Exploring Gold as Alternative Currency for Future Cost ......Next, gold equivalency (in ounces of...

PM World Journal Exploring Gold as Alternative Currency for Cost Vol. I, Issue IV – November 2012 Estimation in Telecommunications Projects www.pmworldjournal.net Featured Paper Hari Kumar Sellappan

© 2012 Hari Kumar Sellappan www.pmworldlibrary.net of 23

Exploring Gold as Alternative Currency for Future Cost Estimation in Telecommunication Projects

By Hari Kumar Sellappan

Abstract The volatility of US dollars and its decline in purchasing power have led to major cost overruns during project lifecycle, hence raising doubts to continue using US dollars as basis for cost estimation. Current industry practice is to build in risk contingency as a fix percentage of total project budget or factor inflation for project cost estimation. Both methods have shortcomings and does not account for the changing worth and Purchasing Power fluctuations of the contract base currency, thus the actual cost during project execution is significantly different than assumptions used during project cost estimation. This creates a need for an alternative currency with stable and reliable value to be used as cost estimation baseline. The objective of this paper is to explore gold as a possible alternative currency and test it against several applications relevant to telecommunication projects. First, the reliability of gold in terms of purchasing power will be established by comparing to US dollar. Next, gold equivalency (in ounces of gold) will be applied for selected materials and equipment based on historical data to analyze the proposed alternative cost forecasting model. Finally, the predictive pricing model output for next three years (until 2015) will be presented based on gold equivalency and gold price forecast. The findings show that the proposed method gives a better representation of future material prices compared to relying solely on US Dollars as cost estimation yardstick and recommends a change in cost estimation paradigm for projects with medium to long time horizons. Keywords: Gold Price, Cost Estimation, US Dollars, Inflation, Purchasing Power, Telecommunication, Ready Mix Concrete, IBS Antenna, Base Transceiver Station (BTS), Gold Equivalency, Price Forecast, Project Cost Engineering, fiat currency, paper currency, Consumer Price Index (CPI), Big Mac Index (BMI).

1. Introduction Historically, US dollars have been accepted and used as the international reserve currency in most countries [1]. It has been deemed stable, easily tradable and widely accepted around the world. As such, US dollar is used as contract base currency and also as basis for project cost estimation. However, in the last decade, global market volatility and quantitative easing actions by US government has led to large fluctuations to the value of US dollars, measured relative to other currencies and in terms of purchasing power. As a result, using US Dollars as basis for forecasting prices and cost estimation for future projects is highly risky and requires further evaluation.



1.1. US Dollar Index US Dollar Index is a measure of United States dollar worth relative to a basket of six major foreign currencies [2], which gives a real picture of US Dollar value change. Figure 1 shows the trend of US Dollar Index from 1973 to 2011. Over the last 10 years, the value of US dollar has declined 33% against other major currencies. Thus, cost estimation done for projects outside the United States are significantly affected by this negative trend, especially projects that have relatively high local material and labor content.

Figure 1: US Dollar Index Chart: 1973-2011 (source: US Federal Reserve)

1.2. Inflation “Inflation rate is defined as annualized percentage growth of some broad index of money prices.” [3] Generally, all costs and prices are subjected to inflation or deflation due to local and global conditions. The GAO Cost Estimating and Assessment Guide recommends the recognition of inflation in project cost estimation. However, there are several challenges in applying inflation rates to produce reliable and accurate cost estimates. Firstly, the officially published inflation rate, Consumer Price Index (CPI) does not reflect the real situation and real values are claimed to be intentionally suppressed [4]. Secondly, the CPI refers to a predetermined basket of goods and services; hence may not be relevant to specialized materials and labor to be used in cost estimation process. Thirdly, fluctuation of inflation rate is statistically out of control following the statistical process control (SPC) method. Figure 2 shows the monthly inflation rate from 2006 until 2011 and there is a data point (November 2008; -1.91%) outside the lower control limit (LCL). Based on the three factors mentioned, inflation rate



cannot be accurately determined for project cost estimation and definitely cannot offset the US dollar value decline which results in project cost overruns.

Figure 2: Monthly Inflation Rate 2006 – 2011 (source: www.Inflationdata.com)

1.3. Problem Statement The decline in US dollar value has led to cost overruns in projects, especially when cost estimation was done for medium and long time horizons. Drop in US Dollars value is not only against commodities and material prices, but is also seen against other major currencies. Thus it has significant impact on international projects which uses US Dollars as basis of cost estimation and as contract base value. Using inflation for future cost estimation rate has many challenges and does not accurately offset the drop in US Dollar value. This calls for an alternative currency to be developed as a basis for project cost estimation, especially in forecasting future cost. The objective of this paper is to explore gold as a possible alternative currency and test it against several applications relevant to telecommunication projects. First, the reliability of gold in terms of purchasing power will be established by comparing to US dollar. Next, gold equivalency (in ounces of gold) model will be applied to three selected materials/equipment based on historical data to analyze the proposed alternative cost forecasting model. The typical project cost breakdown of telecommunication cell sites is shown in Figure 3. Based on cost significance and available access to research materials, especially historical price data; ready mix concrete (part of Civil Works), Base Station and IBS Antenna were selected to explore future price estimation.



Finally, the paper will attempt to model historical gold price to forecast its price for next three years (until 2015) and combine with gold equivalency model to project the related prices of the 3 selected materials for next three years.

Figure 3: Cell Site Cost Breakdown (Source: Powerwave Technologies Inc) [5]

2. Purchasing Power of Gold and US Dollar In this chapter, the purchase power (PP) of Gold will be compared to US Dollars to establish that gold is more reliable and sustainable in terms of worth over a long period of time. Using data from 1990 – 2011 (22 years), the PP of Gold and US Dollars were investigated based on 3 established methods.

2.1 Consumer Price Index (CPI)

CPI tracks the change in cost paid by household for a representative basket of goods and services. “CPI was designed to measure the purchasing power of money by answering questions such as how much income is required today to purchase the same basket of goods and services that was purchased in the base period” [6]. Thus, comparing PP of Gold and US Dollars against CPI will give a reliable comparison against implied inflation. Figure 4 shows the PP trend of Gold has increased 139% while PP of US Dollars has dropped 42% over 22 years when benchmarked against CPI. This show Gold has retained its worth as compared to US Dollars.



Figure 4: PP US Dollars and Gold against CPI (source: author)

2.2 Big Mac Index (BMI)

Published annually by The Economist, “BMI gives a simple but reliable measure of Purchase Power Parity (PPP) across multiple countries using the price of a Big Mac hamburger” [7]. In this evaluation, the BMI of United States was used to compare the PP of US Dollar and 1 ounce (oz) of Gold, i.e. how many Big Macs could be purchased annually over 22 years?

Figure 5: PP US Dollars and Gold using BMI (source: author)



Trend shown in Figure 5 clearly shows an increase of 122% in PP of gold compared to decline of 46% in terms of PP of US Dollars. Again, the results show that gold has reliable and sustainable worth in terms of PP.

2.3 An ounce of gold

Finally the PP of US dollar was measured and trended based on gold price (as a benchmark commodity), i.e. how much gold (in oz) can the same amount of US Dollar purchase every year? This comparison reflects the comparative worth against each other. Figure 6 show that the PP of US Dollars in terms of gold oz has dropped 76% over 22 years.

Figure 6: US Dollars PP in terms of gold oz (source: author) US Dollars including other paper currencies have experienced major erosion of PP over years, caused by government manipulations of currency circulation and quantitative easing methods. The real worth of paper currencies continue to decline every year, thus any future project cost estimation done with basis of US Dollars is not reliable and high risk of cost overrun. In contrast, Gold has reliable worth and sustainable PP, which makes it superior compared to US Dollars for future project lifecycle cost estimation.



3. Application 1: Ready Mix Concrete One of the primary cost component within telecommunication Radio Access Network (RAN) projects is the civil works, where it accounts for 43% of cell site cost [5]. Concrete and related activities accounts for 20% of civil works cost, which then translates into almost 9% of total cell site cost. Hence, ready mix concrete was selected for gold equivalency analysis and to test the alternative cost forecasting model using gold. Firstly, historical price of ready-mix concrete from 1975 to 2011 (37 years) in the United States was obtained [8] and converted into gold equivalent in ounces (oz) of gold. The output, a time-series graph of 100 cubic yard of ready-mix concrete worth in both US Dollars and Gold (oz) is shown in Figure 7.

Figure 7: Ready-mix concrete price in US Dollars and Gold ounces (source: author) Applying linear regression trend shows that historical mean price in US Dollars was steadily increasing as a function of time, definitely contributed by currency related inflation. However, the mean price in terms of gold, observed from the chart was relatively stable for 37 years (historical mean range: 10 oz to 12 oz for 100 cubic yard). This shows the value of ready mix concrete in terms of gold was very stable over long period of time, which forms a good basis to estimate future cost using gold equivalency. Next, statistical calculation and control chart was applied as shown in Figure 8 below to determine historical mean and standard deviation (sigma). Data mean was 11.74 oz with standard deviation (sigma) of 3.68 oz. All data points are within +/- 3 sigma limits (UCL and LCL), which shows stability over 37 years. Thus, based on historical data



available, the projected price range (within 95% confidence level) for next 3 years will be between 19.1 oz (+2 sigma) to 4.38 oz (-2 sigma) of gold.

Statistical Calculation Ready Mix in Gold Value(oz) Sample size 37 Average / Mean 11.74 Stand Dev/Sigma 3.68 Variance 13.57 UCL = mean+3σ 22.79 LCL = mean-3σ 0.69

Figure 8: Control Chart for Price in Gold Equivalency (source: author)

4. Application 2: In-Building System (IBS) Antenna The trend of In-Building System (IBS) deployment is expected to increase significantly in Asia Pacific within next few years as reflected in Figure 9. This requires reliable prediction models for future cost projection and hence improve the Capex investment decision making process.



Figure 9: In-building System Deployment Overview (source: ABI Research) [9] At present within telecommunication industry, the main challenges faced for accurate and reliable future cost projection are rapid technological changes, short lifecycle of products, rapid value decline, lack of long terms historical prices and changing requirements for new products to support evolving market demand. An example of passive electronic device that makes up significant cost component of IBS projects is the IBS antenna. This chapter will analyze the value of IBS Antenna in gold equivalency and then predict the value for next 3 years (2015). The price of a wideband antenna model widely used in 2G and 3G IBS deployment was obtained in Malaysian Ringgit (MYR) for a period of 9 years (2004 – 2012), and converted into gold equivalent in ounces (oz). Figure 10 shows value for 100 units of IBS Antenna in both MYR and gold. Antenna value has declined significantly over 9 years period in both MYR and gold terms. In terms of MYR, the price has been relatively stable expect for 2 major cost reduction initiatives taken by the manufacturer, i.e. 20% price reduction by new model introduction in 2007 and a further 23% decline by outsourcing to OEM plant in China in 2011. However, in terms of gold, the value of antenna has progressively reduced, closely following an inverse exponential trend line and thus forming a basis for future value projection.



Figure 10: IBS Antenna (100 units) Value in MYR and Gold ounces (source: author) The regression analysis results are displayed in Table 1, where antenna value in gold was calculated as exponential regression model [Y = 7.985 e-0.239x ]. The coefficient of determination, R2 value was 0.989, indicating that the regression model closely fit the observed data, thus forming a good basis to model projected price in future.

Table 1: Results of regression analysis (source: author)



Figure 11: IBS Antenna (100 units) Value Forecast for 5 years (source: author) Next, the model was used for five year future projection (single value projection). Results obtained are shown in Figure 11. In 2015 (3 years ahead), the value of 100 units of IBS antenna is estimated at 0.45 oz of gold, declined 84% from 2004 base value. This has significant impact on cost estimation of future projects. In contrast to ready-mix concrete, passive electronics devices like antenna are decreasing in cost every year as technology matures and cost reduction measures are taken by manufacturers. The current model of antenna used for evaluation is highly likely to be replaced with completely new model after 2015 to support LTE technology and incorporate higher frequency bands. Thus forecasting beyond 2015 in such cases will lead to high risk of errors due to rapid technology changes and shorter product lifecycle in telecommunications.

5. Application 3: Base Transceiver Station (BTS) The cost of Base Transceiver Station (BTS) is estimated 34% of total cost of cell site Capex in a telecommunication operator [5]. Therefore, it is essential to explore the price trend of the BTS and attempt to forecast the value until 2015 to create a reliable projection of future telecommunication network project Capex. The price of a particular BTS vendor from 1990 until 2010 was obtained in US Dollars [10] and depicted in Figure 12. The lifecycle of BTS is relatively short, which is a



common characteristic of telecommunication electronic devices. Every three to four years, newer model of BTS is launched and the older model becomes obsolete. Hence the challenge was to have sufficient historical data to model the price. This analysis was done using available pricing data of a particular range of BTS models (same vendor) over 20 years which has seen 3 generations of BTS model.

Figure 12: BTS Price in US Dollars (source: author) After price was converted into gold equivalency, historical price trend was modeled with “best fit” curve by regression analysis. Then, extrapolation was used to project BTS value in gold oz for 2015. The output is described in Figure 13, where the “best fit” curve followed an exponential trend and mathematically model by [Y = 3257 e-0.82x]. The representation of the model against historical data is supported by the coefficient of determination, R2 value of 0.905, which means only 9.5% data falls outside the modeled trend line. The result of 3 year ahead (year 2015) projection of BTS price was 23.43 oz of gold.



Figure 13: Projected BTS Value in Gold Equivalency – log scale (source: author) From the historical price available, the value of the BTS has dropped 97% since 1990. Based on the project value for 2015, BTS value in terms of gold has declined 98%. Again, in contrast to ready-mix concrete, telecommunication equipments such as antenna and BTS are decreasing in value every year as technology matures, new models are introduced, competition intensifies and cost reduction measures are taken by manufacturers.

6. Forecasting Gold Price until 2015 In this chapter, the historical gold price will be analyzed using regression method and then forecasted for next 3 years (upto 2015) using range estimation. Data used was average monthly gold price over 34 years (from Dec 1978 until Dec 2011), obtained from World Gold Council (using London PM Fix price) [11]. The resulting 397 sample data, shown in Figure 14, was sufficient to build a reliable and accurate model for forecast estimation.



Figure 14: Historical Gold Price in US Dollars (source: World Gold Council) Historical mean was calculated as USD 484.59, while standard deviation (sigma) was 286.50. The price has increased exponentially in the last 5 years, and exceeded the +3 sigma level. Thus regression analysis was applied, to trend the historical data and create a mathematical model to forecast future prices. Results obtained using 6 different regression types were plotted on the actual historical data, and extrapolated for next 3 years as shown in Figure 15. The corresponding R2 value is listed in Table 2. The “best fit” criteria required R2 value approx near to or better than 0.95, which is fulfilled by fourth order polynomial (R2 = 0.948) and sixth order polynomial (R2 = 0.955). However, employing Principle of Parsimony, the fourth order polynomial model is selected for future price forecast (see Equation 1).

Figure 15: Gold Price Forecast using Regression Models (source: author)



Table 2: Coefficient of Determination (R2 value) for each regression model (source: author)

Equation 1: Mathematical Model of Gold Price Trending (source: author)

The model was tested using residual (error) analysis to explore the reliability of the predictive model. Figure 16 shows the residual plot after applying Equation 1 output to historical data. Results of residual analysis indicate that the regression model is reliable, supported by the following conditions [12]. Therefore, it will be used as basis for range estimate of future gold prices. Mean of residual data (error) is zero and the variance of residual data is relatively

constant - neither increasing or decreasing over long period (stationary condition) Residuals show no drift with time (consistency condition) Distribution of residual (error) values show 94% are within 2 sigma limit and 97%

within 3 sigma (shown in Figure 17).

Figure 16: Residual Plot (Error Analysis) of Gold Price Model (source: author)



Table 3: Residual Analysis of Gold Price Model (source: author)

Figure 17: Distribution Analysis of Residual (Error) Values (source: author) Finally, the range estimate of future gold price with 90% confidence until Dec-2015 is shown in Figure 18. Estimate was done using basis of residual error and its standard deviation. In conclusion, based on historical data and error analysis for the model developed, the gold price projected for Dec-2015 is within range of $3735 to $3085.



1000.00

1500.00

2000.00

2500.00

3000.00

3500.00

4000.00

4500.00

Output of Gold Price Forecast (Jan 2012 - Dec 2015)

Projected Price Actual Price Range Est_U Range Est_D

Actual data until Dec 2011

Projected Dec 2012

$2206 -$1816

Projected Dec2013

$2673-$2153

Projected Dec 2015

$3735-$3085

RANGE FORECAST

Figure 18: Output of Gold Price Forecast Jan 2012 - Dec 2016 (source: author)

7. Conclusion This paper has explored gold as an alternative currency for price estimation of selected materials/equipment within telecommunication industry. Ready mix concrete value is stable in terms of gold and is expected to continue the trend. Thus for cost estimation purpose, future price of ready mix concrete should related to projected future gold price, instead of purely relying on inflation rate. However, the value of electronic devices such as IBS Antenna and BTS are declining in terms of gold and currency over time. This is expected as cost of technology decreases over time as the production matures and efficiency measures are taken. The projection of future BTS and IBS Antenna value until 2015, shown in Figure 19 and Figure 20, leads to an interesting finding. Although their value in terms of gold equivalency drops significantly, their value in terms of currency does not follow similar trend. IBS Antenna price is projected to increase in 2012 before declining again. Remarkably, the price of BTS, which was expected to continue dropping, is now estimated to increase until 2015. This finding underlines that “declining cost of technology” is in fact reversed in terms of fiat currency due to over circulation of currency, inflation and other forms of government manipulation. Only real money with intrinsic value such as gold will stand the test of time, as it has for many centuries.



Figure 19: Estimated BTS Value until 2015 (source: author)

Figure 20: Estimated IBS Antenna Value (100 units) until 2015 (source: author) Forecasting the prices of telecommunication equipment will be essential for future project cost estimation and will directly impact CAPEX investment decisions and ROI calculations. To date, US Dollars have been used extensively as basis of cost estimation including forecasting of future prices and project costs. However, an alternative currency is urgently required for cost estimation of future telecommunication projects in view of the following factors:

1) Unpredictable volatility and declining purchasing power of US Dollars leads to project cost overruns during execution phase, especially for project with medium and long time horizons



2) US Dollar related inflation and CPI is broad spectrum for consumer products, and does not give reliable benchmark for telecommunication equipments and related materials

3) Paper currencies are prone to government manipulations due to lack of intrinsic value, thus becomes an unreliable yardstick for cost estimation

Quotation from Ron Paul [13] best depicts the current situation:

“Federal Reserve has ‘a responsibility to protect the value of the dollar’ but without a consensus on the ‘definition of a dollar,’ the dollar’s value cannot be sustained.” “Every single day it buys less the next day. To me it’s sort of like…a builder had a yardstick that changed its value every single day. I mean, just think of the kind of building we would have?”

“We have a debt-based system. The more debt we have, and the more debt the Federal Reserve buys, the more currency they can print, and they monetize this debt. And no wonder we’re in a debt crisis.”

If the yardstick of cost estimation (the US Dollars) keeps changing in its value, then the outcome of even the best cost estimation methodology will not yield optimal results and will impact project stakeholders. In conclusion, cost estimation paradigm has to change and adapt with current economic realities, especially for projects with medium and long time horizons. Real currencies with intrinsic value, such as Gold, should be adapted as feasible alternative to establish new yardstick for cost baseline.



References

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About the Author

Hari Kumar Sellappan Author

Hari Kumar Sellappan is a telco professional with over 12 years of experience in Telecommunication Engineering,

Project Management and Technical Operations. He is currently the Vice President for Network Projects and Implementation at SmartFren Telecom (Indonesia). Graduated from University College London (UCL), Hari Kumar holds a M.Sc. (Distinction) in Spacecraft Technology and Satellite Communications and a Bachelor’s degree in Engineering. His past engagement includes Maxis Communications (Malaysia) and Huawei Technologies (APAC Region). Hari Kumar is a Certified Cost Engineer (CCE), driven by passion to advance telco cost engineering and service delivery. He lives in Jakarta, Indonesia and can be reached at [email protected].

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