1. The Ohio DOT Inflation Forecasting and Related Activities Jennifer McAllister, Ohio DOT presenting for Jeff Hisem

2. What is BART?? Who does inflation forecasting at Ohio DOT? –BART (Bid Analysis & Review Team) Created by Jeff Hisem, Office of Estimating Multi-person group combines the knowledge and expertise of economics and construction Currently 2 economists Open position for engineer/construction experience

3. 8/2/2015 BART’s History with Forecasting In 2005 BART was requested to track and explain historical trends in construction prices. Starting in 2006, BART was requested by the director to create an inflation forecast. –In March 2006, BART presented its first forecast Cost Estimation and Inflation Trends Produce forecast January and July each year –Annual forecast out five years into future

4. Predicting OhDOT Construction Cost Inflation Monitor past OhDOT in-place construction cost trends. Research developments for key construction commodities. Model likely scenarios of in-place construction costs 8/2/2015

5. Monitor Construction Cost Trends

6. 8/2/2015

7. OhDOT In-Place Vs. BLS Hwy Index 8/2/2015

8. Research Developments for Key Construction Commodities Key Drivers Aggregate Ready Mix Concrete –Cement Energy –Oil Diesel Liquid asphalt –Electricity –Natural gas Steel Labor Macro Issues US Construction Demand Exchange rates World demand Regional Factors –Ohio construction economy –Commodity specific supply/demand 8/2/2015

9. “How might we model scenarios of in-place construction costs?” 1.Consultant – Pay for a final forecast 2.Best guess based upon industry publications 3.A spreadsheet model tracking labor, energy, materials, and equipment costs – Provides a system for a rudimentary forecast 4. Purely statistical model – Provides a statistically defensible forecast Methods 3 and 4 allow for in-house scenario testing Simple Complex

10. Model Likely Scenarios Of In-Place Construction Costs (continued) Key considerations for forecasting group –Group with multiple perspectives –Unbiased & insulated from politics –Group consensus forecast (not an average) –Inclusive process that informs key stake holders: Planning Finance } Provide insight about OhDOT’s future spending plans so that these expenditures can be included in the forecast model.

11. Predicted Cost Inflation CY06-CY10: January 2006 CY06CY07CY08CY09CY10 High12.0%7.0%6.0% 5.0% Most Likely8.5% [12.6%]5.5%5.0%4.0% Low7.0%4.5%4.0%3.0% FY07FY08FY09FY10FY11 High14.0%7.0%6.0%5.5% Most Likely11.5% [11.6%]6.0%4.5%4.0% Low8.0%4.0%3.5%3.0% Predicted Cost Inflation FY07-FY11: July 2006 [%] – Actual construction cost inflation (OhDOT Construction Cost Index) Historical OhDOT Forecasts

12. CY07CY08CY09CY10CY11 High10.5%9.5%7.0%5.0% Most Likely6.0% [6.3%]5.5%5.0%4.0% Low4.0%3.5% 3.0% Predicted Cost Inflation CY07-CY11: January 2007 FY08FY09FY10FY11FY12 High14.5%14.0%13.0%10.0%8.0% Most Likely10.0% [4.4%]10.0%8.0%6.0%5.0% Low7.0%6.5%5.0%4.0%3.0% Predicted Cost Inflation FY08-FY12: July 2007 Historical OhDOT Forecasts [%] – Actual construction cost inflation (OhDOT Construction Cost Index)

13. FY08FY09FY10FY11FY12 Business Plan10.0%8.0%7.0%6.0%5.0% Budget Forecast Inflation FY08-FY12: November 2007 CY08CY09CY10CY11CY12 High7.0%6.0% Most Likely5.0%4.0% 4.5% Low-1.0%-2.0%0.0%2.0% Predicted Cost Inflation CY08-CY12: January 2008 Historical OhDOT Forecasts

14. FY09FY10FY11FY12FY13 High12%10%9%8%7% Most Likely7.5%6%5%4% Low4%2% Predicted Cost Inflation FY09-FY13: July 2008 Historical OhDOT Forecasts

15. Application of inflation forecast Inflation adjust bid histories for creation of bid history models used in Estimator and CES.

16. Application of inflation forecast OhDOT administration determines own inflation forecast for program budgeting (after BART construction cost forecast) Budget forecast application –Planning future road maintenance costs. –Planning estimates for major projects. In Estimator software inflation applied as contingency. Inflation calculated for mid-year of construction –“Inflation calculator:” tool available to aid calculation

17. Review Forecast to Actual Continually improve the methods for forecasting

18. Energy Diesel –Of all our commodities, diesel is the most prone to international influences Liquid Asphalt –Pricing is regionally based –Few regional refineries –OhDOT is a major consumer of asphalt* –Shortage of polymer modified asphalt Production interactions between asphalt, diesel, and gasoline affect pricing Speculation trading Exchange Rates 8/2/2015

19. Energy – Liquid Asphalt OhDOT placing index –Indicator of state asphalt binder prices 8/2/2015

20. West Texas Intermediate Oil Price: Four Scenarios 8/2/2015 Scenarios incorporated in July 2008 construction cost forecast.

21. Steel Iron & Steel Products (WPU101) rose 37% from December 2007 through June 2008. 8/2/2015

22. Iron and Steel Producer Price Index

23. Steel Input costs and manufacturing costs: –Rising energy and transport costs –Rising thermal and coking coal prices –Increases in iron ore & scrap steel costs in 2008. Weak dollar –Reduced imports –Increased exports Result: rapidly rising prices in short-term –Iron & Steel Products (WPU101) rose 37% from December 2007 through June 2008. Assumption: Short-term price increases that are maintained in the long-term. 8/2/2015

24. U.S. Gross Domestic Product GDP growth acts as a proxy for overall construction demand in the US. GDP ASSUMPTIONS: –BART – GDP growth is slow in the short term and improves towards the long term rate of ~ 3% - 4% 8/2/2015 Calendar Year 200820092010201120122013 US GDP GROWTH: 0.50%0.75%2.00%2.50%3.00%

25. Commodities, GDP and the OhDOT Index STAGFLATION: “an inflationary period accompanied by rising unemployment and lack of growth in consumer demand and business activity” –For the first time, OhDOT forecasts an economic future in which we must marry rising commodity prices with an overall depressed demand for construction services. OhDOT Index = ƒ(commodity prices, economy’s health) 8/2/2015

26. Competition and Inflation 8/2/2015 Through many studies, OhDOT has proven that increased competition has a downward effect on prices. Recent declines in vendor competition may be a result of the challenges associated with volatile commodity prices.

27. Statistical Inflation Forecast Model The model says that most of the movement of the OhDOT Cost Index since 2002 can be estimated by tracking: –West Texas Intermediate Oil Prices –Steel Mill Prices –The Price for Asphalt binder type PG 64-22 –U.S. Gross Domestic Product (GDP) OTHER WORK: –Review peer works –Contact other economic professionals 8/2/2015

28. Vendor Analysis How is vendor behavior affecting competition and thus prices? –Who owns whom? –Are there sole-source owners? –Founded on game theory from the business and economics realms Using this analytical work, BART can provide suggestions for modifying bidding rules to enhance competition as the construction environment changes over time.

29. Industry Analysis BART provides situational awareness –BART understands how events external to the jobsite affect prices.

30. OhDOT Actual Composite, BART Modeled Index and the Combined Actual and Predicted Inflation Rates 8/2/2015