A Multivariate Unobserved Components Model to Estimate Potential Output in the Euro Area: A Production Function Based Approach

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.

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TOTAL FACTOR PRODUCTIVITY AND FRONTIER PRODUCTION FUNCTION = PRODUKTIVITAS FAKTOR PRODUKSI TOTAL DAN FUNGSI PERODUKSI FRONTIER

Agro Ekonomi ◽

10.22146/agroekonomi.16895 ◽

2016 ◽

Vol 24 (2) ◽

pp. 2

Author(s):

Sri Widodo

Keyword(s):

Total Factor Productivity ◽

Production Function ◽

Productivity Growth ◽

Factor Productivity ◽

Single Factor ◽

Cross Sectional ◽

Potential Output ◽

Total Productivity ◽

Cross Sectional Studies ◽

Frontier Production Function

The total factor productivity became an interesting concept in the measurement of productivity growth. Productivity is a ratio of output to input. The most common measurement of productivity is single factor productivity or partial productivity such as of land, labor, or capital.A total (factor) productivity is a productivity of all factors of production where the factors are aggregated. In cross-sectional studies this total productivity is a ratio of actual to potential output where the potential output is estimated from ther frontier production function. One of the methods to estimate this frontier function is by using linear programming technique.The total productivity does not always coincide with a single factor productivity of land (yield), that in the study area the larger farms tend to have higher total productivity than yield

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

Macroeconomic Dynamics ◽

10.1017/s1365100510000647 ◽

2011 ◽

Vol 16 (3) ◽

pp. 396-422 ◽

Cited By ~ 15

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.

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Detecting unemployment hysteresis: A simultaneous unobserved components model with Markov switching

Economics Letters ◽

10.1016/j.econlet.2016.04.027 ◽

2016 ◽

Vol 144 ◽

pp. 115-118 ◽

Cited By ~ 12

Author(s):

Sabine Klinger ◽

Enzo Weber

Keyword(s):

Markov Switching ◽

Unobserved Components ◽

Unobserved Components Model

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