What Is It About Organic Milk? An Experimental Analysis

Auction experiments were used to examine demand relationships and willingness to pay (WTP) for organic, rBST-free, no antibiotics used, and conventional milk. Elasticities showed strong substitute and complement relationships between organic, rBST-free, and no antibiotics varieties. The sum of the latter two's premiums were not significantly different than the organic premium, suggesting diminishing marginal utility for added attributes. Results from a two-stage heteroskedastic tobit model demonstrated that WTP premiums for the varieties differ significantly by demographics and beliefs regarding the conventional version. These suggest market segments for rBST-free and no antibiotics versions could succeed alongside organic, benefiting consumers and producers.     

Financial Openness,Aggregate Consumption and Threshold Effects

We analyse the influence of financial openness on the level of aggregate consumption, a research question that has been left surprisingly unexplored by the previous literature. We construct a complete and balanced panel data set of 88 countries for the period 1980–2010, and then differentiate between four groups of countries. Models for non‐stationary heterogeneous panels, as well as panel threshold regression models, are used to estimate the determinants of aggregate consumption. The core finding of the paper is that the financial openness effect on consumption changes in the course of economic development, with the level or per capita income acting as a threshold which is consistently estimated within the model. The openness effect is non‐homogeneous across groups, stronger for low levels of per capita income and diminishes as income rises. These findings provide new insights into the welfare effect of financial liberalization.     

Firms and the global crisis: French exports in the turmoil

Global trade contracted quickly and severely during the global crisis. This paper uses a unique dataset of French firms to match export data to firm-level credit constraints and shows that most of the 2008–2009 trade collapse was due to the unprecedented demand shock and to product characteristics. While all firms have been affected by the crisis, the effect on large firms has been mainly at the intensive margin and has resulted in a smaller portfolio of products being offered to export destinations. The effect on smaller exporters has been to reduce the range of destinations served or to stop exporting altogether. Credit constraints have been an added aggravation for firms active in high financial dependence sectors. However, the share of credit constrained firms is small and their number has not increased hugely during the crisis, with the result that the overall impact of credit constraints on trade has been limited.     

Firm heterogeneity,sunk costs,spatial characteristics and export market participation: Evidence from China

This paper develops a dynamic discrete-choice model to analyze the exporting decisions of Chinese firms in Zhejiang province. The results show that sunk costs are found to be significant and prior export experience, productivity, scale, FDI, export spillovers, coastal area and economic zones are all positively related with the propensity of exporting while state ownership concentration has a negative impact. The export behavior of firms varies with country-specific characteristics.     

International Exploitation of Domestic R&D Exploration: New Insights from Russian Manufacturing Firms

In this paper, we approach R&D cooperation and international market expansion from an exploration-exploitation perspective and look how various domestic R&D partners affect international market expansion activities in Russian firms. Our findings, based on a data survey of 206 manufacturing companies, show that different partners affect differently when it comes to market expansion and that their effect depends on a number of things such as the proximity of the international market. Using the exploration-exploitation approach, we are able to explain the phenomenon in more detail and so contribute to the existing international business and innovation management literature.     

Welfare,competition, specialization and growth

In this paper we consider a model of horizontal differentiation with a quite general production function and derive the closed form solutions for the level of the variables in the decentralized economy and in the social planner case. This enables us to analyze how consumers’ welfare varies in terms of the degree of competition and the degree of returns to specialization. We find that welfare is increasing in the degree of returns to specialization both in the market economy and in the centralized economy and the decentralized economy's welfare is a bell-shaped function of the degree of competition.     

Inattention, wealth inequality and equilibrium asset prices

Heterogeneity in planning propensity affects wealth inequality and asset prices. This paper presents an economy where attentive agents plan their consumption period by period, while inattentive agents plan every other period. Inattentive consumers face more uncertainty and trade at unfavorable prices. If the only source of uncertainty is future income, inattentive consumers accumulate more wealth. In contrast, with uncertain asset returns inattentive investors accumulate less wealth. Asset prices must induce attentive consumers to voluntarily bear the burden of adjusting to aggregate shocks and, as a result, are much more volatile than in a representative agent model with full attention.     

Wolves' contribution to structural change in grazing systems among swiss alpine summer farms: The evidence from causal random forest

The return of wolves to Swiss mountains and the damage they cause to sheep and goat herds in the region have raised concerns about a consequent wave of farm closures. In this paper, we examine the relationship between wolf attacks and the decline of Alpine summer farms, a specific high-altitude farm type. We collected farm structure data and monitoring data on wolf attacks between 2004 and 2021 and analysed them using a causal random forest method, enabling a detailed analysis of the relation between wolf attacks and the number of different types of Alpine summer farms at a regional level. The results show that the farming systems are unaffected by incidental and infrequent wolf attacks, but that a high number of wolf attacks in a region is related to faster decrease in number of grazing systems where sheep are most vulnerable to such attacks. In contrast, systems that allow for better herd protection tend to show an increase in areas with frequent wolf attacks.     

Exploring the Role of a Country's Institutional Environment in Internationalization: Strategic Responses of SMEs in Russia

Based on the suggested five-pillar institutional framework, the study empirically investigates the impact of the institutional environment on internationalization aspirations of small and medium enterprises (SMEs) in emerging economies and maps their strategic responses against imposed institutional pressures. The data collected across five forest cluster SMEs in Saint Petersburg and Moscow are analyzed. Political instability, corruption, bounded cognition, over-patriotism, and high power distance act as the main constraints, while demands for new knowledge and funding are identified as the main drivers for internationalization. The classified institutional challenges are mapped against the possible strategic responses of the SMEs, such as acquiescence, compromise, avoidance, defiance, and manipulation.     

GenD An Evolutionary System for Resampling in Survey Research

The paper is a preliminary research report and presents a method for generating new records using an evolutionary algorithm (close to but different from a genetic algorithm). This method, called Pseudo-Inverse Function (in short P-I Function), was designed and implemented at Semeion Research Centre (Rome). P-I Function is a method to generate new (virtual) data from a small set of observed data. P-I Function can be of aid when budget constraints limit the number of interviewees, or in case of a population that shows some sociologically interesting trait, but whose small size can seriously affect the reliability of estimates, or in case of secondary analysis on small samples. The applicative ground is given by research design with one or more dependent and a set of independent variables. The estimation of new cases takes place according to the maximization of a fitness function and outcomes a number as large as needed of ‘virtual’ cases, which reproduce the statistical traits of the original population. The algorithm used by P-I Function is known as Genetic Doping Algorithm (GenD), designed and implemented by Semeion Research Centre; among its features there is an innovative crossover procedure, which tends to select individuals with average fitness values, rather than those who show best values at each ‘generation’. A particularly thorough research design has been put on: (1) the observed sample is half-split to obtain a training and a testing set, which are analysed by means of a back propagation neural network; (2) testing is performed to find out how good the parameter estimates are; (3) a 10% sample is randomly extracted from the training set and used as a reduced training set; (4) on this narrow basis, GenD calculates the pseudo-inverse of the estimated parameter matrix; (5) ‘virtual’ data are tested against the testing data set (which has never been used for training). The algorithm has been proved on a particularly difficult ground, since the data set used as a basis for generating ‘virtual’ cases counts only 44 respondents, randomly sampled from a broader data set taken from the General Social Survey 2002. The major result is that networks trained on the ‘virtual’ resample show a model fit as good as the one of the observed data, though ‘virtual’ and observed data differ on some features. It can be seen that GenD ‘refills’ the joint distribution of the independent variables, conditioned by the dependent one. This paper is the result of deep collaboration among all authors. Cinzia Meraviglia wrote § 1, 3, 4, 6, 7 and 8; Giulia Massini wrote §5; Daria Croce performed some elaborations with neural networks and linear regression; Massimo Buscema wrote §2.