The Dynamics of Brand Equity: A Hedonic Regression Approach to the Laser Printer Market

The authors develop a dynamic approach to measuring the evolution of comparative brand premium, an important component of brand equity. A comparative brand premium is defined as the pairwise price difference between two products being identical in every respect but brand. The model is based on hedonic regressions and grounded in economic theory. In constrast to existing approaches, the authors explicitly take into account and model the dynamics of the brand premia. By exploiting the premia’s intertemporal dependence structure, the Bayesian estimation method produces more accurate estimators of the time paths of the brand premia than other methods. In addition, the authors present a novel yet straightforward way to construct confidence bands that cover the entire time series of brand premia with high probability. The data required for estimation are readily available, cheap, and observable on the market under investigation. The authors apply the dynamic hedonic regression to a large and detailed data set about laser printers gathered on a monthly basis over a four-year period. It transpires that, in general, the estimated brand premia change only gradually from period to period. Nevertheless the method can diagnose sudden downturns of a comparative brand premium. The authors’ dynamic hedonic regression approach facilitates the practical evaluation of brand management.brand equity, price premium, hedonic regression, Bayesian estimation, dynamic linear model

Dynamic models in fMRI

Most statistical methods for assessing activated voxels in fMRI experiments are based on correlation or regression analysis. In this context the main assumptions are that the baseline can be described by a few known basis-functions or variables and that the effect of the stimulus, i.e. the activation, stays constant over time. As these assumptions are in many cases neither necessary nor correct, a new dynamic approach that does not depend on those suppositions will be presented. This allows for simultaneous nonparametric estimation of the baseline as well as the time-varying effect of stimulation. This method of estimating the stimulus related areas of the brain furthermore provides the possibility of an analysis of the temporal and spatial development of the activation within an fMRI-experiment

Anatomy of regional price differentials: Evidence from micro price data

Over the last three decades the supply of economic statistics has vastly improved. Unfortunately, statistics on regional price levels (sub-national purchasing power parities) have been exempt from this positive trend, even though they are indispensable for meaningful spatial comparisons of regional output, income, wages, productivity, standards of living, and poverty. To improve the situation, our paper demonstrates that a highly disaggregated and reliable regional price index can be compiled from data that already exist. We use the micro price data that have been collected for Germany's Consumer Price Index in May 2016. For the computation we introduce a multi-stage version of the Country- Product-Dummy method. The unique quality of our price data set allows us to depart from previous spatial price comparisons and to compare only exactly identical products. We find that the price levels of the 402 counties and cities of Germany are largely driven by the cost of housing and to a much lesser degree by the prices of goods and services. The overall price level in the most expensive region, Munich, is about 27 percent higher than in the cheapest region. Our results also reveal strong spatial autocorrelation

Bias and Inefficiency in Quality-Adjusted Hedonic Regression Analysis

Numerous quality-adjusted hedonic price-trend studies based on computer prices have provided support to widely held suspicions that officially released price indices are not accurately measuring the price declines occurring in many information technology (IT) products. If verifiable, then general price inflation is being overestimated and, consequently, real GDP is being underestimated. Existing evidence, however, is inconclusive. First, empirical findings for IT-products other than computers are extremely rare and, secondly, estimation bias is inherent in the hedonic regression technique most commonly employed. This paper presents an unbiased method together with an estimated quality-adjusted price trend for laser printers (1993-2004)

Hedonic Price Measurement: The CCC Method

Abstract An accurate measurement of general price inflation is an essential prerequisite for sound economic analysis and prudent policy-making. Numerous hedonic regression studies (predominately focusing on computers) have suggested that due to significant product quality changes over time, driven onward by technical progress, national statistical agencies are not compiling and releasing unbiased price-trend estimates. This paper argues, however, that the estimation method commonly applied in hedonic studies is an unsatisfactory one. Therefore, an alternative estimation procedure is introduced. Utilizing this novel technique, a quality-adjusted twelve-year pricetrend for laser printers (1992 to 2003) is estimated and compared with the officially published price-trend

Influence of Crop Technology on Yields

Economists measure the influence of variety improvements, fertilizer application, regional specialization and other crop yield factors for seven major United States crops

A Novel Target (Oxidation Resistant 2) in Arabidopsis thaliana to Reduce Clubroot Disease Symptoms via the Salicylic Acid Pathway without Growth Penalties

The clubroot disease (Plasmodiophora brassicae) is one of the most damaging diseases worldwide among brassica crops. Its control often relies on resistant cultivars, since the manipulation of the disease hormones, such as salicylic acid (SA) alters plant growth negatively. Alternatively, the SA pathway can be increased by the addition of beneficial microorganisms for biocontrol. However, this potential has not been exhaustively used. In this study, a recently characterized protein Oxidation Resistant 2 (OXR2) from Arabidopsis thaliana is shown to increase the constitutive pathway of SA defense without decreasing plant growth. Plants overexpressing AtOXR2 (OXR2-OE) show strongly reduced clubroot symptoms with improved plant growth performance, in comparison to wild type plants during the course of infection. Consequently, oxr2 mutants are more susceptible to clubroot disease. P. brassicae itself was reduced in these galls as determined by quantitative real-time PCR. Furthermore, we provide evidence for the transcriptional downregulation of the gene encoding a SA-methyltransferase from the pathogen in OXR2-OE plants that could contribute to the phenotype.Fil: Mencia, Regina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; ArgentinaFil: Welchen, Elina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; ArgentinaFil: Auer, Susann. Technische Universität Dresden; AlemaniaFil: Ludwig Müller, Jutta. Technische Universität Dresden; Alemani

3D LTE spectral line formation with scattering in red giant stars

We investigate the effects of coherent isotropic continuum scattering on the formation of spectral lines in local thermodynamic equilibrium (LTE) using 3D hydrodynamical and 1D hydrostatic model atmospheres of red giant stars. Continuum flux levels, spectral line profiles and curves of growth for different species are compared with calculations that treat scattering as absorption. Photons may escape from deeper, hotter layers through scattering, resulting in significantly higher continuum flux levels beneath a wavelength of 5000 A. The magnitude of the effect is determined by the importance of scattering opacity with respect to absorption opacity; we observe the largest changes in continuum flux at the shortest wavelengths and lowest metallicities; intergranular lanes of 3D models are more strongly affected than granules. Continuum scattering acts to increase the profile depth of LTE lines: continua gain more brightness than line cores due to their larger thermalization depth in hotter layers. We thus observe the strongest changes in line depth for high-excitation species and ionized species, which contribute significantly to photon thermalization through their absorption opacity near the continuum optical surface. Scattering desaturates the line profiles, leading to larger abundance corrections for stronger lines, which reach -0.5 dex at 3000 A for Fe II lines in 3D with excitation potential 2 eV at [Fe/H]=-3.0. The corrections are less severe for low-excitation lines, longer wavelengths, and higher metallicity. Velocity fields increase the effects of scattering by separating emission from granules and intergranular lanes in wavelength. 1D calculations exhibit similar scattering abundance corrections for weak lines, but those for strong lines are generally smaller compared to 3D models and depend on the choice of microturbulence.Comment: Astronomy & Astrophysics, Volume 529, 05/201

Assessing Brain Activity through Spatial Bayesian Variable Selection

Statistical parametric mapping (SPM), relying on the general linear model and classical hypothesis testing, is a benchmark tool for assessing human brain activity using data from fMRI experiments. Friston et al. (2002a) discuss some limitations of this frequentist approach and point out promising Bayesian perspectives. In particular, a Bayesian formulation allows explicit modeling and estimation of activation probabilities. In this paper, we directly address this issue and develop a new regression based approach using spatial Bayesian variable selection. Our method has several advantages. First, spatial correlation is directly modeled for activation probabilities and indirectly for activation amplitudes. As a consequence, there is no need for spatial adjustment in a post-processing step. Second, anatomical prior information, such as the distribution of grey matter or expert knowledge, can be included as part of the model. Third, the method has superior edge-preservation properties as well as being fast to compute. When applied to data from a simple visual experiment, the results demonstrate improved sensitivity for detecting activated cortical areas and for better preserving details of activated structures