AN ANALYSIS OF MONETARY POLICY SHOCKS IN JAPAN: A FACTOR AUGMENTED VECTOR AUTOREGRESSIVE APPROACH*

This paper analyses monetary policy shocks in Japan using a factor augmented vector autoregressive approach. There are three main findings. First, the time lags with which the monetary policy shocks are transmitted vary between the various macroeconomic time series. These include several series that have not been included thus far in standard vector autoregressive analysis, including housing starts and employment indices. Second, a coherent picture of monetary policy effects on the economy is obtained. Third, it is found that monetary policy shocks have a stronger impact on real variables, such as employment and housing starts, than industrial production.     

CROSS-COUNTRY EVIDENCE ON OUTPUT GROWTH VOLATILITY: NONSTATIONARY VARIANCE AND GARCH MODELS

This paper revisits the issue of conditional volatility in real gross domestic product (GDP) growth rates for Canada, Germany, Italy, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the six countries became noticeably less volatile over the past few decades. In this paper, we employ the modified iterated cumulative sum of squares (ICSS) algorithm to detect structural change in the variance of output growth. One structural break exists in each of the six countries after identifying outliers and mean shifts in the growth rates. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications, modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada and Japan, and disappears entirely in Germany, Italy, the United Kingdom and the United States, once we incorporate the break in the variance equation of output for the six countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary variance. Moreover, we also consider the possible effects of our more correct measure of output volatility on output growth as well as the reverse effect of output growth on its volatility. The conditional standard deviation possesses no statistical significance in all countries, except a significant negative effect in Japan. The lagged growth rate of output produces significant negative and positive effects on the conditional variances in Germany and Japan, respectively. No significant effects exist in Canada, Italy, the United Kingdom, and the United States.     

Macroeconomic forecasting in the Euro area: Country specific versus area-wide information

This paper compares several time series methods for short-run forecasting of Euro-wide inflation and real activity using data from 1982 to 1997. Forecasts are constructed from univariate autoregressions, vector autoregressions, single equation models that include Euro-wide and US aggregates, and large-model methods in which forecasts are based on estimates of common dynamic factors. Aggregate Euro-wide forecasts are constructed from models that utilize only aggregate Euro-wide variables and by aggregating country-specific models. The results suggest that forecasts constructed by aggregating the country-specific models are more accurate than forecasts constructed using the aggregate data.     

WHY DID JAPAN'S TFP GROWTH SLOW DOWN IN THE LOST DECADE? AN EMPIRICAL ANALYSIS BASED ON FIRM‐LEVEL DATA OF MANUFACTURING FIRMS*

This study analyses the cause of the slowdown in Japan's TFP growth during the 1990s. Many preceding studies, examining the issue at the macro‐ or industry‐level, have found that the slowdown was primarily due to the stagnation in TFP growth in the manufacturing sector. Using firm level panel data covering the entire sector, we investigate the causes of the TFP slowdown and find that the reallocation of resources from less efficient to more efficient firms was very slow and limited. This “low metabolism” seems to be an important cause for the slowdown in Japan's TFP growth.     

ROLLING REGRESSION VERSUS TIME‐VARYING COEFFICIENT MODELLING: AN EMPIRICAL INVESTIGATION OF THE OKUN'S LAW IN SOME EURO AREA COUNTRIES

During the last decade, economists have shown that the inverse relationship between economic growth and unemployment rate varies over time. Rolling regression has been the main tool used to quantify such a relationship. This methodology suffers from several well‐known problems which lead to spurious non‐linear patterns in the Okun's coefficient behaviour over time. Here, we take a penalized regression spline approach to estimate the Okun's time‐varying effects. As a result, spurious non‐linearities are suppressed and hence important time‐varying coefficient features revealed. Our empirical results show that the inverse relationship in some Euro area countries is spatially heterogeneous and time‐varying. The findings are complemented by the calculation of the rate of output growth needed for a stable unemployment rate, as proposed by Knotek.     

Regime-switching factor models in which the number of factors defines the regime

We develop regime-switching factor models in which the number of factors determines the operative economic regime. To illustrate the proposed methodology, we analyze the covariance structure of a widely studied set of 25 equity portfolios.     

旅游产业集群:理论与现实的探讨

在对集群概念的讨论基础上,分析了国内外报道和政策中的旅游产业集群的概念,发现现实层面的旅游产业集群基本上违背了集群的本意.在理论上,旅游产业集群是可能存在的.首先,游客需求精致化,中小企业作用日益显著,但中小企业彼此孤立,所以集群可能将旅游目的地的中小企业联系起来.其次,自然资源型旅游地需要环境保护,而环境保护是公共产品,所以需要地方企业、政府、协会等行为主体的合作.集群提供了这样的可能.再次,技术在旅游业中并不像我们想象得那么不重要.基于旅游业中技术扩散和创新而对合作的要求可能使旅游业形成集群.最后,旅游业的强关联性也可能成为相关企业集聚,甚至成为集群的基础.旅游产业集群的理论基础来自于对旅游业特征的理解.     

Outline of forecast theory using generalized cost functions

The cost functions used to form forecasts in practice may be quite different than the squared costs that is often assumed in forecast theory. The impact on evaluation procedures is determined and simple properties for the derivate of the cost function of the errors are found to provide simple tests of optimality. For a very limited class of situations are forecasts based on conditional means optimal, generally, the econometricians needs to provide the whole conditional predicted distribution. Implications for multi-step forecasts and the combination of forecasts are briefly considered.     

On winning forecasting competitions in economics

To explain which methods might win forecasting competitions on economic time series, we consider forecasting in an evolving economy subject to structural breaks, using mis-specified, data-based models. ‘Causal’ models need not win when facing deterministic shifts, a primary factor underlying systematic forecast failure. We derive conditional forecast biases and unconditional (asymptotic) variances to show that when the forecast evaluation sample includes sub-periods following breaks, non-causal models will outperform at short horizons. This suggests using techniques which avoid systematic forecasting errors, including improved intercept corrections. An application to a small monetary model of the UK illustrates the theory.     

台湾地区要素投入对经济增长的作用

经济增长是由资本、劳动力、技术等多种要素共同推动的,各要素投入的数量、质量和效率决定了产出的增长。文章以经济增长相关理论为基础,通过合理选取和度量有关变量数据,构建台湾地区经济增长模型,并对模型进行计量检验和要素分析,从而揭示台湾地区要素投入与经济增长的关系,以及各要素在经济增长中的作用。     

‘JUMPS’ IN MACROECONOMIC MODELS: AN EXAMPLE WHEN EIGENVALUES ARE COMPLEX‐VALUED*

The dynamic properties of continuous‐time macroeconomic models are typically characterised by having a combination of stable and unstable eigenvalues. In a seminal paper, Blanchard and Kahn showed that, for linear models, in order to ensure a unique solution, the number of discontinuous or ‘jump’ variables must equal the number of unstable eigenvalues in the economy. Assuming no zero eigenvalues and that all eigenvalues are distinct, this also means that the number of predetermined variables, otherwise referred to as continuous or non‐ ‘jump’ variables, must equal the number of stable eigenvalues. In this paper, we investigate the application of the Blanchard and Kahn results and establish that these results also carry through for linear dynamical systems where some of the eigenvalues are complex‐valued. An example with just one complex conjugate pair of stable eigenvalues is presented. The Appendix contains a general n‐dimensional model.     

THE INF‐T TEST FOR A UNIT ROOT AGAINST ASYMMETRIC EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE MODELS

This paper proposes a new test for a unit root against an alternative of asymmetric exponential smooth transition autoregressive models, by extending the infimum test developed by Park and Shintani. Simulation results suggest that the test performs reasonably well in finite samples. The proposed test is also applied to real exchange rates to examine their asymmetric and nonlinear mean‐reverting properties.     

MUNICIPAL CONSTRUCTION SPENDING: AN EMPIRICAL EXAMINATION

Despite widespread concern and discussion, no consensus exists concerning the causes of the "infrastructure crisis" or its implications for the efficiency of government decision-making more generally. We investigate several models of the determination of local public capital expenditures. Using Euler equation methods, we cannot reject the hypothesis that construction spending is determined by unconstrained, forward looking municipal planning. Consistent with this result, the stochastic structure of resource flows is an important feature of the determination of construction spending. Only unanticipated changes in a community's resources alter its demand for structures, with an unanticipated increase of one dollar increasing current construction spending by about 5.6 cents.     

A REVISIT TO THE STATIONARITY OF OECD INFLATION: EVIDENCE FROM PANEL UNIT‐ROOT TESTS AND THE COVARIATE POINT OPTIMAL TEST*

This paper re‐examines the stationarity of inflation rates in 19 Organisation for Economic Cooperation and Development countries with the use of cross‐sectional information. We employ the panel unit‐root tests that allow for cross‐sectional dependency and the covariate point optimal test. These tests have high power in common due to the exploitation of cross‐sectional information, and they can assist mutually to draw a concrete conclusion on inflation dynamics for all series in the panel. Our empirical results show that allowing for cross‐sectional dependency rejects the null hypothesis that all series in the panel have a unit root, implying that there is at least one stationary series in the panel. With the help of the results of the covariate test, we can distinguish the panel into a group of stationary and a group of non‐stationary series. For robustness, the two groups of series are re‐confirmed by the panel tests. Our results reveal evidence of mean reversion in inflation for 15 of 19 countries, which is significantly stronger as compared to that obtained by the state‐of‐the‐art univariate unit‐root tests.