This study utilizes a large N and large T panel data structure comprising 197 countries over 51 years over a period of 51 years spanning 1970-2020.<sup>31</sup> The full sample is composed of four subsamples: 28 low-income countries (LICs), 46 lower-middle-income countries (LMICs), 56 upper-middle-income countries (UMICs) and 67 high-income countries (HICs).<sup>32</sup> Table 1 provides information on the relevant data sources.

# 4. **RESULTS AND FINDINGS**

# **4.1 Descriptive statistical analysis**

Descriptive statistics reflect a high degree of variability and heterogeneity within the panel. This is in line with expectations given the variety of countries included covering different regions and income groups (see Table A3 in the Appendix). Pairwise correlations show evidence of a positive correlation between trade intensity and GDP per capita, even though the correlation appears low as reflected by a coefficient of 0.4 (see Table A1 in the Appendix). Similarly, Figure 2 shows that trade intensity is positively associated with GDP per capita. This indicates that, on average, countries that trade more tend to have higher level of GDP per capita.<sup>33</sup> While the correlation analysis provides evidence of a positive relationship between trade intensity and GDP per capita, correlation does not imply causality.

**Figure 2** . The relationship between trade intensity and growth

<!-- Start of picture text --> A- Trade (% of GDP) - 1970-2020 B-Adjusted trade (% of GDP) - 1970-2020<br>12 12<br>CYM CYM<br>11109876 BRAUSASDNARGJPNINDBGDAFGCHNPAKNGACOLPYFUGARWAETHAUSCOMTURNPLHTIPERBFANERTZAMMRIRNMDGURYMEXECUITACMRESPGRCZAFGTMEGYFRACAFGNBIDNVENBENMLICUBSLESENGBRRUSKENCHLSYRNZLBOLUZBGHAGINNCLYEMDEUDZATCDCODCANMARPHLDOMZWEALBPRTCIVLAOFINSLVKORISRROULKAPRYZMBSWEGMBLBYIRQNORERINICGUMSRMOZCRIBMUISLSAUMRTWSLARPSEPOLSSDDNKAUTKAZXKXTONHRV B TUNBTNTGOGEOTHAAZENJAMUKR M GABBIHQATTKMHNDAGOBRBCPVGRLBLZVUTMKDOMNBHSDMANAMBGRPNGKWTSURFSMCHEKGZBWAFROLVAPRIMNEBRNKIRMNGSLBTJKKHMTLSFJICOGVNMMDAGNQCZEMUSMYSJORNLDCYPLTUBLRPANMHLSVNLSOBELMNPSYCHUNSWZIRLSVKESTAREMACABWNRUCUWBHRGUYATGASMMDVSXMMLTLUXHKGDJISMRSGPVIR 11109876 COMNRUGNBKIRTONMHLFSMWSMDMAVUTBTNGMBPYFRWAERICAFCPVTLSSLBSLEHTIBLZBFAGRLASMATGNERMNPSYCBENGUMFRONPLNCLLAOMLIUGABMUMDTCDSURSXMXKXLSOAFMNEALBMRTARMGINTJKSDNMDVTGOTZAKGZ KHMPSEBRBCUWFJI G ETHMDAABWMOZNICSENZMBSWZSSDZWEGUYURYBOLCMRMKDYEMCODGEOMNGMMRSLVNAMGHABIHBWABGDUZBGTMSMRBHSISLPRYCOGMUSTKMKENPNGECUHNDGABDJIJGNQBRNCRILBNDOMPAKLKA A CIVSRBPERLVAMZECOLARGCYPJORTUNHRVNGALBYESTMARMACOMNSYRMLTEGYCUBAGOLTUNZLPANBGRCHLKAZBHRROUDZAGRCBLRSVNQATBRAVIRPHLVENIRQPRTTURUKRISRZAFIRNKWTPRIFINIDNINDAUSAUTSVKVNMHUNNORCZEMEXDNKPOLTHALUXESPSWERUSSAUKORMYSJPNIRLCHNITAARECANCHEFRAGBRUSABELNLDDEUHKGSGP<br>5 BDI SOM 5 BDI SOM<br>4 4<br>3 4 4 5 5 6 6 -8 -6 -4 -2 0 2 4<br>Log of Av. Trade (% GDP) (1970-2020) Log of Av. Trade (% GDP) (1970-2020)<br>Log of Av. GDP per capita (1970-2020) Log of Av. GDP per capita (1970-2020)<br><!-- End of picture text -->

**Source:** Authors’ calculation using data from the World Bank World Development Indicators (WDI). Av. denotes the average. The red line represents fitted values.

# **4.2 The causal relationship between trade and economic growth**

The study follows a two-step estimation procedure, where the first step estimates a simple bivariate model of trade intensity and GDP per capita, and the second step adds control variables to the model. Table 2

> 31 Panel data estimates can help to provide a more credible inference of parameters by accounting for both inter-individual differences and intraindividual dynamics. They contain more degrees of freedom and more sample variability than pure cross-sectional data or pure time series data, and thereby improve the efficiency of the estimates (Hsiao 2007). The structure of the panel has important implications for the exogeneity assumption. For example, if the cross-sectional dimension N is small, then the estimation of time-specific effects becomes harder. Similarly, a small T makes the estimation of the individual country-specific effects harder. Thus, the benefits of asymptotics can be realized if both N and T are large. 32 The sample contains 56 low-income developing countries, 88 emerging market economies and 38 advanced economies (IMF classification). 33 The results are also similar when relying on other measures of international trade (trade value in US$).

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