, structural models have also been developed for industries that deviate from the perfectly competitive framework by permitting differentiated products (Allen 1998) and output price uncertainty (Azzam and Schroeter 1991b). In contrast to the extensive refinement of NEIO market power measurement, empirical work on the _determinants_ of market power has received less attention in the NEIO literature. This was identified early on as an important field of further research: “...although the NEIO has had a great deal to say about measuring market power, it has had very little, as yet, to say about the causes of market power” (Bresnahan 1989, pp.1053-1054).

NEIO studies that do examine the determinants of market power typically estimate values for the market power parameter and then use their estimates as the dependent variable in a regression model. In much of this work the ‘causes’ of market power are often linked back to market structure, either explicitly through the inclusion of market structure variables as independent variables (Gallet 1996; Luo 2002) or implicitly by examining market power in input and output markets simultaneously. A few studies, however, do conduct a wider investigation (Buschena and Perloff 1991; Lopez _, et al._ 1993). In a study of monopsony market power for Haiti, for example, Lopez and You specify the growers’ supply curve and the demand curves for domestic and export markets and estimate a single term, λ , for each year. This parameter serves as a dependent variable that is then regressed on exogenous variables that include institutional policy factors, coffee ICAs, the number and size of exporters and general state-of-the–nation variables. Interestingly, they found that concentration ratios and association formation did not effect the NEIO market power measures, whereas effective periods of ICA quota (that is, those periods where the quota was binding)

> 18 The exposition holds even if demand/supply curves are not linear; Lau derives the extensive demand and cost conditions under which λ is identified (Lau 1981).

> 19 For monopoly, the use of a supply side exogenous variable that interacts with price (the slope of the supply curve) as well as entering into the estimated equation on its own (as a shifter) makes the λ parameter identifiable and estimable (Bresnahan 1982).