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The impact of EF sub-components on FDI
the disappearance of a significant impact of population
Extensive empirical literature exists on the on FDI in the European sample.
macroeconomic impact of EF and its components on FDI. Taran et al. (2016) examined the impact of EF’s factors
Studies have used multiple regression to analyze the on FDI inflow. The authors analyse the 10 EF variables
relationship between components of EF Index and FDI, in including: property freedom, business freedom, fiscal
other to conclude the research results in more detail about freedom, government spending, financial freedom,
the impact of EF on FDI. They used the following model: trade freedom, monetary freedom, investment freedom,
freedom from corruption and labor freedom. The result
shows the insignificant relation between EF and FDI
inflow in 31 European countries. Fofana (2014) compares
the influence of EF on FDI in Sub-Saharan Africa and
Western Europe. The result shows in Western Europe the
Equation (2) represents the final empirical model for size of government, monetary freedom, labor market and
selected regions where i refers to regions, β0 is a constant trade freedom are significantly boost the FDI while the
term β1, β2,…, β8 denote the coefficient parameters of market size, legal system and law are insignificant
the variables and ε is the disturbance term of region and Cabello et al. (2021) assumed equal weights for the
EFi along with the eight independent variables such different individual indicators, which was the common
as property rights, government integrity, tax burden, practice among the providers of these indexes as the
government spending, business freedom, monetary Heritage Foundation. In this paper, they focused on
freedom, trade freedom, investment freedom representing the aggregation and normalization processes used to
EF in the region and FDIi represent the dependent variable build the composite indicator, and we will make use of
for geographical region. the data of the index of EF published by the Heritage
Therefore, with the reference to the standardized Foundation. In particular, they proposed a different more
regression equation (Quazi, 2007; Subasat and Bellos, general and rich aggregation and normalization approach
2011; Taran et al. 2016), the results show EF is positively based on the Multiple Reference Point method. Rather
significant with FDI inflow in East Asia the same than just providing a ranking, the resulting composite
(Quazi, 2007). indicators will be able to show the overall and particular
However, monetary freedom reduces the FDI inflow strengths and weaknesses of the countries in terms of
in East Asia. The reason is that FDI inflow in China over a their EF enriching, therefore, the information provided
few decades is benefitted from the unfair manipulation of by other indexes of EF. Both, numerical scores and their
currency (Cardoso and Duarte, 2017). Similarly, Lily et al. correspondent graphical representation give the decision
(2014) presents long-run negative coefficient cointegration maker a full and detailed picture of the situation of
between FDI and currency in Singapore, Malaysia and the the countries, informing in addition about the relative
Philippines. The results show that constraining monetary performance of the country with respect to other countries.
freedom in East Asian countries benefits the FDI inflow. Combined Impact of EF and EF sub-components on FDI
Besides, Fofana (2014) measures the influence of EF
components on FDI in 25 Western European and 26 Sub- Over the last few decades, the EF Index has recorded
Saharan countries from 2001-2009 where he discovers that a positive relationship between EF and a range of positive
the aggregate index of EF is not a significant explanatory economic and social goals. The ideals of EF are associated
of FDI for African cases, but European countries. He with a healthier society, a cleaner environment, greater
proxies EF with three institutional variables as "the size wealth per capita, human development, democracy, and
of the economy", "the size of the population", and "the the eradication of poverty.
legal system and rule of law"; and with three regulatory Therefore, studies continue to measure the impact
variables such as "size of government", "freedom of of EF on FDI by a combination of the EF index and the
international trade", and "regulations of labor, credit, and components, based on 12 quantitative and qualitative
business". As a result, he observes that only the "legal factors, grouped into the four great categories, or
system and rule of law" variable appears significant in pillars, of EF.
the African sample, whereas it fails to be significant in the Let FDI represent the aggregate annual inflows of FDI
it
European sample. Nonetheless, he finds plausible results into country i at time t, the benchmark empirical equation
for the European sample where EF, i.e., that is proxied can be specified as:
by "size of government", "freedom of international
trade", and "regulations of labor, credit, and business",
appears statistically significant determinant of FDI. He Where in:
also explores very similar results as the African case with EF represents the overall EF index or EF
it
a fixed-effects model that includes cross-section dummy subcomponent index derived from the Fraser Institute or
variables. The only difference between cases appears as the Heritage Foundation

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