Underlying Inflation and the Distribution of Price Change: Evidence from the Japanese Trimmed-Mean CPI

In this paper, we analyze the use of the trimmed-mean Consumer Price Index (trimmed CPI) as a measure of underlying inflation. We focus on empirical evidence that the cross-sectional price change distribution often but temporarily skews extremely to each side and that large but temporary variations in inflation correspond to the occurrence of the skewness. We find that the skewness of the distribution is mainly caused by idiosyncratic, temporary relative price shocks and that the components which contribute to the skewness of the distribution shift from time to time. Trimming 15 percent from each tail of the cross-sectional price change distribution systematically mitigates the fluctuation of the price index related to broad-based temporary relative price shocks. Thus, the trimmed CPI can be regarded as more appropriate for identifying underlying inflation compared with the CPI excluding fresh foods (CPI ex. fresh foods), which is generally regarded as the "core inflation index" in Japan. Distinguishing temporary price variations and underlying inflation using a measure of the skewness of the price change distribution provides central banks with increased information for evaluations of prior policies and present price developments, and for predictions of future inflation.

What Determines the Relation between the Output Gap and Inflation ? An International Comparison of Inflation Expectations and Staggered Wage Adjustment

This paper undertakes a cross-country study on the price- output gap relationship for selected industrialized countries (Japan, the U.S., Germany, the U.K., and Canada). The estimation results show that the price-output gap relationship in these countries can be classified into two categories: (1) a Phillips Curve type (in which the output gap fluctuation affects the inflation rate); and (2) a NAIRU type (in which fluctuations in the output gap affect changes in the inflation rate). In addition, such classifications may vary according to the sample period chosen. During the first half of the observation period (1978-86), NAIRU- type relations existed in all countries except Japan. During the second half (1987-97), NAIRU-type relations were observed in the U.S., the U.K., and Canada, while Phillips Curve-type relations were indicated in Japan and Germany. These results lead to the presumption that the price-output gap relationship is influenced by the recent inflation record, which is one of the most important factors that determine the formation mechanism of inflation expectations and the speed of price adjustment.

How Can We Extract a Fundamental Trend from an Economic Time- Series?

This paper attempts to extract a fundamental trend, which we call a " trend-cycle component," from an economic time-series. The "trend-cycle component" consists of a medium-term business cycle component and a long- term trend component. The objective is to eliminate the short-term irregular and seasonal variations that hide a fundamental trend in an economic time-series. We test five different time-series methods. Among them, the Henderson moving average (which is incorporated in an X-12- ARIMA seasonal adjustment program), the Band-Pass filter (which utilizes a Fourier transformation), and the DECOMP are found to be effective in extracting a "trend-cycle component" with a cyclical period longer than 1 .5 years. However, no method is found to be effective in extracting a " long-term trend component" with a cyclical period longer than that of a medium-term business cycle. Although the HP filter is somewhat successful , it still contains a component with a cyclical period of about three years that corresponds to a business cycle. These methods are useful for forecasting a wide variety of economic variables because they reveal a fundamental trend in the time series. In addition, statistical programs are available for easy application. They have, however, a few shortcomings. First, it is often difficult to provide a meaningful economic interpretation of the revealed characteristics of the "trend- cycle component." Second, the addition of new data can change the estimation results. In particular, an extracted component around the end of a sample period is likely to be revised with new data. Special caution is in order, therefore, in interpreting the estimation results and forecasting the time series when the data exhibit large variations. In this case, comparing the results of different methods provides a useful way to assess the reliability of an extracted "trend-cycle component."

Effects of rehabilitative training on recovery of hand motor function: A review of animal studies

AbstractNeuromotor systems have the capacity for functional recovery following damage to the central nervous system. This recovery can be enhanced by rehabilitative training. Animal studies in which artificial damage is induced in a specific region of the brain or spinal cord of rodents or monkeys have contributed to our understanding of the effects of rehabilitative training. In this article, I provide an overview of recent studies in which experimental animals were used to investigate the effects of rehabilitative training on motor recovery and brain plasticity. A study from my group in the macaque monkey reported the effects of hand motor training on motor recovery after lesioning of the primary motor cortex (M1) or the corticospinal tract at the cervical level. In monkeys that had undergone extensive post-lesion training, manual dexterity recovered to previous levels. Rehabilitative training was more effective in promoting recovery of manual dexterity when initiated immediately after the corticospinal tract lesion rather than 1 month later. Both functional brain imaging and gene expression analyses suggest that functional and structural changes may occur in undamaged motor areas during recovery of hand function after M1 or corticospinal tract lesions