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MACROECONOMIC VOLATILITY, FINANCIAL LIBERALIZATION,
AND THE DIRECTION OF CAPITAL FLOWS IN THE REGION
ASIA-PACIFIC
INTRODUCTION
Since 1990, the presence of economic globalization has increased transactions in global
financial markets as well as market transactions of goods and services between countries
(Rajan 2001). The freer world financial market transactions began around the mid-1980s. The
freedom of financial market transactions is characterized by the movement of increasingly
free capital flows in the industrialized countries, especially countries in Europe and the United
States. The increasing degree of liberalization of the financial sector in the industrialized
countries has then spread to various regions of the world, especially countries in the Asia-
Pacific region. Chinn and Ito (2007) revealed that since 1970 based on the characteristics of
the group of less developed countries, the openness of the financial sector in the Asia-Pacific
region has the highest degree of financial openness compared to other geographical areas. The
fact of the increasingly free movement of international capital flows in the Asia-Pacific region
according to Borensztein (2011) is characterized by the mobility of capital that is increasingly
moving freely and openly between each country. The free mobility of capital then makes most
of the liabilities of companies and banks in the Asian region begin to be dominated by various
foreign currency units.
Figure 1 shows the movement of de jure and de facto financial liberalization data in the
Asia-Pacific region. Financial liberalization which represents the level of de jure financial
liberalization shows the financial liberalization index issued by Chinn and Ito (2007). This
variable calculates the degree of capital account openness to foreign funding in a country.
Meanwhile, financial openness that represents the de jure financial liberalization index is
calculated using the financial openness measure of Lane and Milesi-Ferreti (2006).
Calculation method financial openness is by summing up the total flow of capital in and out
and then dividing by gross domestic product. The degree of financial openness in Asia-Pacific
countries has always increased over time. The movement of the data shows that in 1976 the
average degree of financial openness in Asia-Pacific countries was only 0.45 index units, then
increased by eight times in 2015 by 3.4 index units. Similarly, the degree of financial
56
liberalization shows an increase over time, except in 1997 when it decreased due to the global
financial crisis.
The globalization of the international economy followed by the increasingly free
movement of the financial sector in Asia-Pacific countries is an interesting phenomenon to be
observed. This is mainly because there are various findings that reveal that financial
liberalization followed by trade openness can affect the economic conditions of a country or
region. According to Mirdala, et al. (2015), the development of studies and empirical research
on financial liberalization in the world was initiated due to various important findings
regarding the effect of financial liberalization on the economy. These findings conclude that
the process of capital flow liberalization led by industrialized countries has become a key
driver in improving the efficiency of wealth allocation and sharing financial risks
internationally. The efficiency of wealth allocation and international risk sharing will then
affect the growth and stability of the economy. In addition to the benefits of efficient
allocation and sharing of risks internationally, the freer flow of capital across countries w i l l
also determine the returns to the economy and will further affect the risk of volatility of
macroeconomic variables. Ultimately, the risk of macroeconomic volatility will affect
economic growth and indirectly have implications for the level of welfare in an economy.
Empirical studies conducted by Kose et al. (2005) using a wide sample object has
proven that the globalization of the economy marked by an increase in the volume of
international trade and the financial sector has reduced the negative relationship that occurs
between volatility and economic growth. That is, the higher the degree of financial and trade
openness of an economy will further attenuate the negative relationship between volatility and
economic growth. Similarly, research by Bakaert et al. (2006), Ahmed and Suardi (2009),
Pancaro (2010), Tayebi and Torki (2012), Nicolo and Juvenal (2012), and Mirdala et al.
(2015) have found that an increasingly open financial market sector has a positive
contribution in influencing macroeconomic volatility. The existence of an economy with an
increasingly free financial sector will contribute positively by reducing the volatility of output
growth and consumption. These findings are reinforced by Ozcan et al. (2003) who revealed
that the existence of increasingly integrated cross-country capital flows will maintain
fluctuations in macroeconomic volatility variables. This is because the openness of financial
flows will help countries to reduce the volatility of macroeconomic variables access to capital,
thereby increasing the basic variation in a country's production pattern and in turn maintaining
economic stability.
According to Kose et al. (2003), the empirical results on the positive benefits of
57
financial liberalization on macroeconomic volatility in reality are still unjustified. This is
because there is no clear conclusion and there is still much debate about the relationship
between financial liberalization and macroeconomic volatility. The unclear relationship is
thought to be due to the existence of two major forces in financial liberalization. These two
forces may reduce or increase the risk of macroeconomic volatility. On the one hand,
international financial openness may reduce the volatility of macroeconomic variables due to
diversification in risk sharing. On the other hand, financial openness may lead to greater
specialization and thus increase volatility in the domestic economy. In addition, Mirdala et al.
(2015) revealed that in reality the benefits of world financial liberalization are also influenced
by economic conditions in a country. Financial market openness is more beneficial for
developed countries, while it tends to be detrimental for developing countries.
The existence of debatable theories and empirical results regarding the effect of
financial liberalization on macroeconomic volatility makes it important to study the effect of
financial liberalization on macroeconomic volatility in the Asia-Pacific region. This is
because the Asia-Pacific region is still dominated by less developed countries. Therefore, this
study can ultimately provide an important conclusion whether global financial liberalization
will provide benefits in the Asia-Pacific region or vice versa. Various unclear conclusions
about the impact of financial liberalization on macroeconomic volatility are important
additional points in this study. The aggregation properties of gross capital flows as a measure
of the financial liberalization index essentially mask the effects based on the direction of
capital inflows and capital outflows. Kose et al. (2009) added that in order for research on the
effect of financial liberalization to explain the phenomenon comprehensively, the effect of
different directions of financial capital flows should be considered. This is in order to explain
in detail the possibility of a different potential impact on the direction of capital inflows or
capital outflows on macroeconomic volatility. This study, based on the above issues, will not
only show the relationship between financial liberalization and macroeconomic volatility, but
will also show the contribution of capital flow direction in influencing macroeconomic
volatility in the Asia-Pacific region.
The macroeconomic volatility variables examined in this study will be more detailed
when compared to other studies. If various studies generally only look at the effect of
liberalization and financial openness on output and consumption volatility, then this study
looks at the effect of financial openness liberalization in terms of output volatility,
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consumption and investment. The effect of financial liberalization on investment volatility
may occur because the presence of financial liberalization will increase international capital
flows that move across borders. Then, the existence of cross-border capital flows allows the
process of substitution between domestic investment and foreign investment, and will
eventually affect the volatility of domestic investment (Backus et al. 1992).
In addition, there is an expansion of macroeconomic volatility variables by including
investment volatility variables because investment volatility is an important variable and has a
large contribution to an economy. As Dornbusch et al. (2011) who revealed that there is a
fundamental difference between fluctuations in consumption and investment. Fluctuations in
consumption are proportionally smaller when compared to fluctuations in output, so
consumption which is a large part of output is relatively more stable. Meanwhile, investment
is theoretically more volatile and until now the effect of investment volatility has been
responsible for the large fluctuations in output through the business cycle. Given these
considerations, the effect of financial liberalization on investment volatility will also be
included. This leads the researcher to expand the macroeconomic volatility proxies under
study by dividing them into three parts, namely: output, consumption and investment
volatility. We then examine how financial liberalization and capital flow direction relate to
these three macroeconomic volatility proxies in the Asia-Pacific region.
Problem Formulation
The development of research on factors affecting macroeconomic volatility was initially
due to important findings by Ramey and Ramey (1995). The study has successfully revealed
the detrimental effects of macroeconomic volatility on the economy. The empirical results
concluded that there is a significant negative relationship between output volatility and
growth. This indicates that countries with high volatility have low economic growth, and vice
versa. Not only output volatility has an important influence on economic growth.
Macroeconomic volatility such as consumption and investment also play a big role in
influencing an economy. Although in theory, investment volatility plays a more important
role in the economy when compared to consumption volatility. Dornbusch et al. (2011)
explained that fluctuations in consumption are relatively more stable, while fluctuations in
investment are theoretically more volatile. In addition, the role of investment volatility on
output growth is greater than that of consumption volatility. Through the business cycle,
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investment volatility is more responsible than consumption volatility in influencing the
magnitude of fluctuations in GDP (gross domestic product).
The research of Ramey and Ramey (1995) and the argument of Dornbusch et al. (2011)
leads to the conclusion that macroeconomic volatility that affects economic growth indirectly
plays a role important role in the economy. This is because the risk of macroeconomic
volatility that affects economic growth will ultimately have implications for welfare levels.
The existence of this empirical relationship makes the basic foundation developed by Kose et
al. (2005) to test the relationship between output volatility and growth in the context of
globalization marked by the phenomenon of trade openness and financial integration using a
sample of many countries. The results show that the interaction between financial integration
and trade openness on output volatility has attenuated the negative relationship between
output volatility and growth.
In the relationship between financial integration and economic volatility, Kose et al.
(2003) revealed that international financial integration is believed to have two main potential
benefits, viz: It improves the global allocation of capital and helps countries better share the
risks of their domestic economies. Ultimately, the benefits of financial integration will reduce
macroeconomic volatility. An economy with well-integrated financial markets will give hope
to every economic actor that the country has stable macroeconomic conditions. Stable
fluctuations in macroeconomic variables will lead to lower risk in the economy as a whole,
due to the diversification of internationally shared risk. A broad review of the literature finds
it difficult to conclude that financial liberalization actually reduces macroeconomic volatility.
There are even some studies that find the opposite result, where international financial
liberalization can increase macroeconomic volatility.
Easterly et al. (2001) have examined the factors of volatility using a large sample and
found that a growing financial system will result in financial openness, thus increasing the
risk of an increase in the volatility of output growth. Kose et al. (2003) have examined the
impact of financial integration on macroeconomic volatility using a large sample. The results
show that an increase in financial openness is associated with a relative increase in
consumption and income volatility. Neaime (2005) indicated that financial openness has a
positive and significant relationship with GDP volatility, total and private consumption in
Middle East and North Africa (MENA). Indicates that financial openness has a positive and
significant relationship effect on GDP, total and private consumption. Mujahid and Alam
(2013) have examined the relationship of financial openness and trade to macroeconomic
volatility in Pakistan. Financial openness is associated with a positive effect on output and
60
consumption volatility in Pakistan.
Mirdala et al. (2015) have examined the relationship between international financial
integration and fluctuations in output. The results showed that the relationship between
financial openness and economic development in developed countries seems to be irrelevant.
As a result, the effect of financial integration on macroeconomic volatility disappears over
time. Vice versa, the impact of financial openness on macroeconomic volatility in advanced
economies disappears over time developing countries has a negative effect. Financial openness
has led to greater macroeconomic volatility in developing countries.
The type of financial disclosure and the presence of other country-specific
characteristics may also be meaningful in providing different results. Kose et al. (2005)
concluded that financial and trade openness have a positive effect on the economy by
weakening the negative relationship of output volatility to economic growth. These important
findings have made the study of financial and trade openness more developed. Ahmed and
Suardi (2009) by developing research from Kose et al. (2003) examined the effect of trade
and financial liberalization on macroeconomic volatility in Sub-Saharan Africa. The results
show that increased financial openness in the African region leads to lower volatility in output
and consumption. This is in contrast to relevant theoretical hypotheses that have predicted that
trade openness would result in greater macroeconomic instability in Africa. Bakaert et al.
(2006) have examined the impact of equity market liberalization and capital account
openness on consumption growth volatility. They found that financial liberalization is
associated with lower output growth volatility. Similarly, Nicolo and Juvenal (2012) revealed
that financial integration and globalization are associated with higher growth and lower
growth volatility.
The different empirical results of studies on the relationship between financial
disclosure and macroeconomic volatility have raised debates and have not been able to
provide clear conclusions. This suggests that aggregation studies have generally overlooked
important structural details. In fact, a more focused study could potentially explain the mixed
results on the impact of financial liberalization on macroeconomic volatility. Kose et al.
(2009) have investigated the possibility that capital flows (capital flows in assets and
liabilities) and different types of capital flows (i.e., equity and debt) may be important points
of reference for discerning potentially different effects on macroeconomic volatility. Capital
flows The method used focuses on the level of external assets (capital outflows) and the level
of external liabilities (capital inflows). The existence of different types of capital flows such
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as equity and debt may also have an effect on economic volatility. Equity may be more
conducive to ex-ante risk sharing, while debt may be more helpful for ex-post consumption
smoothing.
This is as the theory explains capital outflows driven by domestic capital holders buying
foreign assets will create variation in handling risk from the home country. Moreover,
domestic investors may be able to increase the return to a given risk by increasing the amount
of capital inflows in buying external assets. Domestic financial assets held offshore will help
domestic capital holders spread the risk of their wealth to deal with the loss of output shocks
in the home country, where each asset holder will still get income from outside the country. It
can be concluded that the presence of large external assets may be associated with low
fluctuations in macroeconomic variables. In contrast, external liabilities are predicted to affect
economic volatility in a different direction. Capital-receiving countries experience capital
inflows, which in turn increase their own specific risk with additional risk from the capital-
giving country. The additional risk may be due to capital flight and negative events due to
global shocks. Large external liabilities are then associated with large economic volatility.
The possibility of different effects of capital inflows and capital outflows on
macroeconomic volatility. Therefore, this study will focus on an observation of financial
liberalization and openness in the Asia-Pacific region while considering the different effects
of different directions of capital flows on the volatility of macroeconomic variables. Capital
outflows are represented by total external assets, external equity assets and external debt
assets. The presence of capital outflows theoretically tends to be associated with low volatility
of macroeconomic variables. Meanwhile, the presence of capital inflows depicted by total
external liabilities, external debt liabilities and external equity liabilities will theoretically tend
to be associated with high volatility of macroeconomic variables.
Research related to the effect of financial openness on the volatility of macroeconomic
variables by dividing it into the volatility of output, consumption and investment and focusing
on the direction and type of direction of different capital flows is still not much done. In
addition, the differences in empirical results of various studies related to the effect of financial
liberalization on the volatility of macroeconomic variables make research that specializes in
specific objects in a particular region urgent to do. The existence of various problems above,
this study focuses on an important problem formulation to see the effect of financial openness
by focusing on the direction of capital flows (capital inflows and capital outflows) on
macroeconomic volatility in the Asia-Pacific region. Based on the description above, the core
issues that can be raised in this study are:
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International Capital Markets and Profits from Trade
Before the advent of open capital flows across countries, there was a process of
financial integration in various regions of the world. The discussion of the benefits of
international trade concentrated only on exchanges involving goods and services. The
provision of a global payment system for trade in goods and services has lowered transaction
costs, and banks have become active in international capital markets in order to expand the
benefits of such exchanges. However, the supply side of international asset trading may be
limited to capital markets between nationals of different regions. Although asset trading is
sometimes viewed as a means of speculation, the benefits of asset exchange transactions can
essentially make consumers everywhere who participate in capital market activities better off.
Essentially, all transactions that take place between residents of a country fall into one
of three types of categories: trade in goods or services for goods or services, trade in goods or
services for assets, and trade in assets for assets. At any given time, a country generally only
conducts trade in each of these categories. Figure 2 assumes. There are two countries, namely
domestic and foreign countries, which illustrate three types of international transactions. Each
of them involves different rules of trade benefits. The first trade advantage is that countries
can benefit by concentrating on their more efficient production activities and using some of
their output to pay for the import of other products from abroad. This type of trade advantage
involves exchanging goods or services for other goods or services. This is shown by the upper
horizontal arrow indicating the exchange of goods and services between home and abroad.
The second trade advantage is the advantage that results from intertemporal trade,
which is the exchange of goods and services for claims of future goods and services, i.e. for
assets. When a developing country borrows abroad (for example, selling bonds to foreigners),
the existence of such transactions can help developing countries import raw materials for
domestic investment and development projects. Such exchange activity is involved in
intertemporal trade. The borrowing country benefits from this trade because it can undertake
projects that cannot easily be financed through domestic savings, while the lending country
benefits because it gets assets that generate higher returns than those available in its own
country. The diagonal arrows in Figure 1 show trade in goods and services for assets. The
horizontal arrows represent the last category of international transactions which is asset-for-
asset trade. An example is the exchange of real estate located in one country for bonds in
another country. This would involve active balance of payments capital outflows and inflows.
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The large volume of assets traded between countries is because international asset trading
creates international risk sharing and improves the efficiency of wealth allocation between
countries. This can be beneficial for all countries involved.
Portfolio Diversification as a Motive for International Asset Trading
International trade in assets can enable both parties to trade better, by allowing them to
reduce the risk of return on wealth. Asset trading can reduce economic risk by allowing both
parties to diversify their wealth in various forms in their portfolios across a wider spectrum of
assets. Such diversification thus reduces the amount of money that has gone up in each
individual asset. This is in line with the words of one economist who described the idea of
portfolio diversification, "don't put all your eggs in one basket." When a country's economy is
opened up to international capital markets. It can reduce the high risk of its wealth by placing
some of its returns in different baskets (portfolio diversification). This reduction in risk is the
basic motive for asset trading. The main function of international capital markets is to
diversify the share of risk that is expected to arise.
International asset trading can exchange a wide variety of assets. Among the many
assets traded on international capital markets are bonds and deposits denominated in different
currencies, stocks, and more complex financial instruments such as shares or currency
options. The purchase of foreign real estate and the direct acquisition of factories in other
countries are other ways to diversify assets abroad. Asset trading is often useful for making a
distinction between debt and equity instruments. Bonds and bank deposits are debt
instruments, as they specify that the issuer of the instrument must pay a fixed value with
additional interest regardless of the state of the economy.
In contrast, a piece of stock is an equity instrument, which is a claim to the company's
profits, not to a fixed payment, and whose yield will vary according to circumstances. By
choosing how their portfolios are allocated between debt and equity instruments, individuals
and countries can manage to stick with their desired levels of consumption and investment,
although different outcomes are possible. The dividing line between debt and equity is not a
pure one in practice. Even if the money instrument of payment is the same in different
countries of the world, the actual payout in a particular country will depend on the national
price level and exchange rate. Payouts as the instrument has been promised and made are
unlikely to occur in the case of bankruptcy, government seizure of foreign-owned assets, and
so on. Assets such as low-grade corporate bonds, which appear to be non-recourse to debt,
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may in reality be equity-like in that they provide a payout that depends on their financial
condition and profitability, albeit sometimes dubious due to increased risky investments.
Measures of Financial Liberalization and Openness
One of the most important ways to see the role of international capital markets on the
economy is to measure a country's financial openness in international capital markets on a
measurable data. Eichengreen (2001) revealed that the importance of making a quantitative
assessment of the impact of financial globalization is to understand the impact of financial
openness and integration on the economy. According to Quinn et al. (2011) the types of
financial integration measures can be grouped into 3 categories: de jure, de facto and hybrid
indicators as well as combination of the two forms of measures. The IMF's Annual Report on
Exchange Arrangements and Exchange Restrictions (AREAER) is the primary source for
most de jure indicators of financial disclosure.
Indicators of de jure Financial Liberalization
The IMF binary table indicator is the beginning of the economic openness indicator
which is converted into a dummy number of size 0/1. Researchers commonly use this variable
as a proxy for capital restriction. This variable symbolizes the number 0 for countries where
there are barriers in the capital market, while the number 1 indicates countries that are free of
barriers in the capital market. Quinn et al. (2011), explained that many researchers have
developed IMF binary indicators, such as: Epstein and Schor (1992) who have developed one
of the main indicators of capital restriction created by AREAER for 16 OECD countries
during the period 1967-1986. Alesina, Grili and Milesi-Ferretti (1994), Garet (1995) who
have each used categorical measures from the AERAER tables for a regression relationship
analysis. Edison and others (2004) and Klein (2003) used a rolling average of IMF binaries
over several years as a proxy.
The level of information released by AREAER in measuring capital restriction has
some limitations and weaknesses. This is due t o their binary nature. For example, the IMF
binary divides countries into groups of equal size at 0/1 for partially open countries,
substantially open but not fully open countries, and completely closed countries. Hence, it
may introduce a systematic size error in the regression development when used as an
independent variable (Voth 2003). A further weakness is that the availability of provisional
data is limited in the published tables to the 1996 volume only. The publication of the updated
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table format for 1996 in the 1997 volume represents a more in-depth enrichment of the
information available in table format. The structure of AREAER after 1997 captures a broader
dimension of the barriers index than just capital proxies, including by investor type and asset
category. The new 1997 table reports on 13 separate aspects of capital account transactions
and highlights cross-country variation in the choice of the composition of restrictions.
The latest format was enriched from 1996 in the 1997 volume which spurred the second
generation measure. Tamirisa (1999), Johnston and Tamirisa (1998) summarized binary
scores for 13 categories across 40 countries in 1996. Miniane (2004) has averaged the 13
scores in the categories and extended the time period from 1983 to 2000, although the country
information is essentially more limited in scope and less detailed, including the inability to
distinguish between capital inflows and outflows. Chinn and Ito (2007) using the AREAER
table have produced KAOPEN to identify the breadth of financial globalization indicators that
rely on data reduction counts. They used principal component analysis on three categorical
financial indicators of current account restrictions (current account capital constraints, export
proceeds conditionality constraints and several proxies for current account restrictions)
exchange rate) plus shares, which are taken as a rolling average of the IMF binary. KAOPEN
is the main basic standardized component of the four AREAER table variables, where the
highest score indicates greater financial openness.
In various studies, there are considerable differences regarding the determination of de
jure size in the field of analysis conducted. Ahmed and Suardi (2009), Kose et al. (2003)
(2005), Neaime (2005) used the de jure size using the binary size of AREAER. Bakaert et al.
(2006) use a measure of capital account openness by considering two measures, namely the
binary measure of AREAER and Quinn (1997), Quinn and Toyoda (2003). Then, Mirdala et
al. (2015) used the Chinn and Ito (2007) index in their research analysis. From various
previous research studies, this research uses the approach of Mirdala et al. (2015) approach in
measuring de jure financial liberalization by using the KAOPEN index from Chinn and Ito
(2007). This is because the conventional capital control measures used by AREAER fail to
account for the intensity of capital controls over time. The KAOPEN index is used because it
incorporates a wider range of measures in one index, namely: (1) variables indicating the
presence of multiple exchange rates, (2) variables indicating current account constraints, (3)
variables indicating capital account constraints, and (4) variables indicating the delivery
terms of the export process. In addition, the Chinn and Ito indices also have a good correlation
with other index measures.
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De Facto Indicator Measures
The de jure financial globalization index does not reflect the extent to which capital
flows actually evolve in response to legal barriers, either because of the absence of
enforcement, or because controls in one area may stimulate a response in other asset flows. In
fact, the index is more disaggregated and does not capture important differences, but only in
describing a country's capital control regime. De jure measures therefore do not necessarily
reflect the capital flow activity that actually occurs due to financial openness. It can be seen
that countries with relatively high capital barriers have become substantially more financially
integrated in recent decades. As such, the existence of de facto measures is one alternative
way of presenting a measure of a country's integration into global financial markets. These
can be divided into three categories: quantity-based, price-based and hybrid measures.
Among quantity-based measures, the total index developed by Lane and Milesi-Ferreti
(2006) is the most widely used de facto measure is used in measuring a country's financial
openness to international financial markets. The total index is calculated as the aggregation of
a country's assets plus liabilities relative to gross domestic product and includes the categories
of portfolio equity, FDI, debt, and financial derivatives, as well as assets and liabilities. Other
de facto indicators exploit the observed phenomenon of increased capital mobility, such as
measures of gross capital flows (IMF 2001). However, a measure of capital flows is more
volatile, and thus more problematic, than a measure based on an index of total measured
capital. The widespread trend of calculations as a measure of international financial
integration according to Lane and Milesi-Ferreti (2006) is to use the following formulation:
One possible reason is the rise in international financial cross-holding due to the
increase in international trade, which has also become substantial in recent decades. That is,
IFI and GEQY which are measured as the ratio of exports plus imports to GDP (IFITRADE,
GEQTRADE) have increased following international trade in assets which has grown much
faster than trade in goods by that measure. In this study the de facto measure uses the measure
from Lane and Milesi-Ferreti (2006) which has been widely used by various other researchers
such as Bakaert, Harvey and Lundblad (2006), Kose, Prasad and Terroness (2003) (2005),
Neaime (2005), Mirdala et al. (2015), Abiad, Leigh and Mody (2009), Nicolo and Juvenal
(2013), Ko (2007), and Mujahid and Alam (2013).
UNCTAD has previously provided two other quantity measures, using FDI flows and
stock inflows from 1970 and 1980 (respectively) onwards for a subset of UN countries. The
data can then be normalized to a country's GDP (LNFDIGDP) or share of FDI flows to the
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world (LNFDIW). However, according to Quinn et al. (2011) some de facto indicators have
certain limitations. Users of indicators that rely solely on FDI measurements such as those by
UNCTAD face the problem of inconsistency in reporting and treatment of FDI between
countries over time. A meaningful comparison of FDI data within a panel is thus very
difficult. A very relevant concern for the UNCTAD measure. De facto measures are also
associated with imperfect conditions under which government policies are implemented.
Financial Liberalization and its Benefits
Baele et al. (2004) have also considered three broad benefits associated with
increasingly integrated finance: opportunities for risk sharing and diversification, better
allocation of capital among investment opportunities and the power for greater growth, and
finally to consider financial development as a beneficial consequence of integrated finance.
Risk Sharing
Economic theory predicts that financial integration has an influence in facilitating risk
sharing. Integration in large markets or even the formation of large markets is beneficial for
firms. According to Baele et al. (2004) financial integration provides additional opportunities
for firms and households to share financial risks and temporally smooth consumption.
Financial integration allows project owners with low initial capital to turn to intermediaries
who can mobilize savings to cover initial costs. Economies of scale can enable firms,
particularly small and medium-sized firms that face credit constraints, to have better access to
broader financial or capital markets.
Risk-sharing opportunities make it possible to finance very risky projects with
potentially very high returns, as the availability of risk-sharing opportunities improves
financial markets and allows investors to avoid risk and hedge against negative shocks.
Because financial markets and institutions can handle credit risk better, financial integration
can also eliminate certain forms of credit constraints faced by investors. The law of large
numbers ensures a reduction in credit risk as the number of customers increases. Individual
risk will also be minimized by financial integration in a large market, while at the same time
increasing portfolio diversification.
Through risk sharing, financial integration leads to specialization of production within a
region. In addition, financial integration also increases portfolio diversification and sharing of
indiosyncratic risks across regions due to the availability of additional financial instruments.
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This It allows households to hold a more diversified equity portfolio, and in fact to diversify
their share of the increased risk of country-specific shocks. In the same way, it allows banks
to diversify their loan portfolios internationally. This diversification will help households to
cushion country-specific income shocks, so that shocks to domestic income will not affect
domestic consumption, as it has been diversified by lending or investing abroad Jappelli and
Pagano 2008).
Increased Capital Allocation
This is in line with Levine's (2001) view that greater financial liberalization will be
followed by a better allocation of capital. An integrated financial market removes all forms of
impediments to trade in financial assets and capital flows, thus allowing for the efficient
allocation of financial resources for investment and production. In addition, investors will be
allowed to invest their funds anywhere for more productive use. More productive investment
opportunities will therefore become available to some or all investors and a reallocation of
funds to increasingly productive investment opportunities will take place (Baele et al. 2004).
Kalemi-Ozcan and Manganelli (2008) point out that with open access to foreign markets,
financial liberalization will give agents a wider range of financing sources and investment
opportunities, and allow the creation of deeper and more liquid markets. This provides more
information to be pooled and processed more effectively, and capital can be allocated in a
more efficient manner.
Financial Development
According to Hartmann et al. (2007) financial development can be explained as a
process of increasing financial innovation, institutions, and organizations in the financial
system. This combination of processes has the effect of reducing asymmetric information,
increasing the perfection of markets and contractual possibilities, as well as reducing
transaction costs and increasing competition. Japelli and Pagano (2008) show that the main
channel through which the removal of barriers to integration can spur domestic financial
development is through enhanced competition or lower costs in intermediation with foreign
sources of finance. These competitive pressures bring lower costs of financial services to
firms and households from countries with less developed financial systems and therefore
expand local financial markets.
The relationship between financial development and financial liberalization is the most
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important as there is strong evidence that financial development is associated with increased
economic growth (Baele et al. 2004). As described in Levine (1997), financial systems serve
several basic purposes. These include: (1) lower uncertainty by facilitating trade, hedging,
diversification, and risk pooling, (2) allocate resources, and (3) mobilize savings. These
functions Financial integration can influence economic growth through capital and technology
accumulation in an intuitive way. Trichet (2005) argues that financial integration promotes
financial development, which in turn creates the potential for higher economic growth.
Financial integration enables the realization of economies of scale and increases the supply of
funds for investment opportunities. Actually the integration process also stimulates
competition and market expansion, thus leading to further financial development. In turn,
financial development can result in a more efficient allocation of capital with a reduction in
the cost of capital.
Previous Research
This study is primarily intended to analyze the effect of financial liberalization on
macroeconomic volatility by considering the additional influence of capital flow direction.
The issue of the effect of financial liberalization on macroeconomic volatility with specific
objects has been studied by many researchers before. The results of various studies in Table 4
show that the presence of financial liberalization is not always followed by low volatility of
economic variables, even the opposite effect of financial liberalization in some specific cases.
The existence of various results is possible due to the different effects of the direction of
capital flows that move differently on macroeconomic volatility in an economy. Some
previous studies used as references in conducting research include:
Data Analysis Method
Research on the effect of financial liberalization and openness on macroeconomic
variables (output, consumption and investment) using dynamic panel data method. Research
on the effect of financial liberalization on the volatility of macroeconomic variables will also
be considered based on different directions and types of capital flows in Asia-Pacific. The
software used in this research is Microsoft Excel 2010, and STATA 11.
Exploratory Analysis of Data
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According to Nazir (1999), exploratory analysis is an analysis in examining a group of
objects, a condition, a system of thought, or a class of events in the present. The purpose of
this analysis is to make a descriptive, systematic description or painting that is factual about
the facts and properties and relationships between phenomena that occur. The form of
exploratory analysis in this study is to study the relationship between financial integration and
financial liberalization variables on the volatility of macroeconomic variables (output,
consumption and investment) in Asia-Pacific countries in the period 1976-2015.
Panel Data
Panel data is one type of data that can be used in the analysis of panel data regression
models, or also called pooled data (pooling of times series and cross-section observations) a
combination of time series and cross-section data. Cross section data is data collected at one
time on many individuals, companies, countries and others. Time series data is data collected
over time on an individual. Using panel data has several advantages. According to Hsiao in
Firdaus (2011) some of the advantages of using panel data are mentioned as follows:
1. By combining time series and cross section data, the number of observations becomes
larger so that the estimated parameters will be more accurate,
2. Provides more informative, more varied data, high degrees of freedom which makes the
model more efficient, and reduces collinearity between variables,
3. Panel data is better suited to the study of the dynamics of adjustment, which allows for
the estimation of individual characteristics as well as characteristics over time
separately,
4. It has a better ability to identify and measure effects that simply cannot be detected by
cross section or time series data alone and is able to control for individual
heterogeneity.
Dynamic Panel Data Regression
Panel data analysis can be used in dynamic models i n relation to the dynamics of
adjustment analysis. This dynamic relationship is characterized by the presence of a lag of the
dependent variable among the regressor variables.As an illustration, consider the following
dynamic panel data model:
In the static panel model, it can be shown that there is consistency and efficiency
regarding the treatment of �I in both the fixed effect model (FEM) and the random effect
model (REM). However, in the dynamic panel model, the situation is substantially different,
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as yit is a function of �i and yit-1 is then also a function of �i . On the other hand, �i is a
function of uit , so it will cause the pooled least square estimator (as used in the model of
static panel) will be biased and inconsistent, even if vit is uncorrelated. This results in
endogeneity problems, so that if the model is estimated with a fixed effects or random effects
approach, it will produce biased and inconsistent estimates.
instrument matrix for SYS-GMM is as follows:
Dynamic Panel Model Specification Test
According to Firdaus (2011), some of the criteria used to find the best dynamic model
or GMM are
Unbiased. The pooled least square estimator is biased upward and the fixed effect estimator is
biased downwards. The unbiased estimator is in between.
1. The instrument is valid. The meaning of valid is if there is no correlation between
the instrument and the error component. Validity is checked using the Sargan test. The null
hypothesis of the Sargan test states that the instrument has no problem with validity (the
instrument is valid). The instrument will be valid if the Sargan test cannot reject the null
hypothesis. If the results of the AB-GMM method show that the instrument used is not valid,
the SYS-GMM method is used.
2. Consistency. The autocorrelation test in the GMM approach is used to determine
the consistency of the estimation results. The consistency properties of the obtained estimators
can be checked from the Arellano-Bond statistics m1 and m2 , which are calculated
automatically in some software. The estimator is consistent if m1 indicates the null hypothesis is
rejected and m2 indicates the null hypothesis is not rejected.
Variable and Operational Definition of Financial Liberalization
The specifications used in determining financial liberalization measures are developed
by dividing them into de jure and de facto measures. Some studies have also developed the
concept of dividing de facto and de jure measures of financial openness. This can be seen in
the research of Kose et al. (2003), Kose et al. (2005), Neaime (2005), Ahmed and Suardi
(2009). Where the variable is used by combining from AREAER, Lane and Milesi-Ferreti
(2006) calculation method, Quinn index (1997), Miniane (2004) and Chin and Ito (2007).
However, in this study, the division of financial liberalization follows the research of Mirdala
et al. (2015). The operational definitions of the variables used are as
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Exploratory Analysis of Macroeconomic Volatility Data in the
Asia-Pacific Region
This section explores the movement of growth volatility data of macroeconomic
variables from 1976-2015. Figure 6 shows the data on the movement of volatility of growth of
macroeconomic variables by dividing the Asia-Pacific region into two groups of countries,
namely: developed countries and developing countries. Macroeconomic volatility data in this
study is divided into three groups, namely the volatility of output or income growth (gross
domestic product and gross national product), volatility of consumption growth (private
consumption and final consumption) and volatility of investment growth (gross fixed capital
formation).
Figure 6 shows that in general, volatility movements in both income groups fluctuate
over time. The interesting thing about Figure
6 shows that the volatility of the growth of macroeconomic variables in developing countries
was always higher than that of developed countries in 1976-2003, but after 2003 the position
of macroeconomic volatility was the opposite. After 2003, developed countries have higher
volatility of macroeconomic variables, compared to developed countries developing countries.
This condition occurs both in the volatility of gross domestic product growth, gross national
product, private consumption, final consumption, and gross fixed capital formation.
Another interesting point shown in Figure 6 is that the volatility of the growth of
macroeconomic variables increased in the period 1998-2000. The increase in the volatility of
the growth of macroeconomic variables in that period was due to the financial crisis that hit
the world. The financial crisis eventually increased the instability of economic conditions
shown in each macroeconomic variable. The volatility of gross fixed capital formation
variable growth in the period 1998-2000 experienced a very high increase to touch 0.24. The
volatility value of gross fixed capital formation growth is very high, when compared to the
volatility of other macroeconomic variables.
Financial Liberalization and Openness in the Asia-Pacific Region
This section explores the movement of financial liberalization and openness data from
1976-2015. Figure 7 provides a graph of the development of de jure and de facto financial
liberalization data in the Asia-Pacific region over time. The financial liberalization graph
shows the de jure financial liberalization level, while the financial openness graph shows the
de facto financial liberalization level.
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Figure 7 shows data on the average level of financial liberalization and openness
divided by Asia-Pacific region, Asia-Pacific developed countries and Asia-Pacific developing
countries. This division is intended to be able to see the differences in data on the level of
financial liberalization and openness based on the characteristics of income groups in the
region Asia-Pacific region. In general, Figure 7 shows the pattern of financial liberalization
and openness data on average increasing over time in the Asia-Pacific region, Asia-Pacific
developed countries and Asia-Pacific developing countries. It can be seen that the level of
financial liberalization for data on countries in the Asia-Pacific region averaged in 1975 was
at the level of 0.44, which increased by 0.64 at the end of 2015. There are only a few points
that have decreased and the decline is generally due to the global financial crisis that hit the
world.
Figure 7 also shows that there are differences in data on the level of financial
liberalization between the Asia-Pacific developed countries and Asia-Pacific developing
countries. Data on the level of financial liberalization in the developed countries group shows
a higher level of financial liberalization, when compared to the developing countries group.
This indicates that countries in the Asia-Pacific developed countries region are more open and
have very low financial market barriers to global financial markets, when compared to the
Asia-Pacific developing countries group. Figure 7 also shows that financial openness has
increased over time in the Asia-Pacific region. Financial openness indicates that financial
activity in the Asia-Pacific region towards global financial markets has always increased over
time. It also shows that capital market activities in Asia-Pacific countries are increasingly
integrated with international capital markets.
Financial openness in the Asia-Pacific developed countries group is greater, when
compared to the Asia-Pacific developing countries group. In addition, financial disclosure
activity in the developed countries group is growing very fast compared to developing
countries which only show slow growth in financial activity.
The next section shows the level of financial liberalization in each country that is the
object of research. Figure 8 shows data on the level of financial liberalization divided into
developed countries and developing countries. Overall, the average level of financial
liberalization of countries in the Asia-Pacific region shows 0.61. Based on income
characteristics, countries included in the Asia-Pacific developed countries group show a high
level of financial liberalization 0.82, while countries in the Asia-Pacific developed countries
group show a low rate of 0.39. This is consistent with the explanation of Figure 7 which
shows that on average the level of financial liberalization in the developed countries group is
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very greater when compared to the developing countries group.
Countries in the Asia-Pacific developed countries group that have the highest level of
financial liberalization on average are Canada, United States, Hong Kong and Macao with an
average level of financial liberalization of 1. This means that in these countries domestic
financial market barriers to global financial markets have been removed. Meanwhile, the
country with the smallest level of liberalization on average in the Asia-Pacific developed
countries group is South Korea with an average level of financial liberalization of 0.37. This
means that South Korea has the highest level of domestic financial market barriers to
globalization in the Asia-Pacific developed countries group. In the Asia-Pacific developing
countries group, the country with the highest level of financial liberalization is Indonesia.
Indonesia has an average financial liberalization level of 0.79, which is then followed by
Malaysia and Peru with an average financial liberalization level of 0.79.
0.65 and 0.64. Meanwhile, the country with the smallest level of financial liberalization in the
Asia-Pacific developing countries group is Bangladesh, which is 0.11. This result shows that
from the total number of countries that are the object of research, Bangladesh is a country that
has high domestic financial market barriers to global financial markets.
Data on the level of financial openness is calculated using the financial openness
measure of Lane and Milesi- Ferreti (2006). The method of calculating the variable is by
summing the capital inflows and outflows then divided by gross domestic product. Overall,
the average level of financial openness in the Asia-Pacific region is 1.94. Based on income
groups, namely Asia-Pacific developed countries and developing countries. The level of
financial openness shows a much different figure. The Asia-Pacific developing countries
group has an average level of financial openness of 2.99, while the Asia-Pacific developed
countries group shows an average level of financial openness of 0.77. There is a considerable
difference in the level of financial liberalization in the two groups, with a difference in the
level of financial openness of 2.22. This is also related to the capital flow barriers in Figure 7,
where the Asia-Pacific developing countries group tends to have a large level of financial
market barriers. This is what causes the capital flow activity of the developing countries group
to the market global finance is very low when compared to the group of developed countries.
The countries in the Asia-Pacific developed countries group that have the highest level
of financial openness are Hong Kong, followed by Singapore and Macao at 12.88, 7.98 and
3.09. The lowest level of financial openness is South Korea with a financial openness level of
0.75. This is consistent with the condition of the level of financial liberalization in Figure 7,
where the high level of financial liberalization in Hong Kong indicates low global financial
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market barriers followed by high activity in international financial markets. Meanwhile, the
liberalization data of the Asia-Pacific developing countries group shows interesting results.
The highest level of financial openness is found in Malaysia, followed by Philipiness and
Thailand with average financial openness levels of 1.53, 1.03 and 0.95. The country with the
lowest level of financial openness in the Asia-Pacific developing countries group is India with
an a v e r a g e financial openness level of 0.38.
The interesting thing about this analysis is that the indicator of financial liberalization
does not determine the level of financial openness of a country. This can be seen in the
condition of the level of financial liberalization and openness in Indonesia. Indonesia has a
high level of financial liberalization in Figure 8, but the level of financial openness and
activity in Indonesia towards global financial markets is still low when compared to
Malaysia, Philiphiness and Thailand. This important difference is one of the reasons why this
study uses two indicators to measure the level of domestic financial liberalization towards
global financial markets. The indicator based on financial barriers depicted in Figure 8 and the
indicator of financial openness depicted in Figure 9. The use of these two indicators is based
on the reason to complement the weaknesses of each existing measure (Quinn et al. 2011).
Development of the Direction of Capital Inflows and Outflows in the Asia-Pacific Region
Figure 10 explains the development of total accumulated capital inflows and outflows in
the Asia-Pacific region by summing up all research objects in 19 countries in the 1976-2015
period. The accumulated capital flows used in the analysis of this study are total capital
inflows and outflows, namely total external liabilities and total external assets. In addition, the
total capital flow is also divided into debt and equity capital flows. Where for the incoming
and outgoing debt capital flows, namely external debt obligations and total external debt
assets. Likewise, the equity capital flow is divided into two, namely total external equity
liabilities and total external equity assets.
Figure 10 shows the accumulated capital flows in the Asia-Pacific region. The amount
of capital accumulation in and out of Asia-Pacific countries has always increased over time,
both in total and in the form of debt and equity. This suggests that financial liberalization and
financial openness that have increased over time (see Figures 8 and 9) have further increased
domestic financial market activity in Asia-Pacific countries. Figure 10 shows the total amount
of accumulated external assets and liabilities in the Asia-Pacific region that have been
summed across the 19 countries under study. The data shows that the total amount of
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accumulated external assets and liabilities at the end of the 2015 period in the Asia-Pacific
region has reached 60 000 (billion US dollars). Where at the beginning of 1976 only
amounted to 780 (billion US dollars). The movement of total external assets and external
liabilities in 1976-2015 shows the same movement, but with the condition that total external
assets are much larger than total external liabilities. This indicates that in total, financial
market activity in the Asia-Pacific region is dominated by capital outflows compared to
capital inflows.
Figure 10 also shows the movement of debt and equity capital flow activity in the Asia-
Pacific region. Figure 10 shows that financial market activity in the form of debt is much
greater t ha n financial activity in the form of equity. The movement of both debt capital
inflow and debt outflow shows the same movement. The movement of debt activity has
always increased over time. Total debt obligations in the Asia-Pacific region in 2015 reached
30,000 (billion US dollars), whereas in 1976 it was only 400 (billion US dollars). Similarly,
total debt assets in 2015 reached 20 000 (billion US dollars), whereas in 1976 it was only 270
(billion US d o ll a r s ) . There is something interesting shown in Figure 10 in the debt capital
activity in the Asia-Pacific Region. Debt inflows are larger than debt outflows over time.
Figure 10 also shows the activity of equity capital flows. When compared to debt capital,
equity capital does not show a significant upward movement. In 2015, equity capital inflows
in the Asia-Pacific region amounted to 9 300 (billion US dollars), whereas in the 1985 period
it was only 210 (billion US dollars). Meanwhile, the average equity capital outflow in the
Asia-Pacific region in 2015 amounted to 9 250 (billion US dollars), whereas in the 1985
period it was only 215 (billion US dollars).
Furthermore, Figure 11 shows the accumulated capital flows of total assets and
liabilities in and out, averaged from 1976 to 2015. The data for total external assets and
liabilities are in US dollar billions. On average, for countries in the Asia-Pacific region total
external assets show a figure of 675.8, while total external liabilities on average amount to
656.6. This shows that on average, total capital outflow activity still dominates in Asia-Pacific
countries when compared to total capital inflow. Figure 11 also shows the average total
capital flows by income group. On average, both capital inflow and outflow activities are still
dominated by developed countries. On average, the total incoming and outgoing capital flow
activity (total external assets + total external liabilities) amounted to 2 250, while developing
countries when averaged only amounted to 314.79. The dominance of large financial
activities in the group of developed countries is related to high financial liberalization and
openness in the group of countries (see Figures 8 and 9). The developed countries group has a
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high level of financial openness due to the industrialized structure of the economy, so that to
expand its domestic production pattern requires high capital flows.
Figure 11 shows that for the developed countries group, the United States still
dominates activity in global financial markets. This is followed by Japan and Hong Kong.
The total external liabilities of each country are 6860, 1535.4 and 818.5. Meanwhile, the total
external assets in each country are 5903.6, 2459.7 and 1077.4. The interesting thing shown in
the figure is related to the condition of the country's capital flow direction in the United
States, where total external liabilities are on average greater than total external assets. Similar
conditions are also shown by Chile, Canada, South Korea, New Zealand and Australia.
Meanwhile, Japan and Hong Kong are in the opposite condition, where total external
liabilities are on average smaller than total external assets. The conditions of countries similar
to Japan and Hong Kong are Singapore and Macao.
The country with the lowest total capital inflows and outflows in the developed
countries group is Macao at 31.7. Figure 11 further regroups the Asia-Pacific countries by
developing countries. In the group of developing countries, the highest and most significant
capital flow activity is the country of China with an average value of total external liabilities of
585.69. While the average total external assets in China amounted to 1371.02. High capital inflows
and outflows after China are India and Indonesia. Interesting things are shown in the conditions in
China, where total external assets on average are much greater than total external liabilities. This is
different from other developing countries, where on the contrary, total external liabilities are much
greater than total external assets. The country with the lowest total capital inflows and outflows in the
group of developing countries is Pakistan at 41.83%.
Figure 12 shows capital inflows and outflows in the form of debt (total assets and
external debt and liabilities) averaged from 1976 to 2015. Data on total external debt assets
and liabilities are shown in billion US dollars. On average for countries in the Asia-Pacific
region, total external debt assets show 290.0, while total external debt liabilities amount to
382.6. This shows that overall, the average capital in the form of incoming debt tends to be
greater than the average external debt with capital in the form of debt coming out. It can be
seen that total debt liabilities tend to be greater than total debt assets, both in the group of
developed countries and developing countries. There are only a few countries that are in the
opposite condition, namely Hong Kong, Macao, Singapore, Japan and China.
Figure 12 also shows the average debt capital inflows and outflows by income group.
The average debt capital inflow and outflow activity is still dominated by developed
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countries. The total debt capital flow activity (total external debt assets + total external debt
liabilities) averaged 1197.6, while developing countries averaged only 90.4. This shows that
there is still a dominance of financial activity in the form of debt in high-income countries in
the Asia-Pacific region. Figure 12 also shows that for developed countries, the United States
still dominates financial activity in the form of debt in the Asia-Pacific region, followed by
Japan, Hong Kong and Canada. The total external debt obligation of the United States is
4126.8, followed by Japan at 1108.2, Hong Kong at 362.9 and Canada at
406.6. The United States again ranked the highest followed by Japan, Hong Kong and
Canada at 2391.0, 1675.0 respectively,
535.5 and 173.0.
Figure 12 further shows the total debt obligations and assets for the developing
countries group. The highest debt capital flow activity for the developing countries group is
China, followed by India and Indonesia. The average total debt obligations of these countries
are 182.7, 98.9 and 94.0, while the average total debt assets of these countries are 224. 9, 9.2,
13.9. The interesting thing shown in the developing countries group is that the majority of
these countries have larger total debt inflows than total debt outflows except China. Thus,
Figure 12 shows that the developing countries in funding their development activities are still
dependent on debt to other countries.
Figure 13 explains the capital inflows and outflows in the form of equity (total external
assets and equity liabilities) which are also averaged from 1976 to 2015. The data for total
external equity assets and liabilities are in US dollar billions. On average for countries in the
Asia-Pacific region, total external equity assets show a figure of 104.6, while total external
equity liabilities amounted to 104.7. When totaled, the average financial activity in the Asia-
Pacific region countries amounted to 209.3. This figure shows that the total equity flow is
lower than the total debt flow (see Figure 12) by a magnitude of reaching
672.6. This suggests that debt capital flow activity dominates over equity capital flow in Asia-
Pacific countries. Figure 7 also shows the average equity capital inflows and outflows by
income group. The average equity capital inflow and outflow activity is still dominated by
developed countries. Where the total equity capital flow activity (total equity capital flow) is
still dominated by developed countries external equity assets + total external equity liabilities)
in developed countries averaged 376.4, while developing countries averaged only 23.1.
Similar to debt capital flows, financial activity in the form of equity is still dominated by
high-income countries in the Asia-Pacific region.
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The Effect of Financial Liberalization and Capital Flow Direction on
Macroeconomic Volatility in the Asia-Pacific Region
Before entering the calculation of regression coefficients to see the impact of financial
liberalization and capital flow direction on macroeconomic volatility in the Asia-Pacific
region, the following is an overview of the variables that make up the regression equation.
Table 8 shows the variables used in the study. The variables are divided into two categories:
dependent variables, and independent variables. The independent variables in this study are
divided into two categories, namely core variables and control variables. Control variables are
used in this study as controlled variables so that the relationship between the independent
variable and the dependent variable is not influenced by external factors under study. The
determination of control variables in this study is based on previous studies developed from
the research of Kose et al. (2003), Neaime (2005) and Ahmed and Suardi (2009).
The dependent variables in Table 8 show that the most volatile macroeconomic variable
is the gross fixed capital formation growth variable as a proxy for the investment variable.
Meanwhile, the macroeconomic variable that has the lowest level of volatility is the gross
domestic product growth variable. The movement of each volatility of macroeconomic
variables, namely income (gross domestic product and gross national product), consumption
(private consumption and final consumption) and investment (gross fixed capital formation) is
similar. It can be seen that all volatility variables decreased in the decade 1986-1995 and then
increased again in the decade 1996-2005. Table 1 also shows the movement of dependent
variables per decade. Financial openness and financial liberalization data on average always
increase every decade. In addition, data on the direction of capital flows consisting of total
external assets, total external liabilities, total external debt assets, total external debt liabilities,
total external equity assets and total external equity liabilities also on average always increase
per decade. The increase in capital inflows or outflows is due to the increasingly liberalized
and integrated financial markets of countries in the Asia-Pacific region to global financial
markets.
Table 8 also shows the movement of the control variables used in the study per decade. The
movement of trade openness data shows an increasing movement every decade. This shows
that the activity of exchange of goods and services in Asia-Pacific countries always increases
from decade to decade. Likewise, the average income per capita in the Asia-Pacific region
has always increased every decade. The increase in income per capita also shows a very
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significant increase where in the 1976-85 decade only amounted to 5735.46 (US $)
significantly increased by 30699.47 (US $) in the 2006-15 decade. Inflation data on average
decreased in the decade 1976-85 to 1996-05 and rose again in the decade 2006-15. The
increase in inflation at the end of the decade was due to several symptoms of the global
financial crisis, such as the subprime mortgage crisis and the European crisis that have
damaged world market prices, resulting in an increase in the inflation rate. As for inflation
volatility has been decreasing every decade. This shows that the price level has stabilized over
time.
Similarly, the terms of trade volatility data has always decreased in each decade. This is
shown in the 1976-85 decade the terms of trade volatility was at 6.63 and at the end of the
2006-15 decade it dropped significantly to 3.71. Discretionary fiscal policy data decreased in
the first three decades and increased again in the last decade. Discretionary fiscal policy
shows the shock of a country's government spending. Decade 1976-85 discretionary fiscal
policy fell until the period 1996-05 from 0.0221 to 0.0121, then rose again in the last decade
to 0.0128. Financial development data also increased every decade, this is because there is a
relationship between increasing financial liberalization and openness. Financial development
increased from the initial decade of 1976-85 by 0.56 to 2006-15 by 0.97. Furthermore,
institutional quality data also increased in the first three decades and decreased in the last
decade. After presenting an overview of the variables that make up the equation, the
following are the results of estimating the equation to answer the effect of financial
liberalization and capital flow direction on macroeconomic volatility in the Asia-Pacific
region.
Table 9 presents the estimation results of the effect of financial liberalization on
macroeconomic volatility in the Asia-Pacific region (see Appendix 1 and 2). The volatility of
macroeconomic variables growth is divided into five parts, namely Vgdp (GDP growth
volatility), Vgnp (GNP growth volatility), Vpc (private consumption growth volatility), Vfc
(final consumption volatility) and Vgfcf (investment growth volatility). Meanwhile, the
financial liberalization factor is divided into two: financial liberalization factor which
indicates de jure financial liberalization (Chinn and Ito 2007) and financial openness factor
which indicates de facto financial liberalization ((Lane and Milesi-Ferreti 2006). The
estimation results also include an Asia-Pacific developed countries dummy (where the value
of 1 is for "developed countries," while the value of 0 is for "developing countries"). In
addition, the Asia-Pacific developed countries dummy is interacted with financial openness.
This is intended to look at the possible effect of financial openness that differs across income
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groups as found by Kose, et al. (2003) and Mirdala et al. (2015). Other factors are also
included in this estimation, namely: trade openness, income per capita, inflation, inflation
volatility, terms of trade volatility, discretionary fiscal policy, fiscal policy procyclicality,
financial development and institutional quality.
The specification test of the dynamic panel model in Table 9 and Table 10 has met the
best criteria. First, the lag estimator of the dependent variable is between pooled least square
and fixed effect, which indicates that the model used is unbiased. Second, the value of the
sargan test on all estimation results does not reject the null hypothesis, indicating that the
estimation results are valid with no correlation between the instrument and the error
component. Third, the estimation results are consistent, where AR1 shows that the null
hypothesis is rejected, and AR2 shows that the null hypothesis is not rejected. The
specification test results can be seen in full in Appendix 1 to Appendix 4.
The estimation results begin by showing the impact of financial openness on the growth
volatility of macroeconomic variables in the Asia-Pacific region. The estimation results show
that financial openness has a significant negative effect. The existence of financial openness
in the Asia-Pacific region will have a positive effect by reducing the volatility of income and
consumption growth. The estimation results show a significant effect on the volatility
variables of GDP growth, GNP, private consumption, and final consumption with coefficients
of -0.0062, -0.0525, -0.0103 and -0.0049. This is similar to the findings of Ahmed Suardi
(2009) who has examined in Sub-Saharan Africa and Kose et al. (2003, 2005) who have
examined in aggregation. However, a question arises based on the fact that various studies
show that financial market openness is more beneficial for developed countries, while tending
to be detrimental for developing countries. This study corrects the estimation results of the
effect of financial openness in the Asia-Pacific region in aggregate by including the effect of
dummies (developed countries=1, developing countries=0) and dummies interacted with
financial openness in the subsequent estimation.
The results show that for the developed countries group, the intercept value is higher
than the developing countries group for the volatility of GDP, GNP and gross fixed capital
formation. The average difference in volatility values between the developed countries group
and the developing countries group if all independent variables are equal to 0 for the volatility
of GDP growth, GNP, private consumption, final consumption and gross fixed capital
formation is 0.0726, 0.0746, 0.0671, 0.0790 and 0.1509. Another interesting result is the slope
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value of financial openness, which in this case is the slope of the developing countries group,
shows significant positive results for all macroeconomic variable growth volatility models.
This explains that the existence of financial openness in the Asia-Pacific region to global
financial markets has not had a positive effect on the group of developing countries by
reducing fluctuations in macroeconomic variables. Meanwhile, for developed countries, the
interaction results with financial openness show significant negative results for all estimation
results.
The estimation results for the slope of the interaction dummy (FI × Asia developed
countries) in the growth volatility equation of GDP, GNP, private consumption, final
consumption and gross fixed capital formation are as follows (slope values
interaction dummy - financial openness slope): -0.0036, -0.0025, -0.0043, -0.0011, and
0.0011. However, these results are consistent with the research of Mirdala et al. (2015), Evans
and Hnatkovska (2006), Neaime (2005), and Kose et al. (2003) which explain the existence of
financial openness in developing countries has increased the degree of volatility of
macroeconomic variables. While on the contrary, the existence of financial openness is
beneficial for developed countries. Then the estimation results show no effect of de jure
financial liberalization on the estimation equation in all macroeconomic volatility. This is
consistent with the research of Neaime (2005) and Kose (2003) which revealed the weakness
in the measure of financial liberalization de jure has been able to be explained by the de facto
financial liberalization proxy described earlier.
Table 9 also describes other factors that affect macroeconomic volatility in the Asia-
Pacific region. Trade openness in the estimation results shows a positive and significant effect
on all macroeconomic volatility in the Asia-Pacific region. This is consistent with the results
of Kose et al. (2003), Dupasquier and Osakwe (2006), Ahmad and Suardi (2009), and Neaime
(2005), that the existence of open trade has a positive influence on the volatility of
macroeconomic variables. The existence of trade liberalization has increased fluctuations in
domestic import and export price levels which will then create uncertainty in domestic
consumption and production, which in turn will increase the volatility of macroeconomic
variables. Other results show a significant positive effect of terms of trade volatility on all
macroeconomic volatility estimation results. An increase in fluctuations in the terms of trade
variable increases the uncertainty of the trade position of countries in the Asia-Pacific Region,
which in turn increases economic fluctuations. This result is similar to the findings of Kose
(2003), Ahmed and Suardi (2009) and Neaime (2005).
Furthermore, the estimation results show the effect of income per capita on the
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volatility of macroeconomic variables which has a positive and significant impact. This is in
line with research from Easterly, Islam and Stiglitz (2000) which shows positive results on
macroeconomic volatility. This means that the higher the per capita income of a country, the
higher the volatility of the growth of its macroeconomic variables. This is as shown in the
exploratory analysis of the data in Figure 1 that developed countries with high per capita
income have a trend of increasing volatility in the growth of macroeconomic variables.
Inflation and inflation volatility variables show a significant positive effect only on the
volatility of GDP and consumption. This is in line with the research of Ahmed and Suardi
(2009) and Neaime (2005) The existence of this negative effect according to Friedman (1977)
in Ahmed and Suardi (2009) is due to the adverse effects of inflation uncertainty on economic
growth. Increased inflation uncertainty will distort the effectiveness of the price mechanism in
allocating resources efficiently, thus causing a negative effect on the volatility of
macroeconomic variables, but in this study the effect of financial liberalization is only
significant on the volatility of consumption variables. The next analysis discusses the effect of
financial development and institutional quality. The results show that both variables have a
significant negative effect on the volatility of investment growth. That is, the existence of
financial development and good institutional quality indicates that the country has low risk,
and will ultimately reduce the volatility of investment growth. This is consistent with the
research of Ahmed and Suardi (2009) which shows that good financial market control will
reduce capital flight so that it will maintain the volatility of domestic investment (Kose et al.
2006).
Furthermore, Table 10 explains the effect of the direction of total capital flows, debt and
equity inflows and outflows on the volatility of the growth of macroeconomic variables (see
Appendix 3 and 4). In theory, the effect of international financial openness has two forces.
These forces may reduce or increase the volatility of macroeconomic variables. On the one
hand, financial openness can reduce macroeconomic volatility due to diversification in risk
sharing which will then maintain the stability of macroeconomic variables. On the other hand,
financial openness may lead to greater specialization and thus increase the volatility of
macroeconomic variables (Kose et al. 2003). In this section, to examine the empirical
evidence of different effects of financial openness. The research is directed towards
examining the issue through the possibility of differential effects of different directions of
capital flows on macroeconomic volatility. Total assets/GDP represents the accumulated stock
value of capital outflows. Total liabilities/GDP shows the value of the accumulated stock of
capital inflows. Table 10 shows that higher levels of total external assets are associated with
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significantly lower volatility of macroeconomic variables. This means that an increase in
capital outflows will maintain the stability of domestic macroeconomic variables. This can be
seen in the growth volatility equation of GDP, GNP, private consumption and final
consumption with coefficients
of
:
-0.049, -0.040, -0.055, -0.047, while the results are not significant to the volatility of
investment growth (gross fixed capital formation).
Furthermore, Table 10 also shows that a higher level of total external liabilities is
associated with higher growth volatility of macroeconomic variables. That is, an increase in
capital inflows will increase fluctuations in domestic macroeconomic variables. This can be
seen in the growth volatility equations of GDP, GNP, private consumption and final
consumption with coefficients of: 0.043, 0.039, 0.026,
0.052. This finding implies that risk diversification, a key benefit of financial liberalization, is
determined by the accumulation of external assets (Kose et al. 2003). Meanwhile, the level of
external liabilities (capital inflows) has the opposite effect on the growth volatility of
macroeconomic variables. This is because the accumulation of capital inflows may provide
greater specialization in the face of country-specific or industry-specific shocks.
Moreover, according to Cardarelli, Elekdag and Kose (2009) capital inflows often
create important challenges for policymakers because of their potential to generate excessive
stress, loss of competitiveness due to an appreciated exchange rate, and increased
vulnerability to crises. Stiglitz (2002) suggests that the downside of capital liberalization may
be that it brings more instability in financial markets rather than increased growth inducing
effects, if an economy is still immature. Rodrik and Subramanian (2008) also argue that the
capital accumulation of developing countries is insufficient not because they lack savings but
because they lack opportunities to invest. The lack of opportunities to i nve st , coupled with
an increase in
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The increase in capital inflows will put more pressure on developing countries and there is no
benefit to be gained from increased investment.
The different effects of capital inflows and outflows in this section can be used as a
basis to explain in detail why financial openness has a negative effect on the volatility of
macroeconomic growth variables in developing countries, while it is beneficial for developed
countries. In Figure 11 it has been shown that capital outflows in total, debt and in the form of
equity for all developing countries (viz: Peru, Pakistan, Malaysia, Indonesia, Philippines,
Thailand, India and Bangladesh) are greater than the capital inflows, except for China. This is
why financial openness has a positive relationship with the growth volatility of
macroeconomic variables in the group of developing countries, the results of Table 9. The
negative effect is because the direction of capital flows in the group of developing countries is
more dominated by capital inflows than capital outflows as found in Table 10.
The study also considers different types of capital flows by dividing external assets and
liabilities into two categories, equity and debt. The results show that a country that holds more
external asset debt than other countries experiences lower macroeconomic growth volatility.
This is shown from the results of the growth volatility equations of GDP, GNP, private
consumption and final consumption of -0.044, -0.043, -0.068 and -0.049. This means that
higher external asset debt by providing net loans to foreign countries will be associated with
lower macroeconomic volatility. While the opposite is shown for total external debt
obligations, a country that holds more debt obligations (as a foreign debt borrower)
experiences higher macroeconomic growth volatility. This is shown from the results of the
growth volatility equation of GDP, GNP, private consumption and final consumption of
0.054, 0.056, 0.070, 0.057. Thus, countries that borrow with other countries abroad in the
form of debt will be exposed to higher volatility because they have to be subject to changes in
the interest rate of their external interest rate loans. An increase in macroeconomic volatility
may occur because the country may specialize its production into riskier ventures.
Table 10 also explains the effect of equity, the results show that a country that holds
more equity assets than other countries experiences lower macroeconomic growth volatility.
This is shown from the results of the growth volatility equation of GDP, GNP, private
consumption and gross fixed capital formation of -0.106, -0.112, -0.174, and -0.174,
respectively.
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-0.199 with all results significant. This means that higher external equity assets are associated
with lower macroeconomic volatility. While different is shown for total external equity
liabilities, a country that holds more equity liabilities experiences higher macroeconomic
growth volatility. This is shown from the results of the growth volatility equation of GNP,
private consumption and gross fixed capital formation of 0.100, 0.200 and 0.163. Separating
total external assets and liabilities into equity and debt, this study found significant results for
both variables in the macroeconomic volatility equation. High total external assets in the form
of equity and debt are associated with low macroeconomic volatility, whereas high external
liabilities in equity and debt are associated with high macroeconomic volatility. In other
words, in terms of macroeconomic volatility, the benefits of risk diversification appear to
come f r o m holding external assets, regardless of whether they are debt or equity.
Meanwhile, high external liabilities in the form of selling domestic assets abroad or
borrowing foreign debt will be accompanied by higher macroeconomic volatility.
CONCLUSIONS:
1. The effect of financial openness as a measure of de facto financial liberalization has a
negative and significant effect on the growth volatility of macroeconomic variables in the
Asia-Pacific region as a whole. This suggests that financial openness has a positive effect by
weakening macroeconomic instability. Furthermore, the results separate countries in the Asia-
Pacific Region by income group using dummy variables. The results show that the negative
relationship between financial openness and macroeconomic volatility in the Asia-Pacific
region only occurs in high-income countries, while for developing countries the opposite is
true. Where financial openness is positively related to macroeconomic volatility. This
suggests that financial openness has a negative effect by increasing the growth volatility of
macroeconomic variables in developing countries. The effect of financial liberalization as a
measure of de jure financial liberalization shows insignificant results on all models of growth
volatility of macroeconomic variables.
2. Total accumulation of external assets as a proxy for capital outflows shows a negative
relationship with all macroeconomic variables growth volatility except gross fixed capital
formation (investment). This suggests that more capital outflows will maintain the stability of
macroeconomic variables. On the other hand, the accumulation of total external liabilities as a
proxy for capital outflows shows a positive relationship with all volatility of macroeconomic
variables. This shows that more capital inflows actually increase the instability of
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macroeconomic variables. The positive effect of capital outflows on the volatility of
macroeconomic variables is due to international risk diversification, while the negative effect
of capital inflows on the volatility of macroeconomic variables is due to international risk
diversification volatility of macroeconomic variables is due to specialization which causes risk
shifting. Debt and equity show similar results, where total debt and equity assets show a negative
relationship, while total debt and equity liabilities show a positive relationship to the volatility of
macroeconomic variable growth.
