This paper undertakes both a narrow and wide replication of the estimation of a money demand function conducted by Ireland (American Economic Review, 2009). Using US data from 1980 to 2013, we show that the substantial increase in the money-income ratio during the period of near-zero interest rates is captured well by the log-log specification but not by the semi-log specification, contrary to the result obtained by Ireland (2009). Our estimate of the interest elasticity of money demand over the 1980-2013 period is about one-tenth that of Lucas (2000), who used a log-log specification. Finally, neither specification satisfactorily fits post-2015 US data.
In regression analyses of money demand functions, there is no consensus on whether the nominal interest rate as an independent variable should be used in linear or log form. For example, Meltzer (1963), Hoffman and Rasche (1991), and Lucas (2000) employ a log-log specification (i.e., regressing real money balances (or real money balances relative to nominal GDP) in log on nominal interest rates in log), while Cagan (1956), Lucas (1988), Stock and Watson (1993), and Ball (2001) employ a semi-log specification (i.e., nominal interest rates are not in log).
WP044
This paper estimates a money demand function using US data from 1980 onward, including the recent near-zero interest rate period. We show that the substantial increase in the money-income ratio during the period of near-zero interest rates is captured well by the log-log specification, but not by the semi-log specification. Our result is the opposite of the result obtained by Ireland (2009), who found that the semi-log specification performs better. This mainly stems from the difference in the sample period employed: ours contains 24 quarters with interest rates below 1 percent, while Ireland’s (2009) sample period contains only three quarters.
In regression analyses of money demand functions, there is no consensus on whether the nominal interest rate as an independent variable should be used in linear or log form. For example, Meltzer (1963), Hoffman and Rasche (1991), and Lucas (2000) employ a log-log specification (i.e., regressing real money balances (or real money balances relative to nominal GDP) in log on nominal interest rates in log), while Cagan (1956), Lucas (1988), Stock and Watson (1993), and Ball (2001) employ a semi-log specification (i.e., nominal interest rates are not in log).
WP034
Changes in people's behavior during the COVID-19 pandemic can be regarded as the result of two types of effects: the "intervention effect" (changes resulting from government orders or requests for people to change their behavior) and the "information effect" (voluntary changes in people's behavior based on information about the pandemic). Using mobile location data to construct a stay-at-home measure for different age groups, we examine how the intervention and information effects differ across age groups. Our main findings are as follows. First, the age profile of the intervention effect of the state of emergency declaration in April and May 2020 shows that the degree to which people refrained from going out was smaller for older age groups, who are at a higher risk of serious illness and death, than for younger age groups. Second, the age profile of the information effect shows that, unlike the intervention effect, the degree to which people stayed at home tended to increase with age for weekends and holidays. Thus, while Acemoglu et al. (2020) proposed targeted lockdowns requiring stricter lockdown policies for the oldest group in order to protect those at a high risk of serious illness and death, our findings suggest that Japan's government intervention had a very different effect in that it primarily reduced outings by the young, and what led to the quarantining of older groups at higher risk instead was people's voluntary response to information about the pandemic. Third, the information effect has been on a downward trend since the summer of 2020. While this trend applies to all age groups, it is relatively more pronounced among the young, so that the age profile of the information effect remains upward sloping, suggesting that people's response to information about the pandemic is commensurate with their risk of serious illness and death.
The number of COVID-19 infections in Japan began to increase in earnest in the latter half of February, and by the end of March, the cumulative number of infections had reached 2,234. In response to the spread of infections, the government declared a state of emergency on April 7 for seven prefectures including Tokyo, and on April 16, the state of emergency was expanded to cover all prefectures. As a result, people refrained from going out, and the number of new infections in Japan, after peaking at 720 on April 11, began to drop, falling to almost zero by the end of May. This was the first wave of infections. However, in July, the number of new infections began to increase again, and continued to increase throughout the summer (peaking at 1,605 new infections on August 7). This was the second wave. While the second wave had subsided by the end of August, the number of new infections began to increase once again in late October, and on December 31, 2020, the number of new infections in Tokyo reached 1,353, exceeding 1,000 for the first time (the number of new infections nationwide was 4,534). In response, the government again declared a state of emergency on January 7. We are currently in the middle of the third wave.
WP029
Japan’s government has taken a number of measures, including declaring a state of emergency, to combat the spread COVID-19. We examine the mechanisms through which the government’s policies have led to changes in people’s behavior. Using smartphone location data, we construct a daily prefecture-level stay-at-home measure to identify the following two effects: (1) the effect that citizens refrained from going out in line with the government’s request, and (2) the effect that government announcements reinforced awareness with regard to the seriousness of the pandemic and people voluntarily refrained from going out. Our main findings are as follows. First, the declaration of the state of emergency reduced the number of people leaving their homes by 8.6% through the first channel, which is of the same order of magnitude as the estimate by Goolsbee and Syverson (2020) for lockdowns in the United States. Second, a 1% increase in new infections in a prefecture reduces people’s outings in that prefecture by 0.026%. Third, the government’s requests are responsible for about one quarter of the decrease in outings in Tokyo, while the remaining three quarters are the result of citizens obtaining new information through government announcements and the daily release of the number of infections. Our results suggest that what is necessary to contain the spread of COVID-19 is not strong, legally binding measures but the provision of appropriate information that encourages people to change their behavior.
In response to the spread of COVID-19, the Japanese government on February 27 issued a request to local governments such as prefectural governments to close schools. Subsequently, the Japanese government declared a state of emergency on April 7 for seven prefectures, including Tokyo, and on April 16 expanded the state of emergency to all 47 prefectures. Prime Minister Abe called on citizens to reduce social interaction by at least 70% and, if possible, by 80% by refraining from going out. In response to these government requests, people restrained from going out. For example, in March, the share of people in Tokyo leaving their homes was down by 18% compared to January before the spread of COVID-19, and by April 26, during the state of emergency, the share had dropped as much as 64%. As a result of people refraining from leaving their homes, the number of daily new infections in Tokyo fell from 209 at the peak to two on May 23, and the state of emergency was lifted on May 25.
WP027
This paper estimates a money demand function using Japanese data from 1985 to 2017, which includes the period of near-zero interest rates over the last two decades. We compare a log-log specification and a semi-log specification by employing the methodology proposed by Kejriwal and Perron (2010) on cointegrating relationships with structural breaks. Our main finding is that there exists a cointegrating relationship with a single break between the money-income ratio and the interest rate in the case of the log-log form but not in the case of the semi-log form. More specifically, we show that the substantial increase in the money-income ratio during the period of near-zero interest rates is well captured by the log-log form but not by the semi-log form. We also show that the demand for money did not decline in 2006 when the Bank of Japan terminated quantitative easing and started to raise the policy rate, suggesting that there was an upward shift in the money demand schedule. Finally, we find that the welfare gain from moving from 2 percent inflation to price stability is 0.10 percent of nominal GDP, which is more than six times as large as the corresponding estimate for the United States.
There is no consensus about whether the interest rate variable should be used in log or not when estimating the money demand function. For example, Meltzer (1963), Hoffman and Rasche (1991), and Lucas (2000) employ a log-log specification (i.e., the log of real money balances is regressed on the log of the nominal interest rate), while Cagan (1956), Lucas (1988), Stock and Watson (1993), and Ball (2001) employ a semi-log form (i.e., the log of real money demand is regressed on the level of the nominal interest rate). The purpose of this paper is to specify the functional form of money demand using Japanese data covering the recent period with nominal interest rates very close to zero.
WP013
This paper estimates a money demand function using US data from 1980 onward, including the period of near-zero interest rates following the global financial crisis. We conduct cointegration tests to show that the substantial increase in the money-income ratio during the period of near-zero interest rates is captured well by the money demand function in log-log form, but not by that in semi-log form. Our result is the opposite of the result obtained by Ireland (2009), who, using data up until 2006, found that the semi-log specification performs better. The difference in the result from Ireland (2009) mainly stems from the difference in the observation period employed: our observation period contains 24 quarters with interest rates below 1 percent, while Ireland’s (2009) observation period contains only three quarters. We also compute the welfare cost of inflation based on the estimated money demand function to find that it is very small: the welfare cost of 2 percent inflation is only 0.04 percent of national income, which is of a similar magnitude as the estimate obtained by Ireland (2009) but much smaller than the estimate by Lucas (2000).
In regression analyses of money demand functions, there is no consensus on whether the nominal interest rate as an independent variable should be used in linear or log form. For example, Meltzer (1963), Hoffman and Rasche (1991), and Lucas (2000) employ a log-log specification (i.e., regressing real money balances (or real money balances relative to nominal GDP) in log on nominal interest rates in log), while Cagan (1956), Lucas (1988), Stock and Watson (1993), and Ball (2001) employ a semi-log specification (i.e., nominal interest rates are not in log).
WP002
Central banks react even to intraday changes in the exchange rate; however, in most cases, intervention data is available only at a daily frequency. This temporal aggregation makes it difficult to identify the effects of interventions on the exchange rate. We apply the Bayesian MCMC approach to this endogeneity problem. We use “data augmentation” to obtain intraday intervention amounts and estimate the efficacy of interventions using the augmented data. Applying this new method to Japanese data, we find that an intervention of one trillion yen moves the yen/dollar rate by 1.7 percent, which is more than twice as much as the magnitude reported in previous studies applying OLS to daily observations. This shows the quantitative importance of the endogeneity problem due to temporal aggregation.
Are foreign exchange interventions effective? This issue has been debated extensively since the 1980s, but no conclusive consensus has emerged. A key difficulty faced by researchers in answering this question is the endogeneity problem: the exchange rate responds “within the period” to foreign exchange interventions and the central bank reacts “within the period” to fluctuations in the exchange rate. This difficulty would not arise if the central bank responded only slowly to fluctuations in the exchange rate, or if the data sampling interval were sufficiently fine.
This paper estimates fiscal policy feedback rules in Japan, the United States, and the United Kingdom for more than a century, allowing for stochastic regime changes. Estimating a Markovswitching model by the Bayesian method, we find the following: First, the Japanese data clearly reject the view that the fiscal policy regime is fixed, i.e., that the Japanese government adopted a Ricardian or a non-Ricardian regime throughout the entire period. Instead, our results indicate a stochastic switch of the debt-GDP ratio between stationary and nonstationary processes, and thus a stochastic switch between Ricardian and non-Ricardian regimes. Second, our simulation exercises using the estimated parameters and transition probabilities do not necessarily reject the possibility that the debt-GDP ratio may be nonstationary even in the long run (i.e., globally nonstationary). Third, the Japanese result is in sharp contrast with the results for the U.S. and the U.K. which indicate that in these countries the government’s fiscal behavior is consistently characterized by Ricardian policy.
Recent studies about the conduct of monetary policy suggest that the fiscal policy regime has important implications for the choice of desirable monetary policy rules, particularly, monetary policy rules in the form of inflation targeting (Sims (2005), Benigno and Woodford (2007)). It seems safe to assume that fiscal policy is characterized as “Ricardian” in the terminology of Woodford (1995), or “passive” in the terminology of Leeper (1991), if the government shows strong fiscal discipline. If this is the case, we can design an optimal monetary policy rule without paying any attention to fiscal policy. However, if the economy is unstable in terms of the fiscal situation, it would be dangerous to choose a monetary policy rule independently of fiscal policy rules. For example, some researchers argue that the recent accumulation of public debt in Japan is evidence of a lack of fiscal discipline on the part of the Japanese government, and that it is possible that government bond market participants may begin to doubt the government’s intention and ability to repay the public debt. If this is the case, we may need to take the future evolution of the fiscal regime into consideration when designing a monetary policy rule.
日本の通貨当局は 2003 年初から 2004 年春にかけて大量の円売りドル買い介入を行った。この時期の介入は John Taylor によって Great intervention と命名されている。本稿では，この Great intervention が，当時，日本銀行によって実施されていた量的緩和政策とどのように関係していたかを検討した。第 1 に，円売り介入により市場に供給された円資金のうち 60%は日本銀行の金融調節によって直ちにオフセットされたものの残りの 40%はオフセットされず，しばらくの間，市場に滞留した。この結果は，それ以前の時期にほぼ 100%オフセットされていたという事実と対照的である。第 2 に，介入と介入以外の財政の支払いを比較すると，介入によって供給された円資金が日銀のオペによってオフセットされる度合いは低かった。この結果は日本銀行が介入とそれ以外の財政の支払いを区別して金融調節を行っていたことを示唆している。第 3 に，不胎化された介入と不胎化されない介入を比較すると，為替相場に与える効果は後者の方が強い傾向が見られ，ゼロ金利の下でも，介入が不胎化されたか否かによって為替への効果に違いがあることを示している。ただし，この結果は，不胎化されるか否かに関する市場参加者の予想の定式化に依存しており，必ずしも頑健でない。
2001 年から 2006 年にかけて日本の通貨当局は 2 つの重要かつ興味深い政策を採用した。第 1 は，日本銀行によって 2001 年 3 月に導入された量的緩和政策である。この政策は，日本銀行がそれまで政策金利としていたコール翌日物金利を下限であるゼロまで引き下げても十分な景気刺激効果が得られなかったため，さらなる金融緩和策として政策変数を金利からマネー供給量に変更するというものである。量的緩和政策は日本経済が回復する 2006 年 3 月まで継続された。第 2に，日本の財務省は 2003 年 1 月から 2004 年 3 月にかけて外国為替市場において大規模な円売り介入を実行した。Taylor (2006) はこれを Great intervention とよんでいる。この時期の介入は 2 日に一度という頻度で行われており，1 日当りの介入金額は 2700 億円，総額で 35 兆円にのぼった。日本の通貨当局は活発な介入行動で知られるが，それにしてもこの頻度と金額は他の時期に例を見ないものである。
Central banks react even to intraday changes in the exchange rate; however, in most cases, intervention data is available only at a daily frequency. This temporal aggregation makes it difficult to identify the effects of interventions on the exchange rate. We propose a new method based on Markov Chain Monte Carlo simulations to cope with this endogeneity problem: We use “data augmentation” to obtain intraday intervention amounts and then estimate the efficacy of interventions using the augmented data. Applying this method to Japanese data, we find that an intervention of one trillion yen moves the yen/dollar rate by 1.7 percent, which is more than twice as large as the magnitude reported in previous studies applying OLS to daily observations. This shows the quantitative importance of the endogeneity problem due to temporal aggregation.
Are foreign exchange interventions effective? This issue has been debated extensively in the 1980s and 1990s, but no conclusive consensus has emerged. A key difficulty faced by researchers in answering this question is the endogeneity problem: the exchange rate responds “within the period” to central bank interventions and the central bank reacts “within the period” to fluctuations in the exchange rate. As an example, consider the case of Japan. The monetary authorities of Japan, which are known to be one of the most active interveners, started to disclose intervention data in July 2001, and this has rekindled researchers’ interest in the effectiveness of interventions. However, the information disclosed is limited: only the total amount of interventions on a day is released to the public at the end of a quarter, and no detailed information, such as on the time of the intervention(s), the number of interventions over the course of the day, and the market(s) (Tokyo, London, or New York) in which the intervention(s) were executed, is disclosed. Most importantly, the low frequency of the disclosed data poses a serious problem for researchers because it is well known that the Japanese monetary authorities often react to intraday fluctuations in the exchange rate
本稿では，政府税収の四半期データと四半期での税収の産出量弾性値を作成した上で，それを用いて構造VAR モデルを推計し日本の財政乗数を計測する。分析の結果，財政乗数は 1980 年代半ば以降，顕著に低下していることが確認された。すなわち，バブル前（1965-86 年）の期間は，政府支出や税へのショックが産出量に有意な影響を及ぼしていたが，それ以降（1987-2004 年）はほとんど影響を及ぼしていない。ただし，1980 年代以降の財政乗数の低下は米英などでも観察されており，必ずしも日本に固有の現象ではない。
財政乗数は低下したのか。低下したとすればそれはなぜか。これらは，バブル崩壊以降，財政をめぐる重要な論点であった。しかし現時点でもコンセンサスが得られているとは言いがたい。例えば，井堀・中里・川出 (2002) などは 1990 年代に財政乗数が低下したと主張している一方，堀・伊藤 (2002) は，1990 年代に財政乗数が低下したという証拠は見当たらないとしている。
From the beginning of 2003 to the spring of 2004, Japan’s monetary authorities conducted large-scale yen-selling/dollar-buying foreign exchange operations in what Taylor (2006) has labeled the “Great Intervention.” The purpose of the present paper is to empirically examine the relationship between this “Great Intervention” and the quantitative easing policy the Bank of Japan (BOJ) was pursuing at that time. Using daily data of the amount of foreign exchange interventions and current account balances at the BOJ, our analysis arrives at the following conclusions. First, while about 60 percent of the yen funds supplied to the market by yen-selling interventions were immediately offset by the BOJ’s monetary operations, the remaining 40 percent were not offset and remained in the market for some time; this is in contrast with the preceding period, when almost 100 percent were offset. Second, comparing foreign exchange interventions and other government payments, the extent to which the funds were offset by the BOJ were much smaller in the case of foreign exchange interventions, and the funds also remained in the market longer. This finding suggests that the BOJ differentiated between and responded differently to foreign exchange interventions and other government payments. Third, the majority of financing bills issued to cover intervention funds were purchased by the BOJ from the market immediately after they were issued. For that reason, no substantial decrease in current account balances linked with the issuance of FBs could be observed. These three findings indicate that it is highly likely that the BOJ, in order to implement its policy target of maintaining current account balances at a high level, intentionally did not sterilize yen-selling/dollar-buying interventions.
During the period from 2001 to 2006, the Japanese monetary authorities pursued two important and very interesting policies. The first of these is the quantitative easing policy introduced by the Bank of Japan (BOJ) in March 2001. This step was motivated by the fact that although the overnight call rate, the BOJ’s policy rate, had reached its lower bound at zero percent, it failed to sufficiently stimulate the economy. To achieve further monetary easing, the BOJ therefore changed the policy variable from the interest rate to the mone suppl . The quantitative easing polic remained in place until March 2006, b which time the Japanese econom had recovered. The second major polic during this period were interventions in the foreign exchange market b Japan’s Ministr of Finance (MOF), which engaged in large-scale selling of the en from Januar 2003 to March 2004. Ta lor (2006) has called this the “Great Intervention.” The interventions during this period occurred at a frequenc of once ever two business da s, with the amount involved per dail intervention averaging \286 billion and the total reaching \35 trillion. Even for Japan’s monetar authorities, which are known for their active interventionism, this frequency as well as the sums involved were unprecedented.
This paper estimates fiscal policy feedback rules in Japan, the United States, and the United Kingdom, allowing for stochastic regime changes. Using Markov-switching regression methods, we find that the Japanese data clearly reject the view that fiscal policy regime is fixed; i.e., the Japanese government has been adopting either of Ricardian or Non-Ricardian policy at all times. Instead, our results indicate that fiscal policy regimes evolve over time in a stochastic manner. This is in a sharp contrast with the U.S. and U.K. results in which the government’s fiscal behavior is consistently characterized by Ricardian policy.
Recent studies about the conduct of monetary policy argue that fiscal policy regime has important implications for the choice of desirable monetary policy rules, in particular, monetary policy rules in the form of inflation targeting (Sims (2005), Benigno and Woodford (2006)). Needless to say, we can safely believe that fiscal regime during the peace time is characterized as “Ricardian” in the terminology of Woodford (1995), or “passive” in the terminology of Leeper (1991). In such a case, we are allowed to design an optimal monetary policy rule without paying any attention to fiscal regimes. However, if the economy is unstable in terms of fiscal situations, it would be dangerous to choose a monetary policy rule independently of fiscal policy regimes. For example, some researchers argue that rapid accumulation of public debt in Japan is an evidence for the lack of fiscal discipline of the Japanese government. If this is the case, it would be possible that participants in the government bond market will come to have doubts about the government’s intention to repay public debt. Given this environment, it would not be desirable to design a monetary policy rule without paying any attention to the future evolution of fiscal policy regime. The purpose of this paper is to estimate fiscal policy feedback rules in Japan, the United States, and the United Kingdom for more than a century, so as to acquire a deeper understanding about the evolution of fiscal policy regime.
