1 SHORT-RUN DENSITY FORECAST FOR ETHANOL AND MTBE PRICES Michael H. Lau Joe L. Outlaw James W. Richardson Brian K. Herbst Texas A&M University Department.

Slides:



Advertisements
Similar presentations
SEASONALITY IN THE THAI STOCK INDEX
Advertisements

Line Efficiency     Percentage Month Today’s Date
WV Faculty Salaries Proposal. Full Professor WV salaries.
Unit Number Oct 2011 Nov 2011 Dec 2011 Jan 2012 Feb 2012 Mar 2012 Apr 2012 May 2012 Jun 2012 Jul 2012 Aug 2012 Sep (3/4 Unit) 7 8 Units.
HOW TO MAKE A CLIMATE GRAPH CLIMATE GRAPHING ASSIGNMENT PT.2.
Roberta Russell & Bernard W. Taylor, III
Leading People, Leading Organizations Information Center Department Statistics Report October 2003 Deborah Keary, SPHR.
Market Analysis & Forecasting Trends Businesses attempt to predict the future – need to plan ahead Why?
Time-Series Forecast Models EXAMPLE Monthly Sales ( in units ) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Data Point or (observation) MGMT E-5070.
Line Graph- a graph that uses a line to show the relationship between two sets of data. Line graphs show how data changes over time.
ProjectImpactResourcesDeadlineResourcesDeadline Forecast Plan Time Resources Risk 001xx 002xx 003xx 004xx 005xx 006xx 007xx TotalXX Example 1: Portfolio.
Quantitative Forecasting Methods (Non-Naive)
Chapter 12 Forecasting. Lecture Outline Strategic Role of Forecasting in SCM Components of Forecasting Demand Time Series Methods Forecast Accuracy Regression.
1 Upper Basin Snowpack as of 3/26/2014
Jan 2016 Solar Lunar Data.

The 6 steps of data collection:
Q1 Jan Feb Mar ENTER TEXT HERE Notes
Comparative Statistics September 2017

Project timeline # 3 Step # 3 is about x, y and z # 2
Average Monthly Temperature and Rainfall
Comparative Statistics June 2017


Mammoth Caves National Park, Kentucky
2017 Jan Sun Mon Tue Wed Thu Fri Sat

Gantt Chart Enter Year Here Activities Jan Feb Mar Apr May Jun Jul Aug
Q1 Q2 Q3 Q4 PRODUCT ROADMAP TITLE Roadmap Tagline MILESTONE MILESTONE
Free PPT Diagrams : ALLPPT.com


Calendar Year 2009 Insure Oklahoma Total & Projected Enrollment
MONTH CYCLE BEGINS CYCLE ENDS DUE TO FINANCE JUL /2/2015
Jan Sun Mon Tue Wed Thu Fri Sat

©G Dear 2008 – Not to be sold/Free to use
Electricity Cost and Use – FY 2016 and FY 2017
Agricultural Marketing

Tutorial 1 Inferential Statistics, Statistical Modelling & Survey Methods (BS2506) Pairach Piboonrungroj (Champ)
Agricultural Marketing
Agricultural Marketing
Unemployment in Today’s Economy
Agricultural Marketing
Text for section 1 1 Text for section 2 2 Text for section 3 3
Text for section 1 1 Text for section 2 2 Text for section 3 3
Operations Management Dr. Ron Lembke
Text for section 1 1 Text for section 2 2 Text for section 3 3
Operations Management Dr. Ron Lembke
Text for section 1 1 Text for section 2 2 Text for section 3 3
Q1 Q2 Q3 Q4 PRODUCT ROADMAP TITLE Roadmap Tagline MILESTONE MILESTONE
Free PPT Diagrams : ALLPPT.com


Agricultural Marketing
Text for section 1 1 Text for section 2 2 Text for section 3 3
Text for section 1 1 Text for section 2 2 Text for section 3 3
Text for section 1 1 Text for section 2 2 Text for section 3 3
Objective - To make a line graph.
Text for section 1 1 Text for section 2 2 Text for section 3 3
Text for section 1 1 Text for section 2 2 Text for section 3 3
Text for section 1 1 Text for section 2 2 Text for section 3 3
Project timeline # 3 Step # 3 is about x, y and z # 2
Agricultural Marketing
TIMELINE NAME OF PROJECT Today 2016 Jan Feb Mar Apr May Jun

Table 5. Johansen Cointegration Test Results (Lag length - 2)
Q1 Q2 Q3 Q4 PRODUCT ROADMAP TITLE Roadmap Tagline MILESTONE MILESTONE
Presentation transcript:

1 SHORT-RUN DENSITY FORECAST FOR ETHANOL AND MTBE PRICES Michael H. Lau Joe L. Outlaw James W. Richardson Brian K. Herbst Texas A&M University Department of Agricultural Economics Agriculture as a Producer and Consumer Energy Conference Arlington, VA, June 24-25, 2004

2 Introduction Rapidly increasing ethanol production. –The National Energy Act exemption and the Clean Air Act of 1990 aided ethanol growth. Gallagher, et. al. (2003) and Lidderdale (2000) looked at long run effects of renewable fuel standards. Ethanol price determined by wholesale gasoline price and the excise tax exemption on blended gasoline (Coltrain, 2001; CFDC, 2004; NDLC, 2001).

3 Objectives and Methods Create short-run probabilistic (density) forecasts for ethanol and MTBE prices for a 24-month period from October 2003 to September –Why probabilistic (density) forecasts? The results from this study will provide interested parties an unbiased analysis and forecast of ethanol and MTBE prices as production and demand for ethanol continues to grow.

4 Historical Ethanol and MTBE Price Nov to Sept Ethanol and MTBE prices are available from Hart’s Oxy-Fuel News. Wholesale gasoline price is available from the Energy Information Agency (EIA) of the U.S. Department of Energy (DOE).

5 Summary Statistics for Ethanol and MTBE Prices Nov to Sept Ethanol PriceMTBE PriceWholesale Gasoline Price Mean Standard Deviation % LCI % UCI CV Min Median Max Autocorrelation Coefficient Source: Energy Information Agency, U.S. Department of Energy.

6 Other Exogenous Variables Considered for Forecasting Retail gasoline price, ethanol fuel demand, gasoline production, diesel price, diesel production, gasoline stock, diesel stock, oil production, oil imports, oxygenated gasoline production, reformulated gasoline production, oxygenate stock, corn prices, and corn production. None were statistically significant and did not improve the forecasting abilities of the VEC model based on the mean absolute percent error (MAPE)

7 Augmented Dickey Fuller and Johansen Co-integration Tests Co-integrating Equation Augmented Dickey Fuller Test for Stationarity. VariableLevels*First Difference** Ethanol Price MTBE Price Wholesale Gasoline Price * Fail to reject "Ho: Data series is non-stationary" at 1 % significance level. ** Reject "Ho: Data is non-stationary at 1% significance level. Johansen Unrestricted Co-integration Rank Test HypothesizedTrace5 Percent1 Percent No. of CE(s)EigenvalueStatisticCritical Value None ** At most 1 * *(**) denotes rejection of the hypothesis at the 5%(1%) level Trace test indicates 2 co-integrating equation(s) at the 5% level Trace test indicates 1 co-integrating equation(s) at the 1% level

8 Ethanol and MTBE Price VEC Equations Out of Sample MTBE Price MAPE 6 % MTBE Price CoefficientStd. ErrorT-StatisticProb. MTBE Price t MTBE Price t Ethanol Price t Wholesale Gasoline Price t R-squared0.5822Durbin-Watson Statistic Out of Sample Ethanol Price MAPE 8.6% Ethanol Price CoefficientStd. ErrorT-StatisticProb. Co-Integrating Eq. t MTBE Price t MTBE Price t Ethanol Price t Ethanol Price t Ethanol Price t Ethanol Price t Constant Wholesale Gasoline Price t Subsidy t R-squared0.5786Durbin-Watson Statistic1.8606

9 Ethanol and MTBE Price Forecasts Oct to Sept Historical Prices Out of Sample Forecast Period Forecasted Prices

10 Simulation Summary Statistics Ethanol and MTBE Prices Oct to Sept Ethanol PriceMeanSt. Dev.C.V.MinimumMaximum MTBE PriceMeanSt. Dev.C.V.MinimumMaximum Oct Oct Nov Nov Dec Dec Jan Jan Feb Feb Mar Mar Apr Apr May May Jun Jun Jul Jul Aug Aug Sep Sep Oct Oct Nov Nov Dec Dec Jan Jan Feb Feb Mar Mar Apr Apr May May Jun Jun Jul Jul Aug Aug Sep Sep

11 PDF Graphs for Ethanol and MTBE Prices Jan and July 2005

12 Fan Graph for Ethanol Price Oct to Sept. 2005

13 Fan Graph for MTBE Price Oct to Sept. 2005

14 Conclusions and Questions VEC is successfully for forecasting Ethanol and MTBE Prices from Oct to Sept Simulation is beneficial for predicting density forecasts of ethanol and MTBE prices. Limitations of Study –Dependent on forecasted values of wholesale gasoline price. –Perpetual forecast should be used where the coefficients are updated as realized prices occur for ethanol, MTBE, and wholesale gasoline.