Bayesian estimation of inefficiency heterogeneity in stochastic frontier models

Estimation of the one sided error component in stochastic frontier models may erroneously attribute firm characteristics to inefficiency if heterogeneity is unaccounted for. However, unobserved inefficiency heterogeneity has been little explored. In this work, we propose to capture it through a random parameter which may affect the location, scale, or both parameters of a truncated normal inefficiency distribution using a Bayesian approach. Our findings using two real data sets, suggest that the inclusion of a random parameter in the inefficiency distribution is able to capture latent heterogeneity and can be used to validate the suitability of observed covariates to distinguish heterogeneity from inefficiency. Relevant effects are also found on separating and shrinking individual posterior efficiency distributions when heterogeneity affects the location and scale parameters of the one-sided error distribution, and consequently affecting the estimated mean efficiency scores and rankings. In particular, including heterogeneity simultaneously in both parameters of the inefficiency distribution in models that satisfy the scaling property leads to a decrease in the uncertainty around the mean scores and less overlapping of the posterior efficiency distributions, which provides both more reliable efficiency scores and rankings.     

PLAYING THE FERTILITY GAME AT WORK: AN EQUILIBRIUM MODEL OF PEER EFFECTS

We study workplace peer effects in fertility decisions using a game theory model of strategic interactions among coworkers that allows for multiple equilibria. Using register‐based data on fertile‐aged women working in medium‐sized establishments in Denmark, we uncover negative average peer effects. Allowing for heterogeneous effects by worker type, we find that positive effects dominate across worker types defined by age or education. Negative effects dominate within age groups and among low‐education types. Policy simulations show that these estimated effects make the distribution of where women work an important consideration, beyond simply if they work, in predicting population fertility.     

What do we [not] know about technology entrepreneurship research?

This study aims to review what we do (and do not) know about technology entrepreneurship (TE) research to date. Based on a categorized bibliometric analysis resulting from a systematic review of 135 scientific articles published in refereed journals over the past 27 years (1986–2013), we identify the core domains of TE, its intellectual structure, the scientific journals with a major impact in this field of research, and the affiliation and collaboration networks within it. Specifically, through a detailed analysis of article co-citations within the TE area, this study provides co-citation networks of authors, journals, and their respective clusters, revealing their rankings in terms of contributions to the TE literature. This comprehensive analysis can be used to enhance our understanding of TE and support further research in this field.     

Psychological Constructs Underlying Farmers’ Decisions to Diversify or Specialise their Businesses – An Application of Theory of Planned Behaviour

We use the theory of planned behaviour (TPB) to explain how underlying psychological constructs influence farmers’ decisions to extend their farm businesses to income‐generating ventures outside conventional agricultural production. The analysis contrasts the influence of psychological constructs on this decision with those on decisions to specialise in a single farm enterprise or to have multiple farm enterprises. This is one of the first studies to introduce psychological constructs into the study of farm diversification. It is based on a sample of 929 Swedish farms participating in the official Swedish Farm Economic Survey. These data are supplemented with a detailed postal questionnaire to the participating farmers, generating a response rate of 73% and an effective sample size of 679 farmers and their businesses. Data are analysed with factor and multinomial logistic regression analyses. Results show that psychological constructs in TPB (attitude, subjective norm and perceived behavioural control) influence farmers’ decisions regarding the strategy they adopt. Attitude and subjective norm are found to be especially influential in these decisions. Given the prominent role agriculture still has in rural development policy, where the development of new ventures in farm businesses is perceived as the engine for rural economic growth and employment, these findings have clear policy implications.     

Pricing to market with trade liberalization: The role of market heterogeneity and product differentiation in India’s exports

This paper studies the links between pricing to market (PTM) and trade liberalization using data for India’s exports (at the 4-digit level of classification) during the economic reforms period (1992–2005). We estimate a PTM model for exports to the G3 and three other emerging markets (Brazil, China and South Africa), distinguishing homogeneous from differentiated goods and correcting for changes in the level of protection faced by India’s exporters (import tariffs in destination markets), inflation and openness in the export destination market, a macroeconomic policy index partly reflecting changes in exporter’s costs, the share of the exporter in the destination market and the share of the product in the exporter’s total exports. We find that market heterogeneity changes the level of PTM, but PTM does not significantly differ between homogeneous and differentiated products. Indian exporters practice PTM by absorbing exchange rate changes into their mark-up in G3 markets, where they face tougher competition, but fully pass-through exchange rate changes in emerging markets. On the contrary, Indian exporters seem to be taking advantage of trade liberalisation in destination markets by marginally increasing exporter currency prices into emerging markets but not into the G3. However, in the case of differentiated goods, we find this effect of trade liberalisation for both G3 and emerging markets.     

Data frequency and exchange rate pass-through: Evidence from India's exports

This paper studies the pricing behavior of Indian exporters using both annual and monthly data in order to uncover the role of data frequency in determining variation in the degree of short and long-run exchange rate pass-through (ERPT). Export price data during the post-1991 economic reforms period is disaggregated at the two-digit industry level and using a novel methodology in the ERPT literature (cointegration for heterogeneous panels) cross-industry differences in adjustment are identified. We observe that there is clear evidence of incomplete ERPT to prices in India's export markets, after having controlled for the level of exchange rate volatility and domestic inflation as an indicator of variations in marginal cost. The empirical results indicate that monthly data reflect more incomplete ERPT to destination market prices, relative to annual data, in which all the short run rigidities are more likely to have been adjusted. Thus studies that use higher frequency data are more likely to find incomplete ERPT in the short-run, even in the context of an emerging market economy. In the long-run, incomplete ERPT subsists in a few industries for both data frequencies.     

When transparency pays off: Enticing sceptical consumers with two-sided advertising

It has been generally assumed that higher levels of scepticism towards advertising invariably lead to higher resistance to advertising appeals. The main purpose of the present research was to examine whether highly sceptical consumers' resistance can be overcome by appeals associated with higher credibility. We tested our hypotheses using message sidedness as an advertising variable that has been associated with higher (two-sided) versus lower (one-sided) credibility. In three experimental studies, we examined more versus less sceptical consumers' responses to two- versus one-sided appeals. We found that two-sided messages are more effective in increasing purchase intentions, through enhanced credibility, but only for consumers who are more sceptical of advertising. Less sceptical consumers trust both messages equally and their purchase intentions are not affected by the type of message. Importantly, we also showed that highly sceptical consumers trust two-sided appeals as much as their less sceptical counterparts. The study contributes to the literature on advertising and persuasion knowledge by showing that advertising scepticism does not elicit a single response tendency, as originally conceptualized. Rather, advertising scepticism is more consistent with the underpinnings of the Persuasion Knowledge Model, in that higher knowledge about persuasion tactics aids consumers to better cope with, and not invariably resist persuasion attempts. We conclude that transparency pays off because it may entice a more sceptical audience and, at the same time, it does not harm less sceptical consumers' trust and purchase intentions.     

A network approach for assembling and linking input–output models

Input–output (IO) models, describing trade between different sectors and regions, are widely used to study the environmental repercussions of human activities. A frequent challenge in assembling an IO model or linking several such models is the absence of flow data with the same level of detail for all components. Such problems can be addressed using proportional allocation, which is a form of algebraic transformations. In this paper, we propose a novel approach whereby the IO system is viewed as a network, the topology of which is transformed with the addition of virtual nodes so that available empirical flow data can be mapped directly to existing links, with no additional estimation required, and no impact on results. As IO systems become increasingly disaggregated, and coupled to adjacent databases and models, the adaptability of IO frameworks becomes increasingly important. We show that topological transformations also offer large advantages in terms of transparency, modularity and increasingly importantly for global IO models, efficiency. We illustrate the results in the context of trade linking, multi-scale integration and other applications.     

Stress at the top: myth or fact? Causal explanations from a fuzzy-set qualitative comparative analysis (fsQCA)

Stress and its associated health issues are a serious concern, because they not only affect employees but also organizations through related costs. The common perception is that being at the top of a hierarchy is associated with higher levels of stress because of the increased responsibilities, challenges, and demands. The present study examines this perception by applying a fuzzy-set qualitative comparative analysis. The study investigates how the top position, authority, number of subordinates, workload, and a sense of control, alone or in combination, lead to stress or its absence. The results show that there are several recipes for stress and that being (or not being) in the top position is neither a sufficient nor a necessary condition for stress (or absence of stress). One of the recipes, however, indicates that being in the top position might be conducive to stress. This finding shows that the position an individual has in the hierarchy does not determine stress. The present study also shows that the absence of a sense of control is almost always a necessary condition for predicting stress and is present in all recipes for the absence of stress. The results can inform managers about the conditions that cause stress and enable managers to think about solutions that can lead to good mental health in their organizations.