Wyniki wyszukiwania - BazEkon

1

The Dynamics of the Credit Cycle in Selected Asian Countries

100%

Lenart Ł., Pipień M.

Folia Oeconomica Cracoviensia

|

2017

|

58

127-134

W artykule przedstawiono cechy cyklu kredytowego w wybranych krajach azjatyckich. Zasadniczym celem analiz jest omówienie różnic w cyklu w świetle zróżnicowanego wpływu kryzysu azjatyckiego z lat 1997-1998 na gospodarkę regionu wschodniej Azji. W pracy zastosowano nieparametryczny test, umożliwiający wnioskowanie o statystycznie istotnych częstościach dyskretnego spektrum procesu opisującego cykliczne fluktuacje. Uzyskane rezultaty empiryczne pozwalają stwierdzić, że cechy cyklu kredytowego znacznie się różnią w regionie azjatyckim. Kraje najsilniej dotknięte kryzysem, to jest Korca Południowa i Malezja, charakteryzują się cyklem kredytowym o długim okresie, przekraczającym dwie dekady. Cykle kredytowe w krajach słabiej dotkniętych kryzysem, takich jak Singapur i Tajwan, charakteryzują się okresami znacznie krótszymi i relatywnie silniejszymi amplitudami wahań. (abstrakt oryginalny)

2

Probabilistic Predictive Analysis of Business Cycle Fluctuations in Polish Economy

84%

Mazur B.

Equilibrium

|

2017

|

12

|

nr 3

435-452

Research background: The probabilistic setup and focus on evaluation of uncertainties and risks has become more widespread in modern empirical macroeconomics, including the analysis of business cycle fluctuations. Therefore, forecast-based indicators of future economic conditions should be constructed using density forecasts rather than point forecasts, as the former provide description of forecast uncertainty.Purpose of the article: We discuss model-based probabilistic inference on business cycle fluctuations in Poland. In particular, we consider model comparison for probabilistic prediction of growth rates of the Polish industrial production. We also develop a class of indicators of future economic conditions constructed using probabilistic information on the rates (that make use of joint predictive distribution over several forecast horizons).Methods: We use Bayesian methods (in order to capture the estimation uncertainty) and consider two groups of models. The first group consists of Dynamic Conditional Score models with the generalized t conditional distribution (with conditional heteroscedasticity and heavy tails, being important for modelling of extreme observations). Another group of models relies on deterministic cycle modelling using Flexible Fourier Form. Ex-post density forecasting performance of the models is compared using the criteria for probabilistic prediction: Log-Predictive Score (LPS) and Continuous Ranked Probability Score (CRPS).Findings & Value added: The pre-2013 data support the deterministic cycle models whereas more recent observations can be explained by a simple mean-reverting Gaussian AR(4) process. The results indicate a structural change affecting Polish business cycle fluctuations after 2013. Hence, forecast pooling strategies are recommended as a tool for further research. We find rather limited support in favor of the first group of models. The probabilistic indicator of future economic conditions considered here leads actual phases of the growth cycle quite well, though the effect is less obvious after 2013. (original abstract)

3

Bayesian Inference for a Deterministic Cycle with Time-Varying Amplitude: The Case of the Growth Cycle in European Countries

84%

Lenart Ł.

Central European Journal of Economic Modelling and Econometrics (CEJEME)

|

2018

|

10

|

nr 3

233-262

The main goal of this paper is to propose the probabilistic description of cyclical (business) fluctuations. We generalize a fixed deterministic cycle model by incorporating the time-varying amplitude. More specifically, we assume that the mean function of cyclical fluctuations depends on unknown frequencies (related to the lengths of the cyclical fluctuations) in a similar way to the almost periodic mean function in a fixed deterministic cycle, while the assumption concerning constant amplitude is relaxed. We assume that the amplitude associated with a given frequency is time-varying and is a spline function. Finally, using a Bayesian approach and under standard prior assumptions, we obtain the explicit marginal posterior distribution for the vector of frequency parameters. In our empirical analysis, we consider the monthly industrial production in most European countries. Based on the highest marginal data density value, we choose the best model to describe the considered growth cycle. In most cases, data support the model with a time-varying amplitude. In addition, the expectation of the posterior distribution of the deterministic cycle for the considered growth cycles has similar dynamics to cycles extracted by standard bandpass filtration methods. (original abstract)

4

Non-Parametric Test for the Existence of the Common Deterministic Cycle : the Case of the Selected European Countries

67%

Lenart Ł., Pipień M.

Central European Journal of Economic Modelling and Econometrics (CEJEME)

|

2017

|

9

|

nr 3

201-241

The aim of the article is to construct an asymptotically consistent test, based on a subsampling approach, to verify hypothesis about existence of the individual or common deterministic cycle in coordinates of multivariate macroeconomic time series. By the deterministic cycle we mean the periodic or almost periodic fluctuations in the mean function in cyclical fluctuations. To construct test we formulate a multivariate non-parametric model containing the business cycle component in the unconditional mean function. The construction relies on the Fourier representation of the unconditional expectation of the multivariate Almost Periodically Correlated time series and is related to fixed deterministic cycle presented in the literature. The analysis of the existence of common deterministic business cycles for selected European countries is presented based on monthly industrial production indexes. Our main findings from the empirical part is that the deterministic cycle can be strongly supported by the data and therefore should not be automatically neglected during analysis without justification. (original abstract)