Lower Bounds of Concentration in a Small Open Economy

We examine how Sutton’s “bounds” approach works in a small country where industries have relatively high export and import intensities. The bounds are estimated as stochastic frontiers, where observable industry characteristics, entry barriers, and export intensity are allowed to affect the mean and variance of the deviations from the frontier. In accordance with the theory, high R&D intensity industries have a lower bound for concentration, which is higher than that for exogenous sunk cost industries. For high advertising industries the theory does not hold as well.      

Investment service providers gaining competitive advantage by focusing on consumers’ varying investment goals

Laddering data collected from 95 individuals and network analysis were used to reveal and identify 747 linkages among 33 content-analysed goals as reasons for investing in individual stocks, mutual funds and/or voluntary pension plans. The results suggest that consumers’ goals associated with investments are: (i) besides economic, also functional, emotional and symbolic; and (ii) influenced by the type of investment product under evaluation rather than being independent of the investment alternatives. The article presents guidelines for investment service providers on: (i) how to provide facilities that support consumers’ investment-related goals; and (ii) how to encourage consumers to take an active role in customising and personalising their investment practices when using these facilities. Thus, economic and functional but also – and especially – emotional and symbolic goals of investing give insight into these strategic decisions that enable investment service providers to deliver value to consumers. While economic, functional, emotional and symbolic goals are well established in consumer research literature, these elements contribute to a novel understanding of the drivers underlying investment in general and the differences in distinct product categories in particular.     

On the Interpretation of Value Efficiency

Halme et al., Management Science, 45, 103–115 (1999) have proposed Value Efficiency Analysis as an approach to incorporate preference information in Data Envelopment Analysis (DEA). Generally, a value function includes only ordinal information and thus a value efficiency score does not provide information on the value difference. The score only describes the improvements in the input/output values that are needed in order to make the Decision-Making Unit (DMU) as preferred as the Most Preferred Solution (MPS). This Paper discusses two sets of additional assumptions that enable us to give the efficiency score a value difference interpretation.     

Returns to workers and hours in finnish manufacturing

Production functions, where the number of workers, their average standard hours, and average overtime hours appear as separate inputs, are estimated using pooled data from Finnish industries. The results show that the returns to workers are higher than the returns to average hours and both returns are below one. This is in accordance with the assumption usually made in theoretical analyses of the demand for workers and hours. The productivity of overtime hours is slightly higher than that of standard hours. All the output elasticities are, however, fairly close to each other. Diagnostic tests show that there is collinearity between the explanatory variables, but application of several adaptive ridge estimators shows that this has not affected the results much.     

STRATEGIC R&D AND NETWORK COMPATIBILITY

We analyse the effects of network externalities in strategic R&D competition. We present a model of two firms competing with R&D investments and prices in a differentiated consumer market. Buyers form firm-specific networks which can be compatible. A high degree of compatibility and large spillovers moderate price competition due to weak strategic value of firm-specific networks and R&D investments, respectively. Asymmetry in product qualities brings out network effects that cancel out in conventional symmetric settings. The lower quality firm increases R&D and decreases its price as spillovers or network compatibility is increased. This happens when R&D and firm-specific network size have high strategic value.