1. Binyam Afewerk Demena demena@iss.nl
MAER-Net Colloquium (11-13 September 2014)
A Meta-Analysis of FDI and Productivity Spillovers in Developing Countries
Binyam Afewerk Demena

2. The paper in a nutshell
Topic: the impact of FDI on productivity spillovers
Setting:
In 31 developing countries for the period of 1986 to 2013.
1,450 estimates taken from 69 studies carried out by 93 researchers.
Question 1: does the combined average spillovers effect adequately represent the true empirical effect size?
Question 2: why do the studies result in different answer of spillovers effect?
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3. Today’s plan Definition & motivation Literature Data & methodology
Findings
Conclusions
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4. Productivity spillovers
Domestically-owned firms benefit from the presence of foreign-owned firms.
FDI believed to transfer such benefit, i.e., productivity spillover.
This expectation is the main driver for FDI friendly regime.
Definition & motivation
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5. Productivity spillovers …
Source: Author’s own computation from collected empirical studies
Definition & motivation
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6. Literature First wave: 1980s for Mexican firms Second wave: 1990s
Cross-sectional data and industry-level spillovers
Second wave: 1990s
Panel firm-level data
Binding element: pipeline model
Third wave: 2000s
Extensively investigated the spillover effects
Towards domestic capability model
All-in-one: Focus on whether or not spillovers occur
Literature
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7. Systematic review of the literature
Search engines: Google Scholar, Econlit, Scopus & the WB database
Cut-off point: September 2013 (English literature)
Keywords: 'productivity spillover + FDI', 'productivity spillover + FDI + developing countries', 'FDI presence effect on host economy', and 'technology transfer + foreign firms'.
Exclude: literature reviews, duplicate studies, not accessable, inter-industry analysis, missing information
69 empirical studies
Data & methodology
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8. Coding I used all reported estimates.
Data extraction template designed in excel (131,325 cells manually filled) then transferred to a stata file for analysis.
Data were first coded by the Meta-Analyst himself and a research assistant checked all portion of the data (thanks to EDEM).
If the specification was not in log-level, I re-computed the effect size (thanks to Havránek T.)
Missing information or unclear methodology: I have contacted the authors, 23% (thanks to their cooperation)
Data & methodology
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9. Empirical approach
Data & methodology
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10. Empirical approach …
Data & methodology
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11. Empirical approach …
Data & methodology
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12. Empirical approach …
Data & methodology
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13. Funneling spillover estimates
Left: all studies and right: published studies
Source: Author’s own computation from collected empirical studies
Findings
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14. FAT and PET
Findings
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15. Source: Author’s own computation from collected empirical studies
Multivariate MRA
Findings
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Source: Author’s own computation from collected empirical studies
Binyam

16. Meta-effect via a Multivariate MRA
The underlying true Meta-effect estimated from the result of multivariate MRA conditional on method heterogeneity, labelled the ‘best practice’ method (e.g., see Doucouliagos and Stanley 2009, Havránek and Iršová 2011, Stanley and Doucouliagos 2012 … ).
data type, estimation a one step log-linear regression, control for sectoral fixed effect, specification controls for technological gap, & fixed effects used for spillovers estimation.
these parameters yield significant genuine spillover effect, 0.084
Findings
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17. Conclusions The study uncovers the existence publication bias.
Spillovers are economically important, but exaggerated than the actual one.
11 aspects of data, methodology, & publication characteristics influence spillovers affect.
Empirical work disregarded the argument that spillovers requires analysis of the transmission channels.
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18. Last but not least May be your reflections on the paper please? THANK
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Binyam