Consumers’ fluid milk consumption behaviors in TURKEY: an application of multinomial logit model

Although consumers’ fluid milk consumption behavior related to skim milk, low fat milk and whole milk have attracted a lot of attention in the last decade, relatively a few studies have examined the consumers’ unprocessed and processed fluid milk consumption. The objective of this study was to analyze consumers’ fluid milk consumption and preference in Turkey by using cross-sectional national survey data. The Chi-square test of independence and multinomial logit procedure were used to investigate the selected socioeconomic and demographic characteristics of consumers that determine households’ fluid milk consumption choices between unprocessed fluid milk, processed fluid milk and non-consumption choices. Empirical results indicate that unprocessed fluid milk preference is related positively to household size, number of children in family, household income, and age of housewife; and negatively to education level and employment status of housewife. On the other hand, processed fluid milk preferences are related positively to household income, number of children in households and education level of housewife and negatively to household size and age of housewife.     

Beta-product dependent Pitman–Yor processes for Bayesian inference

Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process mixture approach and define a new class of multivariate dependent Pitman–Yor processes (DPY). The proposed DPY are represented in terms of vectors of stick-breaking processes which determine dependent clustering structures in the time series. We follow a hierarchical specification of the DPY base measure to account for various degrees of information pooling across the series. We discuss some theoretical properties of the DPY and use them to define Bayesian non-parametric repeated measurement and vector autoregressive models. We provide efficient Monte Carlo Markov Chain algorithms for posterior computation of the proposed models and illustrate the effectiveness of the method with a simulation study and an application to the United States and the European Union business cycle.     

Predator–prey model for stock market fluctuations

Journal of Economic Interaction and Coordination - We present a dynamical model for the price evolution of financial assets. The model is based on a two-level approach: In the first stage, one...     

Affordable dwelling-layout system design—A model for optimization

The systems nature of the residential land planning has been outlined and an optimization model for minimizing the cost of a layout has been presented earlier. In the present paper, a model for optimal design of the dwelling-layout system, consisting of the dwelling as well as the residential layout, has been developed. In this model, which is also a non-linear programming problem, maximizing the dwelling space has been taken as the objective function. Affordable cost and physical design standards such as density, public open space, circulation interval, have been taken as the constraints in the model. The problem has been solved using the geometric programming technique and the programme developed by the author. Using this model, a dwelling-layout system could be designed directly to achieve the maximum benefit i.e. maximum dwelling space, within the given affordable cost and fulfilling the given physical design standards mentioned above.     

A simple mean–dispersion model of ambiguity attitudes

Several characterizations of ambiguity aversion decompose preferences into the expected utility of an act and an adjustment factor, an ambiguity index, or a dispersion function. In each of these cases, the adjustment factor has very little structure imposed on it, and thus these models provide little guidance as to which function to use from the infinite class of possible alternatives. In this paper, we provide a simple axiomatic characterization of mean–dispersion preferences which uniquely determines a subjective probability distribution over a set of possible priors and which uniquely identifies the dispersion function. We provide an algorithm for determining this subjective probability distribution and the coefficient in the dispersion function from experimental data. We also demonstrate that the model accommodates ambiguity aversion in the Ellsberg paradox.     

A SHARP model of bid–ask spread forecasts

This paper proposes an accurate, parsimonious and fast-to-estimate forecasting model for integer-valued time series with long memory and seasonality. The modelling is achieved through an autoregressive Poisson process with a predictable stochastic intensity that is determined by two factors: a seasonal intraday pattern and a heterogeneous autoregressive component. We call the model SHARP, which is an acronym for seasonal heterogeneous autoregressive Poisson. We also present a mixed-data sampling extension of the model, which adopts the historical information flow more efficiently and provides the best (among all the models considered) forecasting performances, empirically, for the bid–ask spreads of NYSE equity stocks. We conclude by showing how bid–ask spread forecasts based on the SHARP model can be exploited in order to reduce the total cost incurred by a trader who is willing to buy or sell a given amount of an equity stock.     

A disaster response model driven by spatial–temporal forecasts

In this research, we propose a disaster response model combining preparedness and responsiveness strategies. The selective response depends on the level of accuracy that our forecasting models can achieve. In order to decide the right geographical space and time window of response, forecasts are prepared and assessed through a spatial–temporal aggregation framework, until we find the optimum level of aggregation. The research considers major earthquake data for the period 1985–2014. Building on the produced forecasts, we develop accordingly a disaster response model. The model is dynamic in nature, as it is updated every time a new event is added in the database. Any forecasting model can be optimized though the proposed spatial–temporal forecasting framework, and as such our results can be easily generalized. This is true for other forecasting methods and in other disaster response contexts.     

General existence of competitive equilibrium in the growth model with an endogenous labor–leisure choice

We prove the existence of competitive equilibrium in the canonical optimal growth model with elastic labor supply under general conditions. In this model, strong conditions to rule out corner solutions are often not well justified. We show using a separation argument that there exist Lagrange multipliers that can be viewed as a system of competitive prices. Neither Inada conditions, nor strict concavity, nor homogeneity, nor differentiability are required for existence of a competitive equilibrium. Thus, we cover important specifications used in the macroeconomics literature for which existence of a competitive equilibrium is not well understood. We give examples to illustrate the violation of the conditions used in earlier existence results but where a competitive equilibrium can be shown to exist following the approach in this paper.     

Structural model for analysis of key performance indicators for sustainable manufacturer–supplier collaboration: A grey-decision-making trial and evaluation laboratory-based approach

With growing competition in the market and dire need for sustainability, it has become imperative for companies to build long-term relationship with their supply chain partners through sustainable collaboration. Among these, the supplier–manufacturer relationship is crucial for improved organizational, business and sustainable performance. Sustainable collaboration with suppliers involves crucial decision-making processes such as continuous supplier monitoring and supplier development. Hence, a critical challenge that a company faces is to identify the key performance indicators (KPIs) for assessing the performance of a supplier for sustainable collaboration. In this regard, this study focuses on identification of KPIs for an Indian home appliance company through exhaustive discussions involving multiple decision-makers. Further, a grey-based decision-making trial and evaluation laboratory (DEMATEL) model is proposed in the study for analysing the importance levels among the fifteen KPIs based on multiple stakeholder perspectives. The results of the grey structural model indicate seven KPIs as influencing KPIs and eight KPIs as influenced KPIs. The KPI ‘Information disclosure’ has been identified as the most influential KPI for the evaluation of suppliers for sustainable collaboration. The implications drawn from the result analysis model can provide meaningful insights to managers for identifying strategies towards strengthening the supplier–manufacturer relationship and achieving organizational and market competence.     

What model for entry in first-price auctions? A nonparametric approach

We develop a selective entry model for first-price auctions that nests two polar models often estimated in the empirical literature on auctions, Levin and Smith (1994), and Samuelson (1985). The selective entry model features a pro-competitive selection effect. The selection effect is shown to be nonparametrically identifiable, and a nonparametric test for its presence is proposed. This test can be used to discriminate between the two polar models.     

An economic–probabilistic model for risk analysis in technological innovation projects

This paper presents the application of an economic–probabilistic model to conduct risk analysis in technological innovation (TI) projects. The model integrates risk and economic analysis by quantifying both value and probability of occurrence of cash flow deviations, thus resulting in an economic–probabilistic analysis of the expected returns. The main risk categories and factors in TI projects are identified and associated to cash flow groups. The model allows to calculate risk-adjusted values for cash flow groups and project net present value through stochastic simulation. As a result, the model provides both the risk-adjusted project economic return with the associated probability distribution to its NPV and the variability that each risk factor generates in the project return. The model offers important benefits from the point of view of practitioners, including a condensed list of independent risk factors and the use of a monetary scale to assess risk impact which is familiar to most decision makers.     

Bayesian estimation of labor demand by age: theoretical consistency and an application to an input–output model

Extended input–output models require careful estimation of disaggregated consumption by households and comparable sources of labor income by sector. The latter components most often have to be estimated. The primary focus of this paper is to produce labor demand disaggregated by workers’ age. The results are evaluated through considerations of its consistency with a static labor demand model restricted with theoretical requirements. A Bayesian approach is used for more straightforward imposition of regularity conditions. The Bayesian model confirms elastic labor demand for youth workers, which is consistent with what past studies find. Additionally, to explore the effects of changes in age structure on a regional economy, the estimated age-group-specific labor demand model is integrated into a regional input–output model. The integrated model suggests that ceteris paribus ageing population contributes to lowering aggregate economic multipliers due to the rapidly growing number of elderly workers who earn less than younger workers.     

A necessary and sufficient condition for the positivity of the growth rate in the Neumann–Gale model of economic growth

In the paper I will discuss an extension of the classical problem of the positivity of the growth rate in the Gale–Neumann model. I will show that the exploitation of the labour is a necessary and sufficient condition for the positivity of the growth rate.     

Accounting for wage and employment changes in the US from 1968–2000: A dynamic model of labor market equilibrium

In this article, we present a unified treatment of and explanation for the evolution of wages and employment in the US over the last 30 years. Specifically, we account for the pattern of changes in wage inequality, for the increased relative wage and employment of women, for the emergence of the college wage premium and for the shift in employment from the goods to the service-producing sector. The underlying theory we adopt is neoclassical, a two-sector competitive labor market economy in which the supply of and demand for labor of heterogeneous skill determines spot market skill rental prices. The empirical approach is structural. The model embeds many of the features that have been posited in the literature to have contributed to the changing US wage and employment structure including skill-biased technical change, capital-skill complementarity, changes in relative product-market prices, changes in the productivity of labor in home production and demographics such as changing cohort size and fertility.     

A new sub-national multi-region input–output database for Indonesia

ABSTRACT

As a large archipelago with significant geographical variation and economic diversity, Indonesia requires detailed regional information when subjected to economic modelling. While such information is available, it however has not been integrated and harmonised into a comprehensive input–output database, thus preventing economic, social, and environmental modelling for investigating sub-national regional policy questions. We present the new IndoLab, a collaborative research platform for Indonesia, enabling input–output modelling of economic, social, and environmental issues in a cloud-computing environment. Within the IndoLab researchers are for the first time able to generate a time series of regionally and sectorally detailed and comprehensive, sub-national multi-region input–output (MRIO) tables for Indonesia. By integrating a multitude of economic, social, and environmental data into a single standardised processing pipeline and harmonised data repository, the IndoLab is able to generate MRIO tables capturing up to 1148 sectors, and 495 cities and regencies. Researchers can freely choose from this detail to construct tables with customised classifications that suit their own research questions. First results from the IndoLab clearly demonstrate the unique characteristics of regions in terms of their sectors’ employment intensity. Thus, the IndoLab has great potential for investigating policy questions that cannot be comprehensively addressed using a single national database.     

Which model of technology transfer for nanotechnology? A comparison with biotech and microelectronics

Nanotechnologies are often presented as breakthrough innovations, where technology transfer and knowledge-bridging will play a pivotal role in the industrial dynamics. This article investigates the model of knowledge transfer in the nanotechnologies in depth, by comparing it with the models of two recently emerged technologies: biotech and microelectronics. Our results show that the nanotechnology transfer model is very different from that involved in biotechnology evolution: while small–medium firms play a valuable technology-bringing role, the central function of “translating” new knowledge between public research and industry is carried by the larger firms, just as it was in the early stages of the microelectronics sector. These results suggest that specific policy initiatives to facilitate biotech's transfer are inappropriate to boost the diffusion of nanotechnology.     

A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction

In this study a LASSO – TLBO – SVR hybrid model is used for portfolio construction. Relevant economic parameters are determined and used for stock selection. Along with stock selection, weights for the stocks are obtained by solving a portfolio optimization problem using three methods: GRG Nonlinear, Evolutionary method based on Genetic Algorithm, and Equal weight method. The portfolio return in the proposed model is compared with the return of the Indian market portfolio (NSE and BSE). It is observed that the proposed model outperforms the market portfolio.