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The purpose of this paper is to assess price linkages and patterns of transmission among producer and consumer markets for apple in Slovenia.

Non-linear error correction models are applied. Non-linearities are allowed by means of threshold and multivariate local linear regression estimation techniques. Monthly prices over the period 2000-2011 are used in the empirical application.

Both techniques provide evidence of non-linearities in price adjustments. Findings suggest that producer and consumer prices tend to increase rather than decrease. Results also indicate that parametric threshold approaches may have difficulties in adequately representing price behavior dynamics.

The main contribution of this work to the literature relies on the fact that this is the first attempt to assess vertical price transmission in the apple sector in Central and Eastern European Country markets. Further, it is the first attempt to use multivariate local linear regression techniques in this context.

The purpose of this paper is to propose an interactive 2D–3D garment parametric pattern-making and linkage editing scheme that integrates clothing design, simulation and interaction to design 3D garments and 2D patterns. The proposed scheme has the potential to satisfy the individual needs of fashion industry, such as precise fit evaluation of the garment, interactive style editing with ease allowance and constrained contour lines in fashion design.

The authors first construct a parametric pattern-making model for flat pattern design corresponding to the body dimensions. Then, the designing 2D patterns are stitched on a virtual 3D mannequin by performing a virtual try-on. If the customer is unsatisfied after the virtual try-on, the adjustable parameters (appearance parameters and fit parameters) can be adjusted using the 2D–3D linkage editing with hierarchical constrained contour lines, and the fit evaluation tool interactively provides the feedback.

The authors observed that the usability and efficiency of the existing garment pattern-making method simplifies the garment pattern-making process. The authors utilize an interactive garment parametric flat pattern-making model to generate an individualized garment flat pattern that effectively adjust and realize the local editing of the garment pattern-making. The 2D–3D linkage editing is then employed, which alters the size and shape of garment pattern for a precise human model fit of the 3D garment using hierarchical constrained contour lines. Various instances have validated the effectiveness of the proposed scheme, which can increase the reusability of the existing garment styles and improve the efficiency of fashion design.

First, the authors do not consider the garment pattern-making design of sophisticated styles. Second, the authors do not directly consider complex garment shapes such as wrinkles, folds, multi-layer models and fabric physical properties.

The authors propose a pattern adjustment scheme that uses the 3D virtual try-on technology to avoid repetitions of reality-based fit tests and garment sample making in the designing process of clothing products. The proposed scheme provides interactive selections of garment patterns and sizes and renders modification tools for 3D garment designing and 2D garment pattern-making. The authors present the 2D–3D interactive linkage editing scheme for a custom-fit garment pattern based on the hierarchical constraint contour lines. The spatial relationship among the human body, pattern pieces and 3D garment model is adequately expressed, and the final design result of the garment pattern is obtained by constraint solving. Meanwhile, the tightness tension of different parts of the 3D garment is analyzed, and the fit and comfort of the garment are quantitatively evaluated.

The paper aims to develop a method for improving the accuracy of smart sensors (deemed as digital measuring instruments) by organizing combined measurements and processing their results by the parametric adjustment method at heterogeneous dispersion of the random error of the applied regression model.

When carrying out combined measurements, the problem of joint processing of measurement results of functionally related quantities must be solved. The function type can be known in advance or obtained experimentally. The number of combined measurements exceeds the number of unknown measured quantities. The redundant measurements can improve the accuracy of estimates of measured values but lead to inconsistency of the measurement results. The problem of inconsistency is solved by the parametric adjustment method, which is rather widely used mainly in the field of geodetic measurements, wherein the parametric equations are linear and the measured quantities are additive.

The proposed method allows to reduce the uncertainty of type B of a measurement result, caused by the maximum permissible error of a digital measuring instrument, by 1.2–4 times in comparison with the direct estimation method.

A compact description of the parametric adjustment method in matrix form is given. Recommendations are given on shaping a sensitivity matrix of functions for the proposed method. The geometric interpretation of the proposed method is considered. The results of the proposed method experimental testing are given when evaluating resistance values.

The purpose of this paper is to examine the usefulness of a heuristic expert system, to show its applicability to real‐world valuation problems, and to suggest several avenues for statistical testing.

The expert systems follow a traditional sales adjustment grid format, with sufficient data for non‐parametric testing.

The paper finds that, while non‐parametric statistics provide weaker results than traditional (e.g. hedonic regression) modeling, the technique provides a statistically testable model useful in situations with limited data and/or poorly characterized probability functions.

This paper addresses the conundrum faced by real estate valuers on the lack of statistical underpinnings of traditional heuristic models.

This is one of the first empirical studies in the valuation literature exploring statistical characterization of heuristic valuation methods.

Stochastic models are seldom used when we analyze the stability and the efficiency of enterprise cost systems. Despite of numerous restrictions, along with the complexity of mathematic formalization, this approach would encourage more rational use of resources under conditions of extreme change in external and internal business environments. Different methods of Maximum Likelihood Estimations (MLE) have been introduced to weaken these parametric drawbacks.

However, the high computational complexity makes its use difficult. This work prevailingly demonstrates the use of coenosis theory to design and analyze cost systems of industrial enterprises, including the use of numerically reliable statistical computations.

This approach can also be observed as a delicate parametric adjustment of economic coenosis structures ensuring stability and sustainability. The chapter provides the example of the mentioned methodology within the frame of an ordinary industrial enterprise.

The purpose of this paper is to determine if hedge funds perform poorly as claimed by more recent research. The authors find hedge funds perform well from 2001 to 2013 when compared to sample of firms known to experience superior performance, namely, a sample of seasoned equity offerings (SEOs).

This paper uses a portfolio approach in comparing the performance of hedge funds and SEO firms. Other comparisons involve a number of common methodologies used to compute and analyze short-run and long-run returns.

Contrary to a growing and prevalent belief, the paper offers evidence hedge funds as a whole have performed well for a recent 13-year period. This finding includes periods up to six years around SEO announcement months.

This paper is limited to examining monthly returns for a portfolio of hedge funds. This limitation led to incorporating a portfolio approach.

The findings suggest that a portfolio of hedge funds are an important investment consideration. This consideration has practical implications because investing in a portfolio of hedge funds has become more available for all investors in recent years.

Society can be enhanced as this paper helps future investors make optimal investment decisions.

This paper adds to the hedge fund research by being the first paper to compare the performance of hedge funds with that for firms undergoing an important corporate event. The findings are new and can impact investment decision making.

Selective laser melting (SLM) is increasingly used to manufacture bone implants from titanium alloys with particular interest in porous lattice structures. These complex constructs have been shown to be capable of matching native bone mechanical behaviour leading to improved osseointegration while providing numerous clinical advantages, encouraging their broad use in medical devices. However, producing lattices with a strut diameter similar in scale to a typical SLM melt pool or using the same process parameters and scan strategies intended for bulk solid components may lead to geometric inaccuracies. The purpose of this study is to evaluate and optimise the single contour strategy for the production of Ti-6Al-4V lattices.

Herein, the potential of an unfilled single contour (SC) scanning strategy to improve the reproducibility of porous lattices when compared with a single contour and fill approach (SC + F) is explored. For this purpose, two parametric analysis were carried out on Ti-6Al-4V diamond unit cell lattices with different strut sizes and scan strategies. Porosity and accuracy measurements were correlated with processing parameters and printing strategy to provide the optimal processing window for lattice manufacturing.

SC is shown to be a viable strategy for production of Ti-6Al-4V lattices with a strut diameter below 350 µm. Parametric analysis highlights the limits of this method in producing fully dense struts with energy density presented as a useful practical tool to guide some aspects of parameter selection (design strut diameter achieved at approximately 0.1 J/mm in this study). Finally, a process map combining data from both parametric studies is provided to guide, predict and control lattice strut geometry and porosity obtained using the SC strategy.

These results explore the use of non-standard SC scanning strategy as a viable method for producing strut-based lattice structures and compare against the traditional contour and fill approach (SC + F).

An overview of the cointegration approach to econometric specification and estimation is provided. A non‐technical approach is adopted, and is intended to serve as an entry into this important new literature for the reader with no background knowledge of the subject but with some limited knowledge of econometrics. Particular emphases are given to the rationale for using cointegration techniques in the estimation of economic relationships, to providing intuitive explanations of the concepts and techniques, and to demonstrating their applications in practice. Reference is made throughout to other articles which explain particular methods or recent developments more formally and fully than is possible here. Finally, a simple application of cointegration techniques to the estimation of the consumption function is provided.

The purpose of this paper is to examine the stock price movements for existence of informed trading prior to a merger announcement for the companies listed on the emerging markets of India for the period from 1996 to 2010.

This study applies several event study methodologies and regression analyses to analyze the stock price movement surrounding a merger announcement. The paper divides mergers in two different types: industry merger cases and non-industry merger cases and in two different time periods: recession and boom.

The results show that the information held only by insiders’ works its way into prices. The paper finds strong evidence of insider trading in the case of industry mergers and mergers during recessions.

The results from this study have immediate policy implications for India and other developing markets as the paper provides the type of mergers and time periods when merger announcements are more susceptible to insider trading.

The paper extends the literature on mergers and insider trading by analyzing firms trading on a developing capital market, which, unlike the developed markets, is characterized by inadequate disclosure and a weaker enforcement of securities regulations. The results support this notion and recommend Indian securities market regulators to tighten the lax regulations. In addition, the author document the divergence in price reaction to the merger announcements for different types of mergers: industry mergers and non-industry mergers, as well as for mergers during different market conditions: recession vs booming capital markets.

This study aims to investigate if the level of economic freedom matters for how corruption affects per capita income in US states.

Using a new (and novel) index of corruption, which is based on Associated Press news wires, the author estimates the long-run cointegrating relationship between corruption, economic freedom and per capita income with fully modified ordinary least squares (FMOLS) following Pedroni (2000).

The author finds that there is a threshold level of economic freedom that determines if corruption reduces the per capita income in a state. According to the FMOLS estimations, the negative effects of corruption on income decrease as economic freedom increases, and they eventually disappear.

This is the first study investigating the intricate relationship between corruption, economic freedom and economic performance using data from US states. The study uses a news-based measure of corruption constructed by Dincer and Johnston (2017), which has several advantages over the convictions-based measure used in previous studies analyzing the relationship between corruption and growth using US data. The study takes into account the integration and cointegration properties of the data and estimates the relationship among the cointegrated variables using FMOLS following Pedroni (2000).