Tax Policy and Consumer Spending: Evidence from Japanese Fiscal Experiments

This paper studies the extent to which the impact of tax policy on consumer spending differs between temporary and permanent, as well as anticipated and unanticipated tax changes. To discriminate between them, we use institutional information such as legal distinction between temporary and permanent tax changes, as well as timing of policy announcement and implementation. We find that the impact of temporary changes is significantly smaller than the impact of permanent changes. We also find that more than 80 per cent of Japanese consumers, including those who distinguish between temporary and permanent tax changes, respond to tax changes at the time of their implementation and not at the time of a policy announcement. We suggest an interpretation that these consumers follow a near-rational decision rule.

POWER LAWS IN REAL ESTATE PRICES DURING BUBBLE PERIODS

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.

Emergence of power laws with different power-law exponents from reversal quasi-symmetry and Gibrat’s law

To explore the emergence of power laws in social and economic phenomena, the authors discuss the mechanism whereby reversal quasi-symmetry and Gibrat’s law lead to power laws with different powerlaw exponents. Reversal quasi-symmetry is invariance under the exchange of variables in the joint PDF (probability density function). Gibrat’s law means that the conditional PDF of the exchange rate of variables does not depend on the initial value. By employing empirical worldwide data for firm size, from categories such as plant assets K, the number of employees L, and sales Y in the same year, reversal quasi-symmetry, Gibrat’s laws, and power-law distributions were observed. We note that relations between power-law exponents and the parameter of reversal quasi-symmetry in the same year were first confirmed. Reversal quasi-symmetry not only of two variables but also of three variables was considered. The authors claim the following. There is a plane in 3-dimensional space (log K, log L, log Y ) with respect to which the joint PDF PJ (K,L, Y ) is invariant under the exchange of variables. The plane accurately fits empirical data (K,L, Y ) that follow power-law distributions. This plane is known as the Cobb-Douglas production function, Y = AKαLβ which is frequently hypothesized in economics.

Power laws in real estate prices during bubble periods

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.Econophysics, Power law, Bubbles, House prices, Land prices, Price dispersion

Temporal and Cross Correlations in Business News

We empirically investigated temporal and cross correlations in the frequency of news reports on companies using a unique dataset with more than 100 million news articles reported in English by around 500 press agencies worldwide for the period 2003-2009. Our main findings are as follows. First, the frequency of news reports on a company does not follow a Poisson process; instead, it is characterized by long memory with a positive autocorrelation for more than a year. Second, there exist significant correlations in the frequency of news across companies. Specifically, on a daily or longer time scale, the frequency of news is governed by external dynamics such as an increase in the number of news due to, for example, the outbreak of an economic crisis, while it is governed by internal dynamics on a time scale of minutes. These two findings indicate that the frequency of news on companies has similar statistical properties as trading activities, measured by trading volumes or price volatility, in stock markets, suggesting that the flow of information through news on companies plays an important role in price dynamics in stock markets.

High quality topic extraction from business news explains abnormal financial market volatility

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affect trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affect stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized fact in financial economies, namely that at certain times trading volumes appear to be "abnormally large," can be partially explained by the flow of news. In this sense, our results prove that there is no "excess trading," when restricting to times when news are genuinely novel and provide relevant financial information.Comment: The previous version of this article included an error. This is a revised versio

Pressure-induced new magnetic phase in Tl(Cu0.985_{0.985}Mg0.015_{0.015})Cl3_3 probed by muon spin rotation

We carried out zero-field muon-spin-rotation (ZF-$\mu$SR) measurements in hydrostatic pressures in impurity-doped quantum spin gap system Tl(Cu$_{0.985}$Mg$_{0.015}$)Cl$_3$ to investigate microscopic magnetic properties of the pressure-induced phase. The spontaneous muon spin precession, which indicates the existence of a long-range coherent order, is observed in pressures. With decreasing temperature in 3.1 kbar, the internal static magnetic field at the muon sites {\it H}$_{\rm int}$ tends to saturate to 280 Oe around 4 K, however, decreases to 240 Oe at 2.3 K. These results suggest a rearrangement of ordered spins, and we speculate that the oblique antiferromagnetic phase, which is observed in the pressure of 14 kbar on the pure TlCuCl$_3$, appears in the Mg-doped system in lower pressures.Comment: To be published to the proceedings of ASR200