Re‐examining the impact of sectoral‐ and industrial‐level FDI on growth: Does institutional quality, education levels and trade openness matter?

Abstract

This study examines whether institutional quality, education levels and trade openness affect the relationship between sectoral‐ and industrial‐level foreign direct investment (FDI) inflows and economic growth. Previous studies highlight the heterogeneous effects of FDI at the sectoral‐ and industrial‐level suggesting the need to examine the growth effects of FDI at a disaggregated level. However, previous studies have not empirically explored the role of absorptive capacities at the industrial‐ and sectoral‐level. Consequently, using a sample of 36 Organisation for Economic Co‐operation and Development countries from 2000 to 2019, we examine the relationship using the system generalised method of moments estimator to control for endogeneity. Our results show that the magnitudinal effects of overall FDI is dampened as sectoral‐ and industrial‐effects are not considered. We find that both manufacturing and services FDI contributes to growth. However, the effect of manufacturing FDI is greater. Meanwhile, we find education levels to be an effective moderator for services FDI, while trade openness enhances the growth effects of manufacturing FDI more effectively. Institutional quality is shown to have a positive complementary effect across both sectors and certain industries. Policy implications are discussed.

Spillover effects of FDI inflows on output growth: An analysis of aggregate and disaggregated FDI inflows of 13 MENA economies

“…This paper aims to investigate the effect of sector‐specific FDI inflows in host countries (MENA countries) on growth at both the aggregate and sectoral levels. We estimate the following dynamic model, similar to (Doytch, 2021; Doytch & Uctum, 2011, 2019; Gönel & Aksoy, 2016; Haini & Tan, 2022): where is real per capita growth output in sector k in the constant year 2010 USD {the ‘ k ’ superscript corresponds to any one of agriculture, mining, manufacturing, services sectors as well as aggregate GDP}, refers to FDI flows as a percentage of GDP {the ‘ s ’ superscript corresponds to the primary, secondary and tertiary sectors, as well as the total FDI} (according to the International Standard Industry Classification [ISIC], we categorised FDI inflows into the following economic sectors: primary [including petroleum and mining], secondary [including food, fabricated metals, chemical, electrical, industrial machinery and transportation equipment] and tertiary [comprising depository institutions (financial institutions, commonly referred to as ‘depository institutions’ in the United States) and wholesale trade]). For more detailed information regarding this classification, we recommend referring to the study conducted by Doytch et al (2015), is a vector of other variables in country i at period t , which are {IQ, investment rate, school, trade openness, natural resource rent as a share of GDP, and government spending}, denotes country‐fixed effects that capture unobservable heterogeneity across different countries in the analysis, denotes time‐fixed effects represented by year dummies that capture common shocks to a dependent variable for all countries.…”

“…Since our sample dataset is based on a sample of 13 MENA countries from 2000 to 2020, panel estimators are suitable for the study. Due to the dynamic nature of FDI and economic growth in its data‐generating process, it might be possible that endogeneity and simultaneity exist (Haini & Tan, 2022; Iamsiraroj, 2016; Li & Liu, 2005). It has been demonstrated that good institutions may promote FDI, with human capital increasing FDI in the service sector and good institutions attracting FDI in the manufacturing sector (Ahmad et al, 2018; Doytch & Eren, 2014).…”

“…More precisely, the system GMM estimator utilises lagged differences and lagged levels as simultaneous instruments, avoiding the problem of weak instruments that arise when choosing adequate instruments (Roodman, 2009). Following a number of recent empirical studies that have explored the relationship between sectoral‐level FDI and growth (Doytch & Uctum, 2011; Haini & Tan, 2022; Ingham et al, 2020), We employ the two‐step system GMM estimator approach as suggested by Roodman (2009). Using system GMM will help us to purge the FDI variables of their endogenous component (Bergougui & Murshed, 2021).…”

“…In terms of measuring IQ, empirical research on FDI and institutions offered two approaches. The first approach focuses mainly on the impact of a specific institutional aspect, such as the rule of law or corruption index on growth (Acemoglu et al, 2004, 2008; Acemoglu & Robinson, 2010; Aziz, 2022; Doytch & Uctum, 2011, 2019; Haini & Tan, 2022). The second approach examines the effect of a composite institutional indicator, primarily created by calculating the average of various institutional variables across multiple dimensions (Alfaro, 2003; Shittu et al, 2022).…”

An asymmetric nexus between clean energy, good governance, education and inward FDI in China: Do environment and technology matter? Evidence for chines provincial data

“…As a critical determinant of FDI inflows in the economy, the support and availability of skilled manpower have emerged as a motivation for foreign investors to transfer technology and operation processes in the form of capital. In terms of empirical association, a growing number of studies have posted the beneficial role of education in inducing foreign investors in the host economy [ 27 , [49] , [50] , [51] , [52] ]. For instance, Su, Jiang [ 53 ] considering the provincial data, investigated the effect of environmental investment in higher education on FDI and established positive and statistically significant linkage in the long run.…”