Potential for Inward Foreign Direct Investment in Japan †Takeo Hoshi
Stanford University, National Bureau of Economic Research,
and Asian Bureau of Finance and Economic Research
Kozo Kiyota
Keio University, University of Hawaii,
and Research Institute of Economy, Trade and Industry

July 5, 2018
Last Revision: March 13, 2019
Abstract
Promotion of inward foreign direct investment (FDI) into Japan has been an important policy in
the Abenomics growth strategy. This paper examines if we observe positive impacts of thepolicy in the data. We first estimate a gravity model of bilateral FDIs using data for 35 OECD
countries as destination countries. In estimating the model, we handle zero values for FDI stock
explicitly. The model includes (origin and destination) country-specific effects as well as
destination-country specific time trends. We take the model prediction as a reasonablecounterfactual and compare that to the actual inward FDI stock for Japan. Although the actual
inward FDI stock has been growing and is likely to achieve the goal of 35 trillion yen by 2020,
the growth under the Abe administration has been comparable to or slightly lower than the
counterfactual suggested by the estimated model. We also estimate the model without Japan as adestination country and use the estimated model to calculate the counterfactual level of Japan’s
inward FDI. Although we expect the gap between the counterfactual and the actual become
narrower if Abenomics policy has been successful, we fail to find that. These results cast a
doubt on the effectiveness of the Abenomics policies to encourage inward FDI at least as of2015.

Keywords: Inward foreign direct investment; Gravity model; Abenomics
JEL Classification: F14, F21, F23†

We benefited from useful discussion with Kenta Yamanouchi. We also thank Shin-ichi Fukuda, Keith Head,Tomohiko Inui, Hirokazu Ishise, Banri Ito, Keiko Ito, Tadashi Ito, Masayuki Kudamatsu, Hiroshi Mukunoki,Takeshi Murooka, Naoto Jinji, Ayumu Tanaka, Yasuyuki Todo, an anonymous referee and participants at the 2018spring meeting of the Japan Society of International Economics, TRIO Conference and seminars at Osaka
University and Gakushuin University. Kozo Kiyota gratefully acknowledges financial support from the Japan
Society for the Promotion of Science (JSPS), Grant-in-Aid (JP16H02018, JP18H03637). All remining errors are our
own.

1.

Introduction

An important motivation for corporations to expand into foreign countries is to use theiradvantage over the competitors in the host countries. Thus, foreign companies often have higher
productivities than domestic companies. 1 From host country’s point of view, allowing more
foreign direct investment (FDI) may lead to higher economic growth through productivity
spillovers from foreign companies, which would ultimately increase social welfare. 2
The benefit of increasing inward FDI for Japan may be especially large because Japan
has been known for its very low level of inward FDI compared with other advanced economies.
Table 1 presents the inward FDI stock to gross domestic product (GDP) ratio for 35 Organization
for Economic Co-operation and Development (OECD) countries from 1985 to 2015. 3 The tableindicates that the inward FDI stock to GDP ratio for Japan is 4.2 percent in 2015, far below theOECD average of 50.4 percent and the smallest among all the OECD countries.
=== Table 1 ===Recently Japan has tried to promote inward FDI to enhance its potential growth.
Promotion of inward FDI has been an important goal of the growth strategy under Abenomics.
Since 2013, the Abe administration pursued the goal of increasing its inward FDI stock to 35
trillion yen (up from 19.2 trillion yen at the end of 2012) by 2020. Figure 1 plots the inward FDI
stock for Japan from 1996 to 2017. By the end of 2017, Japan’s inward FDI stock rose to 28.6
trillion yen. At this rate, the goal of 35 trillion yen will be easily reached by 2020. As Hoshi(2018) argues, however, Abenomics does not seem to have changed the long-run trend of Japan’s
inward FDI. The increase of inward FDI under Abenomics is almost exactly what the past trend
would have predicted. Thus, Hoshi (2018) concludes that there is no evidence that the
Abenomics policy to promote inward FDI has been effective.
=== Figure 1 ===This paper also examines Japan’s inward FDI under Abenomics, but goes beyond Hoshi(2018) by using more carefully constructed counterfactual than a simple extrapolation of the pasttrend. We estimate gravity models of FDI stock and use those to infer how Japan’s inward FDI
stock would have evolved in the absence of Abenomics policies. We implement two slightly
different approaches.
1

Several studies found that the productivity of foreign companies is, on average, higher than that of domestic
companies. See, for example, Doms and Jensen (1998) for the case of the United States and Kimura and Kiyota(2007) for the case of Japan.
2
A number of studies found that knowledge brought by multinational firms spills over to domestic industries andincrease their productivity. See, for example, Javorcik (2004) for the case of Lithuania and Todo (2006) for the caseof Japan. Similarly, Fukao, Ito, Kwon, and Takizawa (2008) found that the acquisition by foreign firms improved
target firms’ productivity and profitability significantly more and quicker than the acquisitions by domestic firms inJapan.
3
The list of countries and their abbreviations are presented in Table 3. For Japan, year 1995 data are missing in theOECD International Direct Investment Statistics database. Tables A1 and A2 presents the inward FDI stocks and
GDP to compute Table 1. Table A3 presents the inward FDI flows. Section 2 presents a more detailed description of
the data.

1

In the first approach, we estimate a model that assumes country fixed effects. We start by
estimating the gravity model of inward FDI stocks for OECD countries from 1985 to 2012,noting that Abenomics was started in December 2012. 4 Then, we use the estimated model topredict inward FDI stock for Japan after 2013. We interpret the predicted values to be theinward FDI stocks that would have been observed if the Abenomics had not started its promotionof inward FDI. If the Abenomics policy of promoting inward FDI was effective overall, we
would expect to find that the total inward FDI in Abenomics years exceeds the predicted values.
In the second approach, we exclude Japan as a destination country in estimating a gravity
model. We then use the estimated model to calculate what Japan’s inward FDI stock would be.
We examine the gap between the counterfactual calculated in this way and the actual inward FDI
to Japan. If Abenomics policy has been successful, we should find the gap has narrowed underthe Abe administration.
Both of these analyses look for the changes in Japan’s inward FDI after 2013 that cannot
be explained by GDPs and other observables in the gravity model. These unexplained changes
would certainly include the impacts of the Abenomics policy to promote inward FDI, but they
may reflect many other factors that are not related to Abenomics. Thus, it is possible that weoverestimate or underestimate the impacts of Abenomics policy, depending on what kind offactors that we are missing. This is a weakness of our approach.
Our paper adds to the growing literature on inward FDI into Japan. Several studies
examined the determinants of inward FDI to Japan. 5 Kimino, Saal, and Driffield (2007) lookedat FDI flows from 17 countries to Japan between 1989 and 2002. They found that source
country characteristics such as political and economic stability were important determinants ofinward FDI to Japan while exchange rates and labor costs were not.
Sato and Oki (2012) studied the distribution of US outward FDI from 1990 to 2009.
They estimated a log-linear version of gravity model and found that the US FDI to Japan was
low compared with other destination countries even after controlling for gravity variables such as
the market sizes of the destination countries. They concluded that Japan was less attractive for
the US investors than other countries, although they did not explore what made Japan lessattractive.
Head and Ries (2005) also estimate the gravity model for Japan’s FDI, but they put thaton a solid theoretical ground. Based on the framework developed by Head and Ries (2008), they
estimate a gravity model of FDI using the data for 181 countries from 1980 to 2002. Theirresults indicate that both inward and outward FDI shares of Japan is lower than the prediction of
the model.

4

The gravity model is used not only to explain the patters of bilateral trade but also those of bilateral FDI. See,
Anderson (2011) and Head and Mayer (2015), for a literature review. Román, Bengoa, and Sánchez-Roble (2016) isa recent example of estimating the gravity model of FDI.
5
For the earlier literature on inward FDI in Japan, see Yoshitomi and Graham (1996).

2

Our paper builds on these previous studies and asks if the low level of inward FDI stockin Japan has changed under Abenomics. The paper also introduces a methodologicalimprovement on the previous studies, many of which estimated a log linear form of the gravity
model. A problem is that many country pairs have no FDI between them. The previous studies
usually dealt with this problem by dropping the country pairs with zero FDI. Throwing away theobservations with zero FDI, however, leads to inconsistent parameter estimates. To solve thisproblem, we employ Pseudo-Poisson Maximum Likelihood model proposed by Santos Silva andTenreyro (2006). In addition to the explicit treatment of zero FDI, our study covers a longer andmore recent period than the previous studies.
The paper is organized as follows. The next section provides a brief overview of thepolicies to promote inward FDI to Japan under Abenomics. We argue that success of any of
those policies is likely to show up as a structural shift of the relation between Japan’s inward FDI
and its standard determinants in a gravity model such as distances and sizes of the origin
countries. Section 3 introduces gravity models of FDI and the estimation method that we use inthis paper. The section also goes over the two approaches we use to examine the effectiveness ofthe FDI promotion under Abenomics. Section 4 describes the dataset we use and reportssummary statistics. Section 5 reports the estimation results and discusses if the Abenomics FDI
promotion policy has been successful. Section 6 concludes.

2.

Inward FDI Promotion under Abenomics

Promotion of inward FDI has been a prominent part of the growth strategy of the Abeadministration (aka the third arrow of Abenomics) from the start. The original growth strategy
published in June 2013 stated:
The government will develop an environment where all companies and human resources
enjoy the benefits of global economy and facilitate full-fledged globalization in Japan inorder to attract outstanding overseas manpower and technologies to Japan and to create
employment and innovation. It will also aim to double inward FDI stocks to 35 trillion yen
in 2020 (17.8 trillion yen at the end of 2012). (Headquarters for Japan’s Economic
Revitalization 2013, p.137)
The growth strategy has been revised every year since then, but the latest one that was
published in June 2018 still includes promotion of inward FDI as one of the important policies.
The Japanese government website dedicated for Abenomics(https://www.japan.go.jp/abenomics/, accessed July 3, 2018) features “Improve businessenvironment to drive inward FDI” as one of the four main goals of Abenomics. 6
From the late 2013 to date, the Abe administration has been trying several policies thatare explicitly geared toward boosting inward FDI into Japan. In early 2014, Expert Group on
Foreign Direct Investment in Japan was created and completed a report that recommends several
policies to remove the impediments to inward FDI to Japan (Expert Group on Foreign Direct
Investment in Japan, 2014). First, the report identified three important policy areas to promote
6

The other three are “Boost productivity”, “Pursue regulatory reforms”, and “Build on international opportunities”.

3inward FDI. The first is a set of economic reforms to reduce the substantial differences between
the Japanese system and the global system in several areas including (i) corporate tax system, (ii)employment system, (iii) corporate governance, (iv) system for corporate mergers, and (v)various regulations and administrative procedures. The second is establishing intergovernmental agreements including economic partnership agreements (EPAs), social security
treaties, and tax treaties. The third is a set of policies to improve living conditions for foreigners
in Japan. In addition to these three policy areas, the report also recommends expanding direct
support for foreign firms entering Japan by government entities and expanding government
efforts to promote the appealing aspects of Japan that are “not sufficiently understood.”
The report is very helpful in describing and understanding the FDI promotion policies in
Abenomics, because it identifies almost all the issues that are taken up in the policy discussion
and implementation that followed. In particular, we can compare a particular policy intervention
implemented to the three policy areas identified by the report and see in which area the efforts
progressed most rapidly and effectively.
The first comprehensive policy document for inward FDI promotion was “Five Promises
for Attracting Foreign Businesses to Japan” published in March 2015. The Japanese government
promised (1) to make it easier to live in Japan without Japanese language skills, (2) free public
Wi-Fi access points everywhere in Japan, (3) business jet access to any regional airport in Japan
with a short advance notice, (4) to enrich educational environment for children from overseas
and ensure Japanese students can communicate in English, and (5) to establish “Investment
Advisor Assignment System” that provides foreign business direct access to state ministers ofJapan.
The Five Promises are mostly on the third policy area identified in the expert groupreport, which is improving living conditions for the foreigners. The Promises are silent on theother two policy areas, which are reforms to achieve harmonization to the global standard andpromotion of inter-governmental agreements.
In May 2016, the government announced “Policy Package for Promoting Foreign Direct
Investment into Japan to Make Japan a Global Hub,” which now included policies to improve“regulations and administrative procedures.” Thus, the Package addresses the first policy areathat the expert group report emphasized, but that was only a small part of the package. The othermeasures continued to focus on improving the living environment for foreign nationals andgovernment promotion and PR to attract foreign companies.
The regulatory reform aspect of the inward FDI promotion policy finally started toreceive emphasis by creation of the Working Group for Revising Regulations and Administrative
Procedures in late 2016. The working group completed the final report in April 2017 andidentified the regulatory and administrative issues that foreign companies face in Japan andproposed policies to mitigate those. 7 The issues include (1) difficulty of incorporating andregistering companies, (2) problems for foreign nationals to set up legal residency, (3) lack of

7

The final report (English version) is available at http://www.investjapan.go.jp/policy/simplify_regulations_and_procedures/compilation_report_en.pdf (accessed on July 3, 2018).

4

one-stop administrative services, (4) paucity of business and administrative information inforeign languages, and (5) administrative burdens in following necessary procedures for imports.

3.

Gravity Model of Foreign Direct Investment

Our approach uses a gravity model of FDI that is developed by Head and Ries (2008). Theymodel FDI as a consequence of managers of one country bidding to acquire production units inanother country. 8 In their model, managers in home country monitor managers at overseas
subsidiaries by incurring monitoring cost. The monitoring cost is assumed to be proportional tothe distance between the home country and the country where subsidiaries are located. Thus, theprobability of winning bid falls as the distance between the manager’s country and the target
country increases. With additional assumptions (e.g., the numbers of managers and production
units are both proportional to the economy’s GDP), they derive a gravity model of FDI stock. 9
Letting 𝑖𝑖 and 𝑗𝑗 denote the origin and the destination of FDI respectively, the gravity
equation for FDI stock is:′
𝐹𝐹𝐹𝐹𝐹𝐹𝑖𝑖𝑖𝑖 = exp�𝐎𝐎′𝑖𝑖 𝛼𝛼 + 𝐃𝐃𝑗𝑗′ 𝛽𝛽 + 𝐰𝐰𝑖𝑖𝑖𝑖
𝛾𝛾� × 𝜀𝜀𝑖𝑖𝑖𝑖 ,(1)

Here exp(•) denotes exponential function, 𝐎𝐎𝑖𝑖 and 𝐃𝐃𝑗𝑗 are the vectors of the origin- anddestination-country dummies to capture the fixed effects. 10 𝐰𝐰𝑖𝑖𝑖𝑖 is the vector of characteristics ofthe origin-destination pair (such as distance) and 𝜀𝜀𝑖𝑖𝑖𝑖 is the disturbance term.

Note that the disturbance term is assumed to multiply the exponential function.
Traditionally, researchers specified the gravity model by including the disturbance as an extra
additive term in the argument for the exponential function. This allowed them to take the log ofboth sides of the equation and estimate a linear regression model. The problem of this approachis that country pairs with zero FDI stocks are dropped from the estimation because the log ofzero is not defined. By specifying the disturbance multiplicatively and assuming the expectedvalue is equal to one, we can estimate the gravity model directly by employing Pseudo-Poisson
Maximum Likelihood (PPML) estimation proposed by Santos Silva and Tenreyro (2006).
Although the estimation can be done by non-linear least square, the PPML estimator is known tobe more efficient than non-linear least square estimator (Santos Silva and Tenreyro, 2006). 11
Since our dataset is a panel data, we introducing time dimension to get:

8

De Sousa and Lochard (2011) showed that the model can be applied also to greenfield investment by consideringfirms selecting the best investment projects across all potential host countries.
9
Note that their gravity model explains the bilateral FDI stocks rather than FDI flows because the model is based on
the ownership of assets.
10
The origin and destination country fixed effects are analogous to the "multilateral resistance term" in the gravity
model of trade (Anderson and van Wincoop, 2003).
11
Another option is to use the negative binomial estimation, but the estimates are known to be sensitive to the unitsof the measurement for the dependent variable. For more details, see Bosquet and Boulhol (2013).

5

′
′
′
𝐹𝐹𝐹𝐹𝐹𝐹𝑖𝑖𝑖𝑖𝑖𝑖 = exp�𝐎𝐎′𝑖𝑖 𝛼𝛼 + 𝐃𝐃𝑗𝑗′ 𝛽𝛽 + 𝐰𝐰𝑖𝑖𝑖𝑖
𝛾𝛾 + 𝐱𝐱 𝑖𝑖𝑖𝑖𝑖𝑖
𝜆𝜆 + 𝐲𝐲𝑖𝑖𝑖𝑖′ 𝛿𝛿 + 𝐳𝐳𝑗𝑗𝑗𝑗𝜁𝜁� × 𝜀𝜀𝑖𝑖𝑖𝑖𝑖𝑖 ,(2)

where 𝐱𝐱 𝑖𝑖𝑖𝑖𝑖𝑖 is the vector of time-variant country-pair specific factors; 𝐲𝐲𝑖𝑖𝑖𝑖 and 𝐳𝐳𝑗𝑗𝑗𝑗 are the vectorsof origin- and destination-country-year specific variables respectively. The origin- anddestination-country-year specific variables that we consider are population (𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖𝑖𝑖 and 𝑃𝑃𝑃𝑃𝑃𝑃𝑗𝑗𝑗𝑗 )and per-capita GDP (𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖𝑖𝑖 and 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑗𝑗𝑗𝑗 ). In this paper, we estimate the equation (2) using the
PPML estimation.
Although our dataset has time dimension, we do not examine dynamics of FDI. This isconsistent with the approach of Head and Ries (2008), who uses a static model to motivate thegravity model of FDI. Thus, our regression analysis ignores some factors such as exchange rate
fluctuations that mostly influence the timings of FDI. We do not concern the lag-leadrelationship between FDI and its determinants, either. One may argue that FDI responds to the
future (expected) levels of population and GDP, but examining this is beyond the scope of thispaper.
We choose to use FDI stocks rather than FDI flows as dependent variables for the same
reason: we do not attempt to explain the dynamics. By using FDI stocks, we also avoid the
problem that FDI flows often have negative values. Nonetheless, we estimate the models using
FDI flows (and dropping the observations with negative values) or lagged explanatory variables
as robustness check.
As we saw above, Japan’s inward FDI relative to GDP has been very low compared withother OECD countries. This is partly expected because Japan has high labor costs, does notshare a common language with any other country, and is located far away from other advanced
countries such as the United States and the Western European countries. All of these areimportant factors that would lower the inward FDI according to the gravity model. The previous
studies using the gravity model, however, found that Japan’s inward FDI is abnormally low evencontrolling for these standard gravity variables. If this is also the case for our data, we expect tosee the destination specific effect of Japan to be lower than many other countries. Thus, we
expect to find the coefficient 𝛽𝛽𝑗𝑗 for Japan to be low.

If Abenomics has been effective in increasing inward FDI to Japan drastically, that would
show up as an increase in the destination specific effect for Japan in the gravity model. To checkthis, we consider two similar but different approaches.

The first approach starts by estimating the equation (2) using the data up to 2012. Then,
we use the estimated model to predict Japan’s inward FDI stock for 2013 and after. If
Abenomics successfully increased the destination specific effect for Japan, the estimated modelthat has low Japan specific destination effect would under-predict the growth of inward FDI for2013 and after. If this under-prediction is substantial, we can infer that Abenomics was effective
in promoting inward FDI.
The second approach also starts by estimating the equation (2) but the estimation drops
all the observations that involve Japan as the destination. We use the entire sample period toestimate the model. Then, we use the estimated model to predict the FDI stocks from each6

country to Japan in each year. Since we do not have an estimate for the destination specificeffect for Japan, we use zero. This means that we calculate what the Japan’s FDI stocks would
have been if Japan’s destination specific effect was the same as the reference country in the
regression (the U.S. in the estimation below). We can compare that to actual FDI stocks ofJapan. If the Abenomics policy to promote inward FDI had been successful, we would find thegrowth of actual value was larger than that of predicted value after 2012. The choice of thedestination-country specific effect is arbitrary but does not influence our inference on the effectsof Abenomics policy, because we examine if the growth after 2012 exceeded the counterfactual.
As we report below, our best fit gravity model includes the destination-country-specifictrend. Thus, we need to decide the destination-country-specific trend to use in predicting FDI
stocks for Japan in the second approach. The choice of destination-country-specific effect isimportant because it matters for the growth of predicted FDI after 2012, which is our focus.
Assuming too high trend would obviously overestimate the FDI growth under the counterfactual
scenario and would underestimate the contribution of the Abenomics FDI promotion policy.
Assuming too low trend would underestimate the FDI growth and overestimate the contributionof Abenomics. Below we use a couple of different values for the Japan specific trend in
producing the counterfactual values in the second approach and examine how the choice
influences our inference on the effectiveness of the Abenomics.

4.

Data

The data for inward FDI stock ( 𝐹𝐹𝐹𝐹𝐹𝐹𝑖𝑖𝑖𝑖𝑖𝑖 ) from 1985 to 2015 are obtained from the OECD
International Direct Investment Statistics database. In the database, the inward FDI stock isdefined as the nominal value of foreign investors' equity and net loans to enterprises resident in
the economy. In 2015, the dataset covers inward FDI from about 200 origin countries to 27 OECDdestination countries.
In the OECD database, zeros and missing values are distinguished, so we follow thedistinction of the database. For a small number of countries, inward FDI stocks are negative.
This can happen if the total amount of foreign parent companies’ borrowings from theirsubsidiaries in the country exceeds the total amount of foreign companies’ investments and loans
to the subsidiaries. For the analyses of this paper, we replace them with missing values.
There are two types of origin countries reported in the OECD database: immediate
counterpart and ultimate counterpart. Although only immediate counterpart is available in many
countries, we use ultimate counterpart as an origin country when available. If ultimate
counterpart is not available, we use immediate counterpart as origin country.
The OECD database changed the benchmark definition from the 3rd to the 4th edition in
2013. In the 4th edition, more detailed classifications of the type of entity is available. The
database distinguishes the difference between special purpose entities (SPEs) and non-SPEs.
SPEs are used by multi-national enterprises to channel investments through several countries
before reaching their final destinations. We exclude investments by foreign SPEs from inward
FDI stock when the data allow.
7

For time invariant country-pair specific variables (𝐰𝐰𝑖𝑖𝑖𝑖 ), we use a standard set of gravity
variables such as distance, common language dummy, common religion dummy, and colonial
relationship dummy. These variables are obtained from the CEPII (Centre d’Etudes Prospectives
et d’Informations Internationales) gravity data.
The time variant country-pair variables (𝐱𝐱 𝑖𝑖𝑖𝑖𝑖𝑖 ) are the RTA (Regional Trade Agreement)
dummy, the WTO membership, and the common currency dummy. We use the Mario Larch's
Regional Trade Agreements Database (Egger and Larch, 2008) to judge if a country pair belongs
to common RTA. The RTA in this database includes customs union (e.g., European Union), free
trade agreement and economic integration agreement (e.g., North America Free Trade
Agreement and Japan-Singapore economic partnership agreement), and partial scope agreement(e.g., South Asian Preferential Trade Arrangement). The WTO and common currency dummies
take 1 if both countries are members of the GATT/WTO and a common currency union
respectively. Both come from the CEPII gravity data.
We also include a dummy variable that takes 1 if the two countries have bilateral
investment treaties (BIT) (Egger and Pfaffermayr, 2004; Neumayer and Spess, 2005; Busse,
Königer, and Nunnenkamp, 2010). The BIT data are obtained from the World Bank Database of
Bilateral Investment Treaties. The database reports the signature date and entry into force date.
We use the entry into force date to construct the BIT dummy. 12
Population (𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖𝑖𝑖 and 𝑃𝑃𝑃𝑃𝑃𝑃𝑗𝑗𝑗𝑗 ) and per-capita GDP (𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖𝑖𝑖 and 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑗𝑗𝑗𝑗 ) are thedestination and origin country-specific characteristics (𝐲𝐲𝑖𝑖𝑖𝑖 and 𝐳𝐳𝑗𝑗𝑗𝑗 ). GDP is measured in current
thousand US dollars and the population is measured in thousand. These variables are also
obtained from the CEPII gravity data.
Data on FDI often include outliers, which are presumably caused by the lumpiness of
FDI. For example, Table 1 indicates that the inward FDI stock to Ireland increased by 88
percent from 2014 to 2015. To prevent estimation results to be driven by outliers, we drop theobservations with the changes in inward FDI stock from the previous year falling in the top 1
percent or the bottom 1 percent of all observations in the estimations below.
=== Table 2 ===Table 2 provides summary statistics for the data used for this paper. Note that the medianof inward FDI stock is zero. This suggests how to treat these observations with zero values caninfluence the estimation results.

5.

Has Abenomics been successful in promoting Japan’s inward FDI?

12The World Bank Database of Bilateral Investment Treaties (BIT) sometimes report the signature and entry into
force dates more than once because the database lists treaties concluded on a multilateral basis or as chapters in afree trade agreement separately. We define the first entry into force date as the beginning of the BIT. Thus, the BIT
dummy takes one after the first entry into force date and zero otherwise.

8

Table 3 shows the estimation results of the gravity model (equation (2)) for the period
from 1985 to 2012. We consider three types of the gravity model that differ in consideration for
country-fixed effects and country specific time trends. The model in column 1 does not include
origin- and destination-country fixed effects, but the model in column 2 does include those fixed
effects. For country fixed effects, we set the United States as a reference country. The model incolumn 3 includes the destination-country specific time trends in addition to the country fixed
effects.
=== Table 3 ===We first examine whether the estimate models are adequate or not. Following Santos
Silva and Tenreyro (2006), we perform a heteroskedasticity-robust RESET test. This is a test forthe correct specification of the conditional expectation, which is performed by investigating thesignificance of an additional regressor constructed as the square of the fitted value. Table 3
reports the corresponding p-values. The test does not reject the hypothesis that the coefficient on
the test variable is zero for all specifications. Thus, the RESET test provides no evidence of
misspecification of the gravity equations estimated using PPML.
To select the best model out of these three to use for our inference, we perform the HPC
test proposed by Santos Silva, Tenreyro, and Windmeijer (2015) for selection between
alternative models for non-negative observations with many zeros such as the dataset that we
examine. The HPC test is built on the tests of non-nested hypotheses developed by Davidson
and MacKinnon (1981). The HPC test in essence examines whether the prediction of thedependent variable generated by a model can be improved by using the predictions from analternative model. If that is found to be the case, it is considered to be an evidence against theoriginal model. We test each model taking each of the other models as the alternative. The pvalue for the null hypothesis (the null model is better than the alternative model) for eachalternative is presented at the bottom of each column. The HPC tests clearly reject model (1)against model (2), model (1) against model (3), and model (2) against model (3) at 1 percent
level. This suggests that the model (3) is the most preferred model. Including both country fixed
effects and destination-country specific time trend seem important.
We also use HPC tests to confirm that including observations with zero values isimportant. When we test the log-linear specification that drops all observations with zero values
against the model (3) as the alternative, the p-value for the test is 0.000, suggesting the model (3)is better. When we test the reverse (taking the log-linear as the alternative), the p-value is 0.058,
suggesting that the log-linear specification is not better. These results suggest that handling zero
values explicitly is important.
The model (3) is also attractive in that most of the estimated coefficients take the values
that are considered a priori plausible. Having RTA, common currency, common language,common religion, and colonial relationship have significantly positive effects on inward FDI
whereas distance has significantly negative effects. The per-capita GDP of both origin anddestination countries has significantly positive effects on inward FDI. This implies that inward
FDI is more likely to be observed between high-income countries. The size of the origin anddestination countries, measured by population, also matters as the coefficient of population is9significantly positive. Somewhat surprisingly, the coefficients of BIT and GATT-WTO
membership dummies are statistically insignificant. This may be due to the fact that destination
countries in our sample are all OECD countries, which do not have much variations.
Compared with the model (3), some of the results in columns (1) and (2) are difficult to
explain. For example, model (1) has significantly negative coefficient on the BIT dummy. Inmodel (2), destination country’s population enters the model insignificantly. Because model (3)is preferred in terms of the coefficients as well as the specification test, we use this model as ourbaseline model to generate the counterfactual.
Japan’s inward FDI relative to GDP has been very low compared with other OECD
countries. Our estimation result confirms that the standard gravity factors alone cannot explain
the low inward FDI into Japan. We can see this by comparing the estimated coefficients ondestination-country dummies (𝛽𝛽̂𝑗𝑗 in equation (2)). Table 4 provides such comparison. 13 A
negative coefficient on a destination-country dummy shows that some factor specific to the hostcountry tends to reduce its inward FDI compared with the reference country (the U.S. in thiscase). The table shows that the coefficient estimate for Japan is significantly negative and themagnitude is one of the largest in the sample. The estimated value -2.573 means that Japan’s
inward FDI stock would be about 7.6% (𝑒𝑒 −2.573 = 0.0763) of the US inward FDI stock holding
other factors (such as distances to host countries) equal. This is roughly the same order of theratio of the average FDI stocks for the two countries for the sample period (6.5%).
=== Table 4 ===Now we are ready to ask the central question of the paper. Has Abenomics beensuccessful in promoting inward FDI in Japan? In the first approach, we answer this by looking at
the growth of inward FDI for Japan after 2012, noting Abenomics was started in December
2012. When we use our model estimated using the sample before Abenomics to predict the FDI
into Japan after 2012, we would under-predict the growth if Abenomics policy for FDI
promotion has been effective.
Figure 2 presents the result of our first approach. The solid line indicates the actual
inward FDI in Japan while the dotted line is the prediction from the estimated model. To remove
unwanted effects of exchange rate fluctuations on US dollar value of the FDI stock, we plot thelevel of inward FDI stock divided by GDP in current prices. Figure 2 clearly shows that,
although inward FDI stock increased under the Abe administration, the actual growth was lower
than what the model predicts. The model predicts the inward FDI stock to GDP ratio would haveincreased by 1.42 percentage points from 2012 to 2015, while the actual increase was 0.88
percentage points.
=== Figure 2 ===13

Latvia is not included in this estimation because Latvia has been a member of the OECD since 2013 and its FDI
stocks before 2012 are not included in the database.

10

One may be concerned that the global financial crisis in 2008 distorts the estimation of
the gravity model. Table 1 indicates that the inward FDI stock relative to GDP declined
significantly in many European countries. Because majority of OECD countries are European
countries, our results may be sensitive to whether or not the estimation period includes thefinancial crisis. To address this concern, we estimate the gravity model using only the data
before the financial crisis (1985-2007) and use the estimated model for prediction.
The results are presented as the dashed line in Figure 2. The dashed line indicates thatthe levels predicted by the model for the period after 2012 using 1985-2007 data only are lower
than those predicted by the model that is estimated for 1985-2012. Nonetheless, the growth from2012 to 2015 was not much lower (0.77 percentage points). These results suggest that thegrowth of the inward FDI in Japan under Abenomics has been driven mainly by explanatory
variables other than the destination specific effects for Japan. Given the increases in GDPs andpopulations for many countries and the past trend, the model predicts that growth of inward FDI
stock for Japan after 2013 would have been higher than or at least comparable to the actual
growth. Thus, there is no clear evidence that the Abenomics policies to promote inward FDI
were effective.
The second approach estimates the gravity model without observations that involve Japanas the destination country and use the estimated coefficients to calculate what Japan’s inward
FDI would be if Japan had the same destination country specific effect as the reference country(the U.S. in this case). Because our preferred specification of the gravity model includes
destination country specific trend, we need to decide what trend we use in calculating
counterfactual level of Japan’s inward FDI. We have tried both (1) the trend for Japan estimatedin the first approach and (2) the trend for the reference country (U.S.) estimated in the second
approach. 14 Too large value for trend would overestimate the counterfactual FDI growth andhence underestimate the contribution of the Abenomics policies, while too small value for trend
would underestimate the counterfactual FDI growth and overestimate the contribution of
Abenomics.
Figure 3 shows the counterfactual predictions of Japan’s inward FDI stock calculated inthis way as well as the actual values. The dotted line shows the counterfactual prediction using
the trend estimated for Japan in the first approach, and the broken line shows the counterfactual
prediction using the trend estimated for the reference country in the second approach. The solidline shows the actual level of inward FDI stock.
If we use the trend for the U.S. in calculating the counterfactual prediction (broken line),
the predicted FDI increases by 1.40 percentage points, clearly larger the actual growth (0.88%).
When we use the trend for Japan estimated in the first approach (dotted line), the predicted
increase is much larger (8.38 percentage points). Thus, our second approach also fails to find an
evidence that Abenomics policy to promote inward FDI was successful.
=== Figure 3 ===14

We also calculated predicted values imposing zero trend. Under this extreme assumption, the predicted value forJapan’s inward FDI stock becomes lower than the actual value every year since 2007, implying Japan’s inward FDI
would have been even lower if Japan had been like other OECD countries.

11

Note that the inward FDI in Japan was dominated by some OECD countries. Figure 4
presents the share of Japan’s inward FDI Stock in 2016 by origin country. The largest origin
country of inward FDI to Japan is the United States (25.2 percent), followed by the Netherlands(13.6 percent), France (12.0 percent), the United Kingdom (8.1 percent), Singapore (7.9 percent),and Switzerland (4.6 percent). These six countries together account for more than 70 percent of
inward FDI stock in Japan. How do actual and predicted growth calculated in our second
approach differ for inward FDI from each of the six origin countries?
=== Figure 4 ===Table 5 presents the actual and predicted growth of inward FDI stocks to Japan from thesix countries from 2012 to 2015. For the predicted values, we use the ones generated assuming
the U.S. trend. The numbers are represented as a percentage of Japan’s GDP. The table also
reports the difference between the actual and predicted values, which we call “gap,” for eachcountry each year. Table 5 shows that the gaps were almost zero in both 2012 and 2015 for the
Netherlands, Singapore, and Switzerland. Thus, Japan’s inward FDI from those countries were
not necessarily low. The gap was zero for France in 2012 but it dropped below zero in 2015.
This may have resulted from the FDI promotion in Abenomics, though we need to examine thisfurther to be confident. For the U.S. and the UK, the gaps were positive and did not shrink
between 2012 and 2015. Especially for the U.S., the gap was big, suggesting that there is still
unrealized potential for inward FDI from the U.S.
=== Table 5 ===We use FDI stocks in our analysis for several reasons. FDI stocks are widely used inestimating gravity equation in the literature. The goal of Abenomics FDI promotion policy isalso stated in stock. Our interest is mainly in the steady state level of FDI rather than the
dynamics. For these reasons, we believe the stock measure is the right measure to use, but wehave also conducted robustness check using FDI flow variables instead.
One problem of using flows instead of stocks is that the FDI variable can become
negative. For the estimation for robustness check, we dropped all the observations with negative
FDI flows.
Table 6 replicates the gravity equation estimation in Table 2 by replacing FDI stocks with
FDI flows. The most preferred model is again the one with origin and destination fixed effects
and destination country specific time trend. The distance tends to reduce inward FDI flow, while
having colonial relationship, common religion and regional trade agreement tend to increase FDI
flow. These results are qualitatively the same as those in Table 2, but there are some differences
as well. Population of the origin country and per-capita GDP of the destination country havepositive influences on FDI flow, but we do not find the impacts of per-capital GDP of the origin
country and population of the destination country. We also fail to find that common official
language increases FDI, while we find bilateral investment treaty tends to increase FDI.
=== Table 6 ===12We have also applied our two approaches to see if the Abenomics FDI promotion policies
increased inward FDI using flow data instead of stock data. Figure 5 shows the result of the first
approach (out of sample prediction) and Figure 6 shows the result of the second approach(prediction from estimation without Japan). In Figure 5, the increases for the predicted values(0.16 percentage points for the dotted line and 0.28 percentage points for the broken line) arelarger than the actual increase of FDI flow from 2012 to 2015 (0.11 percentage points). In
Figure 6, the increases for the predicted values (1.31 percentage points when the trend estimatedfor Japan is used and 9.86 percentage points when the trend estimated for the U.S. is used) areagain larger than the actual growth of FDI flow. Thus, the analysis using FDI flows instead ofstocks suggests the same conclusion: the increase of inward FDI from 2012 to 2015 can be
explained by the factors captured in the gravity model other than an increase in Japan’s
destination country specific effect. In this sense, we fail to find the impact of Abenomics FDI
promotion policies.
=== Figure 5 ====== Figure 6 ===Another robustness check that we conducted concerns the timing of the explanatory
variables in the gravity equation. We use contemporaneous variables rather than lagged values
mainly because we are not concerned with the dynamics. Table 7 replicates the gravity equation
estimation in Table 2 by using one-year lag for the explanatory variables that change over time.
The results in Table 7 are very similar to those in Table 2. The preferred model is again the one
with origin and destination fixed effects and country specific time trends. The only qualitative
difference is that we do not find the impact of per-capita GDP of the destination country when
we use lagged explanatory variables. The result is puzzling because the estimated coefficient on
per-capital GDP is positive and statistically significant in the specifications without destination
country specific time trend. It is possible that per-capita GDP may look too much like timetrend, but if that is the case we would expect a similar problem to arise when we use
contemporaneous explanatory variables.
=== Table 7 ===We also applied our two approaches to examine the effectiveness of Abenomics FDI
promotion policies using lagged explanatory variables. Figure 7 shows the results of the first
approach and Figure 8 shows the results of the second approach. In Figure 7, the increases forthe predicted values (2.15 percentage points for the dotted line and 1.26 percentage points for the
broken line) are much larger than the actual increase (0.88 percentage points as we saw earlier).
In Figure 8, the increases for the predicted values (3.14 percentage points when the U.S. trend isused and 7.64 percentage points when the Japan trend is used) are again much larger than theactual growth. Thus, the use of lagged explanatory variables leads us to the same conclusion: we
do not find obvious impacts of the FDI promotion policies of the Abe administration.
=== Figure 7 ====== Figure 8 ===13

Increasing inward FDI to Japan has been touted as one of the most important policy goalsof Abenomics, and the amount of inward FDI stock has been rising toward the goal of 35 trillion
yen by 2020. Yet, our analysis using the gravity model of inward FDI suggests that the increasein Japan’s inward FDI from 2012 to 2015 was not larger than the predictions of the model.
Why did Abenomics FDI promotion fail to deliver obvious results? One possibility isthat it takes a long time before the policy leads to visible impacts. Two or three years may not belong enough. We cannot exclude this possibility. If the policy lag is the only reason that we did
not observe obvious impacts of Abenomics in our sample period, all we have to do is to just
wait: Japan’s inward FDI stock will start growing above the trend eventually.
It is also possible, however, that the lack of acceleration in Japan’s inward FDI is indeed
a result of ineffective or incomplete policies. For example, as we discussed in Section 2, theimplementation of FDI promotion has been skewed to the measures to make it easier forforeigners to live or stay in Japan. The deregulation measures to make it easier to foreign (anddomestic) businesses to do business in Japan has been slow. This may have limited theeffectiveness of the Abenomics policy so far.
Improving Japan's rank in the World Bank Doing Business Ranking to one of the top
three among OECD has been another goal of Abenomics growth strategy, but there has been no
progress as Haider and Hoshi (2015) point out. The lack of progress in improving the condition
for doing business may be related to no visible impacts of Abenomics on Japan’s inward FDI
stock. This can be checked by examining if the World Bank's doing business indices (measured
as distance to frontier) matters for inward FDI after controlling for the gravity and othervariables. The distance to frontier measure of the World Bank doing business index is higher if
the country has better business condition (e.g., 90% to the frontier is better than 60% to thefrontier). Thus, we would expect the doing business index enter the regression with a positivecoefficient.
=== Table 8 ===Table 8 reports the estimation results of the equation (2) augmented by the doing businessindices. Since the doing business indices are available only after 2005 for many categories (e.g.,
paying taxes) and only after 2009 for overall index, the sample size here is smaller. The results
indicate none of the coefficients on doing business indices are significantly positive, either when
the indices are put in the gravity model one by one or all at the same time. Thus, we cannot
argue that Japan’s low ranking in the World Bank doing business condition is an important factor
to discourage inward FDI.

6.

Conclusion

Promotion of inward foreign direct investment (FDI) into Japan has been an important policy in
the Abenomics growth strategy. This paper examined if we can observe positive effects of theinward FDI promotion policy in the data for inward FDI stocks in Japan. We have tried two
approaches applying a gravity model of bilateral FDIs to data from 35 OECD countries by
14

origins of inward FDIs. In the first approach, we estimated the model assuming origin-country
and destination-country fixed effects as well as destination-country specific time trends for 19852012. The destination-country fixed effect for Japan was estimated to be the third lowest of the
35 countries in our sample, reflecting unusually low level of Japan’s inward FDI, which is wellknown in the literature. We then compared the predicted levels of Japan’s inward FDI stocks for
2013-2015 to the actual levels. Although the actual inward FDI stock has been growing and islikely to achieve the goal of 35 trillion yen by 2020, we find that the growth was lower than theestimated model suggests.
The second approach started by estimating the gravity model excluding all theobservations that involve Japan as the destination country. Then we constructed prediction fromthe estimated model for Japan’s inward FDI. The actual inward FDI into Japan was found to beless than the counterfactual. The gap between the actual and the counterfactual were actuallywidened under the Abe administration.
Thus, our results suggest that Abenomics policies to encourage inward FDI did not havevisible impacts. One shortcoming of our paper is that we do not test the impacts of Abenomics
policies. Instead we try to look for indirect evidence of the impacts of Abenomics policies by
examining any changes in Japan’s inward FDI after 2012. Thus, we would fail to find thepositive impacts of Abenomics policies if those were offset by any other changes that reduced
Japan’s inward FDI. But, we have difficulty coming up with some changes after 2012 thatshould have decreased Japan’s FDI. Instead many changes that we can identify easily would
have increased FDI flows into Japan. For example, the yen depreciated against other major
currencies during our sample period. This must have contributed to raising Japan’s inward FDI.
Similarly, well known increase of foreign visitors should have led to increasing FDI if anything.
Another shortcoming of our paper is the fact that our dataset ends in 2015. Since
Abenomics promotion of inward FDI seemed to have stepped up after 2016 especially in
regulatory and administrative reforms, it is possible that those efforts may show up in future
data. In fact, there is an optimistic interpretation of the results. Japan’s inward FDI stock rose
recently despite the unusually low destination-country effect for Japan is. This means thatJapan’s potential for inward FDI is much higher than what Abenomics targeted. If Japan canremove the impediments that make the inward FDI unusually low, Japan will be able to achieve
the potential.

References
Anderson, James E. and Eric van Wincoop (2003) “Gravity with Gravitas: A Solution to theBorder Puzzle,” American Economic Review, 93(1): 170-192.
Anderson, James E. (2011) “The Gravity Model,” Annual Review of Economics, 3: 133-160.
Baltagi, Badi H., Peter Egger, and Michael Pfaffermayr (2015) “Panel Data Gravity Models ofInternational Trade,” in Badi H. Baltagi (ed.), The Oxford Handbook of Panel Data,
Oxford University Press.

15

Bosquet, Clément and Hervé Boulhol (2014) “Applying the GLM Variance Assumption to
Overcome the Scale-Dependence of the Negative Binomial QGMPL Estimator,”
Econometric Review, 33(7): 772-784.
Busse, Matthias, Jens Königer, and Peter Neunnenkamp (2010) “FDI Promotion throughBilateral Investment Treaties: More than A Bit?” Review of World Economics, 146(1):147-177.
Davidson, Russell, and James G. MacKinnon (1981). “Several Tests for Model Specification in
the Presence of Alternative Hypotheses,” Econometrica, 49(3), 781-793.
De Sousa, José and Julie Lochard (2011) “Does the Single Currency Affect Foreign Direct
Investment?” Scandinavian Journal of Economics, 113(3): 553-578.
Doms, Mark and J. Bradford Jensen (1998) “Comparing Wages, Skills, and Productivity between
Domestically and Foreign-Owned Manufacturing Establishments in the United States,” inRobert E. Baldwin, Robert E. Lipsey, and J. David Richardson (eds), Geography andOwnership as Bases for Economic Accounting, Chicago, IL: University of Chicago Press.
Egger, Peter (2010) “Bilateral FDI Potentials for Austria,” Empirica, 37(1): 5-17.
Egger, Peter H. and Mario Larch (2008) “Interdependent Preferential Trade Agreement
Membership: An Empirical Analysis,” Journal of International Economics, 76(2): 384399.
Egger, Peter and Michael Pfaffermayr (2003) “The Proper Panel Econometric Specification of
the Gravity Equation: A Three-way Model with Bilateral Interaction Effects,” Empirical
Economics, 28(3): 571-580.
Egger, Peter and Michael Pfaffermayr (2004) “The Impact of Bilateral Investment Treaties on
Foreign Direct Investment,” Journal of Comparative Economics, 32(4): 788-804.
Fukao, Kyoji, Keiko Ito, Hyeog Ug Kwon, and Miho Takizawa (2008) “Cross-Border
Acquisitions and Target Firms’ Performance: Evidence from Japanese Firm-Level Data,”in Takatoshi Ito and Andrew K. Rose (eds.), International Financial Issues in the Pacific
Rim: Global Imbalances, Financial Liberalization, and Exchange Rate Policy (NBEREASE Volume 17), Chicago, IL: The University of Chicago Press, 347-389.
Guimarães, Paulo and Pedro Portugal (2010) “A Simple Feasible Procedure to Fit Models with
High-dimensional Fixed Effects,” The Stata Journal, 10(4): 628-649.
Haidar, Jamal Ibrahim and Takeo Hoshi (2015) “Implementing Structural Reforms in
Abenomics: How to Reduce the Cost of Doing Business in Japan,” NBER Working Paper
Series, No. 21507.
Head, Keith and Thierry Mayer (2015) “Gravity Equations: Workhorse, Toolkit, andCookbook,” in Gita Gopinath, Elhanan Helpman, and Kenneth Rogoff (eds.) Handbookof International Economics, Volume 4: 131-195.
Head, Keith and John Ries (2005) “Judging Japan's FDI: The Verdict from A Dartboard Model,”Journal of the Japanese and International Economies, 19(2): 215-232.
Head, Keith and John Ries (2008) “FDI as An Outcome of the Market for Corporate Control:
Theory and Evidence,” Journal of International Economics, 74(1): 2-20.
16

Headquarters for Japan’s Economic Revitalization (2013) Japan Revitalization Strategy: Japanis Back. Accessed 12 June 2017. Available from URL:
http://www.kantei.go.jp/jp/singi/keizaisaisei/pdf/en_saikou_jpn_hon.pdf
Hoshi, Takeo (2018) “Has Abenomics Succeeded in Raising Japan's Inward Foreign Direct
Investment?” Asian Economic Policy Review, 13(1): 149-168.
Javorcik, Beata Smarzynska (2004) “Does Foreign Direct Investment Increase the Productivityof Domestic Firms? In Search of Spillovers Through Backward Linkages,” American
Economic Review, 94(3): 606-627.
Kimino, Satomi, David S. Saal, and Nigel Driffield (2007) “Macro Determinants of FDI Inflows
to Japan: An Analysis of Source Country Characteristics,” The World Economy, 30(3):446-469.
Kimura, Fukunari and Kozo Kiyota (2007) “Foreign-owned versus Domestically-owned Firms:
Economic Performance in Japan,” Review of Development Economics, 11(1): 31-48.
Neumayer, Eric and Laura Spess (2005) “Do Bilateral Investment Treaties Increase Foreign
Direct Investment to Developing Countries?” World Development, 33(10): 1567-1585.
Román, Valeriano Martínez-San, Marta Bengoa, and Blanca Sánchez-Robles (2016) “Foreign
Direct Investment, Trade Integration and the Home Bias: Evidence from the European
Union,” Empirical Economics, 50(1): 197-229.
Santos Silva, Joao M.C. and Silvana Tenreyro (2006) “The Log of Gravity,” Review of
Economics and Statistics, 88(4): 641-658.
Santos Silva, Joao M.C., Silvana Tenreyro, and Frank Windmeijer (2015) “Testing Competing
Models for Non-negative Data with Many Zeros,” Journal of Econometric Methods, 4(1): 29-46.
Sato, Hitoshi and Hiromi Oki (2012) “Foreign Direct Investment and Globalization of Economy(Chokusetsu Toushi to Keizai no Gurobaru ka),” in Tetsuji Okazaki (ed.) History ofCommercial Policy, Volume 3, Industrial Policy, 1980-2000 (Tsusho Sangyo Seisakushi
3, Sangyo Seisaku, 1980-2000), Tokyo: RIETI, 473-566. (In Japanese)
Todo, Yasuyuki (2006) “Knowledge Spillovers from Foreign Direct Investment in R&D:
Evidence from Japanese firm-level data,” Journal of Asian Economics, 17(6): 996-1013.
Yoshitomi, Masaru and Edward M. Graham (eds.) (1996) Foreign Direct Investment in Japan,
Cheltenham, UK: Edward Elgar.
Yotov, Yoto V., Roberta Piermartini, José-Antonio Monteiro, and Mario Larch (2016) An
Advanced Guide to Trade Policy Analysis: The Structural Gravity Model, Online Revised
Version, Geneva, Switzerland: World Trade Organization.

17

Figure 1. Inward FDI Stock for Japan, 1996-2016
30.0

28.6

Inward FDI Stock (trillions of Yen)

25.0

19.2

20.0

15.0

10.0

4.0
5.0

2017

2016

2015

2014

2012
2011

2013

2011
2010

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0

Source: Ministry of Finance (2018) International Investment Position (Historical Data).
Figure 2. Actual versus Predicted Inward FDI Stock for Japan (% of GDP)
5.0%
4.5%
4.0%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%

Predicted (1985-2012 data)

Predicted (1985-2007 data)

2015

2014

2013

2012

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0%

ActualSources: Inward FDI stock data are obtained from the OECD International Direct Investment Database. For other data, seemain text.

18

Figure 3. Actual versus Predicted Inward FDI Stock for Japan (% of GDP)
45.0%

40.0%

35.0%

30.0%

25.0%

20.0%

15.0%

10.0%

5.0%

ActualCounter factual (US trend)

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0%

Counter factual (Japan trend)

Sources: Inward FDI stock data are obtained from the OECD International Direct Investment Database. For other data, see main text.
Figure 4. Share of Japan's Inward FDI Stock by Country (2016)

United States
25.2%

Others28.4%

Netherlands
13.6%

Switzerland
4.6%
Singapore
7.9%

UnitedKingdom
8.1%

France12.0%

Source: Ministry of Finance (2018) International Investment Position.

19

Figure 5. Actual versus Predicted Inward FDI Flow for Japan (% of GDP)
0.9%
0.8%
0.7%
0.6%
0.5%
0.4%
0.3%
0.2%
0.1%

Predicted (1985-2012 data)

Predicted (1985-2007 data)

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0%

ActualSources: Inward FDI flow data are obtained from the OECD International Direct Investment Database. For other data, see main
text.

Figure 6. Actual versus Predicted Inward FDI Inflow for Japan (% of GDP)
60.0%

50.0%

40.0%

30.0%

20.0%

10.0%

ActualCounter factual (US trend)

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0%

Counter factual (Japan trend)

Sources: Inward FDI flow data are obtained from the OECD International Direct Investment Database. For other data, see main text.

20

Figure 7. Actual versus Predicted Inward FDI Stock for Japan (% of GDP): Lagged Variables
6.0%

5.0%

4.0%

3.0%

2.0%

1.0%

Predicted (1985-2012 data)

Predicted (1985-2007 data)

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0%

ActualSources: Inward FDI flow data are obtained from the OECD International Direct Investment Database. For other data, see main
text.

Figure 8. Actual versus Predicted Inward FDI Stock for Japan (% of GDP): Lagged Variables
25.0%

20.0%

15.0%

10.0%

5.0%

ActualCounter factual (US trend)

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0%

Counter factual (Japan trend)

Sources: Inward FDI flow data are obtained from the OECD International Direct Investment Database. For other data, see main text.

21

Table 1. Ratio of Inward FDI Stock to GDP for OECD Countries, 1985-2015
OECD AUS AUT BEL CAN CHE CHL CZE DEU DNK ESP ESTFIN FRA GBR GRC HUN
IRL
ISL1985 0.076 0.124.
. 0.174.
.
. 0.047
.
.
.
.
.
.
.
.
.
.
1986 0.072 0.132 0.046. 0.181.
.
. 0.045
.
.
.
.
.
.
.
.
.
.
1987 0.086 0.180 0.049. 0.184.
.
. 0.047.
.
.
.
. 0.138.
.
.
.
1988 0.083 0.219 0.046. 0.186.
.
. 0.042.
.
.
.
. 0.136.
.
. 0.0151989 0.087 0.194 0.067. 0.186.
.
. 0.062.
.
.
. 0.048 0.157.
.
. 0.0191990 0.088 0.208 0.064. 0.188.
.
. 0.065.
.
.
. 0.060 0.182.
.
. 0.0221991 0.095 0.210 0.074. 0.190.
.
. 0.068 0.116.
.
. 0.070 0.178.
.
. 0.0241992 0.084 0.191 0.066. 0.181.
.
. 0.058.
.
. 0.029 0.090 0.143. 0.111. 0.017
1993 0.106 0.212 0.070. 0.182 0.141.
. 0.060.
.
. 0.043 0.100 0.165. 0.150. 0.0191994 0.116 0.257 0.074. 0.189 0.158.
. 0.069 0.124.
. 0.060 0.115 0.160. 0.162. 0.020
1995 0.157 0.232 0.084. 0.199 0.159.
. 0.071.
.
. 0.060 0.118 0.154.
.
. 0.021
1996 0.158 0.249 0.082. 0.206 0.147.
. 0.152.
.
. 0.064 0.122 0.167.
.
. 0.026
1997 0.162 0.202 0.097. 0.200 0.185. 0.145 0.083.
.
. 0.072 0.133 0.166.
.
. 0.044
1998 0.201 0.222 0.111. 0.219 0.225. 0.209 0.108 0.162.
. 0.120 0.162 0.186. 0.330. 0.050
1999 0.218 0.264 0.103. 0.252 0.243. 0.253 0.122 0.189.
. 0.133 0.162 0.235. 0.361. 0.048
2000 0.232 0.237 0.153. 0.279 0.311. 0.329 0.164 0.334 0.001 0.006 0.191 0.189 0.260. 0.365. 0.044
2001 0.289 0.240 0.168. 0.291 0.310. 0.375 0.163 0.312.
. 0.183 0.210 0.315 0.108 0.360 1.086 0.069
2002 0.322 0.274 0.200. 0.300 0.404. 0.048 0.256 0.355 0.156. 0.244 0.254 0.295 0.108 0.392 1.459 0.064
2003 0.328 0.337 0.211. 0.317 0.448. 0.454 0.273 0.359 0.329 0.638 0.286 0.290 0.304 0.119 0.457 1.309 0.049
2004 0.378 0.343 0.220. 0.309 0.491. 0.476 0.253 0.445 0.319 0.752 0.285 0.310 0.294 0.107 0.483 1.011 0.129
2005 0.338 0.240 0.248. 0.306 0.402. 0.438 0.222 0.436 0.329 0.782 0.264 0.169 0.333 0.106 0.428 0.837 0.113
2006 0.395 0.276 0.313. 0.277 0.548 0.483 0.513 0.261 0.463 0.360 0.709 0.317 0.214 0.419 0.133 0.666 0.712 0.411
2007 0.448 0.329 0.399. 0.343 0.706 0.536 0.593 0.276 0.495 0.391 0.705 0.350 0.235 0.404 0.157 0.671 0.784 0.757
2008 0.411 0.208 0.335 1.603 0.276 0.761 0.518 0.478 0.243 0.420 0.356 0.637 0.289 0.193 0.321 0.104 0.514 0.746 0.524
2009 0.506 0.352 0.402 1.994 0.385 0.895 0.330 0.610 0.268 0.479 0.416 0.802 0.332 0.240 0.446 0.119 0.788 1.084 0.673
2010 0.511 0.341 0.399 1.923 0.351 0.955 0.324 0.620 0.265 0.439 0.431 0.798 0.340 0.240 0.452 0.131 0.693 1.270 0.889
2011 0.467 0.290 0.351 1.884 0.314 0.842 0.372 0.537 0.251 0.396 0.408 0.709 0.323 0.229 0.451 0.100 0.586 1.175 0.858
2012 0.526 0.313 0.376 1.836 0.332 0.913 0.391 0.652 0.280 0.450 0.444 0.824 0.369 0.244 0.536 0.109 0.748 1.663 0.733
2013 0.457 0.275 0.388 1.019 0.354 0.981 0.470 0.562 0.237 0.279 0.426 0.793 0.278 0.260 0.422 0.125 0.722 1.694 0.448
2014 0.420 0.308 0.355 0.855 0.347 0.943 0.547 0.546 0.199 0.255 0.403 0.703 0.288 0.227 0.377 0.117 0.672 1.533 0.441
2015 0.447 0.323 0.379. 0.351 1.057 0.615 0.565. 0.305 0.419 0.748 0.308 0.270 0.388 0.134 0.609 1.517 0.451
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment Database. GDP data are obtained from the CEPII gravity data.

ISR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
0.230
0.176
0.172
0.159
0.171
0.184
0.156
.

ITA
0.033
0.032
0.031
0.034
0.046
0.043
0.042
0.032
0.043
0.046
0.050
0.051
0.052
0.065
0.068
0.083
0.077
0.083
0.113
0.120
0.119
0.150
0.166
0.135
0.165
0.153
0.155
0.178
0.131
0.115
0.133

JPN
0.003
0.003
0.003
0.003
0.004
0.004
0.005
0.005
0.005
0.005
.
0.005
0.006
0.006
0.008
0.010
0.011
0.018
0.019
0.021
0.021
0.023
0.028
0.039
0.038
0.037
0.037
0.033
0.034
0.037
0.042

KOR
.
.
.
.
.
0.018
0.019
0.019
0.019
0.018
0.017
0.019
0.025
0.051
0.059
0.064
0.077
0.073
0.071
0.073
0.069
0.066
0.061
0.070
0.127
0.123
0.111
0.127
0.126
0.117
0.123

LUX LVA
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
0.771
.
0.696
.
0.814
.
0.948
.
0.845
.
1.020
.
1.161
.
1.395
.
0.298
.
1.358
.
1.077
.
1.151
.
1.258
.
1.126
.
1.448
.
1.278
.
1.163
.
1.308
.
. 0.447. 0.462. 0.529

MEX
0.037
0.056
0.062
0.078
0.069
0.076
0.085
0.099
0.077
0.067
0.114
0.109
0.104
0.120
0.129
0.133
.
.
.
.
.
.
.
.
0.380
0.368
0.328
0.383
0.381
0.374
0.444

NLD
0.150
0.146
0.157
0.143
0.173
0.187
0.189
0.174
0.180
0.216
0.215
0.232
0.248
0.290
0.433
0.587
0.661
0.749
0.732
0.721
0.646
0.747
0.910
0.650
0.699
0.687
0.651
0.690
0.855
0.763
0.901

NOR
.
.
0.093
0.086
0.091
0.104
0.123
0.096
0.101
0.121
0.117
0.114
0.118
0.164
0.167
0.165
0.169
0.198
0.189
0.283
0.232
0.259
0.279
0.226
0.353
.
0.336
0.390
0.340
0.321
0.337

NZL
.
.
.
.
.
.
.
.
0.321
0.393
0.392
0.465
0.414
0.497
0.485
0.478
0.266
0.303
0.305
0.407
.
0.475
0.441
0.324
0.433
0.412
0.392
0.509
0.396
0.369
0.365

POL
.
.
.
.
.
.
.
.
.
0.025
0.054
0.068
0.087
0.122
0.148
0.183
0.207
0.229
0.264
0.336
0.292
0.359
0.403
0.300
0.414
0.443
0.378
0.465
0.375
0.324
0.320

PRT
.
.
.
.
.
.
.
.
.
.
0.121
0.153
0.168
0.202
0.175
0.230
0.246
0.307
0.293
0.315
0.290
.
0.436
0.350
0.434
0.431
0.404
0.478
0.545
0.481
0.537

SVK
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
0.150
0.168
0.233
0.336
0.378
0.375
0.475
0.494
0.508
0.590
0.567
0.533
0.603
0.597
0.497
.

SVN
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
0.225
0.296
0.280
0.222
0.218
0.219
0.258
0.251
0.247
0.291

SWE
.
0.033
0.042
0.040
0.045
0.039
0.060
0.048
0.060
0.091
0.110
0.113
0.137
0.180
0.263
0.351
0.362
0.425
0.474
0.510
0.437
0.546
0.601
0.544
0.743
0.691
0.608
0.690
0.647
0.526
0.581

TUR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
0.072
0.100
0.081
0.110
0.097
0.140
0.177
0.237
0.110
0.232
0.255
0.173
0.240
0.336
0.225
0.205

USA
0.037
0.043
0.050
0.056
0.061
0.062
0.067
0.064
0.066
0.070
0.074
0.079
0.074
0.079
0.091
0.111
0.108
0.120
0.121
0.122
0.123
0.129
0.137
0.138
0.143
0.151
0.151
0.157
0.161
0.166
0.173

22

Table 2. Summary Statistics
N
59,66559,66559,66559,66559,66559,66559,66559,66559,665Mean
2,098,331
0.278
0.135
0.789
0.032
8.556
0.098
0.183
0.039

S.D.
13,976,827
0.448
0.342
0.408
0.177
0.895
0.297
0.245
0.192

p25

Medianp75
47,938
1.000
0.000
1.000
0.000
9.171
0.000
0.287
0.000

Inward FDI stock
00
RTA dummy
0.000
0.000
Bilateral investment treaties dummy
0.000
0.000
GATT-WTO member dummy
1.000
1.000
Common currency dummy
0.000
0.000
Distance (log value)
8.076
8.846
Common official language dummy
0.000
0.000
Common religion dummy
0.007
0.059
Colonial relationship dummy
0.000
0.000
Origin country
Population (log value)
59,665
8.811
2.064
7.770
9.016
10.213Per-capita GDP (log value)
59,665
1.449
1.642
0.090
1.440
2.928
Destination country
Population (log value)
59,665
9.541
1.579
8.590
9.304
10.965Per-capita GDP (log value)
59,665
3.205
0.729
2.747
3.297
3.745
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment Database. For other data, see main text.

23

Table 3. Gravity Model Estimation, 1985-2012: Baseline Results(1)-0.202[0.197]-0.590***[0.124]-0.076[0.263]0.212[0.150]-0.561***[0.091]0.708***[0.141]0.672***[0.253]0.565***[0.187](2)
Origin/destination fixed
effect0.269*[0.144]0.190*[0.111]
0.059[0.174]0.318***[0.107]-0.506***[0.069]0.335***[0.093]
1.532***[0.237]0.433***[0.107](3)
Origin/destination fixed
effect0.298**[0.134]0.135[0.112]0.021[0.168]0.260**[0.112]-0.499***[0.066]
0.338***[0.094]
1.591***[0.235]0.440***[0.105]0.639***[0.041]
1.897***[0.086]1.601***[0.484]0.795***[0.130]0.826*[0.428]0.589***[0.122]0.774***[0.051]0.637***[0.085]59,665
No
No
0.730

0.852
[0.557]0.923***[0.111]
59,665
Yes
No
0.370

3.168***[0.669]0.376***[0.101]
59,665
Yes
Yes
0.852

0.442

0.419
0.152

Traditional
gravity variables
RTA dummy
Bilateral investment treaties dummy
GATT-WTO member dummyCommon currency dummy
Distance
Common official language dummyCommon religion dummyColonial relationship dummy
Origin country
Population
Per-capita GDP
Destination country
Population
Per-capita GDP
Number of observations
Origin and destination fixed effects
Country-specific time trend
RESET test p -value
HPC test p -values
Column 1 as Alternative
Column 2 as Alternative
Column 3 as Alternative

0.000
0.000

0.000

Notes: ***, **, and * indicate statistically significant at 1%, 5%, and 10%, respectively.
Standard errors, which are clustered by pairs, are reported in brackets. Observations with thechanges in inward FDI stock from the previous year falling in the top 1% or the bottom 1% of
all observations are dropped. All the models are estimated by PPML.
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment
Database. For other data, see main text.

24

Table 4. Destination-Country Specific Effects for OECD Countries
Country name
Australia
Austria
Belgium
CanadaChile
Czech Republic
Denmark
Estonia
FinlandFranceGermany
GreeceHungary
Iceland
IrelandIsrael
Italy
Japan
Korea
LatviaLuxembourg
MexicoNetherlands
New Zealand
NorwayPolandPortugal
Slovakia
Slovenia
Spain
SwedenSwitzerland
TurkeyUnited Kingdom
United States

Abbreviations
AUS
AUT
BEL
CAN
CHL
CZE
DNK
EST
FIN
FRA
DEU
GRC
HUN
ISL
IRL
ISR
ITA
JPN
KOR
LVA
LUX
MEX
NLD
NZL
NOR
POL
PRT
SVK
SVN
ESP
SWE
CHE
TUR
GBR
USA

Coefficient Standard Errors
7.151***[1.822]4.125*[2.364]7.689***[2.524]5.033***[1.542]9.307***[2.514]2.005[2.182]
6.603**[2.708]9.798***[3.642]4.468*[2.579]1.794*[1.021]0.428[0.860]5.963***[2.291]2.180[2.004]6.268[5.564]12.740***[3.293]16.290***[4.908]0.788[1.038]-2.573***[0.747]-1.188[1.359]not available
15.623***[4.650]0.029[0.908]5.461***[1.890]11.497***[3.073]
6.897**[2.833]-3.160**[1.277]3.750*[2.168]3.102[2.620]14.973***[3.656]4.590**[1.915]4.251*[2.326]3.990[2.742]-3.039*[1.717]2.259**[1.084]
reference country

Notes: Coefficients and standard errors are obtained from the model in column 3
of Table 2. ***, **, and * indicate the coefficient estimate is statisticallysignificant at 1%, 5%, and 10% respectively. Standard errors, which are clusteredby pairs, are reported in brackets. Coefficients on Latvia is not available because
Latvia has been a member of the OECD since 2013.
Sources: Inward FDI stock data are obtained from the OECD International Direct
Investment Database. For other data, see main text.

25

Table 5. Actual and Counter-factual Inward FDI Stock, by Major Origin Country
US trend
actualUnited States

1.0

Netherlands

0.5France0.3

United Kingdom

0.3

Singapore

0.3

Switzerland

0.2

Total

3.3

Japan trend
actual

2012
countergap
factual(% of total)
2.1
1.1(34.4)
0.6
0.1
(3.1)
0.3
0.0
(0.0)
0.6
0.3
(9.4)
0.2
-0.1
(-3.1)
0.3
0.1
(3.1)
6.5
3.2
(100.0)2012
counterfactual
9.9

1.3

2015
counterfactual
2.6

0.6

0.6

0.6

0.3

0.3

0.7

0.3

0.2

0.2

0.3

4.2

7.9

actualgap(% of total)
1.3(35.1)
0.0
(0.0)
-0.3
(-8.1)
0.4(10.8)-0.1(-2.7)
0.1
(2.7)
3.7
(100.0)2015
counterfactual
13.1

gap
actualgap(% of total)(% of total)
United States
1.0
8.9
1.3
11.8
(32.8)(34.2)
Netherlands
0.5
2.6
2.1
0.6
3.1
2.5
(7.7)
(7.2)
France
0.3
1.3
1.0
0.6
1.5
0.9
(3.7)
(2.6)
United Kingdom
0.3
2.8
2.5
0.3
3.6
3.3
(9.2)
(9.6)
Singapore
0.3
0.7
0.4
0.3
0.9
0.6
(1.5)
(1.7)
Switzerland
0.2
1.3
1.1
0.2
1.7
1.5
(4.1)
(4.3)
Total
3.3
30.4
27.1
4.2
38.7
34.5
(100.0)(100.0)Notes: This figure indicates actual and counter-factual inward FDI stock as a percentage of Japan's GDP.
Counterfactual inward FDI stock is obtained from the second approach. Gap indicates the difference between
counterfactual and actual values. Figure in parenthesis indicates the ratio of each country's gap to total gap.
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment Database. For

26

Table 6. Gravity Model Estimation, 1985-2012: FDI Inflows(1)-0.258[0.223]-0.569***[0.132]0.155[0.278]0.315**[0.151]-0.419***[0.082]0.592***[0.163]0.698***[0.248]0.684***[0.248](2)
Origin/destination fixed
effect0.223[0.152]0.290***[0.105]0.135[0.279]0.330**[0.149]-0.389***[0.074]0.039[0.110]0.961***[0.280]0.286**[0.130](3)
Origin/destination fixed
effect0.292**[0.147]0.315***[0.104]0.300[0.257]0.259*[0.155]-0.372***[0.073]0.027[0.111]1.028***[0.276]
0.311**[0.125]0.530***[0.038]1.507***[0.086]

1.858***[0.699]0.345[0.219]1.461**[0.665]0.204[0.199]0.489***[0.088]1.056***[0.173]44,546
No
No
0.055

0.541
[1.114]1.031***[0.177]44,546
Yes
No
0.705

-1.657[1.577]0.556**[0.269]44,546
Yes
Yes
0.999

0.060

0.040
0.390

Traditional
gravity variables
RTA dummy
Bilateral investment treaties dummy
GATT-WTO member dummyCommon currency dummy
Distance
Common official language dummyCommon religion dummyColonial relationship dummy
Origin country
Population
Per-capita GDP
Destination country
Population
Per-capita GDP
Number of observations
Origin and destination fixed effects
Country-specific time trend
RESET test p -value
HPC test p -values
Column 1 as Alternative
Column 2 as Alternative
Column 3 as Alternative

0.000
0.000

0.000

Notes: ***, **, and * indicate statistically significant at 1%, 5%, and 10%, respectively.
Standard errors, which are clustered by pairs, are reported in brackets. Observations with thechanges in inward FDI stock from the previous year falling in the top 1% or the bottom 1% of
all observations are dropped. All the models are estimated by PPML.
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment
Database. For other data, see main text.

27

Table 7. Gravity Model Estimation, 1985-2012: Lagged Independent Variables(1)-0.220[0.201]-0.627***[0.121]0.030[0.256]0.203[0.150]-0.558***[0.093]0.729***[0.142]0.654***[0.250]0.549***[0.187](2)
Origin/destination fixed
effect0.271*[0.141]0.194*[0.112]-0.043[0.183]0.352***[0.104]-0.506***[0.068]0.333***[0.093]
1.499***[0.238]0.432***[0.107](3)
Origin/destination fixed
effect0.306**[0.132]0.136[0.113]-0.055[0.172]0.279**[0.109]-0.497***[0.066]
0.337***[0.094]
1.584***[0.236]0.440***[0.106]0.624***[0.041]1.846***[0.083]

1.831***[0.492]0.735***[0.132]0.742*[0.445]0.527***[0.125]0.767***[0.052]0.578***[0.082]55,031NoNo
0.810

1.346**[0.554]0.749***[0.114]55,031
Yes
No
0.280

4.323***[0.800]0.076[0.116]55,031
Yes
Yes
0.997

0.405

0.391
0.159

Traditional
gravity variables
RTA dummy
Bilateral investment treaties dummy
GATT-WTO member dummyCommon currency dummy
Distance
Common official language dummyCommon religion dummyColonial relationship dummy
Origin country
Population
Per-capita GDP
Destination country
Population
Per-capita GDP
Number of observations
Origin and destination fixed effects
Country-specific time trend
RESET test p -value
HPC test p -values
Column 1 as Alternative
Column 2 as Alternative
Column 3 as Alternative

0.000
0.000

0.001

Notes: ***, **, and * indicate statistically significant at 1%, 5%, and 10%, respectively.
Standard errors, which are clustered by pairs, are reported in brackets. Observations with thechanges in inward FDI stock from the previous year falling in the top 1% or the bottom 1% of
all observations are dropped. All the models are estimated by PPML.
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment
Database. For other data, see main text.

28

Table 8. Gravity Model Estimation with Doing Business: 2005-2015

RTA dummy
Bilateral investment treaties dummy
GATT-WTO member dummyCommon currency dummy
Distance
Common official language dummyCommon religion dummyColonial relationship dummy
Origin country
Population
Per-capita GDP
Destination country
Population
Per-capita GDP
Doing-business: Starting business

(1)

(2)

(3)

(4)

(5)

Starting
business

Paying tax

Enforcing
contract

All

Overall

0.314**[0.128]0.071[0.111]0.644***[0.213]0.063[0.138]-0.529***[0.063]0.315***[0.102]
1.649***[0.238]0.464***[0.110]0.314**[0.124]0.06[0.112]0.599**[0.236]0.051[0.139]-0.536***[0.062]0.317***[0.105]1.642***[0.242]0.473***[0.113]0.314**[0.128]0.071[0.111]0.640***[0.213]0.063[0.138]-0.529***[0.063]0.315***[0.102]
1.649***[0.238]0.464***[0.110]0.314**[0.124]0.06[0.112]0.599**[0.235]0.051[0.139]-0.536***[0.062]0.317***[0.105]1.642***[0.242]0.473***[0.113]

0.346***[0.128]0.084[0.119]0.615***[0.218]-0.02[0.148]-0.544***[0.061]0.310***[0.114]1.620***[0.262]0.515***[0.125]0.866[0.697]0.411***[0.110]0.438[0.807]
0.296***[0.101]0.85[0.694]0.421***[0.109]0.433[0.806]
0.299***[0.101]-0.853[1.284]0.1[0.161]-0.506[1.923]0.557***[0.091]
0.002[0.004]1.628[1.721]0.351***[0.094]-0.379[1.824]0.561***[0.090]2.084[1.787]0.352***[0.095]0.007**[0.003]-0.002[0.003]0[0.003]-2.215[3.016]
0.297**[0.146]

Doing-business: Paying tax-0.002[0.003]-0.005[0.003]

Doing-business: Enforcing contract
Doing-business: Overall
Number of observations
Country-specific time trend
Origin and destination fixed effects
RESET test p -value

47,464
Yes
Yes
0.145

40,386
Yes
Yes
0.081

47,464
Yes
Yes
0.158

40,386
No
Yes
0.082

-0.001[0.011]
23,586
No
Yes
0.049

Notes: ***, **, and * indicate statistically significant at 1%, 5%, and 10%, respectively. Standard errors, which areclustered by pairs, are reported in brackets. Observations with the changes in inward FDI stock from the previous
year falling in the top 1% or the bottom 1% of all observations are dropped. All the models are estimated by
PPML.
Sources: Inward FDI stock and flows data are obtained from the OECD International Direct Investment Database.
For other data, see main text.

29

Table A1. Inward FDI Stocks
AUS AUT BEL CAN CHE CHL CZE DEU DNK ESP EST FIN FRA GBR GRC HUN
1985
22
.
.
63
.
.
.
35
.
.
.
.
.
.
.
.
1986
24
5
.
68
.
.
.
47
.
.
.
.
.
.
.
.
1987
34
6
.
79
.
.
.
61
.
.
.
.
. 101
.
.
1988
52
6
.
94
.
.
.
58
.
.
.
.
. 121
.
.
1989
58
9
. 105
.
.
.
87
.
.
.
.
50 141
.
.
1990
65
11
. 111
.
.
. 115
.
.
.
.
77 194
.
.
1991
68
13
. 116
.
.
. 126
16
.
.
.
89 199
.
.
1992
62
13
. 107
.
.
. 124
.
.
.
3 126 166
.
4
1993
66
13
. 105
37
.
. 124
.
.
.
4 133 172
.
6
1994
83
15
. 109
46
.
. 152
19
.
.
6 162 180
.
7
1995
85
20
. 120
54
.
. 183
.
.
.
8 190 190.
.
1996 100
20
. 129
48
.
. 379
.
.
.
8 198 217
.
.
1997
88
21
. 130
53
.
9 183
.
.
.
9 195 239
.
.
1998
89
24
. 138
66
.
14 24229.
.
16 245 285.
161999 103
22
. 170
71
.
16 26934.
.
18 243 366
.
18
2000
98
30
. 206
84
.
20 31855
1
0
24 258 402
.
17
2001
91
33
. 213
86
.
25 31751.
.
24 291 482
15
19
2002 10843. 225 122.
4 532
63 110.
34 382 495
16
26
2003 157
55. 281 158.
45 68278 298649 536 592
24
39
2004 210
66. 315 193.
57 713 112 342
956 658 676
26
50
2005 16678. 356 164.
60 635 115 380
11
54 372 803
26
48
2006 206 105. 363 23575
80 782 131 455
12
69 498 1083
36
76
2007 281 154. 501 337
93 112 947 158 579
16
89 626 1198
50
932008 219 143 834 425 420
93 113 910 148 581
15
82 566 895
37802009 326 160 969 528 483
57 125 914 153 624
16
84 646 1030
39 102
2010 389 156 931 567 555
70 128 904 140 616
16
84 636 1087
39
90
2011 402 151 995 559 586
93 122 941 135 610
16
88 656 1170
29
82
2012 480 153 916 605 608 104 135 989 145 602
19
94 655 1402
27
952013 429 166 535 646 673 130 117 884
94 59420
74 729 1130
30
962014 448 155 455 619 663 142 114 770
88 55618
78 644 1132
28
942015 433 143. 544 709 148 105.
90 5021771 653 1109
26
74
Notes: Figures are reported in the billions of US dollars.
Sources: Inward FDI stock data are obtained from the OECD International Direct Investment Database.

IRL
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
118
186
214
195
176
164
211
204
253
277
279
369
393
393
430

ISL
.
.
.
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
2
2
7
16
9
9
12
13
10
7
8
7

ISR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
49
36
40
41
44
54
48
.

ITA
15
20
25
31
43
51
53
43
45
50
58
66
65
83
85
95
90
105
177
217
220
291
365
323
360
326
353
372
281
248
241

JPN KOR LUX LVA MEX NLD NOR
5
.
.
.
7
21
.
6
.
.
.
7
29
.
7
.
.
.
9
38
9
9
.
.
.
14
37
9
12
.
.
.
15
44
9
14
5
.
.
20
58
12
18
6
.
.
27
61
15
20
7
.
.
36
62
12
23
7
.
.
39
63
12
27
8
.
.
35
80
15
.
9
17
.
39
96
17
24
11
15
.
43 103
18
24
14
16
.
50 102
19
25
19
19
.
60 125
25
35
29
19
.
75 190
26
46
36
22
.
91 243
28
47
41
24
.
. 282
29
73
44
32
.
. 348
38
82
48
9
.
. 418
42
96
56
46
.
. 466
74
97
62
40
.
. 434
71
102
67
48
.
. 537
88
124
68
62
.
. 758 110
190
70
62
.
. 605 103
189 11473. 340 600 134
205 13467. 387 575.
218 13469. 384 582 165
199 15574. 454 568 195
168 164.
14 480 729 175
169 166.
14 486 671 160
174 169.
14 508 676 130

NZL
.
.
.
.
.
.
.
.
15
21
25
32
27
28
28
25
14
20
27
42
.
52
60
42
52
59
64
87
74
74
63

POL
.
.
.
.
.
.
.
.
.
3
8
11
14
21
25
31
40
46
57
85
89
123
173
159
181
211
198
231
197
177
153

PRT SVK SVN SWE TUR USA
.
.
.
.
. 161
.
.
.
5
. 198
.
.
.
8
. 245
.
.
.
8
. 296
.
.
.
10
. 345
.
.
.
10
. 368
.
.
.
16
. 414
.
.
.
13
. 420
.
.
.
13
. 453
.
.
.
21
. 514
14
.
.
29
. 569
19
.
.
32
. 641
20
.
.
36
. 634
25
.
.
48
. 718
22
.
.
71
. 882
27
4
.
91
19 114730
5.
87
20 114841
8. 112
19 131848
16. 157
33 1391
60
22. 195
38 149257
24. 170
68 1604.
33
9 229
94 1787105
42
14 293 153 1982
92
51
16 28080 2035
106
52
11 319 143 2063
103
50
10 337 187 2266
99
52
11 342 134 2348
10456
12 375 189 2534
124
58
12 375 276 2698
111
50
12 302 180 2879
107.
12 288 147 3118

30

Table A2. GDP
AUS AUT BEL CAN CHE CHL CZE DEU DNK ESP EST FIN FRA
1985 18069
87 363 107
16
28 73062 180.
56 5551986 182
99 120 376 154
18
32 104288 251.
74 775
1987 189 124 150 429 193
21
36 1293 109 318.
92 9381988 236 133 163 506 209
25
36 1396 115 375. 109 1024
1989 299 133 165 564 20228
35 1394 112 414. 119 1030
1990 311 166 206 592 257
32
40 1765 138 535. 142 1275
1991 326 173 211 608 260
36
30 1862 139 576
7 128 1276
1992 325 195 236 590 271
44
34 2123 153 629. 113 1409
1993 312 190 226 575 264
48
40 2069 143 524.
89 1330
1994 323 203 246 576 292
55
47 2206 156 529. 103 1402
1995 368 240 289 602 342
71
60 2591 185 613
4 134 1610
1996 401 237 281 627 330
76
67 2502 188 641
5 132 1614
1997 436 212 254 651 287
83
62 2216 174 589
5 127 1461
1998 399 218 260 631 295
79
66 2240 177 617
6 134 1511
1999 389 217 260 674 290
73
65 2197 178 633
6 135 1500
2000 415 196 237 739 272
79
61 1947 164 595
6 126 1368
2001 378 197 237 733 279
72
67 1948 165 626
6 129 1382
2002 394 213 258 753 301
71
82 2076 179 705
7 140 1500
2003 466 261 319 888 352
78
99 2502 218 907
10 171 1848
2004 613 300 370 1018 394 101 119 2816 251 1070
12 197 2124
2005 693 315 387 1164 408 124 136 2858 265 1157
14 204 2204
2006 747 334 411 1311 429 155 155 2998 283 1264
17 217 2325
2007 853 386 472 1458 477 173 189 3436 320 1479
22 255 2663
2008 1055 428 520 1543 552 180 235 3747 353 1635
24 284 2924
2009 926 398 486 1371 540 172 206 3413 320 1499
20 251 2694
2010 1141 390 484 1614 581 218 207 3412 320 1432
19 248 2647
2011 1388 429 528 1779 696 251 227 3752 341 1495
23 274 2863
2012 1534 408 499 1821 666 266 207 3533 322 1356
23 256 2687
2013 1560 428 525 1827 685 277 209 3730 336 1393
25 267 2806
2014 1455 438 532 1784 703 259 208 3879 346 1381
26 272 2839
2015 1339 377 455 1551 671 241 185 3363 295 1199
22 232 2419
Notes: Figures are reported in the billions of US dollars. Negative values are treated as missing values.
Sources: GDP data are obtained from the CEPII gravity data.

GBR GRC HUN
486
48
21
597
57
24
733
66
26
891
77
29
899
79
29
1067
98
33
1116 10635
1158 117
39
1043 10940
1130 117
43
1236 137
461305 147
46
1439 143
47
1529 145
49
1558 143
49
1549 13147
1529 136
54
1674 153
67
1944 202852298 240 103
2412 248 112
2583 273 114
2963 319 139
2792 355 157
2309 330 129
2408 300 130
2592 289 139
2615 250 127
2678 242 133
2999 236 139
2858 195 122

IRL
21
29
34
38
39
49
50
56
52
57
69
76
83
90
99
99
108
127
163
193
210
231
269
274
234
218
238
222
232
256
284

ISL
3
4
6
6
6
7
7
7
6
6
7
8
8
8
9
9
8
9
11
14
17
17
21
18
13
13
15
14
15
17
17

ISR
24
30
35
44
45
52
59
66
66
75
99
109
113
115
116
131
130
120
125
134
141
152
177
214
206
233
258
257
291
309
299

ITA
451
639
803
889
926
1178
1243
1316
1062
1096
1171
1309
1240
1267
1249
1142
1163
1267
1570
1799
1853
1943
2204
2392
2186
2127
2278
2092
2149
2150
1821

JPN
1385
2051
2485
3015
3017
3104
3537
3853
4415
4850
5334
4706
4324
3915
4433
4731
4160
3981
4303
4656
4572
4357
4356
4849
5035
5495
5906
5954
4920
4596
4123

KOR LUX LVA MEX NLD NOR
104
5. 184 14164
120
7. 129 19877151
9
6 140 24192
202
10
7 183 258 100
249
10
8 223 254 101285
13
7 263 313 118332
14
7 314 322 120356
16
5 364 357 128392
17
4 504 348 118459
18
5 527 373 125559
22
5 344 445 149603
22
6 397 443 160560
19
6 481 410 158
376
20
7 502 431 151486
22
7 579 440 159562
21
8 684 413 168533
21
8 725 426 171609
23
9 742 464 192
681
29
11 713 571 225765
34
14 770 646 260898
37
16 866 672 304
1012
42
20 967 719 3401123
49
29 1043 833 393
1002
55
34 1099 931 454902
50
26 895 858 3791094
52
24 1052 836 421
1202
59
28 1170 894 491
1223
56
28 1186 823 5001305
60
31 1261 854 513
1411
65
31 1298 880 498
1378
58
27 1144 750 387

NZL
24
30
40
45
44
45
42
41
46
55
63
70
65
56
58
52
53
66
87
103
114
110
135
130
119
143
164
171
186
200
174

POL
71
74
64
69
82
65
84
93
94
109
139
157
158
173
168
172
191
199
218
254
304
343
429
530
436
477
524
496
526
545
477

PRT SVK SVN SWE TUR USA
27
.
. 113
67 434739.
. 148
76 459048.
. 180
87 487056.
. 204
91 525361.
. 215 107 5658
79
13
. 258 151 5980
89
14
. 270 151 6174
108
15
. 280 159 6539
95
16
. 210 180 6879
100
20
. 226 131 7309
118
26
21 264 169 7664
123
28
21 288 181 8100
117
28
21 264 190 8609
124
30
22 267 269 9089
127
30
23 271 250 9661
118
29
20 260 267 10285
122
31
21 240 196 10622
134
35
24 264 233 10978
165
47
30 331 303 11511
189
57
34 382 392 12275
197
63
36 389 483 13094
209
70
40 420 531 13856
240
86
48 488 647 14478
262 100
56 514 730 14719
244
89
50 430 615 14419
238
89
48 488 731 14964
245
98
51 563 775 15518
218
93
46 544 789 16163
227
98
48 580 822 16768
230 101
50 574 799 17393
199
87
43 496 718 18037

31

Table A3. Inward FDI FlowsAUS AUT BEL CAN CHE CHL CZE DEU DNK ESP EST FIN FRA GBR GRC HUN IRL
ISL ISR
1985
2 .
.
1 .
.
.
1
0
1 .
0
2
5 .
.
0 .
.
1986
2 .
.
2
0 .
.
2
0
2 .
0
2
7 .
.
0 .
.
1987
1 .
.
6
1 .
.
3
0
4 .
0
4
13
1 .
0 .
.
1988
5 .
.
5
0 .
.
4
1
5 .
0
7
20
1 .
0
0 .
1989
8 .
.
3
0 .
.
7
1
7 .
0
9
27
1 .
0
0 .
1990
5 .
.
5
3 .
.
5
1
12 .
1
8
28
1 .
0
0 .
1991
5 .
.
2
1 .
.
6
1
10 .
0
10
15
1 .
0
0 .
1992
4 .
.
3
1 .
.
3
1
10 .
0
14
15
3 .
0
0 .
1993
4 .
.
4
0 .
1
5
2
12 .
1
10
14 .
.
0
0 .
1994
4
0 .
8
4 .
1
8
5
13 .
2
10
9 .
.
0
0 .
1995
3
0 .
6
3 .
2
14
4
11 .
1
22
23 .
.
0
0 .
1996
9
0 .
8
3 .
1
13
1
12 .
2
22
25 .
.
1
0 .
1997
7 .
.
10
6 .
1
14
3
12 .
2
21
32 .
.
1
0 .
1998
6 .
.
18
9 .
3
29
6
10 .
13
25
67 .
.
.
0 .
1999
6
3 .
25
13 .
5
66
11
19 .
5
34
91 .
3 .
0 .
2000
7
10 .
18
19 .
5 199
32
39 .
9
41 112 .
.
.
0 .
2001
4
6 .
32
10 .
6
46
12
28 .
4
52
52
1
4
16
0 .
2002
14
2
21
19
8 .
1
56
8
41 .
8
50
28
0
2
23
0 .
2003
14
8
44
5
16 .
3
53
3
28
1
4
42
19
1
4
29
0 .
2004
43
4
53
6
8 .
5
31
5
31
1
4
42
46
2
4
21
1 .
2005
14
11
32
18
21 .
11
79
15
28
3
6
34 188
2
8
13
0 .
2006
20
10
62
41
32
7
7
62
12
33
2
8
34 152
6
9
18
4 .
2007
35
44 101
70
40
13
12
89
16
68
3
13
71 175
3
10
44
9 .
2008
47
16 200
29
33
14
8
56
10
88
2
9
58
95
6
10
27
1 .
2009
39
11
81
14
72
11
6
37
7
35
2
6
40
94
3
13
52
1 .
2010
36
10
85
17
24
13
10
70
4
55
2
10
39
63
2
10
58
0
3
2011
63
27 139
22
28
23
7
83
11
48
2
6
42
74
3
11
18
1
5
2012
55
9
30
24
26
28
11
48
8
31
2
8
34
58
3
19
48
1
4
2013
56
13
30
40
37
20
9
61
6
22
1 .
51
40
3
6
51
0
8
2014
46
11
25
20
36
22
10
49
5
27
1 .
30
52
3
10
56
1
3
2015
31
6
76
35
49
8
5
39
6
15
1 .
54
66
2
8
40
1 .
Notes: Figures are reported in the billions of US dollars. Negative values are treated as missing values.
Sources: Inward FDI flow data are obtained from the OECD International Direct Investment Database.

ITA
1
1
3
4
5
6
1
2
3
2
4
3
2
3
6
13
12
14
16
18
22
40
40
38
33
21
42
27
28
30
27

JPN KOR LUX LVA MEX NLD NOR
1
0 .
.
3
1 .
1
0 .
.
4
2
1
1
1 .
.
3
2
1
3
1 .
.
3
3
1
2
1 .
.
4
4
1
2
1 .
.
3
7
2
4
1 .
.
5
3
1
3
1 .
.
8
5
1
3
1 .
.
7
7
2
4
1 .
.
12
5
2
3
1 .
.
8
10
2
6
2 .
.
8
12
5
4
3 .
.
11
12
5
8
5 .
.
7
22
4
11
10 .
.
14
41
6
17
7 .
.
21
64
7
15
4 .
.
30
53
2
11
3 116 .
24
28
1
11
4
89 .
19
28
2
33
8
86 .
25
15
6
6
7 118 .
24
46
3
6
6 131 .
2225
7
22
4 227 .
32 140728
9 217 .
294415
14
7 213 .
1850
45
16
9 162 .
2726
28
8
10 315 .
2640 .
11
13 475 .
21
24 .
6
7 .
1
48 134 .
17
7 .
1
27
81 .
12
5 .
1
33
86 .

NZL POL
0 .
0 .
0 .
0 .
0 .
2 .
2 .
2 .
2
1
3
1
3
3
4
4
2
5
3
6
3
7
2
9
1
6
2
5
5
5
7
13
3
10
7
20
2
23
2
16
1
15
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14
5
31
5
15
4
10
4
19
2
15

PRT SVK SVN SWE TUR
0 .
.
0 .
0 .
.
1 .
0 .
.
0 .
1 .
.
1 .
1 .
.
1 .
2 .
.
2 .
2 .
.
6 .
2 .
.
3
1
1 .
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3
1
1 .
.
6
1
1 .
.
12
1
2 .
.
5
1
2 .
.
9
1
2 .
.
17
1
2 .
.
19
1
7
2 .
17
2
6
1 .
13
3
2
4 .
13
1
3
2 .
11
1
4
3 .
13
2
5
3 .
14
7
11
5
1
31
18
6
4
2
20
19
5
5
2
50
17
6
3
0
16
7
5
3
1
12
7
10
4
1
27
14
11
3
1
28
11
5 .
0
20
11
7
2
2
24 .
10 .
2
28 .

USA
19
35
62
57
65
44
32
20
50
42
55
87
91
164
260
269
162
81
76
149
121
230
240
319
162
230
236
216
222
263
363

32