Multivariate L1 mean

The center of a univariate data set {x ₁,…,x _n} can be defined as the point μ that minimizes the norm of the vector of distances y′=(|x ₁−μ|,…,|x _n−μ|). As the median and the mean are the minimizers of respectively the L ₁- and the L ₂-norm of y, they are two alternatives to describe the center of a univariate data set. The center μ of a multivariate data set {x ₁,…,x _n} can also be defined as minimizer of the norm of a vector of distances. In multivariate situations however, there are several kinds of distances. In this note, we consider the vector of L ₁-distances y′₁=(∥x ₁- μ∥₁,…,∥x _n- μ∥₁) and the vector of L ₂-distances y′₂=(∥x ₁- μ∥₂,…,∥x _n-μ∥₂). We define the L ₁-median and the L ₁-mean as the minimizers of respectively the L ₁- and the L ₂-norm of y ₁; and then the L ₂-median and the L ₂-mean as the minimizers of respectively the L ₁- and the L ₂-norm of y ₂. In doing so, we obtain four alternatives to describe the center of a multivariate data set. While three of them have been already investigated in the statistical literature, the L ₁-mean appears to be a new concept. Received January 1999     

Der österreichische Merkantilismus und die Wurzeln seiner Zunftpolitik

Ohne Zusammenfassung     

Stochastic FDH/DEA estimators for frontier analysis

In this paper we extend the work of Simar (J Product Ananl 28:183–201, 2007) introducing noise in nonparametric frontier models. We develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specifically, our approach first allows for statistical noise, similar to Stochastic frontier analysis (even in a more flexible way), and second, it allows modelling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to what is done in non-parametric methods, like Data Envelopment Analysis (DEA), Free Disposal Hull (FDH), etc.... The methodology is based on the theory of local maximum likelihood estimation and extends recent works of Kumbhakar et al. (J Econom 137(1):1–27, 2007) and Park et al. (J Econom 146:185–198, 2008). Our method is suitable for modelling and estimation of the marginal effects onto inefficiency level jointly with estimation of marginal effects of input. The approach is robust to heteroskedastic cases and to various (unknown) distributions of statistical noise and inefficiency, despite assuming simple anchorage models. The method also improves DEA/FDH estimators, by allowing them to be quite robust to statistical noise and especially to outliers, which were the main problems of the original DEA/FDH estimators. The procedure shows great performance for various simulated cases and is also illustrated for some real data sets. Even in the single-output case, our simulated examples show that our stochastic DEA/FDH improves the Kumbhakar et al. (J Econom 137(1):1–27, 2007) method, by making the resulting frontier smoother, monotonic and, if we wish, concave.     

What Drives Household Choice of Organic Products in Grocery Stores?

This paper studies how households choose organic products on a given store visit. We develop a three-stage purchase incidence/brand choice/purchase quantity model for organic products. Shared random effects parameters link the three stages of the model. We empirically quantify the effects of category variables, marketing mix, and demographic variables on the purchase of organic products using a unique household panel dataset that includes actual organic purchase data from two markets, by over 4,500 households in 25 stores for the period between January 2004 and June 2009. First, we find that the purchase of organic products is greater among the high income, college educated, and older families as well as among consumers holding high-level occupations. Second, households tend not to purchase organic products when buying in concentrated categories. Third, on average, households tend to buy organic store brands more than the organic national brands. Promotions of organic brands (feature ad and display) are less likely to drive households to buy organic brands and so does the organic brand's distribution breadth. Finally, price has an inverted U-shaped effect. We discuss the implications of these results for retailers, manufacturers and researchers.     

Scale efficiency and homotheticity: equivalence of primal and dual measures

We address the issue of equivalence of primal and dual measures of scale efficiency in general production theory framework. We find that particular types of homotheticity of technologies, which we refer to here as scale homotheticity, provide necessary and sufficient condition for such equivalence. We also identify the case when the scale homotheticity is equivalent to the homothetic structures from Shephard (Theory of cost and production functions, Princeton studies in mathematical economics. Princeton University Press, Princeton, 1970).     

Is foreign-bank efficiency in financial centers driven by home or host country characteristics?

This paper investigates whether home or host country factors can explain differences in technical efficiency among foreign banks operating in the Luxembourg financial center. We first address heterogeneity across banks by using the group-wise bootstrap to compare DEA measures of bank efficiency between branches and subsidiaries, focused and diversified banks, and euro area and non-euro area banks. We then control for these factors in a second-stage regression indentifying the impact of country-specific regulatory and macroeconomic variables on individual bank efficiency scores. Our regulatory indicators capture the strictness of capital requirements, private monitoring, official disciplinary power and restrictions on bank activities. Our macroeconomic indicators capture GDP per capita in the home country and its position in the business cycle. Our results carry policy implications for bank regulators in both home and host countries and provide insight into banks’ choice between establishing a branch or a subsidiary to develop cross-border activities through international financial centers.     

Testing differences in efficiency of regions within a country: the case of Ukraine

In this paper we synthesize and adopt the recently developed methods in efficiency analysis to the case of comparison of regions within a country. We take Ukrainian regions as a subject of investigation, yet the same toolkit can be applied to test disputable differences in productivity for many other countries where such questions can be of national concern (e.g., Belgium, Great Britain, Spain, etc.). Contrary to common perception of economists focusing on Ukraine, we find no significant differences in distributions and aggregate efficiencies between the agricultural and industrial regions, neither between western (mostly Ukrainian speaking) and eastern (mostly Russian speaking) regions of Ukraine. However, we find strong support for a rapidly increasing gap between the capital (Kyiv) and all the regions since 2001. Using truncated regression analysis with bootstrap we also find robust evidence that the inefficiency of regions is positively related to alcohol and tobacco consumption, the amount of foreign direct investment and inversely related to criminality in the region. On the other hand, we also find strong evidence that amount of capital in the region and its wealth is positively associated with efficiency level of this region.     

Reaping the Fruits of Science: Comparing Exploitations of a Scientific Breakthrough in European Innovation Systems

This paper is an attempt to unpack the emergence and dynamics of science-based technologies in conceptual forms that allow us to understand better when and how the social and economic organization of search and problem-solving matters. The evolution over two decades of a specific science-based technology is mapped with data from its 192 patents. For the five European countries generating the majority of patents, we identify the host organizations of all 275 inventors involved in the R&D behind the patents. Using network analysis we then map the evolution of separate innovation systems and their structural and evolutionary characteristics. The best performing system combines a cumulative pattern with frequent and shifting connections to non-system R&D partners while maintaining a small core of almost omnipresent inventor-organizations. The role of multinational corporations in orchestrating innovation systems is apparent.