878 resultados para Price Spike


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Consumers often pay different prices for the same product bought in the same store at the same time. However, the demand estimation literature has ignored that fact using, instead, aggregate measures such as the “list” or average price. In this paper we show that this will lead to biased price coefficients. Furthermore, we perform simple comparative statics simulation exercises for the logit and random coefficient models. In the “list” price case we find that the bias is larger when discounts are higher, proportion of consumers facing discount prices is higher and when consumers are more unwilling to buy the product so that they almost only do it when facing discount. In the average price case we find that the bias is larger when discounts are higher, proportion of consumers that have access to discount are similar to the ones that do not have access and when consumers willingness to buy is very dependent on idiosyncratic shocks. Also bias is less problematic in the average price case in markets with a lot of bargain deals, so that prices are as good as individual. We conclude by proposing ways that the econometrician can reduce this bias using different information that he may have available.

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This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.

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How have shocks to supply and demand affected global oil prices; and what are key policy implications following the resurgence of oil production in the United States? Highlights: − The recent collapse in global oil prices was dominated by oversupply. − The future of tight oil in the United States is vulnerable to obstacles beyond oil prices. − Opinions on tight oil from the Top 25 think tank organizations are considered. Global oil prices have fallen more than fifty percent since mid-2014. While price corrections in the global oil markets resulted from multiple factors over the past twelve months, surging tight oil production from the United States was a key driver. Tight oil is considered an unconventional or transitional oil source due to its location in oil-bearing shale instead of conventional oil reservoirs. These qualities make tight oil production fundamentally different from regular crude, posing unique challenges. This case study examines these challenges and explores how shocks to supply and demand affect global oil prices while identifying important policy considerations. Analysis of existing evidence is supported by expert opinions from more than one hundred scholars from top-tier think tank organizations. Finally, implications for United States tight oil production as well as global ramifications of a new low price environment are explored.

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Ajuste assimétrico de preço é observado em diversos mercados, notavelmente varejo de gasolina: um aumento de custo é passado para os consumidores mais rápido do que uma redução. Eu desenvolvo um modelo de busca dos consumidores que gera essa predição sob aversão à perda. Uma fração dos consumidores ignora os preços no mercado e pode adquirir informação a um custo, o que permite que as firmas tenham lucro com dispersão de preços. Ajuste assimétrico de preço emerge se os consumidores são aversos a perdas em relação a um preço de referência. Custos mais altos tornam os consumidores mais dispostos a procurar, mas também diminui as chances de encontrar preços baixos, gerando uma relação custo-preço convexa.

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In field experiments with subjects living either inside or outside Brazilian slums (n=955), we show that consumers living in slums are less price sensitive, in opposition with recent price sensitivity research. Comparing slum and non-slum dwellers, we found that negatively stereotyped consumers (e.g. slum dwellers) were more likely to pay higher amounts for friendlier customer service when facing social identity threats (SITs) in marketplaces such as banks. The mechanism which makes them less price sensitive is related to the perception of how other people evaluate their social groups, and we argue that they pay more because they are seeking identity-safe commercial relationships. This work, besides extending the literature in SITs, presents a perspective for the exchange between economics and psychology on price sensitivity, showing that consumers living in slums are willing to pay more to avoid possibly social identity threating experiences.

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Increasing competition caused by globalization, high growth of some emerging markets and stagnation of developed economies motivate Consumer Packaged Goods (CPGs) manufacturers to drive their attention to emerging markets. These companies are expected to adapt their marketing activities to the particularities of these markets in order to succeed. In a country classified as emerging market, regions are not alike and some contrasts can be identified. In addition, divergences of marketing variables effect can also be observed in the different retail formats. The retail formats in emerging markets can be segregated in chain self-service and traditional full-service. Thus, understanding the effectiveness of marketing mix not only in country aggregated level data can be an important contribution. Inasmuch as companies aim to generate profits from emerging markets, price is an important marketing variable in the process of creating competitive advantage. Along with price, promotional variables such as in-store displays and price cut are often viewed as temporary incentives to increase short-term sales. Managers defend the usage of promotions as being the most reliable and fastest manner to increase sales and then short-term profits. However, some authors alert about sales promotions disadvantages; mainly in the long-term. This study investigates the effect of price and in-store promotions on sales volume in different regions within an emerging market. The database used is at SKU level for juice, being segregated in the Brazilian northeast and southeast regions and corresponding to the period from January 2011 to January 2013. The methodological approach is descriptive quantitative involving validation tests, application of multivariate and temporal series analysis method. The Vector-Autoregressive (VAR) model was used to perform the analysis. Results suggest similar price sensitivity in the northeast and southeast region and greater in-store promotion sensitivity in the northeast. Price reductions show negative results in the long-term (persistent sales in six months) and in-store promotion, positive results. In-store promotion shows no significant influence on sales in chain self-service stores while price demonstrates no relevant impact on sales in traditional full-service stores. Hence, this study contributes to the business environment for companies wishing to manage price and sales promotions for consumer brands in regions with different features within an emerging market. As a theoretical contribution, this study fills an academic gap providing a dedicated price and sales promotion study to contrast regions in an emerging market.

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The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent t~3=2. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

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This paper describes a branch-and-price algorithm for the p-median location problem. The objective is to locate p facilities (medians) such as the sum of the distances from each demand point to its nearest facility is minimized. The traditional column generation process is compared with a stabilized approach that combines the column generation and Lagrangean/surrogate relaxation. The Lagrangean/surrogate multiplier modifies; the reduced cost criterion, providing the selection of new productive columns at the search tree. Computational experiments are conducted considering especially difficult instances to the traditional column generation and also with some large-scale instances. (C) 2004 Elsevier Ltd. All rights reserved.

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Relata-se a ocorrência de Learedius learedi Price 1934 (Digenea, Spirorchiidae) em Chelonia mydas Linnaeus 1758 (Testudines, Chelonidae) no Brasil. Onze animais foram examinados e destes, 54,6% estavam parasitados. Duzentos e cinqüenta e cinco exemplares de L. learedi foram recuperados de órgãos (coração, fígado, baço, pulmões, rins, mesentério) e do lavado corporal dos animais. Os resultados contribuem para o conhecimento da helmintofauna de quelônios marinhos e sua distribuição geográfica. Este é o primeiro registro da ocorrência de L. learedi na região do Atlântico Sul Ocidental.

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We investigate the Heston model with stochastic volatility and exponential tails as a model for the typical price fluctuations of the Brazilian São Paulo Stock Exchange Index (IBOVESPA). Raw prices are first corrected for inflation and a period spanning 15 years characterized by memoryless returns is chosen for the analysis. Model parameters are estimated by observing volatility scaling and correlation properties. We show that the Heston model with at least two time scales for the volatility mean reverting dynamics satisfactorily describes price fluctuations ranging from time scales larger than 20min to 160 days. At time scales shorter than 20 min we observe autocorrelated returns and power law tails incompatible with the Heston model. Despite major regulatory changes, hyperinflation and currency crises experienced by the Brazilian market in the period studied, the general success of the description provided may be regarded as an evidence for a general underlying dynamics of price fluctuations at intermediate mesoeconomic time scales well approximated by the Heston model. We also notice that the connection between the Heston model and Ehrenfest urn models could be exploited for bringing new insights into the microeconomic market mechanics. (c) 2005 Elsevier B.V. All rights reserved.

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Includes bibliography.

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Includes bibliography