Stochastic Frontier Regression Research Articles

Optimal carrying capacity in rural tourism: Crowding, quality deterioration, and productive inefficiency

This paper introduces a novel framework for characterizing destination overcrowding in rural tourism using a production approach. We build upon destination life cycle, carrying capacity, and consumer preference theories to characterize optimal levels of overnight stays in the presence of disutility from crowding. Using panel data for rural tourism in Spanish provinces, we model crowding non-linearly as a demand shifter within a service production function. To deal with plausible endogeneity, we use a control function approach within a Stochastic Frontier regression. Consistent with our theoretical predictions, we show there is a non-linear concave relationship between overnight stays and crowding. We calculate optimal carrying capacity levels (turning points) for each province and illustrate which regions are exhibiting negative externalities from overcrowding.

Technical Efficiency of Broiler Production in Delta State, Nigeria

Purpose: The study examined the technical efficiency of broiler production in Delta State, Nigeria. Specifically, it determined the effects of socio-economic characteristics of the farmers on production output, determined the profitability of broiler production, and established the levels of technical efficiency attained by the farmers. It also ascertain the socio-economic factors of the farmers that influence their technical efficiency levels; assessed the nature of returns to scale and elasticities of broiler production inputs; and identified the constraints to broiler production in the area. A survey research design approach was used in the study. Multistage random sampling technique was used to select 240 registered broiler farmers. Primary data were collected in the 2019 production season using structured questionnaire administered to the respondents by personal interview. Methodology: Descriptive and parametric statistics such as frequencies, means, percentages, ratios, enterprise budgeting, profit function regression and Cobb-Douglas stochastic frontier regression techniques were used in data analysis. Findings: Findings indicated that broiler production output was significantly influenced by age, household size, farm size, farming experience and cost of feeds while gender, marital status, educational level, access to credit and extension visits were not significant. Mean technical efficiency scores of 0.94 was attained with 0.97 maximum and 0.90 minimum. Output elasticities with respect to farm size, labour, capital and feeds were 0.42, 0.13, 0.13 and 0.17 respectively. Technical efficiency of the farmers was significantly influenced by educational level, farming experience, household size, gender and access to credit, but weakly determined by age. Broiler farms operated at decreasing returns to scale. Major constraints to broiler production in the area arranged in descending order of seriousness were high cost of feeds, inadequate capital, high cost of labour, parasites and diseases, high mortality rate and inadequate feeds. Unique contributor to theory, policy and practice: Policy measures such as increased budgetary allocation to livestock production, subsidization of inputs, provision of soft loans to broiler farmers by relevant institutions, provision of requisite infrastructures and improved funding of extension agencies to enhance information dissemination to broiler farmers are advocated.

PROFITABILITY AND CONSTRAINTS OF PERI-URBAN VEGETABLE PRODUCTION IN KADUNA STATE, NIGERIA

In human nutrition, vegetables are an essential protective food containing vitamins and minerals, any balanced diet should include vegetables and fruits for this reason. The study assesses profitability and constraints of peri-urban vegetable production in Kaduna State, Nigeria. Primary data collected with the aid of structured questionnaire were used for this study through farm survey in 2018. A multistage sampling procedure was used in selecting 217 vegetable farmers for this study. Descriptive statistics, net farm income (NFI) and stochastic profit frontier regression model were used to analyze the data. It was revealed that tomatoes production has the highest profit of N145,580.7 compared with that of cucumber N112,992.7 and cabbage N78,450.3, respectively. The result showed that the estimated coefficients of (-0.342), agrochemical (-0216), fuel (0.906) and fixed cost (0.233) were statistically significant. The coefficient of fertilizer implies that a 1% increase in fertilizer cost will decrease the profit made from vegetable enterprise by -0.342 units. Furthermore, the estimated coefficient of fuel cost will increase the profit made from vegetable enter by (0.906) units. The results of inefficiency model showed that the coefficient for age (0.024) was positive and statistically significant at 1% level of probability which implies that younger vegetable farmers are more profit efficient than the older ones. Conversely, the coefficient of household size (-0.027) was negative and statistically significant at 1% level of probability implying that farmers who have large household sizes are more profit efficient than those with few. Unstable market price, high cost of labour and incidence of pest and disease were the most critical constraints faced by vegetable farmers in the study area. It is recommended that; agribusiness industries and non-governmental organization should encourage and support the vegetable famers through provision of farm inputs at a subsidies rate.

Effect of Branch Expansion on Cost Efficiency of Ethiopian Commercial BANKS. (Stochastic Cost frontier Approach)

Banks are a vital parts of a nation’s economy that catalyzed Economic growth through facilitate spending and investment in the economy.Bank institutionis one and the top from the major financial institutions in Ethiopia.The number of all branches of the industry including public banks increased from year to year aggressively.Thus, the overall objective of this study was to investigate effect of branch expansion on cot efficiency Ethiopian commercial banks.Accordingly, from the population, Commercial banks operating in the country a total of 18, among these, 2 public and 16 private commercial banks (a total of 14 commercial banks) were included in the study period 2010/11-2018/19 based on non-probability, purposefully sampling method. The research used theprice of labor, prices of capital,Number of branches, annual inflation rate, real GDP growth, Total loan output, management performances, market share, capital adequacy ratio,liquidity risk, prices of deposit and total securities variables to measure cost efficiency. To this end, the study used secondary data from the NBE, balance sheets and income statements of individual commercial banks obtained from the period from to 2010/11 to 2018/9. Then nine years’ panel data of bank levelvariables has been collected and analyzed using stochastic cost frontier regression analysis. As a resultthe researcher concluded that stochastic frontier model as appropriate to represent inefficient operation among the commercial banks of Ethiopia .The Ethiopian commercial banks expanded their branches throughout the country’s territory; most of the bank branches were opened.Despite the various challenges, banks preferred to go ahead with its plan to open more branches to reach customers. However their cost efficiency had been decreased as of aggressively opened branches in the study years.Accordingly the analysis result Zemen bank was the most cost efficiency and become the best practiced bank and CBE the most inefficiency bank and in reverses also characterizes in branch expansion profile.The researcher recommended thatEthiopianbanking institutions should continue to innovate so as to reduce their cost inefficiencies. Moreover, NBE and government stand towards policy that forbids foreign banks entry, the Reserve required ratio amount, and competition environment and policy in opening branches must revised. Keywords: Branch expansion, cost efficiency, Ethiopian commercial banks DOI: 10.7176/RJFA/12-9-04 Publication date: May 31 st 2021

Reineke based guide to manage density in Pinus montezumae stands in Puebla, Mexico

Objective: Generate a density management guide (DMG) based on the Reineke density index for even-aged stands of Pinus montezumae in Puebla, Mexico. Methodology: Dasometric information from 90 sampling sites of the Forest Management Unit 2103 of the state of Puebla was processed. Each site was 1,000 m2, circularly, coming from natural stands in high density and competition; all growth conditions and age range were covered. The variables density per hectare (N) and quadratic diameter (Dq) were used to adjust the Reineke density-size model. The technique of linear ordinary least squares (OLS) was compared against that of stochastic frontier regression (SFR); the quality of the adjustments was assessed using statistical and graphic criteria. The self-thinning line was determined and a DMG was constructed defining four zones of Langsaeter growth. Contribution: The SFR technique in its semi-normal mode better defined the limit of the maximum boundary of the observed data. DMG is useful for prescribing thinnings as intermediate silvicultural treatments for stands of the species. The maximum density index for a reference Dq of 25 cm was 886 trees ha-1.

A stochastic frontier regression model with dynamic frontier

We consider a stochastic frontier regression model with a time dependent efficiency process, which is assumed to follow an exponential autoregressive sequence. The likelihood for the model is derived in the context of a bivariate exponential distribution. Bayesian method is suggested for the estimation of parameters. We apply the model and the estimation procedure to a panel of US airlines data and show empirically that the model is dynamic in the sense that it reveals improvement in the efficiency or reduction in the inefficiency over time.

Determinants of Technical Efficiency in Wheat Production in Ethiopia

Ethiopia is the second largest wheat producing countries in Sub-Saharan Africa and most people rely on rain fed agriculture for their livelihoods. Wheat production has increased from 2,176,603 tons in 2005 to 4,219,257 tons in 2016 with 51.6% production volume increment. However, this production cannot meet the consumption demand and obliged to import wheat because of rapid population growth. This study intended to determine the technical efficiency of smallholder wheat farmers in Ethiopia. The main objective of study was to examine the effect of demographic, socioeconomic and institutional factors on technical efficiency of small holder wheat farmers in Ethiopia. The study used household level cross sectional data collected in 2015/16 cropping season from 1611 sample farmers selected by multistage sampling technique. A stochastic production frontier and two-limit Tobit regression models were used to estimate level of technical efficiency and identify factors affecting technical efficiency respectively. The study indicated that the average technical efficiency level of wheat producing farmers was 62% implying that there was technical efficiency variation among smallholder farmers in the study area. The result implied that there is an opportunity for wheat producers to increase output at existing levels of inputs with present technologies. By shifting the average farmer to the production frontier, the average yield would increase by 0.5 tons per hectare. The two-limit Tobit regression model results showed that experience of growing wheat, family size, own farm labor, livestock size, extension contact and training had positive and significant effect on technical efficiency. However, distant wheat plot have a negative and significance effect on technical efficiency level of the farmers. This suggests attention to productivity gains arising from efficient use of existing technologies is necessary. Therefore, the study suggested, policies and strategies should be directed towards increasing productivity through improving efficiency of the production process.

Technical Efficiency of Yam Commodity in Semarang Regency

Semarang Regency has the largest area of ​​yam harvest in Central Java. Although the area of ​​yam harvest in Semarang Regency is much more than other districts including Karanganyar Regency, the production and productivity level of yam in Semarang Regency are lower compared to Karanganyar Regency. The tendency of increasing yam harvest area in Semarang Regency was not followed by an increase in production. This study aims to analyze the efficiency of yam farming in Semarang Regency. The sample is 97 farmers with the data analysis technique is stochastic frontier regression. Based on the results, an average efficiency is 0.75. It implies that yam farmers have not been able to combine the use of land area, seeds, urea, SP-36 and phonska. The results of price efficiency is 19.233. The results of these calculations indicate that the use of production factors in yam has not efficiency. Farmers can optimize the use of production factors by adding production factors. The level of economic efficiency is 14.433, it indicate that the use of production factors has not been efficient based on economic aspects, because the calculation results is more than 1.

Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis

This study analyzes the electric and fuel energy efficiency for five different metal-based durable manufacturing industries in the United States over the time period 1987–2012, at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days HDD and cooling degree days CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. Own energy price elasticities range from −0.7 to −1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100% = best practice level) range from a low of 33% (fuel, NAICS 334 - Computer and Electronic Products) to 86% (electricity, NAICS 332 - Fabricated Metal Products). Electric efficiency is consistently better than fuel efficiency for all NAICS. Assuming that all plants in the least efficient quartile of the efficiency distribution achieve a median level of performance, we compute the decline in total energy use to be 21%. A Malmquist index is used to decompose the aggregate change in energy performance into indices of efficiency and frontier (best practice) change. Modest improvements in aggregate energy performance are mostly change in best practice, but failure to keep up with the frontier retards aggregate improvement. Given that the best practice frontier has shifted, we also find that firms entering the industry are statistically more efficient, i.e. closer to the frontier; about 0.6% for electricity and 1.7% for fuels on average.

Diagrama para manejo de la densidad en rodales de Pinus patula Schiede ex Schltdl. & Cham. en Puebla, México

Un diagrama para el manejo de la densidad (DMD) es una herramienta técnica para aplicar silvicultura cuantitativa, la que contribuye a mejorar el manejo técnico de los bosques. El objetivo fue generar un diagrama para manejar la densidad con base en el índice de densidad de rodal de Reineke en bosques coetáneos de Pinus patula en Puebla, México. Se procesó una muestra compuesta por 252 sitios de muestreo para inventario seleccionados en condiciones de máxima densidad, que cubrió todas las condiciones de crecimiento y del intervalo de edades. La información de densidad y diámetro cuadrático se procesó mediante regresión estadística ajustando la relación funcional tamaño-densidad de Reineke. Se comparó la técnica de mínimos cuadrados ordinarios contra la de regresión frontera estocástica en sus modalidades de modelo semi-normal, normal truncado y normal exponencial. Una evaluación de la calidad de ajuste estadístico y gráfico evidenció que la técnica de regresión frontera estocástica en su modalidad semi-normal fue superior, por lo que se seleccionó para determinar la línea de autoaclareo. El índice de densidad máximo fue de 1 078 árboles ha-1 para un Dq de referencia de 20 cm. El DMD se generó con la definición de las diferentes zonas de crecimiento de Langsaeter. El DMD es útil para gestionar y prescribir la intensidad de aclareos como tratamientos silvícolas intermedios, en términos del número de árboles en una hectárea por remover y su equivalente en área basal por hectárea para rodales coetáneos.

Profitability of Investment and Farm Level Efficiency Among Groups of Vitamin A Cassava Farmers in Oyo State Nigeria

Biofortified (vitamin A) cassava was developed through convectional breeding similar to most other improved varieties cultivated by Nigeria farmers. Despite its potential in addressing the increasing food demand and malnutrition in the country, lack of empirical knowledge about its yield and return on investment has been a major barrier to the uptake of this technology among farmers in Nigeria. This study examined the socio-economic characteristics of vitamin A cassava farmers; analyzed farm level efficiency and return on investment from vitamin A cassava in the study area; determined the factors affecting farm level efficiency and productivity, and examined the constraint to productivity and profitability among vitamin A cassava farmers. A multistage random sampling was used to select a total of 100 vitamin A cassava farmers in the study area. The data collected were analyzed using descriptive statistics, stochastic frontier production function (SFPF), profitability ratio and regression analysis. The results indicated that investing in vitamin A cassava as a business was very profitable. The result showed that 82% of the respondents were male, the mean age of the farmers was 53.25, 49% had only primary school certificate education, 66% farmed on the land between 1-2 hectares. The result further showed that on the average, total revenue was N261511.90, the total variable cost was N87754, gross margin was N173757.9, total cost was N179828.8, and net income was N81683.05. Mean technical efficiency was 78.73%. The study concluded that vitamin A cassava production in the study area was efficient and profitable. These results have implications for the design of effective advocacy strategies to attract more farmers into vitamin A cassava production in Nigeria.

Site sensitive maximum stand density index models for mixed conifer stands across the Inland Northwest, USA

Density management is a key silvicultural tool for developing management prescriptions that maintain and enhance forest health and productivity, particularly in droughty, fire-prone ecosystems of the Inland Northwest, USA. Within this context, understanding the role of species mixing, climate, topography, and soil properties on maximum stand density is critical for predicting forest stand response to management given a suite of site characteristics and species composition. We assembled a dataset from public and private land management organizations that allowed us to test the role of ecological variables on modifying maximum stand density frontiers. Maximum stand density frontier models were built for selected conifer species using stochastic frontier regression. The influence of species mixing was assessed by including as a covariate basal area proportion of the three conifer species of interest in this study: Pinus ponderosa var. ponderosa, Pseudotsuga menziesii var. glauca, and Abies grandis var. idahoensis. A single, parsimonious model was found to fit each species, with variable coefficients reflecting species adaptation to varying abiotic site factors across the region. Site factors that increased maximum density included cool, moist conditions, soils containing volcanic ash over coarse-textured bedrock, and high tree-species diversity. These observations correspond to regional silvicultural guidance, thereby providing both a site-sensitive, quantitative maximum density measure for mixed species stands, and a tool for evaluating the effect of climate scenarios on future stand carrying capacity.

Autoaclareo y manejo de la densidad en rodales coetáneos de Pinus patula Schiede ex Schlechtdl. & Cham.

La comunidad de Ixtlán de Juárez, Oaxaca, posee un potencial maderable importante debido a la productividad alta de su bosque. Una de las especies con mayor importancia es Pinus patula debido a la distribución y valor comercial alto; además, es de crecimiento rápido. Por lo tanto, es necesario determinar los límites de la densidad máxima posible que los rodales pueden sustentar para dirigir acciones encaminadas al control de la competencia y redistribución del espacio de crecimiento. En este estudio se estimó la línea de densidad máxima (límite superior del autoaclareo) con el modelo de Reineke mediante dos enfoques de estimación de los parámetros: (1) mínimos cuadrados ordinarios (MCO) y (2) regresión de frontera estocástica (RFE) con los modelos de tipo seminormal (half-normal) y normal truncado (truncated-normal). Para el ajuste del modelo se utilizaron datos de 64 parcelas permanentes de investigación silvícola de 400 m2 de rodales puros y coetáneos de P. patula. La estimación del límite superior del autoaclareo con el modelo de RFE en la forma seminormal fue eficiente y permitió conocer el índice de densidad máxima de los rodales estudiados. La línea de densidad máxima representó el insumo primordial para construir una guía de densidad; herramienta indispensable para la definición de regímenes de aclareo y optimización del espacio de crecimiento.

Identifying Sales Performance Gaps with Internal Benchmarking

This research investigates how retailers can benefit from identifying the sales growth potential of in-store salespeople in every product category. The proposed novel approach helps retailers develop an equitable evaluation of their sales force, using both observable and unobservable factors that affect sales. By extending stochastic frontier regression to a multivariate case, the resulting factor-analytic frontier formulation leverages the correlation pattern of sales across product categories and salespeople over time. A unique data set, from a franchise chain with 481 salespeople, operating in 35 stores and selling 11 related product categories, identifies a gap between observed category profits and an estimated profit frontier for each salesperson and category. This novel model also can benchmark each salesperson against all others across product categories while accounting for observable and unobservable factors. This approach has practical value, in that retailers can identify both top-performing salespeople and underperformers, who then might be matched to establish a positive learning environment that aligns top performers with proven sales expertise in a product category with peers who struggle with that category.

Analysis of Productive Resources of Maize Crop Among Farming Households in Ekiti State, Nigeria

This study examined productive resources of maize crop among farming households in Ekiti State, Nigeria. The study used multistage sampling techniques. Data were collected from 120 maize farmers through well-structured questionnaires from three Local Government Areas of Ekiti State. The collected data were analyzed by using descriptive statistics, and stochastic frontier regression model. Results from descriptive analysis showed that 30 percent of the maize farmers had secondary school education and above. Majority of the respondents (66.70%) had between 5 and 8 members that made up the household in the study area. It was revealed through the study that the majority of the respondents produced on a fairly large scale with average maize farm size of 3.39 hectares. Also, 80.0% of the maize farmers in the study area had more than 15 years farming experience. With profit of ₦116,590 per hectare and percentage profit of 58.63%, the venture is considered to be highly profitable. Farmers who invested ₦1 realized revenue of ₦1.59. The level of technical efficiency in maize production in Ekiti State ranged from 29.8% to 96.5% with a mean of 64.3%. This means that there are substantial opportunities to increase productivity and income through more efficient utilization of productive resources The RTS parameter (0.931) was obtained from the summation of the coefficients of the estimated inputs (elasticities) which indicates that maize production in the study area was in the Stage II of the production surface. Depreciation, hired labour, family labour, farm size and quantity of seed are the major farm specific variables that influence efficiency of the maize farmers while farming experience, extension access, land acquisition and access to credit contributed to technical inefficiency. It is therefore suggested that effort should be geared towards increasing the technical manpower of farmers, land redistribution policy that will increase the farm size of farmers in order to boost maize production should be encouraged; and in order to increase farmers’ profit, variable costs have to be cut down, since the bulk of the variable cost is incurred on labour, which would lead to greater gross margins and hence the profitability of the enterprise.

Environmental Efficiency Analysis with one Detrimental Input Variable through A Stochastic Frontier Analysis Approach (A Case Study of Shallot Farming System)

Sustainable agriculture having high complexity, especially related to the choice of using inputs that could potentially harm the environment or often called a detrimental input. In order to realize sustainable agriculture, the level of efficiency of the use of these inputs must be able to measure, especially from the aspect of environmental efficiency. The objective of this research in to analyze the environmental efficiency (EEnv) with a detrimental input variable namely the Nitrogen surplus in shallot farming through approach Stochastic Frontier Analysis (SFA). At the initial stage has been built translog stochastic frontier regression model consisting of the response variable namely the production of onion, five independent variables, namely land, seed, Phospor fertilizer, Kalium fertilizer, labor and pesticides, as well as one independent variable is a surplus of nitrogen as a detrimental input. Stochastic frontier translog regression models were built to explain some of the interactions between several independent variables affect the production of shallot. Some interactions are significant, namely seeds and pesticides, fertilizer P with a surplus of nitrogen, and the interaction between K fertilizer with nitrogen surplus. From the regression model can also be calculated value of elasticity, where the elasticity of independent variables namely seed is the highest, equal to 0.1687. Furthermore stochastic frontier translog model can be calculated value EEnv, the results show the value of EEnv still low at only at 0.2765. This may imply inefficient shallot farmers from the aspects of the environment, especially if associated with the use of nitrogen fertilizer. Although technically shallot farmers have achieved a level of technical efficiency (ET), which is indicated on the ET value of 0.9475.

Measuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis

This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.

Efficiency of Ontario primary care physicians across payment models: a stochastic frontier analysis.

ObjectiveThe study examines the relationship between the primary care model that a physician belongs to and the efficiency of the primary care physician in Ontario, Canada.MethodsSurvey data were collected from 183 self-selected physicians and linked to administrative databases to capture the provision of services to the patients served for the 12 month period ending June 30, 2013, and the characteristics of the patients at the beginning of the study period. Two stochastic frontier regression models were used to estimate efficiency scores and parameters for two separate outputs: the number of distinct patients seen and the number of visits.ResultsBecause of missing data, only 165 physicians were included in the analyses. The average efficiency was 0.72 for both outputs with scores varying from 4 % to 93 % for the visits and 5 % to 94 % for the number of patients seen. We observed that there were both very low and very high efficiency scores within each model. These variations were larger than variations in average scores across models.

Stochastic frontier estimation of budgets for Kuhn–Tucker demand systems: Application to activity time-use analysis

We propose a stochastic frontier approach to estimate budgets for the multiple discrete–continuous extreme value (MDCEV) model. The approach is useful when the underlying time and/or money budgets driving a choice situation are unobserved, but the expenditures on the choice alternatives of interest are observed. Several MDCEV applications hitherto used the observed total expenditure on the choice alternatives as the budget to model expenditure allocation among choice alternatives. This does not allow for increases or decreases in the total expenditure due to changes in choice alternative-specific attributes, but only allows a reallocation of the observed total expenditure among different alternatives. The stochastic frontier approach helps address this issue by invoking the notion that consumers operate under latent budgets that can be conceived (and modeled) as the maximum possible expenditure they are willing to incur. The proposed method is applied to analyze the daily out-of-home activity participation and time-use patterns in a survey sample of non-working adults in Florida. First, a stochastic frontier regression is performed on the observed out-of-home activity time expenditure (OH-ATE) to estimate the unobserved out-of-home activity time frontier (OH-ATF). The estimated frontier is interpreted as a subjective limit or maximum possible time individuals can allocate to out-of-home activities and used as the time budget governing out-of-home time-use choices in an MDCEV model. The efficacy of this approach is compared with other approaches for estimating time budgets for the MDCEV model, including: (a) a log-linear regression on the total observed expenditure for out-of-home activities and (b) arbitrarily assumed, constant time budgets for all individuals in the sample. A comparison of predictive accuracy in time-use patterns suggests that the stochastic frontier and log-linear regression approaches perform better than arbitrary assumptions on time budgets. Between the stochastic frontier and log-linear regression approaches, the former results in slightly better predictions of activity participation rates while the latter results in slightly better predictions of activity durations. A comparison of policy simulations demonstrates that the stochastic frontier approach allows for the total out-of-home activity time expenditure to either expand or shrink due to changes in alternative-specific attributes. The log-linear regression approach allows for changes in total time expenditure due to changes in decision-maker attributes, but not due to changes in alternative-specific attributes.

Estimation of Annual Mileage Budgets for a Multiple Discrete-Continuous Choice Model of Household Vehicle Ownership and Utilization

This paper presents an empirical comparison of the following approaches to estimate annual mileage budgets for multiple discrete-continuous extreme value (MDCEV) models of household vehicle ownership and utilization: (a) a log-linear regression approach to model observed total annual household vehicle miles traveled (AH-VMT), (b) a stochastic frontier regression approach to model latent annual vehicle mileage frontier, and (c) other approaches used in the literature to assume annual household vehicle mileage budgets. For the stochastic regression approach, MDCEV and multiple discrete-continuous heteroscedastic extreme value (MDCHEV) models were estimated and examined. When model predictions were compared with observed distributions of vehicle ownership and utilization in a validation data sample, the log-linear regression approach performed better than other approaches. However, policy simulations demonstrate that the log-linear regression approach does not allow for AH-VMT to increase or decrease as a result of changes in vehicle-specific attributes, such as changes in fuel economy. The stochastic frontier approach overcomes that limitation. Policy simulation results with the stochastic frontier approach suggest that increasing the fuel economy of a category of vehicles increases the ownership and use of those vehicles. But this does not necessarily translate into an equal decrease in the use of other household vehicles, confirming previous findings in the literature that improvements in fuel economy tend to induce additional travel. In view of policy responsiveness and prediction accuracy, using the stochastic frontier regression (for estimating mileage budgets) in conjunction with the MDCHEV model for discrete-continuous choice analysis of household vehicle ownership and utilization is recommended.