Monopoly with local knowledge of demand function

In this note, we propose a model where a quantity setting monopolist has incomplete knowledge of the demand function. In each period, the firm sets the quantity produced observing only the selling price and the slope of the demand curve at that quantity. Given this information and through a learning process the firm estimates a linear subjective demand curve. We show that the steady states of the dynamic equation are critical points of the objective profit function. Moreover, results depend on convexity/concavity of the demand. When the demand function is convex and the objective profit function has a unique critical point: the steady state is a globally stable maximum; conversely when then steady state is not unique, local maximums are locally stable, while local minimums are locally unstable. On the other hand when the demand function is concave, the unique critical point is a maximum: there can be stability or instability of the critical point and period two cycles around it via a flip bifurcation. Moreover, through simulations we can observe that, with a mixed inverse demand function, there are different dynamic behaviors, from stability to chaos and that we have transition to complex dynamics via a sequence of period-doubling bifurcations. Finally, we show that the same results can be obtained if the monopolist is a price setter.     

The economic returns to schooling for Italian men. An evaluation based on instrumental variables

We study the relationship between (log) hourly earnings and schooling for male household heads in Italy, using cross-sectional data from the 1993 and 1995 waves of the Bank of Italy (BI) survey on the income and wealth of Italian households. In line with international evidence, we find that OLS under-estimate the return to schooling. When the endogeneity of schooling is taken into account, the return to an additional year in school increases from 4.8% to 5.6%. This estimate is lower than the estimates tabulated by Card [Card, D., 1994. Earnings, Schooling and Ability Revisited. NBER Working Paper no. 4832.] for the United States. We also find evidence that this return increases with higher levels of educational attainment.     

Structure and Location of Innovative Activity in the Italian Economy, 1981–85

An ‘innovative activity matrix’ is established from a recent ISTAT/CNR survey of innovation. After specifying the particularities of an innovative activity matrix in comparison with other flow matrices, we show that it is asymmetrical and clustered in parts of economic space. The structure of the innovative activity matrix is similar to that of the domestic and import requirement but not the capital flow matrix. Strong correlations indicate the following: that input–output analysis is useful for identifying the location of innovative activities in economic space; that it can be analyzed in an economically meaningful way; that its location is structured; and that, furthermore, it is structured in ways which are statistically related to economic activity. The paper ends with suggestions for the examination of possible causal relationships.     

On the relation between ownership dispersion and the firm's market value

Firms with widely-held ownership are relatively few. Shareholders controlling a firm are willing to forego the benefit of portfolio diversification because they can obtain a ‘rent from control’ at the expense of minority shareholders. This entails relevant conclusions for financial theory: (1) the total market value of a closely-held firm is lower, and its cost of capital higher than that of an identical widely-held firm is lower and its cost of capital higher than that of (3) different prices of control and minority shares and disconuities may impede evolution from closely to widely-held ownership.     

Autocorrelation and masked heterogeneity in panel data models estimated by maximum likelihood

In a panel data model with random effects, when autocorrelation in the error is considered, (Gaussian) maximum likelihood estimation produces a dramatically large number of corner solutions: the variance of the random effect appears (incorrectly) to be zero, and a larger autocorrelation is (incorrectly) assigned to the idiosyncratic component. Thus heterogeneity could (incorrectly) be lost in applications to panel data with customarily available time dimension, even in a correctly specified model. The problem occurs in linear as well as nonlinear models. This article aims at pointing out how serious this problem can be (largely neglected by the panel data literature). A set of Monte Carlo experiments is conducted to highlight its relevance, and we explain this unpleasant effect showing that, along a direction, the expected log-likelihood is nearly flat.