Price Index AnalysisPrice index is a normalized average of prices for a given class of goods or services in a given region, during a given interval of time. It is a statistic designed to help to compare how these prices, taken as whole, differ between times of periods of geographical locations. The indexes are used to measure the economy’s price level. This was used to help the Company with its business plans and pricing. This will help determine the future market price of the productsproduced by the company. Historical Retail Price Index in Metro Manila The following data were obtained from the records on National Statistic Office of Selected Philippine Economic Indicators of 2010 from the National Statistics Office (NSO) Library. The data obtained represents the retail price index of Chemicals (Polyamides are categorized in this group of products) from 2005 to 2009. Table: Historical Retail Price Index in Metro Manila Year 2005 2006 2007 2008 2009 Price index 184 218.6 221 264.5 147.3 Figure: Historical Retail Price Index in Metro Manila Records show that the trend of the price index is not continually increasing. The year with the highest price index is 2008 and the lowest value is on the year 2009. A significant increase was observed from the year 2004 to 2008 as visible in the figure and an abrupt reduction in price index in the year 2009 due to inflation. 1 176. it represents the wholesale price index of Chemicals from 2005 to 2009. Table: Historical Wholesale Price Index in Metro Manila Year 2005 2006 2007 2008 2009 Price index 141. RETAIL PRICE INDEX PROJECTION .1 179.4 162.6 152.2 Figure: Historical Wholesale Price Index in Metro Manila The bar graph implies that the trend of the price index is continually increasing. Moreover. The records were gathered from the National Statistics Office (NSO) Library. This trend is assumeduntil upon the establishment and the production of the plant.Historical Wholesale Price Index in Metro Manila The following data were obtained from the records on National Statistic Office of Selected Philippine Economic Indicators. 5602 143.925 -628. (4) Statistical geometric curve and (5) Statistical straight line.125 128. The best projection of price index was then used to compute for the price of the product for the year 2017.095 -1190.559 10.093 -892.5337 178.4631 138. The best projection was chosen by comparing the standard deviations and zscore.6176 157.83 196.075 73.The Retail Price Index of Polyamides for the years 2010-2017 was projected using five different methods: (1) Arithmetic geometric curve.9 23.04974 Statistical Straight Line 198. (3) Statistical parabolic curve.310737 138. (2) Arithmetic straight line.33 179. Year Arithmetic Geometric Curve 2010 2011 2012 2013 2014 2015 2016 2017 Standard Deviation Table: Summary of Projections of Retail Price Index 145.95 119.2614 183.5788 -45. COMBINED RETAIL PRICE INDEX PROJECTION The table and figure presented below illustrates the summary of all the values computed for the projection of the price index of the product for the five methods.8041 137.33 190.8409 142.08 182.6 101.4315 170.58 187.425 92.7807 161.83 185.301042 .58 6.6 531.1646 135.59 -398.9436 4.9247 174.142 140.0888 -204.122 Arithmetic Straight Statistical Parabolic Statistical Geometric Curve 188.775 110.08 193.68975 79.25 83.0511 165.5445 133.93 -1524. Arithmetic Geometric Curve Method Year 2010 2011 2012 2013 2014 2015 2016 2017 Price Index 145.Figure: Graphical Representation of the Retail Price Index The table summarizes the projection produced by the four methods.80 41 137. From the data the proponents inferred that the highest retail price index projected is the Statistical Straight Line Method while the lowest projection is the Statistical Parabolic Curve Method which also has the highest Standard Deviation.56 02 143. The Arithmetic Geometric Curve Method has the Lowest Standard Deviation compared to other projections which a gives a decent price index.94 36 Table: Projection Values of Arithmetic Geometric Curve Figure: Projected Values for Arithmetic Geometric Curve Method .14 2 140.54 45 133.84 09 142. I.16 46 135.46 31 138. Arithmetic Straight Line Method Year Arithmetic Straight Line 2010 2011 2012 2013 2014 2015 2016 2017 138.6 101.775 110. III. Statistical Parabolic Curve Method Year Statistical .9 for the retail price index at 2017.075 73.95 119.9346 for the 2017. The projected value of the retail price index in this method is 133.9 Table: Projected Values for Arithmetic Straight Line Method Figure: Projection Values of Arithmetic Straight Line Method The projected value for arithmetic straight line method is 73. Since the values of the retail price index are declining.425 92. The projection of this method is the one will be used as the price index of retail for 2017.The projected values of price index for price index using the Arithmetic Geometric Curve method are presented. it has also the lowest variance. Generally. the projected values are expected to be like this.125 128.25 83. II. Its projected values are declining like the previous method. 2614 183.0888 -204.6 Table: Projected Values of Statistical Parabolic Curve Method Figure: Projected Values of Statistical Parabolic Curve The projected value for the retail price index for 2017 the Statistical Parabolic Curve Method is -1524.093 -892.6176 157.0511 165.59 -398.7807 161.559 Table: Projection Values of the Retail Price Index for Statistical Geometric Curve . IV.9247 174.4315 170.095 -1190. Statistical Geometric Curve Method Year Statistical Geometric Curve 2010 2011 2012 2013 2014 2015 2016 2017 188.925 -628.6 which is not applicable for the purpose of the price index due to that the values are far too large for a price index for the proposed price.5337 178.5788 -45.Parabolic Curve 2010 2011 2012 2013 2014 2015 2016 2017 79.93 -1524. 08 182. it is the second to the highest projection values but third only in the lowest standard deviation.83 196.33 190. Statistical Straight Line Method Year Statistical Straight Line 2010 2011 2012 2013 2014 2015 2016 2017 198.599.08 193.58 187.83 185. It is also the second to the most minimal in variance. Both are decreasing upon .58 Table: Projected Values of Price Index of Statistical Straight Line Method Figure: Projected Value of Statistical Straight Line Method . V.33 179. Comparison of Projected Retail Price I. The Statistical Straight Line Method projected the highest Retail Price index for 2017.Figure: Projected Values of Statistical Geometric Curve The projected value of Statistical Geometric Curve Method of retail price index for 2017 is 157. Arithmetic Geometric Curve and Arithmetic Straight Line Fig: Comparison of Arithmetic Geometric and Arithmetic Straight Line The bar graph compares the projected retail price index for 2017 of Arithmetic Geometric with Arithmetic Straight line. The standard deviation of Statistical Parabolic Curve is also greater than Arithmetic Geometric Curve. Since the standard deviation is close to each other and the retail price index of Statistical Straight Line has a greater value than Arithmetic Geometric Curve Method.reaching the 2017. But the method of Arithmetic Straight Line has greater decrease than the arithmetic geometric. IV. The Statistical Parabolic Curve method is like the Arithmetic Geometric Curve Method but this method has greater decrease than Arithmetic Geometric Curve Method that it gave a negative retail price index. The price indexes for the both projection are decreasing until 2017. III. The standard variation of Arithmetic Straight is larger than Arithmetic Geometric. The proponents still prefers the Arithmetic Geometric Curve Method. Arithmetic Geometric Curve projection is more preferred than the Statistical Geometric Curve projection. II. Arithmetic Geometric Parabolic Curve Curve and Statistical Fig: Comparison of Arithmetic Geometric Curve with Statistical Parabolic Curve The bar graph shown above compares the projection of Arithmetic Geometric Curve and Statistical Parabolic Curve. The standard deviation of the two projections is also most the same. The proponents still prefers the Arithmetic Geometric Curve Method since it would be more beneficial to the company caused it would give a higher retail price. . Arithmetic Geometric Geometric Curve Curve and Statistical Fig: Comparison of Geometric Curve with Statistical Geometric Curve The bar graph shown above is compares the Arithmetic Geometric Curve and Statistical Geometric Curve. Arithmetic Geometric Curve and Statistical Straight Line Fig: Comparison of Arithmetic Geometric Curve and Statistical Straight Line The bar graph above compares the Arithmetic Geometric Curve Method and Statistical Straight Line Method. Like the other methods the trend of the retail price indexes are decreasing. Also the Arithmetic Geometric Curve has the lower Standard Deviation than Statistical Geometric. These prices are acquired from the actual producers which are the following: Company Names Manila Bay Spinning Mills. For 2017 Retail Price at 2017= Proposed Price at Present( Price Index for 2017Present Price Index) Retail Price at 2017=260 133.00 Table: Manufacturer’s Price Fig: Manufactures Price The prices they use are the one used to calculate the future value of the company’s product. Inc. Crown Knitting Corporation Altamar Philippine Industry Actual Price 280. While the Retail Price Index were taken from the projection made by the proponents with respect to the National Statistic Office of Selected Philippine Economic Indicators of 2010 from the National Statistics Office (NSO) Library.00 250.00/kg WHOLESALE PRICE INDEX PROJECTION .9436143. Inc.8409=242. it would propose a lower price of the product. Since the company is new to the market.00 270.Computation of the Retail Price of Nylon at 2017 The Actual Price of nylon according to the producers is P250-300/kg. Philippine Synthetic Products. The proposed value of the company for retail is P260/kg.00 300.1101/kg The proposed retail price of the company is P245. 86 177. Arithmetic geometric curve.29 261.721 264.9114 233.7187 214.3049 299.7832 219. COMBINED WHOLESALE PRICE INDEX PROJECTION The table and figure presented below illustrates the summary of all the values computed for the projection of the price index of the product for the five methods.46 214.62 231.4388 206.7409 213.73 221.9 192.4857 34.27941 Statistical Geometric Curve 194.38 184.18 22.1263 201.41656 Statistical Parabolic Curve 206.4 251.6649 214.1642 10.34 169.01765 Arithmetic Straight Line 162. Arithmetic straight line.2465 208.5117 281. Statistical parabolic curve. The best projection of price index will then be used to compute for the price of the product for the year 2017. 4.4005 210.2485 212.66084 . The best projection will be chosen later on by comparing the standard deviation.2 190. 3.The Wholesale Price Index of Polyamides for the years 2010-2017 was projected using five different methods: 1.873 248.0672 240.51 241.601 271.42 199.04974 Statistical Straight Line 191.018 227.912 255.95 201.84 211. Statistical straight line.98 19.1856 35.94 207. Statistical geometric curve and 5.6589 203.4957 214. 2. Year Arithmetic Geometric Curve 2010 2011 2012 2013 2014 2015 2016 2017 Standard Deviation Table: Summary of Projections of Wholesale Price Index 179. 601 271. I. Arithmetic Geometric Curve Method Arithme tic Geomet ric Curve 179. The wholesale retail price index increases as the year progresses.912 255. .2 190.718 7 214.126 3 201. From the data the proponents can interfere that the highest wholesale price index projected is the Wholesale Price is the Statistical Geometric Curve which also has the lowest standard deviation.067 2 240.185 6 Year 2010 2011 2012 2013 2014 2015 2016 2017 Table: Projection Values of Arithmetic Geometric Curve Figure: Projected Values for Arithmetic Geometric Curve Method The figure above illustrates the projection made by the Arithmetic Geometric Curve Method.018 227.Figure: Graphical Representation of the Wholesale Price Index The table summarizes the projection produced by the five methods. 4005 . Statistical Parabolic Curve Method Year Statistical Parabolic Curve 2010 206.34 169.46 214.This method produces the second to the highest price index but has the largest standard deviation. Like the first projection the wholesale price index still increases as the year approaches 2017.38 184.86 177. It is the second to the lowest standard deviation compared with the other projections.98 Table: Projected Values for Arithmetic Straight Method Figure: Projection Values of Arithmetic Straight Line Method The figure above presents the projection produced by the arithmetic straight line method. II. Arithmetic Straight Line Method Year Arithmetic Straight Line 2010 2011 2012 2013 2014 2015 2016 2017 162.94 207. III.9 192.42 199. IV.721 264.6589 203.2465 208.2011 2012 2013 2014 2015 2016 2017 210. Statistical Geometric Curve Method Year Statistical Geometric Curve 2010 2011 2012 2013 2014 2015 2016 2017 194.4957 214.6649 214.4857.9114 233.7832 219.4857 Table: Projected Values of Statistical Parabolic Curve Method Figure: Projected Values of Statistical Parabolic Curve The projected value of wholesale price index for 2017 of Statistical Parabolic Curve Method is 203.873 248.2485 212.1642 Table: Projection Values of the Retail Price Index for Statistical Geometric Curve .7409 213. This method produces the second to the highest standard deviation with only a little difference between the highest standard deviation.5117 281.4388 206.3049 299. 4 251. Both of the projections are increasing as it reaches 2017. The Arithmetic Geometric Curve has a higher projection than Arithmetic Straight Line Method but also has a higher . V.18.29 261. Arithmetic Geometric Curve and Arithmetic Straight Line Fig: Comparison of Arithmetic Geometric and Arithmetic Straight Line The figure above the compares the projected wholesale price index by Arithmetic Geometric Curve Method and Arithmetic Straight Line Method.73 221. This method produces the highest wholesale price index which also has the lowest standard deviation.18 Table: Projected Values of Price Index of Statistical Straight Line Method Figure: Projected Value of Statistical Straight Line Method .84 211.51 241.95 201. The wholesale price index is gradually increasing like the first two methods. The wholesale price index produced by Statistical is 261. Comparison of Projected Retail Price I. The figure above represents the projected values of the Statistical Straight Line Method.62 231.Figure: Projected Values of Statistical Geometric Curve This bar graph above represents the projection made by Statistical Geometric Curve Method. Statistical Straight Line Method Year Statistical Straight Line 2010 2011 2012 2013 2014 2015 2016 2017 191. Almost of all the projections is increasing including this method. III. The Statistical Geometric Curve Method produces a higher price index than Statistical Straight Line Method. Statistical Geometric Curve and Statistical Straight Line Fig: Comparison of Statistical Geometric Curve and Statistical Straight Line The figure above compares the projection produced by Statistical Geometric Curve and Statistical Straight Line. The Arithmetic Straight Line Method produces a higher wholesale retail price than Statistical Parabolic Curve Method. The proponents still prefers the Statistical Geometric Curve Method because it will be more profitable for the company to use this projection. II. The proponents prefer the Statistical Geometric Curve than Arithmetic Straight Line Method because of it has a higher projected value of wholesale price index and has the lower standard deviation. While the standard deviation of the Statistical Geometric Line has a lower value than the standard deviation Statistical Straight Curve. The Statistical Geometric Curve Method also has the lowest value of standard deviation compared all the other projections. Arithmetic Straight Line and Statistical Geometric Curve Fig: Comparison of Arithmetic Straight Line with Statistical Geometric Curve The bar graph represents the comparison of Arithmetic Straight Line Method with Statistical Geometric Curve Method. The Arithmetic Straight Line Method also has lower value of standard deviation and is still preferred by the proponents against the Statistical Parabolic Curve Method. IV. The Statistical Geometric Curve gives a higher wholesale price index compared with Arithmetic Straight Line Method. The proponents prefer the Arithmetic Straight Line Projection than Arithmetic Geometric Curve Method.Standard Deviation. . Arithmetic Straight Line and Statistical Parabolic Curve Fig: Comparison of Arithmetic Straight Line with Statistical Parabolic Curve The figure above represents the comparison of Arithmetic Straight Line Method with Statistical Parabolic Curve Method. Both of the projections are increasing. 1642206. Inc.00 270. Company Names Actual Price Manila Bay Spinning Mills. For 2017 Wholesale at 2017= Proposed Price at Present( Price Index for 2017Present Price Index) Wholesale Price at 2017=240 299.7832=347.2207/kg .00 250.Computation of the Wholesale Price of Nylon at 2017 The Proposed Price of nylon upon the establishment of the plant is P240270/kg. While the Retail Price Index were taken from the projection made by the proponents with respect to the National Statistic Office of Selected Philippine Economic Indicators of 2010 from the National Statistics Office (NSO) Library. Crown Knitting Corporation Altamar Philippine Industry 260. Philippine Synthetic Products.00 240. The computed price is based on the projected price index as shown above.00 Table: Manufactures Price Figure: Manufactures Price Since the company is new to the market. it will propose an introductory price of 240/kg on the first year which is 2017. These are the following price of the actual producing and will be the competitors of the company upon the erection of the production plant. Inc. The proposed wholesale price is P 350.00/kg of product. .