investment climate assessment for apec...

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2017/SOM1/IEG/016 Agenda Item: 7.1

Investment Climate Assessment for APEC Economies

Purpose: Information

Submitted by: APEC Business Advisory Council

First Investment Experts’ Group Meeting Nha Trang, Viet Nam 23-24 February 2017

Investment Climate Assessment for

APEC Economies

February 2017

Regional Investment Analytical Group

Investment Climate Assessment Framework for APEC economies

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Contents

Introduction ............................................................................................................................................... 3

Overview of the FDI in the APEC region..................................................................................................... 3

The FDI Inflow Performance ...................................................................................................................... 5

Econometric analysis of inward FDI determinants .................................................................................... 6

Conclusion .................................................................................................................................................. 9

Appendix .................................................................................................................................................. 14

Definitions of WEF’s 12 Global Competitiveness Pillars ...................................................................... 14

References ............................................................................................................................................... 15


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Introduction

This report presents a brief review of the recent FDI trends in the APEC region relevant to

RIAG’s work on using publicly available indicators for FDI analysis and econometric modelling

of inward FDI stock drawing on data sourced from UNCTAD, the World Economic Forum,

World Bank, OECD and other sources. The analysis show that FDI flows into the APEC region

increased between 2014 and 2015. However, recent reports by UNCTAD indicate that FDI

flows declined in 2016. It includes commentary on the most recent ratings under RIAG’s

investment performance indicators and as analysis of inward FDI determinants and comments

on the OECD’s FDI Restrictiveness Index.

The results of econometric estimations show that financial market development, higher

education and training, infrastructure, market size and FDI restrictiveness index are (not

surprisingly) statistically significant determinants of inward FDI.

Overall, high level results of the econometric modelling show that economies within the APEC

region should work towards developing domestic financial markets, enhancing human capital,

increasing investment in infrastructure and reducing unnecessary regulatory burdens on

foreign investment to increase FDI inflows.

Overview of the FDI in the APEC region

Table 1 below shows trends in investment flows for APEC economies as a percentage of GDP

from 2000 to 2015. The APEC region as a whole (Table 2) shows a continuation of the FDI

growth trend, a percentage of global world FDI, despite increased uncertainty in the economic

environment globally. Several APEC economies including Australia, Brunei Darussalam,

Indonesia, Japan, Korea, New Zealand, Peru, Philippines, Russian Federation and Thailand

experienced reductions, whereas Canada, Hong Kong China, Malaysia, Mexico, Singapore,

United States and Viet Nam improved between 2014 and 2015. According to UNCTAD’s Global

Trends Investment Monitor1 FDI flows fell in developing Asia and Oceania and Latin America

and the Caribbean in 2016.

Compared to inflows, FDI outflows increased in Brunei Darussalam, Canada, Chile, Japan,

Mexico, PNG, Chinese Taipei, and Thailand. Hong Kong China showed substantial reduction

from 57% to 18% of GDP, and Singapore a slight reduction from 13.5% to 12.3% of GDP

between 2014 and 2015. It is interesting to note that some developing APEC economies are

experiencing more outflows compared to inflows.

As a region, in 2015, APEC was the second largest recipient of global FDI flows, attracting 54.1

per cent of the total FDI, a rise from 52.1 per cent in 2014. This was roughly in line with

APEC’s share of world GDP (Table 2).

1 UNCTAD’s Global Trends Investment Monitor 2016 (No 25)


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Table 1: FDI Inflow and Outflow as % of GDP 200-2015

2000 2010 2014 2015

Infl

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Australia 3.5 0.7 2.8 1.5 3.5 0.0 1.7 -1.3

Brunei Darussalam 9.2 0.5 3.9 0.0 3.8 0.0 1.1 3.3

Canada 9.0 6.0 1.8 2.2 3.0 2.9 3.1 4.6

Chile 6.3 5.2 7.7 4.8 8.9 5.0 8.4 6.5

China 3.4 0.1 1.9 1.2 1.3 1.2 1.2 1.1

Hong Kong, China 31.8 31.5 30.9 37.7 35.8 49.4 57.0 18.00

Indonesia - - 1.9 0.4 2.7 0.8 1.9 0.7

Japan 0.2 0.7 0.0 1.0 0.0 2.5 -0.1 3.2

Korea 2.0 0.9 0.9 2.6 0.7 2.2 0.4 2.0

Malaysia 3.9 2.1 3.7 5.4 3.3 5.0 3.8 3.4

Mexico 2.8 0.1 2.5 1.4 1.8 0.4 2.7 0.7

New Zealand 2.5 1.1 0.7 0.5 1.7 0.0 -0.6 0.1

Papua New Guinea 2.8 0.0 0.3 0.0 -0.2 0.0 -0.2 1.0

Peru 1.6 0.0 5.7 0.2 3.8 0.0 3.6 0.1

Philippines 2.8 0.2 0.7 0.3 2.2 2.5 1.8 1.9

Russian Federation 1.0 1.2 2.8 3.5 1.1 3.0 0.8 2.1

Singapore 16.5 7.1 23.6 14.3 22.4 13.5 22.7 12.3

Chinese Taipei 1.5 2.0 0.6 2.6 0.5 2.4 0.5 2.9

Thailand 2.7 0.0 2.7 1.3 3.1 1.9 2.8 2.0

United States 3.0 1.4 1.3 1.8 0.5 1.9 2.1 1.7

Viet Nam 4.1 0.0 6.9 0.8 4.9 0.6 6.1 0.6

Source: UNCTAD (2016)

Multinational Enterprises (MNE) from Japan, Korea, China, Hong Kong China, and Chinese

Taipei have a significant presence in other Asian APEC members, while United States and

Canadian MNEs are heavily invested in the NAFTA subregion. Taken together, these MNEs are

contributing to a wide production network and to inter- and intraregional value chains across

the Pacific (UNCTAD, 2016). Compared to APEC, other groupings, ASEAN, ASEAN+3 and

COMESA experienced falls in investment flows during this period, while the G20, NAFTA and

OECD groupings improved from 2014 to 2015 (Table 2).


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Table 2: Total FDI Inflow (% of total world FDI)

Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

APEC 34.6 42.0 40.1 53.7 41.4 49.0 48.0 48.9 57.0 52.4 54.1

ASEAN 4.7 4.6 4.6 3.4 3.9 7.9 6.0 7.7 8.6 9.8 7.1

ASEAN + 14.2 10.0 10.7 13.0 13.7 17.2 14.4 17.1 18.1 20.7 15.0

COMESA 1.1 1.2 1.3 1.4 1.4 1.3 0.5 1.4 1.0 1.4 1.1

G20 63.0 58.7 57.3 65.1 55.3 56.1 56.4 51.1 60.9 51.0 52.6

NAFTA 16.7 22.9 19.5 26.6 15.5 19.0 18.7 16.2 23.6 14.9 26.0

OECD 65.3 68.8 69.2 55.6 58.4 54.6 55.4 51.6 51.9 44.7 57.6

Source: UNCTAD (2016)

The FDI Inflow Performance

The APEC FDI inflow performance indicator (first published by RIAG in 2016) – Table 3

compares each economy’s share of FDI in global FDI inflow and its relative GDP share in global

GDP. The ratio of these shares equal to one, indicates that the economy attracts the same

amount of FDI as its contribution to the world GDP. A value greater than one indicates a larger

share of FDI relative to GDP; a value less than one indicates a smaller share of FDI relative to

GDP. These values are normalised to render them comparable over longer periods. Hong

Kong China and Singapore were excluded as their shares of FDI (and trade) are much higher

than other APEC economies and their extreme values may influence subsequent steps in

analysis. Accordingly, the highest ratings are assigned for Hong Kong China and Singapore

without including them in the calculations.

Table 3 shows that twelve economies retained their positions while Malaysia, Mexico,

Thailand and United States improved. Australia, Brunei Darussalam, China and New Zealand

showed reversals, perhaps reflecting a subdued global economic performance.

Table 3: Inward FDI Rating of APEC Economies, 1989-2015

1989-

1995

1996-

2000

2001-

2005

2006-

2010 2011 2012 2013 2014 2015

Change

2014-2015

Australia B C B A A A B B C

Brunei Darussalam C A A B A A A A C

Canada C B B A B B B A A

Chile B A A A A A A A A

China A A A C C C C B C

Hong Kong, China A A A A A A A A A

Indonesia C D D C B B C B B

Japan D D D D D D D D D

Korea, Rep. D D C D D D D D D

Malaysia A A B B B B A B A

Mexico C C B B C C B C B


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New Zealand A B C C B C D B D

Papua New Guinea A B C C D D D D D

Peru B B B A A A A A A

Philippines B C D D D C C C B

Russian Federation D D C B B B B C C

Singapore A A A A A A A A A

Chinese Taipei D D D D D D D D D

Thailand B B A B C B B C B

United States D C D D C D C D B

Viet Nam A A A A A A A A A

Source: RIAG(2016)

Econometric analysis of inward FDI determinants

There is a consensus that foreign direct investment (FDI) produces economic benefits

including spill over effects to the recipient countries by providing capital, technology, access

to foreign markets, increasing competitiveness, assists human capital development,

contributes to global value chains and to enterprise development.

Dunning (1993) argues that issues related to the determinants of FDI are multidimensional,

because different types of motives work behind the decision to invest in foreign countries by

multinational corporations (MNCs). For example, some seek to benefit through investment in

a large foreign market (market seeking FDI), and some seek assured access to the supply of

natural resources (resource seeking FDI). Some relocate their plants to other countries to

reduce production costs and to link to the global market more strongly (efficiency seeking

FDI). Assuncao (2011) and Blonigen (2005) provide a literature review of the FDI determinants

based on various theories.

The econometric modelling supporting the analysis in this section of the report is shown in

the Attachment to this paper.

Other data that contributes to an understanding of factors impacting on investment inflows

to APEC economies draws on panel data covering the period from 2006 to 2015 for 20 APEC

economies and sourced from the WEF Global Competitiveness Report, UNCTAD and the OECD

(PNG data was not available). (A note on the WEF Global Competitiveness Pillars are shown in

the Appendix to this report.)

Figures 1 and 2 below provide an overview of Global competiveness pillars for developed and

developing APEC economies. Figure 1 shows that infrastructure, market size and financial

market development and institutional factors (mainly the FDI policy framework, including

screening) impact adversely on competitiveness in some developed APEC economies.


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Figure 1: Global Competiveness Pillars for Developed APEC economies 2015

Figure 2: Global Competiveness Pillars for Developing APEC economies 2015

Source: WEF (2016)

0

1

2

3

4

5

6

7Market size

Business sophistication

Innovation

Institutions

Infrastructure

Macroeconomicenvironment

Health and primaryeducation

Higher education andtraining

Goods marketefficiency

Labor marketefficiency

Financial marketdevelopment

Technologicalreadiness

AUS CAN HKG JPN

KOR NZL SGP USA

0

1

2

3

4

5

6

7Market size

Business sophistication

Innovation

Institutions

Infrastructure

Macroeconomicenvironment

Health and primaryeducation

Higher education andtraining

Goods market efficiency

Labor market efficiency

Financial marketdevelopment

Technological readiness

CHL CHN IDN MYS MEXPER PHL RUS THA VNM


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Global competiveness pillars for developing economies show a somewhat different picture.

Overall innovation, higher education and training and technological readiness are key factors

impacting on competitiveness in developing APEC economies. This suggests that factors

contributing to weaknesses in competitiveness could be addressed, in part at least, through

investment policies aimed at enhancing competitiveness.

FDI regulations and their applications are a determinant of a country’s attractiveness to

foreign investors. According to OECD (2016), FDI restrictions tend be prominent mostly in

primary sectors such as mining, fishing and agriculture, but also in media and transport.

Figure 3 presents the data from the OECD database. It indicates that Japan and Chile are the

least restrictive economies (lower than OECD average), while Philippines, China and Indonesia

are the most restrictive in the APEC region (on a scale of 0 to 1, restrictive economy).

Figure 3: OECD FDI Restrictiveness Index 2015

Source: OECD (2016)

The FDI Restrictiveness Index was available for 14 economies of APEC; the exceptions are

Brunei Darussalam, Hong Kong China, PNG, Singapore, Chinese Taipei, Thailand and Viet

Nam.

Table 4 in the Attachments provides correlation statistics for Inward FDI stock and its

determinants over 2006 and 2015 period. According to column 2 of Table 4 of the

Attachments, correlation between FDI inward stock and other variables are highly statistically

significant except macroeconomic environment and market size. The correlation statistics also

reveal negative correlation between inward FDI stock and FDI regulatory environment

(restrictiveness).

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

Primary Secondary Tertiary Total FDI Restrictiveness Index (right axis)


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The results of the econometric estimates both without cross section weights and with cross

section weights are provided in Table 5 of the Attachments. They indicate statistically positive

relationship between inward FDI Stock and financial market development, higher education,

infrastructure and market size. Interestingly we find statistically significant estimates between

the goods market efficiency and inward FDI stock with negative sign. This might indicate that

some potential investors in foreign markets are deterred because there are relatively high

levels of competition in the markets of interest.

The econometric estimates with the FDI restrictiveness index indicate statistical significance

at 5% level with a negative sign in the model with cross-section weights but not in the model

without cress-section weights. Nevertheless, both estimations resulted in a negative sign.

Overall, the results of the econometric modelling suggest that APEC economies region should

work towards developing domestic financial markets, increasing human capital, building

infrastructure and reducing unnecessary regulatory burdens on foreign investment to ensure

high level of FDI inflows. However, due to the aggregate nature of the econometric model,

the results provide very high-level indications on what countries might want to do to attract

specific types of FDI. Future research would also be required to compare effects of FDI

determinants on other regions vis-à-vis APEC.

Conclusion

This report provides a brief review of the recent FDI trends in the APEC region. The analysis

show that FDI flows into the APEC region has increased between 2014 and 2015 but the

composition of contributions by economies has changed. Early reports by UNCTAD indicate

that FDI flows have declined in 2016 perhaps due to changing regulatory environment globally

with signs of protectionist measures, increasing cost of investment and concerns about

setbacks in the negotiation of the TPP. These developments will likely cause disruptions to the

FDI flows further both worldwide and within the APEC region. These developments suggest

that APEC should elevate its focus in investment flows and desirable policy objectives. In

particular, a more focused approach towards developing domestic financial market,

increasing human capital, building infrastructure and reducing unnecessary foreign

investment regulatory burden may facilitate attracting productive FDI flows into APEC

economies.


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ATTACHMENT

AN ECONOMETRIC APPROACH TO INWARD FDI DETERMINANTS

The baseline fixed effects econometric model is defined as follows:

𝑦𝑖,𝑡 = 𝛽′𝑿𝑖,𝑡 +∝𝑖+ 𝜀𝑖,𝑡

where i denotes the individual economy, and t denotes time (year). y is the natural logarithm

of inward FDI stock in economy i at time t, and X includes explanatory variables in natural

logarithms such as business sophistication, financial market development, goods market

efficiency, Health and primary education, Higher education and training, infrastructure,

innovation, institutions, labour market efficiency, macroeconomic environment, market size

and technological readiness. α is an economy-specific fixed effect, and ɛ is the error term,

assumed independently and identically distributed (Normal distribution).

In order to ensure that causality goes in the right direction we employ lags of the explanatory

variables in the model. The intuition is that the inward FDI stock in the current period is based

on the information from previous years. Moreover, employing lags in the estimation also

mitigates against the possibility of reverse causality or endogeneity. We also allow for

heteroscedasticity of the effects among cross – sections by employing GLS cross section

weights to account for varying degree of effects on the basis of different levels of economic

development.

Definitions and descriptive statistics for each variable are provided in Table 6. Data for the

dependent variable (FDI Inward Stock) was obtained from UNCTAD Statistics database.

Independent variables were sourced from WEF global competitiveness database for 2006-

2015.


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Table 4: Correlation between Inward FDI Stock and its determinants

FDISTOCK BUSOFST FIN GOODMKT HEALTH EDU HIGHEDU INFSTR INNOV INST LBOUR MACRO

MKT SIZE TECH RESTRICT

FDISTOCK 1.00

BUSOFST 0.28*** 1.00

FIN 0.64*** 0.62*** 1.00

GOODMKT 0.53*** 0.82*** 0.87*** 1.00

HEALTHEDU 0.57*** 0.60** 0.53*** 0.68*** 1.00

HIGHEDU 0.69*** 0.68*** 0.63*** 0.74*** 0.82*** 1.00

INFSTR 0.54*** 0.76*** 0.53*** 0.72*** 0.81*** 0.88*** 1.00

INNOV 0.38*** 0.92*** 0.51*** 0.74*** 0.72*** 0.82*** 0.89*** 1.00

INST 0.67*** 0.68*** 0.85*** 0.90*** 0.76*** 0.77*** 0.71*** 0.66*** 1.00

LBOUR 0.59*** 0.66*** 0.70*** 0.76*** 0.58*** 0.71*** 0.67*** 0.70*** 0.75*** 1.00

MACRO -0.02 -0.41*** -0.16* -0.14 -0.03 -0.11 -0.09 -0.29*** -0.10 -0.27*** 1.00

MKTSIZE -0.10 0.31*** -0.27*** -0.08 0.14 0.13 0.35*** 0.48*** -0.14 0.18** -0.17* 1.00

TECH 0.66*** 0.73*** 0.63*** 0.74*** 0.78*** 0.96*** 0.90*** 0.83*** 0.75*** 0.65*** -0.15* 0.13 1.00

RESTRICT -0.28*** -0.34*** -0.27*** -0.31*** -0.22** -0.41*** -0.45*** -0.35*** -0.25*** -0.35*** 0.27*** 0.02 -0.51*** 1.00 *, ** and *** represents the level of significance at 10, 5 and 1 percent levels, respectively

Note: See the appendix for the definitions of variables


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Table 5: Econometric estimates for APEC Inward FDI Stock

Without Cross-section weights With Cross-section weights

Variable Coefficient Coefficient Coefficient Coefficient

C 2.58 -1.30 1.32 -2.34

st.error 1.78 2.57 1.27 2.09

LOG(BUSOFST(t-1)) -1.09 -0.54 -0.61 -0.10

st.error 0.93 1.17 0.78 0.95

LOG(FIN(t-1)) 1.07*** 1.18** 0.47 0.76**

st.error 0.39 0.47 0.31 0.38

LOG(GOODMKT(t-1)) -1.69** -3.56*** -1.11* -2.44***

st.error 0.71 0.95 0.60 0.78

LOG(HEALTHEDU(t-1)) -0.03 0.16 0.25 0.52

st.error 0.66 0.81 0.50 0.61

LOG(HIGHEDU(t-1)) 2.78*** 2.37** 2.28*** 2.44***

st.error 0.85 1.11 0.66 0.92

LOG(INFSTR(t-1)) 0.68** 0.61 0.99*** 1.04***

st.error 0.31 0.41 0.25 0.35

LOG(INNOV(t-1)) 0.59 0.86 -0.30 -0.35

st.error 0.60 0.72 0.47 0.61

LOG(INST(t-1)) -1.36*** -0.80 -0.67* -0.40

st.error 0.51 0.64 0.38 0.50

LOG(LBOUR(t-1)) 0.20 1.21* -0.03 0.86

st.error 0.50 0.66 0.44 0.55

LOG(MACRO(t-1)) 0.08 0.39 0.13 0.41

st.error 0.26 0.32 0.21 0.29

LOG(MKTSIZE(t-1)) 2.16*** 3.72*** 2.44*** 3.24***

st.error 0.81 1.24 0.55 1.01

LOG(TECH(t-1)) 0.32 0.07 0.56 0.02

st.error 0.41 0.58 0.34 0.48

LOG(RESTRICT(t-1))

-0.12

-0.32**

st.error

0.17

0.13

ADJ R^2 0.987 0.984 0.995 0.989 Note: *,**,*** stands for significance at 10%, 5%, 1% levels Source: Author’s estimations


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Table 6: Descriptive Statistics for Inward FDI Determinants

FDISTOCK BUSOFST FIN GOODMKT HEALTHEDU HIGHEDU INFSTR

Mean 7044.45 4.63 4.67 4.68 5.97 4.81 4.71

Median 2855.66 4.61 4.65 4.75 6.06 4.78 4.74

Maximum 31318.83 5.92 6.08 5.56 6.82 5.87 6.21

Minimum 193.10 3.31 3.03 3.58 5.07 3.62 2.53

Std. Dev. 8182.15 0.61 0.73 0.49 0.45 0.68 1.04

Skewness 1.29 0.31 -0.13 -0.25 -0.17 -0.07 -0.41

Kurtosis 3.48 2.58 2.16 2.01 1.91 1.52 1.99

INNOV INST LBOUR MACRO MKTSIZE TECH RESTRICT

Mean 4.08 4.45 4.65 5.31 5.32 4.40 0.20

Median 3.94 4.60 4.63 5.35 5.36 4.28 0.18

Maximum 5.84 6.09 5.80 6.58 6.98 5.90 0.45

Minimum 2.68 2.95 3.71 3.64 3.69 2.79 0.05

Std. Dev. 0.90 0.88 0.51 0.65 0.87 0.97 0.12

Skewness 0.30 0.06 0.14 -0.44 0.24 0.01 0.60

Kurtosis 2.03 1.75 2.18 2.93 2.35 1.49 2.24


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Appendix

Definitions of WEF’s 12 Global Competitiveness Pillars

1. Institutions. These collective bodies and structures comprise the legal and administrative

environment in which individuals, firms and governments interact to generate wealth. Simply stated,

investors need to believe the marketplace is fair and that their investments are going to be protected.

2. Infrastructure. Roads, transportation and reliable utilities are crucial to facilitating the sale,

purchase and transporting of goods and services.

3. Macroeconomic environment. Healthy competition requires a stable economy with a reasonably

stable monetary unit. Businesses find it challenging to operate efficiently during periods of high

inflation.

4. Health and primary education. Basic healthcare and education are critical to a trainable,

sustainable workforce with low absenteeism and the skills to perform more than just rudimentary

manual labour.

5. Higher education and training. Economies that want to move beyond simple production and

products need to provide a way for workers to adapt and continuously improve their skills. Otherwise,

they are forced to import skills.

6. Goods market efficiency. Healthy competition – both domestic and foreign – encourages the

efficient production of the right goods in the right quantities at a fair price.

7. Labour market efficiency. A healthy labour market that allows workers to be employed at their

highest and best use enhances quality and productivity.

8. Financial market development. An efficient financial sector weighs risks and allocates resources to

those entrepreneurial or investment projects with the highest expected rates of return, rather than to

the politically connected.

9. Technological readiness. A competitive economy needs to provide access to existing and emerging

technologies or risk falling behind other countries with those capabilities.

10. Market size. Economies of scale can make a big difference in pricing and productivity.

11. Business sophistication. The most competitive economies are those with the most networked and

advanced operations and strategies.

12. Innovation. Beyond technological readiness, a competitive economy must nurture original

thought, leading to the creation of new technologies, new applications, and new processes and

procedures.


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References

Assuncao, S., Forte, R., Teixeira, A. (2011) Location Determinants of FDI: a Literature Review, FEP

Working Paper, no. 433.

Blonigen, B.A (2005) A Review of the Empirical Literature on FDI Determinants, Working Paper,

University of Oregon

Centre for International Development, Harvard University (2015). The Observatory of

Economic Complexity, Available at: http://atlas.media.mit.edu/en/

Dunning, J. H. (1993). Multinational enterprises and the global economy. Wokingham,

Berkshire: Addison Wesley

fDiMarkets (2016) Foreign Direct Investment Database, Financial Times, Available at:

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www.unctad.org/en/PublicationsLibrary/wir2015_en.pdf

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http://www.doingbusiness.org/data/exploretopics/resolving-insolvency

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2016.pdf

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http://unctad.org/en/Pages/Statistics.aspx

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