scholarly journals Economic valuation of attributes of Lake Tana: random parameter model

Heliyon ◽  
2021 ◽  
pp. e08356
Author(s):  
Asmamaw Getnet ◽  
Tefera Berihun
Keyword(s):  
Economic Valuation ◽  
Random Parameter ◽  
Lake Tana ◽  
Random Parameter Model

A calibrateable site index model for Pinus kesiya plantations in southeastern Africa

2002 ◽  
Vol 32 (11) ◽  
pp. 1916-1928 ◽  
Author(s):  
Kalle Eerikäinen ◽  
Danaza Mabvurira ◽  
Ladislaus Nshubemuki ◽  
Jussi Saramäki
Keyword(s):  
Random Parameter ◽  
Site Index ◽  
Stand Age ◽  
Random Parameters ◽  
Index Model ◽  
Forest Inventories ◽  
Pinus Kesiya ◽  
Dominant Height ◽  
Random Parameter Model ◽  
Site Index Model

The aim of the study was to develop a site index model for Pinus kesiya Royle ex Gordon plantations in southeastern Africa based on the relationship between the dominant height and stand age. Conversely, analysis of dominant height and age data showed that the growth patterns of plantations were different. In addition, the asymptotes and forms of standwise dominant height curves varied within plantations. In developing a common site index model, instead of using the more common approach of estimating separate dominant height–age models for different plantations or sites, a mean curve approach based on a linear random parameter model with fixed and random parameters was applied. The random parameter model of this study was calibrated by predicting random parameters for the plantation and stand effects, in accordance with the standard linear prediction theory. The analyses showed that the calibration of the dominant height model was an efficient method to obtain reliable dominant height predictions of a stand, particularly when several dominant height–age observations from different stands of a plantation and at least one measured dominant height and stand age of a target stand are available. This is the case in many forest inventories based on temporary samples, i.e., cross-sectional data. The new site index model is a useful tool for use in different mensurational applications, and its properties can efficiently be utilized for example in forest inventories of P. kesiya plantations in southeastern Africa.

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

2014 ◽  
Vol 17 (4) ◽  
pp. 96-111
Author(s):  
Thong Tien Nguyen ◽  
Hung Manh Nguyen
Keyword(s):  
Discrete Choice ◽  
Low Income ◽  
Latent Class ◽  
Choice Model ◽  
Latent Class Model ◽  
Random Parameter ◽  
Discrete Choice Model ◽  
Class Model ◽  
Additional Information ◽  
Random Parameter 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.

scholarly journals A Random-Parameter Height-Dbh Model for Cherrybark Oak

2005 ◽  
Vol 29 (1) ◽  
pp. 22-26 ◽  
Author(s):  
Thomas B. Lynch ◽  
A. Gordon Holley ◽  
Douglas J. Stevenson
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Random Parameter ◽  
Parameter Estimates ◽  
Quercus Pagoda ◽  
Random Parameter Model ◽  
Natural Range ◽  
Height Prediction ◽  
Effect Parameter ◽  
Height Predictions

Abstract 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.

scholarly journals The efficiency of public employment services: a matching frontiers approach

2019 ◽  
Vol 27 (81) ◽  
pp. 169-183
Author(s):  
Jose F. Baños ◽  
Ana Rodriguez-Alvarez ◽  
Patricia Suarez-Cano
Keyword(s):  
Unobserved Heterogeneity ◽  
Random Parameter ◽  
Information Criteria ◽  
Public Employment ◽  
Employment Services ◽  
Content Type ◽  
The Public ◽  
Random Parameter Model ◽  
Stochastic Matching ◽  
Office Level

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.

Valuing forest park attributes by giving consideration to the tourist satisfaction

2018 ◽  
Vol 25 (5) ◽  
pp. 711-733
Author(s):  
Nannan Kang ◽  
Erda Wang ◽  
Yang Yu
Keyword(s):  
Economic Valuation ◽  
Random Parameter ◽  
Compensating Variation ◽  
Forest Park ◽  
Resource Valuation ◽  
Conditional Logit ◽  
Parameter Estimations ◽  
Tourist Satisfaction ◽  
Level Of Satisfaction ◽  
High Level

Despite the economic valuation of forest park resources has triggered a great deal of interest to the research community and park management, up to now no attention has been paid to the effect of psychological factors such as tourist satisfaction, which could potentially play a considerable role in contributing to the park resource valuation. This article attempts to fill this niche by carrying out a study on the economic valuation of the Xian-Ren-Tai National Forest Park in China, taking consideration of the tourist satisfaction. In the process, the choice experiment survey was used for data collection. Then, both conditional logit (CL) and random parameter logit models were used in parameter estimations to examine the factors that could potentially impact on the tourists’ willingness to pay. Results indicate that the tourists attach the greatest importance to the park’s natural environment and traffic conditions, and yet the level of tourists’ satisfaction on their tourism experience plays a big part in explaining the valuation results. Tourists who uphold a high level of satisfaction tend to pay more for the park attribute improvement than those with less satisfaction ones. The estimated compensating variation of the overall current park attributes has reached ¥184.95 per person per trip, of which 12.83% shall be attributable to the tourist satisfaction.

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

2019 ◽  
Vol 16 (19) ◽  
pp. 3542 ◽  
Author(s):  
Jingjing Xu ◽  
Behram Wali ◽  
Xiaobing Li ◽  
Jiaqi Yang
Keyword(s):  
Large Scale ◽  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Random Parameter ◽  
Passenger Vehicle ◽  
Severe Injuries ◽  
Safe Driving ◽  
Explanatory Factors ◽  
Random Parameter Model ◽  
Minor Injuries

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.

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