25 resultados para Markov-switching modelate


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This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of technology shocks in explaining aggregate fluctuations. To this end we estimate the model’s posterior density using Markov-Chain Monte-Carlo (MCMC) methods. Within this framework we extend Ireland’s (2001, 2004) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model’s errors not explained by the basic RBC model. The results of marginal likelihood ratio tests reveal that the more general model of the errors significantly improves the model’s fit relative to the VAR and AR alternatives. Moreover, despite setting the RBC model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions, suggests that the RBC model is still capable of explaining a significant fraction of the observed variation in macroeconomic aggregates in the post-war U.S. economy.

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This paper develops a general theoretical framework within which a heterogeneous group taxpayers confront a market that supplies a variety of schemes for reducing tax liability, and uses this framework to explore the impact of a wide range of anti-avoidance policies. Schemes differ in their legal effectiveness and hence in the risks to which they expose taxpayers - risks which go beyond the risk of audit considered in the conventional literature on evasion. Given the individual taxpayer’s circumstances, the prices charged for the schemes and the policy environment, the model predicts (i) whether or not any given taxpayer will acquire a scheme, and (ii) if they do so, which type of scheme they will acquire. The paper then analyses how these decisions, and hence the tax gap, are influenced by four generic types of policy: Disclosure – earlier information leading to faster closure of loopholes; Penalties – introduction of penalties for failed avoidance; Policy Design – fundamental policy changes that design out opportunities for avoidance; Product Register - the introduction of GAARs or mini-GAARs that give greater clarity about how different types of scheme will be treated. The paper shows that when considering the indirect/behavioural effects of policies on the tax gap it is important to recognise that these operate on two different margins. First policies will have deterrence effects – their impact on the quantum of taxpayers choosing to acquire different types schemes as distinct to acquiring no scheme at all. There will be a range of such deterrence effects reflecting the range of schemes available in the market. But secondly, since different schemes generate different tax gaps, policies will also have switching effects as they induce taxpayers who previously acquired one type of scheme to acquire another. The first three types of policy generate positive deterrence effects but differ in the switching effects they produce. The fourth type of policy produces mixed deterrence effects.

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This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

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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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The implications of local currency pricing (LCP) for monetary regime choice are analysed for a country facing foreign monetary shocks. In this analysis expenditure switching is potentially welfare reducing. This contrasts with the existing LCP literature, which focuses on productivity shocks and thus analyses a world where expenditure switching is welfare enhancing. This paper shows that, when home and foreign producers follow LCP, expenditure switching is absent and a floating rate is preferred by the home country. But when only home producers follow LCP, expenditure switching is present and a fixed rate can be welfare enhancing for the home country.

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We propose an elementary theory of wars fought by fully rational contenders. Two parties play a Markov game that combines stages of bargaining with stages where one side has the ability to impose surrender on the other. Under uncertainty and incomplete information, in the unique equilibrium of the game, long confrontations occur: war arises when reality disappoints initial (rational) optimism, and it persist longer when both agents are optimists but reality proves both wrong. Bargaining proposals that are rejected initially might eventually be accepted after several periods of confrontation. We provide an explicit computation of the equilibrium, evaluating the probability of war, and its expected losses as a function of i) the costs of confrontation, ii) the asymmetry of the split imposed under surrender, and iii) the strengths of contenders at attack and defense. Changes in these parameters display non-monotonic effects.

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This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

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This paper studies the aggregate and distributional implications of Markov-perfect tax-spending policy in a neoclassical growth model with capitalists and workers. Focusing on the long run, our main fi ndings are: (i) it is optimal for a benevolent government, which cares equally about its citizens, to tax capital heavily and to subsidise labour; (ii) a Pareto improving means to reduce ine¢ ciently high capital taxation under discretion is for the government to place greater weight on the welfare of capitalists; (iii) capitalists and workers preferences, regarding the optimal amount of "capitalist bias", are not aligned implying a conflict of interests.

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In an input-output context the impact of any particular industrial sector is commonly measured in terms of the output multiplier for that industry. Although such measures are routinely calculated and often used to guide regional industrial policy the behaviour of such measures over time is an area that has attracted little academic study. The output multipliers derived from any one table will have a distribution; for some industries the multiplier will be relatively high, for some it will be relatively low. The recentpublication of consistent input-output tables for the Scottish economy makes it possible to examine trends in this mdistribution over the ten year period 1998-2007. This is done by comparing the means and other summary measures of the distributions, the histograms and the cumulative densities. The results indicate a tendency for the multipliers to increase over the period. A Markov chain modelling approach suggests that this drift is a slow but long term phenomenon which appears not to tend to an equilibrium state. The prime reason for the increase in the output multipliers is traced to a decline in the relative importance of imported (both from the rest of the UK and the rest of the world) intermediate inputs used by Scottish industries. This suggests that models calibrated on the set of tables might have to be interpreted with caution.

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Vector Autoregressive Moving Average (VARMA) models have many theoretical properties which should make them popular among empirical macroeconomists. However, they are rarely used in practice due to over-parameterization concerns, difficulties in ensuring identification and computational challenges. With the growing interest in multivariate time series models of high dimension, these problems with VARMAs become even more acute, accounting for the dominance of VARs in this field. In this paper, we develop a Bayesian approach for inference in VARMAs which surmounts these problems. It jointly ensures identification and parsimony in the context of an efficient Markov chain Monte Carlo (MCMC) algorithm. We use this approach in a macroeconomic application involving up to twelve dependent variables. We find our algorithm to work successfully and provide insights beyond those provided by VARs.