An Unobserved Components Model that Yields Business and Medium-Run Cycles

2013 ◽  
Vol 45 (7) ◽  
pp. 1351-1373 ◽  
Author(s):  
JUN MA ◽  
MARK E. WOHAR
Keyword(s):  
Unobserved Components ◽  
Unobserved Components Model

scholarly journals A Note on ‘What Drives Share Prices in the Middle East?’

2008 ◽  
Author(s):  
Panos Priftakis ◽  
M. Ishaq Bhatti
Keyword(s):  
Middle East ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Predictive Ability ◽  
Oil Prices ◽  
Unobserved Components ◽  
Market Prices ◽  
Share Prices ◽  
Unobserved Components Model

There are several hypotheses suggesting that some properties of oil prices make it interesting to focus on the predictive ability of oil prices for stock returns. This paper reviews some models recently used in the literature and selects the most suitable one for measuring the relationships and/or linkages of oil prices to the stock markets of the selected five oil producing countries in the Middle East. In particular, the paper uses two methodologies to test for the presence of a cointegrating relationship between the two variables and an unobserved components model to find a relationship between the two variables. The results rejects convincingly that there is no linkage between the prices of oil and the stock market prices in these oil-based economies.  

scholarly journals OUTPUT FLUCTUATIONS IN THE G-7: AN UNOBSERVED COMPONENTS APPROACH

2011 ◽  
Vol 16 (3) ◽  
pp. 396-422 ◽  
Author(s):  
Sinchan Mitra ◽  
Tara M. Sinclair
Keyword(s):  
Structural Breaks ◽  
Previous Literature ◽  
Unobserved Components ◽  
The Real ◽  
Real Gdp ◽  
Output Fluctuations ◽  
Transitory Shocks ◽  
Unobserved Components Model ◽  
Explicit Correlation

This paper proposes a multivariate unobserved-components model to simultaneously decompose the real GDP for each of the G-7 countries into its respective trend and cycle components. In contrast to previous literature, our model allows for explicit correlation between all the contemporaneous trend and cycle shocks. We find that all the G-7 countries have highly variable stochastic permanent components for output, even once we allow for structural breaks. We also find that common restrictions on the correlations between trend and cycle shocks are rejected by the data. In particular, we find that correlations across permanent and transitory shocks are important both within and across countries.

scholarly journals Quantifying the impact of Ramadan on global raw sugar prices

2018 ◽  
Vol 11 (4) ◽  
pp. 510-528
Author(s):  
Kazi Abrar Hossain ◽  
Syed Abul Basher ◽  
A.K. Enamul Haque
Keyword(s):  
Moving Average ◽  
Global Market ◽  
Unobserved Components ◽  
Content Type ◽  
Autoregressive Integrated Moving Average ◽  
Sugar Price ◽  
Raw Sugar ◽  
Moving Average Model ◽  
Unobserved Components Model ◽  
The Impact

Purpose The purpose of this study is to quantify the impact of Ramadan on both the level and the growth of global raw sugar price. Design/methodology/approach The study uses a dummy and a fractional variable to capture Ramadan to overcome the asynchronicity of time between Ramadan fasting (which is based on the Islamic lunar calendar) and the movement in prices (which follows the Gregorian solar calendar). To capture the seasonality of sugar production, the data on sugar price span 34 years so that the Islamic calendar makes a complete cycle of the Gregorian calendar. The empirical model is estimated using both autoregressive integrated moving average model and unobserved components model. Findings The results show that monthly raw sugar prices in the global market increases by roughly 6.06 per cent (or $17.78 per metric ton) every year ahead of Ramadan. Practical implications The study illustrates the implications of the results for the consumption of imported sugar in Bangladesh. Originality/value The study uses a broader set of Ramadan indicators in its empirical models and checks the robustness of its baseline model using the unobserved components model. It also performs seasonal unit root tests on the global raw sugar prices.

scholarly journals A COMPARATIVE ANALYSIS OF ALTERNATIVE UNIVARIATE TIME SERIES MODELS IN FORECASTING TURKISH INFLATION

2012 ◽  
Vol 13 (2) ◽  
pp. 275-293 ◽  
Author(s):  
A. Nazif Çatık ◽  
Mehmet Karaçuka
Keyword(s):  
Time Series ◽  
Time Series Models ◽  
Unobserved Components ◽  
Inflation Forecasting ◽  
Long Run ◽  
Univariate Time Series ◽  
Forecasting Performance ◽  
Unobserved Components Model ◽  
One Step ◽  
Conventional Models

This paper analyses inflation forecasting power of artificial neural networks with alternative univariate time series models for Turkey. The forecasting accuracy of the models is compared in terms of both static and dynamic forecasts for the period between 1982:1 and 2009:12. We find that at earlier forecast horizons conventional models, especially ARFIMA and ARIMA, provide better one-step ahead forecasting performance. However, unobserved components model turns out to be the best performer in terms of dynamic forecasts. The superiority of the unobserved components model suggests that inflation in Turkey has time varying pattern and conventional models are not able to track underlying trend of inflation in the long run.

scholarly journals Seasonal adjustment of the Spanish sales daily data

SERIEs ◽  
2021 ◽  
Author(s):  
Ángel Cuevas ◽  
Ramiro Ledo ◽  
Enrique M. Quilis
Keyword(s):  
Value Added ◽  
Signal Extraction ◽  
Economic Conditions ◽  
Seasonal Adjustment ◽  
Unobserved Components ◽  
Spanish Economy ◽  
Short Term ◽  
Daily Data ◽  
Daily Frequency ◽  
Unobserved Components Model

AbstractWe present a procedure to perform seasonal adjustment over daily sales data. The model adjusts daily information from the Immediate Supply of Information System for Value Added Tax declaration forms compiled by the Spanish Tax Agency. The procedure performs signal extraction and forecasting at the daily frequency, by means of an unobserved components model. The daily information allows a permanently updated monitoring of the short-term economic conditions of the Spanish economy.

Seasonal and Cyclical Properties of Ifo Business Test Variables / Saisonale und zyklische Eigenschaften von ifo Konjunkturtest Variablen

2003 ◽  
Vol 223 (5) ◽  
Author(s):  
Gebhard Flaig
Keyword(s):  
Survey Data ◽  
Seasonal Pattern ◽  
Business Climate ◽  
Unobserved Components ◽  
Empirical Results ◽  
Business Survey Data ◽  
Unobserved Components Model ◽  
Business Survey ◽  
Working Day ◽  
Over Time

SummaryIn this paper, an Unobserved Components Model is used to decompose the balances of Ifo Business survey data into the cyclical, the seasonal and the irregular components, as well as the working day effect. The empirical results show that the total cycle consists of three subcycles with about 3, 5 and 11 years. Each subcycle of the assessment variable is “similar” to the corresponding subcycle of the expectations variable. The seasonal pattern is changing over time and the working day effect is significant for the assessment of the current business situation and for the Ifo Business Climate, but not for the expectation series.

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