the effect of human capital on fdi: a meta-regression analysis
DESCRIPTION
The effect of human capital on FDI: A meta-regression analysis. Artane Rizvanolli, AAB- Riinvest University Ancona , 21 May 2010. Contents. Introduction: FDI and growth Rationale for MRA Sample MRA model Empirical results Conclusion and further research. Introduction: FDI and growth. - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/1.jpg)
The effect of human capital on FDI: A meta-regression analysis
Artane Rizvanolli, AAB-Riinvest University
Ancona, 21 May 2010
![Page 2: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/2.jpg)
Contents Introduction: FDI and growth Rationale for MRA Sample MRA model Empirical results Conclusion and further research
![Page 3: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/3.jpg)
Introduction: FDI and growth
FDI conventionally considered beneficial Technology and know-how transfer (?) Spillovers (?) Hence, overall productivity and growth (?)
Especially important for transition economies Need for restructuring and modernisation (at firm
and economy level) Limited domestic resources
However, are the benefits automatic?
![Page 4: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/4.jpg)
The rationale for meta-regression analysis (MRA)
• Theory: human capital (HC) attracts FDI – Enhancement of productivity, technology adoption
and adaption• No consensus in the empirical literature– Negative, positive and insignificant results
found• Potential reasons for the diversity of results? – Wide range of specifications, HC measures,
countries– Lack of “universal” relationship between HC
and FDI: differences in motivation for FDI, sector of economic activity, etc.
![Page 5: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/5.jpg)
The rationale for meta-regression analysis (2)
MRA as a means of Quantifying a survey of empirical literature Analysing the sensitivity of results to different
study characteristics (!) Identifying and quantifying the “genuine” effect of
HC, if present Identifying publication bias (?) Informing the specification of further research on
the HC-FDI relationship: which measures?
![Page 6: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/6.jpg)
Sample Around 30 regression analyses identified
EconLit, SSRN, Google Scholar References in papers
Some excluded Measures not convincing/comparable No results reported Only interaction/squared terms
Preferred regressions only (?)
![Page 7: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/7.jpg)
Sample (2) 28 studies with a total of 231 regressions
t-stats range -7.8 - 7.7, with a mean of 0.93
Structure: Developing, transition, mixed, China, developed Mostly secondary and tertiary education measures Majority(static and dynamic) panels
![Page 8: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/8.jpg)
Model Linear regression: weighted to give
each study the same weight, clustered robust (cluster: study), dependent variables divided by SEpcc
Dependent variable: t-statistic of HC variableModerator variable
Description
Constant Provides an estimate of publication bias (bias across the whole range of results in the literature)
1/SEpcc SE of the PCC (standardised measure of association) – a precision measure; provides an estimate of the “true” effect in the literature in terms of the PCC
FDIFLOW Flow measures for FDI used
FDIREL FDI measured relative to population/GDP
HCFLOW Flow measures for FDI (enrolment, decision to invest)
![Page 9: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/9.jpg)
Model (2)
Moderator variable
Description
LITERACY , PRIMARY, TERTIARY, SECTER, AVGYRED
HC measure: Literacy/illiteracy rate, primary education, tertiary education, secondary and tertiary combined, average yrs of education (RC: secondary education)
PANEL, DYNAMIC P., QUALITYDV
Static panel, dynamic panel, quality dependent variable model (RC: cross-section)
DEVELOPED, TRANSITION, MIXED, CHINA
Sample according to group of countries (RC: Developing countries)
HCCOST If model controls for HC cost
HCPROD If model controls for HC productivity
PUBYR Year of publication (working paper)
MEDIANYR Median year of the period covered in the study
NOEXPVAR Number of explanatory variables in the model (includes FEM dummies)
ENDOGENEITY If attempts were made to address endogeneity
![Page 10: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/10.jpg)
Preliminary results
• Bi-variate MRA– no publication bias OR “genuine effect”
• Multi-variate MRA– Same result as above– Full model mis-specified
– Ramsey RESET test : F(3, 205) = 94.52 , Prob > F = 0.0000
– Suffers from multicollinearity
Dependent variable
Coefficient
t-statistic p-value
Con 0.60 0.99 0.33
INVSEEpcc 0.04 1.28 0.31
![Page 11: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/11.jpg)
Preliminary results (2) Testing down: standard procedure in MRA
Improves functional form Significantly reduces multicollinearity
Some variables highly correlated with INVSEPCC (PERIOD, MEDIANYR, LABCOST, TNOEXPVAR?, EDNOGENITY?, HCSTOCK?)
![Page 12: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/12.jpg)
Preliminary results (3)Variable Coefficient p-value
Constant -0.014 0.96
INVSEEpcc -0.002 0.96
CROSS 0.127 0.19
QUALDV 0.228 0.00
MIXED 0.091 0.01
DEVELOPED 0.152 0.05
TRANSITION 0.113 0.10
CHINA 0.143 0.00
AVGYRED 0.081 0.13
TERTIARY -0.029 0.41
LABPROD 0.043 0.27
PRIMARY -0.027 0.60
DYNAMIC 0.003 0.89
FDIREL -0.044 0.25
![Page 13: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/13.jpg)
Conclusion and further research
Heterogeneity in HC-FDI literature can be explained to a very limited extent (!)
Appears to be no genuine effect in the literature: Models not specified correctly?
Further research: specify model in accordance with theory human capital variable: level and stock/flow
![Page 14: The effect of human capital on FDI: A meta-regression analysis](https://reader035.vdocument.in/reader035/viewer/2022062218/56815acb550346895dc89dcc/html5/thumbnails/14.jpg)
Thank you!
Questions & Comments?