Silviase/jgov_v1.4_full_ann huggingface dataset:
### 1. Introduction

Since the financial crisis of 2009, many countries have embarked on extremely loose monetary policies. Short-term interest rates have been cut to zero, and central banks have purchased government bonds and other assets in massive quantities. These measures that expanded Central Bank balance sheets are collectively called Quantitative Easing policies. While many studies have examined the impact of quantitative easing policies on the domestic Japanese economy (Hoshi, 2014; Rogers and Wright, 2014), few studies have analyzed the manner in which quantitative easing policies have affected Japan's neighboring economies are scarce.

One of the few studies examining spillover effects on neighboring countries is that by Dekle and Hamada (2015). The authors examine how monetary shocks in Japan and in the U.S. affect each other. Furthermore, they examined short-term interest rate and base money changes in Japan and in the U.S. to investigate how GDP growth rates and inflation rates in each country are affected. The authors use a sequence of two-country nonstructural vector autoregression (VARs) to show, the effects of changes in short-term interest rates and monetary base stocks. They find that an expansionary monetary policy in the U.S. appreciates the Japanese yen and impacts Japanese GDP for approximately three quarters, after which point Japanese GDP began to grow, owing to the expansion of U.S. GDP. An expansionary Japanese monetary policy has a small negative effect on the U.S. economy in the short-run, because of the appreciation of the dollar, and a small positive effect on U.S. GDP growth in the long-run, because of the expansion of Japanese GDP, which stimulated U.S. exports to Japan.

However, changes in Japanese monetary policies are expected to primarily affect Japan's smaller or closer in-neighbor such as Korea, China, and Thailand. The impact of Japan's monetary policy on the U.S. economy, while not negligible, cannot be as large as its impact on Japan's Asian neighbors, given the relative sizes of Japan and the U.S. and the geographical proximity of Korea, China, and Thailand to Japan.

As a follow-up to Dekle and Hamada (2015), I examine the effects of an expansion in Japanese monetary policy on the economies of Japan's Asian neighbors, specifically on Korea, China and Thailand, both in the short-run and in the long-run. I choose Korea because of its proximity to Japan, China was chosen because of its current size, and
Thailand, because of its Southeast Asian location, and complementary trade structure with Japan.

Loose monetary policies in Japan can affect the economies of Japan’s neighboring Asian countries in several ways. If the policy causes the yen to depreciate relative to Japan’s partner currencies, then the trade positions of Japan’s partner countries will be affected, damaging the GDP growth prospects of these countries. However, in the medium-run, if a loose monetary policy causes capital to flow from Japan to these partner countries, then that may help raise their investment, asset prices, and GDP. In the even longer run, an increase in Japanese GDP owing to looser monetary policies may help raise the GDPs of the partner countries by growing their exports to Japan.

I examine the impact of Japanese expansionary monetary policies on its neighbors through the mechanism of the global vector autoregression model (the Global GVAR), as advanced by Pesaran, Schuerman, and Weiner (2004). The standard Vector Autoregression (VAR) approach as pioneered by Chris Sims is a way of summarizing time series data such as GDP, inflation, interest rates, exchange rates, and other variables. Once a pattern in these variables are established through estimation, then counterfactuals can be performed by impulse response analysis. For example, we can examine the impact of a cut in Japanese short-term interest rates on Japanese GDP (Kim and Roubini, 2000).

However, when we have more than one country, in a typical VAR analysis, all the variables in the other countries have to be included in the estimation of the model in each country, resulting in inadequate observations to perform the estimation. For example, let us summarize the relations among the following four variables: short-term interest rates, GDP, inflation, and exchange rates among Japan, Korea, and China. If we have only one country, we would need to estimate a $ 4 \times 4 $ variable VAR system. With three countries, however, we would need to estimate a $ 12 \times 12 $ variable VAR system, or obtain coefficient estimates for 144 variables. Given the lengths of conventional quarterly time series data, we would quickly run out of observations to estimate the three country model.

As described below, the GVAR approach imposes strong restrictions on the usual VAR model so that enough parsimony can be achieved in the estimation. In the estimates below, I use the GVAR Toolbox Program 2.00 (2014) to estimate a 26-country model. While the data are available from 1979Q1–2013Q1, the estimation and calculated impulse responses mainly use the sample 1990Q1–2013Q1. The key to
the GVAR modelling approach is the inclusion of own-country variables along with the foreign variables, to deal with the common factor dependencies that exist in the world economy. Since the included foreign variables are the same for all the countries, the foreign variables will be the common factor.

This paper is organized as follows. Section 2 describes the main hypothesis to be tested. Section 3 describes the GVAR methodology in more detail. Section 4 discusses some of the literature to empirically identify recent Japanese quantitative easing policies. Section 5 presents the results from the impulse responses (from the GVAR estimates). Section 6 quantifies from the impulse response, the likely magnitudes of the effects of the recent expansions in Japanese base money on Japanese, Korean, Chinese, and Thai GDP. Section 7 concludes the paper.

### 2. Hypothesis

My main hypothesis is that in the short-run, the expansionary monetary policies in Japan will depreciate the yen, and appreciate the currencies of Japan's partner countries in Asia, resulting in a decline in trade balances and the GDP growth rates of Japan's Asian partner countries. However, in the longer run, the expansion in Japanese GDP caused by the Japanese expansionary monetary policy will increase the GDPs of Japan's partner countries.

Before I move to the formal testing of these hypothesis using the GVAR approach, I take a quick look at the data. Following Prime Minister Shinzo Abe's election, announcements about the expansion of the Japanese monetary base began to appear in late 2012. Figure 1 depicts the trends in the nominal effective exchange rates (NEER) of Japan, Korea, China, and Thailand from 2010 to the second quarter of 2015 $ ^{1} $ . We can see that the Japanese NEER appreciated slightly from 2010 to 2012, after which it depreciated sharply by about 25 percent. The timing of this depreciation accords well with the announcements of the monetary base expansions. Meanwhile, the Korean NEER has appreciated by 10 percent from 2012, while the Chinese NEER appreciated by about 20 percent. The Thai NEER appreciated slightly. While many economic shocks such as GDP changes, natural disasters, such as the Tohoku earthquake, and other shocks affect nominal exchange rates, the prospects of a rapid
Fig.1 : Nominal effective exchange rates

increase money supply in Japan (relative to its trading partners) from late 2012 has contributed to the sharp depreciation of the yen.

The Japanese merchandise current account fell from 108 billion dollars in 2010 to -4.5 billion dollars in 2011 mainly because of the effects of the earthquake, which raised materials and energy imports needed for the reconstruction (not depicted here to save space). Japan's merchandise current account recovered to -3 billion dollars by 2015Q2. While part of this recovery may be related to the weaker yen, the other part may be related to the recovery of the Japanese economy and the fall in global commodity prices. Since 2014, both the Korean and Chinese merchandise current accounts fell relative to their GDPs. However, given the many other shocks hitting these economies, it is difficult to ascribe how much their stronger NEERs impacted the Korean and Chinese current account deteriorations.

The start of the Japanese monetary announcements coincided with a weak period of Japanese growth owing to the effects of the 2011 Tohoku earthquake. Consequently, Japanese real GDP growth was slightly negative in 2011 (see Figure 2) but rebounded between 2012 and 2015Q2 (except for 2014). From the data, it is difficult to see how the rebound in Japanese GDP growth contributed to growth in Korea and China since the growth in these countries has actually deteriorated. After falling in 2012, Korean real GDP growth began to rebound in 2013, but fell sharply in 2015. Chinese real GDP growth has been declining steadily from 2010 from over 10 percent to under 7 percent by 2015Q2. Thai GDP, on the other hand, has tracked Japanese GDP well.

Given that graphically, it is difficult to test my hypothesis that recent Japanese
Fig.2: Real GDP growth rates

recent monetary policies have negative impacted its neighbors in the short-run, while having a positive effect in the longer run, I adopt the more sophisticated statistical (GVAR) methodology to evaluate the effects of Japanese monetary shocks on the GDPs of its Asian neighbors.

### 3. The GVAR Model

The GVAR model was first introduced in Pesaran, Schuermann, and Weiner (2004). It was originally developed in the aftermath of the 1997 East Asian financial crisis to quantify the effects of changing macroeconomic conditions. Although a few large global macroeconomic models existed at the time, they were difficult to use for simulation analysis. The existing models were often incomplete and did not present a closed, global system. The GVAR model was specifically developed to fill this gap in modelling and simulation analysis.

The initial version of the GVAR model was quite basic, contained only 11 countries, and did not include interest rates, either short- or long-term. The version of the GVAR model presented below is based on the study by Dees, di Mauro, Pesaran, and Smith (2007) which included 26 countries, and contained a full set of financial variables, such as short- and long-term interest rates and the value of the equity market.

The international transmission of business cycles take place through several channels. It can be through common global shocks such as global commodity prices and technology shocks. However, it is likely that even when all global shocks are considered, there could be strong policy and trade spillover effects among countries.
The spillover of monetary policies such as a decrease in say U.S. short term interest rates may have negative spillover effects on the GDPs of Japan and other countries, depreciating the dollar and impacting the competitiveness of the exports of other countries.

The transmission channels among countries are complex. For example, a fall in U.S. interest rates may slow the Japanese economy, by appreciating the yen. The slowdown in the Japanese economy could hurt the economies of Korea and China, leading to a slowdown of exports from the U.S. to Asia overall, with negative feedback effects on the U.S. economy.

Given these complex transmission mechanisms, quantitative analysis of say, the spillover effects of a fall in Japanese short-term interest rates requires a practical, yet general modelling framework for the quantitative analysis of the relative importance of different shocks and channels of transmission. In modern macroeconomics, the default is the stochastic dynamic general equilibrium model, but such models work well for at most two countries. Other ad hoc models with more than two, and in fact, many countries exist, but they are essentially static models with questionable dynamics. We need to have some reasonable dynamics to answer the question: what is the impact over time of a Japanese monetary expansion on Japanese and neighboring Asian countries?

In this paper, I use the GVAR model that combines a non-structural VAR model with an individual country error-correction model. This model includes domestic variables (say, of Japan) and country-specific foreign variables that are constructed to match the international trade and financial linkages of the country in question. In this case, the model includes Japan's foreign trade linkages with other countries as foreign variables.

The GVAR model allows for complex interactions/interdependencies at the national and international levels. Most importantly, it handles the “curse of dimensionality” by postulating that most of the foreign variables are weakly exogenous. This weak exogeneity assumption is the key feature of GVAR, since it allows country models to be estimated individually.

In other words, the objective is to model a number of country-specific macroeconomic variables such as real GDP, inflation, base money, interest rates, and exchange rates collected in the vector, $ x_{it} $ over time, $ t=1,2,\cdots,T $ , and across the $ N+1 $ countries. Given the general nature of global interdependence, it is obviously desirable
to treat all the country-specific variables $ x_{it} $ and global variables endogenously. However, such an attempt is impossible because of the “curse of dimensionality.” In a typical time-series, there are simply not enough observations to estimate all of the parameters. To get around this, the GVAR framework imposes weak exogeneity on the foreign country-specific and global variables. It assumes that an individual country, with the exception of the U.S., is a “small” country with respect to the rest of the world. These assumptions can be stated algebraically as follows.

For country i, consider the structure :

$$ x_{it}=a_{i0}+a_{i1}t+\emptyset_{i1}x_{i,t-1}+\emptyset_{i2}x_{i,t-2}+y_{i0}x_{i,t}^{*}+y_{i1}x_{i,t-1}^{*}+y_{i2}x_{i,t-2}^{*}+u_{t} $$

Where $ x_{it} $ is a k by 1 vector of domestic variables, $ x_{it}^{*} $ is a $ k^{*} $ by 1 vector of foreign variables, and u is a serially uncorrelated and cross-sectionally weakly dependent process. Foreign-specific variables are computed as a weighted average of the corresponding domestic variables of all countries, with the weights also being country-specific, that is, $ x_{it}^{*}=\sum_{j=0}^{N}w_{ij}x_{ij} $ , where $ w_{ij}, J=0,1,\cdots,N $ are a set of weights such that they add up to unity. The weights are meant to capture the importance of country j for the ith economy. The weights may reflect, for example, trade linkages depending on the purpose of the modelling exercise. Note that the set of foreign variables can differ from the domestic variables. For example, in my model, the variable real base money (nominal base money divided by the CPI index) appears instead of the short-term nominal interest rate only for Japan.

In the actual estimation, (1) is estimated in error-correction form so that all variables are stationary. For ease of exposition, let the vector $ x_{it} $ refer to Japan (J) and include only two variables, base money, $ m_{Jt} $ , and real GDP, $ y_{Jt} $ . (1) can be re-written as follows :

$$ \Delta m_{Jt}=c_{Jt}+\alpha_{Jt}(\beta_{m}m_{Jt}+\beta_{y}y_{Jt}+\beta_{x}^{^{\prime}}x_{t}^{*})+\delta_{J1}^{^{\prime}}\Delta x_{it}^{*}+\theta_{J1}\Delta m_{Jt-1}+\upmu_{J1}\Delta y_{Jt-1}+u_{1t} $$

For the second equation for Japan, $ \Delta y_{J} $ , the right-hand side explanatory variables are identical. The term in the parentheses above refer to the long run cointegrating relationships among Japanese base money, real GDP, and the vector of foreign variables.

The two equations for Japan can be estimated jointly, conditional on the vector of foreign variables $ \Delta x_{it}^{*} $ for all other countries i. As mentioned, an important assumption of the GVAR approach is that the vector of foreign variables is weakly exogenous. The
foreign variables are weighed by their relative trade with Japan. Given the weak exogeneity assumption, the foreign variables enter as contemporaneous variables.

More generally, for my purposes, $ x_{it} $ , for i=Japan, will include Japanese real GDP, Japanese real base money, real exchange rates (against the U.S. dollar), real equity prices, and nominal long-term (10 year) interest rates. The foreign variables include the weighted averages over the other 25 countries of the same variables (except that we substitute short-term interest rates for base money for countries other than Japan).

The version of the GVAR adopted for my estimation and used in the impulse responses below has, 26 countries, estimated over the period 1990Q1–2013Q1. It is well-known that VAR estimations (of which the GVAR specifications are a special case) are plagued by numerous expectational, regime, and structural shifts. While the data to estimate the model are available from 1979Q1–2012Q1, as shown below, this long period results in some peculiar impulse responses. For example, the effect of monetary loosening in Japan on GDP was found to be more than two times greater in China than in Japan. This is probably because China went through such enormous growth and structural change during this entire period. While today China is twice as big as Japan, during the early 1980s, China was less than $ 1/10^{th} $ the size of Japan. Thus, while on average, over the 1979–2013 period, shocks in Japan had large spillover effects on China, today shocks in Japan should have much smaller effects on China today.

Thus, in calculating impulse responses from Japanese shocks to China today, it is better to estimate the GVAR on a more recent sample, say from 2005. However, such a late start date results in a limited number of time series observations, which makes efficient estimation difficult. Thus, I start my estimation of GVAR in 1990Q1 to have a long enough series of observations, while minimizing structural changes in the sample of countries.

For all the countries, the GVAR model includes the following variables: real GDP, CPI inflation, real equity prices, the real exchange rate against the U.S. dollar, the nominal long-term (10 year) interest rate, and a monetary policy variable. The monetary policy variables are the level of real base money (for Japan) and the short-run nominal interest rate (for the other countries). The weights reflect the share of the country's trade (imports plus exports/total imports plus exports) with another country. The quarterly data used to estimate the 26-country model are from Rebucci et. al. (Inter-American Development Bank), except for Japanese base money, which are
from the Bank of Japan web page.

The estimates of the error-correction form for the change in Japanese real GDP are depicted in Table A1. These are estimates in the context of the full GVAR model with 5 variables and 26 countries. Note that if all the estimates for Japan are depicted, there will be other columns for the changes in CPI inflation, real equity prices, the real exchange rate against the U.S. dollar, the nominal long-term interest rate, and real base money. (They are not depicted to save space.) In addition, in the full GVAR results, there will be columns for all 6 variables for all the 25 other countries.

Table 1: Estimates of the error-correction representation of Japanese GDP (in GVAR)

Coefficient Estimates
Dependent Variable: Japanese Change in GDP, Ch (GDP)
Constant	0.16
Japanese Lagged Variables
Ch (GDP, -1)	0.16
Ch (CPI, -1)	0.025
Ch (Equity, -1)	0.01
Ch (Real Exch., -1)	-0.22
Ch (Real Base Mon., -1)	-0.21
Ch (Long Interest, -1)	0.019
Foreign Contemporaneous Variables, *Denotes trade weighted foreign variables for the other 25 countries.
Ch (GDP*)	0.68
Ch (CPI*)	0.061
Ch (Equity*)	0.01
Ch (Real Exch. Rate*)	0.022
Ch (Short Interest*)	-0.44
Ch (Long Interest*)	-1.95
Japanese Cointegrated Variables
GDP	1
CPI	0.00044
Equity	-0.069
Real Exch	-0.053
Real Base Mon.	-32.78
Long Interest	28.41
Foreign Cointegrated Variables are not depicted to save space.

Sample: 1990Q1 to 2012Q1
### 4. Identifying Japanese Monetary Policy (Quantitative Easing) Shocks

Quantitative easing policies affect the real economy in several ways. The official view among central banks appears to be that such policies raise real economic growth by reducing long-term (10-year) nominal interest rates and raising long-term inflation expectations, thereby stimulating the economy by reducing long-term real interest rates $ ^{2} $ . The Bank of Japan (2015) officially says that the quantitative easing policies of the Abe administration are aimed at increasing long-term inflation expectations and lowering long-term bond yields. Examining the policy effects from January 2013 to December 2014, the Bank of Japan finds that 10-year yields declined by 0.3 percent and inflation expectations over the long-horizon increased by 0.5 percent, resulting in a decline in real interest rates by 0.8 percent.

This ability of Japanese quantitative easing policies to reduce long-term real interest rates is echoed by Hausman and Wieland (2014). They perform an event study for Japan, and find that the package of Abenomics announcements from late 2012 to mid-2013, mainly regarding monetary policies, increased long-run inflation expectations by 1 percent and led to a negligible decline in 10-year bond rates, resulting in a 1 percent decline in real interest rates.

Others take a broader view of the channels of Japanese quantitative easing policies. Fukuda (2015) use an event study approach and focuses on the effects of Abenomics announcements on nominal yen exchange rates and the stock market. He finds that most of the moves in nominal exchange rates and in the yen stock market happened after markets were closed in Japan, suggesting that most of the market participants moving the foreign exchange and stock markets were foreigners. Hausman and Wieland (2014) also find that Abenomics announcements had large effects on depreciating the yen. Honda and Kuroki (2003) not only find a strong link in the late-1990s between short-term interest (call) rates in Japan and long-term 10-year interest rates but also between short-term interest rates and the Japanese stock market. They use econometric techniques to find that a 1 percent surprise cut in call
rates result in a 60-basis point decline in long-term market interest rates and a 3 percent increase in the Japanese stock market. Thus, Japanese actual monetary policies and policy announcements appear to depreciate the yen and raise the value of the Japanese stock market.

In this paper, I take the view that Japanese quantitative easing policies in the last few years were mainly achieved by the expansion of Japanese base money. This was the assumption of Dekle and Hamada (2015). I examine how the increase in Japanese base money has affected the Japanese economy and the economy of its Asian neighbors. Furthermore, I examine the transmission channels of the expansion of Japanese base money—whether the expansion of Japanese base money works through a decline in long-term real interest rates, a depreciation in the real yen, or an increase in stock market values. I examine these transmission channels of base money to GDP growth, both domestically, within Japan, and internationally, to Japan’s Asian neighbors.

### 5. Results

### 5.1 Impulse Response Analysis

I first estimated the entire GVAR model over 26 countries, and calculated their Generalized Impulse Responses (Pesaran and Shin, 1998) $ ^{3} $ . As mentioned above, I characterize Japanese monetary policy as a change in base money. In fact, I use the log of Japanese nominal base money minus the log of the Japanese CPI index as the measure of Japanese monetary policy. This is because until the late 1990s, Japan had higher inflation rates than today, and during this period, the Bank of Japan partly expanded its base money supply to accommodate this rise in prices. In recent years, CPI inflation rates in Japan have been negligible, so the increase in log real base money has essentially reflects the expansion in nominal base money. As mentioned, the GVAR is estimated for a sample from 1990Q1–2013Q1 $ ^{4,5} $ .