On Public Inefficiencies in a Mixed Duopoly

The aim of this paper is to investigate the welfare effect of a change in the public firms objective function in oligopoly when the government takes into account the distortionary effect of rising funds by taxation (shadow cost of public funds). We analyze the impact of a shift from welfare- to profit-maximizing behaviour of the public firm on the timing of competition by endogenizing the determination of simultaneous (Nash-Cournot) versus sequential (Stackelberg) games using the game with observable delay proposed by Hamilton and Slutsky (1990). Differently from previous work that assumed the timing of competition, we show that, absent efficiency gains, instructing the public firm to play as a private one never increases welfare. Moreover, even when large efficiency gains result from the shift in public firm's objective, an inefficient public firm that maximizes welfare may be preferred.

A Producer Theory with Business Risks

In this paper, we consider a producer who faces uninsurable business risks due to incomplete spanning of asset markets over stochastic goods market outcomes, and examine how the presence of the uninsurable business risks affects the producer's optimal pricing and production behaviours. Three key (inter-related) results we find are: (1) optimal prices in goods markets comprise ‘markup’ to the extent of market power and ‘premium’ by shadow price of the risks; (2) price inertia as we observe in data can be explained by a joint work of risk neutralization motive and marginal cost equalization condition; (3) the relative responsiveness of risk neutralization motive and marginal cost equalization at optimum is central to the cyclical variation of markups, providing a consistent explanation for procyclical and countercyclical movements. By these results, the proposed theory of producer leaves important implications both micro and macro, and both empirical and theoretical.

Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.