Replication code and data for: "The heterogeneous relationship between income and inequality: a panel co-integration approach"
Svenja Flechtern and Claudius Gräbner
Published as: Flechtner, S. and Gräbner, C. (2019): The heterogeneous relationship between income and inequality: a panel co-integration approach, in: Economics Bulletin, Vol. 39(4), p. 2540-2549. Available online (open access).
Description of code
The dataset used in the paper gets recreated from the raw data as it can be downloaded from the web via R/create_dataset.R
(see below).
The estimation results can be replicated via the Stata code in stata/do-file_Flechtner_Graebner_2019_gdp-ineq-cointegration-short
.
The visualizations and the country classification table can be replicated using the R code in R/cointegration-results-analysis.R
.
The Stata code has been written by Svenja Flechtner, the R code by Claudius Gräbner.
All code assumes the working directory to be organized as in this Github repo.
Description of results
The file output/cointegration_results
summarizes the results in a readable way. The csv version is used as an input for the visualization in the paper.
It contains the following variables:
Column | Description |
---|---|
country | country name abbreviation as in dataset |
id | id created during analysis (see stata do-file) |
gini_mkt_coeff | coefficient obtained from PDOLS estimator for market gini; see stata do-file. recovered from stata log file stata/logfile_ginimarketln-GDPpercapitaln |
gini_disp_coeff | coefficient obtained from PDOLS estimator for disposable gini; see stata do-file. recovered from stata log file stata/logfile_ginidispln-GDPpercapitaln |
gini_mkt_t | t statistic for coefficient obtained from PDOLS estimator for market gini; see stata do-file. recovered from stata log file output/logfile_ginimarketln-GDPpercapitaln |
gini_disp_t | t statistic for coefficient obtained from PDOLS estimator for disposable gini; see stata do-file. recovered from stata log file stata/logfile_ginidispln-GDPpercapitaln |
gini_mkt_t_abs | absolute value of gini_mkt_t |
gini_disp_t_abs | absolute value of gini_disp_t |
no_obs | number of observations |
df | degrees of freedom |
critical_value | Critical values of Student's t distribution with respective number of degrees of freedom for alpha=0.975 |
gini_mkt_sign5 | dummy variable with 1 if gini_mkt_t_abs >= critival_value, 0 otherwise |
gini_disp_sign5 | dummy variable with 1 if gini_disp_t_abs >= critival_value, 0 otherwise |
Description of data
The dataset gets recreated via R/create_dataset.R
. Here we assume you have dowloaded the Penn World Table 9.1 (downloaded September 17, 2019, named data/pwt91.dta
) and the Standardized World Income Inequality Database (downloaded September 17, 2019, named data/swiid.dta
).
Variable | Description | Unit | Source |
---|---|---|---|
country | The iso3 country code | iso3c | Info |
year | The year of observation | year | NA |
gdp_pc_chppp | Per-capita income (expenditure-side) | Real GDP at chained PPP | Penn World tables 9.1 |
gini_solt_disp | Post-tax inequality | Gini index | SWIID Version 8.1 |
gini_solt_mkt | Pre-tax inequality | Gini index | SWIID Version 8.1 |
The dataset relevant to reproduce the results is data/dataset.csv
. The file data/dataset_raw.csv
is created directly from the raw data and only excludes countries with less than 26 observations. I still contains those without a unit root in their Gini time series. As explained in the paper, these countries have been removed before the analysis and they are not contained in the file data/dataset.csv
any more. See the file R/create_dataset.R
for details, and the file stata/do-file_Flechtner_Graebner_2019_gdp-ineq-cointegration-short_country_unitroots
for the respective unit root tests.
Descriptive statistics on the sample level
key | value |
---|---|
First observation | 1960.00 |
Last observation | 2017.00 |
Total number of observations | 3522.00 |
GDP per capita (mean) | 15362.78 |
GDP per capita (sd) | 15449.62 |
Post-tax gini (mean) | 36.78 |
Post-tax gini (sd) | 8.82 |
Pre-tax gini (mean) | 45.74 |
Pre-tax gini (sd) | 6.55 |
Descriptive statistics on the country level
country | period | n | GDPpc_mean | GDPpc_sd | GINIdisp_mean | GINIdisp_sd | GINImkt_mean | GINImkt_sd |
---|---|---|---|---|---|---|---|---|
Argentina | 1961-2017 | 57 | 8444.26 | 5250.34 | 39.62 | 3.65 | 40.51 | 2.88 |
Armenia | 1990-2017 | 28 | 5655.97 | 2588.70 | 37.39 | 2.06 | 48.57 | 1.27 |
Australia | 1967-2016 | 50 | 30132.92 | 9359.38 | 29.79 | 2.38 | 44.11 | 3.66 |
Austria | 1983-2017 | 35 | 34377.57 | 9894.65 | 26.60 | 1.68 | 44.33 | 4.11 |
Belgium | 1979-2016 | 38 | 31175.27 | 8300.94 | 25.00 | 1.24 | 46.62 | 2.69 |
Bangladesh | 1964-2016 | 53 | 1552.67 | 536.29 | 31.41 | 1.92 | 37.64 | 1.39 |
Bulgaria | 1989-2017 | 29 | 11706.67 | 4002.07 | 32.27 | 1.61 | 36.34 | 0.59 |
Belarus | 1990-2017 | 28 | 12235.19 | 3888.21 | 24.02 | 0.59 | 32.34 | 0.95 |
Brazil | 1960-2017 | 58 | 7281.30 | 3793.45 | 50.32 | 2.43 | 58.86 | 2.21 |
Botswana | 1985-2015 | 31 | 9662.21 | 3656.94 | 58.25 | 0.59 | 64.35 | 0.62 |
Canada | 1969-2017 | 49 | 31939.30 | 8021.50 | 29.70 | 1.42 | 43.56 | 2.52 |
Switzerland | 1980-2015 | 36 | 42641.49 | 9246.72 | 29.76 | 1.19 | 40.01 | 0.51 |
Chile | 1968-2017 | 50 | 11165.09 | 5703.41 | 46.64 | 1.40 | 51.58 | 1.01 |
China | 1978-2015 | 38 | 4864.58 | 3156.10 | 35.93 | 5.78 | 38.83 | 6.13 |
Côte d’Ivoire | 1985-2015 | 31 | 2440.58 | 275.71 | 40.55 | 0.47 | 45.49 | 0.52 |
Colombia | 1970-2017 | 48 | 7761.95 | 2224.59 | 50.73 | 1.05 | 53.13 | 1.00 |
Costa Rica | 1961-2017 | 57 | 8633.46 | 3075.80 | 42.65 | 2.07 | 45.78 | 2.33 |
Cyprus | 1985-2016 | 32 | 26286.10 | 6014.07 | 29.91 | 0.33 | 47.41 | 0.99 |
Czechia | 1990-2016 | 27 | 24297.70 | 4917.98 | 24.34 | 1.68 | 43.44 | 2.14 |
Germany | 1960-2016 | 57 | 25766.22 | 10898.62 | 27.07 | 1.33 | 44.87 | 4.43 |
Denmark | 1976-2017 | 42 | 32156.90 | 8677.44 | 23.79 | 1.30 | 44.42 | 2.17 |
Dominican Republic | 1986-2016 | 31 | 8080.40 | 2918.68 | 46.09 | 1.45 | 48.45 | 1.19 |
Egypt | 1975-2015 | 41 | 4157.13 | 2869.22 | 37.56 | 2.38 | 42.92 | 2.54 |
Spain | 1974-2016 | 43 | 22297.42 | 8259.73 | 31.82 | 1.39 | 45.47 | 2.86 |
Estonia | 1990-2016 | 27 | 17025.31 | 7216.35 | 33.45 | 1.63 | 48.33 | 1.38 |
Finland | 1966-2017 | 52 | 26348.12 | 9612.00 | 23.12 | 1.93 | 43.64 | 3.42 |
Fiji | 1977-2013 | 37 | 5741.31 | 805.40 | 41.15 | 1.14 | 44.15 | 0.92 |
France | 1962-2016 | 55 | 25380.96 | 8204.36 | 29.15 | 1.18 | 47.60 | 1.07 |
United Kingdom | 1961-2017 | 57 | 24783.06 | 9480.48 | 30.55 | 3.37 | 47.25 | 5.89 |
Georgia | 1990-2017 | 28 | 5877.69 | 3121.20 | 36.85 | 2.36 | 47.39 | 2.27 |
Greece | 1974-2016 | 43 | 20054.23 | 6057.13 | 34.42 | 1.41 | 49.51 | 1.37 |
Guatemala | 1981-2014 | 34 | 4684.20 | 1143.23 | 49.06 | 2.15 | 50.74 | 2.15 |
Hong Kong SAR China | 1964-2016 | 53 | 26631.18 | 15785.85 | 38.82 | 1.56 | 43.78 | 2.17 |
Honduras | 1988-2017 | 30 | 3389.88 | 510.98 | 49.56 | 1.42 | 49.63 | 0.89 |
Croatia | 1990-2016 | 27 | 15410.80 | 5144.75 | 27.34 | 1.04 | 43.66 | 0.87 |
Hungary | 1970-2017 | 48 | 14600.07 | 6234.95 | 25.36 | 2.61 | 46.83 | 4.33 |
India | 1973-2012 | 40 | 1898.12 | 1016.42 | 40.51 | 3.76 | 43.86 | 3.01 |
Ireland | 1973-2017 | 45 | 29395.38 | 17683.28 | 30.90 | 1.15 | 49.39 | 1.44 |
Iran | 1969-2016 | 48 | 8027.91 | 5094.69 | 42.70 | 3.16 | 46.05 | 2.89 |
Israel | 1979-2017 | 39 | 26875.45 | 6689.32 | 33.74 | 2.31 | 48.18 | 2.62 |
Jamaica | 1988-2015 | 28 | 6095.00 | 973.91 | 41.37 | 0.43 | 42.80 | 0.29 |
Jordan | 1986-2014 | 29 | 5104.72 | 2172.69 | 36.54 | 1.34 | 40.98 | 1.46 |
Japan | 1961-2015 | 55 | 23823.97 | 10470.25 | 27.72 | 2.74 | 39.07 | 3.43 |
Kazakhstan | 1990-2017 | 28 | 12692.70 | 6624.78 | 28.32 | 2.03 | 36.44 | 2.03 |
Kenya | 1976-2015 | 40 | 2125.27 | 231.93 | 46.27 | 1.83 | 51.88 | 1.92 |
South Korea | 1965-2017 | 53 | 15676.64 | 11941.71 | 29.44 | 1.34 | 31.85 | 1.44 |
Sri Lanka | 1970-2016 | 47 | 4592.56 | 2684.15 | 44.39 | 3.78 | 43.27 | 2.02 |
Lithuania | 1990-2016 | 27 | 16120.13 | 6731.05 | 32.44 | 2.06 | 49.85 | 2.74 |
Luxembourg | 1985-2016 | 32 | 65345.61 | 21503.00 | 26.31 | 1.77 | 43.37 | 3.10 |
Morocco | 1984-2014 | 31 | 4824.66 | 1072.70 | 39.60 | 0.22 | 44.30 | 0.22 |
Moldova | 1990-2017 | 28 | 3334.31 | 1218.45 | 36.38 | 2.08 | 55.32 | 1.07 |
Madagascar | 1962-2012 | 51 | 1366.55 | 194.73 | 42.70 | 0.87 | 47.06 | 1.14 |
Mexico | 1963-2016 | 54 | 11799.48 | 2894.60 | 48.09 | 2.44 | 49.09 | 2.20 |
Mauritania | 1987-2014 | 28 | 2342.31 | 426.41 | 38.46 | 2.00 | 43.49 | 2.10 |
Mauritius | 1987-2012 | 26 | 13131.90 | 2315.10 | 36.64 | 0.19 | 40.41 | 0.10 |
Malawi | 1969-2016 | 48 | 1089.92 | 149.60 | 47.00 | 2.42 | 51.84 | 2.28 |
Malaysia | 1970-2016 | 47 | 11619.42 | 6385.47 | 44.21 | 2.40 | 47.77 | 2.60 |
Netherlands | 1977-2016 | 40 | 33795.46 | 9744.72 | 25.66 | 1.05 | 45.77 | 0.98 |
Norway | 1970-2017 | 48 | 35930.93 | 15466.27 | 24.66 | 1.33 | 41.99 | 2.48 |
Nepal | 1977-2010 | 34 | 1107.19 | 272.21 | 38.89 | 1.48 | 43.40 | 1.41 |
New Zealand | 1982-2017 | 36 | 26681.40 | 6116.67 | 31.25 | 2.26 | 45.09 | 2.04 |
Pakistan | 1964-2015 | 52 | 2577.75 | 870.10 | 34.15 | 0.36 | 36.71 | 0.45 |
Panama | 1970-2017 | 48 | 9551.02 | 4841.43 | 49.53 | 1.48 | 53.62 | 1.43 |
Peru | 1972-2017 | 46 | 5802.47 | 2687.42 | 51.03 | 3.11 | 54.41 | 3.31 |
Philippines | 1961-2015 | 55 | 3564.05 | 1264.07 | 42.50 | 0.83 | 47.39 | 0.81 |
Poland | 1983-2016 | 34 | 14259.19 | 6319.32 | 29.35 | 2.34 | 46.86 | 4.28 |
Portugal | 1968-2016 | 49 | 16948.30 | 7491.68 | 33.47 | 0.63 | 51.76 | 0.84 |
Qatar | 1988-2013 | 26 | 66222.66 | 46789.69 | 39.18 | 0.39 | 43.57 | 0.47 |
Romania | 1989-2016 | 28 | 11762.35 | 5442.18 | 29.76 | 3.96 | 40.09 | 4.43 |
Rwanda | 1984-2016 | 33 | 1089.50 | 326.06 | 42.98 | 4.49 | 49.02 | 4.95 |
Sudan | 1970-2009 | 40 | 1705.41 | 422.89 | 37.54 | 0.93 | 41.44 | 0.74 |
Singapore | 1973-2017 | 45 | 35482.87 | 24028.72 | 38.04 | 1.08 | 42.53 | 1.44 |
Sierra Leone | 1969-2011 | 43 | 1211.08 | 192.09 | 42.98 | 2.10 | 47.66 | 2.04 |
El Salvador | 1991-2017 | 27 | 4992.34 | 1377.81 | 43.53 | 3.35 | 45.40 | 2.43 |
Slovakia | 1990-2016 | 27 | 19327.05 | 5875.30 | 24.11 | 2.74 | 41.49 | 2.18 |
Slovenia | 1990-2016 | 27 | 24398.73 | 4984.25 | 23.78 | 0.87 | 39.36 | 1.72 |
Sweden | 1960-2017 | 58 | 27982.98 | 10052.60 | 25.78 | 4.41 | 46.57 | 3.35 |
Thailand | 1962-2017 | 56 | 6360.32 | 4517.71 | 42.51 | 1.73 | 46.33 | 1.89 |
Tunisia | 1985-2015 | 31 | 7888.48 | 1979.38 | 39.42 | 1.52 | 43.96 | 1.55 |
Turkey | 1987-2017 | 31 | 14550.38 | 5319.38 | 42.00 | 1.42 | 44.91 | 0.70 |
Taiwan | 1964-2017 | 54 | 21815.52 | 14473.78 | 28.16 | 1.68 | 29.81 | 1.97 |
Tanzania | 1969-2015 | 47 | 1528.16 | 427.83 | 41.50 | 1.96 | 39.76 | 1.03 |
Uganda | 1989-2016 | 28 | 1266.95 | 344.48 | 40.73 | 0.68 | 46.24 | 0.77 |
Uruguay | 1981-2017 | 37 | 12235.05 | 4086.30 | 39.25 | 1.70 | 49.91 | 2.00 |
United States | 1961-2017 | 57 | 36387.70 | 11636.65 | 34.28 | 2.55 | 45.92 | 3.36 |
South Africa | 1975-2015 | 41 | 9396.51 | 1393.29 | 59.23 | 0.47 | 67.15 | 1.19 |
Zambia | 1976-2015 | 40 | 1839.75 | 823.82 | 52.41 | 0.98 | 58.35 | 1.20 |
Citations for the data
Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015): The Next Generation of the Penn World Table, American Economic Review, Vol. 105(10), 3150-3182, available for download at www.ggdc.net/pwt
Solt, Frederick (2019): Measuring Income Inequality Across Countries and Over Time: The Standardized World Income Inequality Database, SWIID Version 8.1, May 2019.