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Linear regression Number of obs = 131 F(11, 119) II 143. 13 Prob > F II D. 0606 R-squared 5. 8941 ROOL MSE = .

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Linear regression Number of obs = 131 F(11, 119) II 143. 13 Prob > F II D. 0606 R-squared 5. 8941 ROOL MSE = . 35402 Robust Intpos_pc Coof. Std. Err. [95% Conf. Interval] Inypepenn -. 9599562 . 4732335 -2. 03 9 . 045 -1. 897095 -. 9229065 Inypcpenn2 . 0954567 . 0256192 3. 73 9447282 . 1461852 In_gasprice -. 2392021 .0566569 -4. 22 3 . 609 -. 3513885 -. 1270157 temp_coldest -. 01857 . 005238 -3.55 3. 601 -. $289417 -. 0981983 temp_warrest 0166677 - 016809 1. 04 3. 300 -. $150318 . 0483671 In_annualprecip . 306395 . 6539954 0. 12 0.906 -. 1005213 . 1133114 ffrents . 0026254 . 5028546 0.99 0 . 325 -. 6028319 .0084728 Inpop -. 0469675 . 038335 -1. 23 0. 223 -. 1228657 . 6289456 Inland . 0546541 . 0328958 1. 66 0. 099 -. 5194628 . 119791 Iincomegra_2 1032733 .2283648 3 . 45 0 . 652 -. 3489118 . 5554584 Iincomegro_3 -. 0828519 . 1007342 -0.82 9. 412 -.2823156 . 1166118 cons 8.303336 2. 40965 3. 45 0. 001 3.531989 13 . 97468 Log referrers to natural logarithm!We model energy use per capita of 131 countries in a given year as follows: Lntpes_pc = Bo + BLnypcpenn + B2Lnypcpenn2 + BLnGasprice + B4LnAnnualprecip + TempColdest + TempWarmest + Byffrents + BLnPop + BoLnLand + D_incomegroups + u The variables are defined as follows: Lntpes_pc = log of total primary energy consumption per capita (ktoe) Lnypcpenn =log of GDP per capita (USD) Lnypcpenn2 = square of log of GDP per capita (USD) Ln gasprice = log of pump price for gasoline (USD/liter) LnAnnualprecip- log of annual precipitation (mm) Temp_coldest = average temperature for the coldest month in a year (in C) Temp_warmest= average temperature for the warmest month in a year (in C) ffrents = Fossil Fuel Rents (% of GDP) LnPop = log of population (in millions) LnLand = log of land area (in km2) I Incomegroup = refers to income groups "1" , "2" and "3", low, mid and high income countries. *Log" always refers to natural logs or "In" here

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