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Explore global economic growth data, trends, and cycles, examining stability, stationarity, and business cycle correlations across countries.
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Econ 314: Project 1 Answers and Questions
Examining the Growth Data Trends, Cycles, and Turning Points
Cycle Turning Points Peaks Troughs
Measuring Growth Rates Compounding and Growth Rate Formulas
Product growth formula Continuously compounded: Formula holds exactly.
Product growth formula Annually compounded: Formula holds approximately. Close when ab is small.
Trend growth vs. average growth • Trend rate is slope of best-fit line • What is average growth rate? From period 0 to 2:
Trend growth vs. average growth • Trend rate is slope of best-fit line • What is average growth rate? From period 0 to T:
Trend growth vs. average growth Actual Log GDP - Egypt Fitted values 18.5 18 lnGDPT – lnGDP0 17.5 17 T 16.5 1950 1960 1970 1980 1990 Year
Is Trend Growth Stable? Examining the Record
Is the trend stable? Single trend for Japan
Is the trend stable? Stability Test for Japan Source | SS df MS Number of obs = 51 -------------+------------------------------ F( 3, 47) = 5988.24 Model | 39.488173 3 13.1627243 Prob > F = 0.0000 Residual | .103310446 47 .002198095 R-squared = 0.9974 -------------+------------------------------ Adj R-squared = 0.9972 Total | 39.5914834 50 .791829668 Root MSE = .04688 ------------------------------------------------------------------------------ lgdp_jpn | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- year | .0908236 .0013825 65.69 0.000 .0880424 .0936049 d | 115.4399 3.557021 32.45 0.000 108.2841 122.5957 dyear | -.0585122 .0018037 -32.44 0.000 -.0621408 -.0548836 _cons | -171.915 2.711848 -63.39 0.000 -177.3706 -166.4595 ------------------------------------------------------------------------------
Stationarity and Trends Is Log-Linear Trend Appropriate?
“Definition” of stationarity • Stationary variable: • Same mean, variance, etc. at all times • Nonstationary variable: • Different level, variability, etc. over time • Includes trended or drifting variables • ln GDP is nonstationary for all countries
Kinds of nonstationary series • Trend stationary • Deviations from a fixed trend line are stationary • Shocks from trend line are temporary • Difference stationary • Difference (yt - yt -1) is stationary, but may have nonzero mean (drift) • Shocks are permanent
Difference stationary series • Random walk: • Random walk with drift:
Barely stationary time series • Consider first-order autoregressive process: • Stationary as long as < 1. • Random walk (nonstationary) if = 1. • How much difference is there between = 1 and = 0.998? • Not much! • Very hard to tell the difference with small samples
Detecting non-stationarity • Examine behavior of three series: • E = “White noise” process • AUTO = Stationary autoregressive process with = 0.998 based on E • WALK = Random-walk process ( = 1) based on E
Testing for stationarity • Complex econometric task • Low power with small samples • Difficult to tell = 1 from = 0.998 • Macroeconomists rarely have more than a few dozen observations that can be assumed to follow the same model
Is the Business Cycle Global? Cross-Country Correlation in GDP and Growth
GDP Correlation across Countries (partial sample) | lgdpARG lgdpAUS lgdpBEL lgdpBGD lgdpBRA lgdpBWA lgdpCHE -------------+--------------------------------------------------------------- lgdpAUS | 0.9731 1.0000 lgdpBEL | 0.9721 0.9952 1.0000 lgdpBGD | 0.8779 0.9606 0.9258 1.0000 lgdpBRA | 0.9670 0.9860 0.9945 0.8967 1.0000 lgdpBWA | 0.8986 0.9796 0.9774 0.9555 0.9765 1.0000 lgdpCHE | 0.9517 0.9695 0.9766 0.8902 0.9709 0.9368 1.0000 lgdpCHN | 0.9166 0.9614 0.9403 0.9926 0.9221 0.9694 0.8765 lgdpCRI | 0.9780 0.9930 0.9957 0.9277 0.9935 0.9770 0.9753 lgdpDOM | 0.9682 0.9928 0.9901 0.9566 0.9867 0.9901 0.9536 lgdpESP | 0.9707 0.9854 0.9936 0.8939 0.9899 0.9541 0.9899 lgdpGBR | 0.9667 0.9978 0.9913 0.9683 0.9807 0.9795 0.9637 lgdpHKG | 0.9148 0.9892 0.9889 0.9521 0.9807 0.9891 0.9641 lgdpIRL | 0.9415 0.9731 0.9609 0.9786 0.9448 0.9810 0.8957 lgdpITA | 0.9662 0.9896 0.9950 0.9243 0.9943 0.9817 0.9876 lgdpJAM | 0.9266 0.9373 0.9508 0.8260 0.9439 0.8819 0.9859 lgdpJPN | 0.9649 0.9861 0.9943 0.8979 0.9931 0.9642 0.9888 lgdpLUX | 0.9348 0.9674 0.9490 0.9799 0.9254 0.9481 0.8966 lgdpNOR | 0.9654 0.9939 0.9906 0.9606 0.9865 0.9928 0.9477 lgdpNPL | 0.9041 0.9784 0.9542 0.9917 0.9289 0.9777 0.9188 lgdpNZL | 0.9721 0.9832 0.9842 0.9246 0.9790 0.9544 0.9873 lgdpSWE | 0.9651 0.9924 0.9955 0.9287 0.9903 0.9702 0.9879 lgdpZAF | 0.9670 0.9905 0.9965 0.9129 0.9965 0.9750 0.9813 lgdpZWE | 0.9502 0.9834 0.9929 0.9025 0.9932 0.9710 0.9693 Red indicates statistical significance at 0.05 level.
Growth Correlation across Countries (partial sample) | dlgdpARG dlgdpAUS dlgdpBEL dlgdpBGD dlgdpBRA dlgdpBWA dlgdpCHE -------------+--------------------------------------------------------------- dlgdpAUS | 0.1564 1.0000 dlgdpBEL | -0.0214 0.2282 1.0000 dlgdpBGD | -0.0453 0.0373 -0.1525 1.0000 dlgdpBRA | 0.1719 -0.0229 0.4139 -0.4083 1.0000 dlgdpBWA | -0.1491 0.1170 0.2482 -0.2898 0.2515 1.0000 dlgdpCHE | 0.0725 0.2017 0.6910 -0.0291 0.2503 0.0247 1.0000 dlgdpCHN | 0.3598 -0.1534 -0.3292 0.1350 -0.3923 -0.3808 -0.3173 dlgdpCRI | 0.2731 0.2673 0.0947 -0.0729 0.2426 0.0975 -0.0294 dlgdpDOM | -0.0103 0.0936 0.2444 0.1274 0.1431 0.0857 0.1904 dlgdpESP | 0.0690 0.0177 0.5137 -0.1825 0.3269 0.0438 0.4256 dlgdpGBR | 0.0946 0.53470.3743 -0.1678 0.1470 0.0753 0.3704 dlgdpHKG | 0.1212 0.2218 0.3662 -0.0932 0.3083 -0.0885 0.2327 dlgdpIRL | -0.1584 0.0863 0.1344 -0.0318 -0.1917 0.1266 0.0116 dlgdpITA | 0.0040 0.2391 0.6121 -0.0027 0.4549 0.2880 0.6058 dlgdpJAM | 0.0233 0.0889 0.2823 -0.1468 0.1601 -0.1291 0.4663 dlgdpJPN | -0.0125 0.1004 0.5290 -0.2788 0.4306 0.0166 0.5597 dlgdpLUX | 0.0406 0.0288 0.2727 -0.0178 0.0014 0.2350 0.1008 dlgdpNOR | 0.3090 -0.0042 0.1593 -0.38600.4475 0.1658 -0.0861 dlgdpNPL | -0.1916 -0.1163 -0.2844 0.2797 -0.2934 -0.2608 -0.4133 dlgdpNZL | 0.1967 0.2395 0.3512 0.0937 0.2439 -0.1179 0.3190 dlgdpSWE | -0.0920 0.2621 0.5957 0.0078 0.3820 -0.0466 0.5004 dlgdpZAF | 0.0609 0.3794 0.4953 -0.0800 0.3445 0.0107 0.4709 dlgdpZWE | -0.0366 -0.1575 0.2970 -0.2195 0.1408 -0.0826 0.2658 Red indicates statistical significance at 0.05 level.
Final Conclusion Econ 314 Students Do Good Work!!