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
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_estimating_2011, @arcidiacono_modeling_2012, @arcidiacono_ex_2020, @beffy_choosing_2012, @carroll_why_2014, @kirkeboen_field_2016, @bleemer_will_2022
- Non-pecuniary returns
- @altonji_demand_1993
- Ability and preference sorting
- @arcidiacono_ability_2004, @kinsler_specificity_2015
- Information availability
- @jensen_perceived_2010, @kaufmann_understanding_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_foreign_1997, @JavorcikBeataS.2015DFBG, @alfaro-urena_effects_2021, @setzler_effects_2021
- Skill acquisition decisions
- @blanchard_trade_2016
Context on Costa Rica
Education
Public universities require applicants to list their two preferred majors when applying Example
- Helps identify demand for major, rather than observing equilibrium enrollment outcomes
- Applicants submit demographic information
Multinational Firms
Costa Rica incentivizes FDI inflows through dedicated Free Trade Zone (FTZ) regime
- Firms locate within multinational dedicated industrial parks
- Multiple locations across the country
Distance in Costa Rica
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