The Great Intervention and Massive Money Injection: The Japanese Experience 2003-2004

From the beginning of 2003 to the spring of 2004, Japan's monetary authorities conducted large-scale yen-selling/dollar-buying operations in what Taylor (2006) has labeled the "Great Intervention." This paper examines the relationship between this "Great Intervention" and the quantitative easing policy the Bank of Japan was pursuing at that time. First, we find that about 40 percent of the yen funds supplied to the market by yen-selling interventions were not offset by the BOJ's monetary operations and remained in the market for a while; this is in contrast with the preceding period, when almost 100 percent were immediately offset. Second, comparing interventions and other government payments, the extent to which the funds were offset was much smaller in the case of interventions, suggesting that the BOJ differentiated between, and responded differently to, interventions and other government payments. These two findings indicate that it is likely that the BOJ intentionally did not sterilize yen-selling interventions to achieve its policy target of maintaining the current account balances of commercial banks at the BOJ at a high level. Finally, we find that an unsterilized intervention had a greater impact on the yen-dollar rate than a sterilized one, suggesting that it matters whether an intervention is sterilized or not even when the economy is in a liquidity trap

Testing for flexible nonlinear trends with an integrated or stationary noise component

This paper proposes a new test for the presence of a nonlinear deterministic trend approximated by a Fourier expansion in a univariate time series for which there is no prior knowledge as to whether the noise component is stationary or contains an autoregressive unit root. Our approach builds on the work of Perron and Yabu (2009a) and is based on a Feasible Generalized Least Squares procedure that uses a super-efficient estimator of the sum of the autoregressive coefficients α when α = 1. The resulting Wald test statistic asymptotically follows a chi-square distribution in both the I(0) and I(1) cases. To improve the finite sample properties of the test, we use a bias-corrected version of the OLS estimator of α proposed by Roy and Fuller (2001). We show that our procedure is substantially more powerful than currently available alternatives. We illustrate the usefulness of our method via an application to modelling the trend of global and hemispheric temperatures

Fiscal Policy Switching: Evidence from Japan, the U.S., and the U.K.

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 Markov-switching 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.Fiscal Policy Rule, Fiscal Discipline, Markov-Switching Regression

Spurious Regressions in Technical Trading: Momentum or Contrarian?

This paper investigates the spurious effect in forecasting asset returns when signals from technical trading rules are used as predictors. Against economic intuition, the simulation result shows that, even if past information has non predictive power, buy or sell signals based on the difference between the short-period and long-period moving averages of past asset prices can be statistically significant when the forecast horizon is relatively long. The theory implies that both e momentumf and econtrarianf strategies can be falsely supported, while the probability of obtaining each result depends on the type of the test statistics employed. Several modifications to these test statistics are considered for the purpose of avoiding spurious regressions. They are applied to the stock market index and the foreign exchange rate in order to reconsider the predictive power of technical trading rules.Efficient market hypothesis, Nonstationary time series, Random walk, Technical analysis

The Great Intervention and Massive Money Injection: The Japanese Experience 2003-2004

From the beginning of 2003 to the spring of 2004, Japan's monetary authorities conducted large-scale yen-selling/dollar-buying operations in what John Taylor has labeled the "Great Intervention." This paper examines the relationship between this "Great Intervention" and the quantitative easing policy the Bank of Japan was pursuing at that time. First, we find that about 40 percent of the yen funds supplied to the market by yen-selling interventions were not offset by the BOJ's monetary operations, and remained in the market for a while; this is in contrast with the preceding period, when almost 100 percent were immediately offset. Second, comparing interventions and other government payments, the extent to which the funds were offset were much smaller in the case of interventions, suggesting that the BOJ differentiated between and responded differently to interventions and other government payments. These two findings indicate that it is likely that the BOJ intentionally did not sterilize yen-selling interventions to achieve its policy target of maintaining current account balances of commercial banks at the BOJ at a high level. Finally, we find that an unsterilized intervention had a greater impact on the yen-dollar rate than a sterilized one did, indicating that it matters whether an intervention is sterilized or not even when the economy is in a liquidity trap

A New Method for Identifying the Effects of Foreign Exchange Interventions

The monetary authorities 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.Foreign exchange intervention, Intraday data, Markov-chain Monte Carlo method, Endogeneity problem, Temporal aggregation

Fiscal Policy Switching in Japan, the U.S., and the U.K.

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 Markov-switching 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

Japan’s Voluntary Lockdown

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

Japan’s Voluntary Lockdown: Further Evidence Based on Age-Specific Mobile Location Data

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