Demand Analysis

In this paper it will be argued that Albert O. Hirschman's research work is a remarkable instance of a methodological shift that began in the Fifties, and of which there seems to be scarce awareness nowadays notwithstanding its relevance for some of the issues that are in the agenda of contemporary economics. In his work -so as in the work of other economists of his generation -systems theory was used as a general methodology to frame the study of structural change in the economy. The methodological questions raised by the study of 'economic evolution', extensively discussed nowadays, were very much in evidence in economics already in the Fifties in the theory of economic development. Contrary to what it often said, attempts to build a theoretical interpretation of economic change were in fact conducted within this research programme. Indeed, the focus of Hirschman's research activity has been on the explanation of the relationship between the evolution of the social system and the economic process, and systems theory has been the methodological perspective he has relied upon in the study of this relationship. He was certainly not alone while walking along this pathway. Yet, more than other contemporary economists, Hirschman addressed, although with some elusiveness, a fundamental issue in the study of economic evolution, and namely the micro-foundation of economic change. Most of his research ought to be properly understood as an attempt to put forward micro-founded (meta-)theory of economic evolution. To discuss the whole corpus of Hirschman's research work would be a too demanding task. The aim of this paper is in fact more modest. It intends to call attention to the methodology that Hirschman elaborated to address the issue of explaining 'economic evolution' -and to interpret it as a response to a class of why-questions that have constantly been prominent in the agenda of economists in the last decades.

This digital transformation of manufacturing processes presents unique challenges in adapting proven retail forecasting methodologies to industrial settings. This paper introduces a novel cloud-native framework that bridges the gap between retail and manufacturing demand forecasting, leveraging advanced data analytics and scalable architecture. We present (1) an adaptive methodology for translating retail demand patterns to manufacturing contexts, (2) a cloud-native architecture supporting real-time data integration and scalable processing, and (3) empirical validation using public retail and manufacturing datasets. Our framework demonstrates significant improvements in forecast accuracy (15.0% reduction in Mean Absolute Percentage Error) and resource utilization (40% reduction in computing costs). Analysis across 50 manufacturing facilities shows that our retail-derived demand forecasting techniques effectively optimize manufacturing processes while maintaining 99.999% system availability. The framework achieves a 25% reduction in safety stock levels and 35% improvement in inventory turnover, providing practical insights for organizations pursuing digital transformation initiatives in manufacturing.

This study examined the effect of Agriprenuership on consumer demand for yam value-added products. Specifically, it determined the effect of product quality enhancement, grading innovation, and supply chain efficiency on price sensitivity, purchase intentions, and brand loyalty for yam value added products respectively. Using a survey research design, the study's population comprised 2313 consumers involved in the yam product market within Oredo, Ikpoba Okha, and Egor Local Government Area (LGA) of Edo State, Nigeria. A representative sample size of 341 was determined by applying the Yamane formula. The primary source of data was the questionnaire and it was administered online. The responses generated were analysed using both descriptive and inferential statistics through the SPSS version 25. The findings were that significant relationships existed among the agriprenuerial practices, namely product quality enhancement, grading innovation, and supply chain efficiency and consumer demand (such as price sensitivity, purchase intentions, and brand loyalty) for yam value added products. The study therefore recommended that Agripreneurs should prioritise continuous improvement, invest in creative and visually appealing packaging designs, focus on improving their supply chain processes by optimising logistics and reducing delivery times, and adopt a comprehensive marketing strategy that combines product quality, effective branding, and efficient distribution

This paper jointly examines the length between successive participations in several activity purposes using a 1999 multi-week travel survey conducted in the German cities of Halle and Karlsruhe. A multivariate hazard model that accommodates a flexible duration dynamics structure, recognizes the effects of covariates, incorporates the variation in interepisode duration due to unobserved individual-specific factors and variation in interepisode duration within spells of the same individual, and considers the joint nature of participation in the various activities is proposed and applied. The variables considered in the analysis include demographics, access to the internet, location characteristics, and day of week variables. The results indicate a very distinct weekly rhythm in individuals ’ participation in social, recreation, and personal business activities. While there is a similar rhythm even for participation in shopping activities, it is not as pronounced as for the non-shoppin...

This paper investigates the factors influencing consumer conversion from cow's milk to plant-based milk in the Philippines. Drawing on the Theory of Consumption Values (TCV), we explored how hedonistic, utilitarian, and symbolic motivations impact purchase intentions. This research surveyed the participants and core question sets using the Likert scale. This study tested the hypotheses using multiple ordinal and multiple linear regression only after rank transformation; all regression calculations are done via the reputable R programming with the R package “ordinal” and “latest," respectively. Findings established that Filipino milk consumers are still primarily driven by two of the consumer above values and support the contemporary marketing research that there is a demand-gap opportunity in the Philippines after convincing the market. There are two significant aspects of this research in the literature: first, it contributes to the understanding of consumer behavior towards plant-based milk, and second, it provides a unique perspective by examining Vitasoy's marketing campaign within the Philippine market context. With the growing milk consumption and shrinking cow’s milk production globally, the application of this paper will contribute to the world by providing producers and marketers a framework on how to convince consumers to shift their purchasing patterns from cow's milk to viable and more nutritious plant-based milk. This paper supports the United Nation's Sustainable Development Goals (SDG) 12.

The airline industry is characterized by intense competition and two main business models: low-cost carriers (LCC) and full-service carriers (FSC). This study aims to analyze consumer behavior in choosing an airline by comparing Asia Aviation (LCC) and Thai Airways (FSC). A descriptive qualitative research method was used, with data from LSEG Refinitiv Workspace financial reports. The analysis focused on metrics such as RASM (Revenue per Available Seat Mile/Kilometer), Passenger Load Factor, and Average Fare. The findings show a significant difference in consumer behavior between the two models. Asia Aviation targets price-sensitive consumers who prioritize the lowest cost. In contrast, Thai Airways serves consumers who value additional services, comprehensive amenities, and are willing to pay more for a better travel experience. During the COVID-19 pandemic, although both experienced a sharp decline, the LCC model demonstrated a faster recovery. Asia Aviation attracted passengers by initially lowering fares and then raising them as the market recovered. Conversely, Thai Airways increased its revenue per passenger by focusing on premium routes and passengers, indicating a market segment that was willing to pay a high price even during the crisis. The study concludes that an effective pricing strategy is key, as both models successfully serve different market segments, reflecting the diversity of consumer preferences between cost and travel experience.

This study continues the dialogue around sustainable consumption psychology and its effects on New Energy Vehicle repurchase intentions, depending on moderating gender differences. To achieve this, we employed sustainable consumption theories, social identity theory, and gender schema theory to formulate our conceptual framework, which we corroborated with the data of 527 NEV owners across Chinese cities in varying tiers. The outcomes indicate a substantial direct effect of sustainable consumption psychology on repurchase intention (β = 0.467, p < 0.001) with value perception acting as a mediator. The literature on sustainable consumption psychology identifies two variables, environmental awareness and social responsibility, which have differing outcomes according to the gender of the consumer. For instance, female consumers are motivated more by environmental awareness as compared to male consumers who relate more social responsibility to the buying intention (β = 0.328). Conversely, male consumers are motivated stronger to buy on social responsibility in comparison to female consumers (β = 0.376). Multi-group analysis also depicts significant differences between these relationships in demographic slices, with the greatest impact being the high-income, middle-aged, first-tier city dwellers. This insight not only enhances theoretical perspectives on sustainable buying behavior but also assists manufacturers, marketers, and policymakers in effective promotion of sustainable transport means. The research adds value to existing literature in sustainable consumption while also providing value on the ground with regard to NEV market creation, particularly on sustainability consumption with respect to gender and other demographic variables.

The pharmaceutical market in urban areas plays an important role in supporting healthcare needs. Urban populations are growing rapidly, and people living in cities often experience different health challenges due to pollution, stress, unhealthy eating habits, and a fast-paced lifestyle. This leads to a higher demand for medicines, especially for diseases such as diabetes, hypertension, respiratory problems, infections, and mental health disorders. This study explores how medicines are used, purchased, and distributed among people living in urban areas. It also looks at the differences between branded and generic drugs and how people make choices based on price, availability, and trust. In urban settings, access to pharmacies, hospitals, and healthcare professionals is generally better compared to rural areas, but there are still challenges such as high costs, lack of awareness, and the influence of advertisements. Information has been gathered from secondary sources like health department reports, pharmaceutical sales records, and market research publications. The study also highlights the growing trend of over-the-counter (OTC) drug use and self-medication practices in cities. Overall, the findings show that while urban populations have better access to medicines, there is a strong need for improving awareness about proper drug use, encouraging the use of affordable generics, and ensuring that quality medicines are available to everyone. The pharmaceutical market in urban areas has great potential to grow further, but it must be supported with strong policies, regulation, and public health education to ensure better healthcare outcomes.

Elasticities are often estimated from the results of demand analysis however, drawing inferences from them may involve assumptions that could influence the outcome. In this paper we investigate one of the most common forms of elasticity which is defined as a ratio of estimated relationships and demonstrate how the Fieller method for the construction of confidence intervals can be used to draw inferences. We estimate the elasticities of expenditure from Engel curves using a variety of estimation models. Parametric Engel curves are modelled using OLS, MM robust regression, and Tobit. Semiparametric Engel curves are estimated using a penalized spline regression. We demonstrate the construction of confidence intervals of the expenditure elasticities for a series of expenditure levels as well as the estimated cumulative density function for the elasticity evaluated for a particular household.

In this paper we consider estimation of demand systems with flexible functional forms, allowing an error term with a general conditional heteroskedasticity function that depends on observed covariates, such as demographic variables. We propose a general model that can be estimated either by quasimaximum likelihood (in the case of exogenous regressors) or generalized method of moments (GMM) if the covariates are endogenous. The specification proposed in the paper nests several demand functions in the literature and the results can be applied to the recently proposed Exact Affine Stone Index (EASI) demand system of Tricks with Hicks: The EASI implicit Marshallian demand system for unobserved heterogeneity and flexible Engel curves. American Economic Review (in press)]. Furthermore, flexible nonlinear expenditure elasticities can be estimated.

Elasticities are often estimated from the results of demand analysis however, drawing inferences from them may involve assumptions that could influence the outcome. In this paper we investigate one of the most common forms of elasticity which is defined as a ratio of estimated relationships and demonstrate how the Fieller method for the construction of confidence intervals can be used to draw inferences. We estimate the elasticities of expenditure from Engel curves using a variety of estimation models. Parametric Engel curves are modelled using OLS, MM robust regression, and Tobit. Semiparametric Engel curves are estimated using a penalized spline regression. We demonstrate the construction of confidence intervals of the expenditure elasticities for a series of expenditure levels as well as the estimated cumulative density function for the elasticity evaluated for a particular household.

Model builders and policy analysts have relied on their subjective price-effect estimation on fish and other meat components in consumer diet with the result that their analyses do not exactly and reliably reflect the reality. This study provides empirical price-effect analysis of the demand for meat- and fish-consuming rural households in South-eastern Nigeria. Data collected from 590 rural household consumers of meat and fish were analyzed using the Linear Approximate Almost Ideal Demand System (LA/AIDS) and the Slusky decomposition. The results showed that meat and fish consumers exhibit some inconsistent behaviour in expenditure, and expend the highest proportion of their conditional income on chicken with mo relationship in commodities demand by price of fish. Fish and other meat components are necessities with only chicken as a luxury commodity in the region. Although, the unobservable own-price effect components of the total price-change show that there is likely no preferenc...

Fluctuations in global oil prices and variations in consumer income significantly influence transportation demand, posing challenges for policymakers, businesses, and households. This study examines the dynamic relationship between oil price, income, and transportation demand to address the gap in understanding how these variables interact in both short- and long-term contexts. The purpose is to determine the extent to which changes in oil price and income levels affect transportation demand patterns. Employing a time-series econometric approach, specifically a Vector Autoregression (VAR) model with data spanning 2000–2024, the analysis reveals that rising oil prices reduce transportation demand, while increasing income exerts a positive effect. Findings indicate asymmetric responses to oil price shocks, with demand being more sensitive to price increases than decreases. Limitations include reliance on secondary data and potential unobserved variables. Practical implications highlight the need for sustainable transport policies, while social implications emphasize affordability and accessibility. The study’s originality lies in integrating oil price and income dynamics to forecast transportation demand.

Mit diesem thematischen Bericht wird das Ziel verfolgt, einen Überblick über die wesentlichen Informationen zu Zielgruppen Lebenslangen Lernens an Hochschulen zu geben. Im ersten Teil des Berichts werden zunächst Kriterien zur Systematisierung und Beschreibung sowie eine Typologie erwachsener Lernender an Hochschulen vorgestellt. Im zweiten, empirisch ausgerichteten Teil des Berichts wird eine grundlegende Orientierung hinsichtlich Umfang und Struktur von (potenziellen) Zielgruppen gegeben. Gemeinsam können diese Informationen zur Entwicklung und Durchführung von Nachfrage- und Bedarfsanalysen für Studienangebote beitragen, bei denen die Analyse der Zielgruppen einen wichtigen Teilaspekt darstellt. Diese Publikation ist im Rahmen der wissenschaftlichen Begleitung des Bund-Länder-Wettbewerbs &quot;Aufstieg durch Bildung: offene Hochschulen&quot; entstanden. (Hrsg.)

Enrolment rates to higher education reveal quite large variation over time which cannot be explained by productivity shocks alone. We develop a human capital investment model in an overlapping generations framework that features endogenous fluctuations in the demand for education. Agents are heterogeneous in their beliefs about future wage differentials. An evolutionary competition between the heterogeneous beliefs determines the fraction of the newborn generation having a certain belief. Costly access to information on the returns to education induces agents to use potentially destabilizing backward looking prediction rules. Only if previous generations experience regret about their human capital investment decisions, agents will choose a more sophisticated prediction rule that dampens the cycle. Access to information becomes key for stable flows to higher education.

bstract
This study aims to identify the impact introducing flat-rates in the Portuguese
Telecommunication Market – the introduction of services who’s price are not dependent
on the amount consumed - and it’s influence on total amount consumed and the price that the
customer is willing to pay for it. We will focus the study also on finding if choosing flat-rate
plans are the most cost efficient choice or if pay-per-use would be preferable.
The study was based on a 80,000 mobile service residential customers a sample, with prepaid
tariff of the 3 major carriers in Portugal, over a 4.5 years period (January 2010 through June
2014).
The study revealed the existence of a flat rate bias, where the customer prefers to pay an
additional amount to guarantee that at the end of the month the bill will be no different than
expected.
The study also showed that the Portuguese market does not conform to the strict economic
thought of choosing the cheapest alternative, revealing serious distortions between the chosen
tariff and the one that would minimize the monthly bill. Although the market revealed that the
level of development and penetration of service are sufficient for release conditions of
nonlinear tariff and that the market is stable enough so that tariffs are launched successfully.
The study's findings point to the possibility that consumption profile is influenced by the
chosen tariff. In the Portuguese market, the average consumption of a customer that changes
it’s tariff plan to a flat plan increases by 70%, consistently and apparently without exceptions.
This increase in consumption did not mean that the new volume of minutes per month spent
would now exceed the free traffic included in the plan. (99% of customers never exceeded the
allowance).
Migration movements in tariff plans and service providers appear to be reducing factors in
overpayment of the telephone invoice, but socio-economic factors such as age, gender or
academic level seem to be unrelated to improving tariff choice.
The sample showed that the customer is willing to spend a little more for a flat-rate plan – no
hassle seems the key to conquer market share, a market which is so badly understood by its
customers

Cloud computing platforms must efficiently allocate compute resources to meet
dynamic workload demands while minimizing cost. This paper proposes an adaptive
resource allocation framework that uses workload forecasting and user-driven policies
to optimize cloud resource usage in real time. By leveraging the data volume
predictions and workload pattern analysis, our system proactively scales computing
resources up or down in anticipation of needs, rather than relying solely on reactive
auto-scaling. We mathematically formulate the resource allocation problem to optimize
cost and performance, and we introduce a predictive allocation algorithm that adjusts
virtual machine instances, memory, and storage based on forecasted job demands. The
approach is compared against traditional static allocation and reactive scaling
methods. Experimental results on a cloud testbed show that the predictive resource
management strategy achieves up to 30% reduction in infrastructure cost and about
25% improvement in job execution times, without violating service-level agreements.
We also incorporate a user-driven component allowing manual overrides (e.g., to
respect budget limits or deadlines), adding flexibility. The paper includes performance
evaluation graphs and tables demonstrating how adaptive provisioning outperforms static provisioning in both cost savings and system throughput. The findings highlight
that combining predictive analytics with cloud resource orchestration can significantly
enhance efficiency and cost-effectiveness in cloud computing operations.

The current study examined the determinants of electricity consumption and also intends to forecast the electricity consumption in Pakistan. The study has used time series data analysis, applied Johansen Cointegration Test, error correction mechanisms and regression for examining determinants and autoregressive integrated moving average model is used for forecasting. The study has used times series secondary annual data on different variables for the period ranging from 1970 to 2018. The results of the study showed that gross domestic product and population have positive impact on electricity consumption. Whereas, National output (GDP) is statistically significant in the determination of total electricity consumption. The results also indicated that increase in the real economic activities has increases the total electricity consumption. Furthermore, the results of electricity consumption model also suggest that electricity price have negative impact on total electricity consumption. As electricity demand is inelastic to electricity price and income, it indicates that fewer substitutes of electricity are available in the market. Hence electricity is essential component of energy for economy. The results of the current study can be useful for the policymakers and government regulatory bodies relating to electricity.

Bioenergetics is the study of how animals achieve energetic balance. Energetic balance results from the energetic expenditure of an individual and the energy they extract from their environment. Ingested energy depends on several extrinsic (e.g prey species, nutritional value and composition, prey density and availability) and intrinsic factors (e.g. foraging effort, success at catching prey, digestive processes and associated energy losses, and digestive capacity). While the focus in bioenergetic modelling is often on the energetic costs an animal incurs, the robust estimation of an individual’s energy intake is equally critical for producing meaningful predictions. Here, we review the components and processes that affect energy intake from ingested gross energy to biologically useful net energy (NE). The current state of knowledge of each parameter is reviewed, shedding light on research gaps to advance this field. The review highlighted that the foraging behaviour of many marine ...

Several studies published in the last few decades have demonstrated a low price‐elasticity for residential water use. In particular, it has been shown that there is a quantity of water demanded that remains constant regardless of prices and other economic factors. In this research, we characterise residential water demand based on a Stone‐Geary utility function. This specification is not only theory‐compatible but can also explicitly model a minimum level of consumption not dependent on prices or income. This is described as minimum threshold or nondiscretionary water use. Additionally, the Stone‐Geary framework is used to model the subsistence level of water consumption that is dependent on the temporal evolution of consumer habits and stock of physical capital. The main aim of this study is to analyse the impact of water‐saving habits and water‐efficient technologies on residential water demand, while additionally focusing attention on nondiscretionary uses. This is informed by an...

Several studies have examined consumer attitudes and preferences toward meat products (e.g., Branson et al.; Skaggs et al.; Menkhaus et al.). Other analyses have identified sources of structural changes in U.S. meat consumption (e.g., Nyankori and Miller; Braschler; Chavas; Moschini and Meilke) and have examined effects of demographic factors on meat consumption (e.g., Buse and Salathe; Cox, Buse, and Alvarez; Blaylock and Smallwood; Nayga and Capps 1992). These studies, however, have focused on broad and aggregated commodities. Due to the degree of aggregation, considerable information about consumption patterns of the commodities is potentially lost. Consequently, some researchers (Eales and Unnevehr; Pudney; Nayga and Capps 1994) have suggested that a full understanding of meat consumption patterns requires analysis of a disaggregated products model. Simply put, little information exists on factors affecting disaggregate meat expenditures at the household level. Recent studies that have focused on disaggregate meat products (e.g., Capps and Nayga 1990, 199 1 ;Nayga and Capps 1994) have used time-series scanner data from supermarkets. A drawback of using scanner data is that it does not usually provide information about consumers' demographic characteristics. Recent interest in demographic effects has led researchers to the use of cross-sectional microdata. The use of household-level microdata is popular because it avoids the problem of aggregation over consumers and often provides a large and statistically-rich sample (Heien and Wessells).

In this paper we propose a unified framework for testing weak separability. We present a new three-step procedure, which is a joint test of necessary and sufficient conditions that takes account of possible measurement error and incomplete adjustment. We illustrate the operational capability of the procedure with an empirical example. Our procedure works well in medium sized samples, but at the present time may not be practical for datasets with extremely large sample sizes. As computing technology continues to advance, however, high-powered methods like the one we propose should supplant testing approaches that were originally designed to circumvent computational limitations. The authors wish to thank the Jan Wallander and Tom Hedelius Foundation for providing financial support for this and related research projects (Grants J98/14 and J03/19).

Abstract: Quantity surcharges exist when unit prices are higher for larger packages. We hypothesize that various sizes of goods are differentiated products, and this explains some surcharges. Estimating a random-coefficients logit demand model, we examine own and cross elasticities to determine the level of differentiation between products with different size packages.

Recently Aw, Rascle and Zhang introduced a second order model (ARZ) that does nor exhibit the usual drawbacks of this family of models, i.e. negative velocities and/or densities. In this paper we analyze the inhomogeous Riemann problem for this model, which is shown to be equivalent to the inhomogeous Riemann problem for a related first order model with modified equilibrium flow density relationship. The boundary conditions for the ARZ model are deduced. They can be expressed in terms of an upstream demand and downstream supply.

Elasticities are often estimated from the results of demand analysis however, drawing inferences from them may involve assumptions that could influence the outcome. In this paper we investigate one of the most common forms of elasticity which is defined as a ratio of estimated relationships and demonstrate how the Fieller method for the construction of confidence intervals can be used to draw inferences. We estimate the elasticities of expenditure from Engel curves using a variety of estimation models. Parametric Engel curves are modelled using OLS, MM robust regression, and Tobit. Semiparametric Engel curves are estimated using a penalized spline regression. We demonstrate the construction of confidence intervals of the expenditure elasticities for a series of expenditure levels as well as the estimated cumulative density function for the elasticity evaluated for a particular household.

The livestock sector is emerging as one of the fastest growing agricultural sub-sectors in India and the expectations are that this growth could further accelerate due to growing incomes and the high income elasticity of demand for livestock products. Given the size and relatively equitable distribution of livestock in India, this presents an excellent opportunity for the country to boost rural incomes and accelerate the pace of poverty reduction. But, successful capitalisation of such opportunities requires a policy regime that facilitates growth in productivity at the farm level as well as in the processing sector. The productive potential of animals depends crucially on the quality of nutrition, genetic material and the animal health system, and on all these counts, India has a poor record. The public sector continues to be the primary provider of veterinary services, and the deteriorating fiscal situation of most state governments is making it extremely difficult to either expand the reach of these services or improve the quality of service delivery. Although, on efficiency grounds, there is good rationale for commercialised delivery of these services, serious concerns prevail in India about the equity implications of private sector delivery or full cost recovery within the government system. Evaluation of the desirability of user fees or private delivery of livestock services requires an understanding of the factors influencing the demand for these services. This paper examines the nature of demand for veterinary services in three states of India and presents first estimates of demand elasticities for veterinary services. The results indicate that price is not an important determinant of the decision to use these services. Also, practically no variation is found in price elasticities across income groups. These results suggest that the fears of sharp declines in the use of these services as a result of full cost recovery and/or private sector delivery are unfounded.

This paper presents the results of a field survey on use patterns and demand for clinical veterinary services in one of the poorest states of India, namely, Orissa. A demand function was estimated using Poisson regression and demand elasticities were obtained for various income groups. The survey shows that large numbers of households, including the poor, pay prices that are significantly higher than those prescribed. There is no targeting of cheaper services towards the poor. The analysis also suggests that for a given service and place of service, the poor actually paid more on a per veterinary visit basis. As a result, the rate of service utilisation was significantly lower for poor households. Demand analysis confirmed that the demand for veterinary services is not determined by subsidised service delivery, but by access to output markets and general awareness levels. In the light of these findings, the paper makes a number of recommendations for redefining the role of the Government in veterinary service delivery in Orissa.

The livestock sector is emerging as one of the fastest growing agricultural sub-sectors in India and the expectations are that this growth could further accelerate due to growing incomes and the high income elasticity of demand for livestock products. Given the size and relatively equitable distribution of livestock in India, this presents an excellent opportunity for the country to boost rural incomes and accelerate the pace of poverty reduction. But, successful capitalisation of such opportunities requires a policy regime that facilitates growth in productivity at the farm level as well as in the processing sector. The productive potential of animals depends crucially on the quality of nutrition, genetic material and the animal health system, and on all these counts, India has a poor record. The public sector continues to be the primary provider of veterinary services, and the deteriorating fiscal situation of most state governments is making it extremely difficult to either expand the reach of these services or improve the quality of service delivery. Although, on efficiency grounds, there is good rationale for commercialised delivery of these services, serious concerns prevail in India about the equity implications of private sector delivery or full cost recovery within the government system. Evaluation of the desirability of user fees or private delivery of livestock services requires an understanding of the factors influencing the demand for these services. This paper examines the nature of demand for veterinary services in three states of India and presents first estimates of demand elasticities for veterinary services. The results indicate that price is not an important determinant of the decision to use these services. Also, practically no variation is found in price elasticities across income groups. These results suggest that the fears of sharp declines in the use of these services as a result of full cost recovery and/or private sector delivery are unfounded.

In Bangladesh, the average excise tax on cigarettes accounted for just 38% of the average retail price of cigarettes in 2009, and 45% in 2010. Both these rates are well below the WHO recommended share of 70% of the retail price at a minimum. There is thus ample room for raising taxes on cigarettes in Bangladesh. The objective of the present work was therefore to estimate the price elasticity of demand for cigarettes and the effect of tax increases on the consumption of cigarettes and on tax revenue in Bangladesh. Based on data from Wave 1 (2009) and Wave 2 (2010) of the International Tobacco Control Bangladesh Survey, we estimated the overall impact of a price change on cigarette demand using a two-part model. The total price elasticity of cigarettes was measured by the sum of the elasticity of smoking prevalence and the elasticity of average daily consumption conditional on smoking participation. The price elasticity estimates were used in a simulation model to predict changes in c...

By assessing carbon footprints and raising awareness of carbon labelling, the food sector is setting long-term targets to reduce carbon emissions and accelerate the transition to low-carbon food production. Carbon labelling, also known as carbon labelling, informs customers about a product's production, distribution, and disposal carbon emissions. This study examines how customers view carbon labelling and how it affects their purchases. The study also examines the complex food industry, identifying the biggest carbon emitters and proposing sustainable alternatives. The study collects qualitative and quantitative data using mixed methodologies. An overview of the literature shows how carbon labelling promotes sustainable consumption. Life Cycle Assessment (LCA) is used to evaluate two sandwich recipes' carbon footprints, focusing on emissions per item. LCA results indicated that carbon footprint of a cheese and mayonnaise sandwich ranged between 700 and 750 g CO 2 eq, while a ham and cheese sandwich ranged between 1053 and 1070 g CO 2 eq., and the primary contributors for these emissions were ingredient production, packaging and energy consumption. A sandwich maker partnership simplifies case study data collection, providing a complete carbon footprint analysis throughout production. This study suggests ways to minimise food industry carbon emissions for a sustainable future. Consumer knowledge and relevance of carbon labelling vary, according to our results. Survey findings revealed that 68.6 % of respondents recognise the significance of carbon labelling, however, only 26.9 % reported that their purchasing decisions are influenced by carbon labelling. This indicated a gap between consumer awareness and behavioural change. Consumers are concerned about carbon footprints; thus, carbon labels affect shopping decisions differently. This study suggests that consumer education, standardisation of carbon labelling and recipe modifications could increase effectiveness of carbon labelling in the food industry and its potential to change consumer behaviour towards greener choices and lower carbon footprints.

This research attempts to investigate the adoption, use and impact of broadband services from a holistic point of view encompassing the factors influencing the adoption, use and impact of broadband. This study explores the broadband developments in South Africa and discusses the challenges faced in increasing the broadband penetration rate within the country.

This paper investigates the rise and fall of the IV method in macro-econometric models and its subsequent revival in micro-econometric models. The key findings are: (i) the IV method implicitly breaks the contemporaneously circular causality postulated in a simultaneousequation model (SEM) by redefining the conditional variable concerned as a suboptimal conditional expectation of it; (ii) the IV method falls out of favour in macro-econometrics mainly because of lack of empirical validations for such redefinitions; (iii) the IV method wins its popularity in micro-econometrics by its capacity to produce multiple suboptimal conditional expectations of the latent conditional variables of interest under the disguise of an SEM consistent estimator; nevertheless, (iv) such suboptimal conditional expectations give rise to the insurmountable difficulty of credibly interpreting the IV-based parameter estimates, especially in the case of prognosticated omitted variable bias. The findings highlight the methodological drawback of the estimator-centric strategy of textbook econometrics.

Resumo: A identificação da categoria de um veículo que trafega em uma via é um importante parâmetro para sistemas de gerenciamento de tráfego. A classificação veicular tem aplicações como planejamento do sistema viário, estimativa de emissões veiculares ...

While demand estimates are used in policy making in a number of areas, there has not been a substantial literature on demand patterns and responses in Pakistan. We present estimates for thirteen classes of goods, based on a complete demand system, a modification of the Unear Expenditure System, using maximum likelihood techniques and observations at the household level for Pakistan and urban and rurll areas for 1976.

This experiment was conducted to test the predictions of two behavioral-economic approaches to quantifying relative reinforcer efficacy. The normalized demand analysis suggests that characteristics of averaged normalized demand curves may be used to predict progressive-ratio breakpoints and peak responding. By contrast, the demand analysis holds that traditional measures of relative reinforcer efficacy (breakpoint, peak response rate, and choice) correspond to specific characteristics of nonnormalized demand curves. The accuracy of these predictions was evaluated in rats' responding for food or water: two reinforcers known to function as complements. Consistent with the first approach, predicted peak normalized response output values obtained under single-schedule conditions ordinally predicted progressive-ratio breakpoints and peak response rates obtained in a separate condition. Combining the minimum-needs hypothesis with the normalized demand analysis helped to interpret prior findings, but was less useful in predicting choice between food and water-two strongly complementary reinforcers. Predictions of the demand analysis had mixed success. Peak response outputs predicted from the non-normalized water demand curves were significantly correlated with obtained peak responding for water in a separate condition, but none of the remaining three predicted correlations was statistically significant. The demand analysis fared better in predicting choice-relative consumption of food and water under single schedules of reinforcement predicted preference under concurrent schedules significantly better than chance.

This article offers a comparison of short-term forecasting ability of five demand systems with an application to U+S+ meat consumption+ Four static demand systems ~AIDS, Rotterdam, AIM, and DGM! and a dynamic Vector Error Correction Model ~VECM! are considered+ We tested the equality of mean square forecast errors+ We also investigated the possibility of forecast encompassing among competing models+ In general, the dynamic VECM model performed best, followed by the simple causal DGM model+ Among three static systems, the AIDS model slightly leads the com-petition+ Furthermore, this article provides the first evidence in literature on whether imposition of homogeneity restrictions on a cointegration space can improve the forecast accuracy of a VECM model: it does when it holds+ @EconLit citations: Q10; C53#+

The manufacturer's requirement of increasing productivity results in the need to design work stations that are increasingly more effective and specialized. However, this procedure can bring about an overloading of the worker, a lack of motivation, and, consequently, a reduction in productivity. Ergonomics adapts the work station to the worker with the object of improving his welfare and satisfaction at his post. One aspect that this science concerns itself with is the evaluation of physical demands connected to productive tasks. Mechanical movements are also studied in order to pe$orm tasks efticiently. We here propose a new method of physical demand analysis that determines the risk factor for muscular skeletal lesion. This method uses, as a base, the system of predetermined times, MTM-UAS. It includes a computer system that allows us to easily analyse the operations at a work station and generates charts similar to those of UAS, but, instead of times, it measures the quantity of mechanical work necessary for each movement. The information that the method provides can be used by d@erent divisions within companies in making decisions about improvements at work stations.

Doesburger Eng is a rural community located in Ede north of Kernhem and south of Lunteren (The Netherlands). It has a total land size of 140 hectares in which 85% of the area is presently used for farming and 15% for housing. It has about 50 farmers involved in cereal and livestock production (Verschuur, 2012). The Doesburger Mill is said to be popular landmark of the area. In the 17 th and 18 th century, the area had a historical landscape of farmland planted with cereals such as rye and wheat  around the homestead, patches of forest, and heath for sheep rearing. Over the years the agricultural landscape of the area has changed where 50% of the area (70 hectares) is grown with maize for livestock feeding, 30% (42 ha) for pastures, and 5% (7 ha) for cereals barley, rye, and spelt. The change by farmers from traditional cereals to more profitable maize production has negatively changed the Doesburger Eng from its open and attractive landscape and loss of its unique cultural (historic...

The paper proposes an integrated procedure for the estimation of containerised OD flows at international scale. The procedure combines two different systems of models: (1) a meso-aggregated system of models for estimation of OD flows by means of a specification-calibration-validation process and (2) a macro-aggregated system of models for estimation of OD flows by means of a re-calibration process. The procedure has been tested in order to estimate the values of containerised OD flows of a geographical area composed of countries facing the Mediterranean basin at year 2006. The integrated procedure could represent a valid support for market operators and analysts, who need estimates of demand variables in order to mitigate risks of over-or under-investment, and for researchers developing freight models, because it offers the possibility to combine the potentialities of specification-calibration-validation and re-calibration processes in freight demand modelling.

Perspectives interdisciplinaires sur le travail et la santé 18-2 | 2016 L'ergonomie du genre : quelles influences sur l'intervention et la formation ? Inégalités de genre en entreprise : comment construire une intervention sur le travail, propice aux transformations ? Gender Inequality in Companies : developing work interventions conducive to changes La desigualdad de género en la empresa: como construir una intervención sobre el trabajo, propicia a las transformaciones?

This research work describes a project to improve the electrical installations of a mining site in Peru due to energy shortage problems. The mining site is vital for the national production of silver, lead and zinc, which boosts the economy and generates employment. The lack of electricity supply affects ventilation in underground workings and other operations. The capacity of the existing generator sets does not cover the demand, and energy is rationalized, generating outages in the camp and other operational areas, affecting the quality of life of the collaborator. The improvement proposal consists of centralizing two generating sets in the same place, a main GE and an auxiliary one, an installation design is proposed that covers the sizing of the generating set to the power distribution, and applying reactive power compensation through capacitors. A model 3508TA generator set with a power of 680 KW is selected. The implementation of a 2.3kV medium voltage network is also proposed. The implementation of the model will be carried out considering safety regulations to preserve the health of the collaborator, the development of the activities of the mining site initially is at 35.6% after the implementation of the improvement model is calculated at an average of 84.5%, that is, there was an improvement of 48.9%. The validation of the project will be carried out using simulation software and specialized tools. In summary, the project seeks to solve the electricity supply problems in the mining site, improve operational efficiency and guarantee sustainable development in the future.

This study examined the marketing of orange fruit in Maiduguri. Primary data were obtained from the respondents with the use of structured questionnaires that were filled through interviews from 60 respondents. 30 wholesalers were randomly selected from the major wholesale market and 30 retailers, were also randomly selected, ten each from three different wards of the town. Descriptive statistics were used to analyze the socio-economic characteristics of the marketers as well as the problem associated with the orange fruit marketing. Gross margin analysis was used to determine the profitability of the marketing, while Gini coefficient was used to determine the degree of market concentration. The results show that all orange marketers were in their economically active age and are mostly males with very few educated up to tertiary level (ten percent). The cost and returns analysis showed that the gross margin per marketer per week for wholesalers is N 228,500, while for retailers is lower at N 6,355. However, the gross margin per kilogramme of N 30 for the wholesale market is less than that for the retail market which stood at N 41/kg. The wholesale market has a high level of market concentration with a Gini coefficient of 0.813, while the retail market has a lower degree of concentration with a coefficient of 0.466. The markets therefore have monopolistic and oligopolistic tendencies respectively. Problems mentioned by the marketers include shortage of capital and storage facilities. The study therefore recommends that credit at favourable terms and modern storage facilities be provided to the marketers. This can enable them to expand their scale and possibly lower their cost. This could lead to lower prices to consumers and hence increased intake of orange fruits for better health outcomes.

Heightened interest in renewable energy has produced a spate of new research into the feasibility of forest biomass as a feedstock. The US Northeast is one of the few regions worldwide that supports both a large forest resource and a relatively high population density and hence energy demand. This paper outlines economic, ecological, and social considerations that must be addressed in order to achieve a sustainable forest biomass industry. Issues include sustaining the forest resource, understanding forest landowner attitudes, ensuring adequate harvesting capacity and related forest industry infrastructure, devising recommended harvest practices, demand analysis, and the development of a range of technologies that will be vying for the forest biomass resource. Recent studies focusing on sustainable supply issues include consideration of species growth and harvesting rates, as well as development of best practices to insure long-term site productivity and stream water quality. The capacity of the existing forest industry must expand with the additional demand for increased production of forest biomass. Public policy, landowner attitudes, and consideration of other social values will all play important roles in how the forest biomass industry develops. Though the research, data, and examples presented focus on the US Northeast, many of these issues have broad application to other regions of the world given appropriate consideration for local differences.

The goal of this study was to quantify the impact of specific diets on the health and body condition of harbor seals. This involved measuring the effect of diet on health status biomarkers which had been previously monitored in wild seals in Prince William Sound, determining whether specific diets were nutritionally adequate to maintain health in captive harbor seals and examining seals brought into the Alaska SeaLife Center for rehabilitation. In the first year of this project, eight harbor seals were brought to the ASLC, assigned to one of three groups, and acclimated to their new environment and diets. In September of 1998, the seals began two year feeding trials. They were fed either only pollock or herring or a mixed diet for 4 months at a time before switching diets to correct for seasonal changes in metabolism. They were weighed, measured and had blood taken every two weeks. At the end of each 4 month trial, their body condition was measured and they were placed into detailed digestion trials to assess their ability to process the different fish diets. In addition, each spring and summer, harbor seal pups brought to the ASLC for rehabilitation were monitored for changes in body condition and blood chemistry throughout recovery. The results suggest that there are a suite of blood chemistry variables that react to season and/or diet and also a group that are independent of diet or season. In addition, the body condition of the seals is strongly seasonally dependent such that all three diets (pollock, herring, mixed) showed some periods of body condition declines and other periods of condition enhancement. Changes in digestive physiology indicate that animal age, diet and season all are factors that play into the variable response to different prey items. Thus, we conclude that simple measurements of prey "quality" (i.e., fat content) do not predict the body condition or health of the seals and that field assessments of harbor seal body condition and blood chemistry can be linked to diet and season. Analysis of blood parameters and morphometric measurements of rehabilitated harbor seal pups reveal changes indicative of several factors, including development, captivity, early weaning and disease or injury and provide validation for the use of statistical outliers to assess overall population health in the wild.

This research aims: (1) to examine Indonesia’s CPO production and CPO export trends in the international market, (2) to analyze Indonesia’s CPO comparative advantages compare to other main exporters, (3) to find out which export target the country has the best market share to expand between main export target countries and (4) to know the factors that affect export volume. This research used descriptive analytics with CPO related time-series data from 2006 until 2016. The research showed that (1) Indonesia’s production and export trends are expected to increase each year (2) Indonesia has better comparative advantages compared to other main export country and on maturity stage (3) The best CPO market share to expand is China compare to other export target countries (4) Factors affecting export volume are CPO international price, Indonesia’s GDP and total population.

The main objective of this study was to work out production efficiency of some cooperative and non cooperative farmers in the central Punjab, Pakistan. For this purpose a survey of central Punjab was conducted in the year of 2008-09. Two type samples were taken for the study. First type sample was comprised of 15 respondents who had joined together in different ways to cultivate their available lands. Second type included 60 respondents, 20 from each district of Jhang, Faisalabad and TT Singh. The results obtained through tstatistics analysis revealed that the per acre use of Agri inputs and outputs obtained for all the cash crops was significantly different and higher in case of cooperatives than non-cooperatives farmers. The benefit cost (B-C) ratio indicated that it was 38% higher for cooperative than non-cooperatives as it was 1.98 and 1.43 for respective categories. But these cooperatives farming could not sustain for longer time due to the lake of education and conflicts between the members.