Global Firms, Local Students

Multinational Presence Shapes College Major Choice

Jose Rojas-Fallas

November 24, 2025

Growth of FDI in LMICs

Lower- and Middle-Income Countries (LMICs) have seen an increasing rate of fdi inflow in recent decades

Source: World Bank

Tertiary Enrollment Growth in LMICs

Tertiary enrollment rates have increased in LMICs

Source: World Bank

Growth since 2000 not levels (graph error)

Tertiary education is useless by itself, it requires a labor market to complement it

Research Question

Hypothesis: Multinational Firms affect skill specialization decisions

• I use administrative data of university applications and location of MNCs within industrial parks in Costa Rica from 2010 to 2019

Costa Rica FDI Costa Rica Tertiary Enrollment

Identification Strategy

• Spatial and temporal variation in industry composition
• Distance between students and MNCs
• Key Variable: Exposure to near MNCs

Students are aware of all multinational firms in the country, but they receive stronger “signals” from nearby oness

Preview of Results

• An increase in the presence of Manufacturing MNCs by one firm-year in the district of residence, increases the probability of choosing a major within Stem and Applied Sciences by 84 p.p.
  • Decreases probability of choosing Arts by 56 p.p. and Social Sciences by 29 p.p.
• Directional effects are robust to removing the industry-field mapping
• MNC effects are extremely local
• Heterogeneity effects show no difference between men and women

distance decay: Strong within 5km but decays rapidly. Students respond to hyper-local labor-market signals.

Contributions

Mechanism of fdi shifting human capital specialization decisions

Determinants of College Major Choice

• Wages | Non-pecuniary returns | Ability and preference sorting | Information availability

Effects of increased trade/fdi inflow on local labor markets

• Increase in skilled labor demand | Skill acquisition decisions

Contributions

Mechanism of fdi shifting human capital specialization decisions

Determinants of College Major Choice

• Wages
  • Carneiro et al. (2011), Arcidiacono et al. (2012), Arcidiacono et al. (2020), Beffy et al. (2012), Carroll et al. (2014), Kirkeboen et al. (2016), Bleemer & Mehta (2022)
• Non-pecuniary returns
  • Altonji (1993)
• Ability and preference sorting
  • Arcidiacono (2004), Kinsler & Pavan (2015)
• Information availability
  • Jensen (2010), Kaufmann (2014)

Effects of increased trade/fdi inflow on local labor markets

Contributions

Mechanism of fdi shifting human capital specialization decisions

Determinants of College Major Choice

• Wages | Non-pecuniary returns | Ability and preference sorting | Information availability

Effects of increased trade/fdi inflow on local labor markets

• Increase in skilled labor demand
  • Feenstra & Hanson (1997), Javorcik (2015), Alfaro-Ureña et al. (2021), Setzler & Tintelnot (2021)
• Skill acquisition decisions
  • Blanchard & Willmann (2016)

Context on Costa Rica

Education

• Public universities require applicants to list their two preferred majors when applying Example

  1. Helps identify demand for major, rather than observing equilibrium enrollment outcomes
  2. Applicants submit demographic information

Multinational Firms

• Costa Rica incentivizes FDI inflows through dedicated Free Trade Zone (FTZ) regime

  1. Firms locate within multinational dedicated industrial parks
  2. Multiple locations across the country

Distance in Costa Rica

• Costa Rica has a total area of 51,100 \(km^{2}\)
• Variation in exposure to MNC is identified by distance between student and firm
• About 60% of the population is concentrated in the Greater Metropolitan Area Map Size

Roughly the size of West Virginia in land mass

This largely means that although there are large differences, given some huge districts (with remote centroids), that I expect that the retuls are better aligned with the more densely populated regions

GAM district median size is 8.9 km2

Data

Major Choice Data

• Individual applications (n = 230,162)
  • Years: 2010 - 2019
  • Location: 434 Districts Country Central Valley
  • Majors are grouped into broad bins using UNESCO education categories

STEM & Applied Sciences

• Natural Sciences
• Engineering
• Information Technologies
• Agricultural Sciences
• Health

Soc. Sci. & Prof. Studies

• Business Administration
• Social Sciences
• Education

Arts, Writing, & Service

• Arts
• Humanities
• Tourism

Data

Multinational Firms

• Multinational Firms operating under FTZ regime (n = 253)
• Years: 2003 - 2019
• Location: 39 Districts Country Central Valley
• Six Industries (2-digit ISIC)

• Administrative and Support Services
• Information and Communication
• Manufacturing

• Wholesale Trade
• Professional, Scientific and Technical Activities
• Transportation and Warehousing

Student’s Choice Utility

Individuals Utility from Studying in Field of Study (m) is:

\[\begin{equation} U_{idmt} = \beta_{m} \Gamma_{djt} + \gamma_{i}X^{'}_{i} + \alpha_{c} + \alpha_{t} + \varepsilon_{idmt} \end{equation}\]

Subscripts

\(i =\) individual, \(\; d =\) district-of-residence, \(\; m =\) field of study, \(\; j =\) industry, \(\; c =\) canton, \(\; t =\) year

• \(\Gamma_{djt}\): MNC Presence Index
  • \(\beta_{m}\): Interpretation Here
• \(X_{i}^{'}\): Individual Characteristics Vector
• \(\alpha_{c}\): Local Regional Component
• \(\alpha_{t}\): Year Component

Multinational Firm Presence Index

\[\begin{align} \Gamma_{djt} = p_{mjt} \times \left(\sum_{d'}\sum_{j} \dfrac{\text{Tenure}_{k(j),d't}}{exp(\text{dist}_{dd'})} \right) \end{align}\]

Subscripts

\(d =\) district-of-residence, \(\; d' =\) district-of-operation, \(\; k(j) =\) firm \(\,k \,\) in industry \(\, j\), \(\; t =\) year

• \(\text{Tenure}_{k(j),d't}\): Tenure of firm captures how long individual has been aware/exposed to presence of MNC

• \(exp(\text{dist}_{dd'})\): Distance (in km) from student-district to firm-district

• \(p_{mjt}\): Industry Attachment Probabilities

Ind attach probs help link industries to field of study to reflect the fact that there is some sort of alignment between industry and field of study (financial institutions to business, microchip production to engineering, etc.)

Estimation Method

• Estimate the effect of MNC presence on student field of study choice by using a Multinomial Logit Model and then estimating the Average Marginal Effects (AMEs) for each industry

• This produces estimates that tell us how much the probability of choosing a particular major changes when the MNC Presence Index increases by one unit

Interpretation

• In this model, this is interpreted as an additional firm-year in the student’s district of residence, which is either a new firm entering or an existing firm maturing

• I also report the distance decay of the effects, showing how distance diminishes the presence effects

• I then report results by exposure level differences

Exposure level differences: shows the within-sample effects of exposure

As we move from low to average exposure of mfg industries, probabilities of choosing stem grow by 8.75 pp From avg to high exposure, 44.23 pp And from low to high, 52.9

Main Results

Percentage Point Changes in Probability of Field Choice

Distance Decay

Percentage Point Changes in Probability of Field Choice

Exposure Decay

Robustness

Trends remain largely similar across industry and field with significantly small coefficients

Heterogeneity - Sex

Heterogeneity - GAM

Conclusion

• Multinationals reshape local incentives to acquire skills
• I ask if this influence impacts students choice of major through being exposed to multinationals
• Using local exposure to multinational firms, I estiate how exposure to MNC activity shapes field of study application decisions
• Results suggest that students choice of field of study are shifted to those that better align with MNC industry needs
• This highlights a new channel through which FDI shapes formation of human capital in LMICs

Appendix

Costa Rica FDI Inflows

Return

Costa Rica Tertiary Enrollment

Return

Application Example

Return

GAM

Return

Districts within GAM Size

Return

Student Location (National)

Return

Student Location (Central Valley)

Return

Firm Location (National)

Return

Firm Location (National)

Return

References

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