Working Party on Forest Economics and Statistics 27 th Session, 22-24 March 2005, Geneva Evaluation of Timber Committee Forecasts Goal: Improve response.

Slides:



Advertisements
Similar presentations
IHPA and the National Efficient Price (NEP) Independent Hospital Pricing Authority.
Advertisements

Plans to improve estimators to better utilize panel data John Coulston Southern Research Station Forest Inventory and Analysis.
Forecasting Performance Measures Performance Measures.
Graphs Showing Forecasts made for 70th Timber Committee meeting (supplement) UNECE/FAO Forestry and Timber Section Geneva, Switzerland October 2012.
LECTURE 5 Assertions and Tests of Detail
Econ Prof. Buckles1 Welcome to Econometrics What is Econometrics?
Economics 20 - Prof. Anderson
Validation and Monitoring Measures of Accuracy Combining Forecasts Managing the Forecasting Process Monitoring & Control.
Joint Session of the ECE Timber Committee and the FAO European Forestry Commission Location, Turkey – October 2011 Graphs Showing Forecasts made.
Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Forecasting Operations Chapter 12 Roberta Russell & Bernard.
1.Explain role of demand management 2.Differentiate between demand management and forecasting 3.Describe various forecasting procedures 4.Develop forecast.
Demand Planning: Forecasting and Demand Management
Best Practices in Communications Forum Vancouver, Canada, 6-8 October 2002 Photo: APA Global Outlook—Supply & Demand for Wood Products By Ed Pepke Forest.
Chapter 8 Introduction to Hypothesis Testing. Hypothesis Testing Hypothesis testing is a statistical procedure Allows researchers to use sample data to.
1 Formal Evaluation Techniques Chapter 7. 2 test set error rates, confusion matrices, lift charts Focusing on formal evaluation methods for supervised.
ASSESSING THE EFFICIENCY OF EARLY RELEASE ESTIMATES OF ECONOMIC STATISTICS Charles Aspden Working Party on National Accounts, October 2008.
Graphs Showing Forecasts made for 72nd Committee on Forests and the Forest Industry, UNECE/FAO Forestry and Timber Section Kazan, Russian Federation
IMPROVING DIABETES MANAGEMENT IN PRIMARY CARE
Joint UNECE/FAO Working Party on Forest Economics and Statistics, March 2005, Geneva Consistency of European forest products statistics
S7: Audit Planning. Session Objectives To explain the need for planning To explain the need for planning To outline the essential elements of planning.
Demand Planning: Forecasting and Demand Management CHAPTER TWELVE McGraw-Hill/Irwin Copyright © 2011 by the McGraw-Hill Companies, Inc. All rights reserved.
Audit Planning. Session Objectives To explain the need for planning To outline the essential elements of planning process To finalise the audit approach.
Session 7.11 Session overview Monetary Unit Sampling (MUS)  advantages  limitations, and  relevance to substantive test of details Steps in MUS.
Auditing: The Art and Science of Assurance Engagements
Copyright © 2007 Pearson Education Canada 1 Chapter 14: Completing the Tests in the Sales and Collection Cycle: Accounts Receivable.
Sampling and Sample Size Part 1 Cally Ardington. Course Overview 1.What is Evaluation? 2.Outcomes, Impact, and Indicators 3.Why Randomise? 4.How to Randomise?
Publication / Fit for Purpose Kirsty Anderson Principal Information Analyst.
{ Methodology of Sales Forecast Brenda Pérez Elizabeth Morales Viridiana Breceda Aimee Segovia.
Session II.I Improvement in economic surveys Workshop on national accounts for Asian member countries of the organization of Islamic Conference Ankara,
UNECE TIMBER COMMITTEE Sixtieth session, September 2002 Panels Timber Committee forecasts by Mr. Jorge Najera Expert presentation by Mr. Olli Koskiranta,
EUROPEAN FORESTRY COMMISSION Thirtieth session Rome, 10 October 2000 TIMBER COMMITTEE Fifty-eighth session SAWN HARDWOODS AND LOGS Secretariat introduction.
EUROPEAN FORESTRY COMMISSION Thirtieth session Rome, 10 October 2000 TIMBER COMMITTEE Fifty-eighth session SOFTWOODS: SAWNWOOD AND LOGS Secretariat introduction.
Developing Sales Forecasts. Sales Forecasts Objectives: Objectives: Determining sales force size. Determining sales force size. Designing territories.
Sunglasses Sales Excellence Discussion. Sunglasses Identify and describe at least one further feature of this time series data with reasons. – Sunglasses.
FORECASTING Kusdhianto Setiawan Gadjah Mada University.
EGEE-II INFSO-RI Enabling Grids for E-sciencE NA3 procedures.
Demand Forecasting Prof. Ravikesh Srivastava Lecture-11.
Please hand in homework on Law of Large Numbers Dan Gilbert “Stumbling on Happiness”
Economics 173 Business Statistics Lecture 27 © Fall 2001, Professor J. Petry
UNECE TIMBER COMMITTEE Fifty-ninth session 2-5 October 2001 STRATEGIC REVIEW OF INTEGRATED PROGRAMME Kit Prins Chief, Timber Section.
Copyright © 2014 Pearson Education. All rights reserved Sampling Distributions LEARNING GOAL Understand the fundamental ideas of sampling distributions.
UNECE TIMBER COMMITTEE Fifty-ninth session 2-5 October 2001 SAWN SOFTWOOD Secretariat introduction by Mr. Ed Pepke, Marketing Specialist, UNECE & FAO Timber.
UNECE TIMBER COMMITTEE Sixtieth session, September 2002 Sawn Hardwood Timber Committee forecasts by Mr. Michael Buckley, Wood Industry Consultant,
Joint UNECE/FAO Working Party on Forest Economics and Statistics, 26th session March 2004, Geneva Main results and conclusions of the European Forest.
1 Section 8.4 Testing a claim about a mean (σ known) Objective For a population with mean µ (with σ known), use a sample (with a sample mean) to test a.
ACF Office of Community Services (OCS) Community Services Block Grant (CSBG) Survey of Grantees Satisfaction with OCS Survey of Eligible Entities Satisfaction.
Exports and imports of some product groups 2009 Source: Statistics Sweden Total exports: 998 billion SEK (2008: 1,194 billion SEK) Total imports: 911 billion.
F8: Audit and Assurance. 2 Designed to give you knowledge and application of: Section A: Audit Framework and Regulation Section B: Internal audit Section.
Forecasting. Model with indicator variables The choice of a forecasting technique depends on the components identified in the time series. The techniques.
Exports and Imports of some Product Groups 2013 Source: Statistics Sweden Billion SEK Total Exports: 1,091 Billion SEK (2012: 1,170 Billion SEK ) Total.
Paper Consumption in Sweden Source: Statistics Sweden, Swedish Forest Industries Federation Million Tonnes.
MARKETING RESEARCH.
WIND And Solar ENERGY CONVERSION MODEL GUIDELINES Consultation update – September 2016 Presented by Marcelle Gannon.
ELECTRICITY DISTRIBUTION INDUSTRY DECISION
UNECE/FAO Team of Specialists on Forest Products Markets & Marketing
UNECE TIMBER COMMITTEE
8.1 Sampling Distributions
Production and Exports Sawn Softwood
Sampling Distribution
Sampling Distribution
An overview to this point
Global Outlook—Supply & Demand for Wood Products
The Ecology of Responsibility:
Warmup To check the accuracy of a scale, a weight is weighed repeatedly. The scale readings are normally distributed with a standard deviation of
Economics 20 - Prof. Anderson
Challenge & Constraint
Prodcom ESTP course October 2010
UNECE TIMBER COMMITTEE ANNUAL MARKET DISCUSSIONS
Sawn Softwood Sawn Softwood
Analysing the reliability of forecast information provided by UNECE member states Master’s thesis by Markus Stolze.
Presentation transcript:

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Evaluation of Timber Committee Forecasts Goal: Improve response rate and forecast accuracy What is the response rate What is the accuracy of the forecasts

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Responses

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Response Completeness - forecast for current year

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Completeness of Response

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Responses to specific item – Sawn softwood and OSB

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Forecast Accuracy Constraints One set of forecasts (current and next year) to limit initial work Data sufficiently far back so that forecast years would have more or less final data – October 2002 One product – sawn softwood 31 replies to this item (although not every country forecast all 6 possible data points)

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Summary Statistics Bear in mind More detailed statistics available in attached paper (excluding dropped outliers) This is only for one product, one set of forecasts No weighting by size of country

Forecast Error Distribution - Exports

Forecast Error Distribution - Imports

Forecast Error Distribution - Production

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Significant errors What is a “significant” error? When the direction of the forecast is opposite to the actual outcome We used a cutoff of forecast >1% and actual 1%

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva “No change” forecasts What is a “no change” forecast? Where the forecast % change is between +0.5% and –0.5% Such a forecast could be the outcome of a careful process of consultation, estimation and modeling or simply rounding/repeating an earlier figure

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Are the forecasts better than guessing results of EAD analysis 5 of the 6 series analysed showed a close to normal distribution (the exception was 2002/2001 exports) The forecasts were better than random guessing in more than 80% of the cases (>86% for most series) Forecasts appear to be more conservative than warranted by random outcomes There is still room for improvement

Working Party on Forest Economics and Statistics 27 th Session, March 2005, Geneva Future steps Analytical Cover earlier years (1997, 1987) to compare current forecast success with other periods Cover other products to see if trend in sawn softwood is representative (one roundwood, one panel) Accomplishing goals Reaching out to find more respondents Feedback to show how successful forecasts are, encourage forecasters to “risk” Training / networking to share knowledge and “best practice”