Fonte: Aqui
14 outubro 2016
13 outubro 2016
Samsung
Os problemas da empresa coreana com seu celular Galaxy Note 7 - que estaria explodindo, segundo alguns relatos - pode ter influencia sobre o resultado da empresa:
A Samsung reduziu sua estimativa de lucro do terceiro trimestre em um terço nesta quarta-feira, 12, absorvendo um impacto de US$ 2,3 bilhões ao descartar o smartphone que é seu carro-chefe – o que pode representar uma das falhas de segurança de produto mais custosas da história da tecnologia.
A estimativa é somente para redução da receita da empresa. Eventuais danos para marca e a venda de produtos da empresa é mais difícil de ser quantificado.
A Samsung reduziu sua estimativa de lucro do terceiro trimestre em um terço nesta quarta-feira, 12, absorvendo um impacto de US$ 2,3 bilhões ao descartar o smartphone que é seu carro-chefe – o que pode representar uma das falhas de segurança de produto mais custosas da história da tecnologia.
A estimativa é somente para redução da receita da empresa. Eventuais danos para marca e a venda de produtos da empresa é mais difícil de ser quantificado.
Margem de erro real das eleições: 7%
As anyone who follows election polling can tell you, when you survey 1,000 people, the margin of error is plus or minus three percentage points. This roughly means that 95 percent of the time, the survey estimate should be within three percentage points of the true answer.
If 54 percent of people support Hillary Clinton, the survey estimate might be as high as 57 percent or as low as 51 percent, but it is unlikely to be 49 percent. This truism of modern polling, heralded as one of the great success stories of statistics, is included in textbooks and taught in college classes, including our own.
But the real-world margin of error of election polls is not three percentage points. It is about twice as big.
In a new paper with Andrew Gelman and Houshmand Shirani-Mehr, we examined 4,221 late-campaign polls — every public poll we could find — for 608 state-level presidential, Senate and governor’s races between 1998 and 2014. Comparing those polls’ results with actual electoral results, we find the historical margin of error is plus or minus six to seven percentage points. (Yes, that’s an error range of 12 to 14 points, not the typically reported 6 or 7.)
If 54 percent of people support Hillary Clinton, the survey estimate might be as high as 57 percent or as low as 51 percent, but it is unlikely to be 49 percent. This truism of modern polling, heralded as one of the great success stories of statistics, is included in textbooks and taught in college classes, including our own.
But the real-world margin of error of election polls is not three percentage points. It is about twice as big.
In a new paper with Andrew Gelman and Houshmand Shirani-Mehr, we examined 4,221 late-campaign polls — every public poll we could find — for 608 state-level presidential, Senate and governor’s races between 1998 and 2014. Comparing those polls’ results with actual electoral results, we find the historical margin of error is plus or minus six to seven percentage points. (Yes, that’s an error range of 12 to 14 points, not the typically reported 6 or 7.)
12 outubro 2016
O que torna um preço justo?
Resumo:
People's fairness preferences are an important constraint for what constitutes an acceptable economic transaction, yet little is known about how these preferences are formed. In this paper, we provide clean evidence that previous transactions play an important role in shaping perceptions of fairness. Buyers used to high market prices, for example, are more likely to perceive high prices as fair than buyers used to low market prices. Similarly, employees used to high wages are more likely to perceive low wages as unfair. Our data further allows us to decompose this history dependence into the effects of pure observation vs. the experience of payoff-relevant outcomes. We propose two classes of models of path-dependent fairness preferences—either based on endogenous fairness reference points or based on shifts in salience—that can account for our data. Structural estimates of both types of models imply a substantial deviation from existing history-independent models of fairness. Our results have implications for price discrimination, labor markets, and dynamic pricing.
Fonte: What Makes a Price Fair? An Experimental Analysis of Market Experience and EndogenousFairness ViewsHolger Herz and Dmitry Taubinsky NBER Working Paper No. 22728 October 2016
People's fairness preferences are an important constraint for what constitutes an acceptable economic transaction, yet little is known about how these preferences are formed. In this paper, we provide clean evidence that previous transactions play an important role in shaping perceptions of fairness. Buyers used to high market prices, for example, are more likely to perceive high prices as fair than buyers used to low market prices. Similarly, employees used to high wages are more likely to perceive low wages as unfair. Our data further allows us to decompose this history dependence into the effects of pure observation vs. the experience of payoff-relevant outcomes. We propose two classes of models of path-dependent fairness preferences—either based on endogenous fairness reference points or based on shifts in salience—that can account for our data. Structural estimates of both types of models imply a substantial deviation from existing history-independent models of fairness. Our results have implications for price discrimination, labor markets, and dynamic pricing.
Fonte: What Makes a Price Fair? An Experimental Analysis of Market Experience and EndogenousFairness ViewsHolger Herz and Dmitry Taubinsky NBER Working Paper No. 22728 October 2016
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