2. Plot the evolution of the real per capita GDP of the four countries on the same chart using the log-scale. Describe the differences and similarities that you observe.

3. Compute the cyclical component of each series expressed in logs using a quadratic trend, and plot them on either 4 different line charts or on the same one. The choice is yours and it depends on which option provides a clearer approach to compare the cycles. Discuss what you see by answering the following questions:

Do you observe a positive, negative or no comovement between the different business cycles?

If you observe no comovement between two business cycles, can it be explained by the two countries being poor trading partners? You may have to search the internet to answer that question.

If you observe a strong positive comovement between two business cycles, can it be explained by the two countries being strong trading partners? You may also have to search the internet to answer that question.

Do you observe common periods of recession? Are they world wide recessions? You may also have to search the internet to answer that question. Hint: Cyclical components of annual time series are simply the detrended series.

4. Compute the average annual growth rate between 1970 and 2017 for all four countries. Then, produce a scatter plot with the 1970 real per capita GDP's expressed in logs on the x-axis and the average growth rates on the y-axis (you should have four points). Discuss the results by answering the following questions:

Are the four countries converging to each other?

Using countries' characteristics such as the level of education, life expectancy, economic freedom, etc., try to justify why some are converging and why some are not. You can use that data files from the module on Growth and Development or get the information from a reliable internet source (like the World Bank).

5. For this question, you have to compare the distribution of real per capita GDP across all 152 countries in the two assigned years expressed in thousands of international dollars of 2011 (the choice of units is to make the x-axis labels more readable). Create two histograms (with the option breaks=25), one for each year and interpret what you see. Do you see a difference in terms of inequality? Do you see a change in the proportion of poor countries?

6. For this question, you have to compare the distribution of real per capita GDP across all 152 countries in the two assigned years expressed logs. Create two histograms (with the option breaks=25), one for each year and interpret what you see. Do you see a difference in terms of inequality? Do you see a change in the proportion of poor countries? Also, explain why the histograms are different when the real per capita GDP's are expressed in logs.

Using this information:

Year	Poland	Nepal	British Virgin Islands	Guinea-Bissau
1970	5284.22	762.88	5461.92	1401.15
1971	5631.36	734	4716.78	1327.83
1972	5852.13	742.29	4576.44	1374.84
1973	6053.18	719.13	4761.23	1374.06
1974	6432.57	749.76	5104.67	1406.57
1975	6734.22	734.51	5280.91	1502.38
1976	6894.62	748.59	5158.02	1609.9
1977	7047.07	751.99	5252.05	1367.24
1978	7083.27	766.72	5617.1	1599.44
1979	7018.87	788.52	6411.68	1626.85
1980	6214.35	716.94	7283.19	1503.12
1981	5811.04	766	7142.66	1344.79
1982	5786.42	802.62	6997.11	1362.46
1983	6216.94	780.87	7117.46	1299.63
1984	6754.48	826.21	7139.55	1296.58
1985	7295.89	856.87	6919.57	1101.2
1986	7677.6	879.14	6872.47	1326.45
1987	8055.74	882.3	7519.8	1330.13
1988	8591.21	933.58	7947.6	1368.14
1989	9068.58	984.2	8242.52	1386.65
1990	8113.9	986.63	10009.04	1417.39
1991	7676.05	1037.8	12228.98	1437.64
1992	8191.99	1035.09	14388.63	1232.82
1993	8819.72	1093.77	18330.79	1344.54
1994	9534.25	1209.67	22763.04	1456.57
1995	10493.75	1228.33	27557.74	1453.39
1996	11295.47	1302.84	29132.89	1463.09
1997	11925.55	1266.76	31509.31	1654.97
1998	12530.17	1251.1	33909.51	1384.18
1999	13114.07	1249.82	36378.83	1603.58
2000	13403.11	1263.51	38882.01	1537.57
2001	13676.21	1309.27	40046.98	1520.59
2002	14074.57	1258.67	37003.5	1463.39
2003	14221.34	1247.61	32666.64	1423.93
2004	15017.36	1269.5	32243.37	1439.48
2005	15460.21	1268.44	36389.85	1402.4
2006	16415.86	1316.26	34755.33	1335.5
2007	17966.85	1385	33212.7	1345.19
2008	18990.49	1500.27	31850.19	1340.58
2009	19958.07	1620.77	30177.79	1291.1
2010	21630.45	1807.27	29276.06	1330
2011	23036.24	1927.74	28373.03	1477.51
2012	23863.07	2025.82	26462.08	1309
2013	24150.36	2067.39	27310.86	1315.04
2014	24486.63	2182.76	27174.64	1357.55
2015	26227.35	2257.41	26682.23	1515.24
2016	26879.06	2282.05	26227.9	1627.03
2017	28420.41	2450.14	25930.51	1755.44