Measuring US Aggregate Output and Output Gap Using Large Datasets

2018 ◽  
Author(s):  
Matteo Barigozzi ◽  
Matteo Luciani
2017 ◽  
Vol 25 (2) ◽  
pp. 927-960
Author(s):  
Jarod Jacobs

In this article, I discuss three statistical tools that have proven pivotal in linguistic research, particularly those studies that seek to evaluate large datasets. These tools are the Gaussian Curve, significance tests, and hierarchical clustering. I present a brief description of these tools and their general uses. Then, I apply them to an analysis of the variations between the “biblical” DSS and our other witnesses, focusing upon variations involving particles. Finally, I engage the recent debate surrounding the diachronic study of Biblical Hebrew. This article serves a dual function. First, it presents statistical tools that are useful for many linguistic studies. Second, it develops an analysis of the he-locale, as it is used in the “biblical” Dead Sea Scrolls, Masoretic Text, and Samaritan Pentateuch. Through that analysis, this article highlights the value of inferential statistical tools as we attempt to better understand the Hebrew of our ancient witnesses.


2018 ◽  
Author(s):  
Andrew Dalke ◽  
Jerome Hert ◽  
Christian Kramer

We present mmpdb, an open source Matched Molecular Pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large datasets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. mmpdb is freely available.


2015 ◽  
Vol 15 (2) ◽  
pp. 37-52
Author(s):  
Mahpud Sujai

This paper is intended to analyze the effect of oil price changes on potential output and actual output in the state budget cycle and identifies the output gap which is the difference between potential output and actual output. The research methodology uses a quantitative approach to analyze problems that occur related to the impact of oil price changes to the state budget cycle. Data analysis was carried out through the approach cyclically adjusted fiscal balance with a simplified approach. This research identified that the potential output is likely to continue increasing in line with Indonesia's oil price trends which is continue to rise following the world oil price movements. In calculating the output gap using a linear trend and HP filter, the result is fuctuating depend on the percentage changes in both potential output and actual output. This paper concludes that Indonesian oil price (ICP) has a significant impact on changes in the state budget cycle. If oil prices rise, the output gap between potential output and actual output is greater, and vice versa. This will make the budget vulnerable to shock that occurs as an external infuence.


2012 ◽  
Vol 38 (11) ◽  
pp. 1831
Author(s):  
Wen-Jun HU ◽  
Shi-Tong WANG ◽  
Juan WANG ◽  
Wen-Hao YING

Author(s):  
Mustapha Baghli ◽  
Carine Bouthevillain ◽  
Olivier de Bandt ◽  
Henri Fraisse ◽  
Hervé le Bihan ◽  
...  
Keyword(s):  

2017 ◽  
Vol 93 (4) ◽  
pp. 101-125 ◽  
Author(s):  
Inga Bethmann ◽  
Martin Jacob ◽  
Maximilian A. Müller

ABSTRACT Tax regimes treat losses and profits asymmetrically when profits are immediately taxed, but losses are not immediately refunded. We find that treating losses less asymmetrically by granting refunds less restrictively increases loss firms' investment: A third of the refund is invested and the rest is held as cash or returned to shareholders. However, the investment response is driven primarily by firms prone to engage in risky overinvestment. Consistent with the risk of misallocation, we find a delayed exit of low-productivity loss firms receiving less restrictive refunds, indicating potential distortion of the competitive selection of firms. This distortion also negatively affects aggregate output and productivity. Our results suggest that stimulating loss firms' investment with refunds unconditional on their future prospects comes at the risk of misallocation. JEL Classifications: G31; H21; H25.


2020 ◽  
Vol 196 ◽  
pp. 105777
Author(s):  
Jadson Jose Monteiro Oliveira ◽  
Robson Leonardo Ferreira Cordeiro

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