Climate change is a global challenge, and many countries have committed to reduce carbon emissions significantly before 2050. To understand the determinants of carbon dioxide emissions, Mr. Tan collected data on CO2 emissions (million tons), GDP (billion US$), population (million), energy use per capita (kg of oil equivalent), and share of electricity production from oil, gas and coal sources, in 2015 from 34 countries from World Development Indicators, and performed the regression analysis. The data can be found in the image uploaded.

(a) Describe the relationship between the CO2 emissions and the four (4) independent variables by writing down the linear equation. Interpret the coefficients to show how each of the independent variables impact CO2 emissions. You are required to show the regression output from Excel.

(b) Mr. Tan wants to estimate the CO2 emissions in country S in 2020. He found GDP is 340 billion USD, population is 5.686 million, per capita energy use is 7,800 kg of oil equivalent, and electricity production from oil, gas and coal sources accounts for 95%. What is your estimate of CO2 emissions in country S?

(c) Execute appropriate hypothesis tests to advise Mr. Tan which variable is significant at the 10% significance level. You are required to write down your steps carefully.

(d) Discuss three (3) statistical concerns in the estimation of CO2 emissions in country S in 2020 in part (b).

Show all working. including excel works clearly.

A B C D E F CO2 emissions (mt) GDP (current US$, billion) Population, total million Energy use (kg of oil equivalent per capita) Electricity production from oil, gas and coal sources (% of total) N Australia 375.97 1351.69 23.82 5483.8 86.36 3 Austria 63.15 381.82 8.64 3800.30 22.22 Belgium 95.20 462.15 11.27 4687.79 39.21 5 Canada 558.80 1556.51 35.70 7631.34 21.07 Chile 31.97 243.92 17.97 2005.55 56.40 7 Czech Republic 100.98 188.03 10.55 3860.00 55.92 8 Denmark 33.60 302.67 5.68 2816.61 31.90 9 Estonia 15.37 22.88 1.32 4173.33 7.15 10 Finland 42.82 234.44 5.48 5924.70 16.19 11 France 310.52 2438.21 56.55 3692.02 6.06 12 Germany 742.31 3356.24 31.69 3817.5 55.06 13 Greece 58.01 195.32 10.82 2182.07 71.13 14 Hungary 43.38 125.07 9.84 2432.75 36.56 15 Iceland 2.06 17.52 0.33 17478.89 0.02 16 Ireland 36.9 291.46 4.70 2819.88 62.81 17 Israel 56.14 300.12 8.38 2777.88 97.67 18 Italy 337.86 1835.90 50.73 2481.75 50.25 19 Japan 1181.50 4444.93 127.14 3428.56 80.26 20 Korea, Rep 506.51 1465.77 51.01 5413.35 57.72 21 Luxembourg 9.13 57.74 0.57 6548.41 62.66 22 Mexico 472.59 1171.87 121.86 1537.26 80.88 23 Netherlands 158.11 765.26 16.94 4233.04 82.23 24 New Zealand 32.19 178.06 4.61 4431.51 19.79 25 Norway 18.64 385.80 5.19 5817.64 1.93 26 Poland 289.05 477.81 37.99 2490.21 86.08 27 Portugal 49.85 199.31 10.36 2131.68 51.87 28 Slovak Republic 30.75 88.47 5.42 3003.66 19.98 29 Slovenia 13.17 43.09 2.06 3174.87 32.44 30 Spain 256.28 1195.12 16.44 2571.34 44.07 31 Sweden 39.20 505.10 9.80 5102.79 1.09 32 Switzerland 39.0 702.15 8.28 2960.07 1.07 33 Turkey 351.59 864.32 78.53 1651.36 67.85 34 United Kingdom 400.37 2932.78 5.12 2764.52 53.18 35 United States 4982.79 18238.30 320.74 6804.00 67.08 36