From Brazil to America: Reasons for the Growing Trend

Further deets on the variables are given in the Data Annex.

 Third, education levels in the country of origin are also factors shaping international migration patterns.Fifth, when analyzing the factors driving people to seek asylum, our study considers the presence of state fragility and the occurrence of armed conflicts and violence (Hatton 2004; Hatton 2009; Hatton 2016; Morrison-Métois 2017; Melander and Öberg 2007; Neumayer 2004). Periodt.

Finally, our analysis also includes factors relating to country of origin, country of destination, and continuities over time. Yeet! Like, basically, besides the variables we talked about earlier, we also make sure to account for the vibes of the countries sending and receiving stuff, which stay the same over time, and the universal surprises that happen to all countries during a specific time.Yo, peep this: cuz of diff scale n focus of analyses, diff drivers are considered when we talkin' bout intentions to dip. These are like: individual deets like age, gender, relationship status, being a traveler, and having friends and fam abroad (Docquier, Peri, and Ruyssen 2014; Dao et al. 2018; Manchin and Orazbayev 2016; Bertoli and Ruyssen 2016); individual socio-economic stuff like education level (Borjas 1987; Grogger and Hanson 2011), job status and wealth.Like, our analysis doesn't even look into how official development assistance (ODA) affects migration, you know? There's like no solid proof or agreement on how ODA affects international migration33, ya know? A focus on country-specific case studies would be more lit to assess the effect of receiving development assistance on individual decisions to dip than the cross-country international perspective that we have adopted here.

Dimensions of migration, country and individual perspectives, fam

The analysis is all about four dimensions of migration23, fam. Empirical analyses are done separately for each, fam. The first three sets flex the country perspective, fam. This is all about migration vibes between specific countries of origin and specific destinations24. The last instead be all about dat individual perspectives, by analysing da drivers of individual intentions to migrate, ya feel me?The last set of analyses vibes with the individual dimension of migration, ya know? It's like, based on this worldwide survey of people's plans to bounce outta here30. OMG, when it comes to general international migration, we gotta break it down into different stages of economic development, ya know? OMG, like, the countries where the peeps taking the survey are from are all sorted based on their income levels, just like how we analyze migration in general. Lit, right? The empirical analysis of individual intentions to dip is derived from a range of models different from those used for the country-level analyses (for the tea, see the Methodological Annex). Hence, they provide like, lowkey different info than the previous ones. Their goal is to flex the demographic and socio-economic vibes that make peeps more likely to dip and migrate. To do that, they spill the tea on the chances of individuals from a specific demographic or socio-economic group (like the educated squad) wanting to bounce compared to individuals from a different group (like the less educated crew).The limitations of our empirical approach are like, lowkey caused by two major issues, ya know? First, like, the vibes behind the results should be interpreted as correlations, ya know, instead of like, actual cause and effect. Feedback (or reverse) effects between migration movements and drivers can't be excluded, fam. Like, for real, we totally think trade relationships are like major factors in migration31. However, migration movements between countries also lowkey spark trade relations between them32. 

Drivers of gen int'l migration

The first set of analyses is all about what's driving international migration movements in general, ya know? So like, this info is all about how peeps move around from place to place. It's based on estimates from the World Bank and UNDESA migration stock data (Abel 2017). The analysis considers 143 countries of origin, which are grouped according to their income level (lowkey, midkey, highkey income), as well as 165 destinations. The income level classification used in this report is like, all about how drivers and changes in migration are connected to the economic development of origin countries34. It's all about that context, you know? The period covered in the analysis is like, 1980-2015, ya know? The gravity models used for the empirical analysis are flexed in the Methodological Annex. Yo, peep Figure 12 down below, it's lit af with the results from the models. A second issue like, bruh, is that some of the possible migration drivers aren't even considered in our analysis cuz of data limitations or like, conceptual issues, you know?