776 research outputs found

    The Central Bank Inflation Bias in the Presence of Asymmetric Preferences and Non-Normal Shocks

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    We investigate the nature of the inflation bias in a model that exhibits asymmetries in preferences and nonā€“normality in shocks but simplifies to the classic Barro-Gordon problem as a special case. The inflation bias is shown to depend on the trade-off between preference, structural and the scale and shape parameters of the model.

    THE PROCESS FOLLOWED BY PPP DATA. ON THE PROPERTIES OF LINEARITY TESTS

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    Recent research has reported the lack of correct size in stationarity test for PPP deviations within a linear framework. However, theoretically well motivated nonlinear models, such as the ESTAR, appear to parsimoniously fit the PPP data and provide an explanation for the PPP ĀæpuzzleĀæ. Employing Monte Carlo experiments we analyze the size and power of the nonlinear tests against a variety of nonstationary hypotheses. We also fit the ESTAR model to data from high inflation economies. Our results provide further support for ESTAR specification.ESTAR, Real Exchange Rate, Size, Linearity Test.

    NONLINEAR PPP UNDER THE GOLD STANDARD

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    Hegwood and Papell (2002) conclude on the basis of analysis in a linear framework that long-run purchasing power parity (PPP)\ does not hold for sixteen real exchange rate series, analyzed in Diebold, Husted, and Rush (1991) for the period 1792-1913, under the Gold Standard. Rather, purchasing power parity deviations are mean-reverting to a changing equilibrium -a quasi PPP (QPPP) theory. We analyze the real exchange rate adjustment mechanism for their data set assuming a nonlinear adjustment process allowing for both a constant and a mean shifting equilibrium. Our results confirm that real exchange rates at that time were stationary, symmetric, nonlinear processes that revert to a non-constant equilibrium rate. Speeds of adjustment were much quicker when breaks were allowed.Purchasing Power Parity, ESTAR, Bootstrapping.

    TEMPORAL AGGREGATION OF AN ESTAR PROCESS: SOME IMPLICATIONS FOR PURCHASING POWER PARITY ADJUSTMENT

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    Nonlinear models of deviations from PPP have recently provided an important, theoretically well motivated, contribution to the PPP puzzle. Most of these studies use temporally aggregated data to empirically estimate the nonlinear models. As noted by Taylor (2001), if the true DGP is nonlinear, the temporally aggregated data could exhibit misleading properties regarding the adjustment speeds. We examine the effects of different levels of temporal aggregation on\ estimates of ESTAR models of real exchange rates. Our Monte Carlo results show that temporal aggregation does not imply the disappearance of nonlinearity and that adjustment speeds are significantly slower in temporally aggregated data than in the true DGP. Furthermore, the autoregressive structure of some monthly ESTAR estimates found in the literature is suggestive that adjustment speeds are even faster than implied by the monthly estimates.ESTAR, Real Exchange Rate, Purchasing Power Parity, Aggregation.

    Cumulative prospect theory and gambling

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    Whilst Cumulative Prospect theory (CPT) provides an explanation of gambling on longshots at actuarially unfair odds, it cannot explain why people might bet on more favoured outcomes. This paper shows that this is explicable if the degree of loss aversion experienced by the agent is reduced for small-stake gambles (as a proportion of wealth), and probability distortions are greater over losses than gains. If the utility or value function is assumed to be bounded, the degree of loss aversion assumed by Kahneman and Tversky leads to absurd predictions, reminiscent of those pointed out by Rabin (2000), of refusal to accept infinite gain bets at low probabilities. Boundedness of the value function in CPT implies that the indifference curve between expected-return and win-probability will typically exhibit both an asymptote (implying rejection of an infinite gain bet) and a minimum at low probabilities, as the shape of the value function dominates the probability weighting function. Also the high probability section of the indifference curve will exhibit a maximum. These implications are consistent with outcomes observed in gambling markets.

    Introduction: Economics of Betting Markets

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    Bounded Cumulative Prospect Theory: Some Implications for Gambling Outcomes

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    Standard parametric specifications of Cumulative Prospect theory (CPT) can explain why agents bet on longshots at actuarially unfair odds. However the standard specification of CPT cannot explain why people might bet on more favored outcomes, where by construction the greatest volume of money is bet. This paper outlines a parametric specification than can consistently explain gambling over all outcomes. In particular we assume that the value function is bounded from above and below and that the degree of loss aversion experienced by the agent is smaller for small-stake gambles (as a proportion of wealth) than usually assumed in CPT. There are a number of new implications of this specification. Boundedness of the value function in CPT implies that the indifference curve between expected-return and win-probability for a given stake will typically exhibit both an asymptote (implying rejection of an infinite gain bet) and a minimum, as the shape of the value function dominates the probability weighting function. Also the high probability section of the indifference curve will exhibit a maximum

    The long memory model of political support: some further results

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    This paper extends the results of Byers, Davidson and Peel (1997) on long memory in support for the Conservative and Labour Parties in the UK using longer samples and additional poll series. It finds continuing support for the ARFIMA(0,d,0) model though with somewhat smaller values of the long memory parameter. We find that the move to telephone polling in the mid-1990s has no apparent effect on the estimated value of d for either party. Finally, we find that we cannot reject the hypotheses that the parties share a common long memory parameter which we estimate at around 0.65.
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