7 resultados para hidden dividend

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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We re-examine the dynamics of returns and dividend growth within the present-value framework of stock prices. We find that the finite sample order of integration of returns is approximately equal to the order of integration of the first-differenced price-dividend ratio. As such, the traditional return forecasting regressions based on the price-dividend ratio are invalid. Moreover, the nonstationary long memory behaviour of the price-dividend ratio induces antipersistence in returns. This suggests that expected returns should be modelled as an AFIRMA process and we show this improves the forecast ability of the present-value model in-sample and out-of-sample.

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Using data from the International Revenue Service, this paper explores the effcts of corporate taxation on U.S. capital invested abroad and on tax planning practices (dividend payments, income shifting, and passive investment). The econometric analysis first indicates that investment is strongly influenced by average tax rates, with a magnified impact for particularly low-tax rates implying that the attractiveness of low-tax countries is not weakened by anti-deferral rules and cross-crediting limitations. Further explorations suggest that firms report higher profit and are less likely to repatriate dividends when they are located in low-tax jurisdictions. Firms also report higher Subpart F income in countries in which they shift their profit, suggesting that cross-crediting provides an incentive to shift passive income in low-tax countries and that passive investment can be an alternative strategy to minimize taxes when active investment opportunities are lacking. Finally, the paper estimates the role of effective transfer pricing regulation on income shifting activities using the quality of host countries' law enforcement. It appears that low degrees of law enforcement are associated with higher income-shifting.

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While much of the literature on cross section dependence has focused mainly on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful interpretation and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England’s monetary policy committee.

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This paper uses an infinite hidden Markov model (IIHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found a clear structural break during the recent financial crisis. Prior to that, inflation persistence was high and fairly constant.

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This paper presents a model of a self-fulfilling price cycle in an asset market. Price oscillates deterministically even though the underlying environment is stationary. The mechanism that we uncover is driven by endogenous variation in the investment horizons of the different market participants, informed and uninformed. On even days, the price is high; on odd days it is low. On even days, informed traders are willing to jettison their good assets, knowing that they can buy them back the next day, when the price is low. The anticipated drop in price more than offsets any potential loss in dividend. Because of these asset sales, the informed build up their cash holdings. Understanding that the market is flooded with good assets, the uninformed traders are willing to pay a high price. But their investment horizon is longer than that of the informed traders: their intention is to hold the assets they purchase, not to resell. On odd days, the price is low because the uninformed recognise that the informed are using their cash holdings to cherry-pick good assets from the market. Now the uninformed, like the informed, are investing short-term. Rather than buy-and-hold as they do with assets purchased on even days, on odd days the uninformed are buying to sell. Notice that, at the root of the model, there lies a credit constraint. Although the informed are flush with cash on odd days, they are not deep pockets. On each cherry that they pick out of the market, they earn a high return: buying cheap, selling dear. However they don't have enough cash to strip the market of cherries and thereby bid the price up.

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Currently, financial economics is unable to predict changes in asset prices with respect to changes in the underlying risk factors, even when an asset's dividend is independent of a given factor. This paper takes steps towards addressing this issue by highlighting a crucial component of wealth effects on asset prices hitherto ignored by the literature. Changes in wealth do not only alter an agents risk aversion, but also her perceived 'riskiness' of a security. The latter enhances significantly the extent to which market- clearing leads to endogenously-generated correlation across asset prices, over and above that induced by correlation between payoffs, giving the appearance of 'contagion.'

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This paper develops a new test of true versus spurious long memory, based on log-periodogram estimation of the long memory parameter using skip-sampled data. A correction factor is derived to overcome the bias in this estimator due to aliasing. The procedure is designed to be used in the context of a conventional test of significance of the long memory parameter, and composite test procedure described that has the properties of known asymptotic size and consistency. The test is implemented using the bootstrap, with the distribution under the null hypothesis being approximated using a dependent-sample bootstrap technique to approximate short-run dependence following fractional differencing. The properties of the test are investigated in a set of Monte Carlo experiments. The procedure is illustrated by applications to exchange rate volatility and dividend growth series.