Evaluating expectations of <Emphasis Type="Italic">L</Emphasis>-statistics by the Steffensen inequality

By combining the Moriguti and Steffensen inequalities, we obtain sharp upper bounds for the expectations of arbitrary linear combinations of order statistics from iid samples. The bounds are expressed in terms of expectations of the left truncated parent distribution and constants that depend only on the coefficients of the linear combination. We also present analogous results for dependent id samples. The bounds are especially useful for L-estimates of the scale parameter of the distribution.     

Economic performance and international trade engagement: the case of Portuguese manufacturing firms

By combining economic and financial data for Portuguese manufacturing firms with data on their exports and imports, we uncover some aspects of the relationship between international trade engagement and firms’ performances. In line with recent theoretical and empirical developments in the international trade literature: (i) we testify that Portuguese international trade is highly concentrated, especially on the import side, and both in inter- and intra-sector terms; (ii) we corroborate previous studies and theses according to which two-way traders outperform only importers, only exporters and above all domestic firms; (iii) we find that the greater the diversification of markets and goods (especially with regard to imports), the better the performance achieved by internationalised firms; (iv) we notice that the higher the intensity of firms’ international trade (especially imports), the better their performance; (v) we also present evidence that destination markets for exports and origin markets for imports are also important in explaining firm’s performance.     

Airline Code-share Alliances and Costs: Imposing Concavity on Translog Cost Function Estimation

This paper provides an assessment of how airline code-share alliances affect the costs of the airline industry. It makes two contributions to the literature. First, it measures the effects of airline alliances by estimating a translog cost function using a panel dataset of 10 major U.S.-based airlines over 29 quarters. Secondly, it ensures concavity of the estimated cost function by using the procedure suggested by Ryan and Wales (2000, Economics Letters 67, 253–260). A conventional translog cost function is first estimated and scale estimates are computed. Unfortunately, the estimated function fails the curvature requirement, which makes interpreting the estimated effects of alliances somewhat dubious. Hence, we re-estimate the cost function by imposing local concavity restrictions. We find that large alliance partners have a small negative effect on airlines costs, but small alliance partners effect on costs appear to be positive, although the magnitude is negligible. We also find material differences in the estimates of scale economies after imposing local concavity.JEL classification: L00, L12, L93     

Approximate maximum likelihood estimation for stochastic differential equations with random effects in the drift and the diffusion

Consider N independent stochastic processes \((X_i(t), t\in [0,T])\), \(i=1,\ldots , N\), defined by a stochastic differential equation with random effects where the drift term depends linearly on a random vector \(\Phi _i\) and the diffusion coefficient depends on another linear random effect \(\Psi _i\). For these effects, we consider a joint parametric distribution. We propose and study two approximate likelihoods for estimating the parameters of this joint distribution based on discrete observations of the processes on a fixed time interval. Consistent and \(\sqrt{N}\)-asymptotically Gaussian estimators are obtained when both the number of individuals and the number of observations per individual tend to infinity. The estimation methods are investigated on simulated data and show good performances.     

Mutual Fund Growth in Standard and Specialist Market Segments

This paper is concerned with differences in the performance-flow relationship (PFR) between standard and specialist market segments of the mutual fund industry. We expect differences in this relationship because investor characteristics might vary across different segments. Our results show that the PFR is more convex in standard segments than in specialist segments. Furthermore, investors in standard segments are less risk-averse and invest more in high-load funds than investors in specialist segments. Our findings are consistent with investors in standard segments being less sophisticated than investors in specialist segments and relying more heavily on the advice of financial brokers, which is compensated for by load fees.     

Efficient discriminating design for a class of nested polynomial regression models

This paper studies efficient designs for simultaneous model discrimination among polynomial regression models up to degree k. Based on the -optimality criterion proposed by Dette (Ann Stat 22:890–903, 1994), a maximin -optimal discriminating design is derived in terms of canonical moments for . Theoretical and numerical results show that the proposed design performs well for model discrimination in most of the considered models.     

Intolerable nuisances: some laboratory evidence on survivor curve shapes

The fraction of a user population willing to tolerate nuisances of size x is summarized in the survivor curve S(x); its shape is crucial in economic decisions such as pricing and advertising. We report a laboratory experiment that, for the first time, estimates the shape of survivor curves in several different settings. Laboratory subjects engage in a series of six desirable activities, e.g., playing a video game, viewing a chosen video clip, or earning money by answering questions. For each activity and each subject we introduce a chosen level \(x \in [x_{\min }, x_{\max }]\) of a particular nuisance, and the subject chooses whether to tolerate the nuisance or to switch to a bland activity for the remaining time. New non-parametric techniques provide bounds on the empirical survivor curves for each activity. Parametric fits of the classic Weibull distribution provide estimates of the survivor curves’ shapes. The fitted shape parameter depends on the activity and nuisance, but overall the estimated survivor curves tend to be log-convex. An implication, given the model of Aperjis and Huberman (SSRN, doi:  10.2139/ssrn.1672820, 2011), is that introducing nuisances all at once will generally be more profitable than introducing them gradually.     

Price control and privatization in a mixed duopoly with a public social enterprise

We explore the issue of the optimal degree of privatization for a public firm that does not need to care about its rival’s profit completely. We find that the optimal privatization of a public social enterprise under exogenous price control depends on the level of the regulated price. Namely, when the regulated price is low (medium, high), the optimal privatization is partial privatization (complete privatization, completely public owned). If the price control is optimized by maximizing social welfare, then the optimal privatization is complete privatization. For the case of the traditionally defined public firm, its optimal privatization is completely public owned when the price control is exogenously given. If the price control is endogenously determined, then privatization policy is redundant.     

A baseline model of industry evolution

The paper analyses some general dynamic properties of industries characterized by heterogeneous firms and continuing stochastic entry.After a brief critical assessment of some significant drawbacks of recent contributions to modeling of stochastic industrial dynamics, we propose a novel analytical apparatus able to derive some generic properties of the underlying competition process combining persistent technological heterogeneity, differential growth of individual firms and turnover. The basic model, we suggest, is indeed applicable with proper modifications to a large class of evolutionary processes, well beyond industrial dynamics.JEL Classification: L11, O30, C60Support to this research by the International Institute for Applied Systems Analysis (IIASA), Austria; the Fujitsu Research Institute for Advanced Information (FRI), Japan; the Italian National Research Council (CNR), the Italian Ministry of Education, University and Research (MIUR, prot. 2002132413 003) and the Free University of Bozen Bolzano, Italy, is gratefully acknowledged. Comments by Andrea Bassanini, Francesca Chiaromonte, Steven Klepper, Uwe Cantner, Drew Fudenberg and the anonymous referees helped in shaping the paper to its present form. Mariele Berté provided the computer simulations of the model. The usual caveats apply.Correspondence to: G. Dosi