2,515 research outputs found

    Unemployment and Hysteresis: A Nonlinear Unobserved Components A Nonlinear Unobserved Components A Nonlinear Unobserved Components A Nonlinear Unobserved Components A Nonlinear Unobserved Components Approach

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    A new test for hysteresis based on a nonlinear unobserved components model is proposed. Observed unemployment rates are decomposed into a natural rate component and a cyclical component. Threshold type nonlinearities are introduced by allowing past cyclical unemployment to have a different impact on the natural rate depending onthe regime of the economy. The impact of lagged cyclical shocks on thecurrent natural component is the measure of hysteresis. To derive anappropriate p-value for a test for hysteresis two alternative bootstrapalgorithms are proposed: the first is valid under homoskedastic errorsand the second allows for heteroskedasticity of unknown form. A MonteCarlo simulation study shows the good performance of both bootstrapalgorithms. The bootstrap testing procedure is applied to data fromItaly, France and the United States. We find evidence of hysteresis forall countries under study.Hysteresis, Unobserved Components Model, Threshold Autoregressive Models, Nuisance parameters, Bootstrap

    AIDS VERSUS ROTTERDAM: A COX NONNESTED TEST WITH PARAMETRIC BOOTSTRAP

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    A Cox nonnested test with parametric bootstrap is developed to select between the linearized version of the First Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. The Cox test with parametric bootstrap is expected to be more powerful than the various orthodox tests used in past research. The new approach is then used for U. S. meat demand (beef, pork, and chicken) and compared to results obtained with an orthodox test. The orthodox test gives inconsistent results. In contrast, under the same varied conditions, the Cox test with parametric bootstrap consistently indicates that the Rotterdam model is preferred to the FDAIDS.Demand and Price Analysis,

    Bootstrap Methods for Inference in a SUR model with Autocorrelated Disturbances

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    Although the Parks (1967) estimator for a SUR model with AR disturbances is efficient both asymptotically and in small samples, Kmenta and Gilbert (1970) and more recently Beck and Katz (1995) note that estimated standard errors tend to be biased downward as compared with the true variability of the estimates. This bias leads to tests that show over-rejection and to confidence intervals that are too small. We suggest bootstrapping the tests to correct this inference problem. After illustrating the over rejection associated with the estimated asymptotic standard errors, we develop a bootstrap approach to inference for this model, illustrate its use, and show using Monte Carlo methods that the bootstrap gives rejection probabilities close to the nominal level chosen by the researcher.

    Nonlinear Exchange Rate Adjustment in the Enlarged Euro zone. Evidence and Implications for Candidate Countries.

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    This paper sheds light on the importance of the validity of PPP hypothesis for the accessing process of the candidate countries towards EMU. The evidence of nonlinear adjustment in real exchange rates insists the estimation of a nonlinear SETAR model. While linear half-life estimates are biased upward (5 years on average), SETAR half-life estimates imply a faster reverting process (1.5 years on average). As a consequence, the evidence in favor of PPP hypothesis and the fast equilibrium adjustment of real exchange rates (setting Euro as the numeraire currency) imply that candidate countries follow a normal integration process towards EMU.EMU enlargement; PPP; Half-life; Nonlinearity; SETAR.

    Detecting Unspecified Structure in Low-Count Images

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    Unexpected structure in images of astronomical sources often presents itself upon visual inspection of the image, but such apparent structure may either correspond to true features in the source or be due to noise in the data. This paper presents a method for testing whether inferred structure in an image with Poisson noise represents a significant departure from a baseline (null) model of the image. To infer image structure, we conduct a Bayesian analysis of a full model that uses a multiscale component to allow flexible departures from the posited null model. As a test statistic, we use a tail probability of the posterior distribution under the full model. This choice of test statistic allows us to estimate a computationally efficient upper bound on a p-value that enables us to draw strong conclusions even when there are limited computational resources that can be devoted to simulations under the null model. We demonstrate the statistical performance of our method on simulated images. Applying our method to an X-ray image of the quasar 0730+257, we find significant evidence against the null model of a single point source and uniform background, lending support to the claim of an X-ray jet

    A Likelihood Ratio Test of Stationarity Based on a Correlated Unobserved Components Model

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    We propose a likelihood ratio (LR) test of stationarity based on a widely-used correlated unobserved components model. We verify the asymptotic distribution and consistency of the LR test, while a bootstrap version of the test is at least first-order accurate. Given empirically-relevant processes estimated from macroeconomic data, Monte Carlo analysis reveals that the bootstrap version of the LR test has better small-sample size control and higher power than commonly used bootstrap Lagrange multiplier (LM) tests, even when the correct parametric structure is specified for the LM test. A key feature of our proposed LR test is its allowance for correlation between permanent and transitory movements in the time series under consideration, which increases the power of the test given the apparent presence of non-zero correlations for many macroeconomic variables. Based on the bootstrap LR test, and in some cases contrary to the bootstrap LM tests, we can reject trend stationarity for U.S. real GDP, the unemployment rate, consumer prices, and payroll employment in favor of nonstationary processes with volatile stochastic trends.Stationarity Test, Likelihood Ratio, Unobserved Components, Parametric Bootstrap, Monte Carlo Simulation, Small-Sample Inference

    A Joint Test of Price Discrimination, Menu Cost and Currency Invoicing

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    This paper investigates price discriminating behaviour and currency invoicing decisions of Canadian pork exporters in the presence of menu costs. It is shown that when export prices are negotiated in the exporter’s currency, menu costs cause threshold effects in the sense that there are bounds within (outside of) which price adjustments are not (are) observed. Conversely, the pass-through is not interrupted by menu costs when export prices are denominated in the importer’s currency. The empirical model focuses on pork meat exports from two Canadian provinces to the U.S. and Japan. Hansen’s (2000) threshold estimation procedure is used to jointly test for currency invoicing and incomplete pass-through in the presence of menu costs. Inference is conducted using the bootstrap with pre-pivoting methods to deal with nuisance parameters. The existence of menu cost is supported by the data in three of the four cases. It also appears that Quebec pork exporters price discriminate and invoice in Japanese yen their exports to Japan. Manitoba exporters also seem to follow the same invoicing strategy, but their ability to increase their profit margin in response to large enough own-currency devaluations is questionable. Our currency invoicing results for sales to the U.S. are consistent with subsets of Canadian firms using either the Canadian or U.S. currency.

    Disentangling non-linearities in the long- and short-run price relationships: An application to the U.S. hog/Pork supply chain

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    Increased concentration at the retail, food processing and farm input manufacturing levels has brought increased attention to patterns in retail-to-farm price spreads. Most studies documenting asymmetric price transmission focus on non-linear error correction processes, as opposed to the current study which analyzes potential non-linearities in the long-run relationship between the farm and retail prices. The null hypothesis of non-linearity in the long-run relationship between farm and retail prices in the U.S. hog/pork supply chain is rejected in favor of a Smooth Transition Cointegration (STC) framework. The STC framework predicts downward price stickiness in retail prices. The predicted residuals of the non-linear model are used to investigate whether it is possible to disentangle non-linearity in the long-run price relationship from non-linearity in the adjustment towards the long-run equilibrium. The results underline the importance of testing for linearity in the long-run price relationship before modeling non-linearity in short-run dynamics.Smooth transition cointegration; farm to retail price transmission; linear cointegration

    Testing for fractional cointegration: the relationship between government popularity and economic performance in the UK

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    Author's draft (March 2003) of chapter published in New Trends in Macroeconomics, Claude Diebolt, Catherine Kyrtsou, editors, Springer Verlag (2005
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