Martin Fukač

Chapter 18 – Identification and Analysis of the Naip Model within a State-Space Framework

Publisher Summary This chapter presents identification and analysis of the non-accelerating inflation product (NAIP) model within a state-space framework. The iterated extended Kalman filter is employed to identify the unobserved states and time-varying parameters. As an approximation of the potential product, the NAIP model is used. The term NAIP is introduced to distinguish among different structural models. The potential product in this concept is modeled as a real product level at which inflation is stable and does not accelerate or decelerate. The model has been estimated in its state-space representation using 30 iterations of EKFS. With this number of iterations, the values of parameters converged and their trajectories are smooth enough to consider the parameters as time invariant. The results are presented for both the time-varying parameters and time-invariant parameters. It can be seen that both cases produce similar responses that only confirm the original statement. It is found that the model implies correct economic relations between model variables.

Chapter 23 – Alternative Models of Adaptive and Near-Rational Expectations — Classification by Bootstrap Filter

Publisher Summary This chapter examines the alternative models of adaptive and near-rational expectations-classification by Bootstrap filter. The problem of deciding between alternative hypotheses is common. There may be two or more theories on a model background or parameter values and the data should determine which alternative is the most plausible. In case one of these models is nonlinear, the Monte Carlo approach should be used instead of linear methods. Such an approach is employed for classifying expectation formation within augmented Phillips curve. It is found that before the prediction phase the importance resampling is performed. It makes it no longer necessary to calculate with sample weights, because they are all equal. The other advantage is that there are no samples with small weights. Some samples with greater weight are selected two or more times while some samples are not selected at all. The prediction step is realized according to the state space model of the system. The probability of each model is computed based on the data. Such an approach is used for the classification of alternative economic models of expectation formation.

Alternative Models of Adaptive and Near-Rational Expectations — Classification by Bootstrap Filter

Abstract The problem of deciding between alternative hypotheses is common. There may exist two or more theories on a model background or parameter values and the data should determine which alternative is the most plausible. In case one of these models is nonlinear, the Monte Carlo approach should be used instead of linear methods. Such an approach is employed for classifying expectation formation within augmented Phillips curve.

Identification and Analysis of the Naip Model Within a State-Space Framework

Abstract In this paper we try to measure the production gap and consequently the Non-Accelerating Inflation Product as a kind of the potential output. The iterated extended Kalman filter is employed to identify unobserved states and time-varying parameters. The analysis is performed on the data of the Czech economy.