Abstract
Adopting a general spatial framework, we analyse collusion concerning a price increase between two firms. We find that any variable affects the sustainability of collusion in the same way it affects the competitive profits.
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Notes
See the textbook by Motta (2004) for a very complete survey about old and new theories concerning collusion.
The relationship between product differentiation and the sustainability of collusion is exemplar of this problem. In fact, one may find a positive monotonic relationship (Chang 1991 and 1992; Hackner 1995; Miklòs-Thal 2008); a negative monotonic relationship (Friedman and Thisse 1993; Gupta and Venkatu 2002), and also a non-monotonic relationship (Deneckere 1983; Ross 1992).
However, Colombo (2011b) analyses collusion by using a spatial model which allows also for spatially asymmetric firms.
The term price schedule here refers to a positive valued function \( p(.) \) defined on S that specifies the price \( p(h) \) at which consumer h is served in equilibrium.
The case of non-optimal punishment is briefly discussed at the end of the article.
The case where the price increase is a percentage of the competitive price rather than a fixed amount yields the same results. We briefly discuss it in the Appendix.
We are restricting attention to prices such that the demand is inelastic. Clearly, whether or not demand is elastic at higher prices does not affect the results. I thank one referee for this point.
As the right-hand-side of (4) is lower than 1/2, if the market discount factor is higher than 1/2 any collusive price increase is sustainable in equilibrium. Therefore, the following Theorem 1 correctly applies only when \( \delta \leqslant {{1} \left/ {2} \right.} \).
Under the grim-trigger strategy (Friedman 1971), both firms start by charging the collusive price schedule. The firms continue to set the collusive price schedule until one firm has deviated from the collusive agreement. After a deviation has occurred, both firms play the equilibrium competitive price schedules forever.
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Acknowledgements
I gratefully acknowledge the helpful comments from two anonymous referees. All remaining errors are my own.
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Appendix
Appendix
In this appendix, we show that the result would be qualitatively the same if the price increase was a percentage of the competitive price rather than a fixed amount. Consider the collusive price schedule. Firms collude to increase the price of a percentage equal to w. It follows that the collusive price schedule is: \( p_h^C = p_h^N(1 + w) \) for all \( h \in S \). Hence, the collusive profits are: \( {\Pi^C} = \int_{{h \in {S^1}}} {[p_h^C - T(a,h)]f(h)dh} = {\Pi^N} + w\int_{{h \in {S^1}}} {p_h^Ndh} \). The deviation profits are: \( {\Pi^D} = \int_h {[p_h^C - T(a,h)]f(h)dh} = {\Pi^C} + w\int_{{h \in {S^2}}} {p_h^Nf(h)dh} \). Due to symmetry, we have: \( \int_{{h \in {S^2}}} {p_h^Nf(h)dh} = \int_{{h \in {S^1}}} {p_h^Nf(h)dh} \). Therefore, we can write: \( {\Pi^D} = {\Pi^N} + 2w\int_{{h \in {S^1}}} {p_h^Nf(h)dh} \). Using the deviation profits, the collusive profits and the punishment profits into (1), we can write the critical discount factor as follows: \( \delta * = \frac{{{\Pi^N} + 2w\int_{{h \in {S^1}}} {p_h^Nf(h)dh} - {\Pi^N} - w\int_{{h \in {S^1}}} {p_h^Ndh} }}{{{\Pi^N} + 2w\int_{{h \in {S^1}}} {p_h^Nf(h)dh} }} = \frac{w}{{1 + 2w - \Gamma }} \), where \( \Gamma = \frac{{\int_{{h \in {S^1}}} {T(a,h)f(h)dh} }}{{\int_{{h \in {S^1}}} {p_h^Nf(h)dh} }} \). However, note that the competitive profits are a decreasing function of \( \Gamma \), as the competitive profits must decrease with the transportation costs and must increase with the equilibrium competitive price. Therefore, we can conclude that the critical discount factor is inversely related to the competitive profits, as shown for a fixed amount increase of the price.
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Colombo, S. Colluding on a Price Increase. J Ind Compet Trade 12, 365–371 (2012). https://doi.org/10.1007/s10842-011-0110-9
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DOI: https://doi.org/10.1007/s10842-011-0110-9