The efficiency of public employment services: a matching frontiers approach

Purpose This paper aims to model the efficiency of labour offices belonging to the public employment services (PESs) in Spain using a stochastic matching frontier approach. Design/methodology/approach With this aim in mind, the authors apply a random parameter model approach to control for observed and unobserved heterogeneity. Findings Results indicate that when the information criteria of the estimates are analysed, it improves by controlling both, observed and unobserved heterogeneity in the inefficiency term. Also, results suggest that counsellors improve the productivity of labour offices and that the share of unemployed skilled persons, unemployed persons aged 44 or younger, as well as the share of unemployed persons in the construction sector, all affect the technical efficiency of PESs offices. Originality/value The model extends the previous specifications in the matching literature that capture only observed heterogeneity. Moreover, as far as the authors know, it is the first paper that estimates a matching frontier for the Spanish case. Finally, the database they use is at the office level and includes the work carried out by counsellors, which is a novelty in the analysis of this type of studies at the Spanish level.

Injury Severity and Contributing Driver Actions in Passenger Vehicle–Truck Collisions

Large-scale truck-involved crashes attract great attention due to their increasingly severe injuries. The majority of those crashes are passenger vehicle–truck collisions. This study intends to investigate the critical relationship between truck/passenger vehicle driver’s intentional or unintentional actions and the associated injury severity in passenger vehicle–truck crashes. A random-parameter model was developed to estimate the complicated associations between the risk factors and injury severity by using a comprehensive Virginia crash dataset. The model explored the unobserved heterogeneity while controlling for the driver, vehicle, and roadway factors. Compared with truck passengers, occupants in passenger vehicles are six times and ten times more likely to suffer minor injuries and serious/fatal injuries, respectively. Importantly, regardless of whether passenger vehicle drivers undertook intentional or unintentional actions, the crashes are more likely to associate with more severe injury outcomes. In addition, crashes occurring late at night and in early mornings are often correlated with more severe injuries. Such associations between explanatory factors and injury severity are found to vary across the passenger vehicle–truck crashes, and such significant variations of estimated parameters further confirmed the validity of applying the random-parameter model. More implications based on the results and suggestions in terms of safe driving are discussed.

POSITIONING VIETNAM’S PANGASIUS CATFISH IN THE FRENCH MARKET USING DISCRETE CHOICE MODEL

The study used discrete choice model to investigate the position of Vietnam’s Pangasius catfish in the French market. Data was collected via a choice experiment designed for 12 aquaculture species familiar to French consumers. The random parameter model was estimated and used to calculate the share elasticity. The market position of the aquaculture products in this study was calculated based on the competitive clout, vulnerability scores, and ranked-order implicit values. The results show that Vietnam’s Pangasius has a low competitive clout, high vulnarability score, and low ranked-order implicit value. A latent class model was also estimated for comparison and acquisition of additional information. A strong segment of Pangasius (11.9%) is described by low income and education consumers, women at mid-age dominated, and family with children. To improve the Pangasius position and image in the international market, Vietnam needs promotional and marketing campaigns at global level for the product.

A Random-Parameter Height-Dbh Model for Cherrybark Oak

A random-parameter model was used to relate total height to diameter at breast height (dbh) for cherrybark oak (Quercus pagoda Raf.). Data were obtained from 561 trees located in 50 stands occurring on bottomland hardwood sites in East Texas, near the western extent of the cherrybarkoak natural range. Mixed-model estimation techniques were used to fit fixed-effects parameters to the height-dbh relationship for cherrybark oak, with random-effects parameters representing sample stands from which tree data were obtained. The fixed-effect parameter estimates can be used topredict average cherrybark oak height for a given dbh in the region from which the data were obtained. Because random parameters associated with stands were used in the data-fitting process, the models can be calibrated to fit new stands by obtaining measurements to fit appropriate randomparameters for that stand. This calibration improves height predictions for individual stands while requiring less data than would the development of a completely new height prediction model for that stand. South. J. Appl. For. 29(1):22–26.