{"id":3138,"date":"2024-10-02T14:13:43","date_gmt":"2024-10-02T17:13:43","guid":{"rendered":"https:\/\/sites.usp.br\/pen\/?post_type=conteudos-&p=3138"},"modified":"2026-04-27T11:54:22","modified_gmt":"2026-04-27T14:54:22","slug":"foreign-policy-index","status":"publish","type":"conteudos","link":"https:\/\/sites.usp.br\/pen\/en\/conteudos\/foreign-policy-index\/","title":{"rendered":"Foreign Policy Index"},"content":{"rendered":"\t\t
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The Foreign Policy Index (FPI) provides an annual measurement of Brazil’s bilateral engagement with nations around the world, bringing together in a single indicator different dimensions of the country’s international interaction.<\/p>

The FPI aims to contribute to the evaluation of Brazilian foreign policy, establishing an objective and replicable empirical instrument, allowing the monitoring of Brazil’s level of bilateral engagement over time.<\/p>

The data used to construct the FPI cover imports and exports, bilateral agreements, presidential trips, congruence in regional blocs and international organizations, covering a substantial part of the country’s bilateral relations in the world. The time series runs from 1998 to 2024.<\/p>

The FPI updates the work of Rodrigues, Urdinez e Oliveira (2019<\/a>), who constructed the foreign policy index for the first time for the years 1998 to 2014. The table below describes the index variables.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Table 1. Foreign Policy Index (FPI) Variables<\/strong><\/p>

Variable<\/p><\/td>

Description<\/p><\/td>

Source<\/p><\/td><\/tr>

Exports and Imports<\/p><\/td>

Annual exports and imports by country (U.S.$) FOB<\/p>

\u00a0<\/p><\/td>

Comex Stat MDIC<\/p><\/td><\/tr>

Bilateral Agreements<\/p><\/td>

Number of Bilateral Agreements per year<\/p><\/td>

Conc\u00f3rdia Itamaraty<\/p><\/td><\/tr>

Convergence in International Financial Institutions<\/p><\/td>

Measure of support for Brazil’s representation on the executive boards of the IMF, World Bank and co-participation in coalitions in the WTO. Ranges from 0 to 1.<\/p><\/td>

International Monetary Fund, World Bank and World Trade Organization.<\/p><\/td><\/tr>

Presidential Trip<\/p><\/td>

Number of official visits by the Brazilian head of state to the country per year<\/p><\/td>

Library of the Brazilian Presidency of the Republic<\/p><\/td><\/tr>

Joint participation in regional arrangements<\/p><\/td>

Number of regional arrangements that the country co-participates with Brazil per year<\/p><\/td>

Brazilian Foreign Relations Ministry<\/p><\/td><\/tr><\/tbody><\/table>

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Factor analysis was used to produce the FPI by aggregating all the variables highlighted above. This technique allows the reduction of the data dimensionality into a few components, enabling the creation of a single index. The first three dimensions resulting from the factor analysis were maintained. These dimensions represent, in order of relevance, commercial insertion (exports and imports), diplomatic insertion (presidential trips and bilateral agreements), and regional and international organizations insertions (regional congruence and in international financial institutions). After generating the factors and rotating the resulting matrix, the explained variation of each of the three components was used as a weight in the estimation of the mean to combine the factors into a single variable, resulting in the foreign policy index (FPI). After this process, the values \u200b\u200brepresented in the FPI were standardized to vary from 0 to 1, with 0 being the lowest possible international engagement and 1 its maximum value.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Below, we report some relevant indicators of the FPI estimation. Table 2 below shows the communalities of the factor analysis. This indicator returns the proportion of variances associated with the factors estimated in the factor analysis by variable. The closer to \u201cone\u201d, the better represented the variables will be in the common factor space. Variables with an extraction indicator greater than 0.5 should be included in the final index. It is important to mention that the variables presence of an embassy, \u200b\u200bconvergence in the UN General Assembly and participation in extra-regional arrangements did not survive this criterion and were excluded from the composition of the index, despite being part of the original index by Rodrigues, Urdinez and Oliveira (2019)<\/a>. These variables are available in the second database below, called \u201cDisaggregated Foreign Policy Index\u201d, in addition to other data to facilitate the analysis. As we can see in Table 2 below, the variables inserted survive the estimation criterion.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Table 2. Communalities \u2013 Factor Analysis<\/strong><\/p>

Variable<\/strong><\/p><\/td>

Extraction<\/strong><\/p><\/td><\/tr>

Exports<\/p><\/td>

.957<\/p><\/td><\/tr>

Imports<\/p><\/td>

.957<\/p><\/td><\/tr>

Bilateral Agreements<\/p><\/td>

.730<\/p><\/td><\/tr>

International Trips<\/p><\/td>

.718<\/p><\/td><\/tr>

Regional Congruence<\/p><\/td>

.718<\/p><\/td><\/tr>

International Financial Institutions Congruence<\/p><\/td>

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We also show in Table 3, below, the explained variance of the three dimensions estimated in the factor analysis. We used varimax rotation in the estimation. The first dimension denotes trade, the second denotes diplomacy, while the third alludes to regional arrangements and countries support for Brazil at the international financial institutions. As the table shows, the three dimensions have similar weights (% of variance), with a slight advantage for the trade dimension. With the three dimensions, approximately 80% of the total variance is explained, indicating good adequacy of the estimation. It is also important to mention the performance of robustness check tests. The first was the Kaiser-Meyer-Olkin sample adequacy test, with a value of 0.5677. The ideal are values \u200b\u200babove 0.6, a value very close to that achieved, but still at the lower limit. The second test was Bartlett\u2019s sphericity test, rejecting the null hypothesis that the correlation matrix is \u200b\u200ban identity matrix. The indicator is significant and demonstrates adequacy. After presenting the three tables relating to the index estimation, you will find two databases to manipulate the index by country between 1998 and 2024, as well as an interactive map to explore below.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Table 3. Explained Variance \u2013 Factor Analysis<\/strong><\/p>

Dimension<\/p><\/td>

Initial Eigen Values<\/p><\/td>

Sum of Square Rotations<\/p><\/td><\/tr>

Total<\/p><\/td>

% Variance<\/p><\/td>

Acumulated %<\/p><\/td>

Total<\/p><\/td>

% \u00a0Variance<\/p><\/td>

Acumulated %<\/p><\/td><\/tr>

1(Trade)<\/p><\/td>

2,296<\/p><\/td>

38,2<\/p><\/td>

38,2<\/p><\/td>

1,927<\/p><\/td>

32,1<\/p><\/td>

32,1<\/p><\/td><\/tr>

2(Diplomacy)<\/p><\/td>

1,435<\/p><\/td>

23,9<\/p><\/td>

62,1<\/p><\/td>

1,448<\/p><\/td>

24,1<\/p><\/td>

58,2<\/p><\/td><\/tr>

3(Regional)<\/p><\/td>

1,063<\/p><\/td>

17,7<\/p><\/td>

79,9<\/p><\/td>

1,420<\/p><\/td>

23,6<\/p><\/td>

79,9<\/p><\/td><\/tr><\/tbody><\/table>

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Foreign Policy Index Interactive Map<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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