Relevant bibliographies by topics / Ordered Probit Model

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Academic literature on the topic 'Ordered Probit Model'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Ordered Probit Model"

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Johnston, Carla, James McDonald, and Kramer Quist. "A generalized ordered Probit model." Communications in Statistics - Theory and Methods 49, no. 7 (January 23, 2019): 1712–29. http://dx.doi.org/10.1080/03610926.2019.1565780.

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Daykin, Anne R., and Peter G. Moffatt. "Analyzing Ordered Responses: A Review of the Ordered Probit Model." Understanding Statistics 1, no. 3 (August 2, 2002): 157–66. http://dx.doi.org/10.1207/s15328031us0103_02.

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Wang, Xiaokun (Cara), and Kara M. Kockelman. "Application of Dynamic Spatial Ordered Probit Model." Transportation Research Record: Journal of the Transportation Research Board 2136, no. 1 (January 2009): 45–56. http://dx.doi.org/10.3141/2136-06.

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Rifaat, S. M., and H. C. Chin. "Accident severity analysis using ordered probit model." Journal of Advanced Transportation 41, no. 1 (September 2007): 91–114. http://dx.doi.org/10.1002/atr.5670410107.

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Park, Seongmin, and Juneyoung Park. "Multilevel Mixed-Effects Models to Identify Contributing Factors on Freight Vehicle Crash Severity." Sustainability 14, no. 19 (September 20, 2022): 11804. http://dx.doi.org/10.3390/su141911804.

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Freight vehicle crashes are more serious than regular vehicle crashes because they are likely to lead to major damage and injury once they occur; therefore, countermeasures are needed. The fatality rate from freight vehicle crashes is 1.5 times higher than that of all other accidents, and the death rate from expressway freight vehicle crashes continues to increase. In this study, the ten-freight-vehicle crash severity models (the ordered logit and probit model, the multinomial logit and probit model, mixed-effects logit and probit model, random-effects ordered logit and probit model, and multilevel mixed-effects ordered logit and probit model) are used to analyze the freight vehicle crash severity factors. The model was constructed using data collected from expressways over eight years, and 13 factors were derived to increase the severity of crashes and 7 factors to reduce the severity of crashes. As a result of comparing the 10 constructed models using AIC and BIC, the multilevel mixed-effects ordered probit model showed the best performance. It is expected that it can contribute to improving the safety of freight vehicles in the expressway section by utilizing factors related to the severity of crashes derived from this study.
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Cameletti, Michela, Valerio De Rubeis, Clarissa Ferrari, Paola Sbarra, and Patrizia Tosi. "An ordered probit model for seismic intensity data." Stochastic Environmental Research and Risk Assessment 31, no. 7 (May 12, 2016): 1593–602. http://dx.doi.org/10.1007/s00477-016-1260-4.

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Kim, Haksoon. "Stock price discreteness and clustering: decimals and ordered probit model." Journal of Financial Regulation and Compliance 22, no. 1 (February 4, 2014): 49–60. http://dx.doi.org/10.1108/jfrc-07-2012-0025.

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Purpose – The purpose of this paper is to revisit the ordered probit model of Hausman et al. after the NYSE decimalization. Design/methodology/approach – The changed ordered probit model. Findings – The model can somewhat capture the different impact of trading-related “explanatory” variables on price changes among three different decimals but does not explain much about price discreteness and irregular transaction intervals among the existing models of stock price discreteness. Overall 1/16th and 1/24th range of the dependent variable is better explained by trading-related explanatory variables than 1/8th range of the dependent variable for small firms and there is not much difference in large firms among three decimals. The results imply that finer specification in decimalization and smaller firm size matters in trading after the decimalization project. Originality/value – First paper to revisit the ordered probit model of Hausman et al. after the NYSE decimalization.
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Zeng, Fan, Xiao Cao, and Huan-Ming Zhang. "Analysis of Digital Life Effect of Residents’ Trust Based on Multivariate Discrete Choice Model." Journal of Function Spaces 2022 (July 18, 2022): 1–14. http://dx.doi.org/10.1155/2022/1801399.

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In view of the impact of digital life on residents’ trust, firstly, based on the data of China Household Finance Survey (CHFS), this paper analyzes the change of residents’ trust in the era of data flooding. Through basic research and marginal effect analysis, it is found that digital life enhances residents’ trust. Secondly, the robustness of the conclusion is confirmed by constructing a series of models such as ordered probit of instrumental variable (IV-O probit), ordered probit of propensity score matching method (PSM-O probit), and ordered probit Heckman (O-probit-Heckman). Finally, through the mechanism test, it is concluded that digital life can enhance residents’ trust by increasing social activities and forming an inclusive social environment. It will also increase trust by obtaining information and increasing their cognitive level. The conclusion that digital life can enhance residents’ trust is more prominent among urban residents, nonpoor Hukou residents, and Han residents. Further research shows that the breadth and depth of digital life have a positive impact on residents’ trust, and digital life can improve residents’ risk tolerance.
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Park, Jong Hee. "Changepoint Analysis of Binary and Ordinal Probit Models: An Application to Bank Rate Policy Under the Interwar Gold Standard." Political Analysis 19, no. 2 (2011): 188–204. http://dx.doi.org/10.1093/pan/mpr007.

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In this paper, I introduce changepoint models for binary and ordered time series data based on Chib's hidden Markov model. The extension of the changepoint model to a binary probit model is straightforward in a Bayesian setting. However, detecting parameter breaks from ordered regression models is difficult because ordered time series data often have clustering along the break points. To address this issue, I propose an estimation method that uses the linear regression likelihood function for the sampling of hidden states of the ordinal probit changepoint model. The marginal likelihood method is used to detect the number of hidden regimes. I evaluate the performance of the introduced methods using simulated data and apply the ordinal probit changepoint model to the study of Eichengreen, Watson, and Grossman on violations of the “rules of the game” of the gold standard by the Bank of England during the interwar period.
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Lin, Zijing, and Wei “David” Fan. "Bicycle Ridership Using Crowdsourced Data: Ordered Probit Model Approach." Journal of Transportation Engineering, Part A: Systems 146, no. 8 (August 2020): 04020076. http://dx.doi.org/10.1061/jtepbs.0000399.

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Dissertations / Theses on the topic "Ordered Probit Model"

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Keller, Joanne Marie. "ANALYSIS OF TYPE AND SEVERITY OF TRAFFIC CRASHES AT SIGNALIZED INTERSECTIONS USING TREE-BASED REGRESSION AND ORDERED PROBIT MODELS." Master's thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4382.

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Many studies have shown that intersections are among the most dangerous locations of a roadway network. Therefore, there is a need to understand the factors that contribute to traffic crashes at such locations. One approach is to model crash occurrences based on configuration, geometric characteristics and traffic. Instead of combining all variables and crash types to create a single statistical model, this analysis created several models that address the different factors that affect crashes, by type of collision as well as injury level, at signalized intersections. The first objective was to determine if there is a difference between important variables for models based on individual crash types or severity levels and aggregated models. The second objective of this research was to investigate the quality and completeness of the crash data and the effect that incomplete data has on the final results. A detailed and thorough data collection effort was necessary for this research to ensure the quality and completeness of this data. Multiple agencies were contacted and databases were crosschecked (i.e. state and local jurisdictions/agencies). Information (including geometry, configuration and traffic characteristics) was collected for a total of 832 intersections and over 33,500 crashes from Brevard, Hillsborough and Seminole Counties and the City of Orlando. Due to the abundance of data collected, a portion was used as a validation set for the tree-based regression. Hierarchical tree-based regression (HTBR) and ordered probit models were used in the analyses. HTBR was used to create models for the expected number of crashes for collision type as well as injury level. Ordered probit models were only used to predict crash severity levels due to the ordinal nature of this dependent variable. Finally, both types of models were used to predict the expected number of crashes. More specifically, tree-based regression was used to consider the difference in the relative importance of each variable between the different types of collisions. First, regressions were only based on crashes available from state agencies to make the results more comparable to other studies. The main finding was that the models created for angle and left turn crashes change the most compared to the model created from the total number of crashes reported on long forms (restricted data usually available at state agencies). This result shows that aggregating the different crash types by only estimating models based on the total number of crashes will not predict the number of expected crashes as accurately as models based on each type of crash separately. Then, complete datasets (full dataset based on crash reports collected from multiple sources) were used to calibrate the models. There was consistently a difference between models based on the restricted and complete datasets. The results in this section show that it is important to include minor crashes (usually reported on short forms and ignored) in the dataset when modeling the number of angle or head-on crashes and less important to include minor crashes when modeling rear-end, right turn or sideswipe crashes. This research presents in detail the significant geometric and traffic characteristics that affect each type of collision. Ordered probit models were used to estimate crash injury severity levels for three different types of models; the first one based on collision type, the second one based on intersection characteristics and the last one based on a significant combination of factors in both models. Both the restricted and complete datasets were used to create the first two model types and the output was compared. It was determined that the models based on the complete dataset were more accurate. However, when compared to the tree-based regression results, the ordered probit model did not predict as well for the restricted dataset based on intersection characteristics. The final ordered probit model showed that crashes involving a pedestrian/bicyclist have the highest probability of a severe injury. For motor vehicle crashes, left turn, angle, head-on and rear-end crashes cause higher injury severity levels. Division (a median) on the minor road, as well as a higher speed limit on the minor road, was found to lower the expected injury level. This research has shed light on several important topics in crash modeling. First of all, this research demonstrated that variables found to be significant in aggregated crash models may not be the same as the significant variables found in models based on specific crash types. Furthermore, variables found to be significant in crash type models typically changed when minor crashes were added to complete the dataset. Thirdly, ordered probit models based on significant crash-type and intersection characteristic variables have greater crash severity prediction power, especially when based on the complete dataset. Lastly, upon comparison between tree-based regression and ordered probit models, it was found that the tree-based regression models better predicted the crash severity levels.
M.S.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil and Environmental Engineering
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Pörn, Sebastian, and Arvid Rönnblom. "Assesing counterparty risk classification using transition matrices : Comparing models' predictive ability." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136667.

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An important part when managing credit risk is to assess the probability of default of different counterparties. Increases and decreases in such probabil- ities are central components in the assessment, and this is where transition matrices become useful. These matrices are commonly used tools when as- sessing counterparty credit risk, and contain the probability of default, as well as the probability to migrate between different predefined rating classifica- tions. These rating classifications are used to reflect the risk taken towards different counterparties. Therefore, it is important for financial institutions to develop accurate transition matrix models to manage predicted changes in credit risk exposure. This is because counterparty creditworthiness and prob- ability of default indirectly affect expected loss and the capital requirement of held capital. This thesis will analyze how two specific models perform when used for generating transition matrices. These models will be tested to investigate their performance when predicting rating transitions, including probability of default.
En viktig del vid hanteringen av kreditrisk är att bedöma sannolikheten för fallissemang för olika motparter. Ökningar och minskningar i dessa sanno- likheter är centrala komponenter i bedömningen, och det är här migrations- matriser blir användbara. Dessa matriser är vanligt förekommande verktyg vid bedömning av kreditrisk mot olika motparter och innehåller sannolikheten för fallissemang samt sannolikheten att migrera mellan olika fördefinierade be- tygsklassificeringar. Dessa betygsklassificeringar används för att återspegla den risk som tas mot olika motparter. Det är därför viktigt för finansinstitut att utveckla träffsäkra migrationsmatris modeller för att hantera förväntade förändringar i kreditriskexponering. Detta beror på att kreditvärdigheten hos motparter samt sannolikheten för fallissemang indirekt påverkar expected loss och kapitalkrav. Detta examensarbete kommer att analysera hur två specifika modeller presterar när de används för att generera migrationsmatriser. Dessa mod- eller kommer att testas för att undersöka hur de presterar när de används för att förutsäga övergångar inom betygsklassificering, inklusive sannolikheten för fallissemang.
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Carrion, Yaguana Vanessa Del Rocio. "Adoption Analysis and Impact Evaluation of Potato IPM in Ecuador." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23286.

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There are several well-known negative side effects associated with pesticide use such as health problems and environmental pollution.  Integrated Pest Management (IPM) seeks to minimize pesticide use while reducing pest infestation to economically tolerable levels.  The introduction of IPM CRSP activities in Ecuador to institutionalize IPM methods focused on priority crops in the country. This study analyzes adoption and the economic impacts of IPM technologies on potato production in the province of Carchi. A model is estimated in which IPM adoption is discrete and ordered and pesticides expenditures are estimated as a function of education, farming experience, wealth, plot size and farmer being sick due to pesticide use for each level of IPM adoption. Results indicate that farmers who were exposed to certain IPM information sources increased adoption of IPM practices on potatoes, but farmers\' education and experience were not important factors in explaining IPM adoption. The calculated economic benefits in terms of aggregate cost savings per production cycle were $823,000.
Master of Science
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Gonzalez-Velez, Enrique. "Safety Evaluation of Roadway Lighting Illuminance Levels and its Relationship with Nighttime Crash Injury Severity for West Central Florida Region." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3122.

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The main role of roadway lighting is to produce quick, accurate and comfortable visibility during nighttime conditions. It is commonly known that good lighting levels enable motorists, pedestrians and bicyclists to obtain necessary visual information in an effective and efficient manner. Many previous studies also proved that roadway lighting minimizes the likelihood of crashes by providing better visibility for roadway users. Appropriate and adequate roadway lighting illuminance levels for each roadway classification and pedestrian areas are essential to provide safe and comfortable usage. These levels are usually provided by national, or local standards and guidelines. The Florida Department of Transportation (FDOT) Plan Preparation Manual recommends a roadway lighting illuminance level average standard of 1.0 horizontal foot candle (fc) for all the roadway segments used in this research. The FDOT Plan Preparation Manual also states that this value should be considered standard, but should be increased if necessary to maintain an acceptable uniformity illuminance ratio. This study aimed to find the relationship between nighttime crash injury severity and roadway lighting illuminance. To accomplish this, the research team analyzed crash data and roadway lighting illuminance measured in roadway segments within the West Central Florida Region. An Ordered Probit Model was developed to understand the relationship between roadway lighting illuminance levels and crash injury severity. Additionally, a Negative Binomial Model was used to determine which roadway lighting illuminance levels can be more beneficial in reducing the counts of crashes resulting in injuries. A comprehensive literature review was conducted using longitudinal studies with and without roadway lighting. Results showed that on the same roadways there was a significant decrease in the number of nighttime crashes with the presence of roadway lighting. In this research, roadway lighting illuminance was measured every 40 feet using an Advanced Lighting Measurement System (ALMS) on a total of 245 centerline miles of roadway segments within the West Central Florida Region. The data were mapped and then analyzed using the existing mile post. During the process of crash data analysis, it was observed that rear-end collisions were the most common first harmful event observed in all crashes, regardless of the lighting conditions. Meanwhile, the average injury severity for all crashes, was found to be possible injury regardless of the lighting conditions (day, dark, dusk, and dawn). Finally, this research presented an Ordered Probit Model, developed to understand the existing relationship between roadway lighting illuminance levels and injury severity within the West Central Florida Region. It was observed that having a roadway lighting average moving illuminance range between 0.4 to 0.6 foot candles (fc) was more likely to have a positive effect in reducing the probability of injury severity during a nighttime crash. A Negative Binomial Model was conducted to determine if the roadway lighting average moving illuminance level, found on the Ordered Probit Model was beneficial in reducing crash injury severity during nighttime, would also be beneficial in reducing the counts of crashes resulting in injuries. It was observed that a roadway lighting average moving illuminance, range between 0.4 to 0.6 fc, was more likely to reduce the count of crashes resulting in injuries during nighttime conditions, thus increasing roadway safety. It was also observed that other factors such as pavement condition, site location (intersection or no intersection), number of lanes, and traffic volume can affect the severity and counts of nighttime crashes. The results of this study suggest that simply adding more roadway lighting does not make the roadway safer. The fact is that a reduction in the amount of roadway lighting illuminance can produce savings in energy consumption and help the environment by reducing light pollution. Moreover, these results show that designing roadway lighting systems go beyond the initial design process, it also requires continuous maintenance. Furthermore, regulations for new developments and the introduction of additional lighting sources near roadway facilities (that are not created with the intent of being used for roadway users) need to be created.
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Siddiqui, Naved Alam. "Crossing locations, light conditions, and pedestrian injury severity." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/2701.

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This study assesses the role of crossing locations and light conditions in pedestrian injury severity through a multivariate regression analysis to control for many other factors that also may influence pedestrian injury severity. Crossing locations include midblock and intersections, and light conditions include daylight, dark with street lighting, and dark without street lighting. The study formulates a theoretical framework on the determinants of pedestrian injury severity, and specifies an empirical model accordingly. An ordered probit model is then applied to the KABCO severity scale of pedestrian injuries which occurred while attempting street crossing in the years 1986 to 2003 in Florida. In terms of crossing locations, the probability of a pedestrian dying when struck by a vehicle, is higher at midblock locations than at intersections for any light condition. In fact, the odds of sustaining a fatal injury is 49 percent lower at intersections than at midblock locations under daylight conditions, 24 percent lower under dark with street lighting conditions, and 5 percent lower under dark without street lighting conditions. Relative to dark conditions without street lighting, daylight reduces the odds of a fatal injury by 75 percent at midblock locations and by 83 percent at intersections, while street lighting reduces the odds by 42 percent at midblock locations and by 54 percent at intersections.
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Basu, Nandita. "Pedestrian route choice behaviour: Influences of built environment on route preference, safety and security." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/236797/1/Thesis_Nandita%2BBasu_24112022.pdf.

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Built environment factors influence pedestrian route choice behaviour, but their impact is not well known. This thesis investigates the influences of the built environment factors on walking route preference and safety. By using the ‘Physical Activity through Sustainable Transport Approaches’ framework, this research studied the perceptions and preferences of pedestrian route choice in a typical suburban environment in Australia through a stated preference survey. This thesis has established the interrelationship between safety, security, and built environment factors across men and women pedestrians. The findings highlight increasing land-use diversity and providing adequate trees may improve perceived safety and security among pedestrians.
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Prakash, Puneet. "Absolute or Relative? Which Standards do Credit Rating Agencies Follow?" restricted, 2005. http://etd.gsu.edu/theses/available/etd-08042005-152025/.

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Thesis (Ph. D.)--Georgia State University, 2005.
Title from title screen. Richard D Phillips, committee chair; Neil A Doherty, Sanjay Srivastava, Jayant R Kale, Ajai Subramanian, committee members. Electronic text (133 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed June 26, 2007. Includes bibliographical references (p. 69-74).
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Ndunda, E. N. (Ezekiel Nthee). "Wastewater reuse in urban and peri-urban irrigation : an economic assessment of improved wastewater treatment, low-risk adaptations and risk awareness in Nairobi, Kenya." Thesis, University of Pretoria, 2013. http://hdl.handle.net/2263/40235.

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The overall goal of this study was to analyse the welfare effect of improved wastewater treatment with the view of making policy recommendations for sustainable urban and peri-urban irrigation agriculture in Kenya. This goal was achieved by investigating three specific objectives. The first objective was to assess the farmers’ awareness of health risks in urban and peri-urban wastewater irrigation. Second objective was to analyse the factors that affect the choice of low-risk adaptations in reuse of untreated wastewater for irrigation. The third objective was to estimate the value that urban and peri-urban farmers who practice wastewater irrigation impute to improvements in specific characteristics of the wastewater input in agriculture. In order to achieve the first objective, an ordered probit model was used to identify the factors that influence farmers’ awareness of health risks in untreated wastewater irrigation. The model was fitted to data collected from a cross-sectional survey of 317 urban farm households in the Kibera informal settlement of Kenya. Results of this study show that gender of household head, household size, education level of household head, farm size, ownership of the farm, membership to farmers’ group, and market access for the fresh produce significantly affect awareness of farmers about health risks in wastewater irrigation. Therefore, there is need for awareness programs to promote public education through regular training and local workshops on wastewater reuse in order to improve the human capital of the urban and peri-urban farmers. To achieve the second objective, the study used a multinomial logit model to analyse the farmers’ choice of low-risk adaptations in untreated wastewater irrigation. A survey of 317 urban and peri-urban farmers was conducted and measures for risk-reduction in wastewater reuse were analysed. The urban and peri-urban farmers were found to have adopted low-risk wastewater irrigation techniques such as cessation of irrigation before harvesting, crop restriction and safer application methods. Results of the study show that adoption of risk-reduction measures is significantly influenced by the following factors: household size, age of the household head, education of household head, access to extension, access to media, access to credit, farmers’ group membership, and risk awareness. Also, marginal analysis of the coefficients confirmed the socio-economic characteristics are key determinants in adoption of low-risk measures in wastewater reuse. The study recommends that policies in support of low-risk urban and peri-urban irrigation agriculture should disaggregate farmers according to their socio-economic and institutional characteristics in order to achieve their intended objectives. To achieve the third objective, the study employed the discrete choice experiment approach to estimate the benefits farmers impute to improvements in attributes of the wastewater irrigation input, whose aim is to reduce the health risks associated with untreated wastewater irrigation. Urban and peri-urban farmers who practice wastewater irrigation drawn from Motoine-Ngong River in Nairobi were randomly selected for the study. A total of 241 farmers completed the presented choice cards for the choice model estimation. A random parameter logit model was used to estimate the individual level willingness to pay for wastewater treatment. The results show that urban and peri-urban farmers are willing to pay significant monthly municipality taxes for treatment of wastewater. Conclusion of this study was that, quality of treated wastewater, quantity of treated wastewater and the riverine ecosystem restoration are significant factors of preference over policy alternative designs in wastewater treatment and reuse.
Thesis (PhD)--University of Pretoria, 2013.
gm2014
Agricultural Economics, Extension and Rural Development
unrestricted
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VENNERI, ANNA VALERIA. "Le banche e il processo di valutazione del merito di credito degli Enti Locali italiani: dal rating esterno ad un modello di analisi interno." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2010. http://hdl.handle.net/2108/1264.

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In seguito al recepimento della nuova disciplina di vigilanza prudenziale, le banche possono optare per due metodi alternativi per il calcolo dei requisiti patrimoniali minimi a fronte del rischio di credito: il metodo standardizzato, che prevede il ricorso ai rating esterni forniti da Agenzie specializzate, ed il metodo dei rating interni, basato su modelli testati internamente dalle banche. Mentre da tempo sono state implementate metodologie interne per il calcolo del rating del segmento imprese (peraltro, ancora non del tutto affidabili), sono poche le banche che hanno sviluppato una valutazione interna delle amministrazioni statali e locali e non si trova, inoltre, adeguato supporto teorico da parte della letteratura scientifica. Partendo da tale premessa, il presente lavoro di ricerca si propone di analizzare le metodologie di valutazione adottate dalle Agenzie di rating per individuare quali fattori economico-finanziari incidono in maggior misura sui sub-sovereign credit rating assegnati agli Enti Locali italiani, anche allo scopo di poter mutuare tali metodologie nei processi di valutazione del merito di credito delle banche. A tal fine, è stato applicato un modello probit ordinato multinomiale ad oltre 310 rating assegnati da Moody’s, Standard & Poor’s e Fitch Ratings ad un campione di Province e Comuni capoluogo italiani tra il 2004 e il 2008. I risultati dell’analisi aggregata consentono di confermare in parte le attese teoriche, evidenziando altresì le divergenze di valutazione tra Agenzie riscontrate in letteratura. In particolare, solo l’indicatore macro-economico rappresentativo del PIL locale pro-capite appare statisticamente significativo e di segno atteso, mentre le variabili di natura strutturale e comportamentale degli Enti sono significative solo per due Agenzie, ma non sempre rispettano il segno atteso. Contrariamente alle attese teoriche e alle evidenze empiriche emergenti in letteratura, il livello di indebitamento locale pro-capite nonché l’indicatore del fabbisogno finanziario non risultano essere statisticamente significativi. Alla luce di tali evidenze, lo studio contribuisce ad arricchire lo stato dell’arte sulla c.d. public finance con spunti di ricerca che offrono importanti implicazioni anche di carattere operativo.
Following the adoption of the new capital adequacy and requirements rules, banks currently have two options in order to calculate the minimum capital requirements for credit risk: the standardised approach, supported by external credit assessments, and the internal ratings-based (IRB) approach, relied on banks’ own internal estimates. While banks have been implementing (not quite reliable yet) internal methodologies to estimate corporate ratings long ago, there are not many banks which currently assess state and local governments, and also literature investigates this theme not much. So the research aims analyzing Agencies’ methodologies to identify which are the economic and financial determinants of Italian local government ratings, so as to transfer Agencies’ experience inside banks. Consequently, this analysis applies a multinomial ordered probit model to more than 310 Italian sub-sovereign ratings, as overall assigned by Moody’s, Standard & Poor’s and Fitch Ratings in the period 2004-2008. The results of pooled analysis allow to partially confirm theoretical expectations, and highlight differences of valuation among Agencies as shown in literature. So, only the local GDP per capita is statistically significant and has the expected sign, while other structural and behavioural variables are significant just for two Agencies, but sometimes have the unexpected sign. Instead, contrary to theoretical expectations and empirical evidences from literature, both local debt per capita and borrowing needs are never statistically significant. So this study contributes to improve the literature on public finance pointing out relevant managerial and operational implications too.
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Lucena, Igor Macedo de. "What characteristics influence the future performance of the investment funds of shares in Brazil?" Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12523.

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nÃo hÃ
Segundo Jensen (1968), a indÃstria de fundos mÃtuos de investimento, cuja expansÃo està prevista teoricamente pelo Teorema da SeparaÃÃo enunciado em Sharpe (1964), teria limitaÃÃes no sentido de bater o mercado em termos de performance risco-retorno mensurada pelo alfa de Jensen. Nesta ampla discussÃo, esta dissertaÃÃo se posiciona em sugerir um exercÃcio empÃrico aplicado a um cross-section contendo 243 fundos de investimentos em aÃÃes, categoria Ibovespa Ativo, o qual visa identificar que variÃveis financeiras, contÃbeis e administrativas se mostram capazes de prever no ano seguinte o sinal e a significÃncia do alfa de Jensen. Foram extraÃdos retornos diÃrios para todos os fundos nos anos de 2011 e 2012, e calculadas mÃtricas clÃssicas de retorno, risco e performance, bem como os 24 balancetes mensais e informaÃÃes administrativas do perÃodo em questÃo. Metodologicamente, as variÃveis explicativas consistem em estatÃsticas descritivas obtidas a partir de dados financeiros diÃrios e contÃbeis mensais, enquanto as performances a serem modeladas sÃo estimadas por meio do Capital Asset Pricing Model (CAPM). Dessa maneira, foi possÃvel ordenar os fundos em trÃs grupos, composto por Loosers, Draw e Winners, de acordo com suas performances em relaÃÃo ao Ãndice Ibovespa. Sendo assim, foi identificado que apenas 71 dos fundos foram capazes de performar melhor que o Ãndice Ibovespa durante o ano de 2012. Os resultados obtidos com a estimaÃÃo do arcabouÃo de Probit ordenado sugerem que fundos com maiores performances mensuradas pelos alfa de Jensen e Ãndices de Calmar e Sortino, associados a menores taxas de administraÃÃo, tendem a bater o mercado no ano seguinte. Entretanto, mÃtricas clÃssicas como desvio-padrÃo, taxa de performance e Ãndice de Sharpe (1964) nÃo se mostraram significantes. O modelo sugere, tambÃm, que a variÃvel Drawdown seja apresentada como mÃtrica eficiente de mensuraÃÃo de risco.
According to Jensen (1968), the mutual funds industry expansion is theoretically predicted by the Separation Theorem stated by Sharpe (1964), however with limitations in order to exceed the market in terms of risk-return performance measured by Jensen's alpha. In this broad discussion, this dissertation suggest an empirical exercise applied to a cross-section containing 243 stock funds, within the Ibovespa Active category, which aims to identify which financial, accounting and administrative variables are capable to predict the next year's value and the significance of the Jensen's alpha. Daily returns were extracted for all funds in 2011 and 2012, and were calculated classic metrics such as return, risk and performance. There were also extracted 24 monthly accounting balances and administrative informations for the period in question. Methodologically, the explanatory variables consist of descriptive statistics obtained from daily financial data and monthly accounting data, while the performances to be modeled are estimated using the Capital Asset Pricing Model (CAPM). Using this technic it was possible divide the funds into three groups, consisting of Loosers, Draw and Winners, according to their performances in relation to the Ibovespa index. Thus, it was discovered that only 71 funds were able to perform better than the Ibovespa Index during the year 2012. The estimation results of the ordered probit framework suggests that funds with higher performances measured by the Jensen's Alpha and with higher Sortino and Calmar ratios, associated with lower management fees tend to surpass the market in the next year. However, classical metrics like standard deviation, performance fees and Sharpe ratio (1964) were not significant. The model also suggests that the drawdown variable should be used as an efficient risk metric.
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Books on the topic "Ordered Probit Model"

1

Holden, Darryl. Normality and homoscedasticity tests in the ordered probit model. Glasgow: Fraser of AllanderInstitute, Dept. of Economics, 1993.

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Pudney, Stephen. Gender, race, pay and promotion in the British nursing profession: Estimation of a generalised ordered probit model. [New York]: Wiley & Sons, 2000.

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Cheung, Stella. Provincial credit ratings in Canada: An ordered probit analysis. Ottawa: Bank of Canada, 1996.

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Murphy, Anthony. Artificial regression based LM tests of mis-specification for ordered probit models. Dublin: University College Dublin, Department of Economics, 1994.

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Pudney, Stephen. Gender, race, pay and promotion in the British nursing profession: Estimation of a generalised ordered probit model. University of Leicester, Public Sector Economics Research Centre, 1997.

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Logit and Probit: Ordered and Multinomial Models (Quantitative Applications in the Social Sciences). Sage Publications, Inc, 2001.

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Glasgow, Garrett, and R. Michael Alvarez. Discrete Choice Methods. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0022.

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This article describes the statistical models commonly used to study discrete choices. It concentrates on the ‘basic’ discrete choice models, and the theoretical choice situations that lead to these models. Specifically the choice situation addressed include: the ordered choice situation and the unordered choice situation. In addition, the article discusses two extensions of the basic discrete choice models commonly seen in political science research — models allowing for heteroskedasticity in the choices made across political agents (such as the heteroskedastic probit), and models that estimate substitution patterns across choice alternatives (such as the multinomial probit and mixed logit). Suggestions for further reading are also given.
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Dossa, Zahir. Co-operatives: A Development Strategy? Edited by Jonathan Michie, Joseph R. Blasi, and Carlo Borzaga. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199684977.013.32.

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The examination of the life cycle, institutional structure, and governance and policy environment of co-operatives in the argan oil sector, in south-west Morocco, outlines the successes and setbacks of the co-operative model as a suitable tool for economic and social development in rural areas. Despite the positive development outcomes argan oil co-operatives attained, they strayed from four basic co-operative tenets: democratic decision-making, equitable profit distribution, open membership, and member education on co-operatives. Starting from this analysis, this chapter argues that the success of argan oil co-operatives is to be attributed to their abandonment of the basic co-operative principles. Furthermore, it seeks to understand the conditions that make co-operatives feasible and effective in particular environments and how co-operatives, or employee-centric firms, can be adapted to their environments, or vice versa, through e-commerce and financial transparency in order to generate economic and social development.
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Maquet, Pierre, and Julien Fanielle. Neuroimaging in normal sleep and sleep disorders. Edited by Sudhansu Chokroverty, Luigi Ferini-Strambi, and Christopher Kennard. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682003.003.0011.

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Functional neuroimaging techniques include methods that probe various aspects of brain function and help derive models of brain organization in health and disease. These techniques can be grouped in two categories. Some are mainly based on electromagnetic signals (electroencephalography, magnetoencephalography), recording brain activity using a large number of sensors with exquisite temporal resolution (usually of the order of a kilohertz) but allowing only indirect characterization of three-dimensional brain activity by resorting to mathematical models. The second type includes different techniques (PET scan, SPECT, MRI, optical imaging) that typically assess metabolic or hemodynamic parameters, with millimeter spatial resolution and usually from the entire brain volume. However, temporal resolution is usually low because it is primarily driven by metabolic processes that unfold in several seconds or minutes. This chapter focuses on this second type, covering the contribution of brain imaging to understanding NREM sleep and REM sleep and also sleep disorders.
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Chalabi, Azadeh. National Human Rights Action Planning. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198822844.001.0001.

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This book deals with human rights action planning, as a largely under-researched area, from theoretical, doctrinal, empirical, and practical perspectives in order to put forward a new account of such planning. As such, the present work provides one of the most comprehensive studies of human rights planning to date. At the theoretical level, by advancing a novel general theory of human rights planning, it offers an alternative to the traditional state-centric model of planning. This new theory contains four sub-theories: contextual, substantive, procedural, and analytical ones. At the doctrinal level, a textual analysis of core human rights conventions is conducted in order to reveal the scope and nature of the obligation to adopt a national human rights action plan and to consider how to ensure that states are in compliance with this obligation. At the empirical level, a cross-case analysis of national human rights action plans of fifty-three countries is conducted exploring the major problems of these plans in different phases and uncovering the underlying causes. At the practical level, both national and supra-national human rights governance systems are examined. At the supra-national level, a networked model of global human rights governance is suggested as a practical response strategy against the extant global governance system which hardly works as an integrated system. At the national level, after suggesting the establishment of a nation-wide network for implementing human rights, the essential parts of human rights action planning are probed in four phases putting forward some methodological techniques for each phase.
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Book chapters on the topic "Ordered Probit Model"

1

Yao, Guangzheng, Yanyan Chen, Kaijun Cui, Donghui Xu, and Jiarui Liu. "A Method of Household Car Ownership Prediction Using Ordered Probit Model." In Lecture Notes in Electrical Engineering, 759–71. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5429-9_57.

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Kang, Kyungwoo. "Ordered Probit Model of the Speed Selection Behavior: Results Based on a Korean Micro Data." In Transportation, Traffic Safety and Health — Human Behavior, 263–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57266-1_16.

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Burnell, E. E., and C. A. de Lange. "Solutes as Probes of Simplified Models of Orientational Order." In NMR of Ordered Liquids, 221–40. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0221-8_10.

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Chi, Ouyang. "Is There a Phenomenon of Despising the Poor and Currying Favour with the Rich in Urban and Rural Residents’ Basic Pension Insurance System? Empirical Test Based on Ordered-Probit Model and Strategy of Establishing an Information Pension Insurance Service System." In Atlantis Highlights in Intelligent Systems, 1572–82. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-030-5_158.

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Habyarimana, Ephrem, and Sofia Michailidou. "Genomic Prediction and Selection in Support of Sorghum Value Chains." In Big Data in Bioeconomy, 207–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_16.

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AbstractGenomic prediction and selection models (GS) were deployed as part of DataBio project infrastructure and solutions. The work addressed end-user requirements, i.e., the need for cost-effectiveness of the implemented technologies, simplified breeding schemes, and shortening the time to cultivar development by selecting for genetic merit. Our solutions applied genomic modelling in order to sustainably improve productivity and profits. GS models were implemented in sorghum crop for several breeding scenarios. We fitted the best linear unbiased predictions data using Bayesian ridge regression, genomic best linear unbiased predictions, Bayesian least absolute shrinkage and selection operator, and BayesB algorithms. The performance of the models was evaluated using Monte Carlo cross-validation with 70% and 30%, respectively, as training and validation sets. Our results show that genomic models perform comparably with traditional methods under single environments. Under multiple environments, predicting non-field evaluated lines benefits from borrowing information from lines that were evaluated in other environments. Accounting for environmental noise and other factors, also this model gave comparable accuracy with traditional methods, but higher compared to the single environment model. The GS accuracy was comparable in genomic selection index, aboveground dry biomass yield and plant height, while it was lower for the dry mass fraction of the fresh weight. The genomic selection model performances obtained in our pilots are high enough to sustain sorghum breeding for several traits including antioxidants production and allow important genetic gains per unit of time and cost.
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Zdybał, K., M. R. Malik, A. Coussement, J. C. Sutherland, and A. Parente. "Reduced-Order Modeling of Reacting Flows Using Data-Driven Approaches." In Lecture Notes in Energy, 245–78. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16248-0_9.

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AbstractData-driven modeling of complex dynamical systems is becoming increasingly popular across various domains of science and engineering. This is thanks to advances in numerical computing, which provides high fidelity data, and to algorithm development in data science and machine learning. Simulations of multicomponent reacting flows can particularly profit from data-based reduced-order modeling (ROM). The original system of coupled partial differential equations that describes a reacting flow is often large due to high number of chemical species involved. While the datasets from reacting flow simulation have high state-space dimensionality, they also exhibit attracting low-dimensional manifolds (LDMs). Data-driven approaches can be used to obtain and parameterize these LDMs. Evolving the reacting system using a smaller number of parameters can yield substantial model reduction and savings in computational cost. In this chapter, we review recent advances in ROM of turbulent reacting flows. We demonstrate the entire ROM workflow with a particular focus on obtaining the training datasets and data science and machine learning techniques such as dimensionality reduction and nonlinear regression. We present recent results from ROM-based simulations of experimentally measured Sandia flames D and F. We also delineate a few remaining challenges and possible future directions to address them. This chapter is accompanied by illustrative examples using the recently developed Python software, PCAfold. The software can be used to obtain, analyze and improve low-dimensional data representations. The examples provided herein can be helpful to students and researchers learning to apply dimensionality reduction, manifold approaches and nonlinear regression to their problems. The Jupyter notebook with the examples shown in this chapter can be found on GitHub at https://github.com/kamilazdybal/ROM-of-reacting-flows-Springer.
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Iannino, Vincenzo, Valentina Colla, Alessandro Maddaloni, Jens Brandenburger, Ahmad Rajabi, Andreas Wolff, Joaquin Ordieres, et al. "Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-Based Approaches: Challenges and Perspectives." In IFIP Advances in Information and Communication Technology, 619–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79150-6_49.

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AbstractIn recent years, the European Steel Industry, in particular flat steel production, is facing an increasingly competitive market situation. The product price is determined by competition, and the only way to increase profit is to reduce production and commercial costs. One method to increase production yield is to create proper scheduling for the components on the available machines, so that an order is timely completed, optimizing resource exploitation and minimizing delays. The optimization of production using efficient scheduling strategies has received ever increasing attention over time and is one of the most investigated optimization problems. The paper presents three approaches for improving flexibility of production scheduling in flat steel facilities. Each method has different scopes and modelling aspects: an auction-based multi-agent system is used to deal with production uncertainties, a multi-objective mixed-integer linear programming-based approach is applied for global optimal scheduling of resources under steady conditions, and a continuous flow model approach provides long-term production scheduling. Simulation results show the goodness of each method and their suitability to different production conditions, by highlighting their advantages and limitations.
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Meng, Fan-Hua, Xiao-Ming Tian, Tien-Hui Chiang, and Yi Cai. "The State Role in Excellent University Policies in the Era of Globalization: The Case of China." In Evaluating Education: Normative Systems and Institutional Practices, 197–217. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7598-3_12.

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AbstractIn order to obtain considerable amounts of capitalist profit available in a globalized market, individual countries need to enhance their own international competitiveness – a goal that can be achieved through the channel of schools by cultivating human capital. The linear linkage among globalization, international competitiveness, human capital and higher education has convinced many countries to engage in the expansion of higher education institutes. The notion of international competition further generates the idea of university ranking and, in turn, many countries have viewed the world class university as the top priority on the political agenda. As neo-liberalism has become a prevailing new world value, constructed by America, the private sector that addresses efficiency is defined as the best mode of running the higher education market. Therefore, this mode functions as the gateway of achieving this political mission. However, this approach may jeopardize state sovereignty because if the state is unable to balance the relation between capital accumulation and social justice, it cannot win people’s trust. The interactive principle between social cultures and education policies also rejects the universal practicality of free market logic. In order to overcome these challenges, individual countries may adopt transformative strategies, allowing them to improve the international reputation of their own top universities. This essay sets out to shed some light on this issue through examining the case of the Double-First-Class-Universities initiative in China.
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"The ordered probit model." In Applied Econometrics for Health Economists, 30–33. CRC Press, 2007. http://dx.doi.org/10.1201/9781785230141-10.

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ASCIUTO, A., and F. FIANDACA. "AN ORDERED PROBIT MODEL FOR THE ANALYSIS OF OVERALL CUSTOMER SATISFACTION (OCS) REGARDING ORGANIC-FOOD COMSUMPTION." In Series on Computers and Operations Research, 321–36. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812796622_0020.

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Conference papers on the topic "Ordered Probit Model"

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Liu, Xiaobo, Mei Chen, and Erin Bachman. "Analyze Bus Delay Severity Using Ordered Probit Model." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)516.

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Li, Ruimin, Xiaoqiang Zhao, Xinxin Yu, Jianan Zhu, Junwei Li, and Nan Cheng. "Incident duration model on urban freeways using Ordered Probit Model." In 2010 International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2010. http://dx.doi.org/10.1109/icicip.2010.5564235.

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Çağlayan Akay, Ebru, and Zamira Oskonbaeva. "An Application of Panel Ordered Probit Model to Credit Scoring." In International Conference on Eurasian Economies. Eurasian Economists Association, 2018. http://dx.doi.org/10.36880/c10.02052.

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Ratings are important in attracting foreign capital so they play a great role in the financial system of a country. The aim of the study is to investigate the impact of macroeconomic indicators on sovereign credit ratings assigned by Fitch. For this aim Panel ordered probit model was applied to the annual data from 2000 to 2011. The analysis rests on panel of 44 countries. According to the results obtained it can be concluded that gross domestic product growth rate , per capita gross domestic product, unemployment, export, default history and the level of economic development significantly affect ratings.
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Cao, Yong, Guotai Chi, and Yanqiu Cheng. "Forecasting jump size of interest rate with ordered Probit model." In 2011 International Conference on E-Business and E-Government (ICEE). IEEE, 2011. http://dx.doi.org/10.1109/icebeg.2011.5881522.

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Magueta, Daniel, Cláudia Veloso, Sónia Estrela, and Maria Felício. "IMPORTANCE OF INTERNSHIPS IN BUSINESS HIGHER EDUCATION: AN ORDERED PROBIT MODEL APPROACH." In 12th International Conference on Education and New Learning Technologies. IATED, 2020. http://dx.doi.org/10.21125/edulearn.2020.1304.

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Qian Fu, Zhibin Li, Mengjia Yao, and Xiang Zhang. "Exploring factors influencing crash injury severity on freeways using ordered probit model." In 2011 International Conference on Transportation and Mechanical & Electrical Engineering (TMEE). IEEE, 2011. http://dx.doi.org/10.1109/tmee.2011.6199277.

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Jeong, Hyung Seok, Hyeon-Shik Baik, and Dulcy M. Abraham. "An Ordered Probit Model Approach for Developing Markov Chain Based Deterioration Model for Wastewater Infrastructure Systems." In Pipeline Division Specialty Conference 2005. Reston, VA: American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40800(180)52.

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Xiao, Daiquan, Xiaofei Jin, Xuecai Xu, and Shengyang Kang. "Determinants of Crash Fatalities in Urban Area: A Bayesian Ordered Probit with Sample Selection Model." In 20th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2020. http://dx.doi.org/10.1061/9780784482933.237.

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Sakaguchi, Junki, Hajime Miyauchi, and Tetsuya Misawa. "Risk assessment of power plant investment by three level ordered probit model considering project suspension." In 2013 IREP Symposium - Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid (IREP). IEEE, 2013. http://dx.doi.org/10.1109/irep.2013.6629398.

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Forciniti, Carmen, Juan De Oña, Rocio De Oña, Laura Eboli, and Gabriella Mazzulla. "An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3199.

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Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3199
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Reports on the topic "Ordered Probit Model"

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Mohammadian, Abolfazl, Ehsan Rahimi, Mohammadjavad Javadinasr, Ali Shamshiripour, Amir Davatgari, Afshin Allahyari, and Talon Brown. Analyzing the Impacts of a Successful Diffusion of Shared E-Scooters and Other Micromobility Devices and Efficient Management Strategies for Successful Operations in Illinois. Illinois Center for Transportation, May 2022. http://dx.doi.org/10.36501/0197-9191/22-006.

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Active transportation can play an important role in promoting more physically active and positive public health outcomes. While walking and biking provide significant physical health benefits, their modal share remains low. As a new form of micromobility service, shared e-scooters can enhance the suite of options available in cities to promote active transportation and fill in the gaps when walking or biking are not preferred. Although e-scooters show potential as a mode of transportation, it is unclear whether people will adopt the technology for everyday use. Furthermore, shared micromobility (e.g., electric scooters) is gaining attention as a complementary mode to public transit and is expected to offer a solution to access/egress for public transit. However, few studies have analyzed integrated usage of shared e-scooters and public transit systems while using panel data to measure spatial and temporal characteristics. This study aims to examine the adoption and frequency of shared e-scooter usage and provide policy implementation. To do so, the researchers launched a survey in the Chicago region in late 2020 and collected a rich data set that includes residents’ sociodemographic details and frequency of shared e-scooter use. To characterize the frequency, the researchers used an ordered probit structure. The findings show that respondents who are male, low income, Millennials and Generation Z, or do not have a vehicle are associated with a higher frequency of shared e-scooter use. Furthermore, this study utilizes shared e-scooter trips for a 35-day measurement period from 10 shared e-scooter operators in Chicago, where the researchers used a random-parameter negative binomial modeling approach to analyze panel effects. The findings highlight the critical role of spatial and temporal characteristics in the integration of shared e-scooters with transit.
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Finkelstain, Israel, Steven Buccola, and Ziv Bar-Shira. Pooling and Pricing Schemes for Marketing Agricultural Products. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568099.bard.

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In recent years there has been a growing concern over the performance of Israel and U.S. agricultural marketing organizations. In Israel, poor performance of some marketing institutions has led to radical reforms. Examples are the two leading export industries - citrus and flowers. In the U.S., growth of local market power is eliminating competitive row product prices which served as the basis for farmer cooperative payment plans. This research studies, theoretically, several aspects of the above problem and develops empirical methods to assess their relative importance. The theoretical part deals with two related aspects of the operation of processing and marketing firms. The first is the technological structure of these firms. To this end, we formalize a detailed theory that describes the production process itself and the firm's decision. The model accounts for multiple products and product characteristics. The usefulness of the theory for measurement of productivity and pricing of raw material is demonstrated. The second aspect of the processing and marketing firm that we study is unique to the agricultural sector, where many such firms are cooperatives. In such cooperative an efficient and fair mechanism for purchasing raw materials from members is crucial to successful performances of the firm. We focus on: 1) pricing of raw materials. 2) comparison of employment of quota and price regimes by the cooperative to regulate the quantities, supplied by members. We take into consideration that the cooperative management is subject to pressure from member farmers. 3) Tier pricing for raw materials in order to ensure efficiency and zero profits at the cooperative level. This problem is examined in both closed and open cooperatives. The empirical part focuses in: 1) the development of methodologies for estimating demand for differentiated products; 2) assessing farmers response to component pricing; 3) measurement of potential and actual exploitation of market power by an agricultural marketing firm. The usefulness of the developed methodologies are demonstrated by several application to agricultural sub-sectors, including: U.S. dairy industry, Oregon wine industry, Israeli Cotton industry and Israeli Citrus industry.
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Friedman, Shmuel, Jon Wraith, and Dani Or. Geometrical Considerations and Interfacial Processes Affecting Electromagnetic Measurement of Soil Water Content by TDR and Remote Sensing Methods. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580679.bard.

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Time Domain Reflectometry (TDR) and other in-situ and remote sensing dielectric methods for determining the soil water content had become standard in both research and practice in the last two decades. Limitations of existing dielectric methods in some soils, and introduction of new agricultural measurement devices or approaches based on soil dielectric properties mandate improved understanding of the relationship between the measured effective permittivity (dielectric constant) and the soil water content. Mounting evidence indicates that consideration must be given not only to the volume fractions of soil constituents, as most mixing models assume, but also to soil attributes and ambient temperature in order to reduce errors in interpreting measured effective permittivities. The major objective of the present research project was to investigate the effects of the soil geometrical attributes and interfacial processes (bound water) on the effective permittivity of the soil, and to develop a theoretical frame for improved, soil-specific effective permittivity- water content calibration curves, which are based on easily attainable soil properties. After initializing the experimental investigation of the effective permittivity - water content relationship, we realized that the first step for water content determination by the Time Domain Reflectometry (TDR) method, namely, the TDR measurement of the soil effective permittivity still requires standardization and improvement, and we also made more efforts than originally planned towards this objective. The findings of the BARD project, related to these two consequential steps involved in TDR measurement of the soil water content, are expected to improve the accuracy of soil water content determination by existing in-situ and remote sensing dielectric methods and to help evaluate new water content sensors based on soil electrical properties. A more precise water content determination is expected to result in reduced irrigation levels, a matter which is beneficial first to American and Israeli farmers, and also to hydrologists and environmentalists dealing with production and assessment of contamination hazards of this progressively more precious natural resource. The improved understanding of the way the soil geometrical attributes affect its effective permittivity is expected to contribute to our understanding and predicting capability of other, related soil transport properties such as electrical and thermal conductivity, and diffusion coefficients of solutes and gas molecules. In addition, to the originally planned research activities we also investigated other related problems and made many contributions of short and longer terms benefits. These efforts include: Developing a method and a special TDR probe for using TDR systems to determine also the soil's matric potential; Developing a methodology for utilizing the thermodielectric effect, namely, the variation of the soil's effective permittivity with temperature, to evaluate its specific surface area; Developing a simple method for characterizing particle shape by measuring the repose angle of a granular material avalanching in water; Measurements and characterization of the pore scale, saturation degree - dependent anisotropy factor for electrical and hydraulic conductivities; Studying the dielectric properties of cereal grains towards improved determination of their water content. A reliable evaluation of the soil textural attributes (e.g. the specific surface area mentioned above) and its water content is essential for intensive irrigation and fertilization processes and within extensive precision agriculture management. The findings of the present research project are expected to improve the determination of cereal grain water content by on-line dielectric methods. A precise evaluation of grain water content is essential for pricing and evaluation of drying-before-storage requirements, issues involving energy savings and commercial aspects of major economic importance to the American agriculture. The results and methodologies developed within the above mentioned side studies are expected to be beneficial to also other industrial and environmental practices requiring the water content determination and characterization of granular materials.
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