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    Cocoa

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    Shazeb Lalu
    1) The document appears to contain regression output analyzing factors that influence demand. 2) Based on the regression statistics, price and year are found to be significant factors influencing demand, while per capita income is not a significant factor. 3) Specifically, for every 1% increase in price, demand is estimated to decrease by 0.22%, and for every additional year, demand is estimated to increase by 3.6%.

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    Cocoa

    Uploaded by

    Shazeb Lalu
    5 views6 pages
    1) The document appears to contain regression output analyzing factors that influence demand. 2) Based on the regression statistics, price and year are found to be significant factors influencing demand, while per capita income is not a significant factor. 3) Specifically, for every 1% increase in price, demand is estimated to decrease by 0.22%, and for every additional year, demand is estimated to increase by 3.6%.

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    1) The document appears to contain regression output analyzing factors that influence demand. 2) Based on the regression statistics, price and year are found to be significant factors influencing demand, while per capita income is not a significant factor. 3) Specifically, for every 1% increase in price, demand is estimated to decrease by 0.22%, and for every additional year, demand is estimated to increase by 3.6%.

    Copyright:

    © All Rights Reserved
    Download as XLSX, PDF, TXT or read online from Scribd
    Download as xlsx, pdf, or txt
    5 views6 pages

    Cocoa

    Uploaded by

    Shazeb Lalu
    1) The document appears to contain regression output analyzing factors that influence demand. 2) Based on the regression statistics, price and year are found to be significant factors influencing demand, while per capita income is not a significant factor. 3) Specifically, for every 1% increase in price, demand is estimated to decrease by 0.22%, and for every additional year, demand is estimated to increase by 3.6%.

    Copyright:

    © All Rights Reserved
    Download as XLSX, PDF, TXT or read online from Scribd
    Download as xlsx, pdf, or txt
    of 6

    Demand Price Pcinc Year L_Demand L_Price L_Pcinc

    646.00 1.40 13253 1960 6.4707995 0.3354885 9.49197922


    714.00 1.11 13438 1961 6.57088296 0.10854371 9.50584179
    710.00 1.05 13898 1962 6.56526497 0.04607408 9.53950022
    734.00 1.29 14235 1963 6.59850903 0.25193242 9.563459
    753.00 1.16 14836 1964 6.62406523 0.14989371 9.60481194
    787.00 0.83 15539 1965 6.66822825 -0.184964 9.65110827
    825.00 1.14 16230 1966 6.71538339 0.12735653 9.69461666
    840.00 1.30 16718 1967 6.73340189 0.26312417 9.72424126
    856.00 1.58 17435 1968 6.75227038 0.4585667 9.76623496
    793.00 1.87 17985 1969 6.67582322 0.625792 9.79729336
    813.00 1.32 18190 1970 6.70073111 0.27888856 9.80862727
    826.00 1.00 18425 1971 6.71659477 0.00163279 9.82146372
    929.00 1.10 19195 1972 6.83410874 0.09451808 9.86240511
    893.00 1.66 20149 1973 6.79458658 0.5094926 9.91090994
    802.00 1.89 20162 1974 6.68710861 0.63397375 9.91155492
    713.00 1.35 19915 1975 6.56948142 0.30368686 9.8992285
    831.00 2.20 20603 1976 6.72262979 0.78731284 9.93319198
    750.00 3.77 21237 1977 6.62007321 1.32607312 9.96350022
    772.00 2.91 22092 1978 6.64898455 1.06815331 10.0029708
    773.00 2.52 22643 1979 6.65027905 0.92587501 10.027606
    797.00 1.81 23006 1980 6.68085468 0.59573338 10.0435103
    855.00 1.45 23387 1981 6.75110147 0.36989007 10.0599356
    902.00 1.25 23382 1982 6.80461452 0.21933843 10.0597218
    961.00 1.56 23779 1983 6.86797441 0.44620542 10.0765581
    1052.00 1.81 25244 1984 6.95844839 0.59090272 10.1363438
    1136.00 1.72 26033 1985 7.0352686 0.54049442 10.1671202
    1165.00 1.37 26634 1986 7.06047637 0.31504516 10.1899439
    1191.52 1.20 27253 1987 7.08298369 0.1864111 10.2129189
    1215.66 0.90 28140 1988 7.10304362 -0.1063952 10.2449473
    1320.95 0.71 28970 1989 7.18610386 -0.3447731 10.2740161
    1485.74 0.70 29345 1990 7.30366693 -0.3617837 10.2868775
    1576.71 0.66 28978 1991 7.36309439 -0.4107392 10.2742922
    1610.27 0.60 29662 1992 7.38415983 -0.5125365 10.297622
    1581.45 0.59 29667 1993 7.36610042 -0.5307994 10.2977906
    1442.21 0.76 30165 1994 7.27393073 -0.2772964 10.3144376
    1402.12 0.71 30761 1995 7.24574294 -0.3448374 10.3340029
    1621.80 0.73 31630 1996 7.39129313 -0.3095734 10.3618613
    1586.81 0.86 32605 1997 7.36948297 -0.1550847 10.3922209
    1727.34 0.93 34207 1998 7.45433902 -0.0754501 10.4401856
    1853.76 0.64 35027 1999 7.52497217 -0.4457674 10.4638745
    1967.61 0.52 36582 2000 7.58457406 -0.6587399 10.5073116
    1963.73 0.63 36600 2001 7.58260221 -0.4551082 10.5078035
    1747.02 1.07 36279 2002 7.4656696 0.06557125 10.4989943
    1918.42 1.00 36337 2003 7.5592555 -0.0004101 10.5005918
    2143.77 0.83 37152 2004 7.67032109 -0.1880879 10.5227729
    2283.04 0.80 37641 2005 7.73326214 -0.2266978 10.5358492
    2318.37 0.80 38672 2006 7.74861903 -0.2173463 10.5628711
    2218.56 0.93 39562 2007 7.70461488 -0.0726848 10.5856243
    2180.22 1.14 39791 2008 7.68718188 0.13026879 10.591396

    Prediction Actual demand


    7.66519690087 2132.8126932908

    Margin of error
    0.17196355927
    Actual
    Upper limit 7.8371604601467 2533.0021
    Lower limit 7.4932333416026 1795.8493
    Year SUMMARY OUTPUT
    1960
    1961 Regression Statistics
    1962 Multiple R 0.9784310526
    1963 R Square 0.9573273248 It is a very good fit
    1964 Adjusted R 0.9544824798
    1965 Standard Er 0.085379708
    1966 Observatio 49
    1967
    1968 ANOVA
    1969 df SS MS F Significance F
    1970 Regression 3 7.359230894 2.453076965 336.512998 8.035E-31
    1971 Residual 45 0.328036254 0.007289695
    1972 Total 48 7.687267148
    1973
    1974 Coefficients Standard Error t Stat P-value Lower 95%
    1975 Intercept -58.86547723 12.76640846 -4.610966147 3.31845E-05 -84.57834
    1976 L_Price -0.222002369 0.033721564 -6.583394798 4.2368E-08 -0.289921
    1977 L_Pcinc -0.571970582 0.353406818 -1.618448068 0.112554826 -1.283768
    1978 Year 0.0361486635 0.008217057 4.39922248 6.59016E-05 0.0195987
    1979
    1980 Interpretation:
    1981 1) Price is a significant co-efficient. For every 1% increase in price, the demand goes down by 0.22
    1982 2) This is not a significant variable. The demand is inelastic to per capita income changes.
    1983 3) For every 1 unit increase in Year (for each additional year) the actual demand increases by 100*
    1984
    1985 Regression without any log transformations
    1986
    1987 SUMMARY OUTPUT
    1988
    1989 Regression Statistics
    1990 Multiple R 0.975594374
    1991 R Square 0.9517843825 Taking natural logarithm is not required for this model since already R2
    1992 Adjusted R 0.948570008
    1993 Standard Er117.22238573
    1994 Observatio 49
    1995
    1996 ANOVA
    1997 df SS MS F Significance F
    1998 Regression 3 12206312 4068770.668 296.1025177 1.251E-29
    1999 Residual 45 618348.9472 13741.08772
    2000 Total 48 12824661
    2001
    2002 Coefficients Standard Error t Stat P-value Lower 95%
    2003 Intercept 100843.67991 26576.36138 3.794487833 0.000439288 47316.14
    2004 Price -133.4085489 30.34967381 -4.395716069 6.66491E-05 -194.5359
    2005 Pcinc 0.1491448619 0.024655606 6.049125808 2.63964E-07 0.0994859
    2006 Year -52.05441827 13.71797219 -3.794614653 0.000439118 -79.68383
    2007
    2008
    Significance F

    Upper 95%Lower 95.0%Upper 95.0%


    -33.15261 -84.57834 -33.15261
    -0.154084 -0.289921 -0.154084
    0.1398273 -1.283768 0.1398273
    0.0526987 0.0195987 0.0526987

    he demand goes down by 0.22% all other variables remaining at same level
    apita income changes.
    tual demand increases by 100*0.036 % = 3.6% all other variables remaining at same level

    or this model since already R2 is good enough

    Significance F

    Upper 95%Lower 95.0%


    Upper 95.0%
    154371.22 47316.14 154371.22
    -72.28117 -194.5359 -72.28117
    0.1988038 0.0994859 0.1988038
    -24.425 -79.68383 -24.425

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