Biased FDI spillovers in incomplete datasets: An empirical examination

Dea Tusha; Jacob A. Jordaan

doi:10.1111/rode.12740

Biased FDI spillovers in incomplete datasets: An empirical examination

Dea Tusha^*, Jacob A. Jordaan

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

We examine biases in foreign direct investment (FDI) productivity spillovers that can arise when using incomplete datasets, by comparing estimates for Indonesia from the World Bank Enterprise Survey (WBES)—an incomplete dataset example—with estimates from the Indonesian Manufacturing Survey (MS). Furthermore, we conduct estimations on samples drawn from MS, following the sampling methodology of WBES. We find that estimates with this sampling framework are inaccurate, due to measurement error in industry-level horizontal and vertical FDI, strong presence of small firms, and small sample size. Relaxing the WBES sampling criteria and using FDI variables from MS produces substantially more reliable findings.

Original language	English
Pages (from-to)	582-600
Number of pages	19
Journal	Review of Development Economics
Volume	25
Issue number	2
DOIs	https://doi.org/10.1111/rode.12740
Publication status	Published - May 2021

Bibliographical note

Publisher Copyright:
© 2020 The Authors. Review of Development Economics published by John Wiley & Sons Ltd

Keywords

foreign direct investment
incomplete datasets
Indonesia
productivity spillovers

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1111/rode.12740Licence: CC BY

rode.12740Final published version, 210 KBLicence: CC BY

Cite this

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title = "Biased FDI spillovers in incomplete datasets: An empirical examination",

abstract = "We examine biases in foreign direct investment (FDI) productivity spillovers that can arise when using incomplete datasets, by comparing estimates for Indonesia from the World Bank Enterprise Survey (WBES)—an incomplete dataset example—with estimates from the Indonesian Manufacturing Survey (MS). Furthermore, we conduct estimations on samples drawn from MS, following the sampling methodology of WBES. We find that estimates with this sampling framework are inaccurate, due to measurement error in industry-level horizontal and vertical FDI, strong presence of small firms, and small sample size. Relaxing the WBES sampling criteria and using FDI variables from MS produces substantially more reliable findings.",

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T1 - Biased FDI spillovers in incomplete datasets

T2 - An empirical examination

AU - Tusha, Dea

AU - Jordaan, Jacob A.

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N2 - We examine biases in foreign direct investment (FDI) productivity spillovers that can arise when using incomplete datasets, by comparing estimates for Indonesia from the World Bank Enterprise Survey (WBES)—an incomplete dataset example—with estimates from the Indonesian Manufacturing Survey (MS). Furthermore, we conduct estimations on samples drawn from MS, following the sampling methodology of WBES. We find that estimates with this sampling framework are inaccurate, due to measurement error in industry-level horizontal and vertical FDI, strong presence of small firms, and small sample size. Relaxing the WBES sampling criteria and using FDI variables from MS produces substantially more reliable findings.

AB - We examine biases in foreign direct investment (FDI) productivity spillovers that can arise when using incomplete datasets, by comparing estimates for Indonesia from the World Bank Enterprise Survey (WBES)—an incomplete dataset example—with estimates from the Indonesian Manufacturing Survey (MS). Furthermore, we conduct estimations on samples drawn from MS, following the sampling methodology of WBES. We find that estimates with this sampling framework are inaccurate, due to measurement error in industry-level horizontal and vertical FDI, strong presence of small firms, and small sample size. Relaxing the WBES sampling criteria and using FDI variables from MS produces substantially more reliable findings.

KW - foreign direct investment

KW - incomplete datasets

KW - Indonesia

KW - productivity spillovers

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JO - Review of Development Economics

JF - Review of Development Economics

IS - 2

ER -

Biased FDI spillovers in incomplete datasets: An empirical examination

Abstract

Bibliographical note

Keywords

UN SDGs

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