Cointegration and the joint confirmation hypothesis

Recent papers by Charemza and Syczewska (1998) and Carrion, Sansó and Ortuño (2001) focused on the joint use of unit root and stationarity tests. In this paper, the discussion is extended to the case of cointegration. Critical values for testing the joint confirmation hypothesis of no cointegration are computed and a small Monte Carlo experiment evaluates the relative performance of this procedure.Cointegration; Joint confirmation hypothesis; Monte Carlo simulations.

An Efficient Test of Fiscal Sustainability

We suggest a multivariate efficient test of the 'strong' fiscal sustainability hypothesis, based on Horvath and Watson's (1995) cointegration test when cointegration vectors are pre-specified. Using data for a set of developed and developing economies, we show that, unlike our procedure, conventional methodologies tend to penalize the sustainability hypothesis.

The cost channel reconsidered: a comment using an identification-robust approach

We re-examine the empirical relevance of the cost channel of monetary policy (e.g. Ravenna and Walsh, 2006), employing recently developed moment-conditions inference methods, including identification-robust procedures. Using US data, our results suggest that the cost channel effect is poorly identified and we are thus unable to corroborate the previous results in the literature.Cost channel; Phillips curve; GMM; Generalized Empirical Likelihood; Weak Identification.

Cointegration and the joint confirmation hypothesis

In this paper, the discussion concerning the joint use of unit root and stationarity tests is extended to the case of cointegration. Critical values for testing the joint confirmation hypothesis of no cointegration are computed and a small Monte Carlo experiment evaluates the relative performance of this approach

The Forecast Performance of Long Memory and Markov Switching Models

Recent research has focused on the links between long memory and structural change, stressing the long memory properties that may arise in models with parameter changes. In this paper, we contribute to this research by comparing the forecasting abilities of long memory and Markov switching models. Two approaches are employed: a Monte Carlo study and an empirical comparison, using the quarterly Consumer Price inflation rate in Portugal in the period 1968-1998. Although long memory models may capture some in-sample features of the data, when shifts occur in the series considered, their forecast performance is relatively poor, when compared with simple linear and Markov switching models. Moreover, our findings, in a more general framework, are in accordance with the works of Clements and Hendry (1998) and Clements and Krolzig (1998), reinforcing the idea that simple linear time series models remain useful tools for prediction.Long Memory; Structural change; Forecasting

Cointegration and the joint confirmation hypothesis

Recent papers by Charemza and Syczewska (1998) and Carrion, Sansó and Ortuño (2001) focused on the joint use of unit root and stationarity tests. In this paper, the discussion is extended to the case of cointegration. Critical values for testing the joint confirmation hypothesis of no cointegration are computed and a small Monte Carlo experiment evaluates the relative performance of this procedure

The Properties of Cointegration Tests in Models with Structural Change

In this paper we examine, by means of Monte Carlo simulation, the properties of several cointegration tests when long run parameters are subject to structural changes. We allow for different types of stochastic and deterministic regime shifts, more specifically, changes governed by Markov chains, martingale parameter variation, sudden multiple breaks and gradual changes. Our Monte Carlo analysis reveals that tests with cointegration as the null hypothesis perform badly, while tests with the null of no cointegration retain much of their usefulness in this context.Structural change; Cointegration; Tests; Monte Carlo

On the Stability of the Wealth Effect

Evidence of instability of the wealth effect in the USA is presented through the estimation of a Markov switching model of the long-run aggregate consumption function. The dating of the regimes appears to bear relation to movements in asset prices. A model-based explanation of the findings is suggested, highlighting the importance of the short-run relation between consumption, income and wealth in explaining the estimated long-run coefficients.Parameter instability; Markov switching; Consumption; Wealth effect

How forward-looking is the Fed? Direct estimates from a ‘Calvo-type’ rule

We estimate an alternative type of monetary policy rule, termed Calvo rule, according to which the central bank is assumed to target a discounted infinite sum of future expected inflation. Compared to conventional inflation forecast-based rules, which are typically of the Taylor-type with discrete forward looking horizons, this class of rule is less prone to the problem of indeterminacy. Parameter estimates obtained from GMM estimation provide support for Calvo-type rules, suggesting that the Federal Reserve targeted a mean forward horizon of between 4 and 8 quarters.Calvo-type interest rules, Inflation Forecast Based rules, GMM, indeterminacy.

A simple method for testing cointegration subject to regime changes

In this paper, we propose a simple method for testing cointegration in models that allow for multiple shifts in the long run relationship. The procedure consists of computing conventional residual-based tests with standardized residuals from Markov switching estimation. No new critical values are needed. An empirical application to the present value model of stock prices is presented, complemented by a small Monte Carlo experiment.Cointegration; Markov Switching; Standardized residuals.