Euro-indicators Working Group
|
|
- Phoebe Kennedy
- 5 years ago
- Views:
Transcription
1 Euro-indicators Working Group Luxembourg, 9 th & 10 th June 2011
2 Item 9.4 of the Agenda New developments in EuroMIND estimates Rosa Ruggeri Cannata Doc 309/11
3 What is EuroMIND? EuroMIND is a Monthly INDicator of economic conditions. It provides an estimate of GDP based on the temporal disaggregation of the quarterly National Accounts estimates, within a set of linked medium-size dynamic factor models for a set of coincident indicators It delivers a timely assessment of the state of the euro area economy It combines methodological pertinence and practical relevance
4 EuroMIND is by construction consistent with the official National Accounts estimates compiled by Eurostat It has desirable properties both for the historical disaggregation of GDP and its main components, and for nowcasting the level of economic activity by sector and expenditure components There are two main versions of EuroMIND for the euro area, differing for the inclusion or not of survey variables (Frale et al. 2008, 2009) (EuroMIND and EuroMIND-S) Now we also have a backdated version EuroMIND-B and a decomposition of EuroMIND into potential output and output gap, EuroMIND-G
5 Methodology (1) We carry out the disaggregation of the chain-linked quarterly value added from the output side (Agriculture, Industry, Construction, Trade, Financial services, Other services) and from the expenditure side (Final consumption, Gross capital formation, Exports, Imports) We adopt a dynamic factor model at the monthly level, taking the temporal aggregation constraint into account. The multivariate models are cast in the state space form and computational efficiency is achieved by implementing univariate filtering and smoothing procedures
6 Methodology (2) The chained-linked total GDP results via a multistep procedure that exploits the additivity of the volume measures expressed at the prices of the previous year The final estimate is obtained by combining the two estimates (output side and expenditure side) with weights reflecting their relative precision
7 EuroMIND and the business cycle The availability of a monthly indicator disaggregated into branches of activity such as EuroMIND is particularly relevant to monitor the business cycle in real time EuroMIND allows to follow in real time the evolution of the different elements of the euro area economy: sectors and demand components
8 Information set Quarterly Value Added are available from the beginning of 1995 in SA and WDA terms and refer to the euro Area Since December 2006 we have estimated EuroMIND once at month, right after the publication of the Industrial Production index (around the 15th). A mixed frequency model is used to disaggregate the quarterly NA values in sample and to compute the monthly values out of sample up to time t-2 The information set includes National Account data, monthly "hard" indicators (industrial production, employment, hours worked etc.) and, for EuroMIND-S, Business and Consumer surveys data
9 EuroMIND: the information set by sector Output side: For Industry (CDE) and Construction (F), a core indicator is represented by the index of industrial production. For the remaining branches (services), the monthly variables tend to be less directly related to the economic content of value added Expenditure size: for Final consumption expenditures some indicators of demand are available together with the production of consumer goods. For Gross capital formation a core indicator is the production index (both for industry and constructions), plus some specific variables for constructions. As far as the External Balance is concerned, the monthly volume index of Imports and Exports is provided by Eurostat, although some delay
10 Extension of the information set: business survey data Unfortunately financial indicators, such as spread, interest and exchange rates..., never resulted statistically significant. In order to catch sentiments and expectations of economic agents we complete this set of variables with the business survey data on Consumers, Business, Building and Services Survey data represent a very timely piece of economic information which originates from the quantification of qualitative survey questions, asking firms and consumers opinions on the state of the economy.
11 Use of business survey data In the U.S. survey data are not listed among the set of series that enter the Conference Board and the Stock and Watson (1989) indices of coincident indicators and they are not monitored by the NBER experts when dating the US business cycle Survey series are featured in the Eurocoin indicator for the euro area produced by the CEPR and in Euro- Sting, the short term indicator of the Euro area growth produced recently by the Spanish central bank
12 EuroMIND-S Business Survey data gave useful results to improve the model in terms of nowcast and short term forecast ability (FMMP(2010)-Survey Data as Coincident or Leading Indicator, JoF 29) The original model has been extended with more than one common factor and a smoother common component (IZAR) which allows for low-frequency cycles and fits survey data features
13 EuroMind-S: last 12 releases Billions of euro, chain linked volumes, reference year Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep Oct-10 Nov-10 Dec-10 Jan-11 Feb-11 Mar Jan-09 Feb-09 Mar-09 Apr-09 May-09 Jun-09 Jul-09 Aug-09 Sep-09 Oct-09 Nov-09 Dec-09 Jan-10 Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-11 Feb-11
14 EuroMIND-S perfomance An application to the valued added for Industry, comparing the extended model versus the original EuroMIND formulation in terms of forecast ability has been developed. The issue of data revisions and news content in each block of series, survey and hard data, was also analyzed Evidence for a better performance of a model including both hard and survey data was found. Information from surveys was related to the lack of hard data (in line with the literature, e.g. Giannone et al. (2009) for the US)
15 Growth rates: comparison among indicators Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan Feb variations over previous period Quarterly GDP EuroMind EuroMind-S variations over same period of previous year Quarterly GDP EuroMind EuroMind-S
16 Other extensions of EuroMIND EuroMIND-B(ackcast): tracking the business cycle in the euro area since the early 70s EuroMIND-G(ap): real time estimates of the output gap based on EuroMIND
17 EuroMIND-B(ackcast) QNA: available from the first quarter of 1995 (introduction of ESA95). Accordingly, EuroMIND estimated since 1996 Recently, Eurostat has produced a database of the main European economic indicators, backdated up to 1971 based on backcasting techniques. This in turn enabled the backcalculation of EuroMIND from 1995 backward The production of a long indicator, measured at the monthly frequency, and based on a rigorous statistical methodology, is clearly a great improvement in the direction of creating a relevant statistical information base for an economic policy at the European level
18 EuroMIND-B and turning points detection EuroMIND-B may play an important role also for the analysis of the business cycle in the Euro area. Estimates of the turning points and of the recession probabilities of the classical cycle for the Euro area Results show three major recessionary patterns: in the 70, in the 90 plus the last recession They confirm the inception of the last recession in Feb. 2008, characterized by the largest steepness and duration
19 EuroMIND-G(ap) During the recent economic and financial crises, the discussion about potential output and long run growth dynamics has regained new interest among policy makers and Institutions the usual decomposition of a time series such as GDP into the trend and the cycle component has assumed an important economic interpretation EuroMInd-G provides the decomposition of EuroMInd into potential output and the output gap
20 EuroMIND-G: methodology (1) EuroMInd-G is based on model based decomposition of both the common cyclical trend and the GDP idiosyncratic component into a low-pass and a high-pass component The decomposition is thus embedded into the dynamic factor model and enables the extraction of the unobserved potential and gap series using standard optimal signal extraction principles The components can be estimated and their reliability assessed by applying the Kalman filter and smoother to a modified state space model
21 EuroMIND-G: methodology (2) The model depends on an integer m (chosen a priori) defining the order of the decomposition of the white noise disturbances driving the common and the idiosyncratic trends And on a non negative scalar λ (chosen a priori) which represents the smoothness parameter and, together with m, defines uniquely the decomposition The variances low-pass and high-pass disturbances are proportional, and depend on λ; as λ increases, the smoothness of the low pass component also increases, since a larger portion of high frequency variation is removed
22 EuroMIND-G: methodology (3) For given values of λ and m, the decomposition defines a new potential output disturbance that uses only the low frequencies whereas the remainder will contribute to the high pass component The spectral density of the disturbances of the low pass component has two poles at the frequency π; on the contrary, the spectral density of the high pass component has two poles at the zero frequency The role of the smoothness parameter can be related to the notion of a cut off frequency
23 Application The cut off period has be set to correspond to eight years (96 monthly observations) The related value of the smoothness parameter is λ = , corresponding to a low-pass component retaining all the potential output fluctuations with a periodicity greater than 8 years In finite samples the estimator of the low pass and high pass components is computed by the Kalman filter and smoother applied to the state space model with measurement equation modified so as to incorporate the band-pass decomposition of GDP. The state-space form is modified so as to account for temporal aggregation of the GDP series
24 Results The main advantage of performing a model based decomposition is that the no special treatment of the end values is necessary, since the optimal estimates of the components are automatically provided by the Kalman filter and smoother associated to the model featuring the band-pass components Results are very encouraging: the estimated cycle capture quite well the swings in the economy as results of consecutive phases of recessions and expansion It is visible how the European economy has entered period of severe slowdown in the economy around 1974, 1980, 1992 and finally in 2008
25 EuroMind the Gap Billions of euro, chain-linked volumes, reference year EuroMind Cycle -15 Trend -20 EuroMind the Gap Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10
26 Thank you for your attention
Euro-indicators Working Group
Euro-indicators Working Group Luxembourg, 9 th & 10 th June 2011 Item 9.3 of the Agenda Towards an early warning system for the Euro area By Gian Luigi Mazzi Doc 308/11 Introduction Clear picture of economic
More informationIntroduction to Forecasting
Introduction to Forecasting Introduction to Forecasting Predicting the future Not an exact science but instead consists of a set of statistical tools and techniques that are supported by human judgment
More informationBusiness Cycle Dating Committee of the Centre for Economic Policy Research. 1. The CEPR Business Cycle Dating Committee
Business Cycle Dating Committee of the Centre for Economic Policy Research Michael Artis Fabio Canova Jordi Gali Francesco Giavazzi Richard Portes (President, CEPR) Lucrezia Reichlin (Chair) Harald Uhlig
More informationNOWCASTING REPORT. Updated: August 17, 2018
NOWCASTING REPORT Updated: August 17, 2018 The New York Fed Staff Nowcast for 2018:Q3 stands at 2.4%. News from this week s data releases decreased the nowcast for 2018:Q3 by 0.2 percentage point. Negative
More informationGAMINGRE 8/1/ of 7
FYE 09/30/92 JULY 92 0.00 254,550.00 0.00 0 0 0 0 0 0 0 0 0 254,550.00 0.00 0.00 0.00 0.00 254,550.00 AUG 10,616,710.31 5,299.95 845,656.83 84,565.68 61,084.86 23,480.82 339,734.73 135,893.89 67,946.95
More informationNOWCASTING REPORT. Updated: September 23, 2016
NOWCASTING REPORT Updated: September 23, 216 The FRBNY Staff Nowcast stands at 2.3% and 1.2% for 216:Q3 and 216:Q4, respectively. Negative news since the report was last published two weeks ago pushed
More informationNOWCASTING REPORT. Updated: October 21, 2016
NOWCASTING REPORT Updated: October 21, 216 The FRBNY Staff Nowcast stands at 2.2% for 216:Q3 and 1.4% for 216:Q4. Overall this week s news had a negative effect on the nowcast. The most notable developments
More informationNOWCASTING REPORT. Updated: July 20, 2018
NOWCASTING REPORT Updated: July 20, 2018 The New York Fed Staff Nowcast stands at 2.7% for 2018:Q2 and 2.4% for 2018:Q3. News from this week s data releases decreased the nowcast for 2018:Q2 by 0.1 percentage
More informationNOWCASTING REPORT. Updated: February 22, 2019
NOWCASTING REPORT Updated: February 22, 2019 The New York Fed Staff Nowcast stands at 2.3% for 2018:Q4 and 1.2% for 2019:Q1. News from this week s data releases increased the nowcast for both 2018:Q4 and
More informationNOWCASTING REPORT. Updated: September 7, 2018
NOWCASTING REPORT Updated: September 7, 2018 The New York Fed Staff Nowcast stands at 2.2% for 2018:Q3 and 2.8% for 2018:Q4. News from this week s data releases increased the nowcast for 2018:Q3 by 0.2
More informationNOWCASTING REPORT. Updated: January 4, 2019
NOWCASTING REPORT Updated: January 4, 2019 The New York Fed Staff Nowcast stands at 2.5% for 2018:Q4 and 2.1% for 2019:Q1. News from this week s data releases left the nowcast for both quarters broadly
More informationNOWCASTING REPORT. Updated: September 14, 2018
NOWCASTING REPORT Updated: September 14, 2018 The New York Fed Staff Nowcast stands at 2.2% for 2018:Q3 and 2.8% for 2018:Q4. This week s data releases left the nowcast for both quarters broadly unchanged.
More informationA look into the factor model black box Publication lags and the role of hard and soft data in forecasting GDP
A look into the factor model black box Publication lags and the role of hard and soft data in forecasting GDP Marta Bańbura and Gerhard Rünstler Directorate General Research European Central Bank November
More informationNOWCASTING REPORT. Updated: November 30, 2018
NOWCASTING REPORT Updated: November 30, 2018 The New York Fed Staff Nowcast for 2018:Q4 stands at 2.5%. News from this week s data releases left the nowcast for 2018:Q4 broadly unchanged. A negative surprise
More informationTime Series Analysis
Time Series Analysis A time series is a sequence of observations made: 1) over a continuous time interval, 2) of successive measurements across that interval, 3) using equal spacing between consecutive
More informationNOWCASTING REPORT. Updated: May 5, 2017
NOWCASTING REPORT Updated: May 5, 217 The FRBNY Staff Nowcast stands at 1.8% for 217:Q2. News from this week s data releases reduced the nowcast for Q2 by percentage point. Negative surprises from the
More informationAdvances in econometric tools to complement official statistics in the field of Principal European Economic Indicators
Advances in econometric tools to complement official statistics in the field of Principal European Economic Indicators GIAN LUIGI MAZZI, FILIPPO MOAURO AND ROSA RUGGERI CANNATA 2016 edition STATISTICAL
More informationShort-term forecasts of GDP from dynamic factor models
Short-term forecasts of GDP from dynamic factor models Gerhard Rünstler gerhard.ruenstler@wifo.ac.at Austrian Institute for Economic Research November 16, 2011 1 Introduction Forecasting GDP from large
More informationA system for a real-time monitoring of the euro area economy
ISSN 1681-4789 Statistical working papers A system for a real-time monitoring of the euro area economy Gian Rilis Luigi augiati Mazzi, siscilit Filippo venis Moauro nim and Rosa Ruggeri Cannata 2016 edition
More informationVolume 38, Issue 2. Nowcasting the New Turkish GDP
Volume 38, Issue 2 Nowcasting the New Turkish GDP Barış Soybilgen İstanbul Bilgi University Ege Yazgan İstanbul Bilgi University Abstract In this study, we predict year-on-year and quarter-on-quarter Turkish
More informationTIGER: Tracking Indexes for the Global Economic Recovery By Eswar Prasad, Karim Foda, and Ethan Wu
TIGER: Tracking Indexes for the Global Economic Recovery By Eswar Prasad, Karim Foda, and Ethan Wu Technical Appendix Methodology In our analysis, we employ a statistical procedure called Principal Component
More informationForecasting the Canadian Dollar Exchange Rate Wissam Saleh & Pablo Navarro
Forecasting the Canadian Dollar Exchange Rate Wissam Saleh & Pablo Navarro Research Question: What variables effect the Canadian/US exchange rate? Do energy prices have an effect on the Canadian/US exchange
More informationTechnical note on seasonal adjustment for M0
Technical note on seasonal adjustment for M0 July 1, 2013 Contents 1 M0 2 2 Steps in the seasonal adjustment procedure 3 2.1 Pre-adjustment analysis............................... 3 2.2 Seasonal adjustment.................................
More informationTIGER: Tracking Indexes for the Global Economic Recovery By Eswar Prasad and Karim Foda
TIGER: Tracking Indexes for the Global Economic Recovery By Eswar Prasad and Karim Foda Technical Appendix Methodology In our analysis, we employ a statistical procedure called Principal Compon Analysis
More informationNowcasting Norwegian GDP
Nowcasting Norwegian GDP Knut Are Aastveit and Tørres Trovik May 13, 2007 Introduction Motivation The last decades of advances in information technology has made it possible to access a huge amount of
More informationNOWCASTING REPORT. Updated: May 20, 2016
NOWCASTING REPORT Updated: May 20, 2016 The FRBNY Staff Nowcast for GDP growth in 2016:Q2 is 1.7%, half a percentage point higher than last week. Positive news came from manufacturing and housing data
More informationESRI Research Note Nowcasting and the Need for Timely Estimates of Movements in Irish Output
ESRI Research Note Nowcasting and the Need for Timely Estimates of Movements in Irish Output David Byrne, Kieran McQuinn and Ciara Morley Research Notes are short papers on focused research issues. Nowcasting
More informationGDP forecast errors Satish Ranchhod
GDP forecast errors Satish Ranchhod Editor s note This paper looks more closely at our forecasts of growth in Gross Domestic Product (GDP). It considers two different measures of GDP, production and expenditure,
More informationANALYSIS AND DEVELOPMENT OF PROCEDURES TO UPDATE THE KANSAS INDEX OF LEADING ECONOMIC INDICATORS RUSLAN VOLODYMYROVYCH LUKATCH
ANALYSIS AND DEVELOPMENT OF PROCEDURES TO UPDATE THE KANSAS INDEX OF LEADING ECONOMIC INDICATORS by RUSLAN VOLODYMYROVYCH LUKATCH B.S., Donetsk State University, Ukraine, 1997 A REPORT submitted in partial
More informationNOWCASTING REPORT. Updated: April 15, 2016
NOWCASTING REPORT Updated: April 15, 2016 GDP growth prospects remain moderate for the rst half of the year: the nowcasts stand at 0.8% for 2016:Q1 and 1.2% for 2016:Q2. News from this week's data releases
More informationTechnical note on seasonal adjustment for Capital goods imports
Technical note on seasonal adjustment for Capital goods imports July 1, 2013 Contents 1 Capital goods imports 2 1.1 Additive versus multiplicative seasonality..................... 2 2 Steps in the seasonal
More informationNOWCASTING THE NEW TURKISH GDP
CEFIS WORKING PAPER SERIES First Version: August 2017 NOWCASTING THE NEW TURKISH GDP Barış Soybilgen, İstanbul Bilgi University Ege Yazgan, İstanbul Bilgi University Nowcasting the New Turkish GDP Barış
More informationApproximating Fixed-Horizon Forecasts Using Fixed-Event Forecasts
Approximating Fixed-Horizon Forecasts Using Fixed-Event Forecasts Malte Knüppel and Andreea L. Vladu Deutsche Bundesbank 9th ECB Workshop on Forecasting Techniques 4 June 216 This work represents the authors
More informationInflation Report April June 2012
August, 212 Outline 1. External Conditions 2. Economic Activity in Mexico 3. Monetary Policy and Inflation Determinants. Forecasts and Balance of Risks External Conditions Global economic growth slowed
More informationThe Central Bank of Iceland forecasting record
Forecasting errors are inevitable. Some stem from errors in the models used for forecasting, others are due to inaccurate information on the economic variables on which the models are based measurement
More informationTHE APPLICATION OF GREY SYSTEM THEORY TO EXCHANGE RATE PREDICTION IN THE POST-CRISIS ERA
International Journal of Innovative Management, Information & Production ISME Internationalc20 ISSN 285-5439 Volume 2, Number 2, December 20 PP. 83-89 THE APPLICATION OF GREY SYSTEM THEORY TO EXCHANGE
More informationEUROINDICATORS WORKING GROUP THE IMPACT OF THE SEASONAL ADJUSTMENT PROCESS OF BUSINESS TENDENCY SURVEYS ON TURNING POINTS DATING
EUROINDICATORS WORKING GROUP 11 TH MEETING 4 & 5 DECEMBER 2008 EUROSTAT D1 DOC 239/08 THE IMPACT OF THE SEASONAL ADJUSTMENT PROCESS OF BUSINESS TENDENCY SURVEYS ON TURNING POINTS DATING ITEM 6.2 ON THE
More informationTime series and Forecasting
Chapter 2 Time series and Forecasting 2.1 Introduction Data are frequently recorded at regular time intervals, for instance, daily stock market indices, the monthly rate of inflation or annual profit figures.
More informationWarwick Business School Forecasting System. Summary. Ana Galvao, Anthony Garratt and James Mitchell November, 2014
Warwick Business School Forecasting System Summary Ana Galvao, Anthony Garratt and James Mitchell November, 21 The main objective of the Warwick Business School Forecasting System is to provide competitive
More informationGROSS DOMESTIC PRODUCT FOR NIGERIA
FEDERAL REPUBLIC OF NIGERIA (HE PRESIDENCY) Q1 - Q4 2011 AND Q1 2012 GROSS DOMESIC PRODUC FOR NIGERIA National Bureau of Statistics Plot 762, Independence Avenue, Central Business District, Abuja www.nigerianstat.gov.ng
More informationFaMIDAS: A Mixed Frequency Factor Model with MIDAS structure
FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure Frale C., Monteforte L. Computational and Financial Econometrics Limassol, October 2009 Introduction After the recent financial and economic
More informationShort-Term Job Growth Impacts of Hurricane Harvey on the Gulf Coast and Texas
Short-Term Job Growth Impacts of Hurricane Harvey on the Gulf Coast and Texas Keith Phillips & Christopher Slijk Federal Reserve Bank of Dallas San Antonio Branch The views expressed in this presentation
More informationLecture Prepared By: Mohammad Kamrul Arefin Lecturer, School of Business, North South University
Lecture 15 20 Prepared By: Mohammad Kamrul Arefin Lecturer, School of Business, North South University Modeling for Time Series Forecasting Forecasting is a necessary input to planning, whether in business,
More informationHandbook on Rapid Estimates
Handbook on Rapid Estimates November 13, 2015 2 Contents 7 Model selection, model specifications and a typology of rapid estimates 5 7.1 Abstract...................................... 5 7.2 Introduction....................................
More informationDates and Prices ICAEW - Manchester In Centre Programme Prices
Dates and Prices ICAEW - Manchester - 2019 In Centre Programme Prices Certificate Level GBP ( ) Intensive Accounting 690 Assurance 615 Law 615 Business, Technology and Finance 615 Mangement Information
More informationApproximating fixed-horizon forecasts using fixed-event forecasts
Approximating fixed-horizon forecasts using fixed-event forecasts Comments by Simon Price Essex Business School June 2016 Redundant disclaimer The views in this presentation are solely those of the presenter
More informationSluggish Economy Puts Pinch on Manufacturing Technology Orders
Updated Release: June 13, 2016 Contact: Penny Brown, AMT, 703-827-5275 pbrown@amtonline.org Sluggish Economy Puts Pinch on Manufacturing Technology Orders Manufacturing technology orders for were down
More informationForecasting using R. Rob J Hyndman. 1.3 Seasonality and trends. Forecasting using R 1
Forecasting using R Rob J Hyndman 1.3 Seasonality and trends Forecasting using R 1 Outline 1 Time series components 2 STL decomposition 3 Forecasting and decomposition 4 Lab session 5 Forecasting using
More informationLucrezia Reichlin London Business School & Now-Casting Economics Ltd and Silvia Miranda Agrippino, Now-Casting Economics Ltd
NOW-CASTING AND THE REAL TIME DATA FLOW Lucrezia Reichlin London Business School & Now-Casting Economics Ltd and Silvia Miranda Agrippino, Now-Casting Economics Ltd PRESENTATION AT BIS, HONG KONG 22 ND
More informationFinancial Factors in Economic Fluctuations. Lawrence Christiano Roberto Motto Massimo Rostagno
Financial Factors in Economic Fluctuations Lawrence Christiano Roberto Motto Massimo Rostagno Background Much progress made on constructing and estimating models that fit quarterly data well (Smets-Wouters,
More informationInternational Seminar on Early Warning and Business Cycle Indicators. 14 to 16 December 2009 Scheveningen, The Netherlands
ESA/STAT/AC.202/S2.2 International Seminar on Early Warning and Business Cycle Indicators 14 to 16 December 2009 Scheveningen, The Netherlands Overview of terminology for high frequency indicators Roberto
More informationCIMA Professional 2018
CIMA Professional 2018 Interactive Timetable Version 16.25 Information last updated 06/08/18 Please note: Information and dates in this timetable are subject to change. A better way of learning that s
More informationPANEL DISCUSSION: THE ROLE OF POTENTIAL OUTPUT IN POLICYMAKING
PANEL DISCUSSION: THE ROLE OF POTENTIAL OUTPUT IN POLICYMAKING James Bullard* Federal Reserve Bank of St. Louis 33rd Annual Economic Policy Conference St. Louis, MO October 17, 2008 Views expressed are
More informationCIMA Professional 2018
CIMA Professional 2018 Newcastle Interactive Timetable Version 10.20 Information last updated 12/06/18 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationLecture Prepared By: Mohammad Kamrul Arefin Lecturer, School of Business, North South University
Lecture 15 20 Prepared By: Mohammad Kamrul Arefin Lecturer, School of Business, North South University Modeling for Time Series Forecasting Forecasting is a necessary input to planning, whether in business,
More informationMultivariate Regression Model Results
Updated: August, 0 Page of Multivariate Regression Model Results 4 5 6 7 8 This exhibit provides the results of the load model forecast discussed in Schedule. Included is the forecast of short term system
More informationTime Series and Forecasting
Time Series and Forecasting Introduction to Forecasting n What is forecasting? n Primary Function is to Predict the Future using (time series related or other) data we have in hand n Why are we interested?
More informationTime Series and Forecasting
Time Series and Forecasting Introduction to Forecasting n What is forecasting? n Primary Function is to Predict the Future using (time series related or other) data we have in hand n Why are we interested?
More informationNSP Electric - Minnesota Annual Report Peak Demand and Annual Electric Consumption Forecast
Page 1 of 5 7610.0320 - Forecast Methodology NSP Electric - Minnesota Annual Report Peak Demand and Annual Electric Consumption Forecast OVERALL METHODOLOGICAL FRAMEWORK Xcel Energy prepared its forecast
More informationTime Series Analysis of Currency in Circulation in Nigeria
ISSN -3 (Paper) ISSN 5-091 (Online) Time Series Analysis of Currency in Circulation in Nigeria Omekara C.O Okereke O.E. Ire K.I. Irokwe O. Department of Statistics, Michael Okpara University of Agriculture
More informationThe Case of Japan. ESRI CEPREMAP Joint Workshop November 13, Bank of Japan
New Monthly Estimation Approach for Nowcasting GDP Growth: The Case of Japan ESRI CEPREMAP Joint Workshop November 13, 2014 Naoko Hara Bank of Japan * Views expressed in this paper are those of the authors,
More informationTable 01A. End of Period End of Period End of Period Period Average Period Average Period Average
SUMMARY EXCHANGE RATE DATA BANK OF ZAMBIA MID-RATES Table 01A Period K/USD K/GBP K/ZAR End of Period End of Period End of Period Period Average Period Average Period Average Monthly January 6.48 6.46 9.82
More informationDesign of a Weather-Normalization Forecasting Model
Design of a Weather-Normalization Forecasting Model Final Briefing 09 May 2014 Sponsor: Northern Virginia Electric Cooperative Abram Gross Jedidiah Shirey Yafeng Peng OR-699 Agenda Background Problem Statement
More informationThe TransPacific agreement A good thing for VietNam?
The TransPacific agreement A good thing for VietNam? Jean Louis Brillet, France For presentation at the LINK 2014 Conference New York, 22nd 24th October, 2014 Advertisement!!! The model uses EViews The
More informationLong-term Water Quality Monitoring in Estero Bay
Long-term Water Quality Monitoring in Estero Bay Keith Kibbey Laboratory Director Lee County Environmental Laboratory Division of Natural Resource Management Estero Bay Monitoring Programs Three significant
More informationTo understand the behavior of NR prices across key markets, during , with focus on:
Jom Jacob The Rubber Board*, India (* The views presented here do not necessarily imply those of the organization ) To understand the behavior of NR prices across key markets, during 7-2012, with focus
More informationCITY OF MESQUITE Quarterly Investment Report Overview Quarter Ending September 30, 2018
CITY OF MESQUITE Quarterly Investment Report Overview Quarter Ending September 30, 2018 Investment objectives are safety, liquidity, yield and public trust. Portfolio objective is to meet or exceed the
More informationCIMA Professional
CIMA Professional 201819 Birmingham Interactive Timetable Version 3.1 Information last updated 12/10/18 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationNowcasting at the Italian Fiscal Council Libero Monteforte Parliamentary Budget Office (PBO)
Nowcasting at the Italian Fiscal Council Libero Monteforte Parliamentary Budget Office (PBO) Bratislava, 23 November 2018 1 Outline Introduction Nowcasting for IFI s Nowcasting at PBO: Introduction The
More informationCIMA Professional
CIMA Professional 201819 Manchester Interactive Timetable Version 3.1 Information last updated 12/10/18 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationAnimal Spirits, Fundamental Factors and Business Cycle Fluctuations
Animal Spirits, Fundamental Factors and Business Cycle Fluctuations Stephane Dées Srečko Zimic Banque de France European Central Bank January 6, 218 Disclaimer Any views expressed represent those of the
More informationAbstract. Keywords: Factor Models, Forecasting, Large Cross-Sections, Missing data, EM algorithm.
Maximum likelihood estimation of large factor model on datasets with missing data: forecasting euro area GDP with mixed frequency and short-history indicators. Marta Bańbura 1 and Michele Modugno 2 Abstract
More informationCITY OF MESQUITE Quarterly Investment Report Overview Quarter Ending June 30, 2018
CITY OF MESQUITE Quarterly Investment Report Overview Quarter Ending June 30, 2018 Investment objectives are safety, liquidity, yield and public trust. Portfolio objective is to meet or exceed the average
More informationSuan Sunandha Rajabhat University
Forecasting Exchange Rate between Thai Baht and the US Dollar Using Time Series Analysis Kunya Bowornchockchai Suan Sunandha Rajabhat University INTRODUCTION The objective of this research is to forecast
More informationA FUZZY TIME SERIES-MARKOV CHAIN MODEL WITH AN APPLICATION TO FORECAST THE EXCHANGE RATE BETWEEN THE TAIWAN AND US DOLLAR.
International Journal of Innovative Computing, Information and Control ICIC International c 2012 ISSN 1349-4198 Volume 8, Number 7(B), July 2012 pp. 4931 4942 A FUZZY TIME SERIES-MARKOV CHAIN MODEL WITH
More informationD Agostino, Antonello; McQuinn, Kieran and O Brien, Derry European Central Bank, Central Bank of Ireland, Central Bank of Ireland
MPRA Munich Personal RePEc Archive Nowcasting Irish GDP D Agostino, Antonello; McQuinn, Kieran and O Brien, Derry European Central Bank, Central Bank of Ireland, Central Bank of Ireland 2011 Online at
More informationE C O N O M I C R E V I E W
UNDP NAMIBIA E C O N O M I C R E V I E W 2 0 0 7 1 Introduction 1 2 Overview of the Namibian Economy 2 2.1 Structure of the Economy 2 3 Economic Policy 5 4 Economic Trends 7 4.1 Primary Industry 7 4.2
More informationPublic Library Use and Economic Hard Times: Analysis of Recent Data
Public Library Use and Economic Hard Times: Analysis of Recent Data A Report Prepared for The American Library Association by The Library Research Center University of Illinois at Urbana Champaign April
More informationAsitha Kodippili. Deepthika Senaratne. Department of Mathematics and Computer Science,Fayetteville State University, USA.
Forecasting Tourist Arrivals to Sri Lanka Using Seasonal ARIMA Asitha Kodippili Department of Mathematics and Computer Science,Fayetteville State University, USA. akodippili@uncfsu.edu Deepthika Senaratne
More informationForecasting. Copyright 2015 Pearson Education, Inc.
5 Forecasting To accompany Quantitative Analysis for Management, Twelfth Edition, by Render, Stair, Hanna and Hale Power Point slides created by Jeff Heyl Copyright 2015 Pearson Education, Inc. LEARNING
More informationOperations Management
Operations Management Chapter 4 Forecasting PowerPoint presentation to accompany Heizer/Render Principles of Operations Management, 7e Operations Management, 9e 2008 Prentice Hall, Inc. 4 1 Outline Global
More informationACCA Interactive Timetable & Fees
ACCA Interactive Timetable & Fees 2018/19 Professional Version 1.1 Information last updated tember 2018 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationACCA Interactive Timetable & Fees
ACCA Interactive Timetable & Fees 2018/19 Professional Version 1.1 Information last updated tember 2018 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationAverage 175, , , , , , ,046 YTD Total 1,098,649 1,509,593 1,868,795 1,418, ,169 1,977,225 2,065,321
AGRICULTURE 01-Agriculture JUL 2,944-4,465 1,783-146 102 AUG 2,753 6,497 5,321 1,233 1,678 744 1,469 SEP - 4,274 4,183 1,596 - - 238 OCT 2,694 - - 1,032 340-276 NOV 1,979-5,822 637 3,221 1,923 1,532 DEC
More informationAverage 175, , , , , , ,940 YTD Total 944,460 1,284,944 1,635,177 1,183, ,954 1,744,134 1,565,640
AGRICULTURE 01-Agriculture JUL 2,944-4,465 1,783-146 102 AUG 2,753 6,497 5,321 1,233 1,678 744 1,469 SEP - 4,274 4,183 1,596 - - 238 OCT 2,694 - - 1,032 340-276 NOV 1,979-5,822 637 3,221 1,923 1,532 DEC
More informationEXAMINATIONS OF THE ROYAL STATISTICAL SOCIETY
EXAMINATIONS OF THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA, 011 MODULE 3 : Stochastic processes and time series Time allowed: Three Hours Candidates should answer FIVE questions. All questions carry
More informationSTATISTICAL FORECASTING and SEASONALITY (M. E. Ippolito; )
STATISTICAL FORECASTING and SEASONALITY (M. E. Ippolito; 10-6-13) PART I OVERVIEW The following discussion expands upon exponential smoothing and seasonality as presented in Chapter 11, Forecasting, in
More informationFactor Mimicking Portfolios
Factor Mimicking Portfolios Bernt Arne Ødegaard 25 October 2018 Contents 1 Factor Mimicking Portfolios 1 1.1 Economic Tracking Portfolios.................................................. 1 1.2 Example.............................................................
More informationACCA Interactive Timetable & Fees
ACCA Interactive Timetable & Fees 2018/19 Professional Version 2.1 Information last updated uary 2019 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationNowcasting gross domestic product in Japan using professional forecasters information
Kanagawa University Economic Society Discussion Paper No. 2017-4 Nowcasting gross domestic product in Japan using professional forecasters information Nobuo Iizuka March 9, 2018 Nowcasting gross domestic
More informationFresh perspectives on unobservable variables: Data decomposition of the Kalman smoother
Fresh perspectives on unobservable variables: Data decomposition of the Kalman smoother AN 2013/09 Nicholas Sander December 2013 Reserve Bank of New Zealand Analytical Note series ISSN 2230 5505 Reserve
More informationREPORT ON LABOUR FORECASTING FOR CONSTRUCTION
REPORT ON LABOUR FORECASTING FOR CONSTRUCTION For: Project: XYZ Local Authority New Sample Project Contact us: Construction Skills & Whole Life Consultants Limited Dundee University Incubator James Lindsay
More informationACCA Interactive Timetable & Fees
ACCA Interactive Timetable & Fees 2018/19 Professional London Version 1.1 Information last updated 3 October 2018 Please note: Information and dates in this timetable are subject to change. A better way
More informationNowcasting. Domenico Giannone Université Libre de Bruxelles and CEPR
Nowcasting Domenico Giannone Université Libre de Bruxelles and CEPR 3rd VALE-EPGE Global Economic Conference Business Cycles Rio de Janeiro, May 2013 Nowcasting Contraction of the terms Now and Forecasting
More informationACCA Interactive Timetable & Fees
ACCA Interactive Timetable & Fees 2018/19 Professional Milton Keynes Version 1.1 Information last updated tember 2018 Please note: Information and dates in this timetable are subject to change. A better
More informationInvestment in Austria: a view from the WIFO Investitionstest
Investment in Austria: a view from the WIFO Investitionstest Werner Hölzl and Gerhard Schwarz Wien 20 März 2017 Introduction Forecasting and nowcasting investment is notoriously difficult It is crucial
More informationACCA Interactive Timetable & Fees
ACCA Interactive Timetable & Fees 2018/19 Professional Version 3.1 Information last updated 1st May 2018 Please note: Information and dates in this timetable are subject to change. A better way of learning
More informationProgram. The. provide the. coefficientss. (b) References. y Watson. probability (1991), "A. Stock. Arouba, Diebold conditions" based on monthly
Macroeconomic Forecasting Topics October 6 th to 10 th, 2014 Banco Central de Venezuela Caracas, Venezuela Program Professor: Pablo Lavado The aim of this course is to provide the basis for short term
More informationLecture 2. Business Cycle Measurement. Randall Romero Aguilar, PhD II Semestre 2017 Last updated: August 18, 2017
Lecture 2 Business Cycle Measurement Randall Romero Aguilar, PhD II Semestre 2017 Last updated: August 18, 2017 Universidad de Costa Rica EC3201 - Teoría Macroeconómica 2 Table of contents 1. Introduction
More informationRecord date Payment date PID element Non-PID element. 08 Sep Oct p p. 01 Dec Jan p 9.85p
2017/18 Record date Payment date PID element Non-PID element 08 Sep 17 06 Oct 17 9.85p - 9.85p 01 Dec 17 05 Jan 18-9.85p 9.85p 09 Mar 18 06 Apr 18 9.85p - 9.85p Final 22 Jun 18 27 Jul 18 14.65p - 14.65p
More information