Does a Survey Based Capacity Utilization Measure Help Predicting Brazilian Output Gap in Real-Time?

2016 ◽  
Vol 12 (1) ◽  
pp. 119-139 ◽  
Author(s):  
Sarah Lima ◽  
Marco Malgarini
Keyword(s):  
Real Time ◽  
Capacity Utilization ◽  
Output Gap

Real time representation of the UK output gap in the presence of model uncertainty

2009 ◽  
Vol 25 (1) ◽  
pp. 81-102 ◽  
Author(s):  
Anthony Garratt ◽  
Kevin Lee ◽  
Emi Mise ◽  
Kalvinder Shields
Keyword(s):  
Real Time ◽  
Model Uncertainty ◽  
Output Gap ◽  
Time Representation ◽  
The Uk

scholarly journals IS BUSINESS CYCLE ASYMMETRY INTRINSIC IN INDUSTRIALIZED ECONOMIES?

2019 ◽  
Vol 24 (6) ◽  
pp. 1403-1436 ◽  
Author(s):  
James Morley ◽  
Irina B. Panovska
Keyword(s):  
Business Cycle ◽  
Model Uncertainty ◽  
Phillips Curve ◽  
Capacity Utilization ◽  
Output Growth ◽  
Underlying Structure ◽  
Output Gap ◽  
Cycle Asymmetry ◽  
Long Run ◽  
Intrinsic Characteristic

We consider a model-averaged forecast-based estimate of the output gap to measure economic slack in 10 industrialized economies. Our measure takes changes in the long-run growth rate into account and, by addressing model uncertainty using equal weights on different forecast-based estimates, is robust to different assumptions about the underlying structure of the economy. For all 10 countries in the sample, we find that the estimated output gap has much larger negative movements during recessions than positive movements in expansions, suggesting business cycle asymmetry is an intrinsic characteristic of industrialized economies. Furthermore, the estimated output gap is always strongly negatively correlated with future output growth and unemployment and positively correlated with capacity utilization. It also implies a convex Phillips Curve in many cases. The model-averaged output gap is reliable in real time in the sense of being subject to relatively small revisions.

scholarly journals Industrial Electricity Usage and Stock Returns

2017 ◽  
Vol 52 (1) ◽  
pp. 37-69 ◽  
Author(s):  
Zhi Da ◽  
Dayong Huang ◽  
Hayong Yun
Keyword(s):  
Growth Rate ◽  
Asset Pricing ◽  
Business Cycle ◽  
Stock Returns ◽  
Real Time ◽  
Risk Premium ◽  
Output Gap ◽  
Financial Variables ◽  
The Future ◽  
The Business Cycle

The growth rate of industrial electricity usage predicts future stock returns up to 1 year with an R2 of 9%. High industrial electricity usage today predicts low stock returns in the future, consistent with a countercyclical risk premium. Industrial electricity usage tracks the output of the most cyclical sectors. Our findings bridge a gap between the asset pricing literature and the business cycle literature, which uses industrial electricity usage to gauge production and output in real time. Industrial electricity growth compares favorably with traditional financial variables, and it outperforms Cooper and Priestley’s output gap measure in real time.

scholarly journals Mathematical Methodology to Predict Energy Generation of Grid Connected PV Power Plants in India

2016 ◽  
Vol 11 (1) ◽  
pp. 156-166
Author(s):  
Suprava Chakraborty ◽  
Pradip Sadhu
Keyword(s):  
Mathematical Method ◽  
Real Time ◽  
Power Plants ◽  
Capacity Utilization ◽  
Energy Generation ◽  
Utilization Factor ◽  
Photovoltaic Plant

This paper presents a reliable mathematical methodology to predict the energy generation from grid connected Photovoltaic plant of different technologies in India. Energy generation of different commercially used PV technologies in different locations of India is predicted using proposed mathematical method. This results show a decisive study to choose the best PV technology for particular location of India. Predicted energy generation is validated with the monthly generation for the whole year of 2014 from operational PV power plants of different technologies. Predicted generation is in good co-relation with the actual real time generation and Capacity Utilization Factor (CUF) of the PV plants.

scholarly journals The Unreliability of Output-Gap Estimates in Real Time

2017 ◽  
Vol 56 (3) ◽  
pp. 193-219 ◽  
Author(s):  
Ahsan Ul Haq Satti ◽  
Wasim Shahid Malik
Keyword(s):  
Real Time ◽  
Linear Trend ◽  
The State ◽  
Output Gap ◽  
Policy Decisions ◽  
Time Data ◽  
Uncertainty Measurement ◽  
Real Time Data ◽  
Final Data ◽  
The Difference

Most research on monetary policy assumes availability of information regarding the current state of economy, at the time of the policy decision. A key challenge for policy-makers is to find indicators that give a clear and precise signal of the state of the economy in real time—that is, when policy decisions are actually taken. One of the indicators used to asses the economic condition is the output gap; and the estimates of output gap from real time data misrepresents the true state of economy. So the policy decisions taken on the basis of real time noisy data are proved wrong when true data become available. Within this context we find evidence of wrong estimates of output gap in real time data. This is done by comparing estimates of output gap based on real time data with that in the revised data. The quasi real time data are also constructed such that the difference between estimates of output gap from real time data and that from quasi real time data reflects data revision and the difference between estimates of output gap from final data and that from quasi real time data portray other revisions including end sample bias. Moreover, output gap is estimated with the help of five methods namely the linear trend method, quadratic trend method, Hordrick-Prescott (HP) filter, production function method, and structural vector autoregressive method. Results indicate that the estimates of output gap in real time data are different from what have been found in final data but other revisions, compared to data revisions, are found more significant. Moreover, the output gap measured using all the methods, except the linear trend method, appropriately portray the state of economy in the historical context. It is also found that recessions can be better predicted by real time data instead of revised data, and final data show more intensity of recession compared with what has been shown in real time data. JEL Classification: E320 Keywords: Data Uncertainty, Measurement Uncertainty, Output Gap, Business Cycle, Economic Activity

scholarly journals The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time

2005 ◽  
Vol 37 (3) ◽  
pp. 583-601 ◽  
Author(s):  
Athanasios Orphanides ◽  
Simon Van Norden
Keyword(s):  
Real Time ◽  
Output Gap ◽  
Inflation Forecasts

scholarly journals Output gap uncertainty and real-time monetary policy

2015 ◽  
Vol 1 (4) ◽  
pp. 329-358 ◽  
Author(s):  
Francesco Grigoli ◽  
Alexander Herman ◽  
Andrew Swiston ◽  
Gabriel Di Bella
Keyword(s):  
Monetary Policy ◽  
Real Time ◽  
Output Gap

Reliable real-time estimates of the euro-area output gap

2020 ◽  
Vol 64 ◽  
pp. 103191
Author(s):  
Lorenzo Burlon ◽  
Paolo D’Imperio
Keyword(s):  
Real Time ◽  
Euro Area ◽  
Output Gap ◽  
Time Estimates
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